Single-bit adaptive channel equalization for narrowband signals

In this paper, a new design of a single-bit adaptive channel equalization is proposed using sigma delta modulation and a single-bit block Least Mean Square (LMS) algorithm. With correlated narrowband input signals, this model is capable to converge and provide equivalent equalization filter with improvement in the SNR and very low Symbol Error Rate (SER). The input, filter coefficients and output values are all in single-bit and ternary format that results in a reduction in hardware complexity compared to traditional multi-bit channel equalization. Additionally, the technique avoids the need for successive conversion from multi-bit to single bit and back at the receiver and transmitter stages

Pemodelan Pengukuran Luas Panen Padi Nasional Menggunakan Generalized Autoregressive Conditional Heteroscedastic Model (GARCH)

This study was aimed to build a model for the estimation of national harvested area of rice by incorporating element of variant heterogeneity and the influence of asymmetry factors on time series data using five types of GARCH models, namely: symmetric GARCH, exponential asymmetric GARCH, quadratic asymmetric GARCH, Threshold GARCH, and non-linear asymmetric GARCH. Those models were compared and evaluated, and then the best model was used to predict the accuracy of the national rice harvested area. The results showed that two types of GARCH had significant coefficient, indicating the validity of the model. Those models were symmetric GARCH and quadratic GARCH models. Based on the value of mean absolute percentage error (MAPE) for the twelve month periods ahead, quadratic GARCH model was better than the symmetric GARCH model. Furthermore, based on the value of mean absolute deviation (MAD) and mean square error (MSE), quadratic GARCH model also seemed to be a better model than symmetric GARCH model. The best model can be used to predict the harvested area in the subsequent year

Selection of DNA nanoparticles with preferential binding to aggregated protein target.

High affinity and specificity are considered essential for affinity reagents and molecularly-targeted therapeutics, such as monoclonal antibodies. However, life's own molecular and cellular machinery consists of lower affinity, highly multivalent interactions that are metastable, but easily reversible or displaceable. With this inspiration, we have developed a DNA-based reagent platform that uses massive avidity to achieve stable, but reversible specific recognition of polyvalent targets. We have previously selected these DNA reagents, termed DeNAno, against various cells and now we demonstrate that DeNAno specific for protein targets can also be selected. DeNAno were selected against streptavidin-, rituximab- and bevacizumab-coated beads. Binding was stable for weeks and unaffected by the presence of soluble target proteins, yet readily competed by natural or synthetic ligands of the target proteins. Thus DeNAno particles are a novel biomolecular recognition agent whose orthogonal use of avidity over affinity results in uniquely stable yet reversible binding interactions

Genetic diversity and population structure of Peronosclerospora sorghi isolates of Sorghum in Uganda

Sorghum is the third most important staple cereal crop in Uganda after maize and millet. Downy mildew disease is one of the most devastating fungal diseases which limits the production and productivity of the crop. The disease is caused by an obligate fungus, Peronosclerospora sorghi (Weston & Uppal) with varying symptoms. Information on the genetic diversity and population structure of P.sorghi in sorghum is imperative for the screening and selection for resistant genotypes and further monitoring possible mutant(s) of the pathogen. Isolates of P. sorghi infecting sorghum are difficult to discriminate when morphological descriptors are used. The use of molecular markers is efficient, and reliably precised for characterizing P. sorghi isolates. This study was undertaken to assess the level of genetic diversity and population structure that exist in P. sorghi isolates in Uganda. A total of 195 P. sorghi isolates, sampled from 13 different geographic populations from 10 different regions (agro-ecological zones) was used. Eleven (11) molecular markers, comprising of four Random amplified microsatellite (RAM) and seven (7) Inter-Simple Sequence Repeat (ISSR) markers were used in this study. The analysis of molecular variation (AMOVA) based on 11 microsatellite markers showed significant (P < 0.001) intra-population (88.9 %, PhiPT = 0.111) and inter-population (8.4 %, PhiPR = 0.083) genetic variation, while the genetic variation among regions (2.7 %, PhiRT = 0.022) was not significant. The highest genetic similarity value (0.987 = 98.7 %) was recorded between Pader and Lira populations and the lowest genetic similarity (0.913 = 91.3 %) was observed between Namutumba and Arua populations. The mean Nei's genetic diversity index (H) and Shannon Information Index (I) were 0.308 and 0.471 respectively. Seven distinct cluster groups were formed from the 195 P. sorghi isolates based on their genetic similarity. Mantel test revealed no association between genetic differentiation and geographical distance (R2 = 0.0026, p = 0.02) within the 13 geographic populations

FORMULATION AND OPTIMIZATION OF LEVAMISOLE CHEWABLE TABLETS

Objective: The aim of the present study was to prepare and optimize levamisole chewable tablets by using various super disintegrants, namely; sodium starch glycolate, DRC Indion 204, and DRC Indion 234. Methods: Drug excipient compatibility study was carried out by FTIR spectroscopy to verify the compatibility of levamisole with the excipients. Nine batches of levamisole chewable tablets were prepared according to 32 factorial designs using a direct compression method by optimizing the super disintegrant concentration. The powder blend was exposed to pre-compression studies of the powder blend followed by post-compression studies of the formulated tablets. Results: FTIR study revealed that the excipients used in the formulations were compatible with the drug. The pre-compression and post-compression parameters were found within the IP limits. Form the dissolution studies, it was evident that the formulation prepared with DRC Indion 234 (50 mg) showed maximum percentage drug release in 45 min (97.13%) hence it is considered as optimized formulation. When compared to all other formulation, the batches with DRC Indion 234 (F7-F9) showed a better release of the drug (90 % drug release within 45 min). Conclusion: Nine batches of levamisole chewable tablets were successfully formulated by optimizing the concentration of super disintegrants such as sodium starch glycolate, DRC Indion 204, and DRC Indion 234. It was concluded from the dissolution studies that the DRC Indion 234 is the best super disintegrant irrespective of their concentration for the formulation of levamisole chewable tablets when compared to sodium starch Glycolate and DRC Indion 204

Generalized 11D supergravity equations from tri-vector deformations

In arXiv:2203.03372 we presented a modification of 11-dimensional supergravity field equations which upon dimensional reduction yields generalized supergravity equations in 10-dimensions. In this paper we provide full technical details of that result which is based on SL(5) exceptional field theory. The equations are obtained by making a non-unimodular tri-vector Yang-Baxter deformation which breaks the initial GL(11) symmetry down to GL(7)xGL(4). We also give some non-trivial solutions to these equations.Comment: v3, refs added, minor correction

A QUANTUM IMPROVEMENT ON DIJKSTRA’S ALGORITHM FOR COMPUTER NETWORK ROUTING

The aim of this paper is to improve the Dijkstra algorithm which is widely used in the internet routing. Quantum computing approach is used to improve the work of Dijkstra algorithm for network routing by exploiting the massive parallelism existing in the quantum environment and to deal with the demands of continuous growing of the internet. This algorithm is compared according to the number of iterations and time complexity with Dijkstra’s algorithm and the result shows that the quantum approach is better in finding the optimal path with better time complexity when it is implemented in quantum computer

Holographic RG flows and boundary conditions in a 3D gauged supergravity

In this work we focus on the study of RG flows of conformal field theories that are holographically dual to Poincar\'e domain wall solutions in $D=3$, $\mathcal{N}=(2,0)$ gauged supergravity coupled to a sigma model with target space $SU(1, 1)/U(1) = H^2$. This theory is truncated to a subsector where the vector field and phase of the scalar field vanish and we consider different boundary conditions for the remaining real scalar field. The RG flows, which are mostly non-superysymmetric, are analyzed by treating the supergravity field equations as a dynamical system for the scalar field and its derivative with respect to the scale factor. Phase diagrams are constructed for different values of the parameter $a^2$, which is related to the curvature of the scalar manifold. The behavior of solutions near the boundary is used to determine their type based on the expansion of the corresponding fake superpotential. By incorporating information on the boundary conditions, the obtained RG flows are interpreted using the holographic dictionary. Numerical solutions and plots of the fake superpotential are also provided.Comment: 36 pages plus Appendix, v2: updated references, tables, corrected misprint