Bibliografie tematiche / Hive Monitoring

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Letteratura scientifica selezionata sul tema "Hive Monitoring"

Autore: Grafiati

Pubblicato: 22 febbraio 2025

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Articoli di riviste sul tema "Hive Monitoring"

Khrystyuk, Andriy, e Kirpichnikov Anton. "Automatic apiary care system". Modeling Control and Information Technologies, n. 5 (21 novembre 2021): 54–55. http://dx.doi.org/10.31713/mcit.2021.16.

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An automatic control system for remote control and monitoring of bee life parameters in hives is developed. Based on the research of the main parameters of the life of bees in the hive, we have developed a scheme for managing and monitoring the weight of the hive, temperature and humidity, noise level, prevention of theft.

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Kuch, Ostap, e Ilona Lahun. "APIARY MONITORING AND AUTOMATION IOT SYSTEM". Measuring Equipment and Metrology 83, n. 4 (2022): 24–29. http://dx.doi.org/10.23939/istcmtm2022.04.024.

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A system of remote monitoring and automation apiary has been developed. This is a low-cost and scalable solution designed for deployment in distant rural areas. An unconventional solution is applying the industrial standard Modbus protocol to transfer data from the hives to a central server. This made it possible to reduce the cost of the system and standardize it. Monitoring the temperature and humidity inside the hives is important for analyzing the condition of bee colonies. The automation of the temperature and humidity control process is implemented based on a fuzzy model of the servo drive of the hive door.

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Bricout, Augustin, Philippe Leleux, Pascal Acco, Christophe Escriba, Jean-Yves Fourniols, Georges Soto-Romero e Rémi Floquet. "Bee Together: Joining Bee Audio Datasets for Hive Extrapolation in AI-Based Monitoring". Sensors 24, n. 18 (19 settembre 2024): 6067. http://dx.doi.org/10.3390/s24186067.

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Beehive health monitoring has gained interest in the study of bees in biology, ecology, and agriculture. As audio sensors are less intrusive, a number of audio datasets (mainly labeled with the presence of a queen in the hive) have appeared in the literature, and interest in their classification has been raised. All studies have exhibited good accuracy, and a few have questioned and revealed that classification cannot be generalized to unseen hives. To increase the number of known hives, a review of open datasets is described, and a merger in the form of the “BeeTogether” dataset on the open Kaggle platform is proposed. This common framework standardizes the data format and features while providing data augmentation techniques and a methodology for measuring hives’ extrapolation properties. A classical classifier is proposed to benchmark the whole dataset, achieving the same good accuracy and poor hive generalization as those found in the literature. Insight into the role of the frequency of the classification of the presence of a queen is provided, and it is shown that this frequency mostly depends on a colony’s belonging. New classifiers inspired by contrastive learning are introduced to circumvent the effect of colony belonging and obtain both good accuracy and hive extrapolation abilities when learning changes in labels. A process for obtaining absolute labels was prototyped on an unsupervised dataset. Solving hive extrapolation with a common open platform and contrastive approach can result in effective applications in agriculture.

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König, Andreas. "An in-hive soft sensor based on phase space features for <i>Varroa</i> infestation level estimation and treatment need detection". Journal of Sensors and Sensor Systems 11, n. 1 (20 gennaio 2022): 29–40. http://dx.doi.org/10.5194/jsss-11-29-2022.

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Abstract. Bees are recognized as an indispensable link in the human food chain and general ecological system. Numerous threats, from pesticides to parasites, endanger bees, enlarge the burden on hive keepers, and frequently lead to hive collapse. The Varroa destructor mite is a key threat to bee keeping, and the monitoring of hive infestation levels is of major concern for effective treatment. Continuous and unobtrusive monitoring of hive infestation levels along with other vital bee hive parameters is coveted, although there is currently no explicit sensor for this task. This problem is strikingly similar to issues such as condition monitoring or Industry 4.0 tasks, and sensors and machine learning bear the promise of viable solutions (e.g., creating a soft sensor for the task). In the context of our IndusBee4.0 project, following a bottom-up approach, a modular in-hive gas sensing system, denoted as BeE-Nose, based on common metal-oxide gas sensors (in particular, the Sensirion SGP30 and the Bosch Sensortec BME680) was deployed for a substantial part of the 2020 bee season in a single colony for a single measurement campaign. The ground truth of the Varroa population size was determined by repeated conventional method application. This paper is focused on application-specific invariant feature computation for daily hive activity characterization. The results of both gas sensors for Varroa infestation level estimation (VILE) and automated treatment need detection (ATND), as a thresholded or two-class interpretation of VILE, in the order of up to 95 % are presented. Future work strives to employ a richer sensor palette and evaluation approaches for several hives over a bee season.

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Nour Elhouda Bakri, Khaled Bouchoucha, Walid Nagara e M’Naouer Djemali. "Enhancing honeybee breeding for sustainable agriculture through temperature and relative humidity monitoring". World Journal of Advanced Research and Reviews 21, n. 2 (28 febbraio 2024): 286–92. http://dx.doi.org/10.30574/wjarr.2024.21.2.0412.

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Through their vital role in pollination, honeybee colonies play a crucial part in sustaining biodiversity and ensuring global food security. This paper aims to: 1) assess temperature and relative humidity variations within the hive and at the brood level; 2) determine genetic parameters for these traits; and 3) predict Breeding Values (PBVs) for honeybee colonies. Temperature and relative humidity data, during the period 2020-2023, were collected in Northern Tunisia using sensors placed inside hives and at the brood level. A dataset comprising 214,128 records for temperature and relative humidity within hives, sourced from 317 devices, was used in this study. Additionally, 20,740 records for temperature and relative humidity obtained from 78 brood-level devices were incorporated into the analysis. Phenotypic and genetic parameters were computed for the four examined traits, and using a BLUP Animal model, colony breeding values (PBVs) were predicted. Main results indicated a highly significant influence (p<0.01) of the month effect on the four temperature and relative humidity traits. Heritability estimates for in-hive temperature, in-hive relative humidity, brood relative humidity, and brood temperature were 0.14, 0.12, 0.16, and 0.28, respectively. Positive correlations were observed between relative humidity inside hives and at the brood level, as well as between temperature within beehives and at the brood level. Colony breeding values were predicted to select the best adapted bee queens to enhance honeybee’s sustainable use under Southern Mediterranean climatic conditions.

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Krishnasamy, Venkateswaran, N. Sridhar e L. Niranjan. "IoT-Based Beehive Monitoring System for Real-Time Monitoring of Apis cerana indica Colonies". Sociobiology 70, n. 4 (20 ottobre 2023): e9352. http://dx.doi.org/10.13102/sociobiology.v70i4.9352.

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A study was conducted to monitor the bee activity in the colonies of diferente strengths in real time using an IoT-based device. The in-hive temperature and relative humidity were measured in the colonies of Apis cerana indica Fabricius of different strengths using the sensor-laden IoT device that was correlated with the movement of foragers into and out of the hive. A significantly higher movement of foragers was recorded at an in-hive temperature and relative humidity of 27.84 ºC and 61.47% at 5-6 p.m. with an observed activity of 9,638 bees/hive/hour in the strong colonies. In the weak colonies, the mean forager activity was 1,436.3 bees/hive/hour, which was recorded at an in-hive temperature of 26.52 ºC and 61.42% relative humidity. The mean honey area in the strong and weak colonies were 1,300.80±177.61 cm2 and 508.80±156.84 cm2, respectively. Pollen area in the strong and weak colonies were 447.60±112.08 cm2 and 116.20±66.43 cm2, respectively. In the strong and weak colonies, the area under egg brood was 470±53.06 cm2 and 88.20±36.85 cm2, larvae brood was 583.40±11.04 cm2 and 80.00±24.67 cm2 and sealed brood was 684.20±57.98 cm2 and 102.80±16.59 cm2, respectively. The real-time data on the movement of foragers in the colonies of different strengths enabled us to undertake timely intervention in the maintenance of the bee colonies.

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Grigoryan, Leonty Rustemovich, Maxim Sergeevich Kovalenko, Anastasia Leontyevna Grigoryan e Dmitry Yuryevich Paroshin. "Intellectual beehives monitoring system". Agrarian Scientific Journal, n. 10 (23 ottobre 2019): 59–65. http://dx.doi.org/10.28983/asj.y2019i10pp59-65.

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A system for remote monitoring of the parameters of bee hives is considered. The problem of remote monitoring at long distances, taking into account the changing weather factors, is very relevant. Among the variety of hardware for keeping bees, there is currently no unified monitoring system. The studies carried out allowed us to determine the optimal circuitry and software components of the construction of a monitoring system. The result of the development of a system with a local hive monitoring system and a remote data collection system using cloud technologies is presented in this work.

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Catania, Pietro, e Mariangela Vallone. "Application of A Precision Apiculture System to Monitor Honey Daily Production". Sensors 20, n. 7 (3 aprile 2020): 2012. http://dx.doi.org/10.3390/s20072012.

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Precision beekeeping or precision apiculture is an apiary management strategy based on the monitoring of individual bee colonies to minimize resource consumption and maximize the productivity of bees. Bees play a fundamental role in ensuring pollination; they can also be considered as indicators of the state of pollution and are used as bio monitors. Beekeeping needs continuous monitoring of the animals and can benefit from advanced intelligent ambiance technologies. The aim of this study was the design of a precision apiculture system (PAS) platform for monitoring and controlling the following environmental parameters: wind, temperature, and relative humidity inside and outside the hive, in order to assess their influence on honey production. PAS is based on an Arduino board with an Atmel microcontroller, and the connection of a load cell for recording the weight of the hive, relative humidity and temperature sensor inside the hive, and relative humidity and temperature sensor outside the hive using an anemometer. PAS was installed in common hives and placed in an open field in a French honeysuckle plot; the system was developed to operate in continuous mode, monitoring the period of 24 April–1 June 2019. Temperature was constant in the monitored period, around 35 °C, inside the hive, proving that no criticalities occurred regarding swarming or absconding. In the period between 24 and 28 May, a lack of honey production was recorded, attributed to a lowering of the external temperature. PAS was useful to point out the eventual reduction in honey production due to wind; several peaks of windiness exceeding 5 m s−1 were recorded, noting that honey production decreases with the peaks in wind. Therefore, the data recorded by PAS platform provided a valid decisional support to the operator. It can be implemented by inserting additional sensors for detecting other parameters, such as rain or sound.

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Newton, Michael I., Luke Chamberlain, Adam McVeigh e Martin Bencsik. "Winter Carbon Dioxide Measurement in Honeybee Hives". Applied Sciences 14, n. 4 (19 febbraio 2024): 1679. http://dx.doi.org/10.3390/app14041679.

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Sensor technologies have sufficiently advanced to provide low-cost devices that can quantify carbon dioxide levels in honeybee hives with high temporal resolution and in a small enough package for hive deployment. Recent publications have shown that summer carbon dioxide levels vary throughout the day and night over ranges that typically exceed 5000 ppm. Such dramatic changes in a measurable parameter associated with bee physiology are likely to convey information about the colony health. In this work, we present data from four UK-based hives collected through the winter of 2022/2023, with a focus on seeing if carbon dioxide can indicate when colonies are at risk of failure. These hives have been fitted with two Sensirion SCD41 photoacoustic non-dispersive infrared (NDIR) carbon dioxide sensors, one in the queen excluder, at the top of the brood box, and one in the crown board, at the top of the hive. Hive scales have been used to monitor the hive mass, and internal and external temperature sensors have been included. Embedded accelerometers in the central frame of the brood box have been used to measure vibrations. Data showed that the high daily variation in carbon dioxide continued throughout the coldest days of winter, and the vibrational data suggested that daily fanning may be responsible for restoring lower carbon dioxide levels. The process of fanning will draw in colder air to the hive at a time when the bees should be using their energy to maintain the colony temperature. Monitoring carbon dioxide may provide feedback, prompting human intervention when the colony is close to collapse, and a better understanding may contribute to discussions on future hive design.

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Sanz, Milagros Casado, Rubén Prado-Jimeno e Juan Francisco Fuentes-Pérez. "Comparative Study of Natural Fibres to Improve Insulation in Wooden Beehives Using Sensor Networks". Applied Sciences 14, n. 13 (1 luglio 2024): 5760. http://dx.doi.org/10.3390/app14135760.

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The beekeeping sector is increasingly focused on creating optimal and natural environments for honeybees to reduce dependence on external factors, especially given progressively hotter summers. Improving hive thermal conditions can enhance bee wellbeing and production. While pinewood hives are predominant, some have started using insulating materials like polystyrene. However, many synthetic materials, despite their excellent insulation properties, are incompatible with organic food production, requiring alternative solutions. This study compares the thermal insulation properties of various natural materials, including white and black agglomerated cork, wood fibres, and rock mineral wool. These materials are potentially compatible with organic food production. Additionally, the research evaluates cost-effective sensor networks to monitor bioclimatic variables in real time. Lab tests using a Langstroth-type hive with a controlled heat source were conducted, monitoring temperature and humidity inside and outside the hive. The results revealed that all selected materials provided similar thermal insulation, superior to a hive without insulation. This finding suggests that using natural materials can enhance hive thermal comfort (i.e., the material’s ability to maintain a stable internal temperature), thereby improving honeybee wellbeing and productivity in a manner compatible with organic food production.

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Tesi sul tema "Hive Monitoring"

Bricout, Augustin. "Instrumentation embarquée avec correction déterministe et exploitation par IA de capteurs électroniques : application à la surveillance de ruches". Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSEI019.

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L'objectif de cette thèse est de développer des solutions de smart sensing à bas coût, permettant d'améliorer des capteurs peu onéreux grâce à des corrections logicielles. Plutôt que de concevoir des capteurs performants mais coûteux, cette approche vise à créer des capteurs low cost qui sont ensuite corrigés et optimisés via des algorithmes embarqués. Les architectures électroniques récentes offrent désormais une puissance de calcul suffisante pour effectuer ces corrections directement au plus proche de la mesure, edge computing, tout en conservant une consommation énergétique extrêmement faible rendant les systèmes sur batterie viables.Deux approches de correction logicielle sont explorées : une méthode basée sur un algorithme déterministe, et une seconde méthode s'appuyant sur l'intelligence artificielle. Après avoir conçu une architecture de collecte de données adaptée aux ruches d'abeilles, ces deux approches sont mises en œuvre. La première approche, déterministe, est utilisée pour corriger les données provenant des jauges de contrainte dans le cadre d'une balance à ruches. La seconde méthode est appliquée à des capteurs audio MEMS, afin d'extraire des métriques de santé des colonies d'abeilles grâce à des techniques de machine learning
The objective of this thesis is to develop low-cost smart sensing solutions, enhancing inexpensive sensors through software-based corrections. Rather than designing high-performance but expensive sensors, this approach aims to create low-cost sensors that are then corrected and optimized via embedded algorithms. Recent electronic architectures now offer sufficient computational power to perform these corrections directly at the measurement source, known as edge computing, while maintaining extremely low energy consumption, making battery-powered systems viable.Two software correction approaches are explored: a method based on a deterministic algorithm, and a second method relying on artificial intelligence. After designing a data collection architecture suited for beehives, both approaches are implemented. The first, deterministic approach is used to correct data from strain gauges in the context of a hive scale. The second method is applied to MEMS audio sensors, to extract bee colony health metrics using machine learning techniques

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Reynolds, Helen Elizabeth. "Therapeutic drug monitoring of the antiretrovirals". Thesis, University of Liverpool, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.273036.

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Otine, Charles. "HIV Patient Monitoring Framework Through Knowledge Engineering". Doctoral thesis, Blekinge Tekniska Högskola [bth.se], School of Planning and Media Design, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00540.

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Uganda has registered more than a million deaths since the HIV virus was first offi¬cially reported in the country over 3 decades ago. The governments in partnership with different groups have implemented different programmes to address the epidemic. The support from different donors and reduction in prices of treatment resulted in the focus on antiretroviral therapy access to those affected. Presently only a quarter of the approximately 1 million infected by HIV in Uganda are undergoing antiretroviral therapy. The number of patients pause a challenge in monitoring of therapy given the overall resource needs for health care in the country. Furthermore the numbers on antiretroviral therapy are set to increase in addition to the stringent requirements in tracking and monitoring of each individual patient during therapy. This research aimed at developing a framework for adopting knowledge engineering in information systems for monitoring HIV/AIDS patients. An open source approach was adopted due to the resource constrained context of the study to ensure a cost effec¬tive and sustainable solution. The research was motivated by the inconclusive literature on open source dimensional models for data warehouses and data mining for monitor¬ing antiretroviral therapy. The first phase of the research involved a situational analysis of HIV in health care and different health care information systems in the country. An analysis of the strengths, weaknesses and opportunities of the health care system to adopt knowledge bases was done. It proposed a dimensional model for implementing a data warehouse focused on monitoring HIV patients. The second phase involved the development of a knowledge base inform of an open source data warehouse, its simulation and testing. The study involved interdisciplinary collaboration between different stakeholders in the research domain and adopted a participatory action research methodology. This involved identification of the most appropriate technologies to foster this collabora¬tion. Analysis was done of how stakeholders can take ownership of basic HIV health information system architecture as their expertise grow in managing the systems and make changes to reflect even better results out of system functionality. Data mining simulations was done on the data warehouse out of which two machine learning algorithms (regression and classification) were developed and tested using data from the data warehouse. The algorithms were used to predict patient viral load from CD4 count test figures and to classify cases of treatment failure with 83% accu¬racy. The research additionally presents an open source dimensional model for moni¬toring antiretroviral therapy and the status of information systems in health care. An architecture showing the integration of different knowledge engineering components in the study including the data warehouse, the data mining platform and user interac-tion is presented.

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Caniglia, Ellen C. "Dynamic Monitoring Strategies for HIV-Positive Individuals". Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:27201722.

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The benefits of immunologic and virologic monitoring for the management of HIV-positive individuals are well established. However, the optimal frequency with which CD4 cell count and HIV RNA should be monitored remains unknown. In this dissertation, we use observational data from two collaborations of prospective cohort studies from high-income countries to estimate the effect of CD4 cell count and HIV RNA monitoring strategies on clinical, virologic, and immunologic outcomes in virologically suppressed HIV-positive patients. In Chapter 1, we compare three CD4 cell count and HIV-RNA monitoring strategies applied to virologically suppressed individuals on combined antiretroviral therapy (cART) without AIDS: once every (i) 3±1 months, (ii) 6±1 months, and (iii) 9-12 ±1 months. We find that monitoring frequency can be decreased from every 3 months to every 6, 9, or 12 months in the short term with respect to clinical outcomes. In Chapter 2, we compare strategies corresponding to three CD4 cell count thresholds at which monitoring frequency is decreased from every 3-6 months to every 9-12 months: 200 cells/µl, 350 cells/µl, and 500 cells/µl. We find that decreasing monitoring from every 3-6 months to every 9-12 months while CD4 cell count>200 cells/µl does not worsen the short-term clinical and immunologic outcomes of HIV-positive, virologically suppressed individuals on cART without AIDS. Our estimates also suggest that decreasing monitoring frequency when CD4 cell count>200 cells/µl compared with when CD4 cell count>500 cells/µl may result in an increased risk of virologic failure at 24 months of follow-up. In Chapter 3, we compare joint monitoring and treatment switching strategies. The strategies expand on those described in Chapter 2 by including two HIV-RNA threshold at which individuals should switch to a new antiretroviral regimen: 200 copies/ml and 1,000 copies/ml. We find that the studied monitoring-switching strategies have little impact on the short-term clinical outcomes of HIV-positive individuals on cART. In summary, we illustrate an approach to compare monitoring strategies in HIV-positive individuals, and provide estimates of the comparative effectiveness of strategies used in clinical practice. Since effects of different monitoring strategies could take years to materialize, longer follow-up is needed to fully evaluate this question.

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Jia, Yujiang. "Monitoring the status of HIV/AIDS in China". Thesis, Birmingham, Ala. : University of Alabama at Birmingham, 2007. https://www.mhsl.uab.edu/dt/2009r/jia.pdf.

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Exner, Natalie Mae. "Surveillance Methods for Monitoring HIV Incidence and Drug Resistance". Thesis, Harvard University, 2014. http://dissertations.umi.com/gsas.harvard:11444.

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Disease surveillance is the continuous collection, analysis, and interpretation of health-related data. Information gained from routine HIV disease surveillance is vital to national program managers deciding to implement new prevention or treatment programs. In this dissertation, we describe methods for estimation of HIV incidence and the prevalence of HIV drug resistance.

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Jani, Ilesh Vinodrai. "Immunological monitoring of HIV disease in resource-poor settings". Thesis, University College London (University of London), 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.404943.

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Corrigan, Gary E. "Evaluation of reverse transcriptase assay for viral load monitoring /". Stockholm, 2007. http://diss.kib.ki.se/2007/978-91-7357-207-1/.

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Archibald, Timothy L., Derek Edward Murrell e Stacy D. Brown. "Chromatographic Methods in Hiv Medicine: Application to Therapeutic Drug Monitoring". Digital Commons @ East Tennessee State University, 2018. https://doi.org/10.1002/bmc.4170.

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HIV antiretroviral therapy spans several different drug classes, meant to combat various aspects of viral infection and replication. Many authors have argued the benefits of therapeutic drug monitoring (TDM) for the HIV patient including compliance assurance and assessment of appropriate drug concentrations; however, the array of drug chemistries and combinations makes TDM an arduous task. HPLC-UV and LC-MS/MS are both frequent instruments for the quantification of HIV drugs in biological matrices with investigators striving to balance sensitivity and affordability. Plasma, the dominant matrix for these analyses, is prepared using protein precipitation, liquid-liquid extraction or solid-phase extraction depending on the specific complement of analytes. Despite the range of polarities found in drug classes relevant to HIV therapeutics, most chromatographic separations utilize a hydrophobic column (C18 ). Additionally, as the clinically relevant samples for these assays are infected with HIV, along with possible co-infections, another important aspect of sample preparation concerns viral inactivation. Although not routine in clinical practice, many published analytical methods from the previous two decades have demonstrated the ability to conduct TDM in HIV patients receiving various medicinal combinations. This review summarizes the analytical methods relevant to TDM of HIV drugs, while highlighting respective challenges.

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De, Milito Angelo. "Immune activation during HIV-1 infection : implication for B cell dysfunctions and therapy monitoring /". Stockholm, 2002. http://diss.kib.ki.se/2002/91-7349-170-5.

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Libri sul tema "Hive Monitoring"

England). Information Technology Services Hammersmith and Fulham (London. HIV resource monitoring system. Hammersmith, London]: [Hammersmith and Fulham Information Technology Services], 1991.

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Royal Colleges of Physicians of the United Kingdom. Committee on Health Promotion. Information for planning and monitoring HIV services. London: Faculty of Public Health Medicine of the Royal Colleges of Physicians of the United Kingdom, 1990.

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Kenya. National HIV/AIDS monitoring and evaluation framework. Nairobi, Kenya: National AIDS Control Council, 2005.

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Tanzania, Tume ya Kudhibiti Ukimwi. National monitoring and evaluation framework for HIV/AIDS. Dar es Salaam, Tanzania: Tanzania Commission for AIDS, 2004.

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McCoy, K. Lynn. Monitoring, evaluation, and reporting for hiv/aids programs. Washington, DC: Pact, 2005.

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1953-, Rugg Deborah L., Peersman Greet e Caraël Michel, a cura di. Global advances in HIV/AIDS monitoring and evaluation. San Francisco, Calif: Jossey-Bass, 2004.

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Swaziland. National Emergency Response Committee on HIV/AIDS. National multisectoral HIV and AIDS monitoring and evaluation system. Mbabane, Swaziland: National Emergency Response Council on HIV and AIDS, 2005.

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Commission, Malawi National AIDS, a cura di. Malawi HIV and AIDS monitoring and evaluation report 2005-2006. Lilongwe: National AIDS Commission, 2006.

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(Lesotho), National AIDS Commission, a cura di. National HIV and AIDS monitoring and evaluation plan (2006-2011). Maseru: National AIDS Commission, 2007.

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Chequer, Pedro. Monitoring and evaluation: Brazilian national STD/AIDS program. Washington, District of Columbia]: [Agency for International Development], 1999.

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Capitoli di libri sul tema "Hive Monitoring"

Atanasov, Atanas Z., Ivaylo S. Hristakov, Milan Koszel e Artur Przywara. "Monitoring Agrometeorological Factors and Weight of the Bee Hive During Black Locust (Robinia pseudoacacia) Flowering". In Lecture Notes in Civil Engineering, 239–51. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13090-8_25.

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Baluran, James Alfred, Dan Lloyd Lomongo, Ivant Fred Ondoy, Jinky Marcelo, Donah Rae Verula, Viceliogems Verula, Mohana Shanmugam e Lemuel Clark Velasco. "Performance Analysis of Deep Learning Models in Detection and Counting of Bees for Hive Monitoring". In Studies in Computational Intelligence, 55–74. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-75091-5_4.

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Richman, Douglas, Suzanne Crowe e Katya Harvey. "HIV Viral Load Monitoring". In Antiviral Chemotherapy 5, 199–212. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4743-3_19.

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Daniel, Volker. "Monitoring von HIV-Patienten". In Zelluläre Diagnostik, 741–58. Basel: KARGER, 2006. http://dx.doi.org/10.1159/000097725.

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Langmann, P., B. Weißbrich, C. Schlör, M. Zilly, E. Richter e H. Klinker. "Pl-Drug Monitoring bei Patienten mit HIV und HCV-Koinfektion". In HIV-Infekt, 507–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59683-4_91.

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Bird, A. G. "Monitoring of disease progression of HIV infection". In Immunology of HIV Infection, 91–111. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2980-0_6.

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Liu, Yufen, Scottie Bussell e Guodong Mi. "Quantitative Performance Monitoring of China’s HIV Response". In HIV/AIDS in China, 441–54. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8518-6_23.

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Haire, Bridget. "Providing Universal Access While Avoiding Antiretroviral Resistance: Ethical Tensions in HIV Treatment". In Ethics and Drug Resistance: Collective Responsibility for Global Public Health, 37–54. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-27874-8_3.

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Abstract The provision of effective antiretroviral therapy is an ethical imperative, and global access to antiretroviral drugs is an important aspect of this. The other less recognised aspect of effective HIV management is in ensuring that HIV does not become resistant to the drugs used in treatment (and increasingly also in prevention), as multi-drug resistant HIV poses a major threat to the sustainability of current responses to HIV control. In resource-constrained environments, the rapid scale up of access to life-saving anti-HIV treatment was achieved using a public health approach that standardised antiretroviral regimens, minimised laboratory monitoring, and devolved responsibilities from clinicians where necessary. In recent years demand for antiretroviral treatment has increased due to new understandings of the clinical importance of early treatment, but global investment has declined. Exponential growth of the population using antiretrovirals without careful monitoring increases the risk of significant antiretroviral drug resistance. In this chapter, I consider the example of single-drug interventions to prevent parent-to-child HIV transmission, and how the implementation of that strategy increased health risks for mothers. I argue that while global antiretroviral scale up must continue, laboratory monitoring at individual and national levels needs to improve to maintain treatment effectiveness, and protocols for moving people from failing regimens need to be strengthened.

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Li, Hongjun. "Introduction to Assessment and Monitoring of Critical AIDS". In Radiology of HIV/AIDS, 69–76. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7823-8_11.

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Stroobant, A., M. Denayer, A. M. Worm, M. Stangerup, A. Pönkä, L. Meyer, J. Stratigos et al. "Monitoring HIV Seroprevalence in STD Patients". In Assessing AIDS Prevention, 69–74. Basel: Birkhäuser Basel, 1992. http://dx.doi.org/10.1007/978-3-0348-7211-9_6.

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Atti di convegni sul tema "Hive Monitoring"

Gljušćić, Petar, Marko Perčić e Saša Zelenika. "Autonomous Energy Harvesting – Based System for Honeybee Hive Monitoring". In 2024 21st International Conference on Mechatronics - Mechatronika (ME), 1–6. IEEE, 2024. https://doi.org/10.1109/me61309.2024.10789729.

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Eslit, John Jairus D. P., Neil Astrologo, Aldon Cris Galido, Jomari Ganhinhin, Percival Magpantay, Marc D. Rosales e John Richard E. Hizon. "CARE HIVE: A Scalable IoT Platform for Collaborative Air Quality Monitoring and Research". In 2024 IEEE International Conference on Omni-layer Intelligent Systems (COINS), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/coins61597.2024.10622137.

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Florea, George, Norocel Codreanu, Vlad Virgiliu Alexandrescu e Vlad Aurelian Preda. "Electronic Apiary Monitoring System with Built-in Sensors and Motorized Hive Access Control". In 2024 IEEE 30th International Symposium for Design and Technology in Electronic Packaging (SIITME), 416–20. IEEE, 2024. https://doi.org/10.1109/siitme63973.2024.10814841.

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Demir, Saliha, Mahnoor Zafar, Anila Khan e Azhar Ilyas. "HIVision: Automated Computer Vision Cell Counting Application for HIV Diagnosis and Monitoring". In 2024 IEEE Long Island Systems, Applications and Technology Conference (LISAT), 1–6. IEEE, 2024. https://doi.org/10.1109/lisat63094.2024.10808102.

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Jegan, S., L. Padmapriya, P. Vidhya Manjari e R. Shanmathi. "Honey hive monitoring using IOT". In PROCEEDINGS OF THE 4TH NATIONAL CONFERENCE ON CURRENT AND EMERGING PROCESS TECHNOLOGIES E-CONCEPT-2021. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0070127.

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Milovanović, M., J. Pejić e P. Pejić. "IoT Enabled Bee Hive Monitoring System". In 2023 IEEE 33rd International Conference on Microelectronics (MIEL). IEEE, 2023. http://dx.doi.org/10.1109/miel58498.2023.10315862.

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Vidrascu, M. G., e P. M. Svasta. "Embedded software for IOT bee hive monitoring node". In 2017 IEEE 23rd International Symposium for Design and Technology in Electronic Packaging (SIITME). IEEE, 2017. http://dx.doi.org/10.1109/siitme.2017.8259887.

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Tashakkori, Rahman, e Ahmad Ghadiri. "Image processing for honey bee hive health monitoring". In SoutheastCon 2015. IEEE, 2015. http://dx.doi.org/10.1109/secon.2015.7133029.

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Atanasov, Atanas, Ivaylo Hristakov e Veselin Dochev. "Monitoring agrometeorological factors and beehive weight during sunflower (Helianthus annuus) flowering". In 22nd International Scientific Conference Engineering for Rural Development. Latvia University of Life Sciences and Technologies, Faculty of Engineering, 2023. http://dx.doi.org/10.22616/erdev.2023.22.tf011.

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The impact of local agrometeorological factors on beehive changing weight during sunflower (Helianthus annuus) flowering was monitored. The study was conducted in 2021 growing season in a hilly flat area with predominant agricultural crops. The location of the experimental apiary is 43°32’4.02”N and 25°45’14.10”E at an altitude of 223 m. The experimental apiary consisted of 122 bee colonies housed in Dadant-Blatt hives. The bees are of the species (Apis mellifera macedonica). The total number of fields sown with sunflower was 6. All sunflower fields were located within a radius of the bees’ optimal flight area. During the experiment there were observed the outside air temperature (Tair), 0°C and air humidity (Hair)%, atmospheric pressure (Ap) hPa, soil moisture (Sm), % at 20 cm depth, soil temperature (St), °C at 10 cm depth, solar radiation (Sr) W·m-2, wind speed (Ws), m·s-1, precipitated rainfall (R), l·m-2. Also the air temperature inside (Tin) the hive was measured. The nectar flow is determined based on the changes in hive weight (Y). The real-time data were available via a web-based application Meteobot®. The results show that there is a significant positive correlation between Y and honey harvesting date D, honey harvesting time per day T, Tair, St, Ap. The other weather indicators as Hair, Sm Ws Dp, Tin are negatively correlated with Y. The indicator Sr is not correlated with Y. The monitoring of the agrometeorological factors and beehive weight during sunflower flowering will help the beekeepers determine the suitable moment for expanding the capacity of the hive and honey extracting.

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Magnier, Baptiste, Gaëtan Ekszterowicz, Joseph Laurent, Matthias Rival e François Pfister. "Bee Hive Traffic Monitoring by Tracking Bee Flight Paths". In International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006628205630571.

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Rapporti di organizzazioni sul tema "Hive Monitoring"

Using a rapid assessment approach to evaluate the quality of care in an integrated program: The experience of the Family Health Division, Ministry of Health, Botswana. Population Council, 1997. http://dx.doi.org/10.31899/rh1997.1001.

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To strengthen existing efforts by the Government of Botswana in responding to the HIV/AIDS epidemic, USAID provided financial and technical assistance through the Botswana Population Assistance (BOTSPA) project. BOTSPA’s goal was to improve the quality and availability of family planning (FP) and sexually transmitted infection (STI) services through designing, implementing, and monitoring activities that would lead to the eventual institutionalization and sustainability of high-quality FP and STI/HIV/AIDS services. The Ministry of Health requested assistance from the Africa OR/TA Project II to develop and test an approach for routinely measuring the quality of service delivery and assessing skills retention by staff trained through in-service courses. A rapid assessment mechanism was designed and then used to determine the readiness of health facilities in Botswana to offer quality FP and STI management services. According to this report, the mechanism was found generally acceptable, easy to use by staff and managers, and provided valid information on the readiness of the health facilities to provide FP and STI services.

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