Vitamin deficiency prevalence in primary school children in Punjab, India

Background: Vitamin deficiencies are the conditions which are prevalent in the society and parents are unaware of them due to their asymptomatic nature. Overcoming this deficiency is integral in achieving the second Sustainable Development Goal charted out by the United Nations. Treatable and preventable nature of these conditions needs to be emphasized. Aims and objectives of the study were to study the prevalence of clinical features of vitamin deficiencies in primary school children.Methods: This single point cross sectional study was conducted in primary school children in Faridkot and comprised of students in the age group of 5-11 years. A total of 849 students were clinically examined. The clinical features of vitamin deficiencies were recorded. Descriptive analysis was used for interpretation.Results: Overall incidence of vitamin deficiency features was 18.96%. The features of vitamin A, B complex, C, and D deficiency were seen in 7.18%, 18.02%, 3.06% and 8.48% respectively. Some children have more than one deficiency features.Conclusions: The primary school children do suffer from vitamin deficiencies and there should be timely evaluation for these diseases. Larger studies substantiated with blood levels would provide more insight into these conditions

A programmed labour protocol for optimizing labour and delivery

Background: Objectives: 1) To evaluate the effect of programmed labor on duration of labor 2) To assess efficiency of analgesics in reducing severity of labor pains and 3) To find out any maternal and fetal/neonatal complications.Methods: 100 primigravida pregnant women meeting inclusion criteria admitted in labor room 50 were randomly enrolled in study group and 50 in control group.Results: Significant reduction in duration of active phase of labor and 43 (86%) cases had pain relief. Out of them 20 (40%) cases experienced excellent pain relief while in controls, only 22% had pain relief.Conclusions: Labour analgesia ensures pain relief, avoid maternal hyperventilation controls alteration of placental circulation thereby safe guarding the fetus against hypoxia. Thus programmed labor is easy, simple and effective method for painless deliver

Physical properties of heteroatom doped graphene monolayers in relation to supercapacitive performance

885-891Electrodes fabricated using graphene are quite promising for electric double layer capacitors. However graphene has the limitations of low ‘Quantum Capacitance (QC)’ near fermi level due to the presence of Dirac point that can be modified by doping graphenewith suitable dopant. The density functional theory DFT calculations are performed for doped graphene using Boron, Sulphur and phosphorus as dopants to improve the quantum capacitance of electrodes fabricated using graphene. The calculations are performed at temperatures of 233, 300 and 353 °K. From present calculations no significant temperature dependence of quantum capacitance is observed, however a marked increase in QC of value above 58μFcm-2 is seen. Forphosphorus and Sulphur doped graphene a significant energy gap shift of ~ 1.5 eV from the Fermi level is observed that significantly increases the QC at Fermi level to a high value of ~ 35 μFcm-2. With boron dopant as well, a shift of energy gap ~ 1.25eV from the Fermi level is observed. The shift in Dirac point increases quantum capacitance at Fermi level that in turn can increase the energy density of supercapacitor remarkably. The effect of increasing doping concentration on quantum capacitance is also investigated. These results suggest that doping of graphene may result in significant increase in QC near Fermi level, if the dopants are selected carefully depending upon the use of graphene as a positive or negative electrode. The results of these calculations reveal that the problem of low QC of graphene in the range of interest can be addressed by modifying itssurface and structure chemistry which may increase energy density in supercapacitors

Benzimidazolil-kinolinil-merkaptotriazoli kao potencijalni antimikrobni i antivirusni agensi

Condensation of ethylaceto acetate (EAA) with resorcinol in concentrated H2SO4 afforded 7-hydroxy-4-methyl coumarin (1) which on reaction with thiosemicarbazide in anhydrous pyridine yielded 7-hydroxy-4-methyl-quinolinyl [1,5-c]-mercaptotriazole (2). Reaction of 2 with formaldehyde solution and amino acid in ethanol yielded 7-hydroxy-4-methyl-8-(N-methyl-aminoacid)-quinolinyl [1,5-c]-2"-mercaptotriazole (3). Interaction of 3 with o-phenylenediamine in pyridine yielded 7-hydroxy-4-methyl-8-(aminobenzimidazolyl)-quinolinyl [1,5-c]-2"-mercaptotriazole derivatives (4a-e). The latter compounds were evaluated for their antiviral and antimicrobial activities.Kondenzacijom etilacetoacetata (EAA) s rezorciolom u koncentriranoj H2SO4 dobiven je 7-hidroksi-4-metil kumarin (1) koji u reakciji s tiosemikarbazidom u bezvodnom piridinu daje 7-hidroksi-4-metil-kinolinil [1,5-c]-merkaptotriazol (2). Reakcijom spoja 2 s otopinom formaldehida i aminokiselinom u etanolu nastao je 7-hidroksi-4-metil-8-(N-metil-aminokiselina)-kinolinil [1,5-c]-2"-merkaptotriazol (3), koji je s o-fenilendiaminom u piridinu dao 7-hidroksi-4-metil-8-(aminobenzimidazolil)-kinolinil [1,5-c]-2\u27\u27-merkaptotriazol derivate (4a-e). Ispitano je antivirusno i antimikrobno djelovanje spojeva 4

Human-Assisted Continual Robot Learning with Foundation Models

Large Language Models (LLMs) have been shown to act like planners that can decompose high-level instructions into a sequence of executable instructions. However, current LLM-based planners are only able to operate with a fixed set of skills. We overcome this critical limitation and present a method for using LLM-based planners to query new skills and teach robots these skills in a data and time-efficient manner for rigid object manipulation. Our system can re-use newly acquired skills for future tasks, demonstrating the potential of open world and lifelong learning. We evaluate the proposed framework on multiple tasks in simulation and the real world. Videos are available at: https://sites.google.com/mit.edu/halp-robot-learning

Benzimidazolil-kinolinil-merkaptotriazoli kao potencijalni antimikrobni i antivirusni agensi

Condensation of ethylaceto acetate (EAA) with resorcinol in concentrated H2SO4 afforded 7-hydroxy-4-methyl coumarin (1) which on reaction with thiosemicarbazide in anhydrous pyridine yielded 7-hydroxy-4-methyl-quinolinyl [1,5-c]-mercaptotriazole (2). Reaction of 2 with formaldehyde solution and amino acid in ethanol yielded 7-hydroxy-4-methyl-8-(N-methyl-aminoacid)-quinolinyl [1,5-c]-2"-mercaptotriazole (3). Interaction of 3 with o-phenylenediamine in pyridine yielded 7-hydroxy-4-methyl-8-(aminobenzimidazolyl)-quinolinyl [1,5-c]-2"-mercaptotriazole derivatives (4a-e). The latter compounds were evaluated for their antiviral and antimicrobial activities.Kondenzacijom etilacetoacetata (EAA) s rezorciolom u koncentriranoj H2SO4 dobiven je 7-hidroksi-4-metil kumarin (1) koji u reakciji s tiosemikarbazidom u bezvodnom piridinu daje 7-hidroksi-4-metil-kinolinil [1,5-c]-merkaptotriazol (2). Reakcijom spoja 2 s otopinom formaldehida i aminokiselinom u etanolu nastao je 7-hidroksi-4-metil-8-(N-metil-aminokiselina)-kinolinil [1,5-c]-2"-merkaptotriazol (3), koji je s o-fenilendiaminom u piridinu dao 7-hidroksi-4-metil-8-(aminobenzimidazolil)-kinolinil [1,5-c]-2\u27\u27-merkaptotriazol derivate (4a-e). Ispitano je antivirusno i antimikrobno djelovanje spojeva 4

Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease

BACKGROUND: Alzheimer’s disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling. RESULTS: Our approach employs integration of three different AD datasets- GWL,GWA and GWE to identify overlapping candidate genes ranked using a novel cumulative rank score (S(R)) based method followed by prioritization using clusters derived from PPI network. S(R) for each gene is calculated by addition of rank assigned to individual gene based on either p value or score in three datasets. This analysis yielded 108 plausible AD genes. Network modelling by creating PPI using proteins encoded by these genes and their direct interactors resulted in a layered network of 640 proteins. Clustering of these proteins further helped us in identifying 6 significant clusters with 7 proteins (EGFR, ACTB, CDC2, IRAK1, APOE, ABCA1 and AMPH) forming the central hub nodes. Functional annotation of 108 genes revealed their role in several biological activities such as neurogenesis, regulation of MAP kinase activity, response to calcium ion, endocytosis paralleling the AD specific attributes. Finally, 3 potential biochemical biomarkers were found from the overlap of 108 AD proteins with proteins from CSF and plasma proteome. EGFR and ACTB were found to be the two most significant AD risk genes. CONCLUSIONS: With the assumption that common genetic signals obtained from different methodological platforms might serve as robust AD risk markers than candidates identified using single dimension approach, here we demonstrated an integrated genomic convergence approach for disease candidate gene prioritization from heterogeneous data sources linked to AD. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-199) contains supplementary material, which is available to authorized users

Green-Synthesized Graphene for Supercapacitors—Modern Perspectives

Graphene is a unique nanocarbon nanostructure, which has been frequently used to form nanocomposites. Green-synthesized graphene has been focused due to environmentally friendly requirements in recent technological sectors. A very important application of green-synthesized graphene-based nanocomposite has been observed in energy storage devices. This state-of-the-art review highlights design, features, and advanced functions of polymer/green-synthesized graphene nanocomposites and their utility in supercapacitor components. Green graphene-derived nanocomposites brought about numerous revolutions in high-performance supercapacitors. The structural diversity of conjugated polymer and green graphene-based nanocomposites has facilitated the charge transportation/storage capacity, specific capacitance, capacitance retention, cyclability, and durability of supercapacitor electrodes. Moreover, the green method, graphene functionality, dispersion, and matrix–nanofiller interactions have affected supercapacitance properties and performance. Future research on innovative polymer and green graphene-derived nanocomposites may overcome design/performance-related challenging factors for technical usages

The Effect of Modifications of Activated Carbon Materials on the Capacitive Performance: Surface, Microstructure, and Wettability

none7siopenKouao Dujearic-Stephane; Meenal Gupta; Ashwani Kumar; Vijay Sharma; Soumya Pandit; Patrizia Bocchetta; Yogesh KumarDujearic-Stephane, Kouao; Gupta, Meenal; Kumar, Ashwani; Sharma, Vijay; Pandit, Soumya; Bocchetta, Patrizia; Kumar, Yoges

Visual evoked potentials in children with type 1 diabetes mellitus

Background: Insulin-dependent (type 1) diabetes mellitus is associated with different degrees of neuropathies affecting peripheral as well as central neural pathways. The subclinical neurological involvement in diabetic children can be assessed by changes appearing in the electrophysiological parameters like Visual Evoked Potentials (VEPs). The objective of the study was to assess the effect of type I diabetes melitus on the visual evoked potentials in children.Methods: This cross-sectional case-control study was done on 30 children with type 1 diabetes mellitus of minimum two years duration as cases and 30 age and gender matched euglycemic children with normal HbA1c taken as controls. Visual Evoked Potentials (VEPs) were done on both the groups of children and the latencies (ms) of waves -N75, P100, N145 and amplitude (μV) of wave P100 were recorded. The data was compiled in the pre-designed proforma and statistically analysed using student t-test.Results: The increase in the mean latencies of waveforms of VEPs N75, P100 and amplitude P100 were found to be highly significant statistically (p<0.001) in both the eyes among the children with type 1 diabetes mellitus. The mean latency of waveform N145 was found to be statistically insignificant in the two groups (p>0.05).Conclusions: The type 1 diabetes does affect the visual pathways in children. Visual Evoked Potentials are helpful in the detection of early changes in the conduction across the neural pathways in the sub-clinical diseases