Search results for: flexible flat plate (FFP) actuators

Authors: Chia-Jung Chen, Yu-Chi Hsu, June-Dong Lin, Kun-Chen Chan, Chieh-Tien Wang, Li-Ching Wu, Chung-Feng Liu

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With fast advances in healthcare technology, various total laboratory automation (TLA) processes have been proposed. However, adopting TLA needs quite high funding. This study explores an early adoption experience by Taiwan’s large-scale hospital group, the Chimei Hospital Group (CMG), which owns three branch hospitals (Yongkang, Liouying and Chiali, in order by service scale), based on the five stages of Everett Rogers’ Diffusion Decision Process. 1.Knowledge stage: Over the years, two weaknesses exists in laboratory department of CMG: 1) only a few examination categories (e.g., sugar testing and HbA1c) can now be completed and reported within a day during an outpatient clinical visit; 2) the Yongkang Hospital laboratory space is dispersed across three buildings, resulting in duplicated investment in analysis instruments and inconvenient artificial specimen transportation. Thus, the senior management of the department raised a crucial question, was it time to process the redesign of the laboratory department? 2.Persuasion stage: At the end of 2013, Yongkang Hospital’s new building and restructuring project created a great opportunity for the redesign of the laboratory department. However, not all laboratory colleagues had the consensus for change. Thus, the top managers arranged a series of benchmark visits to stimulate colleagues into being aware of and accepting TLA. Later, the director of the department proposed a formal report to the top management of CMG with the results of the benchmark visits, preliminary feasibility analysis, potential benefits and so on. 3.Decision stage: This TLA suggestion was well-supported by the top management of CMG and, finally, they made a decision to carry out the project with an instrument-leasing strategy. After the announcement of a request for proposal and several vendor briefings, CMG confirmed their laboratory automation architecture and finally completed the contracts. At the same time, a cross-department project team was formed and the laboratory department assigned a section leader to the National Taiwan University Hospital for one month of relevant training. 4.Implementation stage: During the implementation, the project team called for regular meetings to review the results of the operations and to offer an immediate response to the adjustment. The main project tasks included: 1) completion of the preparatory work for beginning the automation procedures; 2) ensuring information security and privacy protection; 3) formulating automated examination process protocols; 4) evaluating the performance of new instruments and the instrument connectivity; 5)ensuring good integration with hospital information systems (HIS)/laboratory information systems (LIS); and 6) ensuring continued compliance with ISO 15189 certification. 5.Confirmation stage: In short, the core process changes include: 1) cancellation of signature seals on the specimen tubes; 2) transfer of daily examination reports to a data warehouse; 3) routine pre-admission blood drawing and formal inpatient morning blood drawing can be incorporated into an automatically-prepared tube mechanism. The study summarizes below the continuous improvement orientations: (1) Flexible reference range set-up for new instruments in LIS. (2) Restructure of the specimen category. (3) Continuous review and improvements to the examination process. (4) Whether installing the tube (specimen) delivery tracks need further evaluation.

Keywords: innovation decision process, total laboratory automation, health care

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Authors: Lauti Dwita Santy, Hermes Panggabean, Syahrir Andi Mangga

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The Bengkulu Basin is part of the Sunda Arc system, which is a classic convergent type margin that occur around the southern rim of the Eurasian continental (Sundaland) plate. The basin is located between deep sea trench (Mentawai Outer Arc high) and the volvanic/ magmatic Arc of the Barisan Mountains Range. To the northwest it is bounded by Padang High, to the northest by Barisan Mountains (Sumatra Fault Zone) to the southwest by Mentawai Fault Zone and to the southeast by Semangko High/ Sunda Strait. The stratigraphic succession and tectonic development can be broadly divided into four stage/ periods, i.e Late Jurassic- Early Cretaceous, Late Eocene-Early Oligocene, Late Oligocene-Early Miocene, Middle Miocene-Late Miocene and Pliocene-Plistocene, which are mainly controlled by the development of subduction activities. The Pre Tertiary Basement consist of sedimentary and shallow water limestone, calcareous mudstone, cherts and tholeiitic volcanic rocks, with Late Jurassic to Early Cretaceous in age. The sedimentation in this basin is depend on the relief of the Pre Tertiary Basement (Woyla Terrane) and occured into two stages, i.e. transgressive stage during the Latest Oligocene-Early Middle Miocene Seblat Formation, and the regressive stage during the Latest Middle Miocene-Pleistocene (Lemau, Simpangaur and Bintunan Formations). The Pre-Tertiary Faults were more intensive than the overlying cover, The Tertiary Rocks. There are two main fault trends can be distinguished, Northwest–Southwest Faults and Northeast-Southwest Faults. The NW-SE fault (Ketaun) are commonly laterally persistent, are interpreted to the part of Sumatran Fault Systems. They commonly form the boundaries to the Pre Tertiary basement highs and therefore are one of the faults elements controlling the geometry and development of the Tertiary sedimentary basins.The Northeast-Southwest faults was formed a conjugate set to the Northwest–Southeast Faults. In the earliest Tertiary and reactivated during the Plio-Pleistocene in a compressive mode with subsequent dextral displacement. The Block Faulting accross these two sets of faults related to approximate North–South compression in Paleogene time and produced a series of elongate basins separated by basement highs in the backarc and forearc region. The Bengkulu basin is interpreted having evolved from pull apart feature in the area southwest of the main Sumatra Fault System related to NW-SE trending in dextral shear.Based on Pyrolysis Yield (PY) vs Total Organic Carbon (TOC) diagram show that Seblat and Lemau Formation belongs to oil and Gas Prone with the quality of the source rocks includes into excellent and good (Lemau Formation), Fair and Poor (Seblat Formation). The fine-grained carbonaceous sediment of the Seblat dan Lemau Formations as source rocks, the coarse grained and carbonate sediments of the Seblat and Lemau Formations as reservoir rocks, claystone bed in Seblat and Lemau Formation as caprock. The source rocks maturation are late immature to early mature, with kerogen type II and III (Seblat Formation), and late immature to post mature with kerogen type I and III (Lemau Formation). The burial history show to 2500 m in depthh with paleo temperature reached 80oC. Trapping mechanism occur during Oligo–Miocene and Middle Miocene, mainly in block faulting system.

Keywords: fore arc, bengkulu, sumatra, sundaland, hydrocarbon, trapping mechanism

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Authors: Sophio Kobauri, Temur Kantaria, Nina Kulikova, David Tugushi, Ramaz Katsarava

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Polymeric nanoparticles-based drug delivery systems and therapeutics have a great potential in the treatment of a numerous diseases, due to they are characterizing the flexible properties which is giving possibility to modify their structures with a complex definition over their structures, compositions and properties. Important characteristics of the polymeric nanoparticles (PNPs) used as drug carriers are high particle’s stability, high carrier capacity, feasibility of encapsulation of both hydrophilic and hydrophobic drugs, and feasibility of variable routes of administration, including oral application and inhalation; NPs are especially effective for intracellular drug delivery since they penetrate into the cells’ interior though endocytosis. A variety of PNPs based drug delivery systems including charged and neutral, degradable and non-degradable polymers of both natural and synthetic origin have been developed. Among these huge varieties the biodegradable PNPs which can be cleared from the body after the fulfillment of their function could be considered as one of the most promising. For intracellular uptake it is highly desirable to have positively charged PNPs since they can penetrate deep into cell membranes. For long-lasting circulation of PNPs in the body it is important they have so called “stealth coatings” to protect them from the attack of immune system of the organism. One of the effective ways to render the PNPs “invisible” for immune system is their PEGylation which represent the process of pretreatment of polyethylene glycol (PEG) on the surface of PNPs. The present work deals with constructing PNPs from amino acid based biodegradable polymers – regular poly(ester amide) (PEA) composed of sebacic acid, leucine and 1,6-hexandiol (labeled as 8L6), cationic PEA composed of sebacic acid, arginine and 1,6-hexandiol (labeled as 8R6), and comb-like co-PEA composed of sebacic acid, malic acid, leucine and 1,6-hexandiol (labeled as PEG-PEA). The PNPs were fabricated using the polymer deposition/solvent displacement (nanoprecipitation) method. The regular PEA 8L6 form stable negatively charged (zeta-potential within 2-12 mV) PNPs of desired size (within 150-200 nm) in the presence of various surfactants (Tween 20, Tween 80, Brij 010, etc.). Blending the PEAs 8L6 and 8R6 gave the 130-140 nm sized positively charged PNPs having zeta-potential within +20 ÷ +28 mV depending 8L6/8R6 ratio. The PEGylating PEA PEG-PEA was synthesized by interaction of epoxy-co-PEA [8L6]0,5-[tES-L6]0,5 with mPEG-amine-2000 The stable and positively charged PNPs were fabricated using pure PEG-PEA as a surfactant. A firm anchoring of the PEG-PEA with 8L6/8R6 based PNPs (owing to a high afinity of the backbones of all three PEAs) provided good stabilization of the NPs. In vitro biocompatibility study of the new PNPs with four different stable cell lines: A549 (human), U-937 (human), RAW264.7 (murine), Hepa 1-6 (murine) showed they are biocompatible. Considering high stability and cell compatibility of the elaborated PNPs one can conclude that they are promising for subsequent therapeutic applications. This work was supported by the joint grant from the Science and Technology Center in Ukraine and Shota Rustaveli National Science Foundation of Georgia #6298 “New biodegradable cationic polymers composed of arginine and spermine-versatile biomaterials for various biomedical applications”.

Keywords: biodegradable poly(ester amide)s, cationic poly(ester amide), pegylating poly(ester amide), nanoparticles

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Authors: A. Calabrese, V. F. Uricchio, D. di Noia, S. Favale, C. Caiati, G. P. Maggi, G. Donvito, D. Diacono, S. Tangaro, A. Italiano, E. Riezzo, M. Zippitelli, M. Toriello, E. Celiberti, D. Festa, A. Colaianni

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Climate change has a severe impact on human health. There is a vast literature demonstrating temperature increase is causally related to cardiovascular problem and represents a high risk for human health, but there are not study that improve a solution. In this work, it is studied how the clime influenced the human parameter through the analysis of climatic conditions in an area of the Apulia Region: Capurso Municipality. At the same time, medical personnel involved identified a set of variables useful to define an index describing health condition. These scientific studies are the base of an innovative alert system, IPPOCRATE, whose aim is to asses climate risk and share information to population at risk to support prevention and mitigation actions. IPPOCRATE is an e-health system, it is designed to provide technological support to analysis of health risk related to climate and provide tools for prevention and management of critical events. It is the first integrated system of prevention of human risk caused by climate change. IPPOCRATE calculates risk weighting meteorological data with the vulnerability of monitored subjects and uses mobile and cloud technologies to acquire and share information on different data channels. It is composed of four components: Multichannel Hub. Multichannel Hub is the ICT infrastructure used to feed IPPOCRATE cloud with a different type of data coming from remote monitoring devices, or imported from meteorological databases. Such data are ingested, transformed and elaborated in order to be dispatched towards mobile app and VoIP phone systems. IPPOCRATE Multichannel Hub uses open communication protocols to create a set of APIs useful to interface IPPOCRATE with 3rd party applications. Internally, it uses non-relational paradigm to create flexible and highly scalable database. WeHeart and Smart Application The wearable device WeHeart is equipped with sensors designed to measure following biometric variables: heart rate, systolic blood pressure and diastolic blood pressure, blood oxygen saturation, body temperature and blood glucose for diabetic subjects. WeHeart is designed to be easy of use and non-invasive. For data acquisition, users need only to wear it and connect it to Smart Application by Bluetooth protocol. Easy Box was designed to take advantage from new technologies related to e-health care. EasyBox allows user to fully exploit all IPPOCRATE features. Its name, Easy Box, reveals its purpose of container for various devices that may be included depending on user needs. Territorial Registry is the IPPOCRATE web module reserved to medical personnel for monitoring, research and analysis activities. Territorial Registry allows to access to all information gathered by IPPOCRATE using GIS system in order to execute spatial analysis combining geographical data (climatological information and monitored data) with information regarding the clinical history of users and their personal details. Territorial Registry was designed for different type of users: control rooms managed by wide area health facilities, single health care center or single doctor. Territorial registry manages such hierarchy diversifying the access to system functionalities. IPPOCRATE is the first e-Health system focused on climate risk prevention.

Keywords: climate change, health risk, new technological system

Procedia PDF Downloads 867

Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Piotr K. Szewczyk, Arkadiusz Gradys, Sungkyun Kim, Luana Persano, Mateusz M. Marzec, Oleksander Kryshtal, Andrzej Bernasik, Sohini Kar-Narayan, Pawel Sajkiewicz, Urszula Stachewicz

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Piezoelectric polymers have received great attention in smart textiles, wearables, and flexible electronics. Their potential applications range from devices that could operate without traditional power sources, through self-powering sensors, up to implantable biosensors. Semi-crystalline PVDF is often proposed as the main candidate for industrial-scale applications as it exhibits exceptional energy harvesting efficiency compared to other polymers combined with high mechanical strength and thermal stability. Plenty of approaches have been proposed for obtaining PVDF rich in the desired β-phase with electric polling, thermal annealing, and mechanical stretching being the most prevalent. Electrospinning is a highly tunable technique that provides a one-step process of obtaining highly piezoelectric PVDF fibers without the need for post-treatment. In this study, voltage polarity and relative humidity influence on electrospun PVDF, fibers were investigated with the main focus on piezoelectric β-phase contents and piezoelectric performance. Morphology and internal structure of fibers were investigated using scanning (SEM) and transmission electron microscopy techniques (TEM). Fourier Transform Infrared Spectroscopy (FITR), wide-angle X-ray scattering (WAXS) and differential scanning calorimetry (DSC) were used to characterize the phase composition of electrospun PVDF. Additionally, surface chemistry was verified with X-ray photoelectron spectroscopy (XPS). Piezoelectric performance of individual electrospun PVDF fibers was measured using piezoresponse force microscopy (PFM), and the power output from meshes was analyzed via custom-built equipment. To prepare the solution for electrospinning, PVDF pellets were dissolved in dimethylacetamide and acetone solution in a 1:1 ratio to achieve a 24% solution. Fibers were electrospun with a constant voltage of +/-15kV applied to the stainless steel nozzle with the inner diameter of 0.8mm. The flow rate was kept constant at 6mlh⁻¹. The electrospinning of PVDF was performed at T = 25°C and relative humidity of 30 and 60% for PVDF30+/- and PVDF60+/- samples respectively in the environmental chamber. The SEM and TEM analysis of fibers produced at a lower relative humidity of 30% (PVDF30+/-) showed a smooth surface in opposition to fibers obtained at 60% relative humidity (PVDF60+/-), which had wrinkled surface and additionally internal voids. XPS results confirmed lower fluorine content at the surface of PVDF- fibers obtained by electrospinning with negative voltage polarity comparing to the PVDF+ obtained with positive voltage polarity. Changes in surface composition measured with XPS were found to influence the piezoelectric performance of obtained fibers what was further confirmed by PFM as well as by custom-built fiber-based piezoelectric generator. For PVDF60+/- samples humidity led to an increase of β-phase contents in PVDF fibers as confirmed by FTIR, WAXS, and DSC measurements, which showed almost two times higher concentrations of β-phase. A combination of negative voltage polarity with high relative humidity led to fibers with the highest β-phase contents and the best piezoelectric performance of all investigated samples. This study outlines the possibility to produce electrospun PVDF fibers with tunable piezoelectric performance in a one-step electrospinning process by controlling relative humidity and voltage polarity conditions. Acknowledgment: This research was conducted within the funding from m the Sonata Bis 5 project granted by National Science Centre, No 2015/18/E/ST5/00230, and supported by the infrastructure at International Centre of Electron Microscopy for Materials Science (IC-EM) at AGH University of Science and Technology. The PFM measurements were supported by an STSM Grant from COST Action CA17107.

Keywords: crystallinity, electrospinning, PVDF, voltage polarity

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Authors: Essam Gooda, Chadi Abdallah, Hamdi Seif, Safaa Baydoun, Rouya Hdeib, Hilal Obeid

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Floods are common natural disaster occurring in semi-arid regions in Lebanon. This results in damage to human life and deterioration of environment. Despite their destructive nature and their immense impact on the socio-economy of the region, flash floods have not received adequate attention from policy and decision makers. This is mainly because of poor understanding of the processes involved and measures needed to manage the problem. The current understanding of flash floods remains at the level of general concepts; most policy makers have yet to recognize that flash floods are distinctly different from normal riverine floods in term of causes, propagation, intensity, impacts, predictability, and management. Flash floods are generally not investigated as a separate class of event but are rather reported as part of the overall seasonal flood situation. As a result, Lebanon generally lacks policies, strategies, and plans relating specifically to flash floods. Main objective of this research is to improve flash flood prediction by providing new knowledge and better understanding of the hydrological processes governing flash floods in the East Catchments of El Assi River. This includes developing rainstorm time distribution curves that are unique for this type of study region; analyzing, investigating, and developing a relationship between arid watershed characteristics (including urbanization) and nearby villages flow flood frequency in Ras Baalbeck and Fekha. This paper discusses different levels of integration approach¬es between GIS and hydrological models (HEC-HMS & HEC-RAS) and presents a case study, in which all the tasks of creating model input, editing data, running the model, and displaying output results. The study area corresponds to the East Basin (Ras Baalbeck & Fakeha), comprising nearly 350 km2 and situated in the Bekaa Valley of Lebanon. The case study presented in this paper has a database which is derived from Lebanese Army topographic maps for this region. Using ArcMap to digitizing the contour lines, streams & other features from the topographic maps. The digital elevation model grid (DEM) is derived for the study area. The next steps in this research are to incorporate rainfall time series data from Arseal, Fekha and Deir El Ahmar stations to build a hydrologic data model within a GIS environment and to combine ArcGIS/ArcMap, HEC-HMS & HEC-RAS models, in order to produce a spatial-temporal model for floodplain analysis at a regional scale. In this study, HEC-HMS and SCS methods were chosen to build the hydrologic model of the watershed. The model then calibrated using flood event that occurred between 7th & 9th of May 2014 which considered exceptionally extreme because of the length of time the flows lasted (15 hours) and the fact that it covered both the watershed of Aarsal and Ras Baalbeck. The strongest reported flood in recent times lasted for only 7 hours covering only one watershed. The calibrated hydrologic model is then used to build the hydraulic model & assessing of flood hazards maps for the region. HEC-RAS Model is used in this issue & field trips were done for the catchments in order to calibrated both Hydrologic and Hydraulic models. The presented models are a kind of flexible procedures for an ungaged watershed. For some storm events it delivers good results, while for others, no parameter vectors can be found. In order to have a general methodology based on these ideas, further calibration and compromising of results on the dependence of many flood events parameters and catchment properties is required.

Keywords: flood risk management, flash flood, semi arid region, El Assi River, hazard maps

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Authors: Riccardo Fratini, Riccardo Santini, Jacopo Serafini, Massimo Gennaretti, Stefano Panzieri

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This paper presents a nonlinear differential model, for a three-bladed horizontal axis wind turbine (HAWT) suited for control applications. It is based on a 8-dofs, lumped parameters structural dynamics coupled with a quasi-steady sectional aerodynamics. In particular, using the Euler-Lagrange Equation (Energetic Variation approach), the authors derive, and successively validate, such model. For the derivation of the aerodynamic model, the Greenbergs theory, an extension of the theory proposed by Theodorsen to the case of thin airfoils undergoing pulsating flows, is used. Specifically, in this work, the authors restricted that theory under the hypothesis of low perturbation reduced frequency k, which causes the lift deficiency function C(k) to be real and equal to 1. Furthermore, the expressions of the aerodynamic loads are obtained using the quasi-steady strip theory (Hodges and Ormiston), as a function of the chordwise and normal components of relative velocity between flow and airfoil Ut, Up, their derivatives, and section angular velocity ε˙. For the validation of the proposed model, the authors carried out open and closed-loop simulations of a 5 MW HAWT, characterized by radius R =61.5 m and by mean chord c = 3 m, with a nominal angular velocity Ωn = 1.266rad/sec. The first analysis performed is the steady state solution, where a uniform wind Vw = 11.4 m/s is considered and a collective pitch angle θ = 0.88◦ is imposed. During this step, the authors noticed that the proposed model is intrinsically periodic due to the effect of the wind and of the gravitational force. In order to reject this periodic trend in the model dynamics, the authors propose a collective repetitive control algorithm coupled with a PD controller. In particular, when the reference command to be tracked and/or the disturbance to be rejected are periodic signals with a fixed period, the repetitive control strategies can be applied due to their high precision, simple implementation and little performance dependency on system parameters. The functional scheme of a repetitive controller is quite simple and, given a periodic reference command, is composed of a control block Crc(s) usually added to an existing feedback control system. The control block contains and a free time-delay system eτs in a positive feedback loop, and a low-pass filter q(s). It should be noticed that, while the time delay term reduces the stability margin, on the other hand the low pass filter is added to ensure stability. It is worth noting that, in this work, the authors propose a phase shifting for the controller and the delay system has been modified as e^(−(T−γk)), where T is the period of the signal and γk is a phase shifting of k samples of the same periodic signal. It should be noticed that, the phase shifting technique is particularly useful in non-minimum phase systems, such as flexible structures. In fact, using the phase shifting, the iterative algorithm could reach the convergence also at high frequencies. Notice that, in our case study, the shifting of k samples depends both on the rotor angular velocity Ω and on the rotor azimuth angle Ψ: we refer to this controller as a spatial repetitive controller. The collective repetitive controller has also been coupled with a C(s) = PD(s), in order to dampen oscillations of the blades. The performance of the spatial repetitive controller is compared with an industrial PI controller. In particular, starting from wind speed velocity Vw = 11.4 m/s the controller is asked to maintain the nominal angular velocity Ωn = 1.266rad/s after an instantaneous increase of wind speed (Vw = 15 m/s). Then, a purely periodic external disturbance is introduced in order to stress the capabilities of the repetitive controller. The results of the simulations show that, contrary to a simple PI controller, the spatial repetitive-PD controller has the capability to reject both external disturbances and periodic trend in the model dynamics. Finally, the nominal value of the angular velocity is reached, in accordance with results obtained with commercial software for a turbine of the same type.

Keywords: wind turbines, aeroelasticity, repetitive control, periodic systems

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Authors: Charaia Vakhtang

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Global oil prices are seeing new bottoms every day. The prices have already collapsed beneath the psychological verge of 30 USD. This tendency would be fully acceptable for the Georgian consumers, but there is one detail: two our neighboring countries (one friendly and one hostile) largely depend on resources of these hydrocarbons. Namely, the ratio of Azerbaijan in Georgia’s total FDI inflows in 2014 marked 20%. The ratio reached 40% in the January to September 2015. Azerbaijan is Georgia’s leading exports market. Namely, in 2014 Georgia’s exports to Azerbaijan constituted 544 million USD, i.e. 19% in Georgia’s total experts. In the January to November period of 2015, the ratio exceeded 11%. Moreover, Azerbaijan is Georgia’s strategic partner country as part of many regional projects that are designated for long-term perspectives. For example, the Baku-Tbilisi-Karsi railroad, the Black Sea terminal, preferential gas tariffs for Georgia and so on. The Russian economic contribution to the Georgian economy is also considerable, despite the losses the Russian hostile policy has inflicted to our country. Namely, Georgian emigrants are mainly employed in the Russian Federation and this category of Georgian citizens transfers considerable funds to Georgia every year. These transfers account for about 1 billion USD and consequently, these funds previously equalized to total FDI inflows. Moreover, despite the difficulties in the Russian market, Russia still remains a leader in terms of money transfers to Georgia. According to the last reports, money transfers from Russia to Georgia slipped by 276 million USD in 2015 compared to 2014 (-39%). At the same time, the total money transfers to Georgia in 2015 marked 1.08 billion USD, down 25% from 1.44 billion USD in 2014. This signifies the contraction in money transfers is by ¾ dependent on the Russian factor (in this case, contraction in oil prices and the Russian Ruble devaluation directly make negative impact on money transfers to Georgia). As to other countries, it is interesting that money transfers have also slipped from Italy (to 109 million USD from 121 million USD). Nevertheless, the country’s ratio in total money transfers to Georgia has increased to 10% from 8%. Money transfers to Georgia have increased by 22% (+18 million USD) from the USA. Money transfers have halved from Greece to 117 million USD from 205 million USD. As to Turkey, money transfers to Georgia from Turkey have increased by 1% to 69 million USD. Moreover, the problems with the national currencies of Russia and Azerbaijan, along with the above-mentioned developments, outline unfavorable perspectives for the Georgian economy. The depreciation of the national currencies of Azerbaijan and Russia is expected to bring unfavorable results for the Georgian economy. Even more so, the statement released by the Russian Finance Ministry on expected default is in direct relation to the welfare of the whole region and these tendencies will make direct and indirect negative impacts on Georgia’s economic indicators. Amid the economic slowdown in Armenia, Turkey and Ukraine, Georgia should try to enhance economic ties with comparatively stronger and flexible economies such as EU and USA. In other case, the Georgian economy will enter serious turbulent zone. We should make maximum benefit from the EU association agreement. It should be noted that the Russian economy slowdown that causes both regretful and happy moods in Georgia, will make negative impact on the Georgian economy. The same forecasts are made in relation to Azerbaijan. However, Georgia has many partner countries. Enhancement and development of the economic relations with these countries may maximally alleviate negative impacts from the declining economies. First of all, the EU association agreement should be mentioned as a main source for Georgia’s economic stabilization. It is the Georgian government‘s responsibility to successfully fulfill the EU association agreement requirements. In any case the imports must be replaced by domestic products and the exports should be stimulated through government support programs. The Authorities should ensure drawing more foreign investments and money resources, accumulating more tourism revenues and reducing external debts, budget expenditures should be balanced and the National Bank should carry out strict monetary policy. Moreover, the Government should develop a long-term state economic policy and carry out this policy at various Ministries. It is also of crucial importance to carry out constitutive policy and promote perspective directions on the domestic level.

Keywords: oil prices, economic growth, foreign direct investments, international trade

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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