Optimising Vine Weevil, Otiorhynchus sulcatus F. (Coleoptera: Curculionidae), Monitoring Tool Design

Vine weevil, Otiorhynchus sulcatus F. (Coleoptera: Curculionidae), is an economically important insect pest of horticultural crops. To identify an effective and reliable monitoring system for adult vine weevil, this study investigated the influence of colour, height and entrance position on the efficacy of a model monitoring tool using modified paper cups as refuges. Vine weevil preferences were determined by the number of individuals recorded within a refuge. When provided with a binary choice between black or white refuges, vine weevil adults showed a preference for black refuges. Vine weevils provided with a range of coloured refuges (blue, green, red and yellow) in addition to black and white refuges showed a preference for black and blue over the other colours and white refuges in group choice experiments. Refuge height and entrance position also influenced vine weevil behaviour with individuals exhibiting a preference for taller refuges and those with entrance openings around the refuge base. These results provide insights into refuge selection by adult vine weevils, which can be exploited to improve monitoring tool design. The importance of developing an effective monitoring tool for vine weevil adults as part of an integrated pest management programme is discussed.

Monitoring of the Village Malaria Workers to conduct activities of Malaria Elimination Demonstration Project in Mandla, Madhya Pradesh

Background The capacity of the field staff to conduct activities related to disease surveillance, case management, and vector control has been one of the key components for successfully achieving malaria elimination. India has committed to eliminate malaria by 2030, and it has placed significance on monitoring and evaluation at the district level as one of the key strategies in its national framework. To support and guide the country’s malaria elimination objectives, the Malaria Elimination Demonstration Project was conducted in the tribal district of Mandla, Madhya Pradesh. Robust monitoring of human resources received special attention to help the national programme formulate a strategy to plug the gaps in its supply chain and monitoring and evaluation systems. Methods A monitoring tool was developed to test the capabilities of field workers to conduct activities related to malaria elimination work. Between November 2018 to February 2021, twenty-five Malaria Field Coordinators (MFCs) of the project utilized this tool everyday during the supervisory visits for their respective Village Malaria Workers (VMWs). The data was analysed and the scores were tested for variations against different blocks, educational status, duration of monitoring, and post-training scores. Results During the study period, the VMWs were monitored a total of 8974 times using the monitoring tool. Each VMW was supervised an average of 1.8 times each month. The critical monitoring indicators scored well in all seven quarters of the study as monitored by the MFCs. Monitoring by MFCs remained stable at 97.3% in all quarters. Contrary to expectations, the study observed longer diagnosis to treatment initiation time in urban areas of the district. Conclusion This study demonstrated the significance of a robust monitoring tool as an instrument to determine the capacity of the field workers in conducting surveillance, case management, and vector control related work for the malaria elimination programme. Similar tools can be replicated not only for malaria elimination, but other public health interventions as well.

The Italian strategy to fight illegal treatment with growth promoters: Results of the 2017-2019 histological monitoring plan

The Histological Control Plan has been introduced in Italy in 2008 as an indirect monitoring tool of illicit administration of sexual hormones and corticosteroids in bovine. Analysis of 2008-2016 results permitted to draw a new plan targeting risk category. This work presents the results of the histopathological monitoring plan that was carried out from 2017 to 2019. The overall prevalence of samples suspected of treatment with corticosteroid was 11.3% [95% confidence interval (CI) 6.6-17.8] in 2017; 10.2% (95% CI 6.6-16.9) in 2018 and 8.9% (95% CI 4.6-15.4) in 2019. The overall prevalence of samples suspected of treatment with sexual hormones was 2.3 % (95% CI 0.5-6.6) in 2017; 6.2% (95% CI 2.7-11.8) in 2018 and 12.4% (95% CI 7.4- 19.1) in 2019. Although not targeting and measuring specific molecules, this strategy allows to verify the trend of illicit treatments and identify farms to be submitted to further check.

Enhancing Cloud Availability via Intelligent Monitoring using Time Series Database and Machine Learning

Every cloud provider, wishes to provide 99.9999% availabil- ity for the systems provisioned and operated by them for the customer i.e. may it be SaaS or PaaS or IaaS model, the availability of the system must be greater than 99.9999%.It becomes vital for the provider to mon- itor the systems and take proactive measures to reduce the downtime.In an ideal scenario, the support colleagues (24*7 technical support) must be aware of the on-going issues in the production systems before it is raised as an incident by the customer. But currently, there is no effective alert monitoring solutions for the same. The proposed solution presented in this paper is to have a central alert monitoring tool for all cloud so- lutions offered by the cloud provider. The central alert monitoring tool constantly observes the time series database which contains metric val- ues populated by HA and compares the incoming metric values with the defined thresholds. When a metric value exceeds the defined threshold, using machine learning techniques the monitoring tool decides & takes actions.

Pembuatan Alat Monitoring Infus Berbasis NodeMCU ESP8266

The problem of late replacement of infusion mattresses for patients in a medical institution is still common today. It still helps him closely with the nurses' negligence in monitoring the patient's infusion condition. This condition is very dangerous for the patient's health. Therefore the making of infusion monitoring equipment based on NodeMCU esp8266. This tool works by relying on the results of sensor readings that are inserted into the microcontroller which will be processed by NodeMCU. The sensor used in making this system is the sensor module, the sensor reading sensor is the intended emission sensor - in this case, means the drip drops, the sensor will count the number of drops. From the number of drops, it can be used to count the drip infusion. In this study, it can be concluded that the NodeMCU ESP 8266-based infusion monitoring tool using the IR Obstacle sensor component has been successfully made through the functionality test process.

Estimating Actual Evapotranspiration over Croplands Using Vegetation Index Methods and Dynamic Harvested Area

Advances in estimating actual evapotranspiration (ETa) with remote sensing (RS) have contributed to improving hydrological, agricultural, and climatological studies. In this study, we evaluated the applicability of Vegetation-Index (VI) -based ETa (ET-VI) for mapping and monitoring drought in arid agricultural systems in a region where a lack of ground data hampers ETa work. To map ETa (2000–2019), ET-VIs were translated and localized using Landsat-derived 3- and 2-band Enhanced Vegetation Indices (EVI and EVI2) over croplands in the Zayandehrud River Basin (ZRB) in Iran. Since EVI and EVI2 were optimized for the MODerate Imaging Spectroradiometer (MODIS), using these VIs with Landsat sensors required a cross-sensor transformation to allow for their use in the ET-VI algorithm. The before- and after- impact of applying these empirical translation methods on the ETa estimations was examined. We also compared the effect of cropping patterns’ interannual change on the annual ETa rate using the maximum Normalized Difference Vegetation Index (NDVI) time series. The performance of the different ET-VIs products was then evaluated. Our results show that ETa estimates agreed well with each other and are all suitable to monitor ETa in the ZRB. Compared to ETc values, ETa estimations from MODIS-based continuity corrected Landsat-EVI (EVI2) (EVIMccL and EVI2MccL) performed slightly better across croplands than those of Landsat-EVI (EVI2) without transformation. The analysis of harvested areas and ET-VIs anomalies revealed a decline in the extent of cultivated areas and a loss of corresponding water resources downstream. The findings show the importance of continuity correction across sensors when using empirical algorithms designed and optimized for specific sensors. Our comprehensive ETa estimation of agricultural water use at 30 m spatial resolution provides an inexpensive monitoring tool for cropping areas and their water consumption.