Estimating yield-contributing physiological parameters of cotton using UAV-based imagery.

Lint yield in cotton is governed by light intercepted by the canopy (IPAR), radiation use efficiency (RUE), and harvest index (HI). However, the conventional methods of measuring these yield-governing physiological parameters are labor-intensive, time-consuming and requires destructive sampling. This study aimed to explore the use of low-cost and high-resolution UAV-based RGB and multispectral imagery 1) to estimate fraction of IPAR (IPARf), RUE, and biomass throughout the season, 2) to estimate lint yield using the cotton fiber index (CFI), and 3) to determine the potential use of biomass and lint yield models for estimating cotton HI. An experiment was conducted during the 2021 and 2022 growing seasons in Tifton, Georgia, USA in randomized complete block design with five different nitrogen treatments. Different nitrogen treatments were applied to generate substantial variability in canopy development and yield. UAV imagery was collected bi-weekly along with light interception and biomass measurements throughout the season, and 20 different vegetation indices (VIs) were computed from the imagery. Generalized linear regression was performed to develop models using VIs and growing degree days (GDDs). The IPARf models had R2 values ranging from 0.66 to 0.90, and models based on RVI and RECI explained the highest variation (93%) in IPARf during cross-validation. Similarly, cotton above-ground biomass was best estimated by models from MSAVI and OSAVI. Estimation of RUE using actual biomass measurement and RVI-based IPARf model was able to explain 84% of variation in RUE. CFI from UAV-based RGB imagery had strong relationship (R2 = 0.69) with machine harvested lint yield. The estimated HI from CFI-based lint yield and MSAVI-based biomass models was able to explain 40 to 49% of variation in measured HI for the 2022 growing season. The models developed to estimate the yield-contributing physiological parameters in cotton showed low to strong performance, with IPARf and above-ground biomass having greater prediction accuracy. Future studies on accurate estimation of lint yield is suggested for precise cotton HI prediction. This study is the first attempt of its kind and the results can be used to expand and improve research on predicting functional yield drivers of cotton.

Machine-learning-aided application of high-gravity technology to enhance ammonia recovery of fresh waste leachate.

Stripping is widely applied for the removal of ammonia from fresh waste leachate. However, the development of air stripping technology is restricted by the requirements for large-scale equipment and long operation periods. This paper describes a high-gravity technology that improves ammonia stripping from actual fresh waste leachate and a machine learning approach that predicts the stripping performance under different operational parameters. The high-gravity field is implemented in a co-current-flow rotating packed bed in multi-stage cycle series mode. The eXtreme Gradient Boosting algorithm is applied to the experimental data to predict the liquid volumetric mass transfer coefficient (KLa) and removal efficiency (η) for various rotation speeds, numbers of stripping stages, gas flow rates, and liquid flow rates. Ammonia stripping under a high-gravity field achieves η = 82.73% and KLa = 5.551 × 10-4 s-1 at a pH value of 10 and ambient temperature. The results suggest that the eXtreme Gradient Boosting model provides good accuracy and predictive performance, with R2 values of 0.9923 and 0.9783 for KLa and η, respectively. The machine learning models developed in this study are combined with experimental results to provide more comprehensive information on rotating packed bed operations and more accurate predictions of KLa and η. The information mining behind the model is an important reference for the rational design of high-gravity-field-coupled ammonia stripping projects.

Transport and deposition of solid phosphorus-based mineral particles in urine diversion systems.

The deposition of solid phosphorus-based mineral particles is a common problem in urine diversion systems, which occurs in transport systems, particularly in horizontal pipelines. In this work, particle deposition behaviour in turbulent flow in a 3D horizontal pipe was simulated by using the Euler-Lagrange method. The effects of particle diameter, particle density, particle shape factor and fluid flow velocity on particle deposition behaviour were investigated. The results showed that the deposition rate increased by 9.92%,6.88% and 6.88% with increasing particle diameter (10-90 µm), particle density (1400 kg/m3-2300 kg/m3), and particle shape factor (0.2-1), respectively. For particles with larger diameters (>90 µm) or larger density (>2300 kg/m3), the deposition rate of these particles was almost reached 100%. It was found that gravitational sedimentation was the dominant deposition mechanism in low fluid flow velocity range (0.1-0.5 m/s). As fluid flow velocity increased (>0.5 m/s), turbulent fluctuation became the dominant factor that affected particle motion behaviour, whereas the effect of gravitational sedimentation on particle deposition behaviour declined significantly, and the increase in fluid flow velocity no longer significantly affects deposition rate. It was found that the deposition rate decreased by 29.13% as the fluid flow velocity was increased from 0.1 m/s to 0.5 m/s, while the corresponding deposition rate only decreased by 14.24% when the fluid flow velocity was increased from 0.5 m/s to 2 m/s. The optimal flow velocity was found to range between 0.75 and 1.25 m/s, which may mitigate the deposition of mineral solids in urine diversion systems.

Development of a Clinical Decision Support System to Predict Unplanned Cancer Readmissions.

Unplanned 30-day cancer readmissions are an important outcome of cancer hospitalization and can significantly raise mortality rates and costs for both the patient and the hospital. This paper aimed to develop a predictive model using machine learning and electronic health records to predict unplanned 30-day cancer readmissions and further develop it as a clinical decision support system. The three-stage study design followed the 2022 AMIA Artificial Intelligence Evaluation Showcase. In the first stage, the technical performance of the model was determined (81% of AUROC) and contributing factors were identified. In the second stage, the technical feasibility and workflow considerations of using such a predictive model were explored through semi-structured interviews. In the third stage, a decision tree analysis and a cost estimation showed that the model can reduce unplanned readmissions significantly if timely action is taken and that preventing a single readmission may significantly reduce costs.

Factors Affecting Time to Emergence From General Anesthesia Following Clipping of Ruptured Aneurysms: A Prospective Observational Study.

INTRODUCTION: Early emergence from anesthesia is valuable, especially among neurosurgical patients for postoperative neurological evaluation and appropriate interventions. However, the factors affecting the emergence in patients undergoing clipping of ruptured aneurysms have not been studied. MATERIALS AND METHODS: This was a prospective observational study on patients of aneurysmal subarachnoid hemorrhage with World Federation of Neurological Surgeons (WFNS) Grades I to III, undergoing surgical clipping. All relevant preoperative and intraoperative details were collected and analyzed to assess the factors affecting emergence time. RESULTS: A total of 67 patients with a median age of 46 years were included in the study. The number of patients with Fisher Grades I, II, III, and IV was 6, 20, 25, and 16, respectively. The median time to emergence was 17 minutes (interquartile range 10-240 minutes). On univariate analysis, the factors that were found to have a significant relationship with time to emergence were preoperative Glasgow Coma Score (GCS; P = 0.02), WFNS grade (P = 0.005, temporary clipping time (P = 0.03), and the temperature at the end of surgery (P < 0.001) In the multivariate analysis using generalized linear model, preinduction GCS (P < 0.001), patient's temperature at the end of surgery (P < 0.001), and temporary clipping time (P = 0.01) had a significant impact on the emergence time, independent of age, American Society of Anesthesiologists grade, Fisher grade, duration of anesthesia and of each other, with GCS and temperature having the maximum impact. ROC curve for temperature had a cutoff value at 35.3°C with an 83% probability of awakening beyond 15 minutes if the temperature decreased below 35.3°C. CONCLUSION: The preinduction GCS, the temperature of patients at the end of surgery, and the duration of temporary clipping have a significant independent impact on the time to emergence from neurosurgical anesthesia, in the order of the strength of the association.

Knowledge and awareness of school teachers regarding emergency management of dental trauma in school children of Navi Mumbai.

CONTEXT: Dental trauma is a serious oral health problem that can impair function and aesthetics, which affects the overall quality of life in children. AIMS: The aim of the present study was to identify the level of knowledge and awareness of school teachers regarding emergency management of dental trauma in school children of Navi Mumbai. The second objective was to correlate it with demographic characteristics and evaluate the need for oral health education programs for teachers. SETTINGS AND DESIGN: The present study is a cross-sectional survey and involved the completion of a self-administered anonymous questionnaire by teachers. MATERIALS AND METHODS: A total of 559 school teachers of primary and secondary sections completed the questionnaire comprising 19 questions. These included demographic data, knowledge regarding teeth most frequently affected by trauma, immediate action to be taken, awareness about storage media and the use of mouth guards. The questionnaire also assessed the willingness of teachers to participate in future training programs on dental trauma management. Data were statistically analysed using Chi-square test for any correlation. RESULTS: Among 559 school teachers who completed the questionnaire, 75.3% were females and 24.7% were males. Merely 6.6% of them agreed to have received prior training in dental trauma management. The majority of teachers (87.5%) were willing to attend training programs on dental trauma management. CONCLUSIONS: The knowledge and awareness of school teachers about dental trauma management and storage media for avulsed teeth is poor. Overall, they have a fair knowledge of dental trauma management in school children.

Domestic wastewater treatment efficiency of the pilot-scale trickling biofilter system with variable flow rates and hydraulic retention times.

In this study, a pilot-scale trickling biofilter (TBF) using pebbles and gravels media was evaluated for the treatment of domestic wastewater. The TBF system was installed in an open environment at residential area of Quaid-i-Azam University, Islamabad, Pakistan, and was operated at three different recirculation flow rates (Q), i.e. 0.04, 0.072 and 0.1 m3/day and under three different HRTs, i.e. 48, 72 and 96 h. It was observed that the efficiency of pilot-scale TBF system in terms of pathogens removal was significant, i.e. at flow rates of 0.04, 0.072 and 0.1 m3/day, an average reduction of 39.8-62.5% (p = 0.007), 35.9-48.6% (p = 0.01) and 25.8-57.3% (p = 0.009) respectively were attained in CFU/mL under different HRTs. Moreover, it has been observed that due to high void spaces up to 30%, pebbles and gravels filter media in co-ordination allowing good microbial growth and increased the diversity of bacterial species. Furthermore, it also facilitate the removal of different pollutant indicators, i.e. chemical oxygen demand (COD) (74.2-80.5%), total dissolved solids (TDS) (60.3-69.5%), electric conductivity (EC) (62.8-68.6%) and phosphates (PO4) (45.3-60.3%). A significant reduction in total nitrogen (TN) (59-63.3%) was observed at flow rates of 0.04 and 0.072 m3/day (p = 0.005). The experimental data of this research study will be helpful for further modification in the TBF system using different filter media in association and selecting optimal HRTs and flow rates in future study to get maximum efficiency of TBF system while treating domestic wastewater.

Particle size enlargement and 6-fold fluorescence enhancement of colloidal CdS quantum dots induced by selenious acid.

Herein, colloidal CdS QDs have been synthesized by using cysteine as a stabilizing agent. The interaction between the CdS QDs and selenious acid was monitored by using UV-visible, fluorescence and Fourier transform infrared (FTIR) spectroscopy. The onset of absorption of the CdS QDs (430 nm) was progressively red-shifted upon increase in the concentration of selenious acid at pH 10. It indicated enlargement of the particle size which was confirmed by the dynamic light scattering (DLS) measurements. Interestingly, the addition of 100 µM selenious acid at pH 6 resulted in a 6-fold enhancement of the red emission (λmax = 617 nm) of the CdS QDs. The particle size enlargement of CdS was due to an electrostatic interaction between selenious acid and QD stabilizer cysteine. The 6-fold fluorescence enhancement was of the CdS QDs was explained on the basis of hydrogen-bonding interaction between selenious acid and cysteine. The fluorescence-based method was applied for the sensing of selenious acid at pH 6.

Appraisal of suspended growth process for treatment of mixture of simulated petroleum, textile, domestic, agriculture and pharmaceutical wastewater.

The unrestricted discharge of domestic and industrial wastewaters along with agricultural runoff water into the environment as mixed-wastewater pose serious threat to freshwater resources in many countries. Mixed-wastewater pollution is a common phenomenon in the developing countries as the technologies to treat the individual waste streams at source are lacking due to high operational and maintenance costs. Therefore, the need to explore the potential of the suspended growth process which is a well-established process technology for biological wastewater treatment is the focus of this paper. Different wastewater constituents: representing domestic, pharmaceutical, textile, petroleum, and agricultural runoff were synthesized as a representative of mixed-wastewater and treated in two semi-continuous bioreactors (R1 & R2) operated at constant operating conditions, namely MLSS (mg/L): 4640-R1, 4440-R2, SRT: 21-d, HRT: 48-72 h, and uncontrolled pH. The system attained stable condition in day 97, with average COD, BOD and TSS reduction as 84.5%, 86.2%, and 72.2% for R1; and 85.1%, 87.9%, and 75.1% for R2, respectively. Phosphate removal on average was by 74.3% in R1 and 76.6% in R2, while average nitrification achieved in systems 1 and 2 were 56.8% and 54.7%, respectively. The biological treatment system has shown potential for improving the quality of mixed-wastewater to the state where reuse may be considered and tertiary treatment can be employed to polish the effluent quality.

Effectiveness of Virtual Reality Eyeglasses as a Distraction Aid to Reduce Anxiety among 6-10-year-old Children Undergoing Dental Extraction Procedure.

INTRODUCTION: Distraction is commonly used nonpharmacologic pain management technique by pedodontists to manage pain and anxiety. There are some new techniques which uses audiovideo stimulation and distract the patient by exposing him or her to three-dimensional videos. These techniques are referred to as virtual reality audiovisual systems. The aim is to evaluate the effectiveness of virtual reality eyeglasses as a distraction aid to reduce anxiety of children undergoing extraction procedure. OBJECTIVE: The aim of this study is to evaluate the effectiveness of virtual reality eyeglasses as a distraction aid to reduce anxiety of children undergoing dental extraction procedure. MATERIALS AND METHODS: Thirty children of age 6-10 years (n = 60) with bilateral carious primary molars indicated for extraction were randomly selected and divided into two groups of 30 each. The first one was group I (VR group) (n = 30) and group II (control group) (n = 30). Anxiety was measured by using Venham's picture test, pulse rate and oxygen saturation. Anxiety level between group I and group II was assessed using paired "t" test. RESULTS: The mean pulse rate values after extraction procedure in group I were 107.833 ± 1.356 and group II were 108.4 ± 0.927 respectively. The pulse rate values in intergroup comparison were found statistically significant p = 0.03. CONCLUSION: The virtual reality used as a distraction technique improves the physiologic parameters of children aged 6-10 years but does not reduce the patient's self-reported anxiety according to Venham's picture test used. HOW TO CITE THIS ARTICLE: Koticha P, Katge F, et al. Effectiveness of Virtual Reality Eyeglasses as a Distraction Aid to Reduce Anxiety among 6-10-year-old Children Undergoing Dental Extraction Procedure. Int J Clin Pediatr Dent 2019;12(4):297-302.

Understanding the relevance of herb-drug interaction studies with special focus on interplays: a prerequisite for integrative medicine.

Integrative medicine refers to the blending of conventional and evidence-based complementary medicines and therapies with the aim of using the most appropriate of either or both modalities for ultimate patient benefits. One of the major hurdles for the same is the chances of potential herb-drug interactions (HDIs). These HDIs could be beneficial or harmful, or even fatal; therefore, a thorough understanding of the eventualities of HDIs is essential so that a successful integration of the modern and complementary alternative systems of medicine could be achieved. Here, we summarize all the important points related to HDIs, including types, tools/methods for study, and prediction of the HDIs, along with a special focus on interplays between drug metabolizing enzymes and transporters. In addition, this article covers future perspective, with a focus on background endogenous players of interplays and approaches to predict the drug-disease-herb interactions so as to fetch the desired effects of these interactions.

Cysteine-stabilized silver nanoparticles as a colorimetric probe for the selective detection of cysteamine.

The purpose of the present research was to design a method for the colorimetric determination of cysteamine. We have employed cysteine-stabilized silver nanoparticles (AgNPs) as a probe. The addition of cysteamine resulted in the quenching of the 400 nm surface plasmon resonance (SPR) band of the AgNPs. It was accompanied by the appearance of a new absorption band at 560 nm. The colour of the colloidal AgNPs changed from yellow to dark brown within a few seconds. The change in colour of the AgNPs was due to their aggregation induced by the addition of cysteamine. Significantly, other biomolecules such as arginine, asparagine, aspartic acid, cysteine, glutamic acid, glutathione, glycine, methionine and 6-mercaptopurine did not cause any change in the colour of the AgNPs. The limit of detection (LOD) of the method was 0.37 µM. The mechanism of the aggregation of the AgNPs induced by cysteamine has also been described. The method has been applied for the detection of cysteamine in human blood serum.

Encapsulated green magnetic nanoparticles for the removal of toxic Pb2+ and Cd2+ from water: Development, characterization and application.

Current research is based on an innovative approach of the fabrication of encapsulated sustainable, green, phytogenic magnetic nanoparticles (PMNPs), to inhibit the generation of secondary pollutants (Iron/Feo) during water treatment applications. These novel bio-magnetic membrane capsules (BMMCs) were prepared using two-step titration gel crosslink method, with polyvinyl alcohol and sodium alginate matrix as the model encapsulating materials to eliminate potentially toxic metals (Pb2+ and Cd2+) from water. The development of BMMCs was characterized by FTIR, XRD, XPS, SEM, VSM, TGA and EDX techniques. The effects of various operating parameters, adsorbent dose, contact time, solution pH, temperature, initial concentration of metals cations and co-existing ions were studied. The hysteresis loops have illustrated an excellent super-paramagnetic nature, demonstrating the smooth encapsulation of PMNPs without losing their magnetic properties. The maximum monolayer adsorptive capacities estimated at pH 6.5 by the Langmuir isotherm model were 548 and 610.67 mg/g for Pb2+ and Cd2+, respectively. The novel BMMCs did not only control oxidation of PMNPs but also sustained the adsorptive removal over a wide range of pH (3-8), and the electrostatic interaction and ion-exchange were the core adsorption mechanisms. The BMMCs could easily be regenerated using 25% HNO3 as an eluent for successful usage in seven repeated cycles. Therefore, the BMMCs as a material can be used as an excellent sorbent or composite material to remove toxic metals Pb2+ and Cd2+, showing strong potential for improving water and wastewater treatment technologies.

In vitro and in vivo Assessment of Protein Acetylation Status in Mycobacteria.

Protein acetylation is one of the standard post-translational modifications found in proteins across all organisms, along with phosphorylation which regulates diverse cellular processes. Acetylation of proteins can be enzymatically catalyzed through acetyltransferases, acetyl CoA synthetases or non-enzymatically through acyl carrier metabolic intermediates. In this protocol, using response regulator proteins as targets we describe the experimental strategy for probing the occurrence of acetylation using purified recombinant proteins in an in vitro setup. Further using M. smegmatis strains overexpressing the wild type or mutant response regulator protein, we also describe how in vivo acetylation can be validated in Mycobacterial proteins. The described approach can be used for analyzing acetylation of any mycobacterial protein under both in vitro and in vivo conditions.

Development and application of novel bio-magnetic membrane capsules for the removal of the cationic dye malachite green in wastewater treatment.

Novel bio-magnetic membrane capsules (BMMCs) were prepared by a simple two-step titration-gel cross-linking method using a polyvinyl alcohol (PVA) and sodium alginate (SA) matrix to control the disintegration of phytogenic magnetic nanoparticles (PMNPs) in an aqueous environment, and their performance was investigated for adsorbing cationic malachite green (MG) dye from water. The prepared BMMCs were characterized by FTIR, powder XRD, SEM, EDX, XPS, VSM and TGA techniques. The findings revealed that the hysteresis loops had an excellent superparamagnetic nature with saturation magnetization values of 11.02 emu g-1. The prepared BMMCs not only controlled the oxidation of PMNPs but also improved the adsorptive performance with respect to MG dye (500 mg g-1 at 298.15 K and pH 6.5) due to the presence of a large amount of hydrophilic functional groups (hydroxyl/-OH and carboxyl/-COOH) on/in the BMMCs. The smooth encapsulation of PMNPs into the PVA-SA matrix established additional hydrogen bonding among polymer molecular chains, with improved stability, and adsorptive performance was maintained over a wide range of pH values (3-12). Importantly, the prepared BMMCs were easily regenerated just by washing with water, and they could be re-utilized for up to four (4) consecutive treatment cycles without observing any apparent dissolution of iron/Fe0 or damage to the morphology. According to the mass balance approach, an estimated amount of 100 mL of treated effluent can be obtained from 160 mL of MG dye solution (25 mg L-1) just by employing a 0.02 g L-1 adsorbent dosage. Finally, a model of BMMCs based on zero-effluent discharge was also proposed for commercial or industrial applications. The prepared BMMCs are greatly needed for improving the water/wastewater treatment process and they can be utilized as an excellent adsorbent to remove cationic pollutants for various environmental applications.

Appraisal of Cu(ii) adsorption by graphene oxide and its modelling via artificial neural network.

Graphene oxide (GO), as an emerging material, exhibits extraordinary performance in terms of water treatment. Adsorption is a process that is influenced by multiple factors and is difficult to simulate by traditional statistical models. Artificial neural networks (ANNs) can establish highly accurate nonlinear functional relationships between multiple variables; hence, we constructed a three-layered ANN model to predict the removal performance of Cu(ii) metal ions by the prepared GO. In the present research work, GO was prepared and characterized by FT-IR spectroscopy, SEM, and XRD analysis techniques. In ANN modeling, the Levenberg-Marquardt learning algorithm (LMA) was applied by comparing 13 different back-propagation (BP) learning algorithms. The network structure and parameters were optimized according to various error indicators between the predicted and experimental data. The hidden layer neurons were set to be 12, and optimal network learning rate was 0.08. Contour and 3-D diagrams were used to illustrate the interactions of different influencing factors on the adsorption efficiency. Based on the results of batch adsorption experiments combined with the optimization of influencing factors by ANN, the optimum pH, initial Cu(ii) ion concentration and temperature were anticipated to be 5.5, 15 mg L-1 and 318 K, respectively. Moreover, the adsorption experiments reached equilibrium at about 120 min. Combined with sensitivity analysis, the degree of influence of each factor could be ranked as: pH > initial concentration > temperature > contact time.

Spectroscopic investigations on the interaction of thioacetamide with ZnO quantum dots and application for its fluorescence sensing.

The purpose of the present work was to develop a method for the sensing of thioacetamide by using spectroscopic techniques. Thioacetamide is a carcinogen and it is important to detect its presence in food-stuffs. Semiconductor quantum dots are frequently employed as sensing probes since their absorption and fluorescence properties are highly sensitive to the interaction with substrates present in the solution. In the present work, the interaction between thioacetamide and ZnO quantum dots has been investigated by using UV-visible, fluorescence and infrared spectroscopy. Besides, dynamic light scattering (DLS) has also been utilized for the interaction studies. UV-visible absorption studies indicated the bonding of the lone pair of sulphur atom of thioacetamide with the surface of the semiconductor. The fluorescence band of the ZnO quantum dots was found to be quenched in the presence of micromolar concentrations of thioacetamide. The quenching was found to follow the Stern-Volmer relationship. The Stern-Volmer constant was evaluated to be 1.20×105M-1. Infrared spectroscopic measurements indicated the participation of the NH2 group and the sulphur atom of thioacetamide in bonding with the surface of the ZnO quantum dots. DLS measurements indicated that the surface charge of the semiconductor was shielded by the thioacetamide molecules.

Comparative Analysis of 2 Calcium Silicate-based Cements (Biodentine and Mineral Trioxide Aggregate) as Direct Pulp-capping Agent in Young Permanent Molars: A Split Mouth Study.

INTRODUCTION: The purpose of this study was to compare Biodentine and mineral trioxide aggregate (MTA) for direct pulp capping in young permanent molars by clinical and radiographic evaluation in 7- to 9-year-old children. METHODS: In 50 patients, 29 patients with bilateral asymptomatic first permanent molars with carious involvement were selected. According to split mouth design, these patients were then divided into 2 groups, Biodentine group (right side) and MTA group (left side). The pulp-capping procedure was performed by using Biodentine and MTA in 58 asymptomatic bilateral permanent molars with pulp exposure. At each recall (baseline, 6 and 12 months), treatment outcome was assessed clinically through pulpal sensitivity tests as well as radiographically to evaluate dentin bridge formation. RESULTS: The study reported 100% success rate with both Biodentine and MTA at baseline and 6- and 12-month follow-up on the basis of clinical and radiographic parameters. These findings were statistically non-significant (P < .05) between both groups (Biodentine and MTA). Radiographically, dentin bridge formation was not evident with both groups at baseline, but it was evident after 6- and 12-month follow-up. These findings were statistically non-significant (P < .05) in both Biodentine and MTA groups. CONCLUSIONS: This study reported 100% success rate with both MTA and Biodentine when used as direct pulp-capping agent in first permanent molars in 7- to 9-year-old children. The major limitations of the study were smaller sample size and short follow-up period.

Effect of the chemical composition of filter media on the microbial community in wastewater biofilms at different temperatures.

This study investigates the microbial community composition in the biofilms grown on two different support media in fixed biofilm reactors for aerobic wastewater treatment, using next generation sequencing (NGS) technology. The chemical composition of the new type of support medium (TDR) was found to be quite different from the conventionally used support medium (stone). The analysis of 16S rRNA gene fragments recovered from the laboratory scale biofilm system show that biofilm support media and temperature conditions influence bacterial community structure and composition. Greater bacterial diversity was observed under each condition, primarily due to the large number of sequences available and sustenance of rare species. There were 6 phyla found, with the highest relative abundance shown by the phylum Proteobacteria (52.71%) followed by Bacteroidetes (33.33%), Actinobacteria (4.65%), Firmicutes, Verrucomicrobia (3.1%) and Chloroflex (>1%). The dataset showed 17 genera of bacterial populations to be commonly shared under all conditions, suggesting the presence of a core microbial community in the biofilms for wastewater treatment. However, some genera in the biofilms on TDR were observed in high proportions, which may be attributed to its chemical composition, explaining the improved level of wastewater treatment. The findings show that the structure of microbial communities in biofilm systems for wastewater treatment is affected by the properties of support matrix.

Cyanobacteria: A Precious Bio-resource in Agriculture, Ecosystem, and Environmental Sustainability.

Keeping in view, the challenges concerning agro-ecosystem and environment, the recent developments in biotechnology offers a more reliable approach to address the food security for future generations and also resolve the complex environmental problems. Several unique features of cyanobacteria such as oxygenic photosynthesis, high biomass yield, growth on non-arable lands and a wide variety of water sources (contaminated and polluted waters), generation of useful by-products and bio-fuels, enhancing the soil fertility and reducing green house gas emissions, have collectively offered these bio-agents as the precious bio-resource for sustainable development. Cyanobacterial biomass is the effective bio-fertilizer source to improve soil physico-chemical characteristics such as water-holding capacity and mineral nutrient status of the degraded lands. The unique characteristics of cyanobacteria include their ubiquity presence, short generation time and capability to fix the atmospheric N2. Similar to other prokaryotic bacteria, the cyanobacteria are increasingly applied as bio-inoculants for improving soil fertility and environmental quality. Genetically engineered cyanobacteria have been devised with the novel genes for the production of a number of bio-fuels such as bio-diesel, bio-hydrogen, bio-methane, synga, and therefore, open new avenues for the generation of bio-fuels in the economically sustainable manner. This review is an effort to enlist the valuable information about the qualities of cyanobacteria and their potential role in solving the agricultural and environmental problems for the future welfare of the planet.