Adsorptive sequestration of noxious uranium (VI) from water resources: A comprehensive review

Groundwater is usually utilized as a drinking water asset everywhere. Therefore, groundwater defilement by poisonous radioactive metals such as uranium (VI) is a major concern due to the increase in nuclear power plants as well as their by-products which are released into the watercourses. Waste Uranium (VI) can be regarded as a by-product of the enrichment method used to produce atomic energy, and the hazard associated with this is due to the uranium radioactivity causing toxicity. To manage these confronts, there are so many techniques that have been introduced but among those adsorptions is recognized as a straightforward, successful, and monetary innovation, which has gotten major interest nowadays, despite specific drawbacks regarding operational as well as functional applications. This review summarizes the various adsorbents such as Bio-adsorbent/green materials, metal oxide-based adsorbent, polymer based adsorbent, graphene oxide based adsorbent, and magnetic nanomaterials and discuss their synthesis methods. Furthermore, this paper emphasis on adsorption process by various adsorbents or modified forms under different physicochemical conditions. In addition to this adsorption mechanism of uranium (VI) onto different adsorbent is studied in this article. Finally, from the literature reviewed conclusion have been drawn and also proposed few future research suggestions.

Hybridization of long short-term memory with Sparrow Search Optimization model for water quality index prediction

Water quality (WQ) analysis is a critical stage in water resource management and should be handled immediately in order to control pollutants that could have a negative influence on the ecosystem. The dramatic increase in population, the use of fertilizers and pesticides, and the industrial revolution have resulted in severe effects on the WQ environment. As a result, the prediction of WQ greatly helped to monitor water pollution. Accurate prediction of WQ is the foundation of managing water environments and is of high importance for protecting water environment. WQ data presents in the form of multi-variate time-sequence dataset. It is clear that the accuracy of predicting WQ will be enhanced when the multi-variate relation and time sequence dataset of WQ are fully utilized. This article presents the Water Quality Prediction utilising Sparrow Search Optimization with Hybrid Long Short-Term Memory (WQP-SSHLSTM) model. The presented WQP-SSHLSTM model intends to examine the data and classify WQ into distinct classes. To achieve this, the presented WQP-SSHLSTM model undergoes data scaling process to scale the input data into uniform format. Followed by, a hybrid long short-term memory-deep belief network (LSTM-DBN) technique is employed for the recognition and classification of WQ. Moreover, Sparrow search optimization algorithm (SSOA) is utilized as a hyperparameter optimizer of the proposed DBN-LSTM model. For demonstrating the enhanced outcomes of the presented WQP-SSHLSTM model, a sequence of experiments has been performed and the outcomes are reviewed under distinct prospects. The WQP-SSHLSTM model has achieved 99.84 percent accuracy, which is the maximum attainable. The simulation outcomes ensured the enhanced outcomes of the WQP-SSHLSTM model on recent methods.

Effects of long-term exercise training on physiological signals and personality traits in women in law enforcement

Law enforcement teams across the globe experience the highest occupational stress and stress-related diseases. Physical exercise and an active lifestyle are recommended as part of their profession to equip them to fight stress and related health adversities. The research is carried out using objective measures of Heart Rate Variability (HRV), Electro Dermal Activity (EDA), Heart Rate Recovery (HRR), and subjective questionnaires. HRV was generated with an electrocardiogram (ECG) signal acquired using NI myRIO 1900 interfaced with the Vernier EKG sensor. HRR was acquired with the help of a Polar chest strap exercise heart rate monitor and EDA acquisition was carried out with Mindfield E-Sense electrodes. Then statistical features are extracted from the collected data, and feed to the AQCNN (Aquila convolution neural network) classifier to predict the stress. Signal analyses were done in Kubios 4.0, Ledalab V3.x in a MATLAB environment. The results pointed out that exercise training is effective in increasing the vagal tone of the Autonomic Nervous System (ANS) and hence improves the recovery potential of the cardiovascular system from stress. The proposed AQCNN method improves the accuracy of 95.12% which is 93.13%, 85.36% and 80.13% better than MANOVA technique, CNN and ML-SVM respectively. The findings have the potential to influence decision-making in the selection and training of recruits in high-stress positions, hence optimizing the cost and time of training by identifying maladaptive recruits early.

Biodegradation of P-nitro phenol using a novel bacterium Achromobacter denitrifacians isolated from industrial effluent water

In the present investigation, Achromobacter denitrifacians was isolated from industrial wastewater and used in the degradation of para nitro-phenol. Experiments were made as a function of different carbon sources, organic and inorganic nitrogen sources and metal ions to analyse the removal efficiency of para nitro-phenol present in the industrial wastewater sources. Observations revealed that the rate of phenol biodegradation was significantly affected by pH, temperature of incubation, glucose, peptone and metal ion concentration. The optimal conditions for phenol removal were found to be pH of 7.5, temperature, 35 °C and 0.25 gL^-1 supplemented glucose level, 0.25 gL^-1 supplemented peptone level, and 0.01 gL^-1 zinc ion. The key importance of the present study is the utilization of a native bacterial strain isolated from the industrial effluent water itself having an impending role in the bioremediation process of phenol.

Evaluation Strategies for Wireless Ultra Wideband Communication Towards Orthopedic Surgical Scheme

Wireless medical devices shall considerably improve the proficiency and effectiveness in medical segments. Recent wireless inventions enable reduced design, thus becomes inexpensive for manufacturing. Huge quantity of individual information is measured and communicated in wireless manner, consequently safety precautions are needed to be integrated with these wireless technologies. The evaluation strategies for Wireless Ultra Wideband communication towards orthopedic surgical scheme has been explained in this paper. Every devices considered in this paper are identical with each others towards their elementary objective. However, they vary towards different real-world applications. The devices enumerated in this paper have shared operating frequency bands of 2.4 GHz ISM Band and UWB frequency ranging from 3.1 GHz to 10.6 GHz. Every devices entailed here is positioned to fit within the operating frequencies either at 2.4 GHz or 3.1 GHz to 10.6 GHz. This paper targets on protective patient-privacy which is deemed to be energetic characteristics towards isolated patient monitoring schemes. Considering the rise in quantity of feasible wireless medicinal products, this paper targets in the engagement of different wireless standards and measured data on the basis of dissimilar rates. Thus, the foremost significant in this work is towards supplementing the quantity of integration in wireless medical monitoring schemes. Similarly, as the applications of implantable and ingestible wireless medical approaches are becoming increased, they offer easy accessing towards data collecting and data which are previously dreadful, and this has been considered as a vital parameter in this paper. Hence, there becomes bigger possibility towards improving exactness of wireless positioning arrangements. When complications of the system increase, the prevailing protocols shall not be appropriate for superior and satisfactory bandwidth pertaining real-time application, thereby few protocols have been worked out to encounter this issue. Therefore, the major contributions in this paper include advanced speediness, superior data rate designs and effective protocols. In this paper, all the structures entailed have the potential to assist doctors for improving the dominance in lives of patients, thus application development is properly discussed for progressing with these implements.