59 research outputs found
Low Voltage Thin Layer Electrophoresis of Anions on Silica Gel-G And Titanium (IV) Tungstate Layers
The low voltage thin layer electrophoresis of anions has been studied on Silica Gel-G and titanium (iv) tungstate layers in in v arious complexing acid media such as Oxalic acid (O.A), Citric acid(C.A), Tartaric acid (T.A) and Succinic acid (S.A).The electrophoretic migration of anions also correlated with lyotropic number, N. The Spots are well defined in electrophoresis
Electrophoretic Study of d-Block Metal Ions on Plain and Tri-n-Butylamine (TBA) Impregnated Titanium (IV) Tungstate Layers
RPTLE of ninteen d block metal ion studied on TBA impregnated titanium(IV)tungstate layer in nine solvent system among them three are complex forming acids OA,TA, CA to study the effect of complexation on migration. Electrophoretic migration also correlated with Ionc potential,Kd of metal ions and Ka of acids,pH of electrolytes.The spots are well defined in RPTLE and Mi is positiv
Advances in applications of non-destructive testing (NDT): a review
Manufacturing defects and discontinuities in a product are anomalies which can lead to severe damages which may sometimes involve loss of life. These defects must be examined and corrected before the product goes into service. There are two methods of testing a product for defects and discontinuities viz. Destructive Testing and Non-Destructive Testing. Destructive Testing entails subjecting the product to conditions that leads to failure of the product whereas Non-Destructive Testing (NDT) is the process of examining the products for defects in a way in which it retains its usefulness for future service. This paper discusses various methods involved in NDT such as Visual Testing, Magnetic Particle Inspection, Penetrant Testing, Ultrasonic Testing, Radiographic Testing, Acoustic Emission and Eddy Current Testing with a major focus on advances in the applications of NDT
Mirage: Model-Agnostic Graph Distillation for Graph Classification
GNNs, like other deep learning models, are data and computation hungry. There
is a pressing need to scale training of GNNs on large datasets to enable their
usage on low-resource environments. Graph distillation is an effort in that
direction with the aim to construct a smaller synthetic training set from the
original training data without significantly compromising model performance.
While initial efforts are promising, this work is motivated by two key
observations: (1) Existing graph distillation algorithms themselves rely on
training with the full dataset, which undermines the very premise of graph
distillation. (2) The distillation process is specific to the target GNN
architecture and hyper-parameters and thus not robust to changes in the
modeling pipeline. We circumvent these limitations by designing a distillation
algorithm called Mirage for graph classification. Mirage is built on the
insight that a message-passing GNN decomposes the input graph into a multiset
of computation trees. Furthermore, the frequency distribution of computation
trees is often skewed in nature, enabling us to condense this data into a
concise distilled summary. By compressing the computation data itself, as
opposed to emulating gradient flows on the original training set-a prevalent
approach to date-Mirage transforms into an unsupervised and
architecture-agnostic distillation algorithm. Extensive benchmarking on
real-world datasets underscores Mirage's superiority, showcasing enhanced
generalization accuracy, data compression, and distillation efficiency when
compared to state-of-the-art baselines.Comment: 14 pages, 14 figure
PATHOLOGICAL OUTCOME IN THE PATIENTS WITH DIFFERENT AILMENTS: A COMPREHENSIVE STUDY IN LAKHIMPUR DISTRICT, ASSAM
Hemoglobin, total leukocyte count, differential leukocyte count, erythrocyte sedimentation rate, random blood sugar, creatinine and blood urea levels were measured in a total of 1123 participants attended at North lakhimpur Civil hospital during the year 2013. The prevalence of anemia was observed in 45.33% (509/1123) cases. Among the study participants, 5.08% (57/1123) cases were typhoid widal test positive. The level of low monocyte count observed in all the typhoid positive cases. Beside this an increase level of ESR value, random blood sugar, creatinine and blood urea were examined in a considerable number of cases. Male tend to have higher erythrocyte sedimentation rate values than the females. Only a single Plasmodium falciparum positive case was detected among the study samples. The study concludes that hematological and biochemical estimation is probably useful in early detection of case infection.Â
Choice of sedative for deep brain stimulation in Parkinson’s disease: Our experience and comparison of two cases
AbstractIntroductionParkinson’s disease (PD) is a severe, debilitating disease of the extra pyramidal central nervous system, which has a significant effect on lifestyle and day to day living of the affected population. Statistically, more of the elderly are now going to present with this disease. Moving ahead from older procedures such as cingulotomy, pallidotomy and thalamotomy which had irreversible side effects, deep brain stimulation (DBS) has emerged as a new, safer and more attractive option for such patients. Anaesthetic concerns for such procedures mainly incorporate principles of awake craniotomy, for which the basic requirement is a cooperative patient. Although Propofol was somewhat of a gold standard for this purpose until a few years back, Dexmedetomidine has emerged as the new drug of choice.CaseWhile conducting two surgeries for DBS over two days, we had an obverse experience with these drugs. We describe the pre-operative assessment and intra-operative management of the two cases and a discussion of the factors which might have contributed to this contradiction.ConclusionThe choice of sedation for DBS in PD should take into consideration factors such as patient cooperation, ‘drug off’ state due to pre-op medication stoppage, GABA versus non-GABA mediated mechanism of drugs, amount of dependence on PD drugs, severity of disease and finally requirement of the testing team. No drug can be singled out to be better and must be chosen based on individual merits of the patient and disease
Druggable targets for Parkinson’s disease: An overview
One of the most crippling conditions affecting the brain and its progression causes neurodegeneration is Parkinson's disease (PD). The disease is characterized by accumulation of α-synuclein having Lewy bodies and further loss of dopaminergic neuron in substantia nigra, ultimately causing reduced ability of voluntary movements. The main symptoms of PD include tremor, bradykinesia and rigidity. Though, various symptomatic treatment options are available targeting both motor and non-motor signs but none of them claim to improve quality of life of PD patients. Recent studies indicated the identification of targets for PD such as glutamate receptors, α-Syn, c-Abl, molecular chaperones, GPR109Aand metals have been and some drugs targeting these targets are already there in market. The effectiveness of these pharmacological targets in treating PD has to be confirmed by a larger-scale trial. Effective PD therapy may also target pathways mediated by autophagy. Gene therapy and gene editing all have strong therapeutic effects and provide fresh PD medication targets. Additionally, the therapy of PD is more effective when a multi-target response is used. Further, research should be conducted to validate and explore new targets for treatment ofPD
ProtRepeatsDB: a database of amino acid repeats in genomes
BACKGROUND: Genome wide and cross species comparisons of amino acid repeats is an intriguing problem in biology mainly due to the highly polymorphic nature and diverse functions of amino acid repeats. Innate protein repeats constitute vital functional and structural regions in proteins. Repeats are of great consequence in evolution of proteins, as evident from analysis of repeats in different organisms. In the post genomic era, availability of protein sequences encoded in different genomes provides a unique opportunity to perform large scale comparative studies of amino acid repeats. ProtRepeatsDB is a relational database of perfect and mismatch repeats, access to which is designed as a resource and collection of tools for detection and cross species comparisons of different types of amino acid repeats. DESCRIPTION: ProtRepeatsDB (v1.2) consists of perfect as well as mismatch amino acid repeats in the protein sequences of 141 organisms, the genomes of which are now available. The web interface of ProtRepeatsDB consists of different tools to perform repeat s; based on protein IDs, organism name, repeat sequences, and keywords as in FASTA headers, size, frequency, gene ontology (GO) annotation IDs and regular expressions (REGEXP) describing repeats. These tools also allow formulation of a variety of simple, complex and logical queries to facilitate mining and large-scale cross-species comparisons of amino acid repeats. In addition to this, the database also contains sequence analysis tools to determine repeats in user input sequences. CONCLUSION: ProtRepeatsDB is a multi-organism database of different types of amino acid repeats present in proteins. It integrates useful tools to perform genome wide queries for rapid screening and identification of amino acid repeats and facilitates comparative and evolutionary studies of the repeats. The database is useful for identification of species or organism specific repeat markers, interspecies variations and polymorphism
Diffusion Model with Clustering-based Conditioning for Food Image Generation
Image-based dietary assessment serves as an efficient and accurate solution
for recording and analyzing nutrition intake using eating occasion images as
input. Deep learning-based techniques are commonly used to perform image
analysis such as food classification, segmentation, and portion size
estimation, which rely on large amounts of food images with annotations for
training. However, such data dependency poses significant barriers to
real-world applications, because acquiring a substantial, diverse, and balanced
set of food images can be challenging. One potential solution is to use
synthetic food images for data augmentation. Although existing work has
explored the use of generative adversarial networks (GAN) based structures for
generation, the quality of synthetic food images still remains subpar. In
addition, while diffusion-based generative models have shown promising results
for general image generation tasks, the generation of food images can be
challenging due to the substantial intra-class variance. In this paper, we
investigate the generation of synthetic food images based on the conditional
diffusion model and propose an effective clustering-based training framework,
named ClusDiff, for generating high-quality and representative food images. The
proposed method is evaluated on the Food-101 dataset and shows improved
performance when compared with existing image generation works. We also
demonstrate that the synthetic food images generated by ClusDiff can help
address the severe class imbalance issue in long-tailed food classification
using the VFN-LT dataset.Comment: Accepted for 31st ACM International Conference on Multimedia: 8th
International Workshop on Multimedia Assisted Dietary Management (MADiMa
2023
A systematic classification of Plasmodium falciparum P-loop NTPases: structural and functional correlation
Background: The P-loop NTPases constitute one of the largest groups of globular protein domains that play highly diverse functional roles in most of the organisms. Even with the availability of nearly 300 different Hidden Markov Models representing the P-loop NTPase superfamily, not many P-loop NTPases are known in Plasmodium falciparum. A number of characteristic attributes of the genome have resulted into the lack of knowledge about this functionally diverse, but important class of proteins. Method: In the study, protein sequences with characteristic motifs of NTPase domain (Walker A and Walker B) are computationally extracted from the P. falciparum database. A detailed secondary structure analysis, functional classification, phylogenetic and orthology studies of the NTPase domain of repertoire of 97 P. falciparum P-loop NTPases is carried out. Results: Based upon distinct sequence features and secondary structure profile of the P-loop domain of obtained sequences, a cladistic classification is also conceded: nucleotide kinases and GTPases, ABC and SMC family, SF½ helicases, AAA+ and AAA protein families. Attempts are made to identify any ortholog(s) for each of these proteins in other Plasmodium sp. as well as its vertebrate host, Homo sapiens. A number of P. falciparum P-loop NTPases that have no homologue in the host, as well as those annotated as hypothetical proteins and lack any characteristic functional domain are identified. Conclusion: The study suggests a strong correlation between sequence and secondary structure profile of P-loop domains and functional roles of these proteins and thus provides an opportunity to speculate the role of many hypothetical proteins. The study provides a methodical framework for the characterization of biologically diverse NTPases in the P. falciparum genome. The efforts made in the analysis are first of its kind; and the results augment to explore the functional role of many of these proteins from the parasite that could provide leads to identify novel drug targets against malaria
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