162 research outputs found
Some Theorems for Feed Forward Neural Networks
In this paper we introduce a new method which employs the concept of
"Orientation Vectors" to train a feed forward neural network and suitable for
problems where large dimensions are involved and the clusters are
characteristically sparse. The new method is not NP hard as the problem size
increases. We `derive' the method by starting from Kolmogrov's method and then
relax some of the stringent conditions. We show for most classification
problems three layers are sufficient and the network size depends on the number
of clusters. We prove as the number of clusters increase from N to N+dN the
number of processing elements in the first layer only increases by d(logN), and
are proportional to the number of classes, and the method is not NP hard.
Many examples are solved to demonstrate that the method of Orientation
Vectors requires much less computational effort than Radial Basis Function
methods and other techniques wherein distance computations are required, in
fact the present method increases logarithmically with problem size compared to
the Radial Basis Function method and the other methods which depend on distance
computations e.g statistical methods where probabilistic distances are
calculated. A practical method of applying the concept of Occum's razor to
choose between two architectures which solve the same classification problem
has been described. The ramifications of the above findings on the field of
Deep Learning have also been briefly investigated and we have found that it
directly leads to the existence of certain types of NN architectures which can
be used as a "mapping engine", which has the property of "invertibility", thus
improving the prospect of their deployment for solving problems involving Deep
Learning and hierarchical classification. The latter possibility has a lot of
future scope in the areas of machine learning and cloud computing.Comment: 15 pages 13 figure
Detection of Cognitive States from fMRI data using Machine Learning Techniques
Over the past decade functional Magnetic Resonance
Imaging (fMRI) has emerged as a powerful
technique to locate activity of human brain while
engaged in a particular task or cognitive state. We
consider the inverse problem of detecting the cognitive
state of a human subject based on the fMRI
data. We have explored classification techniques
such as Gaussian Naive Bayes, k-Nearest
Neighbour and Support Vector Machines. In order
to reduce the very high dimensional fMRI data, we
have used three feature selection strategies. Discriminating
features and activity based features
were used to select features for the problem of
identifying the instantaneous cognitive state given
a single fMRI scan and correlation based features
were used when fMRI data from a single time interval
was given. A case study of visuo-motor sequence
learning is presented. The set of cognitive
states we are interested in detecting are whether the
subject has learnt a sequence, and if the subject is
paying attention only towards the position or towards
both the color and position of the visual
stimuli. We have successfully used correlation
based features to detect position-color related cognitive
states with 80% accuracy and the cognitive
states related to learning with 62.5% accuracy
Sodium alginate microspheres containing multicomponent inclusion complex of domperidone
Sodium alginate microspheres of domperidone for intranasal systemic delivery were developed
to eliminate first pass metabolism, improve patient compliance and obtain improved therapeutic efficacy
in treatment of migraine, gastro-esophageal reflux and chemotherapy induced nausea and vomiting.
Domperidone was encapsulated as ternary inclusion complex with β-cyclodextrin and citric acid to improve
solubility. The phase solubility studies were performed in order to select suitable acid and ternary
inclusion complex was prepared by kneading method. The complex was characterized by differential scanning
calorimetry, X-ray diffraction and Fourier transform infrared spectroscopy. In vitro dissolution
study was carried out in simulated nasal electrolyte solution, pH 6.4. The microspheres of optimised
ternary inclusion complex were prepared by emulsification-cross-linking method and were evaluated for
particle size, encapsulation efficiency, equilibrium swelling degree, in vitro mucoadhesion and in vitro drug
release. The effect of various formulation variables such as drug loading, polymer concentration, crosslinking
agent concentration and cross-linking time on microsphere characteristics were studied. The microspheres
size range was 57.63-65.3 µm, whereas the percentage drug encapsulation was within the range
15-50 %. All microspheres showed good bioadhesive properties. The formulation variables influenced the
drug release profile. The treatment of in vitro release kinetics with kinetic equations indicated that the
domperidone release followed Higuchi's matrix model.Colegio de Farmacéuticos de la Provincia de Buenos Aire
In vitro absorption studies of acyclovir using natural permeation enhancers
Gastroretentive Delivery Systems are employed to improve the bioavailability of drugs which
are absorbed through upper part of GIT, by increasing their retention time. Incorporation of permeability
enhancers in the formulations of such drugs can further increase their bioavailability; however their use
in the formulations is questionable due to the toxicity exhibited by them. Acyclovir is a class III drug having
low oral bioavailability due to improper absorption. Mucoadhesive tablets of acyclovir containing natural
permeation enhancers were prepared by direct compression and evaluated for mucoadhesion
strength, in-vitro dissolution parameters and in-vitro absorption studies. The formulations containing Aloe
vera extract showed increase in the mucoadhesion strength and retarded the drug release. The in-vitro absorption
studies revealed that the formulations containing Aloe vera extract (Enhancement Ratio 1.94)
and chausath prahar pippal (Enhancement Ratio 1.87) showed significant increase in the permeation of the
drug. The studies led to the conclusion that by formulating mucoadhesive tablets of acyclovir containing
natural permeation enhancers increased the permeability, thus proving to be the cheaper and easily available
alternative to the other permeation enhancers.Colegio de Farmacéuticos de la Provincia de Buenos Aire
Local structural changes in paramagnetic and charge ordered phases of Sm0.2Pr0.3Sr0.5MnO3: An EXAFS Study
Sm{0.5-x}Pr{x}Sr{0.5}MnO{3} exhibits variety of ground states as x is varied
from 0 to 0.5. At an intermediate doping of x = 0.3 a charge-ordered CE type
antiferromagnetic insulating (AFI) ground state is seen. The transition to this
ground state is from a paramagnetic insulating (PMI) phase through a
ferromagnetic metallic phase (FMM). Local structures in PMI and AFI phases of x
= 0.3 sample have been investigated using Pr K-edge and Sm K-edge Extended
X-ray Absorption Fine Structure (EXAFS). It can be seen that the tilting and
rotation of the MnO6 octahedra about the b-axis are responsible for the charge
ordered CE-type antiferromagnetic ground state at low temperatures. In addition
a shift in the position of the rare earth ion along the c-axis has to be
considered to account for observed distribution of bond distances around the
rare earth ion
Far-Ultraviolet to Near-Infrared Observations of SN 2023ixf: A high energy explosion engulfed in complex circumstellar material
We present early-phase panchromatic photometric and spectroscopic coverage
spanning far-ultraviolet (FUV) to the near-infrared (NIR) regime of the nearest
hydrogen-rich core-collapse supernova in the last 25 years, SN~2023ixf. We
observe early `flash' features in the optical spectra due to a confined dense
circumstellar material (CSM). We observe high-ionization absorption lines Fe
II, Mg II in the ultraviolet spectra from very early on. We also observe a
multi-peaked emission profile of H-alpha in the spectrum beginning ~16 d, which
indicates ongoing interaction of the SN ejecta with a pre-existing shell-shaped
CSM having an inner radius of ~ 75 AU and an outer radius of ~140 AU. The
shell-shaped CSM is likely a result of enhanced mass loss ~ 35 - 65 years
before the explosion assuming a standard Red-Supergiant wind. Spectral modeling
of the FUV, NUV, and the optical spectra during 9-12 d, using the radiative
transfer spectrum synthesis code TARDIS indicates that the supernova ejecta
could be well represented by a progenitor elemental composition greater than
solar abundances. Based on early light curve models of Type II SNe, we infer
that the nearby dense CSM confined to ~7+-3e14~cm(~45 AU) is a result of
enhanced mass loss ~1e-(3.0+-0.5) Msol/yr two decades before the explosion.Comment: Submitted to AAS Journals, 4 figures, 2 table
FSP27 Promotes Lipid Droplet Clustering and Then Fusion to Regulate Triglyceride Accumulation
Fat Specific Protein 27 (FSP27), a lipid droplet (LD) associated protein in adipocytes, regulates triglyceride (TG) storage. In the present study we demonstrate that FSP27 plays a key role in LD morphology to accumulate TGs. We show here that FSP27 promotes clustering of the LDs which is followed by their fusion into fewer and enlarged droplets. To map the domains of FSP27 responsible for these events, we generated GFP-fusion constructs of deletion mutants of FSP27. Microscopic analysis revealed that amino acids 173–220 of FSP27 are necessary and sufficient for both the targeting of FSP27 to LDs and the initial clustering of the droplets. Amino acids 120–140 are essential but not sufficient for LD enlargement, whereas amino acids 120–210 are necessary and sufficient for both clustering and fusion of LDs to form enlarged droplets. In addition, we found that FSP27-mediated enlargement of LDs, but not their clustering, is associated with triglyceride accumulation. These results suggest a model in which FSP27 facilitates LD clustering and then promotes their fusion to form enlarged droplets in two discrete, sequential steps, and a subsequent triglyceride accumulation
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