Decentralized energy optimization using blockchain with battery storage and electric vehicle networks.

The research is aimed at filling the gap regarding the development of long-lasting, secure technologies that help build decentralized systems. Other consensus models, such as the Proof of Work (PoW), prevailing in cryptocurrencies, are known to be expensive in terms of energy, hence the development of enlightened models like Proof of Lightweight Hash, whereby while developing the model, an emphasis is placed on energy efficiency without compromising on security. At the same time, new technologies such as battery storage and electric vehicles are disrupting consumer habits where renewable energy is favored, and a decentralized energy market is promoted.

Machine learning boosts wind turbine efficiency with smart failure detection and strategic placement.

The research study objective seeks to improve the efficiency of wind turbines using state-of-the-art techniques in the domain of ML, making wind energy the key player in fashioning a favorable future. Wind Turbine Health Monitoring (WTHM) is typically achieved through either vibration analysis or by using Supervisory Control and Data Acquisition (SCADA) data of wind turbines, wherein conventional fault pattern identification is a time-consuming, guesswork process. This work proposed an intelligent automated approach to early fault detection through the implementation of the HARO (Huber Adam Regression Optimizer) model, which combines Transformer networks with Lasso Regression and the Adam optimizer.

Enhanced human activity recognition in medical emergencies using a hybrid deep CNN and bi-directional LSTM model with wearable sensors.

Human activity recognition (HAR) is one of the most important segments of technology advancement in applications of smart devices, healthcare systems & fitness. HAR uses details from wearable sensors that capture the way human beings move or engage with their surrounding. Several researchers have thus presented different ways of modeling human motion, and some have been as follows: Many researchers have presented different methods of modeling human movements.

Validation of crAssphage microbial source tracking markers and comparison with Bacteroidales markers for detection and quantification of faecal contaminations in surface water.

Human-specific faecal contamination has been affecting surface water and is a threat to both the environment and public health due to its potential co-occurrence with pathogens. Extended studies were conducted to detect and quantify faecal contamination using microbial source tracking (MST) markers targeting bacteria and viruses. The prototypical crAssphage, a presumed Bacteroides-infecting phage discovered in 2014, showed superior specificity to human faeces and high abundance in untreated sewage water.

Estimating best nanomaterial for energy harvesting through reinforcement learning DQN coupled with fuzzy PROMETHEE under road-based conditions.

Energy harvesters based on nanomaterials are getting more and more popular, but on their way to commercial availability, some crucial issues still need to be solved. The objective of the study is to select an appropriate nanomaterial. Using features of the Reinforcement Deep Q-Network (DQN) in conjunction with Fuzzy PROMETHEE, the proposed model, we present in this work a hybrid fuzzy approach to selecting appropriate materials for a vehicle-environmental-hazardous substance (EHS) combination that operates in roadways and under traffic conditions.

AHP VIKOR framework for selecting wind turbine materials with a focus on corrosion and efficiency.

The research objective in the context of the study relates to the major concern of corrosion affecting the wind turbines in operation to find materials with high durability in relation to environmental conditions of operation, strength, and cost. A method is an integration of the Analytical Hierarchy Process (AHP) and VIKOR Multi-Criteria Decision Making (MCDM) techniques that will assess seven different material options on sixteen criteria that comprise corrosion resistance, mechanical properties, cost, and a negative environmental impact. From this result, the AHP method calculated the weights for the indicators and chose potential materials, and finally, the VIKOR method used these materials and compared and ranked them to obtain a compromise solution.

Mixotrophic aerobic denitrification facilitated by denitrifying bacterial-fungal communities assisted with iron in micro-polluted water: Performance, metabolic activity, functional genes abundance, and community co-occurrence.

Low-dosage nitrate pollutants can contribute to eutrophication in surface water bodies, such as lakes and reservoirs. This study employed assembled denitrifying bacterial-fungal communities as bio-denitrifiers, in combination with zero-valent iron (ZVI), to treat micro-polluted water. Immobilized bacterial-fungal mixed communities (IBFMC) reactors demonstrated their ability to reduce nitrate and organic carbon by over 43.

Algicidal activity synchronized with nitrogen removal by actinomycetes: Algicidal mechanism, stress response of algal cells, denitrification performance, and indigenous bacterial community co-occurrence.

The harmful algal blooms (HABs) can damage the ecological equilibrium of aquatic ecosystems and threaten human health. The bio-degradation of algal by algicidal bacteria is an environmentally friendly and economical approach to control HABs. This study applied an aerobic denitrification synchronization algicidal strain Streptomyces sp.

Modelling and Analysis of Hybrid Transformation for Lossless Big Medical Image Compression.

Due to rapidly developing technology and new research innovations, privacy and data preservation are paramount, especially in the healthcare industry. At the same time, the storage of large volumes of data in medical records should be minimized. Recently, several types of research on lossless medically significant data compression and various steganography methods have been conducted.

Diabetic Retinopathy and Diabetic Macular Edema Detection Using Ensemble Based Convolutional Neural Networks.

Diabetic retinopathy (DR) and diabetic macular edema (DME) are forms of eye illness caused by diabetes that affects the blood vessels in the eyes, with the ground occupied by lesions of varied extent determining the disease burden. This is among the most common cause of visual impairment in the working population. Various factors have been discovered to play an important role in a person's growth of this condition.

Multi-Layered Non-Local Bayes Model for Lung Cancer Early Diagnosis Prediction with the Internet of Medical Things.

The Internet of Things (IoT) has been influential in predicting major diseases in current practice. The deep learning (DL) technique is vital in monitoring and controlling the functioning of the healthcare system and ensuring an effective decision-making process. In this study, we aimed to develop a framework implementing the IoT and DL to identify lung cancer.

The prolyl dipeptidyl peptidase cleaves the N-terminal peptide of the immunoprotein CXCL-10.

Dipeptidyl peptidases constitute a class of non-classical serine proteases that regulate an array of biological functions, making them pharmacologically attractive enzymes. With this work, we identified and characterized a dipeptidyl peptidase from (MtDPP) displaying a strong preference for proline residues at the P substrate position and an unexpectedly high thermal stability. MtDPP was also characterized with alanine replacements of residues of its active site that yielded, for the most part, loss of catalysis.

Diversity and abundance of antibiotic resistance genes and their relationship with nutrients and land use of the inflow rivers of Taihu Lake.

Taihu Lake is the third largest freshwater lake in China and an important source for drinking water, flood protection, aquaculture, agriculture, and other activities. This lake is connected to many principal and small rivers with inflow from west and outflow on the eastern side of the lake and these inflow rivers are believed to significantly contribute to the water pollution of the lake. This study was aimed at assessing the diversity and abundance of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs), and their relationship with water quality parameters and land use patterns.

Stagnation trigger changes to tap water quality in winter season: Novel insights into bacterial community activity and composition.

The drinking water distribution system is important for water supply and it affects the quality of the drinking water. Indoor pipeline water quality is regulated by physical, hydraulic and biological elements, such as indoor temperature and stagnation. In this work, the effects of indoor heating and overnight stagnation on the variation in bacterial community structure and the total cell count were assessed by full-length 16S rRNA gene sequencing and flow cytometry, respectively.

The effect of habitat restoration on macroinvertebrate communities in Shaoxi rivers, China.

In recent decades, the biodiversity of freshwater environments has decreased sharply due to anthropogenic disturbances that damaged ecosystem structures and functions. Habitat restoration has emerged as an important method to mitigate the degradation of river ecosystems. Although in many cases a post-project monitoring has been promoted to access the restoration progress, it is still unclear how aquatic community changes following river habitat restoration in China.

Microbially induced calcite precipitation performance of multiple landfill indigenous bacteria compared to a commercially available bacteria in porous media.

Microbially Induced Carbonate Precipitation (MICP) is currently viewed as one of the potential prominent processes for field applications towards the prevention of soil erosion, healing cracks in bricks, and groundwater contamination. Typically, the bacteria involved in MICP manipulate their environment leading to calcite precipitation with an enzyme such as urease, causing calcite crystals to form on the surface of grains forming cementation bonds between particles that help in reducing soil permeability and increase overall compressive strength. In this paper, the main focus is to study the MICP performance of three indigenous landfill bacteria against a well-known commercially bought MICP bacteria (Bacillus megaterium) using sand columns.

Simultaneous measurement of aqueous redox-sensitive elements and their species across the soil-water interface.

The redox-sensitive elements, such as iron, manganese, sulfur, phosphorus, and arsenic, shift their speciation every millimeter (mm) across the soil-water interface in the flooded soil environments. Monitoring of element speciation at this high-resolution (HR) within the SWI is still difficult. The key challenge lies in obtaining sufficient porewater samples at specific locations along the soil gradient for downstream analysis.

Combined effects of seasonality and stagnation on tap water quality: Changes in chemical parameters, metabolic activity and co-existence in bacterial community.

In drinking water distribution pipeline systems, the tap water quality is regulated by several biotic and abiotic factors, which can threaten the health of consumers. Stagnation is inevitable in the water distribution pipeline however, the combined effects of seasonal changes and stagnation on tap water quality are not well understood. Here, we investigated the seasonal variations in the chemical and biological quality of water after overnight stagnation for a period of one year.

Arsenic behavior across soil-water interfaces in paddy soils: Coupling, decoupling and speciation.

The sharp redox gradient at soil-water interfaces (SWI) plays a key role in controlling arsenic (As) translocation and transformation in paddy soils. When Eh drops, As is released to porewater from solid iron (Fe) and manganese (Mn) minerals and reduced to arsenite. However, the coupling or decoupling processes operating within the redox gradient at the SWI in flooded paddy soils remain poorly constrained due to the lack of direct evidence.

Evaluating ecosystem functioning following river restoration: the role of hydromorphology, bacteria, and macroinvertebrates.

Ecological restoration of freshwater ecosystems is now being implemented to mitigate anthropogenic disruption. Most emphasis is placed on assessing physico-chemical and hydromorphological properties to monitor restoration progress. However, less is known about the structural integrity and ecosystem health of aquatic ecosystems.

Impact of Temperature, Nutrients and Heavy Metals on Bacterial Diversity and Ecosystem Functioning Studied by Freshwater Microcosms and High-Throughput DNA Sequencing.

Microbial communities are fundamental components in freshwater, and community shifts in ecosystem structure are indicative of changing environmental conditions. This study aimed at investigating the influence of key environmental parameters on bacterial diversity and ecosystem functioning (i.e.

Mixed-culture aerobic anoxygenic photosynthetic bacterial consortia reduce nitrate: Core species dynamics, co-interactions and assessment in raw water of reservoirs.

Three consortia of mixed-culture Aerobic Anoxygenic Photosynthetic Bacteria (AAPB) with excellent aerobic denitrifying ability were isolated from drinking water source reservoirs. The results showed that the removal of dissolved organic carbon (DOC) and nitrate nitrogen (NO-N) by mixed-culture AAPB were higher than 90% and 99%, respectively. The Illumina MiSeq sequencing of pufM gene revealed that the dominant genera and their relative abundance changed over the culture periods.

Disentangling the drivers of Microcystis decomposition: Metabolic profile and co-occurrence of bacterial community.

In aquatic ecosystems, water microbial communities can trigger the outbreak or decline of cyanobacterial blooms. However, the microbiological drivers of Microcystis decomposition in reservoirs remain unclear. Here, we explored the bacterial community metabolic profile and co-occurrence dynamics during Microcystis decomposition.