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Graphene oxide-activated carbon (GO–AC) composite with different ratios of GO and AC (0.5/0.5, 0.3/0.7 and 0.1/0.9) were synthesized via direct chemical bonding of them using hydrogen peroxide as a chemical linker and used for selective removal of diclofenac sodium (DCF) and ibuprofen (IBP) from aqueous solutions. The adsorbents' surface morphology, composition, and physicochemical structure of the adsorbents were characterized by FE-SEM, FTIR, BET and XRD analysis. The synthesized composite with a ratio of GO and AC (0.1/0.9) was the most suitable among the synthesized adsorbents for both DCF and IBP adsorption. The optimal working conditions for DCF removal were at pH of 2, contact time of 40 min, initial concentration of 100 mg/L, and temperature of 293 K. For IBP removal, the optimal operating conditions were at pH of 2, contact time of 60 min, initial concentration of 20 mg/L, and temperature of 293 K. The highest adsorption capacities of 0.1/0.9 composite for DCF and IBP were 833.33 and 238.095 mg/g at 298 K, respectively. Isotherm, kinetic, and thermodynamic characteristics were assessed to analyze the adsorption process. The synthesized adsorbent displays high removal efficiency by simple recyclability with low-cost reagent and high selectivity for drug pollutants such as DCF and IBP in single and binary systems. [ABSTRACT FROM AUTHOR]

Vanadium is considered one of the heavy metals that can be found in crude oil. Since vanadium is toxic to specific refining catalysts, the amount of vanadium in crude oil can affect its selling price. At the same time, it is responsible for equipment corrosion when temperatures reach high enough. This paper investigates vanadium adsorption by two adsorbents named nano-zeolite and alum sludge (residual from a sedimentary tank in a water treatment plant). A batch adsorption unit was selected to determine the effect of different operating factors such as adsorbent dose, agitation speed, temperature, and contact time in vanadium removal. The highest removal efficiency was 89% and 67%, performed at 2 g of nano-zeolite and 4.5 g of alum sludge, respectively, at 500 rpm agitation speed and 80˚C temperature with a contact time of 480 min for nano-zeolite and 420 min for alum sludge. Adsorption isotherm data was fitting to Langmuir and Freundlich models with R2 of 0.9665, 0.9727 for nano-zeolite and 0.9907, 0.9964 for alum sludge, respectively. Pseudo-first-order and pseudo-second-order models show excellent conformity to adsorption kinetic data with R2 of 0.9617, 0.96624 for nano-zeolite, and 0.97494, 0.96515 for alum sludge, respectively

The present work aims to assess the effectiveness and efficiency of orange peels as a low-cost biosorbent for removing Cr(VI) from an aqueous solution by the biosorbent process. The orange peels as adsorbent was characterized using different methods, such as FTIR, pHpzc, equilibrium pH, TGA, XRD, SEM, and (BET). The tests were conducted in the batch mode, and the effects of different parameters, such as the pH, dosage of the bioadsorbent, influent Cr(VI), and time, on the biosorption of Cr(VI) were investigated. The adsorption kinetics proved that a contact time of 90 min resulted in the highest (approximately 97.8%) Cr(VI) removal, with an adsorption capacity of 4.96 mg/g. Moreover, the increase in the biosorbent dosage (from 1 to 10 g/L) resulted in the enhancement in the Cr(VI) removal effectiveness. Moreover, the pH of the solution also affected significantly the effectiveness of the removal. The tests were conducted under acidic pH solution conditions, and the prediction of the pH value at a zero charge (pH pzc) was confirmed experimentally. Furthermore, the results from the batch-mode assays were successfully tested by an experimental design (full factorial design). The biosorption of Cr(VI) on orange peels occurred mostly according to the pseudo-second-order kinetic model and the uptake of Cr(VI) was satisfactorily described by the Langmuir model. [ABSTRACT FROM AUTHOR]

Constructed wetlands (CWs) provide a low-cost, effective solution for domestic wastewater treatment in developing nations compared to costly traditional wastewater systems. Biochar which is an organic material created by pyrolysis offers straightforward, affordable methods for treating wastewater and lowering carbon footprint by acting as a substrate in CWs. Batch mode biochar-amended subsurface flow (SSF) CWs planted with Eclipta alba (L) with a hydraulic retention time (HRT) of 3 days were used for the treatment of rural domestic wastewater in the present investigation. Two control CWs, without plants (C1) and with plants (C2), and five different amendments of biochar 5% (B5), 10% (B10), 15% (B15), 20% (B20) and 25% (B25) in ratio with soil were set up to check the treatment efficiency of CWs. Removal efficiency (RE%) of the CWs for parameters namely chemical oxygen demand (COD), biochemical oxygen demand (BOD), phosphate (PO42−), sulphate (SO42−), nitrate (NO3−) and total Kjeldhal nitrogen (TKN) was determined using standard methods. Removal efficiency of 93%, 91%, 74% and 77% was observed for BOD, COD, nitrate and sulphate, respectively, in the B25 amendment at HRT 72 h. The highest removal of TKN (67%) was also observed in the B25 amendment at HRT of 72 h. No stable trend for the removal of phosphates was found during the study, and maximum removal was observed at HRT 48 h; afterward, phosphate was slightly inclined with the increasing HRT. The findings of one-way ANOVA using Tukey's test show significant variations (p < 0.05) in the removal efficiencies of pollutants after 72 h between two controls (C1 and C2) and various biochar amendments in CWs, indicating a significant role of the wetland plants and concentration of the biochar as substrate. Biochar shows a positive impact on the removal of organic pollutants and nitrates. Hence, biochar-amended CWs can be a sustainable way of treating rural domestic wastewater. [ABSTRACT FROM AUTHOR]

Anaerobic co‐digestion is defined as the simultaneous anaerobic digestion of two or more substrates. Mixing several substrates has many advantages. In particular, it can increase biogas production. In our work, we built a mathematical model to describe the anaerobic co‐digestion of two substrates, with preference and mortality of bacteria in closed mode. The existence and boundedness of positive solutions are investigated. We show that trajectories converge toward a global attractor which is composed of an infinite number of non‐hyperbolic equilibria. The choice of growth functions, for both bacteria, can completely change the performance of the process. Numerical tests are presented to illustrate the theoretical analysis. They allow the prediction of the quantities of the initial mixture for a better biogas production. [ABSTRACT FROM AUTHOR]

BACKGROUND: There is tremendous potential for reusing lignin, which is generally discarded as waste. This research analyses the batch and fed‐batch mode of the microbial peroxide‐producing cell (MPPC), a type of bio‐electrochemical cell that produces H2O2, a potent green oxidant utilized in the oxidation of Kraft lignin to produce platform chemicals with simultaneous wastewater treatment. RESULTS: The batch mode MPPC had a total shelf life of 10 days, with a peak phase of 5 days and maximum H2O2 of 9.7 ± 0.06 mmol L−1, and voltage of 164 ± 0.021 mV. The intermittent nutrition feeding strategy of fed‐batch MPPCs aided microbe metabolic reactions, extending the system's lifespan to 21 days with a maximum voltage of 294 ± 0.01 to 525 ± 0.008 mV and H2O2 of 14.14 ± 0.12 to 32.96 ± 1.35 mmol L−1, respectively. This offered more exposure time for lignin hydroxyl radical oxidation by H2O2, with enhanced depolymerization of 37–80% of high lignin concentration in repeated cycles compared to batch mode, which accomplished only 53.46%. Fourier transform infrared spectroscopy confirmed the structural changes in lignin of all systems, displaying loss and disorientation of major functional groups with greater intensity in fed batch‐operated MPPCs. Platform chemicals with high commercial value, including guaiacol, ferulic acid, vanillin, and others, were identified using liquid chromatography–mass spectrometry. In terms of wastewater treatment, biochemical oxygen demand and chemical oxygen demand removal efficiency ranged from 59% to 83%, with fed‐batch being the most efficient. CONCLUSION: This research suggests that fed‐batch mode MPPC is significantly more productive than batch mode MPPC for lignin valorization to produce platform chemicals, making it more sustainable, economical, and environmentally friendly. © 2023 Society of Chemical Industry (SCI). [ABSTRACT FROM AUTHOR]

The present work aims to assess the effectiveness and efficiency of orange peels as a low-cost biosorbent for removing Cr(VI) from an aqueous solution by the biosorbent process. The orange peels as adsorbent was characterized using different methods, such as FTIR, pHpzc, equilibrium pH, TGA, XRD, SEM, and (BET). The tests were conducted in the batch mode, and the effects of different parameters, such as the pH, dosage of the bioadsorbent, influent Cr(VI), and time, on the biosorption of Cr(VI) were investigated. The adsorption kinetics proved that a contact time of 90 min resulted in the highest (approximately 97.8%) Cr(VI) removal, with an adsorption capacity of 4.96 mg/g. Moreover, the increase in the biosorbent dosage (from 1 to 10 g/L) resulted in the enhancement in the Cr(VI) removal effectiveness. Moreover, the pH of the solution also affected significantly the effectiveness of the removal. The tests were conducted under acidic pH solution conditions, and the prediction of the pH value at a zero charge (pH pzc) was confirmed experimentally. Furthermore, the results from the batch-mode assays were successfully tested by an experimental design (full factorial design). The biosorption of Cr(VI) on orange peels occurred mostly according to the pseudo-second-order kinetic model and the uptake of Cr(VI) was satisfactorily described by the Langmuir model.

In the present research, zeolite is used for the removal of toxic Congo red dye from water solution. The effects of different operating conditions such as hydrogen potential (pH), contact time (time), zeolite dose (D), initial dye concentration (C0), and ionic strength (I) are investigated for Congo red adsorption under batch mode. It was found that the adsorption process was greatly affected by the initial pH of the dye solution. The removal efficiency decreased from 97.68 to 5.22% when the pH varied from 3 to 5; thus, acidic conditions clearly improve Congo red adsorption on zeolite. At pH 3, an increase in C0 and I and decrease in D resulted in an increase in the adsorption capacity qe. The effects of these three parameters and their interactions were also investigated using the 23 full factorial design experiments approach where qe was chosen as the response. The results obtained from this method followed by the analysis of variance and the Student's t-test show that, the influence of these parameters on dye adsorption process are in the order I < C0 < D. The kinetic studies revealed that adsorption follows a pseudo-second-order kinetic model. The adsorption isotherms experimental data were analyzed using the Langmuir, Freundlich, and Temkin isotherms models. The Freundlich isotherm was the best-fit model to the experimental data. The fitting of kinetics and isotherm models was evaluated by using non-linear modeling, R2, MSE, and RMSE. [ABSTRACT FROM AUTHOR]

Polyribosyl-ribitol-phosphate (PRP) from Haemophilus influenzae type b (Hib) is an active immunizing molecule used in the production of the vaccine against H. influenzae, and industrial production could contribute to satisfying a world demand especially in developing countries. In this sense, the aim of this study was to establish a scale-up process using the constant oxygen mass transfer coefficient (kLa) such as the criterion for production of PRP in three different sizes of bioreactor systems. Three different kLa values (24, 52 and 80 h−1) were evaluated in which the biological influence in a 1.5 L bioreactor and 52 h−1 was selected to scale-up the production process until a 75 L pilot-scale bioreactor was achieved. Finally, the fed-batch phase was started under a dissolved oxygen concentration (pO2) at 30% of the saturation in the 75 L bioreactor to avoid oxygen limitation; the performance of production presented high efficiency (9.0 g/L DCW-dry cell weight and 1.4 g/L PRP) in comparison with previous scale-up studies. The yields, productivity and kinetic behavior were similar in the three-size bioreactor systems in the batch mode indicating that kLa is possible to use for PRP production at large scales. This process operated under two stages and successfully produced DCW and PRP in the pilot scale and could be beneficial for future bioprocess operations that may lead to higher production and less operative cost. [ABSTRACT FROM AUTHOR]

A one dimensional (1D) model accounting for the charge and mass transfer, biofilm formation and the electrochemical reactions that occur in a single chamber microbial fuel cell (SCMFC) operated at batch mode was developed. As the authors are aware, this simplified and easy to implement model for this design and operating mode is unique. The assumptions performed on the model development and the set of parameters used in the model predictions were carefully considered and chosen based on the operating and design conditions and following recommendations from literature. Despite the simplifications and assumptions performed, the model predictions are in good agreement with the experimental data, with a maximum power density of 36.7 mW/cm2. The model predictions concerning the effect of the substrate concentration at the biofilm, anode and cathode overpotentials, cell voltage, current density and power density were also studied. The substrate concentration showed a higher impact on the anode overpotential for the medium to high current density values and predicted well the decrease in substrate availability for increasing current densities and higher anodic reaction rates. The model is rapidly implemented using simple numerical tools (like Excel and Matlab) being, therefore, suitable to seek for possibilities of optimizing the performance of a SCMFC by studying the impact of variations on the design parameters (such as membrane thickness, catalyst loading, electrodes type and thicknesses) and operating conditions (such as substrate concentration). This work demonstrated the value of the developed model in understanding the phenomena behind the MFC systems and on developing more efficient systems, towards an increase of their power output. • A model for a single chamber microbial fuel cell operated at batch mode was developed. • The one dimensional model couples charge and mass transfer, kinetics and biofilm formation. • The model predicts the effect of operating and design conditions on the cell behavior. • The model predictions are in good agreement with the experimental data. • For the design and operating mode considered, the model presented is unique. [ABSTRACT FROM AUTHOR]

The need for water is certainly very alarming in the Middle East and North Africa (MENA) region where water demand for domestic, agriculture, and industrial applications continue to increase, and on the other hand, water resources are increasingly becoming scarce (low precipitation and depletion of renewable groundwater). Inland desalination process in off-grid or remote areas contributes a significant portion to the water supply in Saudi Arabia. However, inland desalination systems have many challenges to be well implemented such as limited water distribution, water transmission cost from seawater desalination plants to the inland area. Many wells in Saudi Arabia have relatively high salinity water, which is not directly usable. This study aims to find the best hybrid diesel-photovoltaic powered reverse osmosis (RO) system to desalinate brackish water that has 6,000 ppm salinity for a remote area near Ummluj City in the Kingdom. Each RO system produces 202 m3/d for two purposes: drinking and household purposes. A batch mode that operates 5 h/d is studied. The hybrid system composed of conventional and renewable energy systems driven brackish RO system are modelled using ROSA and HOMER software. Besides, the advantages of adding a pressure exchanger (PX) and a second-stage are investigated. Further, the effect of the fuel price on the cost of water production is analysed. It was found that adding a second storage tank for household applications with 1,000 ppm reduces the levelized cost of water by 11%. Furthermore, using a pressure exchanger leads to 26% reduction in the specific energy consumption (SEC) while adding a second-stage reduces the SEC by 22%. However, adding PX is economically feasible for fuel price higher than 40 USD/L. [ABSTRACT FROM AUTHOR]

Phenol is a recalcitrant anthropogenic compound whose presence has been reported in both wastewater and drinking water; human exposure to phenolic substances can lead to health problems. The degradation of phenol (measured as COD decrease) through solar heterogeneous photocatalysis with immobilized TiO2 was performed in two different reactors: a flat-plate reactor (FPR) and a compound parabolic collector (CPC). A 23 full factorial experimental design was followed. The variables were the presence of TiO2, H2O2 addition, and the type of reactor. Data were fitted to the pseudo-first-order reaction-rate-kinetics model. The rate constant for photocatalytic phenol degradation with 1 mM of H2O2 was 6.6 × 10−3 min−1 for the FPR and 5.9 × 10−3 min−1 in the CPC. The calculated figures of merit were analyzed with a MANCOVA, with UV fluence as a covariate. An ANCOVA showed that the type of reactor, H2O2 addition, or fluence had no statistically significant effect on the results, but there was for the presence of TiO2. According to the MANCOVA, fluence and TiO2 presence were significant (p < 0.05). The CPC was on average 17.4% more efficient than the FPR when it came to collector area per order (ACO) by heterogeneous photocatalysis and 1 mM H2O2 addition. [ABSTRACT FROM AUTHOR]

Vinasse, a sugar-ethanol residue, is used as a substrate for biogas production. The characteristics of the vinasse wastewater used were 216,000 mg-COD/L, pH 4.1, and 68.42 mg/L volatile solids. The sludge/wastewater ratio was controlled at about 1.5−2.0, by weight. Biogas production enhancement was studied in relation to two parameters – Citadel BioCat + , a commercial biocatalyst containing a large microorganism population as the methanogenic bacteria source (5 and 10 g), and reaction temparature (30 and 37 °C). Biogas production kinetics were evaluated. The presence of the biocatalyst enhanced biogas production significantly, as well as reducing the time required for anaerobic digestion. The first-order kinetic model described the biodegradation process. The best results were found using 10 g of biocatalyst at 37 °C – i.e., the optimum results based on biogas production potential (A), the highest biogas production rate (U), the minimum biogas production time (λ), and kinetic organic biodegradability constants (k) of 102.71 mL/g-COD, 11.17 mL/g-COD/d, 0.95 day, and 0.0533 day−1, respectively. COD removal efficiency was up to 60%. Highlights The presence of a biocatalyst enhanced biogas production and reduced processing time.; Up to 60% of the COD from vinasse wastewater was degraded.; The biocatalyst can reduce the time required to produce biogas.;

Water purification using adsorption is a crucial process for maintaining human life and preserving the environment. Batch and dynamic adsorption modes are two types of water purification processes that are commonly used in various countries due to their simplicity and feasibility on an industrial scale. However, it is important to understand the advantages and limitations of these two adsorption modes in industrial applications. Also, the possibility of using batch mode in industrial scale was scrutinized, along with the necessity of using dynamic mode in such applications. In addition, the reasons for the necessity of performing batch adsorption studies before starting the treatment on an industrial scale were mentioned and discussed. In fact, this review article attempts to throw light on these subjects by comparing the biosorption efficiency of some metals on utilized biosorbents, using both batch and fixed-bed (column) adsorption modes. The comparison is based on the effectiveness of the two processes and the mechanisms involved in the treatment. Parameters such as biosorption capacity, percentage removal, and isotherm models for both batch and column (fixed bed) studies are compared. The article also explains thermodynamic and kinetic models for batch adsorption and discusses breakthrough evaluations in adsorptive column systems. The review highlights the benefits of using convenient batch-wise biosorption in lab-scale studies and the key advantages of column biosorption in industrial applications. [Display omitted] • Adsorption properties of batch and dynamic modes of biosorption were scrutinized in different conditions. • The key advantages and drawbacks of each mode were mentioned. • The benefits of exploitation of each mode were explained depending on the application purpose. • Comparison between batch and dynamic modes of biosorption revealed limitations of the former. • The switch to the dynamic mode seems to be necessary for practical applications. [ABSTRACT FROM AUTHOR]

Abundant data with limited labeling are a widespread bottleneck in multilabel learning. Active learning (AL) is an effective solution to gradually enhance model robustness, however how to effectively extend instance selection criteria to multilabel case remains challenging. Considering the label specificity and label correlation, a granular batch mode-based ranking active model for the multilabel (GBRAML) is proposed. Taking a bottom-up view, three granulation operators are successively constructed to formulate three granular structures. In low-level granulation operator, auxiliary label is introduced to enhance the informativeness and representativeness of each label. The contribution of labels to the usefulness of instances is incorporated with pair-wise label correlation, and is considered in the middle-level granulation operator. The labeling priority is determined by ranking the scorings coming from high-level granulation operator. To alleviate the impact of skewed label correlation, we take a three-way strategy on fitness of representative label correlation, thus a three-way GBRAML model (TGBRAML) is devised. Extensive experiments on six multilabel benchmark demonstrate GBRAML gains 5.4% and 210.1% improvement on MicroF1 and Average Precision over state-of-the-art batch mode multilabel active learning. The effectiveness of three-way decisions in multilabel AL is also verified. [ABSTRACT FROM AUTHOR]

In present study, growth of Anabaena ambigua was examined by supplying CO2 to a 5 L external loop airlift photobioreactor. Carbon dioxide was supplied for different time periods (control, 2 min, 4 min and 6 min) in the batch mode for every 12 hours at constant flow rates of 2 L min-1, 3 L min-1 and 4 L min-1. For different combinations of CO2 supplied viz., different time periods (control, 2 min, 4 min and 6 min) with different flow rates (2 L min-1, 3 L min-1 and 4 L min-1), the biomass of Anabaena ambigua was measured once the culture reached stationary phase. Results revealed that maximum biomass of 0.926 g L-1 was obtained when CO2 was supplied for 2 min at a flow rate of 3 L min-1, which was even found statistically significant by Two-way ANOVA method. [ABSTRACT FROM AUTHOR]

The ability of anaerobic digestion to create value from waste gives it an important role in reducing greenhouse gas emissions and in the transition to a circular economy. For a better understanding of the digestion process and in order to reduce the number of time-consuming batch tests, an analytical model was developed to describe the kinetics of biogas production. Assuming that the organic fraction of the substrate has different degradation rates, the whole process was modelled as two groups of 1st order reactions.The model was tested with published data and showed an excellent performance in reproducing the experimental information. Moreover, its kinetic constants provided a useful insight into the internal processes of anaerobic digestion and the substrate characteristics. Given its accuracy in fitting the data, the model can be used as an auxiliary tool to determine the biogas potential, presenting itself as the most complete empirical model currently available.

iCn3D was initially developed as a web-based 3D molecular viewer. It then evolved from visualization into a full-featured interactive structural analysis software. It became a collaborative research instrument through the sharing of permanent, shortened URLs that encapsulate not only annotated visual molecular scenes, but also all underlying data and analysis scripts in a FAIR manner. More recently, with the growth of structural databases, the need to analyze large structural datasets systematically led us to use Python scripts and convert the code to be used in Node. js scripts. We showed a few examples of Python scripts at https://github.com/ncbi/icn3d/tree/master/icn3dpython to export secondary structures or PNG images from iCn3D. Users just need to replace the URL in the Python scripts to export other annotations from iCn3D. Furthermore, any interactive iCn3D feature can be converted into a Node. js script to be run in batch mode, enabling an interactive analysis performed on one or a handful of protein complexes to be scaled up to analysis features of large ensembles of structures. Currently available Node. js analysis scripts examples are available at https://github.com/ncbi/icn3d/tree/master/icn3dnode. This development will enable ensemble analyses on growing structural databases such as AlphaFold or RoseTTAFold on one hand and Electron Microscopy on the other. In this paper, we also review new features such as DelPhi electrostatic potential, 3D view of mutations, alignment of multiple chains, assembly of multiple structures by realignment, dynamic symmetry calculation, 2D cartoons at different levels, interactive contact maps, and use of iCn3D in Jupyter Notebook as described at https://pypi.org/project/icn3dpy.

In the present research, zeolite is used for the removal of toxic Congo red dye from water solution. The effects of different operating conditions such as hydrogen potential (pH), contact time (time), zeolite dose (D), initial dye concentration (C0), and ionic strength (I) are investigated for Congo red adsorption under batch mode. It was found that the adsorption process was greatly affected by the initial pH of the dye solution. The removal efficiency decreased from 97.68 to 5.22% when the pH varied from 3 to 5; thus, acidic conditions clearly improve Congo red adsorption on zeolite. At pH 3, an increase in C0 and I and decrease in D resulted in an increase in the adsorption capacity qe. The effects of these three parameters and their interactions were also investigated using the 23 full factorial design experiments approach where qe was chosen as the response. The results obtained from this method followed by the analysis of variance and the Student’s t-test show that, the influence of these parameters on dye adsorption process are in the order I < C0 < D. The kinetic studies revealed that adsorption follows a pseudo-second-order kinetic model. The adsorption isotherms experimental data were analyzed using the Langmuir, Freundlich, and Temkin isotherms models. The Freundlich isotherm was the best-fit model to the experimental data. The fitting of kinetics and isotherm models was evaluated by using non-linear modeling, R2, MSE, and RMSE.

Abstract The kinetic profiles of Candida tropicalis TISTR 5306 cultivation based on modified yeast-malt (MYM), assorted grade fresh longan juice (AsgLG) and longan solid waste extract (LSWE) medium were evaluated in 1 l batch mode. The highest ethanol concentration level (25.5 ± 0.8 g/l) and ethanol yield - Yp/s of 0.491 ± 0.017 g ethanol/g consumed substrate, dried biomass concentration level (9.44 ± 0.05 g/l) and dried biomass yield - Yp/s of 0.533 ± 0.170 g dried biomass/g consumed substrate, specific pyruvate decarboxylase (PDC) activity (0.037 ± 0.003 U/mg protein) were achieved (p ≤ 0.05) in AsgLG medium. Scores ranking strategy were employed and AsgLG medium was subsequently selected with in the highest total score (p ≤ 0.05) of 698 ± 7 at 48 h. The cultivation in fed-batch mode with three rounds of pulse feeding (PF) in 1 l AsgLG medium was carried out. The apparent highest ethanol and dried biomass concentration levels with corresponding yields relative to time zero were (28.3 ± 0.5 g/l, 0.482 ± 0.012 g/g) at 120 h of PF2 and (9.39 ± 0.04 g/l, 0.110 ± 0.001 g/g) at 192 h of PF3. The maximum specific PDC activity was 0.057 ± 0.006 U/mg protein during PF1 feeding.

• Locally estimated prediction uncertainty and sampling utility metrics are introduced for active learning. • An effective batch-mode active learning algorithm is introduced based on the proposed metrics. • Experimental results on two time series data demonstrate the effectiveness of the proposed method. Although the one nearest neighbor approach is widely used in time series classification, its successful performance requires enough labeled data, which is often difficult to obtain due to a high labeling cost. This article considers a practical classification scenario in which labeled data are scant but unlabeled data are plenty, and a limited budget for the annotating task is provided. For an effective classification with limited resources, we propose a nearest neighbor-based sampling strategy for active learning. The proposed approach uses highly local information to measure the uncertainty and utility of an unlabeled instance and is applicable to extremely sparse labeled data. Furthermore, we extend the proposed approach to batch mode active learning to select a batch of informative samples at each sampling iteration. Experimental results on the WAFER and ECG5000 data sets demonstrate the effectiveness of the proposed algorithm as compared with other nearest neighbor-based approaches. [ABSTRACT FROM AUTHOR]

Capacitive deionization (CDI) is a promising and rapidly growing technology for water treatment and the electrode materials play a key role in improving CDI performance. In this study, high surface area activated carbon was prepared from chicken feather (CF) bio-waste through pyrolysis and KOH activation; the KOH:CF ratio (R) and activation temperature (Ta) were variable parameters. The material was characterized by using the Brunauer, Emmett and Teller (BET) method, Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). The lead (Pb2+) removal test was performed with a CDI cell containing the fabricated carbon electrode and 100 mg L−1 Pb(NO3)2 solution; the sample prepared with the ratio R of 1:1 and Ta = 800 °C exhibited higher Pb2+ removal efficiency of 81% and electro sorption capacity of 4.1 mg g−1 at the electrode potential 1.2 V and flow rate 5 mL min−1. Therefore, CF-derived carbon is considered as a promising CDI electrode material for removal of heavy metals from waste water.

Polyribosyl-ribitol-phosphate (PRP) from Haemophilus influenzae type b (Hib) is an active immunizing molecule used in the production of the vaccine against H. influenzae, and industrial production could contribute to satisfying a world demand especially in developing countries. In this sense, the aim of this study was to establish a scale-up process using the constant oxygen mass transfer coefficient (kLa) such as the criterion for production of PRP in three different sizes of bioreactor systems. Three different kLa values (24, 52 and 80 h−1) were evaluated in which the biological influence in a 1.5 L bioreactor and 52 h−1 was selected to scale-up the production process until a 75 L pilot-scale bioreactor was achieved. Finally, the fed-batch phase was started under a dissolved oxygen concentration (pO2) at 30% of the saturation in the 75 L bioreactor to avoid oxygen limitation; the performance of production presented high efficiency (9.0 g/L DCW-dry cell weight and 1.4 g/L PRP) in comparison with previous scale-up studies. The yields, productivity and kinetic behavior were similar in the three-size bioreactor systems in the batch mode indicating that kLa is possible to use for PRP production at large scales. This process operated under two stages and successfully produced DCW and PRP in the pilot scale and could be beneficial for future bioprocess operations that may lead to higher production and less operative cost.

Phenol is a recalcitrant anthropogenic compound whose presence has been reported in both wastewater and drinking water; human exposure to phenolic substances can lead to health problems. The degradation of phenol (measured as COD decrease) through solar heterogeneous photocatalysis with immobilized TiO2 was performed in two different reactors: a flat-plate reactor (FPR) and a compound parabolic collector (CPC). A 23 full factorial experimental design was followed. The variables were the presence of TiO2, H2O2 addition, and the type of reactor. Data were fitted to the pseudo-first-order reaction-rate-kinetics model. The rate constant for photocatalytic phenol degradation with 1 mM of H2O2 was 6.6 × 10−3 min−1 for the FPR and 5.9 × 10−3 min−1 in the CPC. The calculated figures of merit were analyzed with a MANCOVA, with UV fluence as a covariate. An ANCOVA showed that the type of reactor, H2O2 addition, or fluence had no statistically significant effect on the results, but there was for the presence of TiO2. According to the MANCOVA, fluence and TiO2 presence were significant (p < 0.05). The CPC was on average 17.4% more efficient than the FPR when it came to collector area per order (ACO) by heterogeneous photocatalysis and 1 mM H2O2 addition.

• Successful immobilizations of laccase on eggshell membrane with different protocols • Immobilized dropped laccase protected 45% of activity for six cycles • Immobilization process improved the kinetic behavior of laccase • The biocatalyst showed an excellent ability to remove syringic acid Eggshell membrane, an eco-compatible, safe and cheap by-product was employed as carrier for the laccase from Trametes versicolor immobilization. In order to evaluate the best protocol to apply for the syringic acid degradation, two different types of laccase loading on eggshell membrane were used by incubation in solution or by enzyme-dropping. Chemicals (covalent) and physicals (adsorption) immobilizations were tested for both procedure using native or periodate-oxidized laccase. It is shown that immobilization of periodate-oxidized laccase on NiCl 2 -pretreated eggshell membrane was the best method for the first procedure (immobilized activity 1300 U/Kg, a residual activity of 30 % for 6 reuse). For the enzyme-dropping protocol a covalent method with the bifunctional cross linker (glutaraldehyde) was the best method (immobilized activity 3500 U/Kg, a residual activity of 45 % for 6 reuse). [ABSTRACT FROM AUTHOR]

Methylthionine chloride (MTC) is a compound with several applications both in the clinical and medical industries. Nevertheless, such compounds can become an environmental problem, as they are not properly treated by wastewater treatment plants. This objective of this work was to study MTC degradation in a flat plate reactor through solar photolysis and heterogeneous photocatalysis processes with TiO2 as a catalyst. In addition to the processes, three pH (3.5, 6.5, and 9) and the effect of H2O2 addition (no dose, 0.5, and 1 mM/L) were tested. The results show that acidic pH is the most appropriate for MTC degradation, which ranged between 56% and 68.7% for photolysis and between 76% and 86.7% in photocatalysis. The H2O2 addition resulted in lower degradation in all cases, leading the authors to conclude that the presence of peroxide actually hinders degradation in solar photolysis and photocatalysis processes. Statistical analysis showed that the constant rate reactions calculated for every process, under the same conditions of pH and H2O2 addition, are significantly different from one another, and the three factors considered for experimental design (process, pH, and H2O2) have a statistically significant effect on MTC degradation. The collector area per order confirmed higher efficiency for photocatalysis when compared to photolysis processes.

This study was developed based on the possibility of reusing and valuing the alginate extraction residue (RES) from the algae Sargassum filipendula. The adsorptive properties of RES were explored through kinetic and equilibrium assays in batch mode, in which the kinetic equilibrium time (200 min) was not influenced by the increase of the initial concentration of Ni solutions and the sorption process was favored by the temperature increase. The modeling revealed the simultaneous occurrence of physical and chemical interactions with the external diffusion as the predominant step. The Langmuir model was more representative for the equilibrium results, with an uptake capacity comparable to that of other biomaterials. The thermodynamic study indicated a spontaneous, favorable, and endothermic process, besides the presence of the ion exchange. The isoelectric point was found at pH 5.3, and the pore size distribution allowed the classification of RES as macroporous. The simplified bath sorption design revealed that the required mass of RES become greater for higher quality degrees. However, it is tenable to consider this process viable due to the easy access to the algae biomass and the large amount of the solid waste generated from the alginate extraction (∼50%), termed as residue (RES). [ABSTRACT FROM AUTHOR]

This article summarizes the results of a research study that was focused on the possibility of removing Cr (VI) from aqueous solution, using low-cost waste biomaterial in a batch mode. A set of seven biosorbents was used: Fomitopsis pinicola, a mixture of cones, peach stones, apricot stones, Juglans regia shells, orange peels, and Merino sheep wool. Three grain fractions (fr. 1/2, fr. 0.5/1.0, and fr. 0/0.5 mm) of biosorbents were studied. The aim was to find the most suitable biosorbent that can be tested with real samples. The influence of other factors on the course of biosorption was studied as well (chemical activation of the biosorbent, pH value, rotation speed during mixing, temperature, and the influence of biosorbent concentration). The use of chemical activation and adjustment of the pH to 1.1 to 2.0 make it possible to increase their sorption capacity and, for some biosorbents, to shorten the exposure times. Two kinetic models were used for the analysis of the experimental data, to explain the mechanism of adsorption and its possible speed control steps: pseudo-first and pseudo-second-order. The pseudo-second-order kinetic model seems to be the most suitable for the description of the experimental data. The thermodynamic parameters suggest that the biosorption was endothermic and spontaneous. In the biosorption equilibrium study, the adsorption data were described by using Langmuir and Freundlich adsorption isotherms. The Langmuir model was applicable to describe the adsorption data of all biosorbents. Both models are suitable for chemically treated sheep fleece and peach stones.

The integrated bacterial mixed culture consortium with disproportionate oxygen demand was discovered to mutually cooperate with one single biofilm in oxidizing sulfide at different concentration. The present work was carried out to verify the potential of bacterial mixed culture (BMC) in developing a predictive optimum condition for sulfide oxidation in a laboratory batch mode. A face centered central composite design (FCCCD) under response surface methodology (RSM) was employed to predict the synergistic effects of initial hydrogen sulfide concentration (100–500 ppm), temperature (30–40 °C) and aeration rates (50–250 vvm) on BMC sulfide oxidation. A total number of 20 experimental runs with 6 centre points were carried out. The obtained results were analyzed using design expert and statistical validation indices to check the adequacy of the obtained quadratic models. The analysis of variance showed that more than 99% of the variation was explained by the models. There was a good agreement between experimental and predicted data. The optimum sulfide removal of 448.75 ppm was achieved at the temperature of 32.4 °C, initial hydrogen sulfide of 500 ppm and aeration rates of 110.06 vvm in 8 h. Therefore, the finding depicts the adequacy of the obtained model in enhancing BMC sulfide oxidation conditions. The model is further affirmed through SEM-EDXS analysis, revealing oxidized sulfide product aggregate of the micrographs coupled with elemental identification and quantitative composition. [ABSTRACT FROM AUTHOR]

Batch mode studies were carried out for investigating the removal efficiency of sawdust carbon prepared by sulphuric acid treatment of Indian Rosewood sawdust for aqueous bivalent nickel ions. Experiments involved the study of influence of varying the parameters like pH, contact period, the initial strength of adsorbate, temperature, agitation speed and dosage of adsorbent on scavenging of adsorbate ions. Characterization of adsorbent has been done using FTIR, SEM-EDX, BET surface area and CHNSO elemental analysis. Adsorption isothermal studies are in good agreement with the Langmuir isotherm model. The highest calculated value of the correlation coefficient suggested Pseudo-second order reaction kinetics for adsorption of nickel bivalent ions on sawdust carbon. Exothermic nature and spontaneity of removal of nickel ions were shown by thermodynamic parameters. Desorption experiments were accomplished using HCl solutions of varying concentrations. High percentage adsorption of sawdust carbon adsorbent observed for Ni (II) ions indicated that it could be efficiently employed for scavenging of aqueous Ni (II) metal ions. [ABSTRACT FROM AUTHOR]

The biological removal of gaseous sulfur dioxide using the sulfate reducing bacteria Desulfovibrio desulfuricans is studied. Laboratory-scale bioreactors were designed to generate sulfur dioxide in them through a chemical reaction. To evaluate the biological reduction, three kinetics (in triplicate) were taken in batch mode with loads of 15, 20 and 25 mmol of SO 2 generated in the gas phase per liter of culture medium in the liquid phase. Lactate was used as substrate (electron donor) and carbon source. The experimental results showed a 100% SO 2 reduction for all the evaluated loads. The tests lasted 24, 72 and 192 h, with lower, intermediate and higher loads, respectively. The total sulfide (S 2− ) produced varied between 75 and 126 mg for the tests with lower and higher load, respectively. These amounts were composed of a fraction in the aqueous phase (287 and 533 mg of S 2− /L) and another in the gas phase (0.9 × 10 8 and 2.7 × 10 8 μg H 2 S/m 3 ). The mass ratio between product formation (sulfide) and electron donor consumption (expressed as COD) ranged from 81% to 90% of the theoretical value (0.67 mg of sulfide produced per mg of COD consumed). [ABSTRACT FROM AUTHOR]

Ceramic membranes (CMs) with different pore sizes (0.14 μm CM1, 150 kDa CM2 and 5 kDa CM3) were tested as separators in two-chamber microbial fuel cells (MFCs). The performance and ionic gradient concentration of MFCs using CMs were compared with that of cation exchange membrane (CEM), Nafion 117. MFC with CMs exhibited a higher performance than that of CEM under batch operation. The highest power density of 1790 ± 60 mW/m 2 , columbic efficiency (CE) of 41 ± 10% and internal resistance of 102 ± 13 Ω were obtained for MFC with CM3 under batch mode operation. The highest power density, columbic efficiency and internal resistance of MFC with CEM were found to be 1225 ± 20 mW/m 2 , 21 ± 1% and 400 ± 10 Ω, respectively. The highest performance of MFC with CM3 was expected due to a higher porosity of CM3 (13.8%) compared with that of CM1 (11.0%) and CM2 (11.05%). MFCs operated with catholyte containing salt solution, phosphate buffer basal medium without carbon source and yeast extract (PBBM-SA), generated lower current than with phosphate buffer (PB) as catholyte. This difference was more significant in the MFCs with the CEM Nafion 117 than with ceramic membranes. The non-selective porous ceramic membranes improved the diffusion of protons in the presence of other high concentration cations and resulted in MFC with higher performance. Hence, the porous ceramic membrane is a potential candidate separator for the development of commercial scale MFCs. [ABSTRACT FROM AUTHOR]

To cope with the unprecedented traffic explosion, Internet giants are urged to rethink their data center design. Unfortunately, the conventional wired data centers struggle to support the impressive growth of both data and online services. In this regard, we resort to augmenting the wired data center network (DCN) with wireless communication (60 GHz technology). Heretofore, only few research work have dealt with the optimization of multi-hop communications in such hybrid DCN (HDCN) infrastructures. In this paper, we investigate, in HDCN, the issue of jointly: 1) routing and 2) channel allocating, in both online and batch arrival modes. First, we formulate the online joint routing and channel assignment problem as a minimum weighted perfect matching problem. We propose a new strategy named joint routing and channel allocation algorithm that makes use of the Blossom algorithm and sequentially computes the optimal routing communication paths. Second, to handle the batched arrivals of flows, we formulate the batch joint routing and channel assignment problem as an advanced multi-commodity flow model. We propose two scalable approaches: 1) a heuristic based solution, named joint routing and channel assignment heuristic and 2) an approximate solution, named scalable joint batch routing and channel allocation, based on the Lagrangian relaxation technique. Based on extensive network simulations conducted in QualNet simulator while considering the full protocol stack, the obtained results for both: 1) real Facebook’s data center and 2) uniform, traces, show that our schemes outperform the related strategies. [ABSTRACT FROM PUBLISHER]

The removal of phosphates from aqueous solutions by adsorption onto date palm fibers (DPF) has been studied in batch mode. The aim of this study was to understand the mechanisms that govern phosphate sorption and find an appropriate model for the kinetics of removal. In order to investigate the mechanism of sorption and potential rate controlling steps, pseudo first-order, pseudo second-order, intra-particle diffusion and the Elovich equations have been used to test experimental data. Kinetic analysis of the four models has been carried out for initial phosphate concentration in the range of 30–110 mg/L. The rate constants for the four models have been determined and the correlation coefficients have been calculated in order to assess which model provides the best fit predicted data with experimental results. Seven statistical functions were used to estimate the error deviations between experimental and theoretically predicted kinetic adsorption values, including the average relative error deviation (ARED), Marquardt’s percent standard error deviation (MPSED), the hybrid fractional error function (HYBRID), the sum of the squares of the errors (SSE) and three alternative statistical functions, including the Chi-square test, the F-test and Student’s T-test. The results showed that, both Elovich equation and pseudo second-order equation provide the best fit to experimental data for different initial phosphate concentrations.

Techniques that combine multiple types of features, such as spectral and spatial features, for hyperspectral image classification can often significantly improve the classification accuracy and produce a more reliable thematic map. However, the high dimensionality of the input data and the typically limited quantity of labeled samples are two key challenges that affect classification performance of supervised methods. In order to simultaneously deal with these issues, a regularized multimetric active learning (AL) framework is proposed which consists of three main parts. First, a regularized multimetric learning approach is proposed to jointly learn distinct metrics for different types of features. The regularizer incorporates the unlabeled data based on the neighborhood relationship, which helps avoid overfitting at early stages of AL, when the quantity of training data is particularly small. Then, as AL proceeds, the regularizer is also updated through similarity propagation, thus taking advantage of informative labeled samples. Finally, multiple features are projected into a common feature space, in which a new batch-mode AL strategy combining uncertainty and diversity is utilized in conjunction with k-nearest neighbor classification to enrich the set of labeled samples. In order to evaluate the effectiveness of the proposed framework, the experiments were conducted on two benchmark hyperspectral data sets, and the results were compared to those achieved by several other state-of-the-art AL methods. [ABSTRACT FROM PUBLISHER]