488 research outputs found
Simultaneous Recovery of Hydrogen and Chlorine from Industrial Waste Dilute Hydrochloric Acid
Recovery of chlorine from byproduct HCl has inevitable commercial importance in industries lately because of insufficient purity or too low concentration to recycle it. Instead it is being neutralized in industries before disposing to meet stringent environmental conditions. Although recovery through catalytic oxidation processes is studied since the 19th century, their high operating conditions combined with sluggish reaction kinetics and low single pass conversions make electrolysis a better alternative. The present motive of this work is to develop a novel electrolysis process which in contrast to traditional processes effectively recovers both hydrogen and chlorine from dilute HCl. For this, an electrolytic cell with an Anionic Exchange Membrane has been designed which only allows the passage of chlorine anions from catholyte to anolyte separating the gasses in a single step. The catholyte can be as low as 3.59 wt% because of fixed anolyte concentration of 1.99 wt% which minimizes oxygen formation. Preliminary results show that the simultaneous recovery of hydrogen and chlorine is possible with high conversion up to 98%. The maximum current density value for 4.96 cm2 membrane surface area (70% active surface area) is 2.54 kAm−2, which is comparable with reported commercial processes. This study is expected to be useful for process intensification of the same in a continuous process environment
Modelling of drying processes of pharmaceutical granules. Pharmaceutical Sciences for the Future of Medicines
Oligomerization, Conformational Stability and Thermal Unfolding of Harpin, HrpZPss and Its Hypersensitive Response-Inducing C-Terminal Fragment, C-214-HrpZPss.
HrpZ-a harpin from Pseudomonas syringae-is a highly thermostable protein that exhibits multifunctional abilities e.g., it elicits hypersensitive response (HR), enhances plant growth, acts as a virulence factor, and forms pores in plant plasma membranes as well as artificial membranes. However, the molecular mechanism of its biological activity and high thermal stability remained poorly understood. HR inducing abilities of non-overlapping short deletion mutants of harpins put further constraints on the ability to establish structure-activity relationships. We characterized HrpZPss from Pseudomonas syringae pv. syringae and its HR inducing C-terminal fragment with 214 amino acids (C-214-HrpZPss) using calorimetric, spectroscopic and microscopic approaches. Both C-214-HrpZPss and HrpZPss were found to form oligomers. We propose that leucine-zipper-like motifs may take part in the formation of oligomeric aggregates, and oligomerization could be related to HR elicitation. CD, DSC and fluorescence studies showed that the thermal unfolding of these proteins is complex and involves multiple steps. The comparable conformational stability at 25°C (∼10.0 kcal/mol) of HrpZPss and C-214-HrpZPss further suggest that their structures are flexible, and the flexibility allows them to adopt proper conformation for multifunctional abilities
Genetic studies of body mass index yield new insights for obesity biology
Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis
Increased ERCP volume improves cholangiogram interpretation: a new performance measure for ERCP training?
Background/Aims: Cholangiogram interpretation is not used as a key performance indicator (KPI) of endoscopic retrograde cholangiopancreatography (ERCP) training, and national societies recommend different minimum numbers per annum to maintain competence. This study aimed to determine the relationship between correct ERCP cholangiogram interpretation and experience. Methods: One hundred fifty ERCPists were surveyed to appropriately interpret ERCP cholangiographic findings. There were three groups of 50 participants each: “Trainees,” “Consultants group 1” (performed >75 ERCPs per year), and “Consultants group 2” (performed >100 ERCPs per year). Results: Trainees was inferior to Consultants groups 1 and 2 in identifying all findings except choledocholithiasis outside the intrahepatic duct on the initial or completion/occlusion cholangiogram. Consultants group 1 was inferior to Consultants group 2 in identifying Strasberg type A bile leaks (odds ratio [OR], 0.86; 95% confidence interval [CI], 0.77−0.96), Strasberg type B (OR, 0.84; 95% CI, 0.74−0.95), and Bismuth type 2 hilar strictures (OR, 0.81; 95% CI, 0.69−0.95). Conclusions: This investigation supports the notion that cholangiogram interpretation improves with increased annual ERCP case volumes. Thus, a higher annual volume of procedures performed may improve the ability to correctly interpret particularly difficult findings. Cholangiogram interpretation, in addition to bile duct cannulation, could be considered as another KPI of ERCP training
Diffusion Tensor Imaging and Tractography in Brown-Sequard Syndrome
This report illustrates the utility of DTI and DTT in delineating regions of cord injury in two patients with traumatic Brown-Sequard syndrome. Our results indicate that DTI provides clinically relevant information that supplements conventional MR imaging for patients with acute SCI
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Optimization of a nanotechnology based antimicrobial platform for food safety applications using Engineered Water Nanostructures (EWNS)
A chemical free, nanotechnology-based, antimicrobial platform using Engineered Water Nanostructures (EWNS) was recently developed. EWNS have high surface charge, are loaded with reactive oxygen species (ROS), and can interact-with, and inactivate an array of microorganisms, including foodborne pathogens. Here, it was demonstrated that their properties during synthesis can be fine tuned and optimized to further enhance their antimicrobial potential. A lab based EWNS platform was developed to enable fine-tuning of EWNS properties by modifying synthesis parameters. Characterization of EWNS properties (charge, size and ROS content) was performed using state-of-the art analytical methods. Further their microbial inactivation potential was evaluated with food related microorganisms such as Escherichia coli, Salmonella enterica, Listeria innocua, Mycobacterium parafortuitum, and Saccharomyces cerevisiae inoculated onto the surface of organic grape tomatoes. The results presented here indicate that EWNS properties can be fine-tuned during synthesis resulting in a multifold increase of the inactivation efficacy. More specifically, the surface charge quadrupled and the ROS content increased. Microbial removal rates were microorganism dependent and ranged between 1.0 to 3.8 logs after 45 mins of exposure to an EWNS aerosol dose of 40,000 #/cm3
Improving automatic source code summarization via deep reinforcement learning
© 2018 Association for Computing Machinery. Code summarization provides a high level natural language description of the function performed by code, as it can benefit the software maintenance, code categorization and retrieval. To the best of our knowledge, most state-of-the-art approaches follow an encoder-decoder framework which encodes the code into a hidden space and then decode it into natural language space, suffering from two major drawbacks: a) Their encoders only consider the sequential content of code, ignoring the tree structure which is also critical for the task of code summarization; b) Their decoders are typically trained to predict the next word by maximizing the likelihood of next ground-truth word with previous ground-truth word given. However, it is expected to generate the entire sequence from scratch at test time. This discrepancy can cause an exposure bias issue, making the learnt decoder suboptimal. In this paper, we incorporate an abstract syntax tree structure as well as sequential content of code snippets into a deep reinforcement learning framework (i.e., actor-critic network). The actor network provides the confidence of predicting the next word according to current state. On the other hand, the critic network evaluates the reward value of all possible extensions of the current state and can provide global guidance for explorations. We employ an advantage reward composed of BLEU metric to train both networks. Comprehensive experiments on a real-world dataset show the effectiveness of our proposed model when compared with some state-of-the-art methods
Circuit Analysis in Metal-Optics
We provide electrical circuit descriptions for bulk plasmons, single surface
plasmons, and parallel-plate plasmons. Simple circuits can reproduce the
exactly known frequency versus wave-vector dispersion relations for all these
cases, with reasonable accuracy. The circuit paradigm directly provides a
characteristic wave-impedance, Zo, that is rarely discussed in the context of
plasmonics. The case of a single-surface-plasmon is particularly interesting
since it can be modeled as a transmission line, even though there is no return
current conductor. The capacitance/unit length and the Faraday inductance/unit
length, of a flat metal surface, are C'=2epsilon_okW, and L'=epsilon_o/2kW
respectively, (where k is wave-vector, and W is the width of the flat metal
surface). We believe that many other metal-optic geometries can be described
within the circuit paradigm, with the prerequisite that the distributed
capacitance and inductance must be calculated for each particular geometr
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