Digital Twins for Wastewater Treatment:A Technical Review

The digital twins concept enhances modeling and simulation through the integration of real-time data and feedback.This review elucidates the foundational elements of digital twins,covering their concept,entities,domains,and key technologies.More specifically,we investigate the transformative potential of digital twins for the wastewater treatment engineering sector.Our discussion highlights the application of digital twins to wastewater treatment plants(WWTPs)and sewage networks,hardware(i.e.,facilities and pipes,sensors for water quality and activated sludge,hydrodynamics,and power consumption),and software(i.e.,knowledge-based and data-driven models,mechanistic models,hybrid twins,control methods,and the Internet of Things).Furthermore,two cases are provided,followed by an assessment of current challenges in and perspectives on the application of digital twins in WWTPs.This review serves as an essential primer for wastewater engineers navigating the digital paradigm shift.

Modelling the biological performance of a side-stream membrane bioreactor using ASM1

Membrane bioreactors(MBRs) are attracting global interest but the mathematical modeling of the biological performance of MBRs remains very limited. This study focuses on the modelling of a side-stream MBR system using Activated Sludge Model No.1(ASM1), and comparing the results with the modelling of traditional activated sludge processes. ASM1 parameters relevant for the long-term biological behaviour in MBR systems were calibrated(i.e. Y H=0.72gCOD/gCOD, Y A=0.25gCOD/gN, b H=0.25 d -1, b A=0.080 d -1 and f P=0.06), and generally agreed with the parameters in traditional activated sludge processes, with the exception that a higher autotrophic biomass decay rate was observed in the MBR. A sensitivity analysis for steady state operation and DO dynamics suggested that the biological performance of the MBR system(the sludge concentration, effluent quality and the DO dynamics) are very sensitive to the parameters(i.e. Y H, Y A, b H, b A, μ maxH and μ maxA), and influent wastewater components(X I, S S, X S, S NH).

Fruit Juice Production in Abomey-Calavi and Cotonou Municipalities (Benin): Socio-Professional Profile of Actors and Adoption Level of Hygienic Practices of Enterprises

Fruit juice production sector is developing in Benin’s major cities and appears to have both organisational and technical shortcomings. This study aimed to 1) establish the socio-professional profile of actors in the fruit juice production sector in Abomey-Calavi and Cotonou municipalities and 2) evaluate the adoption level of hygienic practices of enterprises. The methodological approach adopted in this study combined a semi-structured survey with direct observations in fifty enterprises. The statistical analysis was carried out using the R.4.0.0 software. The study revealed that fruit juice enterprises in both municipalities are mainly artisanal (90%) and located in residential areas (94%). They are therefore exposed to contamination risks from domestic and road activities. More than half of these enterprises were created less than five years ago. Three administrative types of enterprises were noted: non-structured (32%), semi-structured (34%) and structured (34%). Almost half of the enterprises belong to at least one professional association. Only a few enterprises have marketing authorization. Women predominate in the positions of director and production assistant. The majority of production managers are men. Most directors and production managers have a university education, but not necessarily in the field of food sciences. The adoption level of hygienic practices is significantly influenced by the level of enterprises structuration and size. The level of hygiene in these enterprises is also very weakly influenced by the female gender. Structured and semi-industrial enterprises have a higher adoption level of hygienic practices. Those with acceptable or good hygiene level enterprises contain slightly more women.

Applying Rhizobacteria on Maize Cultivation in Northern Benin:Effect on Growth and Yield

The aim of the study was to investigate the effects of five plant growth-promoting rhizobacteria (PGPR) (Bacillus panthothenicus;Pseudomonas Cichorii;Pseudomonas Putida;Pseudomonas syringae and Serratia marcescens) on the growth and yield of maize on a ferruginous soil under field condition. Maize seeds were inoculated with 10 ml of bacterial suspension. Study was conducted in a completely randomized design with fifteen treatments and three replicates. A half-dose of recommended (13, 17, 17 kg?ha?1) NPK was applied 15 days after emergence. The results show that the Serratia marcescens + 50% NPK treatment yielded the best results for height, fresh underground biomass, dry aboveground biomass, dry underground biomass, and grain yield with respective increases of 41.09%, 217.5%, 213.34%, 93.82%, and 39.05% compared to the control. Maximum stem diameter (increases of 49.65%) was recorded in the plants treated with 100% NPK (full dose NPK) while the highest leaf area (466.36 ± 9.57 cm2), obtained on plant treated with Pseudomonas putida + 50% NPK was 32.08% greater than in the non-inoculated control. Our results suggest the use of these rhizobacteria as biological fertilizers for enhancing the growth and maize seed yield in ferruginous soil in the North of Benin.

Expression of the Viral Antigen VP60 in Transgenic Potatoes and its Effect on the Nutritional Composition of Tubers

Recombinant plant-derived pharmaceuticals have been investigated for the last two decades and some products will soon be brought to market. Since veterinary pharmaceuticals seem to be the front-runners of plant-derived vaccines, we selected one model subunit vaccine, the structural capsid protein VP60 against rabbit haemorrhagic disease, and ana-lyzed the expression of three different sequences representing the vp60 open reading frame in potato plants. The gen-eration of antigenic VP60 molecules in the leaf and tuber tissue of potato was tremendously enhanced by replacing virus-derived sequences with plant-optimized codons. In order to identify potentially undesirable alterations in the composition of these genetically modified food components, we studied their nutrient composition and nutritional value in comparison to two parental conventional breeding varieties (Albatros and Desiree). The largest differences in nutrient composition were found between the two conventional breeds and between conventional Desiree and its near-isogenic genetically modified potato plant, indicating that genetic modification as well as conventional breeding can influence nutrient composition. Nevertheless, most parameters of nutritional value seemed to be more affected by conventional breeding than by genetic modification.

Sample Size Affect Ethnobotanical Index Values: Bootstrap as a Remedial Approach

Ethnobotanical indices are widely used to quantify cultural importance of plants in social studies. This study aims to show users of ethnobotanical indices the effect of sample variation and what methodological approach can be used to circumvent the problems related to sample variation. The methods used are to write an algorithm and used to simulate different sample sizes from which four ethnobotanic indices selected for the present study were estimated. Results showed the instability of the ethnobotanical indices under variations in the size of informants. It proposes bootstrapping as a statistical aid tool to remove the sample size effect in quantitative ethnobotany. For the indices used in the present study 1000 re-samplings eliminated the effect of sample size on the value of the indices. Researchers will have to take this new approach into account in order to calculate more precise ethnobotanical indices in order to better appreciate the cultural importance of plants.

Influence of Isolated PGPR Rhizobacteria in Central and Northern Benin on Maize Germination and Greenhouse Growth

The objective of the study was to evaluate the effects of nine plant growth-promoting rhizobacteria (PGPR) alone or in combination on maize seed germination and seedling growth under laboratory and greenhouse conditions. The germination and growth tests were carried out in square petri dishes and pots. Maize seeds were inoculated with suspension of 108 CFU/ml of rhizobacteria. The experimental device was a random block of 16 treatments with four repetitions. Germination test results showed that seeds inoculated with PGPR including the control induced good germination in the range of 93.75% to 100%. The vigor index and root length of the seeds treated with Bacillus panthothenicus were significantly improved by 76.64% and 58.86%, respectively, while the maximal lengths of the seedlings were obtained with Pseudomonas cichorii with an increase of 118.95%. In greenhouse experience, data demonstrated that Serratia marcescens better improved the leaf area, height and underground biomass, respectively by 58.83%, 108.43%, and 59.16% as compared to the control. The highest fresh aerial biomass and air dry matter was obtained with plants treated only with Pseudomonas putida. These results show the potential to use such rhizobacteria as biofertilizers to improve maize productivity in Benin.

Mineral Fertilization Influences the Acceptability of Fresh Pulp and Juice Made from Sugarloaf Pineapple

Fertilization practices can influence the quality of pineapple fruit and consequently its acceptability by consumers who are increasingly oriented towards high quality agri-food products. This study aimed at evaluating the influence of N, P and K on some physico-chemical and organoleptic characteristics of pineapple (Ananas comosus L. Merr) for fresh consumption and juice processing. A complete NPK factorial design was installed in the south Benin. The treatments NPK in g plant-1 were randomized into four blocks: T1;T2;T3;T4;T5;T6;T7;T8;T9. Brix juice was determined using a refractometer and pH with a pH meter. An evaluation of sensory characteristics such as sweetness, acid taste and aroma of fresh pineapple pulp and processed juice was made by a panel of tasters selected and trained. A principal components analysis, followed by a numerical classification was performed on fruits’ sensory and physicochemical characteristics. Results showed that juice pH was significantly influenced by the phosphorus and potassium. Potassium influenced significantly juice yield. Some physico-chemical characteristics and sensory attributes were correlated between them and groups of treatments are formed for both the juice and the fresh fruit.

Metagenomics reveals the microbial community and functional metabolism variation in the partial nitritation-anammox process:From collapse to recovery

Mainstream partial nitritation-anammox(PNA)process easily suffers from performance instability and even reactor collapse in application.Thus,it is of great significance to unveil the characteristic of performance recovery,understand the intrinsic mechanism and then propose operational strategy.In this study,we combined long-term reactor operation,batch tests,and metagenomics to reveal the succession of microbial community and functional metabolism variation from system collapse to recovery.Proper aeration control(0.10-0.25mg O_(2)/L)was critical for performance recovery.It was also found that Candidatus Brocadia became the dominant flora and its abundance increased from 3.5%to 11.0%.Significant enhancements in carbon metabolism and phospholipid biosynthesis were observed during system recovery,and the genes abundance related to signal transduction was dramatically increased.The up-regulation of sdh and suc genes showed the processes of succinate dehydrogenation and succinyl-CoA synthesis might stimulate the production of amino acids and the synthesis of proteins,thereby possibly improving the activity and abundance of AnAOB,which was conducive to the performance recovery.Moreover,the increase in abundance of hzs and hdh genes suggested the enhancement of the anammox process.Changes in the abundance of key genes involved in nitrogen metabolism indicated that nitrogen removal pathway was more diverse after system recovery.The achievement of performance recovery was driven by anammox,nitrification and denitrification coupled with dissimilatory nitrate reduction to ammonium.These results provide deeper insights into the recovery mechanism of PNA system and also provide a potential regulation strategy for the stable operation of the mainstream PNA process.

Deep learning methods for biotic and abiotic stresses detection and classification in fruits and vegetables:State of the art and perspectives

Deep Learning(DL),a type of Machine Learning,has gained significant interest in many fields,including agriculture.This paper aims to shed light on deep learning techniques used in agriculture for abiotic and biotic stress detection in fruits and vegetables,their benefits,and the challenges faced by users.Scientific papers were collected from Web of Science,Scopus,Google Scholar,Springer,and Directory of Open Access Journals(DOAJ)using combinations of specific keywords such as:’Deep Learning’OR’Artificial Intelligence’in combination with fruit disease’,vegetable disease’,‘fruit stress',OR‘vegetable stress'following PRISMA guidelines.From the initial 818 papers identified using the keywords,132 were reviewed after excluding books,reviews,and the irrelevant.The recovered scientific papers were from 2003 to 2022;93%addressed biotic stress on fruits and vegetables.The most common biotic stresses on species are fungal diseases(grey spots,brown spots,black spots,downy mildew,powdery mildew,and anthracnose).Few studies were interested in abiotic stresses(nutrient deficiency,water stress,light intensity,and heavy metal contamination).Deep Learning and Convolutional Neural Networks were the most used keywords,with GoogleNet(18.28%),ResNet50(16.67%),and VGG16(16.67%)as the most used architectures.Fifty-two percent of the data used to compile these models come from the fields,followed by data obtained online.Precision problems due to unbalanced classes and the small size of some databases were also analyzed.We provided the research gaps and some perspectives from the reviewed papers.Further research works are required for a deep understanding of the use of machine learning techniques in fruit and vegetable studies:collection of large datasets according to different scenarios on fruit and vegetable diseases,evaluation of the effect of climatic variability on the fruit and vegetable yield using AI methods and more abiotic stress studies.

Grazing effects on vegetation dynamics in the savannah ecosystems of the Sahel

Background The savannah ecosystems of Sahel have experienced continuous and heavy grazing of livestock for centuries but still,their vegetation response to grazing pressure remains poorly understood.In this study,we analysed the herbaceous plant dynamics,measured by species diversity,composition,cover,and biomass in response to grazing pressure in the savannah ecosystems of Sahel.In Senegal,we selected four savannah sites represented with high,moderate,light and no grazing intensity levels.Transect survey methods were used for sampling the vegetation data within each of the sites.Species richness and composition were analysed using species accumulation curve and multivariate analyses.Furthermore,we used General Linear Models and a piecewise Structural Equation Model(pSEM)to examine the relationships between grazing intensity,vegetation cover,diversity and biomass.Results The herbaceous species diversity and composition varied significantly among the different grazing intensity levels(p<0.001).The plant species composition shifted from the dominance of grass cover to the dominance of forb cover with increasing grazing pressure.Moreover,the attributes of species diversity,herbaceous biomass,and ground cover were higher on sites with low grazing than sites with high and moderate grazing intensity.Across all sites,species diversity was positively related to total biomass.The pSEM explained 37%of the variance in total biomass and revealed that grazing intensity negatively influenced total biomass both directly and indirectly through its negative influence on species diversity.Conclusions Managing grazing intensity may lead to higher plant production and higher mixed forage establishment in the dryland savannah ecosystems.This information can be used to support land management strategies and promote sustainable grazing practices that balance the needs of livestock with the conservation of ecosystem health and biodiversity.

On the reliability of predictions on Covid-19 dynamics: A systematic and critical review of modelling techniques

Since the emergence of the novel 2019 coronavirus pandemic in December 2019(COVID-19),numerous modellers have used diverse techniques to assess the dynamics of transmission of the disease,predict its future course and determine the impact of different control measures.In this study,we conducted a global systematic literature review to summarize trends in the modelling techniques used for Covid-19 from January 1st,2020 to November 30th,2020.We further examined the accuracy and precision of predictions by comparing predicted and observed values for cumulative cases and deaths as well as uncertainties of these predictions.From an initial 4311 peer-reviewed articles and preprints found with our defined keywords,242 were fully analysed.Most studies were done on Asian(78.93%)and European(59.09%)countries.Most of them used compartmental models(namely SIR and SEIR)(46.1%)and statistical models(growth models and time series)(31.8%)while few used artificial intelligence(6.7%),Bayesian approach(4.7%),Network models(2.3%)and Agent-based models(1.3%).For the number of cumulative cases,the ratio of the predicted over the observed values and the ratio of the amplitude of confidence interval(CI)or credibility interval(CrI)of predictions and the central value were on average larger than 1 indicating cases of inaccurate and imprecise predictions,and large variation across predictions.There was no clear difference among models used for these two ratios.In 75%of predictions that provided CI or CrI,observed values fall within the 95%CI or CrI of the cumulative cases predicted.Only 3.7%of the studies predicted the cumulative number of deaths.For 70%of the predictions,the ratio of predicted over observed cumulative deaths was less or close to 1.Also,the Bayesian model made predictions closer to reality than classical statistical models,although these differences are only suggestive due to the small number of predictions within our dataset(9 in total).In addition,we found a significant negative correlation(rho=-0.56,p=0.021)between this ratio and the length(in days)of the period covered by the modelling,suggesting that the longer the period covered by the model the likely more accurate the estimates tend to be.Our findings suggest that while predictions made by the different models are useful to understand the pandemic course and guide policy-making,some were relatively accurate and precise while other not.

In silico assessment of household level closed water cycles:Towards extreme decentralization

Water management in most of the developed world is currently practiced in a highly centralized manner,leading to major infrastructure and energy costs to transport water.To decrease the impacts of water scarcity and climate change,the decentralization of water can increase local robustness.In extremis,decentralization can involve building or house level water supply and treatment.Here,we constructed a MATLAB/Simulink model for two decentralized water management configurations at the household level,assuming the socio-environmental setting of Flanders,Belgium.Independence from the potable water grid and sewer system was pursued through rainwater harvesting,reuse of wastewater streams fitfor-purpose,and discharge via infiltration.The mass balance for water was calculated over the system boundaries showing high potential for independence from the grid with a reasonable treatment train and storage options.Next,the risk of contaminant accumulation within the circular system was assessed,showing a key limitation on decentralized system performance necessitating a system purge.Up to 59%of system rainwater usage was due to the replacement of this purge.Employing treatment units with high(95%)contaminant rejection efficiencies eliminated contaminant accumulation issues.The raw model output was quantitatively assessed by constructing four newly proposed key performance indicators(KPIs),quantifying system independence,circularity,drought tolerance and local water body recharge,which allowed for facilitated system comparison and communication to stakeholders.A sensitivity analysis was performed in which the effect of input parameter variability and uncertainty on system performance was quantified.The sensitivity analysis showed the importance of water recovery and contaminant removal efficiencies of the applied treatment technologies on system performance when contaminant accumulation in the system forms an issue.In systems not severely affected by pollutant accumulation,parameters such as inhabitant number and roof surface had the largest effect.As a whole,this work shows the potential of extreme decentralization of water systems and addresses the obstacle towards implementation formed by the accumulation of contaminants due to system circularity.Additionally,this study provides a framework for operational and technological decision support of decentralized household-scale water systems and,by extension,for future water policy-making.

POLYPHENOLS, CYTOTOXICITY AND ENZYMATIC ACTIVITIES OF THREE ERIACEAE SPECIES FROM ALGERIA

In Algerian traditional medicine,Erica arborea(EA),Erica multiflora(EM)and Arbutus unedo(AU)are reported as antiseptic,diuretic,astringent,depurative,and to treat scalds and wounds.The methanolic extracts of their leaves and aerial parts were screened for enzyme inhibitory and cytotoxic activities.TLC and HPLC chromatographic profiles based on flavonoids allowed to easily distinguish between the three investigated species.Inhibitory

PHENOLIC PROFILE, ANTIBACTERIAL,NEUROPROTECTIVE AND CYTOTOXIC PROPERTIES OF THREE ALGERIAN MENTHA SPECIES

This study was designed to evaluate the antibacterial(direct effect and reversal of antibiotics-resistance),neuroprotective(acetylcholinesterase and carboxylesterase inhibition)and cytotoxic(MTT assay on 2 human cancer cell lines)properties of three Mentha species[M.pulegium L.(MP),M.rotundifolia(L.)Huds(MR),and M.spicata L.(MS)]harvested in Bejaia(Algeria).The phenolic