Fabrication and Analysis of Amorphous Silicon TFT

The display technology and large area electronics got momentum with the introduction of TFT devices. TFTs can be made using different semiconducting materials or organic conducting materials as the active layer. Each one of them differ in their performance depending on the material used for the active layer. In this paper, fabrication of amorphous silicon TFT using PECVD is carried out. Simulation of the a-Si: H TFT is also carried out with the dimensions similar to that of the masks used for the fabrication. The Id-Vd plot for both the simulation and fabrication is obtained and studied

Lymphocytic thyroiditis: a correlation of cytological grades with clinical, biochemical and ultrasound findings

Background: Hashimoto’s thyroiditis sometimes referred to as goitrous thyroiditis is a synonym of chronic lymphocytic thyroiditis or autoimmune thyroiditis. Chronic lymphocytic thyroiditis (Hashimoto’s thyroiditis) is one of the most common cause of goiter and hypothyroidism, it is found most commonly in middle aged and young female, but can also occur in other age groups, including children. Chronic lymphocytic thyroiditis can be graded based on cytomorphology. In this study an attempt has been made to correlate the grades with clinical findings, biochemical levels and ultrasonography findings.Methods:This is a prospective study conducted on 309 patients in the Department of Pathology, Andhra Medical College, Visakhapatnam. The various parameters like patient’s clinical presentation, biochemical levels and thyroid ultrasound were studied. Fine needle aspiration of thyroid gland and grading of thyroiditis was done on smears. The grades were correlated with above parameters and the correlation indices were evaluated statistically. Chi-square tests were used for statistical correlation and p value of <0.05 was considered significant.Results: Most of the patients were females (297, 96.11%) who commonly presented with a diffuse goiter (263, 85.11%). Asymptomatic cases (193, 62.46%) and elevated TSH (194, 62.78%) were common. Most of the cases had grade I/II disease (299, 96.76%) by cytology. Conclusion:FNAC is a simple, safe and cost effective procedure and is a sensitive and specific diagnostic tool in diagnosing chronic lymphocytic thyroiditis. Cytological grading of chronic lymphocytic thyroiditis helps in assessing the severity of the disease and can predict the thyroid functional status. A combined approach of cytological grading of chronic lymphocytic thyroiditis along with ultrasonography and biochemical levels can detect subclinical hypothyroid states and provide a guide to therapy

Plasma chemokines CXCL10 and CXCL9 as potential diagnostic markers of drug-sensitive and drug-resistant tuberculosis

Tuberculosis (TB) diagnosis still remains to be a challenge with the currently used immune based diagnostic methods particularly Interferon Gamma Release Assay due to the sensitivity issues and their inability in differentiating stages of TB infection. Immune markers are valuable sources for understanding disease biology and are easily accessible. Chemokines, the stimulant, and the shaper of host immune responses are the vital hub for disease mediated dysregulation and their varied levels in TB disease are considered as an important marker to define the disease status. Hence, we wanted to examine the levels of chemokines among the individuals with drug-resistant, drug-sensitive, and latent TB compared to healthy individuals. Our results demonstrated that the differential levels of chemokines between the study groups and revealed that CXCL10 and CXCL9 as potential markers of drug-resistant and drug-sensitive TB with better stage discriminating abilities

A longitudinal study to examine the influence of farming practices and environmental factors on pathogen prevalence using structural equation modeling

The contamination of fresh produce with foodborne pathogens has been an on-going concern with outbreaks linked to these commodities. Evaluation of farm practices, such as use of manure, irrigation water source, and other factors that could influence pathogen prevalence in the farming environment could lead to improved mitigation strategies to reduce the potential for contamination events. Soil, water, manure, and compost were sampled from farms in Ohio and Georgia to identify the prevalence of Salmonella, Listeria monocytogenes (Lm), Campylobacter, and Shiga-toxin-producing Escherichia coli (STEC), as well as Arcobacter, an emerging human pathogen. This study investigated agricultural practices to determine which influenced pathogen prevalence, i.e., the percent positive samples. These efforts identified a low prevalence of Salmonella, STEC, and Campylobacter in soil and water (&lt; 10%), preventing statistical modeling of these pathogens. However, Lm and Arcobacter were found in soil (13 and 7%, respectively), manure (49 and 32%, respectively), and water samples (18 and 39%, respectively) at a comparatively higher prevalence, suggesting different dynamics are involved in their survival in the farm environment. Lm and Arcobacter prevalence data, soil chemical characteristics, as well as farm practices and weather, were analyzed using structural equation modeling to identify which factors play a role, directly or indirectly, on the prevalence of these pathogens. These analyses identified an association between pathogen prevalence and weather, as well as biological soil amendments of animal origin. Increasing air temperature increased Arcobacter and decreased Lm. Lm prevalence was found to be inversely correlated with the use of surface water for irrigation, despite a high Lm prevalence in surface water suggesting other factors may play a role. Furthermore, Lm prevalence increased when the microbiome’s Simpson’s Diversity Index decreased, which occurred as soil fertility increased, leading to an indirect positive effect for soil fertility on Lm prevalence. These results suggest that pathogen, environment, and farm management practices, in addition to produce commodities, all need to be considered when developing mitigation strategies. The prevalence of Arcobacter and Lm versus the other pathogens suggests that multiple mitigation strategies may need to be employed to control these pathogens

Universal Plant DNA Barcode Loci May Not Work in Complex Groups: A Case Study with Indian Berberis Species

BACKGROUND: The concept of DNA barcoding for species identification has gained considerable momentum in animals because of fairly successful species identification using cytochrome oxidase I (COI). In plants, matK and rbcL have been proposed as standard barcodes. However, barcoding in complex genera is a challenging task. METHODOLOGY AND PRINCIPAL FINDINGS: We investigated the species discriminatory power of four reportedly most promising plant DNA barcoding loci (one from nuclear genome--ITS, and three from plastid genome--trnH-psbA, rbcL and matK) in species of Indian Berberis L. (Berberidaceae) and two other genera, Ficus L. (Moraceae) and Gossypium L. (Malvaceae). Berberis species were delineated using morphological characters. These characters resulted in a well resolved species tree. Applying both nucleotide distance and nucleotide character-based approaches, we found that none of the loci, either singly or in combinations, could discriminate the species of Berberis. ITS resolved all the tested species of Ficus and Gossypium and trnH-psbA resolved 82% of the tested species in Ficus. The highly regarded matK and rbcL could not resolve all the species. Finally, we employed amplified fragment length polymorphism test in species of Berberis to determine their relationships. Using ten primer pair combinations in AFLP, the data demonstrated incomplete species resolution. Further, AFLP analysis showed that there was a tendency of the Berberis accessions to cluster according to their geographic origin rather than species affiliation. CONCLUSIONS/SIGNIFICANCE: We reconfirm the earlier reports that the concept of universal barcode in plants may not work in a number of genera. Our results also suggest that the matK and rbcL, recommended as universal barcode loci for plants, may not work in all the genera of land plants. Morphological, geographical and molecular data analyses of Indian species of Berberis suggest probable reticulate evolution and thus barcode markers may not work in this case

A fully labelled image dataset of banana leaves deficient in nutrients

Agriculture is the art and science of cultivating the soil, growing crops and raising livestock. Enhancing crop yield becomes essential to improve economy in agriculture sector. Crops need 16 essential nutrients in balanced factor for their proper growth. Deficiency among these essential nutrients causes stunted growth often leading to significant crop loss. Symptoms of nutrient deficiency in plants can be observed visually which needs to be diagnosed correctly to rectify the problem, so that plants can grow healthily, increasing its yield.Among various crops, banana is one of the staple foods for millions of people across country and world. They contain essential nutrients that can have a defending impact on health of the human beings. The year-round availability, affordability, varietal range, taste, nutritive of banana and medicinal value makes it the favorite fruit among all classes of people. In addition, it also has good export potential. Few of the symptoms due to nutrient's deficiency in banana leaves are like curling of leaves, appearance of yellow strips, yellowing of the leaves, bluish color of young leaves. Deficiency symptoms can be visualized prominently on the leaves of the plant. Further, Machine Learning models can be developed to detect nutrient deficiency in leaves and help farmers in taking relevant measures. Thus, a fully labelled dataset becomes essential to train and test these models to detect nutrient deficiency accurately.The dataset created consists of banana leaf images of various categories like Musa acuminata (Dwarf Cavendish), Robusta, Rasthali, Poovan, Monthan, Elakkibale. Images depict deficiency in eight class of nutrients: boron, calcium, iron, potassium, manganese, magnesium, sulphur and zinc. Table 1 summarizes the essential nutrients and their deficiency symptoms visible on the leaves. Dataset also contains images of healthy leaves. Machine Learning Models can be developed by researchers and students and train them by using the created banana dataset to obtain high accuracy

Dietary Fatty Acids and Immune Response to Food-Borne Bacterial Infections

Functional innate and acquired immune responses are required to protect the host from pathogenic bacterial infections. Modulation of host immune functions may have beneficial or deleterious effects on disease outcome. Different types of dietary fatty acids have been shown to have variable effects on bacterial clearance and disease outcome through suppression or activation of immune responses. Therefore, we have chosen to review research across experimental models and food sources on the effects of commonly consumed fatty acids on the most common food-borne pathogens, including Salmonella sp., Campylobacter sp., Shiga toxin-producing Escherichia coli, Shigella sp., Listeria monocytogenes, and Staphylococcus aureus. Altogether, the compilation of literature suggests that no single fatty acid is an answer for protection from all food-borne pathogens, and further research is necessary to determine the best approach to improve disease outcomes

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Not AvailableThe extent of genetic diversity among nineteen coconut accessions comprising collections from the Indian Ocean Islands were characterized with eight polymorphic microsatellite primers. The fixation index (Fst) was found to be higher (0.78) between Laccadive Micro (LMT) and Chowghat Orange Dwarf (COD) population and the lowest Fst value (0.04) was found among the population Guelle Rose Tall (GLT) and Sri Lankan Tall (SLT). An average Fst value of 0.48 was observed for the accessions indicating higher level of population differentiation among the accessions. The maximum genetic distance (2.29) was observed between Laccadive Green Tall (LGT) and Chowghat Orange Dwarf (COD). The minimum genetic distance (0.04) observed between Laccadive Micro(LMT) and Srilankan Tall (SLT). Overall, the within population variation was found to be higher (67%) than among the population variation (33%) for these coconut accessions. The clustering pattern distinguished two main groups among the Indian Ocean Islands population. The control population COD formed the first group and the remaining populations form the second group. The clustering within the second group revealed the relationship among the accessions under study and the information on possible migration of coconut types within the region which could be useful for planning future collections as well the utilization of conserved types.Not Availabl