Influence of Sugar Cane Mechanical Harvest on Clear Juice Quality at Elguneid Sugar Factory

This study aimed to investigate the influence of mechanical harvest on juice clarification in Elguneid sugar factory. Elguneid factory was designed to treat a hand cut cane more than a mechanical cut cane. So, the clarification system was tuned to meet this purpose. Color, turbidity, reducing sugar, sugar content, purity, pH, brix, temperature and phosphate content were determined. The results showed: the color has increased from 3910 to 13921 ICUMSA, turbidity from 3242 to 8496 and reducing sugar increased to 0.928%. Sucrose content decreased from 14.39 to 11.69% and purity from 88 to 83%. The results of Pol% and Purity% were taken at the beginning of crushing season, where the mechanical harvest was higher than hand cut. A comparative study between hand cut and mechanical harvest was made at the middle of the crushing season. The optimum brix in the clarifiers matched the turbidity decreased at brix 12%, 13% respectively. Also from the tests carried out it was shown that the flocculant and phosphoric acid, which were used by the factory personnel was lower than the standard values, phosphoric acid was 183ppm and the polymer was 1,6ppm. These low values affected the precipitation process. There is a relationship between the amount of mud and type of harvest. It was noticed that there is a relationship between sugar yield and type of harvest

Introduction of a novel 18S rDNA gene arrangement along with distinct ITS region in the saline water microalga Dunaliella

Comparison of 18S rDNA gene sequences is a very promising method for identification and classification of living organisms. Molecular identification and discrimination of different Dunaliella species were carried out based on the size of 18S rDNA gene and, number and position of introns in the gene. Three types of 18S rDNA structure have already been reported: the gene with a size of ~1770 bp lacking any intron, with a size of ~2170 bp consisting one intron near 5' terminus, and with a size of ~2570 bp harbouring two introns near 5' and 3' termini. Hereby, we report a new 18S rDNA gene arrangement in terms of intron localization and nucleotide sequence in a Dunaliella isolated from Iranian salt lakes (ABRIINW-M1/2). PCR amplification with genus-specific primers resulted in production of a ~2170 bp DNA band, which is similar to that of D. salina 18S rDNA gene containing only one intron near 5' terminus. Whilst, sequence composition of the gene revealed the lack of any intron near 5' terminus in our isolate. Furthermore, another alteration was observed due to the presence of a 440 bp DNA fragment near 3' terminus. Accordingly, 18S rDNA gene of the isolate is clearly different from those of D. salina and any other Dunaliella species reported so far. Moreover, analysis of ITS region sequence showed the diversity of this region compared to the previously reported species. 18S rDNA and ITS sequences of our isolate were submitted with accesion numbers of EU678868 and EU927373 in NCBI database, respectively. The optimum growth rate of this isolate occured at the salinity level of 1 M NaCl. The maximum carotenoid content under stress condition of intense light (400 μmol photon m-2 s-1), high salinity (4 M NaCl) and deficiency of nitrate and phosphate nutritions reached to 240 ng/cell after 15 days

Safety-aware model-based reinforcement learning using barrier transformation

The ability to learn and execute optimal control policies safely is critical to the realization of complex autonomy, especially where task restarts are not available and/or when the systems are safety-critical. Safety requirements are often expressed in terms of state and/or control constraints. Methods such as barrier transformation and control barrier functions have been successfully used for safe learning in systems under state constraints and/or control constraints, in conjunction with model-based reinforcement learning to learn the optimal control policy. However, existing barrier-based safe learning methods rely on fully known models and full state feedback. In this thesis, two different safe model-based reinforcement learning techniques are developed. One of the techniques utilizes a novel filtered concurrent learning method to realize simultaneous learning and control in the presence of model uncertainties for safety-critical systems, and the other technique utilizes a novel dynamic state estimator to realize simultaneous learning and control for safety-critical systems with a partially observable state. The applicability of the developed techniques is demonstrated through simulations, and to illustrate their effectiveness, comparative simulations are presented wherever alternate methods exist to solve the problem under consideration. The thesis concludes with a discussion about the limitations of the developed techniques. Extensions of the developed techniques are also proposed along with the possible approaches to achieve them

Output Feedback Adaptive Optimal Control of Affine Nonlinear systems with a Linear Measurement Model

Real-world control applications in complex and uncertain environments require adaptability to handle model uncertainties and robustness against disturbances. This paper presents an online, output-feedback, critic-only, model-based reinforcement learning architecture that simultaneously learns and implements an optimal controller while maintaining stability during the learning phase. Using multiplier matrices, a convenient way to search for observer gains is designed along with a controller that learns from simulated experience to ensure stability and convergence of trajectories of the closed-loop system to a neighborhood of the origin. Local uniform ultimate boundedness of the trajectories is established using a Lyapunov-based analysis and demonstrated through simulation results, under mild excitation conditions.Comment: 16 pages, 5 figures, submitted to 2023 IEEE Conference on Control Technology and Application

Simulation of Traffic Flow Model with Traffic Controller Boundary

This paper considers a fluid dynamic traffic flow model appended with a closure linear velocity-density relationship which provides a first order hyperbolic partial differential equation (PDE) and is treated as an initial boundary value problem (IBVP). We consider the boundary value in such a way that one side of highway treat like there is a traffic controller at that point. We present the analytic solution of the traffic flow model as a Cauchy problem. A numerical simulation of the traffic flow model (IBVP) is performed based on a finite difference scheme for the model with two sided boundary conditions and a suitable numerical scheme for this is the Lax-Friedrichs scheme. Solution figure from our scheme indicates a desired result that amplitude and frequency of cars density and velocity reduces as time grows. Also at traffic controller point, velocity and density values change as desired manner. In further, we also want to introduce anisotropic behavior of cars(to get more realistic picture) which has not been considered here. Doi: 10.12777/ijse.5.1.25-30 [How to cite this article: Sultana, N., Parvin, M. , Sarker, R., Andallah, L.S. (2013). Simulation of Traffic Flow Model with Traffic Controller Boundary. International Journal of Science and Engineering, 5(1),25-30. Doi: 10.12777/ijse.5.1.25-30

Biomarkers of Tuberculosis Severity and Treatment Effect: A Directed Screen of 70 Host Markers in a Randomized Clinical Trial.

More efficacious treatment regimens are needed for tuberculosis, however, drug development is impeded by a lack of reliable biomarkers of disease severity and of treatment effect. We conducted a directed screen of host biomarkers in participants enrolled in a tuberculosis clinical trial to address this need. Serum samples from 319 protocol-correct, culture-confirmed pulmonary tuberculosis patients treated under direct observation as part of an international, phase 2 trial were screened for 70 markers of infection, inflammation, and metabolism. Biomarker assays were specifically developed for this study and quantified using a novel, multiplexed electrochemiluminescence assay. We evaluated the association of biomarkers with baseline characteristics, as well as with detailed microbiologic data, using Bonferroni-adjusted, linear regression models. Across numerous analyses, seven proteins, SAA1, PCT, IL-1β, IL-6, CRP, PTX-3 and MMP-8, showed recurring strong associations with markers of baseline disease severity, smear grade and cavitation; were strongly modulated by tuberculosis treatment; and had responses that were greater for patients who culture-converted at 8weeks. With treatment, all proteins decreased, except for osteocalcin, MCP-1 and MCP-4, which significantly increased. Several previously reported putative tuberculosis-associated biomarkers (HOMX1, neopterin, and cathelicidin) were not significantly associated with treatment response. In conclusion, across a geographically diverse and large population of tuberculosis patients enrolled in a clinical trial, several previously reported putative biomarkers were not significantly associated with treatment response, however, seven proteins had recurring strong associations with baseline radiographic and microbiologic measures of disease severity, as well as with early treatment response, deserving additional study

del (5q) solely in Myelodysplastic syndrome

Review on Myelodysplastic syndrome with isolated deletion of 5