Two-stage process described in the present work is a combination of dark and photofermentation in a sequential batch mode. In the first stage glucose is fermented to acetate, CO2 and H2 in an ...anaerobic dark fermentation by Enterobacter cloacae DM11. This is followed by a successive second stage where acetate is converted to H2 and CO2 in a photobioreactor by photosynthetic bacteria, Rhodobacter sphaeroides O.U. 001. The yield of hydrogen in the first stage was about 3.31molH2(molglucose)-1 (approximately 82% of theoretical) and that in the second stage was about 1.5–1.72molH2(molaceticacid)-1 (approximately 37–43% of theoretical). The overall yield of hydrogen in two-stage process considering glucose as preliminary substrate was found to be higher compared to a single stage process. Monod model, with incorporation of substrate inhibition term, has been used to determine the growth kinetic parameters for the first stage. The values of maximum specific growth rate (μmax) and Ks (saturation constant) were 0.398h-1 and 5.509gl-1, respectively, using glucose as substrate. The experimental substrate and biomass concentration profiles have good resemblance with those obtained by kinetic model predictions. A model based on logistic equation has been developed to describe the growth of R. sphaeroides O.U 001 in the second stage. Modified Gompertz equation was applied to estimate the hydrogen production potential, rate and lag phase time in a batch process for various initial concentration of glucose, based on the cumulative hydrogen production curves. Both the curve fitting and statistical analysis showed that the equation was suitable to describe the progress of cumulative hydrogen production.
Within the transport layer security (TLS) protocol version 1.3, RFC 7748 specifies elliptic curves targeted at the 128-bit and the 224-bit security levels. For the 128-bit security level, the ...Montgomery curve Curve25519 and its birationally equivalent twisted Edwards curve Ed25519 are specified; for the 224-bit security level, the Montgomery curve Curve448, the Edwards curve Edwards448 (which is isogenous to Curve448) and another Edwards curve which is birationally equivalent to Curve448 are specified. Our first contribution is to provide the presently best known 64-bit assembly implementations of Diffie–Hellman shared secret computation using Curve25519. The main contribution of this work is to propose new pairs of Montgomery–Edwards curves at the 128-bit and the 224-bit security levels. The new curves are
nice
in the sense that they have very small curve coefficients and base points. Compared to the curves in RFC 7748, the new curves lose two bits of security. The gain is improved efficiency. For Intel processors, we have made different types of implementations of the Diffie–Hellman shared secret computation using the new curves. The new curve at the 128-bit level is faster than Curve25519 for all types of implementations that we considered, while the new curve at the 224-bit level is faster than Curve448 using 64-bit sequential implementation using schoolbook multiplication, but is slower than Curve448 for vectorized implementation using Karatsuba multiplication. Overall, the new curves provide good alternatives to Curve25519 and Curve448.
The fabrication of SERS substrate by gold nanoparticle–decorated polyvinyl alcohol electrospun nanofibers which has been used to detect trace sensing of two widely used poultry antibiotics ...doxycycline hydrochloride and enrofloxacin is demonstrated. The performance of the backscattered Raman signals from the proposed SERS substrate has been initially evaluated with two standard Raman active compounds namely malachite green and rhodamine-6G. The limit of detection of the proposed substrate is estimated to be 7.32 nM. Following this, the usability of the proposed SERS substrate has been demonstrated through the detection of the aforementioned antibiotics in chicken meat samples. The presence of antibiotics in chicken meat sample has been validated with the standard analytical tool of liquid chromatography-mass spectrometry and the results were compared with the proposed sensing technique. Further, principal component analysis has been performed to classify the antibiotics that are present in the field-collected meat samples.
Graphical Abstract
A continuous indirect electro-oxidation (EO) process was developed using graphite electrode to investigate the treatability of reactive turquoise blue RTB21 dye wastewater under specific operating ...conditions of initial pH, current density, hydraulic retention time (HRT), and electrolyte (NaCl) concentration. The experiments were performed in accordance with the central composite design (CCD), and the findings were used to create a model utilizing artificial neural networks (ANNs). According to the predicted findings of the ANN model, the MSE values for colour and COD removal efficiencies were estimated to be 0.748 and 0.870, respectively, while the R2 values were 0.9999 and 0.9998, respectively. The Multi-objective optimization using genetic algorithm (MOGA) over the ANN model maximizes the multiple responses: colour and COD removal efficiency (%). The MOGA generates a non-dominated Pareto front, which provides an insight into the process’s optimum operating conditions.
Separation of sulfuric acid from a dilute solution involved a plate and frame type electrodialysis unit using a commercial anion exchange membrane. Experiments were conducted in batch with catholyte ...concentrations ranging from 1 to 5 wt%. Effect of applied current density, initial catholyte concentration and initial concentration difference of catholyte and anolyte on the molar flux was studied extensively. The maximum molar flux was estimated to be 10.52×10
-8
mol cm
-2
s
-1
at 4.45 wt% catholyte concentration and applied current density of 30 mA cm
-2
. Current efficiencies were observed to be 75 to 85% at lower current density, which rose to more than 100% at 20 and 30mA cm
-2
, at equal initial concentration of catholyte and anolyte. Diffusive flux and flux due to membrane potential contributed very less compared to total flux in presence of applied electric current. An equation was developed to predict the practical molar fluxes, which fitted satisfactorily with minor standard deviation. Pristine and used membrane specimens were characterized using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM).
When the partial pressure of H₂ was decreased by lowering the total pressure in the headspace of the reactor in a batch fermentation process from 760 mm Hg to 380 mm Hg containing Enterobacter ...cloacae, the molar yield of H₂ increased from 1.9 mol to 3.9 mol H₂/mol glucose. The maximum production rate was 0.017 mmol H₂/h l at 380 mm Hg. The lag period as well as total batch time of H₂ production decreased using a decreased partial pressure.
Dehydration of ethylene glycol-water mixture was carried out in a laboratory pervaporation unit using a flat sheet membrane test cell. Polyvinyl alcohol-polyether sulfone (PVA-PES) composite ...membranes were synthesized and cross linked with two different concentrations, viz 0.2 and 0.5% of disodium tetraborate (borax). The derived membranes were extensively characterized for their morphology, intermolecular interactions, thermo-mechanical stability, and physicochemical properties using field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and water uptake studies. The membrane performance was evaluated in terms of pervaporation flux, separation factor, selectivity, permeability and solute diffusion coefficients of EG-water mixture at varying feed flow rate. Both in terms of flux and separation factor PVA-PES-0.2% borax composite membrane was found superior to PVA-PES-0.5% borax crosslinked and its uncrosslinked counterpart. Cross-linking the composite with borax produced a membrane with lower crystallinity and a smaller swelling degree, but having improved thermostability and mechanical properties.
Rifampicin (RIF) and Isoniazid (INH) are two major first-line antitubercular drugs (ATDs) that are typically administered orally, in combination. However, INH-catalysed degradation of RIF under ...acidic pH environment of the stomach is a major concern related to its oral delivery, and is dramatically accelerated upon further exposure to and interaction with INH. This interaction, in turn, triggers a direct decline in the available RIF dose below the sub-therapeutic level, thereby diminishing its therapeutic efficacy. We hypothesized that encapsulation of both these important ATDs into lipid nanoparticle formulations (LNFs) may help mitigate the acid hydrolysis of RIF, its subsequent interaction with INH and its eventual INH-mediated accelerated chemical degradation in the gastric environment. We further hypothesized that these LNFs would be capable of enhanced uptake and localization into intra-cellular compartments of lung macrophages, thereby potentially targeting the Tb pathogen in its in vivo niche. For this purpose, we evaluated two promising LNFs, viz., solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) for encapsulating these ATDs. Here, we report on the design, development and comparative evaluation of SLN and NLC-based lipid formulations of both INH and RIF. Our strategy of nanoencapsulation substantially prolonged encapsulated RIF release and improved its chemical stability in presence of INH in a simulated gastric acidic environment. In vitro cell culture studies showed a well-quantifiable uptake of LNFs in a human alveolar macrophage cell line. Overall, these evaluations provided promising results for establishing the potential of both formulations for TB therapy.
The development of a new vaccine is a challenging exercise involving several steps including computational studies, experimental work, and animal studies followed by clinical studies. To accelerate ...the process, in silico screening is frequently used for antigen identification. Here, we present Vaxi-DL, web-based deep learning (DL) software that evaluates the potential of protein sequences to serve as vaccine target antigens. Four different DL pathogen models were trained to predict target antigens in bacteria, protozoa, fungi, and viruses that cause infectious diseases in humans. Datasets containing antigenic and non-antigenic sequences were derived from known vaccine candidates and the Protegen database. Biological and physicochemical properties were computed for the datasets using publicly available bioinformatics tools. For each of the four pathogen models, the datasets were divided into training, validation, and testing subsets and then scaled and normalised. The models were constructed using Fully Connected Layers (FCLs), hyper-tuned, and trained using the training subset. Accuracy, sensitivity, specificity, precision, recall, and AUC (Area under the Curve) were used as metrics to assess the performance of these models. The models were benchmarked using independent datasets of known target antigens against other prediction tools such as VaxiJen and Vaxign-ML. We also tested Vaxi-DL on 219 known potential vaccine candidates (PVC) from 37 different pathogens. Our tool predicted 175 PVCs correctly out of 219 sequences. We also tested Vaxi-DL on different datasets obtained from multiple resources. Our tool has demonstrated an average sensitivity of 93% and will thus be a useful tool for prioritising PVCs for preclinical studies.
•A web-based deep learning server to predict the antigenicity of proteins.•In silico screening accelerates the process of antigen identification.•Successful testing of deep learning model on bench-marking data sets.•Superior performance compared to most of the previously known prediction methods.
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