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Copyright of Modern Educational Technology is the property of Editorial Board of Modern Educational Technology, Tsinghua University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Large industrial producers consume a huge amount of energy and are a key area of focus for achieving peak carbon and carbon neutrality targets. Based on the operational monitoring of the traditional energy supply system and the transformed PV (photovoltaic) -biogas-gas-electricity system, and the user-side load characteristics and typical daily cooling, heating and the electricity power load scheduling characteristics were analyzed. The annual energy supply data and important energy supply influencing factors of the PV-biogas system were studied, and an evaluation index system for the comprehensive energy system was built, and five factors: PV-biogas system operation status, economic benefits, energy supply quality, environmental benefits and energy efficiency were collaboratively considered, and the comprehensive performance of traditional energy supply system and PV-biogas-gas-electricity system were evaluated. The results show these as follows. Large industrial production enterprises with mainly thermal requirement, typical daily load peaks occur at 09:00—11:00 or 14:00—17:00, the PV-biogas-gas-electricity multi-energy system can meet the cooling, heating and electricity needs of industrial enterprises. The average penetration rate of PV system is less than 10% during nonforce majeure hours, and the proportion of gas storage capacity of the biogas system is higher than 50% during normal hours, and the system supply reliability is improved. The evaluation results of a typical case verify the feasibility and validity of the evaluation index system of PV-biogas-gas-electricity multi-energy system, and provide a reference for the comprehensive utilization and coordinated development of PV-biogas-gas-electricity multi-energy system for large industrial enterprises in the future. [ABSTRACT FROM AUTHOR]

Interest is growing in potable reuse in response to water scarcity and the desire for sustainable supplies. While potable reuse systems must control a variety of physical, chemical, and microbiological contaminants, human enteric viruses are particularly concerning and drive process performance objectives due to their often‐high occurrence in source waters, small size, potential resistance to treatment, and laborious methods to determine infectivity. This paper reviews the alignment of online monitoring practices with the mechanisms and time scales of the various barriers for enteric viruses. While there are numerous studies and reviews of individual barriers, no other review has been identified that covers operational monitoring of the entire potable reuse system. This paper also provides a critical assessment of the efficacy of current practices for operational and verification monitoring of the integrity of barriers to enteric viruses in potable reuse systems. The prevalence of human enteric viruses in wastewater and associated challenges of quantifying them through treatment are discussed within the risk management frameworks currently in use or under development for potable reuse systems. Monitoring approaches are then reviewed throughout the potable reuse water cycle. Current monitoring practices are compared with treatment process mechanisms and time scales, for the treatment barriers of biological wastewater treatment, membrane bioreactors, microfiltration/ultrafiltration, reverse osmosis, ultraviolet irradiation/advanced oxidation, ozonation, granular media/biologically active filtration, and chlorination. Monitoring and pathogen removal mechanisms are also reviewed for both environmental and engineered buffers. Implications are then discussed for future areas of research in potable reuse. [ABSTRACT FROM AUTHOR]

The rising severity and frequency of wildfires in recent years in the United States have raised numerous concerns regarding the improvement in wildfire emergency response management and decision-making systems, which require operational high temporal and spatial resolution monitoring capabilities. Satellites are one of the tools that can be used for wildfire monitoring. However, none of the currently available satellite systems provide both high temporal and spatial resolution. For example, GOES-17 geostationary satellite fire products have high temporal (1–5 min) but low spatial resolution (≥2 km), and VIIRS polar orbiter satellite fire products have low temporal (~12 h) but high spatial resolution (375 m). This work aims to leverage currently available satellite data sources, such as GOES and VIIRS, along with deep learning (DL) advances to achieve an operational high-resolution, both spatially and temporarily, wildfire monitoring tool. Specifically, this study considers the problem of increasing the spatial resolution of high temporal but low spatial resolution GOES-17 data products using low temporal but high spatial resolution VIIRS data products. The main idea is using an Autoencoder DL model to learn how to map GOES-17 geostationary low spatial resolution satellite images to VIIRS polar orbiter high spatial resolution satellite images. In this context, several loss functions and DL architectures are implemented and tested to predict both the fire area and the corresponding brightness temperature. These models are trained and tested on wildfire sites from 2019 to 2021 in the western U.S. The results indicate that DL models can improve the spatial resolution of GOES-17 images, leading to images that mimic the spatial resolution of VIIRS images. Combined with GOES-17 higher temporal resolution, the DL model can provide high-resolution near-real-time wildfire monitoring capability as well as semi-continuous wildfire progression maps. [ABSTRACT FROM AUTHOR]

The contamination of water used in post‐harvest handling and processing operations of fresh and frozen fruit, vegetables and herbs (ffFVHs) is a global concern. The most relevant microbial hazards associated with this water are: Listeria monocytogenes, Salmonella spp., human pathogenic Escherichia coli and enteric viruses, which have been linked to multiple outbreaks associated with ffFVHs in the European Union (EU). Contamination (i.e. the accumulation of microbiological hazards) of the process water during post‐harvest handling and processing operations is affected by several factors including: the type and contamination of the FVHs being processed, duration of the operation and transfer of microorganisms from the product to the water and vice versa, etc. For food business operators (FBOp), it is important to maintain the microbiological quality of the process water to assure the safety of ffFVHs. Good manufacturing practices (GMP) and good hygienic practices (GHP) related to a water management plan and the implementation of a water management system are critical to maintain the microbiological quality of the process water. Identified hygienic practices include technical maintenance of infrastructure, training of staff and cooling of post‐harvest process water. Intervention strategies (e.g. use of water disinfection treatments and water replenishment) have been suggested to maintain the microbiological quality of process water. Chlorine‐based disinfectants and peroxyacetic acid have been reported as common water disinfection treatments. However, given current practices in the EU, evidence of their efficacy under industrial conditions is only available for chlorine‐based disinfectants. The use of water disinfection treatments must be undertaken following an appropriate water management strategy including validation, operational monitoring and verification. During operational monitoring, real‐time information on process parameters related to the process and product, as well as the water and water disinfection treatment(s) are necessary. More specific guidance for FBOp on the validation, operational monitoring and verification is needed. [ABSTRACT FROM AUTHOR]

Abstract The contamination of water used in post‐harvest handling and processing operations of fresh and frozen fruit, vegetables and herbs (ffFVHs) is a global concern. The most relevant microbial hazards associated with this water are: Listeria monocytogenes, Salmonella spp., human pathogenic Escherichia coli and enteric viruses, which have been linked to multiple outbreaks associated with ffFVHs in the European Union (EU). Contamination (i.e. the accumulation of microbiological hazards) of the process water during post‐harvest handling and processing operations is affected by several factors including: the type and contamination of the FVHs being processed, duration of the operation and transfer of microorganisms from the product to the water and vice versa, etc. For food business operators (FBOp), it is important to maintain the microbiological quality of the process water to assure the safety of ffFVHs. Good manufacturing practices (GMP) and good hygienic practices (GHP) related to a water management plan and the implementation of a water management system are critical to maintain the microbiological quality of the process water. Identified hygienic practices include technical maintenance of infrastructure, training of staff and cooling of post‐harvest process water. Intervention strategies (e.g. use of water disinfection treatments and water replenishment) have been suggested to maintain the microbiological quality of process water. Chlorine‐based disinfectants and peroxyacetic acid have been reported as common water disinfection treatments. However, given current practices in the EU, evidence of their efficacy under industrial conditions is only available for chlorine‐based disinfectants. The use of water disinfection treatments must be undertaken following an appropriate water management strategy including validation, operational monitoring and verification. During operational monitoring, real‐time information on process parameters related to the process and product, as well as the water and water disinfection treatment(s) are necessary. More specific guidance for FBOp on the validation, operational monitoring and verification is needed.

Time series analysis is a method of key importance for systems of various hierarchies' economic security studies. This article's main goal is to develop an economic security rapid indicators system, introducing threshold values and utilizing indices with a one-month sampling period, and its approbation during Russia's economic security operational monitoring. In order to develop such a system, the authors accumulated economic security world experience including reliability, visibility and tree structure principles. The authors' monitoring system includes four spheres: real economy, social, monetary and foreign economic, each of which contains three indicators. In order to organize economic security monitoring, it is proposed to use the index method, which converts indicators into a dimensionless form with integral values in subsequent calculations. Based on integral indices values, the economic security generalized index is synthesized, which can be used to analyze a system's development trends. We present economic security normalized indicators and integral indices dynamics for the years 2020–2022, which show two crises dynamics. The first is due the COVID-19 pandemic, while the second is associated with economic sanctions against Russia, implemented in 2022. The proposed economic security operational monitoring indicators system can be used effectively in the government's practical tasks in order to ensure the required level of economic security. This is especially true for rapid diagnosis of crisis phenomena in countries and individual regions. [ABSTRACT FROM AUTHOR]

CONQUER is a pilot blast monitoring program that monitors, quantifies, and reports to military units the training-related blast overpressure exposure of their service members. Overpressure exposure data are collected using the BlackBox Biometrics (B3) Blast Gauge System (BGS, generation 7) sensors mounted on the body during training. To date, the CONQUER program has recorded 450,000 gauge triggers on monitored service members. The subset of data presented here has been collected from 202 service members undergoing training with explosive breaching charges, shoulder-fired weapons, artillery, mortars, and 0.50 caliber guns. Over 12,000 waveforms were recorded by the sensors worn by these subjects. A maximum peak overpressure of 90.3 kPa (13.1 psi) was recorded during shoulder-fired weapon training. The largest overpressure impulse (a measure of blast energy) was 82.0 kPa-ms (11.9 psi-ms) and it was recorded during explosive breaching with a large wall charge. Operators of 0.50 caliber machine guns have the lowest peak overpressure impulse (as low as 0.62 kPa-ms or 0.09 psi-ms) of the blast sources considered. The data provides information on the accumulation of blast overpressure on service members over an extended period of time. The cumulative peak overpressure, peak overpressure impulse, or timing between exposures is all available in the exposure data. [ABSTRACT FROM AUTHOR]

CONQUER is a pilot blast monitoring program that monitors, quantifies, and reports to military units the training-related blast overpressure exposure of their service members. Overpressure exposure data are collected using the BlackBox Biometrics (B3) Blast Gauge System (BGS, generation 7) sensors mounted on the body during training. To date, the CONQUER program has recorded 450,000 gauge triggers on monitored service members. The subset of data presented here has been collected from 202 service members undergoing training with explosive breaching charges, shoulder-fired weapons, artillery, mortars, and 0.50 caliber guns. Over 12,000 waveforms were recorded by the sensors worn by these subjects. A maximum peak overpressure of 90.3 kPa (13.1 psi) was recorded during shoulder-fired weapon training. The largest overpressure impulse (a measure of blast energy) was 82.0 kPa-ms (11.9 psi-ms) and it was recorded during explosive breaching with a large wall charge. Operators of 0.50 caliber machine guns have the lowest peak overpressure impulse (as low as 0.62 kPa-ms or 0.09 psi-ms) of the blast sources considered. The data provides information on the accumulation of blast overpressure on service members over an extended period of time. The cumulative peak overpressure, peak overpressure impulse, or timing between exposures is all available in the exposure data.

Ultrasonic sensors are one of the most common automatic monitoring methods in operational snow depth monitoring with reliable results. On the other hand, there is significant uncertainty when measuring small snow depths (<2 cm), thus it cannot provide binary snow presence (on/off) information. The use of webcams in monitoring snow cover has proven to be successful in recent studies and applications. In this study, we applied an adaptive thresholding technique on images from webcams to obtain reliable snow on/off information to complement the ultrasonic snow depth measurements. Camera and ultrasonic sensor data from two weather stations in Finland were studied. The webcam data was processed using FMIPROT (Finnish Meteorological Institute Image Processing Tool) software, operating in a cloud computing environment, which can generate near real-time data. Our results indicate that webcam-derived data can be successfully used for quality control or as auxiliary data to support operational ultrasonic sensor measurements and provide a cost-effective improvement to operational monitoring capabilities. Webcam monitoring is especially useful during the melting season when the snow depth is below 15 mm, with accuracy values between 72% and 94%. [ABSTRACT FROM AUTHOR]

Time series analysis is a method of key importance for systems of various hierarchies’ economic security studies. This article’s main goal is to develop an economic security rapid indicators system, introducing threshold values and utilizing indices with a one-month sampling period, and its approbation during Russia’s economic security operational monitoring. In order to develop such a system, the authors accumulated economic security world experience including reliability, visibility and tree structure principles. The authors’ monitoring system includes four spheres: real economy, social, monetary and foreign economic, each of which contains three indicators. In order to organize economic security monitoring, it is proposed to use the index method, which converts indicators into a dimensionless form with integral values in subsequent calculations. Based on integral indices values, the economic security generalized index is synthesized, which can be used to analyze a system’s development trends. We present economic security normalized indicators and integral indices dynamics for the years 2020–2022, which show two crises dynamics. The first is due the COVID-19 pandemic, while the second is associated with economic sanctions against Russia, implemented in 2022. The proposed economic security operational monitoring indicators system can be used effectively in the government’s practical tasks in order to ensure the required level of economic security. This is especially true for rapid diagnosis of crisis phenomena in countries and individual regions.

An innovative approach for the automation of operational monitoring activities in agricultural and forestry tasks is described and discussed in this article. This approach can be considered as a solution for Precision Agriculture and Precision Forestry applications and can be used as an information and communication technology (ICT) tool for the management aims by a variety of agricultural and forestry companies. The aim of the proposed concept is to develop a system, composed of both hardware and software units, with the ability to collect and manage operative raw data and then to translate them into operational information that will be used in decision-making processes. All the procedures will be carried out automatically, in order to ensure an objective compilation of the field activity register. Thus, the entrepreneur will have all the operative information automatically updated in a dedicated database system. All the obtained documents can then be used for certification and traceability processes, if required by the procedural guideline, as well as to satisfy any other management tasks, including the estimation of the actual operative costs of the farm.

The cryosphere web portal maintained by the Norwegian Meteorological Institute (MET Norway), https://cryo.met.no , provides access to the latest operational data and the current state of sea ice, snow, and permafrost in Norway, the Arctic, and the Antarctic. We present the latest addition to this portal: the operational permafrost monitoring at MET Norway and methods for visualising real-time permafrost temperature data. The latest permafrost temperatures are compared to the climatology generated from the station’s data record, including median, confidence intervals, extremes, and trends. There are additional operational weather stations with extended measurement programs at these locations. The collocated monitoring offers daily updated data for studying and monitoring the current state, trends, and the effects of, e.g. extreme climate events on permafrost temperatures. Ground temperature rates obtained from the long-term records in the warmer permafrost found in Norway are typically 0.1 ^∘ C–0.2 ^∘ C per decade. In contrast, in the colder permafrost of the High Arctic on Svalbard, a warming of up to 0.7 ^∘ C per decade is apparent. The operational monitoring provides information faster than ever before, potentially assisting in the early detection of, e.g. record high active layer thickness and pronounced permafrost temperature increases. It may also become an important cornerstone of early warning systems for natural hazards associated with permafrost warming and degradation. Currently, data are submitted manually to the international Global Terrestrial Network for Permafrost and are scheduled for integration with World Meteorological Organisation (WMO) operational services through the WMO Global Cryosphere Watch.

In recent years, the awareness of the problem of the performance gap and rebound effect extends the interest in assessing the real operation of buildings, in assessing how buildings match users' needs once they are occupied, and in understanding how occupants' behavior affects the actual building performance. The paper discusses the case study and presents the results of a monitoring campaign of 2 years of occupancy of a large social housing intervention recently built near Milan, for a total of 152 flats. Data about the thermal energy consumption for heating and cooling, the domestic hot and cold water use, and the occupants' intervention on controlling devices are assessed and presented. The case study is representative of the actual design and construction of high-performing multi-family buildings in Italy. All the buildings are class A rated, very highly insulated, and ventilated with centralized mechanical ventilation systems with thermodynamic heat recovery. Centralized water-to-water heat pumps supply hot and refrigerated water for heating and cooling and domestic hot water as well. A building monitoring system is installed, able to track energy and water consumption, factors influencing the energy consumption not related to the building characteristics (weather data, operational setting) as well as the overall building performance data. The results show unexpected high energy and water consumption and moreover a large variability of the energy and water consumption pattern among the dwellings and between the years due to the significant influence of the occupants' behavior and habits.

Abstract River ice breakup and resulting flood risk is a nearly annual concern for communities along the five major rivers draining to the James and Hudson Bay Coasts in Ontario (Moose, Albany, Attawapiskat, Winisk and Severn Rivers). Ice breakup within this region has historically been monitored using flight reconnaissance supplemented by assessment of hydrometric data. More recently, remote sensed imagery have been used to monitor near real-time ice breakup and flood risk. However, the near real-time remotely sensed breakup information was found to have limited utility in the absence of a broader spatial and temporal understanding of breakup progression. The primary purpose of this study was to develop a method for generating a dataset of breakup dates. A secondary objective was to calculate statistics from this dataset that can be used to provide context to operational near real-time imagery analysis and improve understanding of ice processes in the study area. An automated method for detecting river ice breakup dates from 2000 to 2017 using MODIS imagery was developed. This method uses a threshold-based technique that aims to maximize river coverage and minimize effects of cloud obstruction. Image processing was completed in the high-performance Google Earth Engine application which enabled iterative classification and model calibration. The breakup date dataset was used to calculate statistics on breakup timing, duration, annual variability and breakup order. An assessment of patterns within these data is discussed, relationships between breakup timing, duration and highwater years is explored and the operational utility of these statistics is described. The classification compared well with Water Survey of Canada derived breakup dates with mean bias ranging from −2.0 days to 6.7 days and mean absolute error of 3.4 days to 6.9 days across the rivers. Latitude and distance upstream were found to be primary controls on breakup timing with drainage network configuration and reach morphology also having an influence. No relationships between highwater years and calculated breakup statistics were found. It is recommended that future studies use the dataset developed in this study in combination with hydrometric and remotely sensed data to improve prediction of highwater and understanding of breakup processes within these rivers. Highlights • Derive ice breakup dates from MODIS leveraging the rapid processing of GEE • Calculate range of breakup dates, duration, annual variability and sequence • Latitudinal and downstream breakup trends are observed with notable exceptions. • Demonstrate utility of results for informing operational flood monitoring [ABSTRACT FROM AUTHOR]

The primary goal of operational volcano monitoring is the timely identification of volcanic unrest. This provides critical information to decision makers tasked with mitigating the societal impacts of volcanic eruptions. Volcano deformation is recognized as a key indicator of unrest at many active volcanoes and can be used to provide insight into the depth and geometry of the magma source. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique that has detected deformation at many volcanoes globally, but most often with hindsight. To date, the use of InSAR for operational volcano monitoring has been limited to a few cases and only in high income countries. Yet a vast number of active volcanoes are located in low- and middle-income countries (LMICs), where resources for operational monitoring are constrained. In these countries, InSAR could provide deformation monitoring at many active volcanoes, including those that have no existing ground monitoring infrastructure. Several barriers combine to make uptake of InSAR into operational volcano monitoring difficult in most countries, but particularly in resource-constrained environments. To overcome some of these limiting factors, we propose a simplified processing chain to better incorporate InSAR and Global Navigation Satellite Systems (GNSS) data into the decision-making process at volcano observatories. To combine the InSAR and GNSS data we use a joint modelling procedure that infers volume changes of a spherical source beneath the volcano. The benefits of our approach for operational use include that the algorithm is computationally lightweight and can be run quickly on a standard desktop or laptop PC. This enables a volcano observatory to interpret geodetic data in a timely fashion, and use the information as part of frequent reporting procedures. To demonstrate our approach we combine ALOS-PALSAR InSAR data and continuous GNSS data from the Rabaul Caldera, Papua New Guinea between 2007 and 2011. Joint inversion of the two datasets indicates volume loss of ~1 × 107 m3 (deflation) occurring between February 2008 and November 2009, followed by volume gain of ~2.5 × 106 m3 (inflation) until February 2011 in a magma body situated ~1.5 km beneath the caldera.

Copyright of Journal of Engineering for Thermal Energy & Power / Reneng Dongli Gongcheng is the property of Journal of Engineering for Thermal Energy & Power and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article proposes a Rayleigh’s quotient–based damage detection algorithm. It aims at efficiently revealing nascent structural changes on a given structure with the capability to differentiate between an actual damage and a change in operational conditions. The first three damage detection levels are targeted: existence, location, and severity. The proposed algorithm is analytically developed from the dynamics theory and the virtual energy principle. Some computational techniques are proposed for carrying out computations, including discretization, integration, derivation, and suitable optimization methods. Field implementation strategies are also considered for the purpose of online damage monitoring. In order to prove the efficiency of this strategy, one experimental and three numerical case studies were conducted. The proposed algorithm successfully detected the damage in all simulated cases and estimated the damage severity with acceptable accuracy. The conclusion is that the proposed algorithm was able to efficiently detect damage appearance in a range of structures for various damage levels and locations, and under different operational conditions. [ABSTRACT FROM AUTHOR]

Detecting and monitoring the spatial distribution, configuration and propagation rates of aquatic water weeds (i.e. water hyacinth ) in freshwater ecosystems, is arguably important to water resources managers, hydrologists and policy makers, for sustainable water resources management and planning purposes. The principal objective of this work was to develop a model that can satisfactorily detect and map the spatial distribution and configuration of water hyacinth ( Eichhornia crassipes ) in freshwater ecosystems, using both visible, near-infrared and thermal band information derived from the Landsat 8 multispectral sensor. Statistical analysis was done, using two machine learning classification ensembles, which are the Discriminant Analysis (DA) and Partial Least Squares Discriminant Analysis (PLS-DA). Our results have shown that the spatial distribution and configuration of water hyacinth can be accurately detected and mapped with an overall classification accuracy of 95% using Landsat 8 data. The results have further shown that the different growing stages (i.e. young, intermediate and old water hyacinth) could be spectrally detected and mapped, using the new Landsat 8 sensor. In addition, the findings of this study have demonstrated that Landsat 8 bands 5, 6, 7, 8, 10 and 11 are the most influential in detecting and mapping water hyacinth in freshwater ecosystems. Furthermore, allocation of agreement results showed that the DA classification algorithm outperformed PLS-DA in the detection and mapping the distribution and spatial configuration of water hyacinth in freshwater ecosystems. Overall, the derived water hyacinth maps provide critical information required for the development of effective and robust water hyacinth control and eradication programmes. [ABSTRACT FROM AUTHOR]

Forest damage and health problems can be identified, mapped, and better managed through the analysis of satellite imagery. However, a high degree of efficiency is achieved only if a workflow for preprocessing and analysis is mature enough for production and can be deployed in an operational processing environment. This letter shows a path for turning research into an operational tool for the purposes of forest delineation and disturbance monitoring using high-resolution RapidEye satellite imagery. The implemented workflow follows a modularized approach with separate modules for image registration, radiometric normalization, classification, and bitemporal analysis. The tool was developed for commercial service provision. It has successfully been deployed for the fourth year for German state forest customers. It makes use of python and python libraries, as well as algorithms of PCI Geomatica. The letter concludes with a case study showing the defoliation monitoring results of a Scots pine plantation area affected by a nun moth outbreak. [ABSTRACT FROM PUBLISHER]

A system for multiple camera networks is proposed for continuous monitoring of ecosystems by processing image time series. The system is built around the Finnish Meteorological Image PROcessing Toolbox (FMIPROT), which includes data acquisition, processing and visualization from multiple camera networks. The toolbox has a user-friendly graphical user interface (GUI) for which only minimal computer knowledge and skills are required to use it. Images from camera networks are acquired and handled automatically according to the common communication protocols, e.g., File Transfer Protocol (FTP). Processing features include GUI based selection of the region of interest (ROI), automatic analysis chain, extraction of ROI based indices such as the green fraction index (GF), red fraction index (RF), blue fraction index (BF), green-red vegetation index (GRVI), and green excess (GEI) index, as well as a custom index defined by a user-provided mathematical formula. Analysis results are visualized on interactive plots both on the GUI and hypertext markup language (HTML) reports. The users can implement their own developed algorithms to extract information from digital image series for any purpose. The toolbox can also be run in non-GUI mode, which allows running series of analyses in servers unattended and scheduled. The system is demonstrated using an environmental camera network in Finland.

Despite the predominant role played by Internet in the distribution of doping substances, little is currently known about the online offer of doping products. Therefore, the study focuses on the detection of doping substances and suppliers discussed in Internet forums. It aims at having a comprehensive understanding of products and sellers to lead an operational monitoring of the online doping market. Thirteen community forums on the Internet were investigated and one million topics were extracted with source code scrappers. Then, a semantic analysis was conducted with a semi-automatic process to classify the relevant words according to doping matters. Additionally, the ranking of doping products, active substances and suppliers in regards to the number of contributors to the forums were established and analyzed over time. Finally, promotion methods of suppliers were evaluated. The results show that anabolic androgenic steroids, used to enhance body image and performance, are the most discussed type of products. A temporal analysis illustrates the stability of the most popular products as well as the emergence of new products such as peptides (e.g. CJC-1295). 327 suppliers were detected, mostly with dedicated websites or direct sales by e-mail as selling methods. Globally, the implemented methodology shows its ability to detect products and suppliers as well as to follow their temporal trends. The intelligence will serve the definition of online monitoring strategies (e.g. the selection of appropriate keywords). Additionally, it also allows the adjustment of customs inspection strategies and anti-doping analysis by monitoring the popular and emerging substances. [ABSTRACT FROM AUTHOR]

Growing interest on business collaboration motivates today’s industries, especially small and medium enterprises (SMEs) to establish and manage dynamic and non-hierarchical business networks to respond to market opportunities with added business benefits. This business environment requires concurrent work and real-time information sharing between key business partners in order to design and develop customised products. The use of traditional communication media such as e-mail, phone and fax is not satisfactory to get real-time information and is time-consuming and most often ineffective. In such environments, an Information and Communication Technology (ICT)/Web-based technology supports real-time information sharing among networked SMEs for the collaborative design and manufacturing of customised products. This study proposes an innovative ICT platform supporting SMEs collaboration, through Web and the Internet of Things technologies, which follows the Net-Challenge conceptual approach and methodological guidelines for SMEs to form and operate virtual organisations for the collaborative development and delivery of customised products. The ICT Platform was assessed in three different industry domains, namely the textile and apparel, the footwear and the machine tools, respectively. This ICT solution promotes collaboration, with substantial advantages for SMEs including the reduction of costs and delivery time and improvement of the innovation potential. [ABSTRACT FROM AUTHOR]

Predation on native vertebrates and livestock by the European Red Fox ( Vulpes vulpes) remains a significant problem in many parts of Australia. Coordinated approaches to fox control are most effective in protecting these assets and involve placement of baits across the landscape by private and public land managers. However, participation in such programmes varies seasonally and the spatial coverage of baiting is often difficult to determine. Here, we describe a geographic information systems-based system that assists land managers to collect and use spatial information, minimizing gaps in bait coverage and maximizing bait encounters by foxes to increase the effectiveness of pest control. The coordination of data collection and reporting between land managers should facilitate more effective adaptive management by allowing better strategic planning and increasing landholder involvement, which should, in turn, improve the programme's efficacy, provided other critical conditions and resources are met. [ABSTRACT FROM AUTHOR]

The evolution of oil pollution in the Gulf of Mexico from April 20 to May 28, 2010, which resulted from the accident on the BP Deepwater Horizon oil platform that occurred on April 20, 2010, is reviewed. The development of the situation was traced on the basis of a joint analysis of optical and radar images (RIs), which proved to be very effective since the optical images made it possible to exclude the areas of calm on the RIs from consideration, and the RIs gave more complete information about dimensions of the areas covered with oil films indiscernible on optical images. It is shown that the mesoscale water dynamics is of prime importance in oil pollution transport in the gulf; therefore, almost all model predictions of a giant oil spill drift were not justified. [ABSTRACT FROM AUTHOR]

Demand for thermal water in the Mura-Zala basin, situated between Slovenia, Austria, Hungary and Croatia, is constantly increasing, with the sandy geothermal aquifer within the Neogene Mura formation being the most exploited. During the water concession granting process various problems were identified, together with the need for elaboration of the uniform concession granting principles. The latter were devised according to the specific hydrogeological settings and field inspection of 23 geothermal wells, performed through use of an adapted methodology. The inspection revealed changes in wells performance, low efficiency of energy abstraction and a lack of reinjection. The acquired information was applied to the development of particular principles, including the six key indicators. Firstly, a unified and integrated operational monitoring programme must be established, and upgraded by a national surveillance monitoring. Secondly, an application of the best available techniques is proposed. Stimulation of energetic and balneology efficiency is also needed, with recharge and reinjection conditions evaluated and applied where possible. Limited or full water concessions could be granted based on their fulfilment then. This continuous step-by-step approach should enable the implementation of adequate measures to meet the standards required for the thermal groundwater bodies according to the EU water framework directions. [ABSTRACT FROM AUTHOR]

The use of a monitoring system, designed to monitor the condition of hydroelectric plants from the vibrational, mechanical and magnetic characteristics under different operating conditions, is considered. The results of a comparative analysis of similar and different types of plants, obtained using the 'ALMAZ-7010-GÉS' steady monitoring and diagnostics system and new sensors developed by the 'DIAMECH 2000' Company, are presented. [ABSTRACT FROM AUTHOR]

Abstract: Volcanic eruptions produce ash clouds, which are a major hazard to population centers and the aviation community. Within the North Pacific (NOPAC) region, there have been numerous volcanic ash clouds that have reached aviation routes. Others have closed airports and traveled for thousands of kilometers. Being able to detect these ash clouds and then provide an assessment of their potential movement is essential for hazard assessment and mitigation. Remote sensing satellite data, through the reverse absorption or split window method, is used to detect these volcanic ash clouds, with a negative signal produced from spectrally semi-transparent ash clouds. Single channel satellite is used to detect the early eruption spectrally opaque ash clouds. Volcanic Ash Transport and Dispersion (VATD) models are used to provide a forecast of the ash clouds'' future location. The Alaska Volcano Observatory (AVO) remote sensing ash detection system automatically analyzes satellite data of volcanic ash clouds, detecting new ash clouds and also providing alerts, both email and text, to those with AVO. However, there are also non-volcanic related features across the NOPAC region that can produce a negative signal. These can complicate alerts and warning of impending ash clouds. Discussions and examples are shown of these non-volcanic features and some analysis is provided on how these features can be discriminated from volcanic ash clouds. Finally, there is discussion on how information of the ash cloud such as location, particle size and concentrations, could be used as VATD model initialization. These model forecasts could then provide an improved assessment of the clouds'' future movement. [Copyright &y& Elsevier]

A set of guidelines are presented for the definition of monitoring plans in coastal and transitional (estuarine and lagoonal) systems subject to the European Union Water Framework Directive – WFD (2000/60/EC). General principles of best practice in monitoring are outlined, including (a) the definition of three types of broad management objectives: water quality, conservation, and human use, to which the general public may easily relate. These will define the core and research indicators (WFD quality elements) to be used for monitoring; (b) priorities and optimisation in a (financially and logistically) resource-constrained environment; (c) quality assurance; and (d) assessment of monitoring success: this should focus on the outputs, i.e. the internal audit of the monitoring activity, and on the outcomes. The latter component assesses programme effectiveness, i.e. environmental success based on a set of clearly-defined targets, and informs management action. The second part of this work discusses the approach and actions to be carried out for implementing WFD surveillance, operational and investigative monitoring. Appropriate spatial and temporal scales for surveillance monitoring of different indicators are suggested, and operational monitoring is classified into either screening or verification procedures, with an emphasis on the relationship between drivers, pressure, state and response. WFD investigative monitoring is interpreted as applied research, and thus guidelines cannot be prescriptive, except insofar as to provide examples of currently acceptable approaches. Specific case studies are presented for both operational (coastal eutrophication control) and investigative monitoring (harmful algal blooms), in order to illustrate the practical application of these monitoring guidelines. Further information is available at . [ABSTRACT FROM AUTHOR]

Untreated stormwater discharge has been found to have major impacts on urban watercourses. Despite the acknowledgement of the importance of adopting broader-scale approaches to managing stormwater, there is limited information describing the subwatershed benefits of implementing numerous best management practices (BMPs). Operational monitoring of stormwater management facilities (SWMFs) and streams in three subwatersheds undergoing urbanization was undertaken over a five-year period to measure potential changes in suspended solids concentrations, hydrology and temperature. SWMFs at construction sites had elevated total suspended solids (TSS) discharges relative to facilities in stable catchments, but reduced TSS discharges in comparison to uncontrolled construction sites. The discharge from single facilities was found to have the potential to increase downstream watercourse TSS concentrations in headwater areas, but increases were often not detectable further downstream. TSS discharges from SWMFs in stable catchments were similar to published ranges, and were a useful tool to identify facilities that were not functioning as designed. Based upon the current subwatershed imperviousness levels, water quality impacts from cumulative SWMF discharges appear to be less likely to be significant than some other factors, such as the changes in the subwatershed hydrological response. No increase in peakflow or duration of midbankfull flow for the 25-mm and 2-year storm event and no trend in baseflow or water temperature were detectable over the study period, despite the increase in imperviousness due to watershed urbanization. The findings from this operational monitoring study suggest that implementation of BMPs may help to mitigate urban impacts at the subwatershed level. [ABSTRACT FROM AUTHOR]

Intermittent drinking water supply affects the health of over 300 million people globally. In Mozambique, it is largely practiced in cities and small towns. This results in frequent microbial contamination of the supplied drinking water posing a health risk to consumers. In Moamba, a small town in Southern Mozambique with 2,500 water connections, the impact of changes in operational strategies, namely increased chlorine dosage, increased supply duration and first-flush, on the microbial water quality was studied to determine best practices. To that aim, water quality monitoring was enhanced to provide sufficient data on the microbial contamination from 452 samples under the different strategies. The water at the outlet of the water treatment plant during all strategies was free of E. coli complying to the national standards. However, E. coli could be detected at household level. By increasing the chlorine dosage, the number of samples that showed E. coli absence increased at the two sampling locations in the distribution network: in Cimento from 72% to 83% and in Matadouro from 52% to 86%. Modifying the number and duration of supply cycles showed a different impact on the water quality at both locations in the distribution network. A positive effect was shown in Cimento, where the mean concentrations decreased slightly from 0.54 to 0.23 CFU/100 mL and 16.7 to 7.3 CFU/100 mL for E. coli and total coliforms respectively. The percentage of samples positive for bacteria was, however, similar. In contrast, a negative effect was shown in Matadouro where the percentage of positive samples increased and the mean bacterial concentrations increased slightly: E. coli from 0.9 to 1.5 CFU/100 mL and total coliforms 17.6 to 23.0 CFU/100 mL. Enhanced water quality monitoring improved operational strategies safeguarding the microbial water quality. The E. coli contamination of the drinking water at household level could point at recontamination in the distribution or unsafe hygienic practices at household level. Presence of faecal contamination at household level indicates potential presence of pathogens posing a health risk to consumers. Increasing chlorine dosage ensured good microbiological drinking water quality but changing the number of supply cycles had no such effect. [ABSTRACT FROM AUTHOR]