Optimizing echo state networks for continuous gesture recognition in mobile devices: A comparative study.

Continuous gesture recognition can be used to enhance human-computer interaction. This can be accomplished by capturing human movement with the use of the Inertial Measurement Units in smartphones and using machine learning algorithms to predict the intended gestures. Echo State Networks (ESNs) consist of a fixed internal reservoir that is able to generate rich and diverse nonlinear dynamics in response to input signals that capture temporal dependencies within the signal. This makes ESNs well-suited for time series prediction tasks, such as continuous gesture recognition. However, their application has not been rigorously explored, with regard to gesture recognition. In this study, we sought to enhance the efficacy of ESN models in continuous gesture recognition by exploring diverse model structures, fine-tuning hyperparameters, and experimenting with various training approaches. We used three different training schemes that used the Leave-one-out Cross-validation (LOOCV) protocol to investigate the performance in real-world scenarios with different levels of data availability: Leaving out data from one user to use for testing (F1-score: 0.89), leaving out a fraction of data from all users to use in testing (F1-score: 0.96), and training and testing using LOOCV on a single user (F1-score: 0.99). The obtained results outperformed the Long Short-Term Memory (LSTM) performance from past research (F1-score: 0.87) while maintaining a low training time of approximately 13 seconds compared to 63 seconds for the LSTM model. Additionally, we further explored the performance of the ESN models through behaviour space analysis using memory capacity, Kernel Rank, and Generalization Rank. Our results demonstrate that ESNs can be optimized to achieve high performance on gesture recognition in mobile devices on multiple levels of data availability. These findings highlight the practical ability of ESNs to enhance human-computer interaction.

Bedside ultrasonographic evaluation of optic nerve sheath diameter for monitoring of intracranial pressure in traumatic brain injury patients: a cross sectional study in level II trauma care center in India.

BACKGROUND: Optic nerve sheath diameter (ONSD) is an emerging non-invasive, easily accessible, and possibly useful measurement for evaluating changes in intracranial pressure (ICP). The utilization of bedside ultrasonography (USG) to measure ONSD has garnered increased attention due to its portability, real-time capability, and lack of ionizing radiation. The primary aim of the study was to assess whether bedside USG-guided ONSD measurement can reliably predict increased ICP in traumatic brain injury (TBI) patients. METHODS: A total of 95 patients admitted to the trauma intensive care unit was included in this cross sectional study. Patient brain computed tomography (CT) scans and Glasgow Coma Scale (GCS) scores were assessed at the time of admission. Bedside USG-guided binocular ONSD was measured and the mean ONSD was noted. Microsoft Excel was used for statistical analysis. RESULTS: Patients with low GCS had higher mean ONSD values (6.4±1.0 mm). A highly significant association was found among the GCS, CT results, and ONSD measurements (P<0.001). Compared to CT scans, the bedside USG ONSD had 86.42% sensitivity and 64.29% specificity for detecting elevated ICP. The positive predictive value of ONSD to identify elevated ICP was 93.33%, and its negative predictive value was 45.00%. ONSD measurement accuracy was 83.16%. CONCLUSIONS: Increased ICP can be accurately predicted by bedside USG measurement of ONSD and can be a valuable adjunctive tool in the management of TBI patients.

Antimicrobial therapeutics isolated from algal source: retrospect and prospect.

In the last few decades, attention on new natural antimicrobial compounds has arisen due to a change in consumer preferences and the increase in the number of resistant microorganisms. Algae are defined as photosynthetic organisms that demonstrate a wide range of adaptability to adverse environmental conditions like temperature extremes, photo-oxidation, high or low salinity, and osmotic stress. Algae are primarily known to produce large amounts of secondary metabolite against various kinds of pathogenic microbes. Among these algae, micro and microalgae of river, lake, and algae of oceanic origin have been reported to have antimicrobial activity against the bacteria and fungi of pathogenic nature. Various polar and non- polar extracts of micro- and macro algae have been used for the suppression of these pathogenic fungi. Apart from these, certain algal derivatives have also been isolated from these having antibacterial and antifungal potential. Among the bioactive molecules of algae, polysaccharides, sulphated polysaccharides, phyco-cyanobilins polyphenols, lectins, proteins lutein, vitamin E, B12 and K1, peptides, polyunsaturated fatty acids and pigments can be highlighted. In the present review, we will discuss the biological activity of these derived compounds as antifungal/ antibacterial agents and their most promising applications. A brief outline is also given for the prospects of these isolated phytochemicals and using algae as therapeutic in the dietary form. We have also tried to answer whether alga-derived metabolites can serve as potential therapeutics for the treatment of SARS-CoV-2 like viral infections too.

Comparison of Diagnostic Yield of Tuberculosis Loop-Mediated Isothermal Amplification Assay With Cartridge-Based Nucleic Acid Amplification Test, Acid-Fast Bacilli Microscopy, and Mycobacteria Growth Indicator Tube Culture in Children With Pulmonary Tuberculosis.

BACKGROUND: Cartridge-based nucleic acid amplification test (CB-NAAT) has been recommended for diagnosis of tuberculosis (TB) in children, but its wide use is limited by high cost and the need for well-equipped laboratories. This study was conducted in children with pulmonary TB to compare the diagnostic yield of TB-LAMP (loop-mediated isothermal amplification test) with CB-NAAT and other conventional methods. METHODS: Patients ≤ 14 years of age diagnosed with probable pulmonary TB were included in the study. Induced sputum/gastric aspirate was obtained and subjected to acid-fast bacilli (AFB) microscopy, mycobacteria growth indicator tube (MGIT) culture, CB-NAAT, and TB-LAMP. The TB-LAMP assay was performed using 2 different primers, IS6110 and mpb64, for detection of Mycobacterium tuberculosis (MTB). TB-LAMP assays were compared to other assays using appropriate statistical tests. RESULTS: One hundred fourteen subjects were recruited in the study. AFB microscopy, MGIT culture, CB-NAAT, TB-LAMP IS6110, and TB-LAMP mpb64 showed positivity of 32 (28.1%), 59 (51.7%), 66 (57.9%), 75 (65.8%), and 81 (71%), respectively. TB-LAMP IS6110 showed significantly higher MTB detection in comparison to AFB microscopy and MGIT culture (P = .0001 and P = .03, respectively), and showed no significant difference in MTB detection in comparison with CB-NAAT (P = .219). TB-LAMP mpb64 showed significantly higher MTB detection as compared to AFB microscopy, MGIT culture, and CB-NAAT (P = .0001, P = .003, and P = .037, respectively). TB-LAMP mpb64 and IS6110 showed sensitivity of 94.9% (95% confidence interval [CI], 85.9%-98.9%) and 89.8% (95% CI, 79.7%-96.2%), respectively, in reference to MGIT culture. The degree of agreement between TB-LAMP (mpb64 and IS6110) with CB-NAAT showed κ values of 0.718 and 0.834, respectively. CONCLUSIONS: TB-LAMP assay can be a useful alternative test in diagnosis of pulmonary TB in children.

Maternal Ability to Correctly Detect Significant Jaundice in Indian Neonates.

BACKGROUND: The ability of mothers to correctly detect jaundice in their newborns is largely unknown. The objective was to ascertain the ability of mother to correctly detect the presence of significant jaundice in her newborn. MATERIALS AND METHODS: This cross-sectional study was conducted in a tertiary care hospital in eastern India from February 2015 to July 2016. All inborn neonates more than 34 weeks' gestation were included. Congenital malformations, perinatal asphyxia, neonatal sepsis, readmission after discharge, and isoimmunization were excluded. A total of 505 inborn newborns were independently assessed by the mother and the treating pediatrician for significant jaundice every day till discharge. Each newborn underwent total serum bilirubin estimation on suspicion of significant jaundice by either of the two or at discharge, whichever was earlier. RESULTS: The sensitivity, specificity, positive predictive value (PPV), and negative predictive value of maternal detection of significant jaundice was 51.47%, 88.33%, 39.29%, and 92.12%, respectively. CONCLUSION: Mothers have poor sensitivity and PPV to detect significant neonatal jaundice in the Indian population.

Inhibition-induced explosive synchronization in multiplex networks.

To date, explosive synchronization (ES) in a network is shown to be originated from considering either degree-frequency correlation, frequency-coupling strength correlation, inertia, or adaptively controlled phase oscillators. Here we show that ES is a generic phenomenon and can occur in any network by multiplexing it with an appropriate layer without even considering any prerequisite for the emergence of ES. We devise a technique which leads to the occurrence of ES with hysteresis loop in a network upon its multiplexing with a negatively coupled (or inhibitory) layer. The impact of various structural properties of positively coupled (or excitatory) and inhibitory layers along with the strength of multiplexing in gaining control over the induced ES transition is discussed. Analytical prediction for the spread of phase distribution of each layer is provided, which is in good agreement with the numerical assessment. This investigation is a step forward in highlighting the importance of multiplex framework not only in bringing phenomena which are not possible in an isolated network but also in providing more structural control over the induced phenomena.

A comparative screening of abiotic stress tolerance in early flowering rice mutants.

Oryza sativa L. (Rice) a grain crop grown considerably in areas frequented with abiotic stresses has a higher heat and drought tolerance and is deemed a model crop for tolerance studies. Manifold environment testing facilitates recognition of constant genotypes of rice mutants for adverse abiotic stress conditions. Mutants are an imperative genetic reserve which can help as an informative basis of natural disparity. We assessed EMS induced early flowering rice mutants (Control, BM6, BM6´ and BM9) for potential study of stress tolerance under limited water, salinity and high zinc conditions by testing for plant growth (biophysical and biochemical) traits, as well ascytotoxicity and genotoxicity determination assay via MTT and epifluoresence microscopy methods in root tissues of the mutants. Environmental effect was more significant than genotypic contribution on biophysical and biochemical parameters. BM9 mutant was found to be the most stable genotype in tolerance studies among other mutants in artificially created stress environments viz. mannitol (moderated drought), sodium chloride (salinity stress), zinc sulfate (heavy metal stress) and zinc oxide nanoparticles for a time duration. These mutants are a valuable resource for varietal advancements and to determine genes for tolerance to multiple abiotic stresses. To our knowledge this is the first account on validation of manifold abiotic stresses in early flowering rice mutants. This study can additionally assist fastidious detection of stress-tolerance genes in this vital crop.

Inhibitory Mechanism on Combination of Phytic Acid with Methanolic Seed Extract of Syzygium cumini and Sodium Chloride over Bacillus subtilis.

The antibiotic resistance in bacteria responsible for causing community and health care-associated infection displayed a major threat to global health. Use of broad-spectrum antibiotics for the treatment of various ailments poses serious side effects. In the present research, we investigated the combined role of 2% phytic acid with 2% methanolic seed extract of Syzygium cumini and 0.5% sodium chloride for inhibition of Bacillus subtilis and Pseudomonas aeruginosa and found it to be efficient over B. subtilis. The zone of inhibition by present mixture was found to be 2.9 ± 0.0004 and 1.9 ± 0.0006 cm against Bacillus subtilis and P. aeruginosa in comparison to individual component. Mixture was found more potent against B. subtilis and selected for further study. The underlying mechanism involved in inhibitory action of this mixture was determined by Scanning electron microscope, DNA fragmentation and propidium iodide staining. Scanning electron microscopy revealed that inhibition of B. subtilis by this mixture is mainly due to the disruption of bacterial cell membrane, leakage of internal cellular content which ultimately leads to the death of bacterial cells. DNA fragmentation showed apoptotic hallmark through degradation caused by mixture against B. subtilis at various time intervals. Likewise, PI staining also revealed the disruption of bacterial membrane by the mixture as the PI gives fluorescence after binding with DNA. The present study concludes that inhibitory potential of this mixture is mainly due to disruption of bacterial cell membrane, degradation of DNA and creation of pores in the membrane. The mixture could be used for inhibition of food pathogen B. subtilis.

Antimicrobial action of methanolic seed extracts of Syzygium cumini Linn. on Bacillus subtilis.

Phytochemicals of Syzygium cumini are used for the treatment of various diseases as a traditional medicine but the mechanism behind their action is not well reported. Antimicrobial activity of methanolic seed extract of S. cumini was done by agar well diffusion assay on Bacillus subtilis and its zone of inhibition was found to be 20.06 mm in comparison to control having no zone of inhibition. MIC of S. cumini was found to be 0.3 mg/ml. Genomic DNA degradation of B. subtilis reveals apoptosis and FE-scanning electron microscope indicates cell wall cracking on several intervals of time. Results of propidium iodide staining showed few bacterial cells were stained in control; however population of stained cells increased after exposing them for varying period of time. Flow cytometric kinetic data analysis on the membrane permeabilization in bacterial cell showed the significant contribution of antimicrobial potential of the seed extract on antimicrobial-induced permeabilization. In silico analysis revealed two components of S. cumini methanolic extract to be active against four enzymes (PDB ID-1W5D, 4OX3, 3MFD and 5E2F) which are crucial for plasma membrane synthesis in B. subtilis. Moreover lupeol showed highest binding energy for macromolecule 1W5D and 4OX3 forming one hydrogen bond each whereas stigmasterol showed the highest binding energy for macromolecule 3MFD and 5E2F forming four hydrogen bonds and alkyl bonds respectively. It demonstrates that methanolic seed extracts of S. cumini could be used for inhibition of food born infection caused by B. subtilis and also an alternative of prevalent antibiotics.

Optimized evolution of networks for principal eigenvector localization.

Network science is increasingly being developed to get new insights about behavior and properties of complex systems represented in terms of nodes and interactions. One useful approach is investigating the localization properties of eigenvectors having diverse applications including disease-spreading phenomena in underlying networks. In this work, we evolve an initial random network with an edge rewiring optimization technique considering the inverse participation ratio as a fitness function. The evolution process yields a network having a localized principal eigenvector. We analyze various properties of the optimized networks and those obtained at the intermediate stage. Our investigations reveal the existence of a few special structural features of such optimized networks, for instance, the presence of a set of edges which are necessary for localization, and rewiring only one of them leads to complete delocalization of the principal eigenvector. Furthermore, we report that principal eigenvector localization is not a consequence of changes in a single network property and, preferably, requires the collective influence of various distinct structural as well as spectral features.

Isolation and Characterization of Fusarium verticillioides NKF1 for Unsaturated Fatty Acid Production.

Polyunsaturated fatty acid helps to prevent diseases like cardiovascular, inflammation, and cognitive abilities for developmental disorders. The main objective of this research is the screening of polyunsaturated fatty acid producing fungi from soil samples of mangrove from the seashore coastal areas in India. Fusarium verticillioides species showed the presence of saturated and unsaturated fatty acid in the starch yeast-extract medium. Among the representative isolate, F. verticillioides NKF1 was found to grow in a YEP broth medium and produce the maximum lipid. The gas chromatography was used to identify the fatty acids present in fungal strain. Saturated fatty acid such as palmitic acid (C16:0) 0.14/100 g, stearic acid (C18:0) 0.09/100 g, and monounsaturated fatty acid such as oleic acid (C18:1) 0.08/100 g and polyunsaturated fatty acid such as linolenic acid (C18:3ω3) 0.08/100 g were present in significant amount in the fungal strain. Fungal strain F. verticillioides NKF1 was characterized by SEM and molecular characterization by 18S rRNA. The internal transcribed spacer (ITS) sequences were analyzed by 18S rRNA and ITS4 sequences of related fungi were sequenced, and then the data were compared with NCBI database. This newly isolated F. verticillioides NKF1 was found to be a promising culture for the development of an economical method for commercial production of linolenic acid (ω-3 fatty acid).

Network Topologies Decoding Cervical Cancer.

According to the GLOBOCAN statistics, cervical cancer is one of the leading causes of death among women worldwide. It is found to be gradually increasing in the younger population, specifically in the developing countries. We analyzed the protein-protein interaction networks of the uterine cervix cells for the normal and disease states. It was found that the disease network was less random than the normal one, providing an insight into the change in complexity of the underlying network in disease state. The study also portrayed that, the disease state has faster signal processing as the diameter of the underlying network was very close to its corresponding random control. This may be a reason for the normal cells to change into malignant state. Further, the analysis revealed VEGFA and IL-6 proteins as the distinctly high degree nodes in the disease network, which are known to manifest a major contribution in promoting cervical cancer. Our analysis, being time proficient and cost effective, provides a direction for developing novel drugs, therapeutic targets and biomarkers by identifying specific interaction patterns, that have structural importance.

Origin and implications of zero degeneracy in networks spectra.

The spectra of many real world networks exhibit properties which are different from those of random networks generated using various models. One such property is the existence of a very high degeneracy at the zero eigenvalue. In this work, we provide all the possible reasons behind the occurrence of the zero degeneracy in the network spectra, namely, the complete and partial duplications, as well as their implications. The power-law degree sequence and the preferential attachment are the properties which enhances the occurrence of such duplications and hence leading to the zero degeneracy. A comparison of the zero degeneracy in protein-protein interaction networks of six different species and in their corresponding model networks indicates importance of the degree sequences and the power-law exponent for the occurrence of zero degeneracy.

Assortative and disassortative mixing investigated using the spectra of graphs.

We investigate the impact of degree-degree correlations on the spectra of networks. Even though density distributions exhibit drastic changes depending on the (dis)assortative mixing and the network architecture, the short-range correlations in eigenvalues exhibit universal random matrix theory predictions. The long-range correlations turn out to be a measure of randomness in (dis)assortative networks. The analysis further provides insight into the origin of high degeneracy at the zero eigenvalue displayed by a majority of biological networks.