Kooperativer Bibliotheksverbund

Berlin Brandenburg

and
and

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Type of Medium
Language
Year
  • 1
    Language: English
    In: Journal of Chromatography A, 2011, Vol.1218(17), pp.2368-2373
    Description: Rotaviruses are the leading cause of gastroenteritis in children and they exist widely in water environments. Ingestion of 10–100 viral particles is enough to initiate disease, what calls for extremely sensitive detection methods. In this study we have confirmed the validity of a recently published method for rotavirus concentration and detection based on the combination of methacrylate monoliths and real-time reverse transcription-quantitative PCR (RT-qPCR). The method was used to concentrate rotaviruses from different tap water and environmental water samples collected in Slovenia within years 2007 and 2009. The performance of virus concentration using monolithic supports was improved in comparison to the one of tangential ultrafiltration upon application of both methods on a range of environmental samples. Several samples were successfully concentrated on-site after successful adaptation of the method to field requirements. In such on-site format, the combination of concentration using CIM and detection using RT-qPCR detected as low as 30 rotavirus particles/ml, spiked in an environmental water sample.
    Keywords: Rotavirus ; Methacrylate Monoliths ; Concentration and Detection ; On-Site ; Chemistry
    ISSN: 0021-9673
    E-ISSN: 18733778
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    Language: English
    In: Vaccine, 01 May 2014, Vol.32(21), pp.2487-2492
    Description: We explored the possibilities for purification of various ΔNS1 live, replication deficient influenza viruses on ion exchange methacrylate monoliths. Influenza A ΔNS1-H1N1, ΔNS1-H3N2, ΔNS1-H5N1 and ΔNS1-influenza B viruses were propagated in Vero cells and concentrated by tangential flow filtration. All four virus strains adsorbed well to CIM QA and CIM DEAE anion exchangers, with CIM QA producing higher recoveries than CIM DEAE. ΔNS1-influenza A viruses adsorbed well also to CIM SO3 cation exchanger at the same pH, while ΔNS1-influenza B virus adsorption to CIM SO3 was not complete. Dynamic binding capacity (DBC) for CIM QA, DEAE and SO3 methacrylate monoliths for influenza A ΔNS1-H1N1 virus were 1.9E + 10 TCID /ml, 1.0E + 10 TCID /ml and 8.9E + 08 TCID /ml, respectively. Purification of ΔNS1 viruses on CIM QA was scaled up and reproducibility was confirmed. Yields of infectious virus on CIM QA were between 70.8 ± 32.3% and 87 ± 30.8%. Total protein removal varied from 93.3 ± 0.4% to 98.6 ± 0.2% and host cell DNA removal efficiency was ranging from 76.4% to 99.9% and strongly depended on pretreatment with deoxyribonuclease.
    Keywords: Influenza Viruses ; Vaccines ; Purification ; Chromatography ; Monoliths ; Medicine ; Biology ; Veterinary Medicine ; Pharmacy, Therapeutics, & Pharmacology
    ISSN: 0264-410X
    E-ISSN: 1873-2518
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    Language: English
    In: Journal of Chromatography A, 2009, Vol.1216(13), pp.2700-2704
    Description: Rotaviruses are the leading cause of diarrhoea in infants around the globe and, under certain conditions they can be present in drinking water sources and systems. Ingestion of 10–100 viral particles is enough to cause disease, emphasizing the need for sensitive diagnostic methods. In this study we have optimized the concentration of rotavirus particles using methacrylate monolithic chromatographic supports. Different surface chemistries and mobile phases were tested. A strong anion exchanger and phosphate buffer (pH 7) resulted in the highest recoveries after elution of the bound virus with 1 M NaCl. Using this approach, rotavirus particles spiked in 1 l volumes of tap or river water were efficiently concentrated. The developed concentration method in combination with a real time quantitative polymerase chain reaction assay detected rotavirus concentrations as low as 100 rotavirus particles/ml.
    Keywords: Rotavirus ; Methacrylate Monoliths ; Concentrating Viruses ; Ion-Exchange Chromatography ; Water Contamination ; Rt Q-Pcr ; Chemistry
    ISSN: 0021-9673
    E-ISSN: 18733778
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 4
    In: BioProcessing Journal, 04/30/2005, Vol.4(2), pp.79-84
    ISSN: 15388786
    Source: CrossRef
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 5
    Language: English
    In: Journal of Virological Methods, 2009, Vol.162(1), pp.272-275
    Description: Human enteric viruses are detected frequently in various types of environmental water samples, such as irrigation water, wastewater, recreational water, ground or subsurface water and even drinking water, constituting a primary source of gastroenteritis or hepatitis outbreaks. Only a few, but still infective number of viral particles are normally present in water samples, therefore an efficient virus concentration procedure is essential prior to molecular detection of the viral nucleic acid. In this study, a novel chromatographic technology, Convective Interaction Media (CIM) monolithic supports, were optimized and applied to the concentration of hepatitis A virus (HAV) and feline calicivirus (FCV), a surrogate of norovirus (NoV), from water samples. Two-step real-time RT-qPCR was used for quantitation of the virus concentration in the chromatographic fractions. Positively charged CIM QA (quaternary amine) monolithic columns were used for binding of HAV and FCV present in previously inoculated 1.5 l bottled water samples. Column bound viruses were eluted from the monolith using 1 M NaCl to a final volume of 15 ml. Elution volume was concentrated further by ultracentrifugation. When the CIM/ultracentrifugation method was compared with another concentration method employing positively charged membranes and ultrafiltration, the recovery of HAV was improved by approximately 20%.
    Keywords: Monolithic Columns ; Virus Concentration ; Hav ; Fcv ; Water ; Biology
    ISSN: 0166-0934
    E-ISSN: 1879-0984
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 6
    Language: English
    In: Journal of Thermal Analysis and Calorimetry, July, 2014, Vol.117(1), p.277(8)
    Keywords: Disaccharides -- Thermal Properties
    ISSN: 1388-6150
    Source: Cengage Learning, Inc.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 7
    Language: English
    In: Journal of Thermal Analysis and Calorimetry, 7/2014, Vol.117(1), pp.277-284
    Description: The purpose of this study is to research the thermal properties of spreads with maltitol. Thermal characteristics of spreads depend on process parameters (temperature, mixer speed rotation). Spreads are produced at different temperatures (30, 35, and 40 degree C) and mixer speed rotation (1, 1.33, and 1.67 Hz). The thermogravimetric method shows the peak position and determinate the spread composition. The temperature decomposition of sucrose and maltitol is two stages (two peaks), and palm fat has a single stage decomposition (one peak). Maltitol peak is dominant for spreads containing 100 and 70 % maltitol as a sweetener. This peak is sharper than sucrose peak and the inflection point is more expressed. Shape and the position of these peaks in spreads are modified. Peaks of maltitol, palm fat, and sucrose in spreads are lower and wider because of the grinding process and the interaction between spread ingredients. Increasing the process parameters (temperature, mixer speed rotation), temperatures of these peaks are higher (closer to temperature peak of pure ingredients). The dominant parameter is mixer speed rotation. The most thermally stable spreads with any amount of maltitol are produced at a temperature of 40 degree C and high mixer speed rotation (1.33 and 1.67 Hz), while the least stable maltitol spreads are produced at minimum process parameters (30 degree C, 1 Hz).
    Keywords: Ingredients ; Process Parameters ; Sucrose ; Palm ; Inflection Points ; Mixers ; Decomposition ; Spreads ; Instruments and Measurements (So) ; Analysis (MD) ; Chemical Analysis (Ep) ; Chemical Analysis (Ed) ; Chemical Analysis (EC) ; Spreads ; Thermal Characteristics ; Maltitol ; Sucrose ; Process Parameters;
    ISSN: 1388-6150
    E-ISSN: 1588-2926
    Source: Springer (via CrossRef)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 8
    Language: English
    In: Facta Universitatis. Series: Mechanical Engineering, 01 December 2017, Vol.15(3), pp.457-465
    Description: Electricity is a key energy source in each country and an important condition for economic development. It is necessary to use modern methods and tools to predict energy consumption for different types of systems and weather conditions. In every industrial plant, electricity consumption presents one of the greatest operating costs. Monitoring and forecasting of this parameter provide the opportunity to rationalize the use of electricity and thus significantly reduce the costs. The paper proposes the prediction of energy consumption by a new time-series model. This involves time series models using a set of previously collected data to predict the future load. The most commonly used linear time series models are the AR (Autoregressive Model), MA (Moving Average) and ARMA (Autoregressive Moving Average Model). The AR model is used in this paper. Using the AR (Autoregressive Model) model, the Monte Carlo simulation method is utilized for predicting and analyzing the energy consumption change in the considered tobacco industrial plant. One of the main parts of the AR model is a seasonal pattern that takes into account the climatic conditions for a given geographical area. This part of the model was delineated by the Fourier transform and was used with the aim of avoiding the model complexity. As an example, the numerical results were performed for tobacco production in one industrial plant. A probabilistic range of input values is used to determine the future probabilistic level of energy consumption.
    Keywords: Engineering ; Physics
    ISSN: 0354-2025
    E-ISSN: 2335-0164
    Source: Directory of Open Access Journals (DOAJ)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 9
    Language: English
    In: Social Psychiatry and Psychiatric Epidemiology, 2017, Vol.52(8), pp.989-1003
    Description: To access, purchase, authenticate, or subscribe to the full-text of this article, please visit this link: http://dx.doi.org/10.1007/s00127-017-1366-0 Byline: Dzmitry Krupchanka (1,2), Hind Khalifeh (2), Jibril Abdulmalik (3), Sara Ardila-Gomez (4), Aishatu Yusha'u Armiya'u (5), Visnja Banjac (6), Alexey Baranov (7), Nikita Bezborodovs (8), Petrana Brecic (9), Zoran Cavajda (10), Giovanni Girolamo (11), Maria Denisenko (12), Howard Akena Dickens (13), Josip Dujmovic (14), Dubravka Ergovic Novotny (15), Ilya Fedotov (16), Marina A. Fernandez (4), Iryna Frankova (17), Marta Gasparovic (18), Catalina Giurgi-Oncu (19), Tanja Grahovac (20), Bawo O. James (21), Rabaa Jomli (22,23), Ivana Kekin (24), Rajna Knez (20), Mariangela Lanfredi (26), Francesca Lassman (28), Nisha Mehta (29), Fethi Nacef (22,23), Alexander Nawka (30), Martin Nemirovsky (31), Bolanle Adeyemi Ola (32), Yewande O. Oshodi (33), Uta Ouali (22,23), Tomislav Peharda (34), Andrea Razic Pavicic (24), Martina Rojnic Kuzman (24,25), Costin Roventa (27), Rinat Shamenov (35), Daria Smirnova (36), Davorka Smoljanic (34), Anna Spikina (37), Amalia Thornicroft (38), Marko Tomicevic (39), Domagoj Vidovic (9), Paul Williams (2), Yulia Yakovleva (40), Olena Zhabenko (41), Tatiana Zhilyaeva (42), Maja Zivkovic (9), Graham Thornicroft (2), Norman Sartorius (43) Keywords: Patients satisfaction; Service evaluation; Inpatient care; Psychiatry Abstract: Purpose There is disregard in the scientific literature for the evaluation of psychiatric in-patient care as rated directly by patients. In this context, we aimed to explore satisfaction of people treated in mental health in-patient facilities. The project was a part of the Young Psychiatrist Program by the Association for the Improvement of Mental Health Programmes. Methods This is an international multicentre cross-sectional study conducted in 25 hospitals across 11 countries. The research team at each study site approached a consecutive target sample of 30 discharged patients to measure their satisfaction using the five-item study-specific questionnaire. Individual and institution level correlates of 'low satisfaction' were examined by comparisons of binary and multivariate associations in multilevel regression models. Results A final study sample consisted of 673 participants. Total satisfaction scores were highly skewed towards the upper end of the scale, with a median total score of 44 (interquartile range 38--48) out of 50. After taking clustering into account, the only independent correlates of low satisfaction were schizophrenia diagnosis and low psychiatrist to patient ratio. Conclusion Further studies on patients' satisfaction should additionally pay attention to treatment expectations formed by the previous experience of treatment, service-related knowledge, stigma and patients' disempowerment, and power imbalance. Author Affiliation: (1) Department of Social Psychiatry, National Institute of Mental Health, Topolova 748, 250 67, Klecany, Czech Republic (2) Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK (3) Department of Psychiatry, University of Ibadan, Ibadan, Nigeria (4) Research Institute, School of Psychology, University of Buenos Aires, Buenos Aires, Argentina (5) Department of Psychiatry, Jos University Teaching Hospital, Jos, Nigeria (6) Clinic of Psychiatry, University Clinical Center of the Republic of Srpska, Banjaluka, Bosnia and Herzegovina (7) Tambov Psychiatric Hospital, Tambov, Russian Federation (8) Children's Clinical University Hospital, Riga, Latvia (9) University Psychiatric Hospital Vrapce, Zagreb, Croatia (10) Department of Acute and Biological Psychiatry, Clinical Hospital Centre Osijek, Osijek, Croatia (11) Unit of Psychiatric Epidemiology and Evaluation, Saint John of God Clinical Research Centre, Brescia, Italy (12) Mental Health Clinic No1, Nizhny Novgorod, Russian Federation (13) Makerere University College of Health Sciences, Kampala, Uganda (14) KBC Zagreb, Zagreb, Croatia (15) General Hospital "Dr. Josip Bencevic", Slavonski Brod, Croatia (16) Ryazan State Medical University, Ryazan, Russian Federation (17) Bogomolets National Medical University, Kyiv, Ukraine (18) Osijek University Hospital, Osijek, Croatia (19) a[sup.3]Victor Babes" University of Medicine and Pharmacy of Timisoara, Timisoara, Romania (20) University Hospital Center Rijeka, Rijeka, Croatia (21) Federal Neuro-Psychiatric Hospital, Benin City, Nigeria (22) Department of Psychiatry "A" at Razi Hospital, Manouba, Tunisia (23) Faculty of Medicine, University of Tunis El Manar, Tunis, Tunisia (24) University Hospital Centre Zagreb, Zagreb, Croatia (25) Zagreb School of Medicine, Zagreb, Croatia (26) Unit of Psychiatry, Saint John of God Clinical Research Centre, Brescia, Italy (27) Neuropsychiatric Hospital, Craiova, Romania (28) Great Ormond Street Hospital, London, UK (29) NHS Tayside, Dundee, Scotland, UK (30) Institute of Neuropsychiatric Care (INEP), Prague, Czech Republic (31) Proyecto SUMA-Medicus, Buenos Aires, Argentina (32) Lagos State University College of Medicine, Ikeja, Nigeria (33) Department of Psychiatry, College of Medicine, University of Lagos, Lagos, Nigeria (34) Psychiatric ward, General Hospital Pula, Pula, Croatia (35) Samara Psychiatric Hospital, Samara, Russian Federation (36) Department of Psychiatry, Samara State Medical University, Samara, Russian Federation (37) Medical University Named After I.I. Mechnikov, Saint Petersburg, Russian Federation (38) Occupational Therapy Department, St George's University Hospitals NHS Foundation Trust, London, UK (39) Neuropsychiatric Hospital "Dr. Ivan Barbot", Popovaca, Croatia (40) Saint Petersburg Bekhterev Psychoneurological Research Institute, Saint Petersburg, Russian Federation (41) Railway Clinical Hospital 1 Station Kyiv, Kyiv, Ukraine (42) Department of Psychiatry and Medical Psychology, Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russian Federation (43) Association for the Improvement of Mental Health Programmes, Geneve, Switzerland Article History: Registration Date: 18/02/2017 Received Date: 26/09/2016 Accepted Date: 16/02/2017 Online Date: 11/03/2017 Article note: Electronic supplementary material The online version of this article (doi: 10.1007/s00127-017-1366-0) contains supplementary material, which is available to authorized users.
    Keywords: Patients satisfaction ; Service evaluation ; Inpatient care ; Psychiatry
    ISSN: 0933-7954
    E-ISSN: 1433-9285
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 10
    Language: English
    In: 2014 IEEE International Energy Conference (ENERGYCON), May 2014, pp.1223-1227
    Description: Microgrid is defined as a cluster of distributed generation sources, storages and loads that cooperate together in order to improve power supply reliability and overall power system stability. Short-term power production and load profile prediction is very important for power flow optimization in a microgrid, thus enhancing the management of distributed generation sources and storages in order to improve the microgrid reliability, as well as the economics of energy trade with electricity markets. However, short-term load prediction is a complex procedure, mainly because of the highly nonsmooth and nonlinear behaviour of the load time series. In this paper we develop and verify a neural-network-based short-term load profile prediction model. Neural network inputs are lagged load data, as well as meteorological and time data, while neural network output is load at the particular moment. Neural network training and validation is performed on load data recorded at University of Zagreb Faculty of Electrical Engineering and Computing, and on meteorological data obtained from Meteorological and Hydrological Service of Croatia, in period 2011-2013.
    Keywords: Biological Neural Networks ; Load Modeling ; Training ; Neurons ; Predictive Models ; Microgrids ; University Building ; Load Forecast ; Microgrids ; Power Flow Optimization ; Neural Networks
    Source: IEEE Conference Publications
    Source: IEEE Xplore
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages