Linglong Chu, Wenli Zheng, Xiaoxiang Zhao et al.

Research Square • 2023

Abstract Ionic liquids (ILs) are widely used “green solvent” as they have a low vapor pressure and can replace volatile solvents in industry. However, ILs are difficult to biodegrade and are potentially harmful to the environment. This study, herein, investigated the toxicity of three imidazole ILs ([C 8 MIM]Cl, [C 8 MIM]Br, and [C 8 DMIM]Br) towards soil microorganisms. The results showed that the ILs inhibited the growth of soil culturable microorganisms (fungi, bacteria, and actinomycetes) and affected the activity of soil enzyme. In addition, microbial community species and abundance in soil were altered, with significant differences between the control and experimental groups. Alpha diversity analysis showed that the community abundance tended to increase and then decrease with increasing ILs concentrations. The decrease in species abundance implied that the soil microbial system was less resilient to disturbance. Finally, functional prediction analysis revealed that ILs mainly affected the carbohydrate metabolism and amino acid metabolic processes of the microorganisms. ILs with single methyl substituent had a more pronounced effect than those with double methyl substituents. This study contributes to a better understanding of the environmental safety and ecological risks of ILs.

Kabaivanova L

Open Access Journal of Microbiology & Biotechnology • 2024

Anaerobic digestion (AD) is a process driven by microbes that supports renewable energy production, together with waste utilization. The role of microorganisms is undisputable as they are involved in the subsequent processes of hydrolysis, acidogenesis, acetogenesis, and methanogenesis. Microbial communities vary in wide ranges, depending on the type of substrates used and the conditions provided. Anaerobic systems are addressed, operating under mesophilic and thermophilic conditions for the biodegradation of agricultural wastes for biogas/biomethane production. AD comprises successive degradation pathways and syntrophic microbial consortia activities. Identifying the microbial content in digesters could help attaining new information on the digester performance. Archaeal and bacterial associations have to be determined as their important role to be elucidated. Molecular-biological methods of metagenomics are applied to identify the residing mixed cultures therein. Methanogens have been attained to the domain Archaea. Bacterial and archaeal populations, specific for each stage are differentiated in thermophilic or mesophilic conditions as temperature plays a crucial role in AD process, especially for hydrolysis and methanogenesis and determines microorganisms’ variety.

Siew Herng Chan, Muhammad Hafiz Ismail, Chuan Hao Tan et al.

Research Square • 2021

Abstract Background Bacterial communities are responsible for biological nutrient removal and flocculation in engineered systems such as activated floccular sludge. Predators such as bacteriophage and protozoa exert significant predation pressure and cause bacterial mortality within these communities. However, the roles of bacteriophage and protozoan predation in impacting granulation process remain limited. Recent studies hypothesised that protozoa, particularly sessile ciliates, could have an important role in granulation as these ciliates were often observed in high abundance on surfaces of granules. Bacteriophages were hypothesized to contribute to granular stability through bacteriophage-mediated extracellular DNA release by lysing bacterial cells. This current study investigated the bacteriophage and protozoan communities throughout the granulation process. In addition, the importance of protozoan predation during granulation was also determined through chemical killing of protozoa in the floccular sludge. Results Four independent bioreactors seeded with activated floccular sludge were operated for aerobic granulation for 11 weeks. Changes in the phage, protozoa and bacterial communities were characterized throughout the granulation process. The filamentous phage, Inoviridae, increased in abundance at the initiation phase of granulation. However, the abundance shifted towards lytic phages during the maturation phase. In contrast, the abundance and diversity of protozoa decreased initially, possibly due to the reduction in settling time and subsequent washout. Upon the formation of granules, ciliated protozoa from the class Oligohymenophorea were the dominant group of protozoa based on metacommunity analysis. These protozoa had a strong, positive-correlation with the initial formation of compact aggregates prior to granule development. Furthermore, chemical inhibition of these ciliates in the floccular sludge delayed the initiation of granule formation. Analysis of the bacterial communities in the thiram treated sludge demonstrated that the recovery of ‘ Candidatus Accmulibacter’ was positively correlated with the formation of compact aggregates and granules. Conclusion Predation by bacteriophage and protozoa were positively correlated with the formation of aerobic granules. Increases in Inoviridae abundance suggested that filamentous phages may promote the structural formation of granules. Initiation of granules formation was delayed due to an absence of protozoa after chemical treatment. The presence of Candidatus Accumulibacter was necessary for the formation of granules in the absence of protozoa.

Advance in Environmental Waste Management & Recycling • 2022

The demand for an alternative source of energy and challenge of increase in wastes pollution initiates the need for renewable energy and management of waste using anaerobic digestion (AD). Anaerobic digestion is an effective and efficient method of waste treatment and energy generation. The study focused on investigating the physicochemical parameters and microbial community in anaerobic digestion of organic wastes and was conducted using chicken wastes and food wastes as organic substrate under semi-continuous conditions at hydraulic retention time (HRT) of forty-two (42) days in fifteen liter (15L) fabricated digesters labeled D1, D2 and D3 at 37OC. The pH, volatile fatty acid (VFA), moisture content (MC), total ammonia, total solid, volatile solid, alkalinity was assessed before and after digestion while the microbial community diversity was analyzed using 16S rRNA amplicon-based nextgeneration sequencing (NGS). The results indicated a pH value of 6.65 ± 0.12, 7.27 ± 0.13, 6.43 ± 0.27, volatile fatty acid of 72.17 ± 1.42, 58.35 ± 2.58, 40.56 ± 0.38 and moisture content of 98.9 ± 2.65, 92.3 ± 1.81, 96.4 ± 3.60 at day 42 for D1 (Chicken waste and food wastes), D2 (Chicken wastes+), D3 (control) respectively. A collective biogas yield of 686±17.00 kpa for D1, 700±11.00kpa for D2 and 521±21.00 kpa for D3 were recorded. The characterization of biogas analyzed with nondispersive infrared (NDIR) gas analyzer (gas board 3100p) revealed a percentage methane content of 46.11±1.11, 52.4±1.05, 50.31±1.33 for D1, D2 and D3 respectively. The microbial community identified phylum Bacteroidetes, Firmicutes, proteobacteria, Tenericutes, Verrucomicrobia, Actinobacteria, Euryarchaeota among others. The study shows that physicochemical properties and microbial community diversity are useful tools to indicate digester performance and also to enhance anaerobic digestion process.

Claire Gibson, Shameem Jauffur, Bing Guo et al.

bioRxiv (Cold Spring Harbor Laboratory) • 2023

Abstract Wastewater treatment plants (WWTPs) are host to diverse microbial communities and receive a constant influx of microbes from influent wastewater, however the impact of immigrants on the structure and activities of the activated sludge (AS) microbial community remains unclear. To gain insight on this phenomenon known as perpetual community coalescence, the current study utilised controlled manipulative experiments that decoupled the influent wastewater composition from the microbial populations to reveal the fundamental mechanisms involved in immigration between sewers and AS-WWTP. The immigration dynamics of heterotrophs were analysed by harvesting wastewater biomass solids from 3 different sewer systems and adding to synthetic wastewater. Immigrating influent populations were observed to contribute up to 25 % of the sequencing reads in the AS. By modelling the net growth rate of taxa, it was revealed that immigrants primarily exhibited low or negative net growth rates. By developing a protocol to reproducibly grow AS-WWTP communities in the lab, we have laid down the foundational principals for the testing of operational factors creating community variations with low noise and appropriate replication. Understanding the processes that drive microbial community diversity and assembly is a key question in microbial ecology. In the future, this knowledge can be used to manipulate the structure of microbial communities and improve system performance in WWTPs. Importance In biological wastewater treatment processes, the microbial community composition is essential in the performance and stability of the system. To allow future process optimisation to meet new treatment goals, we need a better understanding of factors influencing the microbial community assembly in WWTPs. This study developed a reproducible protocol to investigates the impact of influent immigration (or perpetual coalescence of the sewer and activated sludge communities) with appropriate reproducibility and controls. We demonstrate herein that influent immigration contributed up to 25 % of the sequencing reads in the activated sludge under the studied conditions, highlighting the need to consider this process in future WWTP modelling and design.

Xiaoliang Zhang

2024 6th International Conference on Energy, Power and Grid (ICEPG) • 2024

Off-grid wind and solar hydrogen technology are large-scale development of renewable energy and achieve low-carbon operation. This article studies the evaluation of the economy of systems using the lowest economic indicator of penalty costs for wind and solar curtailment. Finally, reinforcement learning algorithms are used to solve the optimal optimisation model of systems. The calculation example shows that the proposed optimisation strategy can greatly reduce wind and light waste and improve the overall economic of the system.

Mohamed Mosaad, Fahd Banakhr

Research Square • 2021

Abstract Solar photovoltaic (PV) energy has met great attention in the electrical power generation field for its many advantages in both on and off-grid applications. The requirement for higher proficiency from the PV system to reap the energy requires maximum power point tracking techniques (MPPT). This paper presents an adaptive MPPT of a stand-alone PV system using an updated PI controller optimized by harmony search (HS). A lockup table is formed for the temperature and irradiance with the corresponding voltage at MPP (V MPP ). This voltage is considered as the updated reference voltage required for MPP at each temperature and irradiance. The difference between this updated reference voltage at MPP and the variable PV voltage due to changing the environmental conditions is used to stimulate PI controller optimized by HS to update the duty cycle (D) of the DC-DC converter. Another lockup table is formed with the temperature, irradiance and the corresponding duty cycle at MPP to convert this MPP technique into an adaptive one. An experimental implementation of the proposed adaptive MPPT is introduced to test the validity of the simulation results obtained at different irradiance and temperature levels.

Adugnaw Lake Temesgen, Getachew Bekele

Research Square • 2025

Abstract Mini-grids (MGs) have emerged as an economically viable alternative to communities in remote areas with low population density or with geographical constraints. However, identifying optimal locations where investments can lead to long-term and sustainable MG development remains a significant challenge due to the complex interplay of technical, social, and economic factors. This study addresses this challenge by identifying economically feasible renewable MG sites in Ethiopia. The study employs the Open-Source Spatial Electrification Tool (OnSSET) to integrate critical factors such as resource availability, population density, land cover, terrain slope, and proximity to existing infrastructure. These factors are used based on equal weight criteria, under two grid proximity scenarios (2.5 km and 25 km from existing medium-voltage (MV) grid lines). The Levelized Cost of Electricity (LCOE) for the selected sites is calculated to assess economic feasibility. The results show that hydro MGs, with LCOE values ranging from 0.088–0.16 $/kWh, are the most cost competitive option. Under the 2.5 km and 25 km grid proximity scenarios, 306 and 84 potential mini-hydro sites are identified as capable of electrifying approximately 5 and 1.9 million people, respectively. Solar PV MGs exhibit significant potential and LCOE values ranging 0.15–0.22 $/kWh. Solar MGs could electrify 7.2 million people under the 2.5 km scenario and 3.2 million people under the 25 km scenario. Wind MG, with LCOE values ranging from 0.12–1.75 $/kWh, could provide electricity to 4.8 million people under the 2.5 km scenario and 3.1 million under the 25 km scenario. The study provides a roadmap to compare different suitable locations at the prefeasibility stage for MG deployment, guiding policymakers and investors in prioritizing MG deployment for sustainable rural electrification.

Najib Altawell

Advanced Materials Research • 2012

Various types of DG technologies, their viability and other important aspects, such as the economical and performance side have been examined in this paper. The main aim and objective of this workis to find the most suitable off-grid system for rural electrification, i.e. in the form of technical feasibility, acceptable purchasing/installation and maintenance cost, as well asreliability. The selected system should be able to provide continuous electricity supply, particularly in areas where main grid connection is not a viable option. The result from this work has concluded that hybrid renewable energy systems are the best approach in solving some of the problems related to electricity shortage in the countryside. Hybrid systemsconstruction means that sustainable energy and environmental protection will be part of the overall commercial and non-commercial applications for off-grid electricity supply

Magnus de Witt

• 2024

Fossil fuels are the most common energy source for electricity generation among remote Arctic communities. Around 80% of remote Arctic communities are predominantly dependent on fossil fuels. Even if some of the region's raw oil is extracted, the processed diesel must be imported. Transport is complicated and strongly dependent on weather conditions. The harsh Arctic weather conditions make fuel transportation is complex, risky, and costly, leading to an insecure primary energy supply and high fuel prices. For many inhabitants of remote Arctic communities, the high energy costs are a significant cost burden because unemployment, temporary jobs, and a resulting low income are common issues.This presentation will focus on implementation strategies for renewable energy sources into the energy mix or remote Arctic communities, with the aim of lowering the energy cost burden. System dynamics (SD) was used as a methodology to analyze the implementation process. SD is a powerful tool to analyse complex systems with non-linear relationships, as it is expected to find them among the policy strategies for energy transition. Investing in renewable energy technology is a high-risk investment; therefore, the effects of such an investment must be well studied to gain an optimal result. Furthermore, remote communities are often facing financial issues, which limits investments in energy infrastructure. Therefore, the model is looking for affordable ways of investing in energy infrastructure. The model aims for a sustainable performance of the utility provider, whereas the electricity cost for the consumer can be lowered and the utility provider can perform well on a non-profit base.The research indicates that renewables have a significant cost-saving potential. Despite all the positive effects, investment in renewables can be risky and a substantial commitment for small communities. Moreover, depending on the type of renewable energy source, there can be some environmental impact that must be considered as well. With a well-structured integration process, the most can be made out of the investment, which helps lower the energy cost burden even more.

Benard Nsaku

Journal of Developing Country Studies • 2023

Purpose: The purpose of the study is to examine the effects of Multinational Companies involvement in developing nations.
 Methodology: This study adopted a desktop methodology. This study used secondary data from which include review of existing literature from already published studies and reports that was easily accessed through online journals and libraries.
 Findings: The study concluded that the critical roles played by MNCs include providing employment, contributing to community development projects, and providing industrial training to youth. Other roles include providing local markets, providing emergency assistance to disaster survivors, environmental protection, staff development and contributing to the tax base.
 Unique Contribution to Theory, Practice and Policy: The study was anchored on legitimacy and stakeholder’s theory. The study recommends that multinational companies should ensure they have in the board of directors, a member who is originally from the host country. The study also recommends that there should be more incorporation of the community and other stakeholders in future MNC activities to avoid conflicts.

Wakanyi Hoffman

The Humanitarian Leader • 2021


 
 
 In the international humanitarian landscape, crisis interventions are deployed based on a long-standing working culture that presupposes that local authorities are usually overwhelmed during a crisis and unable to mobilise local capacity. Thus, external human resource mobilisation is necessary. However, this may only be true in various instances, such as natural disasters, where rapid response is needed to extinguish further harm to human life. In most cases, there are no mechanisms to make prior assessments that can inform decision-makers about the kind of international assistance needed in the local context.
 This is because existing data for the availability of resources is produced mainly by international aid agencies and their governing political institutions. This database of knowledge, which leans heavily on a post-colonial Anglocentric viewpoint about ‘best practices’, is used as the baseline to assess the ability of potential partners to mobilise their resources, while failing to include the capacity of local agents to determine what capacity exists in a particular context, what they are already capable of delivering and how best to support their response system (United Nations International Strategy for Disaster Reduction [UNISDR] 2008).
 However, as access to digital communication devices and other globally useful technology in resource-constrained rural settings continues to emerge, this may soon change. This paper explores the ways in which Indigenous and local knowledge should contribute to the exploration of intelligent and sustainable solutions that are well-suited within the local context to mitigate and understand humanitarian crises before, during and after they occur, and how to curate, analyse and use local data and knowledge systems to create innovations that are sustainable and adaptive to the priorities of the local population.
 
 

G. Genest

Glocalism • 2015

Why have states, in a somewhat short period of time (1995-2005), suddenly decided to “cooperate” regarding global infectious disease surveillance? What kind of “cooperation” is it? Why did states apparently surrender part of their sovereign power to the WHO by giving it the power to declare pandemic at the global scale without state consent? These questions appear especially relevant in the context where issues of health and diseases at the global scale have been explicitly linked with the concepts of “risk”, “security”, “emergency”, “crisis”, “intelligence”, and “terrorism”. The objective of this article is to start answering these questions by first of all looking at the problems and paradoxes of the practices of Global Health Security through an analysis of the microbial space, capitalistic cooperation, and the production of information and data about health security. Secondly, the article draws the attention to the politics behind the structuration of Global Health Security as a social evidence by looking at contested concepts that represent promising research avenues.

M. Mohammadian, A. D. Moghaddam, L. Almasi et al.

• 2021

Functional emergency food rations with health-promoting attributes can improve the performance of armed forces during military missions, especially if there would not be enough time for food consumption. Therefore, the aim of this study was to produce emergency rations enriched with functional ingredients including whey protein nanofibril (WPN) and its complexes with curcumin (C-WPN) and quercetin (Q-WPN) as bioactive antioxidant compounds. After the formulation and production of the rations, their antioxidant activity, sensory properties, and microbial attributes were investigated. Addition of curcumin and quercetin to rations significantly improved their antioxidant activity as investigated by free radical scavenging method and reducing power assay. In all these methods, rations had higher antioxidant activity in the presence of curcumin and quercetin. The microbial and sensory properties of rations also were acceptable. Therefore, the results of this study suggested that the curcumin and quercetin as biologically active ingredients can be used in the formulation of emergency food rations for increasing their antioxidant activity which is very useful for improving the performance of armed forces and soldiers during military missions and activities.

Mia Tedjosaputro, Anastasia Maurina

Research Square • 2025

Abstract This paper seeks to optimise a system of immediate relief shelters which are quick to deploy, easily assembled by unskilled workers and utilise locally sourced and sustainable materials. It addresses concerns such as time-consuming tent delivery as the first response during emergencies and cost-effectiveness and exploits the self-erecting affordances of tensegrity structures. The research adopts a multi-phase methodology, an iterative multicriteria simulation and prototyping optimisation. The three stages are: (1) computational simulation followed by multi-objective optimisation, (2) full-scale prototyping, and (3) a second round of multi-objective optimisation informed by prototype evaluations. The discussions around the self-build bamboo tensegrity sleeping structures are focused only on the compression and tensional elements (without skin or façade, which will be the focus of a subsequent study). Five design parameters are investigated: the number of bamboo struts, overall height, degree of rotation, and radius of the top and bottom sections. By optimising these parameters, three performance criteria are considered to evaluate spatial needs and portability: the possible number of occupants, the total weight, and the length of each bamboo strut. The study finds that after optimisation, these shelters are best suited to occupancy rates of one to five people, however, three people are required to erect the structures and carry longer bamboo culms so this must be factored into any potential deployment scenario.

Ruth Nyakerario, Naho Mirumachi,

• 2022

This report examines the need to consider conflict sensitivity when planning and carrying out renewable energy projects in energy-scarce areas, such as refugee camps. The report uses a case study from Kenya's Kakuma Refugee Camp to look at the potential for renewable energy projects to lead to conflict or to exacerbate existing tensions. The authors argue that the issue should receive greater consideration in renewable energy project planning and implementation.

Nathalie Pettorelli

Satellite Remote Sensing and the Management of Natural Resources • 2019

This chapter seeks to provide a quick introduction to satellite remote sensing. It starts with a set of definitions, thereby to explain the differences between Earth observations, remote sensing, and satellite remote sensing. It then goes on to describe how satellite remote sensing works, and what the differences between passive and active sensors are. An introduction to the main sensors currently on board active civilian Earth observation satellites is provided, together with details on their key specifications. The complex nature of satellite data, as well as the tools required to manipulate and analyse them are discussed. The chapter ends with a presentation of the main issues to be aware of when dealing with satellite data, and a look at the coming sensors and datasets that will soon expand opportunities for satellite data to inform environmental management.

CONFERENCE PROCEEDING • 2024

The burgeoning demand for sustainable urban development necessitates innovative solutions in urban infrastructure, particularly in the realm of street lighting. This paper introduces a novel sensor-reduced smart street lighting system designed to optimize energy consumption while maintaining safety and comfort in urban environments. Unlike traditional systems that rely heavily on continuous sensor input, our proposed model utilizes a minimal sensor setup coupled with an intelligent algorithm that predicts lighting needs based on historical data and predictive analytics. This approach significantly reduces the system's complexity and cost, making sustainable technology more accessible to municipalities. Through a series of simulations and real-world trials, we demonstrate that our system can achieve up to a 40% reduction in energy usage compared to conventional sensor-based systems without compromising the illumination quality. This research not only highlights the potential of sensor-reduced technologies in urban lighting but also sets a precedent for future sustainable urban infrastructure projects.

.. S. T

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT • 2024

This project develops the purification of textile wastewater using microbial fuel cells (MFC), generating electricity as a byproduct. A NodeMCU module and current sensor setup are used to monitor current production. Through the use of microbial activity, the MFC system breaks down chemicals to produce electrical energy and harmless byproducts. The NodeMCU module makes wireless communication and real-time data capture possible, allowing for remote current output monitoring. IoT technology integration helps with environmental impact assessment and process management. This study presents an environmentally friendly technique for treating textile wastewater using MFC technology with the Internet of Things to produce electricity and purify the water effectively. Key Words: textile wastewater treatment, microbial fuel cell, smart monitoring system.

Munawwar A. Khan, Shams T. Khan

• 2020

Saudi Arabia has world's fifth largest desert and is the biggest importer of food and agricultural products. Understanding soil microbial communities is key to improving agricultural potential of the region. Therefore, soil microbial communities of semi-arid region of Abha known for agriculture and arid regions of Hafr Al-Batin and Muzahmiyah were studied using Illumina sequencing. Microbial community composition varied remarkably from other deserts and from one place to another. Highest diversity was found in rhizospheric soil of Muzahmiyah followed by Abha. Firmicutes, Proteobacteria and Actinobacteria were three main phyla detected in all the samples. Unlike other deserts, Bacteroidetes was not a major constituent and population of Firmicutes was quite high. Soils from agricultural region of Abha were significantly different from other samples in containing only 1 % Firmicutes and three to six times higher population of Actinobacteria and Bacteroidetes, respectively. Presence of photosynthetic bacteria, ammonia oxidizers, and nitrogen fixers along with bacteria capable of surviving on simple and unlikely carbon sources like DMF was indicative of their survival strategies under harsh environmental condition. Functional inference using PICRUSt show abundance of genes involved in photosynthesis and nitrogen fixation. Microbial communities show greater similarity with hot Namib desert than with cold Antarctic desert.

Xin Sun, Jacquelyn Folmar, Ariel Favier et al.

bioRxiv (Cold Spring Harbor Laboratory) • 2023

Abstract A central challenge in community ecology is predicting the effects of abiotic factors on community assembly. In particular, microbial communities play a central role in the ecosystem, but we do not understand how changing factors like temperature are going to affect community composition or function. One of the challenges is that we do not understand the mechanistic impacts of temperature on different metabolic strategies, nor how this metabolic plasticity could impact microbial interactions. Dissecting the contribution of environmental factors on microbial interactions in natural ecosystems is hindered by our understanding of microbial physiology and our ability to disentangle interactions from sequencing data. Studying the self-assembly of multiple communities in synthetic environments, here we are able to predict changes in microbial community composition based on metabolic responses of each functional group along a temperature gradient. This research highlights the importance of metabolic plasticity and metabolic trade-offs in predicting species interactions and community dynamics across abiotic gradients.

E. Stavropoulou, E. Bezirtzoglou

Foods • 2019

Microorganisms can contaminate food, thus causing food spoilage and health risks when the food is consumed. Foods are not sterile; they have a natural flora and a transient flora reflecting their environment. To ensure food is safe, we must destroy these microorganisms or prevent their growth. Recurring hazards due to lapses in the handling, processing, and distribution of foods cannot be solved by obsolete methods and inadequate proposals. They require positive approach and resolution through the pooling of accumulated knowledge. As the industrial domain evolves rapidly and we are faced with pressures to continually improve both products and processes, a considerable competitive advantage can be gained by the introduction of predictive modeling in the food industry. Research and development capital concerns of the industry have been preserved by investigating the plethora of factors able to react on the final product. The presence of microorganisms in foods is critical for the quality of the food. However, microbial behavior is closely related to the properties of food itself such as water activity, pH, storage conditions, temperature, and relative humidity. The effect of these factors together contributing to permitting growth of microorganisms in foods can be predicted by mathematical modeling issued from quantitative studies on microbial populations. The use of predictive models permits us to evaluate shifts in microbial numbers in foods from harvesting to production, thus having a permanent and objective evaluation of the involving parameters. In this vein, predictive microbiology is the study of the microbial behavior in relation to certain environmental conditions, which assure food quality and safety. Microbial responses are evaluated through developed mathematical models, which must be validated for the specific case. As a result, predictive microbiology modeling is a useful tool to be applied for quantitative risk assessment. Herein, we review the predictive models that have been adapted for improvement of the food industry chain through a built virtual prototype of the final product or a process reflecting real-world conditions. It is then expected that predictive models are, nowadays, a useful and valuable tool in research as well as in industrial food conservation processes.

Marko Kesti

Deep Learning Applications • 2021

Chapter deals with latest knowledge on deep reinforcement learning in the context of organizational management. Article presents reinforcement learning (RL) as a tool for the manager on the path to learning winning behavior in the complex environment of organization management. Organization management has wicked learning challenges because agents are under biases that prevent understanding the phenomenon of delayed reward. Therefore, the digital simulation with RL is effective forming breakthrough learning results. Human capital management theories provide architecture in creating organization digital twin where agent can practice management actions effect on business economics and staff wellbeing. Utilizing RL algorithms, it is possible to foster behavior for creating sustainable competitive advantage – this means the Nash equilibrium between profit and staff wellbeing. In this digital twin there is AI learning assistant as a teacher that provides demonstrations on how to act so that the delayed reward is good in the future. The article explains game theoretical approach that is the foundation for creating management deep learning AI system. Human agent at the organization is playing the game of Strategic Stochastic Bayesian Nonsymmetric Signaling game in co-operative or non-cooperative way and at zero-sum or general sum game mind-set.

Wenwen Li

• 2025

GeoAI, or geospatial artificial intelligence, has transformative potential for Earth science by integrating geospatial data with artificial intelligence to enhance environmental monitoring, predictive modeling, and decision-making. This commentary, based on the Greg Leptoukh Lecture at AGU 2024, explores the evolving role of GeoAI in addressing pressing challenges—from environmental change in the Arctic to disaster response in hurricane-prone tropical regions. It highlights advancements in GeoAI-driven analysis of multimodal Earth observation data, ranging from structured remote sensing imagery to semi-structured data and natural language texts. The integration of knowledge graphs and generative AI further strengthens GeoAI by enabling seamless integration of cross-domain data, semantic reasoning, and knowledge inference. By bridging informatics and domain expertise, GeoAI is shaping a more intelligent and actionable digital future for Earth science.

Hamed Taherdust

Artificial Intelligence Evolution • 2023

One of the most significant problems facing humankind now is environmental issues, which have harmed life on the planet. Research has been done continuously to lessen the effects of climate change on the local level and to manage its causes. Due to its indisputable rise in popularity, Artificial Intelligence (AI) will be used in a wide range of businesses and for several causes, such as environmental sustainability. Centers with significant ecological impacts may use AI's potential to alter the globe as the field expands. This article focuses on industries using AI applications for sustainable environmental development such as biodiversity, energy, water, transportation, air, agriculture, and resilience to extreme events. Next, some limitations are presented. To benefit both current and future generations, environmentally friendly AI should be developed.

Dilip Rijal, Vladislav Vasilyev, Feng Wang

ChemRxiv • 2024

Sustainable aviation fuels (SAFs) are crucial for addressing carbon emissions in the aviation industry. With a focus on SAFs, the research aims to establish a quantitative structure-property relationship for polycyclic hydrocarbons (PCHCs) and their net heat of combustion (NHOC) using the innovative approach of machine learning (ML). The model trained with support vector machine (SVM) algorithms in ML is selected as it demonstrates superior performance over other available algorithms with a high coefficient of determination (R2) and low mean absolute error (MAE) of 27.821 KJ/mol for 20% test data. Using the optimum SVM model, thirty-five potential PCHCs are identified as SAF candidates from C6 to C15 sourced from reputable scientific literature and databases. Furthermore, structural analysis revealed that high-performance PCHCs typically consist of saturated alkanes with multiple 3, 4, and 5-membered rings, suggesting that strained energy plays a role in their high energy density. The model obtained from ML can be employed to screen new hydrocarbons for their suitability as SAF candidates before costly experiments and ASTM evaluations.

Demetrius DiMucci, Mark Kon, Daniel Segrè

bioRxiv (Cold Spring Harbor Laboratory) • 2018

Abstract Microbes affect each other’s growth in multiple, often elusive ways. The ensuing interdependencies form complex networks, believed to influence taxonomic composition, as well as community-level functional properties and dynamics. Elucidation of these networks is often pursued by measuring pairwise interaction in co-culture experiments. However, combinatorial complexity precludes the exhaustive experimental analysis of pairwise interactions even for moderately sized microbial communities. Here, we use a machine-learning random forest approach to address this challenge. In particular, we show how partial knowledge of a microbial interaction network, combined with trait-level representations of individual microbial species, can provide accurate inference of missing edges in the network and putative mechanisms underlying interactions. We applied our algorithm to two case studies: an experimentally mapped network of interactions between auxotrophic E. coli strains, and a large in silico network of metabolic interdependencies between 100 human gut-associated bacteria. For this last case, 5% of the network is enough to predict the remaining 95% with 80% accuracy, and mechanistic hypotheses produced by the algorithm accurately reflect known metabolic exchanges. Our approach, broadly applicable to any microbial or other ecological network, can drive the discovery of new interactions and new molecular mechanisms, both for therapeutic interventions involving natural communities and for the rational design of synthetic consortia. Importance Different organisms in a microbial community may drastically affect each other’s growth phenotype, significantly affecting the community dynamics, with important implications for human and environmental health. Novel culturing methods and decreasing costs of sequencing will gradually enable high-throughput measurements of pairwise interactions in systematic co-culturing studies. However, a thorough characterization of all interactions that occur within a microbial community is greatly limited both by the combinatorial complexity of possible assortments, and by the limited biological insight that interaction measurements typically provide without laborious specific follow-ups. Here we show how a simple and flexible formal representation of microbial pairs can be used for classification of interactions with machine learning. The approach we propose predicts with high accuracy the outcome of yet to be performed experiments, and generates testable hypotheses about the mechanisms of specific interactions.

L. Wackett

Microbial Biotechnology • 2021

Poly‐ and perfluorinated chemicals, including perfluorinated alkyl substances (PFAS), are pervasive in today’s society, with a negative impact on human and ecosystem health continually emerging. These chemicals are now subject to strict government regulations, leading to costly environmental remediation efforts. Commercial polyfluorinated compounds have been called ‘forever chemicals’ due to their strong resistance to biological and chemical degradation. Environmental cleanup by bioremediation is not considered practical currently. Implementation of bioremediation will require uncovering and understanding the rare microbial successes in degrading these compounds. This review discusses the underlying reasons why microbial degradation of heavily fluorinated compounds is rare. Fluorinated and chlorinated compounds are very different with respect to chemistry and microbial physiology. Moreover, the end product of biodegradation, fluoride, is much more toxic than chloride. It is imperative to understand these limitations, and elucidate physiological mechanisms of defluorination, in order to better discover, study, and engineer bacteria that can efficiently degrade polyfluorinated compounds.

Foad Buazar, Javad Moavi, Mohammad Hosein Sayahi

Research Square • 2020

Abstract This research presents a novel biological route for the biosynthesis of nickel oxide nanoparticles (NiO NPs) using marine macroalgae extract as a reducing and coating agent under optimized synthesis conditions. XRD and TEM analyses revealed that phytosynthesized NiO NPs are crystalline in nature with a spherical shape having a mean particle size of 11±1 nm. It is found that biogenic NiO NPs is a highly efficient catalyst for benign one-pot preparation of pyridopyrimidine derivatives using aqueous reaction conditions. This environmentally friendly procedure takes considerable advantages of shorter reaction times, excellent product yields (up to 96%), magnetically reusable nanocatalyst (7 runs), low catalyst loadings, and free toxic chemical reagents.

Art Anthony Zoilo Munio, Alvanh Alem Pido, Leo Cristoba II Ambolode

Research Square • 2023

Abstract Due to mounting environmental and public health concerns about the toxicity of Arsenic (As) contamination, there is a strong drive to develop cost-effective sensors and adsorbent material for As. Using density functional theory, we examined the adsorption mechanism, electronic structure, and optical absorption spectra of SWCNT with atomic As and Arsenous acid (H3AsO3). Results indicate that atomic As can strongly interact with SWCNT with significant structural deformation of the SWCNT upon adsorption. This bonding creates modification on the intrinsic electronic structure and the optical absorption spectra of the prototype SWCNT. Hence, SWCNT is an efficient adsorbent and a candidate material for sensing atomic As. On the other hand, H3AsO3 interacts weakly with the SWCNT, with no significant modification observed in the SWCNT's atomic configuration, electronic structure, and optical absorption spectra. The interaction and sensitivity with H3AsO3 significantly improved after doping the SWCNT with Fe. The changes in the band structure patterns and optical absorption spectra of Fe-doped SWCNT is also observed upon exposure to H3AsO3. The results presented here provide fundamental insights into the interaction of SWCNT and As, which serve as a reference for fabricating SWCNT-based adsorbent and sensing platforms of heavy metals. The results further explore how metal-doped SWCNT tunes the bonding and sensitivity with heavy metals.

Soshina Nathan, Soumya Mathunny, J Anjana

bioRxiv (Cold Spring Harbor Laboratory) • 2024

ABSTRACT Given the enormous potential of metal nanomaterials, their sustainable production is of paramount importance and is a key area of focus worldwide. In this regard, bacteria are highly valued because of their potential for rapid, cost-effective and eco-friendly metal nanomaterial synthesis. In this study, culture supernatants of Bacillus cereus and Curvularia sp isolated from heavy metal rich Titanium industry effluent effectively synthesised cobalt and copper nanoparticles of narrow size range at room temperature, neutral pH and static conditions within 2-7 days. This was verified by visible colour changes, UV-Vis spectroscopy and FT-IR. The UV-Visible spectra of the biosynthesized cobalt and copper nanoparticles exhibited sharp narrow peaks at 341 and 342 nm. This suggested that the cobalt and copper nanoparticles were not only small but also had a narrow size distribution, a feature rarely reported in biosynthesis studies. Furthermore, our approach was conducted at room temperature using cell-free supernatant, eliminating the need for additional heating or cooling, and minimising processing thus making the process energy-efficient, cost effective and sustainable. This is a first report on the production of monodisperse cobalt and copper nanoparticles by microbes isolated from this novel extreme environment. Graphical abstract

Fabian Kubannek, Uwe Schröder, Ulrike Krewer

• 2020

<p>Electroactive biofilms are routinely characterized in-operando by dynamic electrochemical measurement techniques such as cyclic voltammetry or electrochemical impedance spectroscopy. Since electrical signals can be recorded and processed very quickly, these techniques allow to investigate slow and fast electron transfer processes.</p> <p> </p> <p>In contrast, the dynamics of species production rates are usually not addressed because standard measurement techniques for the quantification of reaction products such as gas chromatography are slow. Instead it is often assumed that species production rates are either directly proportional to the current - under so called turnover conditions - or equal zero - under so called non-turnover conditions.</p> <p> </p> <p>To challenge this assumption, we measured species production rates of a biofilm electrode with a high time resolution by differential electrochemical mass spectrometry (DEMS). An acetate oxidizing biofilm electrode was placed just micrometers away from the mass spectrometer inlet in which enabled us to observe CO<sub>2</sub> production directly at the electrode during cyclic voltammetry (CV) and potential steps.</p> <p> </p> <p>The measurement results showed that the CO<sub>2</sub> production deviates significantly from the expected value calculated from the current by Faraday’s law under certain operating conditions. We analyze this effect in detail and show that it can be explained with biofilm storage capacities for charge and substrate. These capacities are quantified by deconvoluting the faradaic and non-faradaic currents. [1]</p> <p> </p> <p>Also, the onset of the complete oxidation of acetate to CO<sub>2</sub> during CVs was determined to be just 22 mV above the standard potential for acetate oxidation. Determining this value by directly measuring CO<sub>2</sub> instead of current is advantageous because capacitive effects can be excluded. [1]</p> <p> </p> <p>In conclusion, we demonstrate that electrical current and CO<sub>2</sub> production can be partly decoupled in biofilm electrodes and that DEMS is a valuable technique for analyzing processes in such electrodes.</p> <p> </p> <p>[1] Kubannek, F., Schröder, U., Krewer, U. (2018). Revealing metabolic storage processes in electrode respiring bacteria by differential electrochemical mass spectrometry. Bioelectrochemistry, 121, 160–168, doi: 10.1016/j.bioelechem.2018.01.014</p>

Mark W. Rutland

Faraday Discussions • 2017

It is an honour to be charged with providing the concluding remarks for a Faraday Discussion. As many have remarked before, it is nonetheless a prodigious task, and what follows is necessarily a personal, and probably perverse, view of a watershed event in the Chemical Physics of Electroactive materials. The spirit of the conference was captured in a single sentence during the meeting itself.By Andriy Yaroschuk in commenting on the work of Kelsey Hatzell (DOI: 10.1039/c6fd00243a). “It is the nexus between rheology, electrochemistry, colloid science and energy storage”. The current scientific climate is increasingly dominated by a limited number of global challenges, and there is thus a tendency for research to resemble a football match played by 6 year olds, where everyone on the field chases the (funding) ball instead of playing to their “discipline”. It is thus reassuring to see how the application of rigorous chemical physics is leading to ingenious new solutions for both energy storage and harvesting, via , for example, nanoactuation, electrowetting, ionic materials and nanoplasmonics. In fact, the same language of chemical physics allows seamless transition between applications as diverse as mechano-electric energy generation, active moisture transport and plasmonic shutters – even the origins of life were addressed in the context of electro-autocatalysis!

Mohammed Mouhib, Melania Reggente, Ardemis A. Boghossian

bioRxiv (Cold Spring Harbor Laboratory) • 2023

Abstract Bioelectrochemical systems (BES) are promising for energy, sensing, environmental, and synthesis applications. Escherichia coli were previously bioengineered for application in BES by introduction of extracellular electron transfer (EET) pathways. Inspired by the metal-reducing (Mtr) pathway of Shewanella oneidensis MR-1, several of its cytochromes were heterologously expressed in E. coli , leading to increased EET rates and successful application in BES. Besides direct electron transfer , S. oneidensis MR-1 is known to secrete flavins that act as redox mediators and are crucial for high EET rates. Here we co-express the Mtr pathway and a flavin biosynthesis pathway in E. coli , to enhance EET in engineered strains. The secretion of both flavin mononucleotide and riboflavin was increased up to 3-fold in engineered strains. Chronoamperometry revealed an up to ~3.4-fold increase in current over the wild type when co-expressing cytochromes and flavin biosynthesis genes, and a ~2.3-fold increase when expressing flavin biosynthesis genes on their own. Thus, the introduction of flavin biosynthesis genes yields in a distinct, yet complementary EET mechanism, and holds promise for application in BES.

Anna Nikolaidou, Panagiotis Mougkogiannis, Andrew Adamatzky

Research Square • 2023

Abstract In this study, we present electroactive biofilms made from a combination of Kombucha zoogleal mats andthermal proteinoids. These biofilms have potential applications in unconventional computing and roboticskin. Proteinoids are synthesised by thermally polymerizing amino acids, resulting in the formation ofsynthetic protocells that display electrical signalling similar to neurons. By incorporating proteinoids intoKombucha zoogleal cellulose mats, hydrogel biofilms can be created that have the ability to efficiently transfercharges, perform sensory transduction, and undergo processing. We conducted a study on the memfractanceand memristance behaviours of composite biofilms, showcasing their capacity to carry out unconventionalcomputing operations. The porous nanostructure and electroactivity of the biofilm create a biocompatibleinterface that can be used to record and stimulate neuronal networks. In addition to in vitro neuronal interfaces, these soft electroactive biofilms show potential as components for bioinspired robotics, smart wearables,unconventional computing devices, and adaptive biorobotic systems. Kombucha-proteinoids composite filmsare a highly customizable material that can be synthesised to suit specific needs. These films belong toa unique category of “living” materials, as they have the ability to support cellular systems and improvebioelectronic functionality. This makes them an exciting prospect in various applications. Ongoing effortsare currently being directed towards enhancing the compositional tuning of conductivity, signal processing,and integration within hybrid bioelectronic circuits.

A-Andrew D Jones, Cullen R Buie

bioRxiv (Cold Spring Harbor Laboratory) • 2018

Electroactive bacteria such as Geobacter sulfurreducens and Shewanella onedensis produce electrical current during their respiration; this has been exploited in bioelectrochemical systems. These bacteria form thicker biofilms and stay more active than soluble-respiring bacteria biofilms because their electron acceptor is always accessible. In bioelectrochemical systems such as microbial fuel cells, corrosion-resistant metals uptake current from the bacteria, producing power. While beneficial for engineering applications, collecting current using corrosion resistant metals induces pH stress in the biofilm, unlike the naturally occurring process where a reduced metal combines with protons released during respiration. To reduce pH stress, some bioelectrochemical systems use forced convection to enhance mass transport of both nutrients and byproducts; however, biofilms’ small pore size limits convective transport, thus, reducing pH stress in these systems remains a challenge. Understanding how convection is necessary but not sufficient for maintaining biofilm health requires decoupling mass transport from momentum transport (i.e. fluidic shear stress). In this study we use a rotating disc electrode to emulate a practical bioelectrochemical system, while decoupling mass transport from shear stress. This is the first study to isolate the metabolic and structural changes in electroactive biofilms due to shear stress. We find that increased shear stress reduces biofilm development time while increasing its metabolic rate. Furthermore, we find biofilm health is negatively affected by higher metabolic rates over long-term growth due to the biofilm’s memory of the fluid flow conditions during the initial biofilm development phases. These results not only provide guidelines for improving performance of bioelectrochemical systems, but also reveal features of biofilm behavior. Results of this study suggest that optimized reactors may initiate operation at high shear to decrease development time before decreasing shear for steady-state operation. Furthermore, this biofilm memory discovered will help explain the presence of channels within biofilms observed in other studies.

Akanksha Singh

Preprints.org • 2024

Studies at the molecular, systemic, and epidemiological levels have shown that chronic metal exposure is linked to significant health consequences, including cancer, affecting hundreds of millions worldwide. Subtle and convoluted mechanisms underline metals' toxicity and carcinogenicity. The use of sensors for carcinogenic metals' trace detection is on the rise due to their selectivity, simplicity, and affordability. Biotechnology and microelectronics in the development of sensors have grown complementarily in recent years. This study offers a comprehensive overview of current research and advancements in developing sensors for detecting carcinogenic metals. Here, we have focussed on the developed biosensor platforms for group 1 carcinogens, i.e., arsenic, nickel, cadmium, chromium, and beryllium, along with their brief roles in human carcinogenesis. This review also looks at the importance of sensing such metal exposure in humans from a larger perspective, hoping to influence future research toward early prevention and treatment of illnesses like cancer.

The IUPAC Compendium of Chemical Terminology • 2019

Citation: 'electroactive substance' in the IUPAC Compendium of Chemical Terminology, 3rd ed.; International Union of Pure and Applied Chemistry; 2006. Online version 3.0.1, 2019. 10.1351/goldbook.E01940 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

Ian Sofian Yunus, Julian Wichmann, Robin Wördenweber et al.

bioRxiv (Cold Spring Harbor Laboratory) • 2018

ABSTRACT Liquid fuels sourced from fossil sources are the dominant energy form for mobile transport today. The consumption of fossil fuels is still increasing, resulting in a continued search for more sustainable methods to renew our supply of liquid fuel. Photosynthetic microorganisms naturally accumulate hydrocarbons that could serve as a replacement for fossil fuel, however productivities remain low. We report successful introduction of five synthetic metabolic pathways in two green cell factories, prokaryotic cyanobacteria and eukaryotic algae. Heterologous thioesterase expression enabled high-yield conversion of native acyl-ACP into free fatty acids (FFA) in Synechocystis sp . PCC 6803 but not in Chlamydomonas reinhardtii where the polar lipid fraction instead was enhanced. Despite no increase in measurable FFA in Chlamydomonas , genetic recoding and over-production of the native fatty acid photodecarboxylase (FAP) resulted in increased accumulation of 7-heptadecene. Implementation of a carboxylic acid reductase (CAR) and aldehyde deformylating oxygenase (ADO) dependent synthetic pathway in Synechocystis resulted in the accumulation of fatty alcohols and a decrease in the native saturated alkanes. In contrast, the replacement of CAR and ADO with Pseudomonas mendocina UndB (so named as it is responsible for 1-undecene biosynthesis in Pseudomonas ) or Chlorella variabilis FAP resulted in high-yield conversion of thioesterase-liberated FFAs into corresponding alkenes and alkanes, respectively. At best, the engineering resulted in an increase in hydrocarbon accumulation of 8- (from 1 to 8.5 mg/g dell dry weight) and 19-fold (from 4 to 77 mg/g cell dry weight) for Chlamydomonas and Synechocystis , respectively. In conclusion, reconstitution of the eukaryotic algae pathway in the prokaryotic cyanobacteria host generated the most effective system, highlighting opportunities for mix-and-match synthetic metabolism. These studies describe functioning synthetic metabolic pathways for hydrocarbon fuel synthesis in photosynthetic microorganisms for the first time, moving us closer to the commercial implementation of photobiocatalytic systems that directly convert CO 2 into infrastructure-compatible fuels. Highlights Synthetic metabolic pathways for hydrocarbon fuels were engineered in algae Free fatty acids were effectively converted into alkenes and alkanes Transfer of algal pathway into cyanobacteria was the most effective Alkane yield was enhanced 19-fold in Synechocystis spp . PCC 6803 Alkene yield was enhanced 8-fold in Chlamydomonas reinhardtii

Samuel Fajemilua, Solomon Bada, M. Ahsanul Islam

bioRxiv (Cold Spring Harbor Laboratory) • 2020

Abstract Contaminants of emerging concern (CEC) such as tetracycline, erythromycin, and salicylic acid in groundwater can seriously endanger the environment and human health due to their widespread and everlasting harmful effects. Thus, continuous monitoring of various CEC concentrations in groundwater is essential to ensure the safety, security, and biodiversity of natural habitats. CECs can be detected using whole-cell biosensors for environmental surveillance and monitoring purposes, as they provide a cheaper and more robust alternative to traditional and expensive analytical techniques. In this study, various genetic circuit designs are considered to model three biosensors using the genetic design automation (GDA) software, iBioSim. The genetic circuits were designed to detect multiple CECs, including atrazine, salicylic acid, and tetracycline simultaneously to produce quantitative fluorescent outputs. The biosensor responses and the viability of the genetic circuit designs were further analysed using ODE-based mathematical simulations in iBioSim. The designed circuits and subsequent biosensor modelling presented here, thus, not only show the usefulness and importance of GDA tools, but also highlight their limitations and shortcomings that need to overcome in the future; thereby, providing a practical guidance for further improvement of such tools, so that they can be more effectively and routinely used in synthetic biology research.