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Intra-Operative Frozen Sections: Experience at A Tertiary Care Centre
Preeti, Agarwal,Sameer, Gupta,Kulranjan, Singh,Abhinav, Sonkar Arun,Preeti, Rani,Sunita, Yadav,Mati, Goel Madhu Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.12
The present study was conducted to assess error rates with diagnosis using intra-operative frozen sections, and to indicate ways to increase overall performance. Over a period of two years, 227 cases were biopsied intra-operatively. Errors were observed in 14 cases. Four of these were sampling errors, one by a pathologist and three by surgeons. In seven cases incorrect interpretations were made. Epithelial dysplasia was observed on definitive histology in two cases which was not reported intra-operatively. One case was of ectopic thyroid. In cases of oral cancer where sentinel lymph nodes were sampled, immunohistochemistry for cytokeratin was performed to facilitate identification of micrometastasis. Only single case displayed tumor deposits which was not evident morphologically. Resection margins were reported in seventy eight cases. Some 18% (14/50) benefited from revision of margins; overall sensitivity of intra-operative frozen sections for marginal status was 71.4%, with a specificity of 90.3%. Overall sensitivity was 75% and specificity was 97.5%. Careful observation, pathologist experience and knowledge of limitations help in improving the overall diagnostic outcome.
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Phonatory Characteristics of Male Patients with Classic Essential Tremor
Preetie Shetty Akkunje,Belur Keshavaprasad Yamini,Ravi Yadav,Nagarajarao Shivashankar,Palash Kumar Malo,Kandavel Thennarasu,Shantala Hegde,Pramod Kumar Pal 대한파킨슨병및이상운동질환학회 2021 Journal Of Movement Disorders Vol.14 No.3
This retrospective case-control study compared classic ET patients with age and sex-matched controls. The ET population was subgrouped based on auditory perceptual voice analysis. Electroglottography and acoustic voice samples obtained from both groups were analyzed for contact quotient (CQ) and multidimensional voice program parameters, i.e., fundamental frequency (F0), perturbation, noise, and tremor parameters.
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A Bio-inspired Hybrid Cross-Layer Routing Protocol for Energy Preservation in WSN-Assisted IoT
( Aditya Tandon ),( Pramod Kumar ),( Vinay Rishiwal ),( Mano Yadav ),( Preeti Yadav ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.4
Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.
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Vinod Kumar Malik,Pooja Sangwan,Manjeet Singh,Pavitra Kumari,Niharika Shoeran,Navjeet Ahalawat,Mukesh Kumar,Harsh Deep,Kamla Malik,Preety Verma,Pankaj Yadav,Sheetal Kumari,Aakash,Sambandh Dhal 한국식물병리학회 2024 Plant Pathology Journal Vol.40 No.1
The oldest and most extensively cultivated form of millet, known as pearl millet (<i>Pennisetum glaucum</i> (L.) R. Br. Syn. <i>Pennisetum americanum</i> (L.) Leeke), is raised over 312.00 lakh hectares in Asian and African countries. India is regarded as the significant hotspot for pearl millet diversity. In the Indian state of Haryana, where pearl millet is grown, a new and catastrophic bacterial disease known as stem rot of pearl millet spurred by the bacterium <i>Klebsiella aerogenes</i> (formerly <i>Enterobacter</i>) was first observed during fall 2018. The disease appears in form of small to long streaks on leaves, lesions on stem, and slimy rot appearance of stem. The associated bacterium showed close resemblance to <i>Klebsiella aerogenes</i> that was confirmed by a molecular evaluation based on 16S rDNA and gyrA gene nucleotide sequences. The isolates were also identified to be <i>Klebsiella aerogenes</i> based on biochemical assays, where Klebsiella isolates differed in D-trehalose and succinate alkalisation tests. During fall 2021-2023, the disease has spread all the pearl millet-growing districts of the state, extending up to 70% disease incidence in the affected fields. The disease is causing considering grain as well as fodder losses. The proposed scale, consisting of six levels (0-5), is developed where scores 0, 1, 2, 3, 4, and 5 have been categorized as highly resistant, resistant, moderately resistant, moderately susceptible, susceptible, and highly susceptible disease reaction, respectively. The disease cycle, survival of pathogen, and possible losses have also been studied to understand other features of the disease.
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