Topological Cordial Labeling of Some Graphs

A topological cordial labeling of a graph G = (V(G), E(G)) with |V(G)| = n is an injective function f :V(G) →2X where X is any non – empty set such that |X| < n and {f(V(G))} forms a topology on X, that induces a function f*: E(G) →{0,1} defined by f*(uv) = 1 if f(u)∩f(v) is not an empty set and not a singleton set and 0 otherwise for all uv ϵ E(G) such that |ef (0) – ef (1)| ≤ 1, where ef (0) = number of edges labelled with 0 and ef (1) = number of edges labelled with 1. The graph which admits a topological cordial labeling is called a topological cordial graph. In this paper, topological cordial labeling of some special graphs are discussed

Histopathological analysis on sinonasal masses with special stains and immunohistochemical markers

INTRODUCTION: A variety of non-neoplastic and neoplastic conditions involves the sinonasal region by virtue of their anatomic and histologic diversity. Majority of them are non-neoplastic lesions. The incidence of nasal polyps is 1% - 4% in general population. In the neoplastic lesions, benign tumors were more frequent than malignant tumors.1 Carcinomas of nasal cavity and paranasal sinuses account for 0.2-0.8% of all malignant neoplasms and Squamous cell carcinoma represents 3% of all head and neck neoplasms. By Clinical, radiological and endoscopic modalities it is impossible to distinguish simple nasal polyps from neoplastic polypoidal lesions. Histopathology is the mainstay of definitive diagnosis. Special staining such as PAS, Mucicarmine and Immunohistochemical staining profile plays the most important role in accurate diagnosis. AIM AND OBJECTIVES: 1. To study the pathology of various nonneoplastic and neoplastic lesions. 2. To study the frequency and distribution of various nonneoplastic and neoplastic lesions. 3. To study the rare and unusual lesions. 4. To analyse the difficult cases with the help of Immunohistochemistry. Place of Study: Department of Pathology, Thanjavur Medical College Hospital, Thanjavur. Study period: June 2015 to May 2017. Design of Study: Prospective and observational Study. Ethical committee clearance: Prior approval obtained from ethical committee. Sample: A total of 160 Nasal endoscopic biopsy specimens and excision specimens from patients diagnosed with sinonasal mass in ENT department at Thanjavur Medical College Hospital, Thanjavur were included in the study. Inclusion criteria: 1. Cases of sinonasal masses presented to ENT department. 2. Primary lesions of nasal cavity and paranasal sinuses confirmed with Diagnostic nasal endoscopy. 3. All age groups were included. Exclusion criteria: 1. Lesions of nasal skin. 2. Lesions of vestibule of nose, as these tumors probably were related more to skin primary tumors than to nasal carcinoma. 3. Secondary invasion (metastasis) of the sinuses and nasal cavity. 4. Recurrence cases after: Radio therapy / Chemotherapy. Fixative used: All the tissues were fixed in 10% buffered formalin, processed, stained with H & E. Immunohistochemistry special stains (PAS) were used wherever necessary. RESULTS: Out of total 160 cases of sinonasal masses 119 (74.4 %) were Non Neoplastic Lesions and 41 (25.6 %) were Neoplastic Lesions. Schneiderian papilloma 10 cases (6.3%) were the commonest Benign Neoplastic lesions and Squamous Cell Carcinoma were the commonest Malignant Neoplastic lesions.11 cases (6.8%) with male preponderance in age group between 40 to 60 years. IHC with Cytokeratin AE1 / AE3 was very helpful in accurate diagnosis of Undifferentiated carcinoma and special stain with PAS was very helpful in fungal lesions. CONCLUSION: This study mainly highlights the prevalence of Benign and Malignant sinonasal masses. Histopathological evaluation is mandatory for accurate diagnosis and in certain cases such as Undifferentiated carcinomas, Immunohistochemistry became the ultimate diagnostic technique so that a correct and timely intervention can be made for patient management

Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier

Medical data classification is a prime data mining problem being discussed about for a decade that has attracted several researchers around the world. Most classifiers are designed so as to learn from the data itself using a training process, because complete expert knowledge to determine classifier parameters is impracticable. This paper proposes a hybrid methodology based on machine learning paradigm. This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. As a recent off-line learning method, ELM is a single-hidden layer feedforward neural network (FFNN), proved to be an excellent classifier with large number of hidden layer neurons. In this research, PSO is used to determine the optimum set of parameters for the ELM, thus reducing the number of hidden layer neurons, and it further improves the network generalization performance. The proposed method is experimented on five benchmarked datasets of the UCI Machine Learning Repository for handling medical dataset classification. Simulation results show that the proposed approach is able to achieve good generalization performance, compared to the results of other classifiers

Determinants of immunization status of children aged 1-5 years attending a tertiary health care facility: A cross-sectional study

Background: Childhood immunization is one of the key health interventions, which is useful in decreasing the under-five mortality. There has been a recent decline in immunization coverage rates in India as shown by the National Family Health Survey 4. Objective: This study was undertaken with the objective of determining the socio-economic and demographic risk factors associated with partial immunization of children aged 1-5 years attending a tertiary care center in South India. Materials and Methods: This cross-sectional study was done at the outpatient department of Institute of Child Health and Hospital for Children, Chennai, from May 2015 to October 2015. Children aged 1-5 years attending the outpatient department were included by convenient sampling. A sample size of 1100 was calculated based on a pilot study. After obtaining parental informed consent, data were collected on immunization and socio-demographic factors, namely, gender, place of residence, parental education and occupation, family income, number of children, birth order, place of delivery, and awareness of the type of vaccines to be given. The WHO definitions were used to classify immunization status as full, partial, and delayed immunization. Univariate and multivariate logistic regression analyses were performed to determine independent risk factors for partial immunization. Results: Totally, 1104 children were included in the study. 1056 (95.7% [95% confidence interval 94.5-96.9]) were fully immunized, whereas 41 (3.7% [2.59-4.81]) were partially immunized and 7 (0.6% [0.14-1.06]) had delayed immunization. None of the children were totally unimmunized. Univariate analysis identified rural residence, home delivery, having more than 2 children, birth order more than 2, lack of maternal and paternal education beyond primary school level, and lack of awareness on immunization as significant risk factors for partial immunization. After multivariate logistic regression, rural residence, having more than 2 children, and lack of awareness on immunization emerged as independent risk factors for partial immunization. Conclusion: Residing in rural areas, having more than 2 children, and lack of awareness on immunization are significant independent risk factors for a child not being fully immunized

Varietal identification and fingerprinting of Pearl Millet (Pennisetum glaucum L.) varieties and hybrid using morphological descriptors and SSR markers

Pearl Millet (Pennisetum glaucum) is the sixth most important cereal crop in the world. The genomic resources available in Pearl millet can be utilized for fingerprinting and screening of hybrids using SSR markers and will be helpful for the assessment of seed purity. Hence, the present study was focused on fingerprint popular pearl millet varieties and hybrids of Tamil Nadu for varietal identification and hybrid purity test. The varieties used for DNA fingerprinting were CO (Cu) 9, CO 10, Pearl Millet hybrid CO 9 along with the parents, A' line ICMA 93111A and R' line PT 6029-30. The morphological features were recorded to screen the cultivars. The Pearl millet hybrid CO 9 scored the highest value for more than four quantitative characters via., Number of productive tillers (4-6), Leaf blade length (60-68cm), Leaf blade width (4.0-4.5cm), number of nodes (8-10), and 1000 seed weight (13-14g) which is at par and comparable with the composite CO 10  and higher than that of the variety CO (Cu) 9. PCR was performed using 36 SSR primers to find out polymorphism among the varieties. The SSR markers ICMP3021 and PSMP2089 were able to selectively identify CO (Cu) 9 from the other varieties. Whereas, the SSR markers ICMP3018, PSMP2219, and PSMP2220 were used to distinguish CO 10 from the other varieties. Further, the CO10 variety produced additional alleles for all the markers due to its composite nature. Among the thirty-six SSR primers screened, none of them were found suitable to distinguish the TNAU hybrid CO 9 from its parents. The unique DNA fingerprints developed in the present study can be utilized for seed purity testing and varietal identification

Biomass and Carbon Stock Estimation in Woody Grass (\u3cem\u3eDendrocalamus strictus\u3c/em\u3e L.) in Doon Valley, India

Bamboos commonly kown as woody grass are one of the most important species particularly in Asia, where it is frequently considered as the ―timber of the poor‖ (Rao et al., 1985). With about 23 genera and 136 species, India is the second largest reservoir of bamboos, next only to China (SFR, 2013 and Nath et al., 2009). Bamboos occur extensively in the managed ecosystems of India—both as plantations (and in agroforestry (scattered clumps, hedgerows on farm boundaries etc. Dendrocalamus strictus L. is most commonly found bamboo in India. It is widely distributed in dry deciduous forests and grows rapidly in all climatic conditions and occupies about 53 % of total bamboo area in India. It grows better in the drier parts and on sandstone, granite and coarse grained soils with low moisture- retaining capacity and soils with pH range 5.5–7.6. It grows more than 8 feet in 6–8 months. The species is used widely for as raw material in paper mills and also for variety of purposes such as construction, agricultural implements, musical instruments, furniture etc. The species is also suitable for reclamations of degraded and ravine lands. The accurate assessment of biomass estimates of a forest is important for many applications (Brown, 2002; Chave et al., 2004; Arora et al., 2014; Verma et al., 2014). In recent years, the carbon cycle has become an important issue in the world and plants play a major role in carbon storage. Biomass estimation enables us to estimate the amount of carbon dioxide that can be sequestered from the atmosphere. However, most of the carbon and biomass studies focus on assessing the capability of trees viz., poplar, eucalyptus, shisham, chir teak, subabul etc. The studies related to biomass and carbon stock estimation in bamboos is limited. The present study examine specifically the above ground stand biomass, biomass structure and C storage in D. strictus

Di­hydro­oxazolones and di­hydro­imidazolo­nes derived from acyl­glycines: syntheses, mol­ecular structures and supra­molecular assembly

Syntheses and structures are described for some alkyl­idene-substituted di­­hydro­oxazolones and di­hydro­imidazoles derived from simple acyl­glycines. A second, triclinic, polymorph of 4-benzyl­idene-2-(4-methyl­phen­yl)-1,3-oxazol-5(4H)-one, C17H13NO2, (I), has been identified and the structure of 2-methyl-4-[(thio­phen-2-yl)methyl­idene]-1,3-oxazol-5(4H)-one, C9H7NO2S, (II), has been rerefined taking into account the orientational disorder of the thienyl group in each of the two independent mol­ecules. The reactions of phenyl­hydrazine with 2-phenyl-4-[(thio­phen-2-yl)methyl­idene]-1,3-oxazol-5(4H)-one or 2-(4-methyl­phen­yl)-4-[(thio­phen-2-yl)methyl­idene]-1,3-oxazol-5(4H)-one yield, respectively, 3-anilino-2-phenyl-5-[(thio­phen-2-yl)methyl­idene]-3,5-di­hydro-4H-imid­azol-4-one, C10H15N3OS, (III), and 3-anilino-2-(4-methyl­phen­yl)-5-[(thio­phen-2-yl)methyl­idene]-3,5-di­hydro-4H-imidazol-4-one, C21H17N3OS, (IV), which both exhibit orientational disorder in their thienyl groups. The reactions of 2-phenyl-4-[(thio­phen-2-yl)methyl­idene]-1,3-oxazol-5(4H)-one with hydrazine hydrate or with water yield, respectively, N-[3-hydrazinyl-3-oxo-1-(thio­phen-2-yl)prop-1-en-2-yl]benzamide and 2-(benzoyl­amino)-3-(thio­phen-2-yl)prop-2-enoic acid, which in turn react, respectively, with thio­phene-2-carbaldehyde to form 2-phenyl-5-[(thio­phen-2-yl)methyl­idene]-3-{[(E)-(thio­phen-2-yl)methyl­idene]­amino}-3,5-di­hydro-4H-imidazol-4-one, C19H13N3OS2, (V), which exhibits orientational disorder in only one of its thienyl groups, and with methanol to give methyl (2Z)-2-(benzoyl­amino)-3-(thio­phen-2-yl)prop-2-enoate, C15H13NO3S, (VI). There are no direction-specific inter­molecular inter­actions in the crystal structure of the triclinic polymorph of (I), but the mol­ecules of (II) are linked by two independent C—H⋯O hydrogen bonds to form C22(14) chains. Compounds (III) and (IV) both form centrosymmetric R22(10) dimers built from N—H⋯O hydrogen bonds, while compound (V) forms a centrosymmetric R22(10) dimer built from C—H⋯O hydrogen bonds. In the structure of compound (VI), a combination of N—H⋯O and C—H⋯π(arene) hydrogen bonds links the mol­ecules into sheets. Comparisons are made with some similar compounds