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The exposure conditions experienced by copper-coated high-level nuclear waste containers in a deep geologic repository will evolve with time. An early exposure period involving the gamma irradiation of aerated humid vapor could lead to the formation of nitric acid condensed in limited volumes of water on the container surface. The evolution of the corrosion processes under these conditions have been studied using pH measurements in limited volumes of water containing various concentrations of nitric acid. The extent and morphology of corrosion was examined using scanning electron microscopy on surfaces and on focused ion beam cut cross sections. The composition of corrosion products was determined by energy dispersive x-ray analyses and Raman spectroscopy. In the absence of dissolved oxygen only minor corrosion was observed with the reduction of nitric acid inhibited by the formation of either chemisorbed nitrate and nitrite species or the formation of a thin cuprite (Cu2O) layer. When the solution was aerated, both oxygen and nitric acid acted as cathodic reagents. After extensive exposure periods corrosion was stifled by the formation of corrosion product deposits of Cu2O, CuO (tenorite), and Cu2NO3(OH)3 (rouaite).

Garbage classification is more and more significant recent years. In order to promote the implementation of garbage classification and the improvement of intellectualization of urban sanitation work, a new type of intelligent garbage bin system is designed, which includes the bottom control part, android app and IOT cloud platform. Firstly, the system controls the inlets of intelligent garbage bin through interaction with android app, which realizes the function of ordinary garbage can. On top of that, the bottom control part collects all kinds of data of garbage bin by using some external sensors. And then the data will be reported to Android and Android will report that to cloud platform. Cloud platform server then transmits data to monitoring platform, which facilitates data statistics and the removing of garbage. By deploying the system, garbage classification can be promoted and the status of garbage can be effectively monitored, which will significantly improve garbage recovery efficiency and sanitation work level.

Microbiologically influenced corrosion (MIC) is one of a number of threats to the long-term integrity of nuclear waste containers. As such, the potential for, and extent of, MIC must be assessed and suitable models developed for predicting the long-term behavior of the container. There are two broad approaches to assessing the threat posed by MIC; first, to determine whether the environment will support microbial activity and, if so, where and when it will occur, and second, to estimate the maximum amount of damage that could occur if microbial activity in the repository is possible. A decision-tree approach is used to present evidence for both of these approaches and to decide whether MIC is a significant threat to the integrity of the container. Examples are provided from various international nuclear waste management programs. It is concluded that microbial effects will not compromise the safety of the overall disposal system because they will not lead to either early container failures or to a large number of simultaneous failures, both factors that can lead to an increase in the peak dose.

One of the major challenges faced not just by India but globally as well is waste management. India is the second most populous country and naturally generates tonnes of garbage daily. It is common to find dustbins overflowing with junk scattered everywhere, not to mention that segregation of waste is conveniently neglected. Many-a-times it is observed that despite providing separate bins for dry and wet trash, the convention is carelessly ignored. With the traditional methods of periodic garbage collection and manual segregation of wet, metallic, non-recyclable, and recyclable waste proving to be inefficient, there is a need for a better solution. With the help of IoT, a more effective solution is proposed to improve the current system and take a step forward toward the vision of smart cities. The proposed system uses smart garbage tracking, segregation, and collection systems, interfaced with ultrasonic sensors, rainfall/moisture sensors, inductive proximity sensors, and servo motors, along with the necessary hardware, with Arduino as the main controlling unit. The Arduino platform is used as a software platform for the working of the model and obtaining the expected results.

The purpose of this study is to identify the effect of high-tech bins on people's interest in disposing trash. The method used in this study is a quantitative descriptive method and literature study to analyses community perceptions of smart trash bin. The results of this study state that the mind-set of the community in disposing trash increased after the existence of smart trash bin project. These results were obtained because the community became more interested in disposing trash in the presence of unique designs and diverse functions of these high-tech bins. This study concluded that smart trash bin can increase people's interest in disposing garbage in its place.

Nowadays certain actions are taken to improve the level of cleanliness in the country. People are getting more active in doing all the things possible to clean their surroundings. Various movements are also started by the government to increase cleanliness. We will try to build a system which will notify the corporations to empty the bin on time. In this system, we will put a sensor on top of the garbage bin which will detect the total level of garbage inside it according to the total size of the bin. When the garbage will reach the maximum level, a notification will be sent to the corporation's office, then the employees can take further actions to empty the bin. This system will help in cleaning the city in a better way. By using this system people do not have to check all the systems manually but they will get a notification when the bin will get filled.

Although pharmaceuticals treat illnesses and prevent diseases in humans and animals, ironically, they are now among the emerging pollutants in the environment. As individuals continue to consume medicines, households can become a primary source of pharmaceutical pollutants. This paper explains relevant Malaysian law and policy on the issue. Using a questionnaire survey, it also assesses public perception concerning the environmental impact of pharmaceutical waste and the current methods of disposal that are practiced in Selangor. The survey used a convenience sampling and the data collected were analysed using statistical descriptive analysis. Most of the participants were aware that pharmaceutical waste can have an adverse impact on the environment and public health. Half of the participants disposed of their pharmaceutical waste in trash bins. About 2.9% of the respondents poured their household pharmaceutical waste (HPW) directly down the drain, while 8.8% poured them down the sink in the kitchen or toilet. The study also discovered that while 73.8% of the respondents felt that HPW should be separated from other household solid waste, only 25.2% returned their medicinal waste through the medicine return-back programme. The majority of the respondents (82.5%) agreed that information concerning the proper disposal of HPW is insufficient. The study concludes that while the respondents were aware of the adverse impact of HPW, their practices to ensure proper disposal is discouraging. There is a need for effective unwanted medicines return-back programme as a more prudent disposal method of HPW to avoid any risk to the environment or human health.

Collaborative modelling of the Internet of Things (IoT) with Artificial Intelligence (AI) has merged into the Intelligence of Things concept. This recent trend enables sensors to track required parameters and store accumulated data in cloud storage, which can be further utilized by AI based predictive models for automatic decision making. In a smart and sustainable environment, effective waste management is a concern. Poor regulation of waste in surrounding areas leads to rapid spread of contagious disease risks. Traditional waste object management requires more working staff, increases effort, consumes time and is relatively ineffective. In this research, an Intelligence of Things Enabled Smart Waste Management (IoT-SWM) model with predictive capabilities is developed. Here, local sinks (LS) are deployed in specified locations. At every instant, the current status of smart bins in each LS is notified to users to determine the priority level of LS to be emptied. Based on aggregated sensor values for the three smart bins, LS weight and poison gas value, the priority order of emptying LS is computed, and decision is made whether to notify the users with an alert message or not. It also helps in predicting the LS, which is likely to be filled up at a faster rate based on assigned timestamp. This model is implemented in real time with many LS and it was observed that bins, which were close to more crowded sites filled up faster compared to sparse populated areas. Random forest algorithm was used to predict whether an alert notification is to be sent or not. An average mean of 95.8% accuracy was noted while using 60 decision trees in random forest algorithm. The average mean execution latency recorded for training and testing sets is 13.06 sec and 14.39 sec respectively. Observed accuracy rate, precision, recall and f1-score parameters were 95.8%, 96.5%, 98.5% and 97.2% respectively. Model buildup and the validation time computed were 3.26 sec and 4.25 sec respectively. It is also noted that at a threshold value of 0.93 in LS level, the maximum accuracy rate reached was 95.8%. Thus, based on the prediction of random forest approach, a decision to notify the users is taken. Obtained outcome indicates that the waste level can be efficiently determined, and the overflow of dustbins can be easily checked in time

Since the beginning of their activities in 2015, the muography group of the Institute for Research on the Fundamental Laws of the Universe (IRFU-CEA-France) has been continuously evolving their muon telescopes (based on micromegas detectors) as well as their analysis methods. This allowed the performance of different experiments, going from civil engineering to archaeology, including the nuclear domain. It is on this last topic that activities have been more focused in the last years. Among them, the surveillance of nuclear reactors before its dismantling or the characterisation of nuclear waste containers stand up. A summary of IRFU’s muography activities related to nuclear domain is presented here. This includes the characterisation of a nuclear reactor before its dismantling, for which a validation of the inner structure with respect to the existing models has been done as well as the first 3D muon tomography ever made for such a big object.

Human populations are using oceans as their household dustbins, and microplastic is one of the components which are not only polluting shorelines but also freshwater bodies globally. Microplastics are generally referred to particles with a size lower than 5 mm. These microplastics are tiny plastic granules and used as scrubbers in cosmetics, hand cleansers, air-blasting. These contaminants are omnipresent within almost all marine environments at present. The durability of plastics makes it highly resistant to degradation and through indiscriminate disposal they enter in the aquatic environment. Today, it is an issue of increasing scientific concern because these microparticles due to their small size are easily accessible to a wide range of aquatic organisms and ultimately transferred along food web. The chronic biological effects in marine organisms results due to accumulation of microplastics in their cells and tissues. The potential hazardous effects on humans by alternate ingestion of microparticles can cause alteration in chromosomes which lead to infertility, obesity, and cancer. Because of the recent threat of microplastics to marine biota as well as on human health, it is important to control excessive use of plastic additives and to introduce certain legislations and policies to regulate the sources of plastic litter. By setup various plastic recycling process or promoting plastic awareness programmes through different social and information media, we will be able to clean our sea dustbin in future.