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Background: Personal hygiene plays a major role to promote healthy life. This study was performed to assess the current level of knowledge and practicing behavior in regard to hand washing, bathing, tooth brushing, and taking care of nail and hair. Statement of the Problem: A study to assess the effectiveness of planned teaching programme on personal hygiene of daily routine of students in selected school Ankola. Objectives: To assess the pretest level of knowledge of students regarding personal hygiene; To assess the posttest level of knowledge of students regarding personal hygiene; To find the association between preexisting knowledge on personal hygiene with selected sociodemographic variable. Research Methodology: Research approach: Quantitative evaluative approach; Research design: One Group Pre Test Post Test Design; Research Setting: PPS Ankola; Population: Students studying in 5th 6th 7th student selected rural primary School at Ankola; Sample size: 30 students; Sampling technique: Non probability purposive sampling technique; Tool: Structured knowledge questionnaire. Results: The result showed that the PPS school students who participated in the study were almost evenly distributed by gender (53.33% males and 46.66%females). Most of the students belonged to the 12-13 years age group. The knowledge of the students regarding general body cleanliness was 80% in post-test as compared to 3.6% in pre-test. Conclusion: Overall trend of knowledge about personal hygiene was in poor condition among students at the time of pre-test. Post-test results were highly satisfactory.

The field experiment undertaken during 2018 at Sardarkrushinagar Dantiwada Agricultural University, Sardarkrushinagar evaluated the efficacy of insecticides by foliar application against fruit fly Bactrocera cucurbitae (Coquillet) in cucumber. Among the treatments evaluated, the least fruit damage at 10 and 14 days after second spray was observed with flubendiamide 480SC @ 0.3 l+ jaggery 5 kg/ ha followed by flubendiamide 480SC @ 0.3 l/ ha. The maximum fruit yield (48.29 q/ ha) was obtained with foliar application of flubendiamide 480SC @ 0.3 l/ ha+ jaggery, and maximum benefit in terms of protection cost benefit ratio (PCBR- 1:12.84) was observed with profenophos 50EC @ 1 l + jaggery 5 kg/ ha.

The present study was focused to study the production of secondary metabolite by the fungus, F. chlamydosporum on a non-defined medium with less concentration of nitrogen; the organic nitrogen source being peptone and beef extract. In this context, we have been successful in extracting a polyketide pigment from the fungus by using the homogenization technique. The pigments thus extracted were subjected to various purification techniques via thin layer chromatography, column chromatography, UV-visible spectrophotometry, fourier-transform infrared spectroscopy and finally molecular determination by liquid chromatography coupled to tandem quadrupole mass spectrometry (LC-MS-MS). The polyketide red pigment was finally characterized and identified to be fusarubin following which its cytotoxicity was evaluated in vitro by using normal lung fibroblast cell lines (MRC-5). In the verge of researchers identifying novel compounds for various applications, the production of fusarubin by the fungus can be a major breakthrough as fusarubin has been investigated to exhibit many pharmacological activities. Though fusarubin is reported to be produced by other Fusarium species, this is the foremost study on the production of fusarubin by F. chlamydosporum; the composition of the culture medium is also unique. The production of this polyketide probably correlates in the pathogenesis of F. chlamydosporum as studies comment on this fungus as an opportunistic pathogen.

Although splicing is a major driver of RNA nuclear export, many intronless RNAs are efficiently exported to the cytoplasm through poorly characterized mechanisms. For example, GC-rich sequences promote nuclear export in a splicing-independent manner, but how GC content is recognized and coupled to nuclear export is unknown. Here, we developed a genome-wide screening strategy to investigate the mechanism of export of NORAD, an intronless cytoplasmic long noncoding RNA (lncRNA). This screen revealed an RNA binding protein, RBM33, that directs the nuclear export of NORAD and numerous other transcripts. RBM33 directly binds substrate transcripts and recruits components of the TREX–NXF1/NXT1 RNA export pathway. Interestingly, high GC content emerged as the feature that specifies RBM33-dependent nuclear export. Accordingly, RBM33 directly binds GC-rich elements in target transcripts. These results provide a broadly applicable strategy for the genetic dissection of nuclear export mechanisms and reveal a long-sought nuclear export pathway for transcripts with GC-rich sequences.

Lympho plasmacytoma is distinct type of diffuse large B cell lymphoma predominantly seen in HIV-positive patients. The diagnosis of lympho plasmacytoma could be a challenge due to its overlapping characterizes with those of myeloma and lymphoma. We report a case of a 50-year-old man who initially presented with a painful solitary destructive lesion at the second lumbar vertebra. Clinico-pathological findings were consistent with a solitary plasmacytoma, and he was treated with definitive radiotherapy. Eight months after completing radiotherapy, he was found to have similar lesions at D4 vertebral body, multiple ribs, and pelvis. Subsequent biopsy confirmed lympho plasmacytoma. Because of its rarity and heterogeneous presentations, lympho plasmacytoma could easily be overlooked clinically and pathologically in immunocompetent patients. The diagnosis of lympho plasmacytoma should be considered when there is coexpression of myeloma and lymphoma immune markers.

Studying of bacteria prevalence and antimicrobial susceptibility in samples from foot ulcer patients with chronic wounds will provide the epidemiological information on chronic wound infections, representing support for diagnosis, treatment and management of this pathology, thus preventing further complications of foot infection. There are many risk factors associated with a foot ulcer, so identifying those risk factors and preventing them will help in reducing the incidence of the disease to a certain extend. Identifying the type of organisms causing the chronic wound infection, antibiotic sensitivity and resistance representing support for diagnosis, treatment and management thus preventing further complications of foot infection, and to understand the significant risk factors associated with the development of foot ulcers. An interventional study was conducted among the 80 patients with foot ulcers admitted in General surgery ward of a medical college teaching hospital from Dec 2018 to May 2019. Antimicrobial susceptibility results showed that gram-negative organism was more prevalent and among the species, the isolated majority was found to be Staphylococcus aureus 28 (0.35%) followed by Klebsiella 16(20%) and E.coli15(18.75%). The most sensitive antibiotic found was Meropenam70 (87.5%) followed by Imipenam 67(83.75%) and Linezolid 65(81.25%) The most resistant antibiotic was Cotrimoxazole 66(82.5%). This study concludes that high proportion of foot ulcers were found amongst diabetic patients than non-diabetic patients, and were often associated with trauma, cellulitis, gangrene. Some of the critical risk factors for foot ulcers included low educational status, previous history of foot ulcer, previous amputation was done, duration of ulcers, smoking, peripheral neuropathy, infection and HbA1c levels of patients.

There has been a growth in Australian school-based nurses to address the inequities confronted by vulnerable students and school populations. Failure to address inequities can be evidenced in intergenerational poverty, poorer health and educational attainment and diminished life opportunities. School-based nurses are ideally located to advocate for public health policies and programs that address social determinants that detrimentally affect the health of school populations. However, school-based nurses can confront professional and speciality challenges in extending their efforts beyond individual student advocacy to effect change at the school population level. Guidance is required to redress this situation. This paper describes public health advocacy, the professional and speciality advocacy roles of school-based nurses and the barriers they confront in advocating for the health of school populations and strategies that can be used by key stakeholders to enhance school-based nursing public health advocacy efforts. School-based nurses who are competent, enabled and supported public health advocates are required if we are to achieve substantial and sustained health equity and social justice outcomes for vulnerable school populations.

Field studies on evaluation of pongamia and neem oil soap at various concentrations against okra leaf hopper, Amrasca biguttula biguttula (Ishida) was carried out during the year 2018- Treatments i.e. T1: Pongamia oil soap 0.6%; T2: Pongamia oil soap 1%; T3: Pongamia oil soap 2%; T4: Neem oil soap 0.6%; T5: Soap solution 0.5%; T6: Quinalphos 25 EC @ 0.05%; T7: Standard check applied once at vegetative stage and twice during reproductive stage. Quinalphos 25 EC @ 0.05 % was effective followed by pongamia oil soap 2 per cent, pongamia oil soap 1 per cent, neem oil soap 0.6 per cent and pongamia oil soap 0.6 per cent. The effectiveness of the soap reduced after seven days of treatment.

Cloud computing stands as the most powerful technology for providing and managing resources as a pay-per-usage system. Nowadays, user documents are stocked in the cloud for easy access, less maintenance cost, and better services, etc. Currently, user data stocked up in the cloud are mostly in the form of template-based unstructured text documents. These documents are stocked up in a group by various organizations. Generally, the template-based text document contains large size common information, common terms, conditions, and sensitive information. For protecting the values in the documents, present methods apply encryption algorithms. But these techniques take high encryption time and required more storage space. Applying encryption algorithms is an extremely time-consuming task since the terms and conditions and instructions are common for all documents, and they do not require any security. But the sensitive information in these documents differs as of one user to another user and as well this sensitive information requires protection. Therefore, there is a requirement for an efficient way of segregating, storing and encrypting sensitive information with minimum storage cost, and computational cost. To tackle these issues, a generic safe data storage model is proposed, which makes use of information extraction techniques of Natural Language Processing for sensitive attribute value identification, and Enhanced ECC for securing sensitive data centered on group key. When weighted against the existing entire document and partition-based encryption technique, the proposed generic secure data storage model for cloud takes lesser encryption time and storage space.

Language games represent one of the most fascinating challenges of research in Artificial Intelligence. One of the problems that lies in this set is the development of an automated solution generator for Crossword puzzles. Automatic resolution of crossword puzzles is an open natural language challenge that demands the filling of puzzle grid with candidate answers, while satisfying the grid constraints. Moreover, providing an accurate list of answer candidates has a major impact on the performance of the automatic crossword resolution task. This paper proposes a semantic-based search approach for generating candidate answer lists for definition type clues by taking advantage of the lexical relations encoded in WordNet, the lexical database for English.

Introduction: Larger brain arterial diameters, which may be a consequence of connective tissue disorders or hypertension, are associated with mortality, cognitive decline and risk of dementia. Whether there may be genetic determinants of large brain arterial diameters is unknown, but identifying such traits may shed light into possible mechanistic links between large brain arterial diameters and the observed outcomes. Methods: We studied 3654 participants from four ethnically diverse population-based cohorts: The Atherosclerosis Risk in Communities study (n=1565: 74.3% white, 25.7% black), The Northern Manhattan Study (n=1092: 13.8% white, 16.6% black, 69.6% Hispanic), Epidemiology of Dementia in Singapore (n=647: 31.7% Chinese, 35.7% Malay, 32.6% Indian), and Memory Clinic Cohort in Singapore (n=350: 84.9% Chinese, 7.8% Malay, 7.3% Indian). We measured brain arterial diameters for 13 segments and normalized the averaged diameter per participant to obtain global brain arterial diameter as dependent variable. Genome-wide association studies (GWAS) was performed in each study using linear regression, adjusted for sex, age, head size, number of missing arteries and population substructure. Meta-analysis of association statistics was performed using the METAL to generate combined trait-specific effect estimates. We also performed trans-ethnic meta-regression by MR-MEGA to account for the heterogeneity in allelic effect that is correlated with ancestry. Results: Genome-wide significant (P-8 ) associations were observed for global brain arterial diameter with three SNPs: rs7921574(P=1.2x10 -8 ) mapping to an intron of CNNM2; rs2075858(P=2.47x10 -8 ) and rs2075857 (P=2.37x10 -8 ) mapping to introns of MUC5B. MR-MEGA analysis showed suggestive evidence of association (P=5.05x10 -8 ) for rs7921574. These loci comprise genes involved in response to magnesium transport, neuronal transmission, hypertension, mucociliary clearance and host defense. Conclusion: Our study reveals two novel risk loci for large brain arterial diameters. We have begun to replicate these associations and to identify functional causal variants in independent studies. Identifying these loci may help us to elucidate underlying disease mechanisms.

In order to provide personalized learning and to track student performance, many learning platforms accelerated pre-pandemic. But the focus was for the fortunate students. The recent COVID-19 pandemic taught the education sector the importance of including technology in day-to-day learning activity. Knowledge management is beneficial to all institutes in order to retain experienced teachers and in order to strengthen new teachers with the various steps involved in the process. Managing intellectual assets in order to provide excellent education and to meet all related challenges would be the right step. This study focuses on growth and demand of knowledge management in the education sector. In this chapter, the authors include the matter, like to study the impact of each of the steps involved in knowledge management on the performance of student. In light of the objectives of this chapter, more exploration on studying the effectiveness of knowledge management on education and empirical evidence of the efficacy of KM on the performance of the student is carried out.

Mucormycosis is a rare opportunistic infection, usually seen in diabetics, immunocompromised, or those with coronavirus disease 2019 (COVID-19). Gastrointestinal involvement is uncommon but often deadly. We report a case of gastrointestinal mucormycosis causing intestinal perforation in a non-diabetic, COVID-19 negative, immunocompetent woman, associated with puerperal sepsis. A 22-year-old woman presented to our center on post-natal day five, following delivery with insertion of an intrauterine contraceptive device (IUCD). She had complaints of breathlessness, fatigue, and giddiness. Examination revealed tachycardia, tachypnea, hypotension, and bilateral pedal edema. Following appropriate investigations, she was diagnosed with puerperal sepsis with pre-renal acute kidney injury. Imaging was suggestive of retained products of conception, and she subsequently underwent dilation and evacuation (D&E) on day eight of admission. Following brief symptomatic improvement, on day 10 of admission, she developed vomiting, abdominal distension, and pain, with obstipation. Erect X-ray showed air under the diaphragm, suggestive of perforation. She emergently underwent laparotomy with limited right hemicolectomy, ileostomy with mucous fistula. Intraoperative findings revealed a closed-loop obstruction involving terminal ileum, with two perforations. The biopsy report later revealed colonization of Mucor and hemorrhagic necrosis along the entire length of the resected specimen. She was started on amphotericin B, and after a slow recovery, was discharged. Gastrointestinal mucormycosis is rare and has a mortality rate of 94%. It is usually seen in those with predisposing factors for mucormycosis. This is the first report of mucormycosis associated with puerperal sepsis. It is typically acquired via ingestion and may cause perforation, where mortality is further increased. Diagnosis can only be confirmed by histopathology demonstrating the characteristic morphology of Mucor. Treatment requires resection of necrotic tissues, intensive treatment with amphotericin B, and correction of predisposing factors. Our case highlights the need for a high degree of suspicion for mucormycosis in patients with intestinal perforation, even if immunocompetent, and its potential association with puerperal sepsis.

Greenhouse gas emission during composting process is inevitable, although it relies on natural degradation. A good balance on carbon-to-nitrogen (C/N) ratio as well as the aeration mode could significantly control the emissions. The C/N ratio can be adjusted using optimal feedstock composition. The aeration can be done using passive and active modes. In the present study, greenhouse gas emissions during in-vessel co-composting of septage and organic waste with active and passive modes of aeration were investigated. This fills the gap in implementing suitable septage treatment practice. Retention of high temperature (> 55 °C) for prolonged period ensured the compost hygienization. The active aeration system showed significantly lower greenhouse gas emission compared to that of passive system. The contribution of CH4 and N2O to the total greenhouse gas was estimated to be 2.5% and 7.4% in the passive and 0.9% and 3.8% in the active aeration modes while > 90% was CO2. The resulted compost maturity was confirmed by seed germination index (> 80%) and NO3−/NH4+ index (> 6.25). Our study highlight that in-vessel co-composting with active aeration is a suitable option to convert waste to a nutrient-rich fertilizer in a shorter period compared to other septage treatment options.

The development of vaccines against flaviviruses, including Zika virus (ZIKV) and dengue virus (DENV), continues to be a major challenge, hindered by the lack of efficient and reliable methods for screening neutralizing activity of sera or antibodies. To address this need, we previously developed a plasmid-based, replication-incompetent DENV reporter virus particle (RVP) production system as an efficient and safe alternative to the Plaque Reduction Neutralization Test (PRNT). As part of the response to the 2015–2016 ZIKV outbreak, we developed pseudo-infectious ZIKV RVPs by modifying our DENV RVP system. The use of ZIKV RVPs as critical reagents in human clinical trials requires their further validation using stability and reproducibility metrics for large-scale applications. In the current study, we validated ZIKV RVPs using infectivity, neutralization, and enhancement assays with monoclonal antibodies (MAbs) and human ZIKV-positive patient serum. ZIKV RVPs are antigenically equivalent to live virus based on binding ELISA and neutralization results and are nonreplicating based on the results of live virus replication assays. We demonstrate reproducible neutralization titer data (NT50 values) across different RVP production lots, volumes, time frames, and laboratories. We also show RVP stability across experimentally relevant time intervals and temperatures. Our results demonstrate that ZIKV RVPs provide a safe, high-throughput, and reproducible reagent for large-scale, long-term studies of neutralizing antibodies and sera, which can facilitate large-scale screening and epidemiological studies to help expedite ZIKV vaccine development., Author summary ZIKV is a mosquito-borne virus that can cause severe birth defects and other disorders. Large outbreaks of ZIKV occurred in 2015 and 2016 and there are still no drugs or vaccines available to protect against ZIKV infection. Vaccine development has been hindered by the lack of safe and efficient methods to screen ZIKV neutralizing properties of patient sera or antibodies, especially in the context of large clinical trials. To address this unmet need, we developed and validated the use of ZIKV reporter virus particles (RVPs), a safe, high-throughput, and quantitative alternative to using live virus for neutralization studies. We show that ZIKV RVPs are stable, show lot-to-lot consistency, and provide reproducible neutralization data that is suitable for the large-scale studies needed for development of a ZIKV vaccine, epidemiologic surveillance, and high-throughput screening.

The development of vaccines against flaviviruses, including Zika virus (ZIKV) and dengue virus (DENV), continues to be a major challenge, hindered by the lack of efficient and reliable methods for screening neutralizing activity of sera or antibodies. To address this need, we previously developed a plasmid-based, replication-incompetent DENV reporter virus particle (RVP) production system as an efficient and safe alternative to the Plaque Reduction Neutralization Test (PRNT). As part of the response to the 2015-2016 ZIKV outbreak, we recently developed pseudo-infectious ZIKV RVPs by modifying our DENV RVP system. The use of ZIKV RVPs as critical reagents in human clinical trials requires their further validation using stability and reproducibility metrics for large-scale applications. In the current study, we validated ZIKV RVPs using infectivity, neutralization, and enhancement assays with monoclonal antibodies (MAbs) and human ZIKV-positive patient serum. ZIKV RVPs are antigenically identical to live virus based on binding ELISA and neutralization results and are nonreplicating based on the results of plaque formation assays. We demonstrate reproducible neutralization titer data (NT50 values) across different RVP production lots, volumes, time frames, and laboratories. We also show RVP stability across experimentally relevant time intervals and temperatures. Our results demonstrate that ZIKV RVPs provide a safe, rapid, and reproducible reagent for large-scale, long-term studies of neutralizing antibodies and sera, which can facilitate large-scale screening and epidemiological studies to help expedite ZIKV vaccine development.AUTHOR SUMMARYZIKV is a mosquito-borne virus that can cause severe birth defects and other disorders. Large outbreaks of ZIKV occurred in 2015 and 2016 and there are still no drugs or vaccines available to protect against ZIKV infection. Vaccine development has been hindered by the lack of safe and efficient methods to screen ZIKV neutralizing properties of patient sera or antibodies, especially in the context of large clinical trials. To address this unmet need, we developed and validated the use of ZIKV reporter virus particles (RVPs), a safe, high-throughput and quantitative alternative to using live virus for neutralization studies. We show that ZIKV RVPs are stable, show lot-to-lot consistency and provide reproducible neutralization data that is suitable for large-scale studies are needed for development of a ZIKV vaccine, epidemiologic surveillance, and high-throughput screening.

The present study aimed at understanding the impact of pharmaceutical and personal care product (PPCP) load on compost dynamics and fate of PPCPs during the composting. In addition, the compost dynamics during single PPCP degradation and multiple PPCPs degradation were investigated. Results revealed that co-composting could degrade the pharmaceutical, carbamazepine (CBZ) up to 83% during single pollutant degradation while it was 66% during multiple pollutant system, at an initial concentration (IC) of 5 mg/kg dw. In case of personal care product, namely triclosan (TCS), single pollutant degradation resulted in 86% removal whereas the removal efficiency was 83% in multiple pollutant system. Relatively high concentration of CBZ showed a negative impact on compost dynamics compared to that of TCS. Higher IC resulted in lower temperature development and relatively lower pollutant removal. The study on pollutant transfer in compost solid surface and in leachate revealed that TCS was not leached out while the leaching of CBZ was significant during composting process. The various transformation products formed during composting were identified and tentative pathways for CBZ and TCS degradation were proposed.

Extracting named entities out of unstructured text data is an important problem in natural language processing, with applications in tasks such as sentiment analysis, information retrieval and answer selection in question answering. For identifying named entities, many methods have been developed ranging from knowledge-based methods to supervised machine learning methods. Recently, deep learning models have shown better performance than conventional methods in Named Entity Recognition (NER) tasks. However, it remains unclear how the state-of-the-art neural NER models that have shown superior performance on benchmark datasets perform on other domains. This paper aims to analyze the performance of a state-of-the-art neural NER model in identifying the named entities from judicial text data. The experimentally obtained results show that the model achieved very good results in identifying person names, location names and average result in organization names.

Extracting named entities from natural language text is an important task in natural language processing, with applications in sentiment analysis, information retrieval, and answer selection in question answering. For identifying named entities, many methods have been developed ranging from knowledge-based methods to supervised machine learning methods. In recent years, deep learning models have achieved cutting-edge results in language processing tasks, particularly in Named Entity Recognition (NER). NER aims to locate and categorize proper names in natural language text into predefined classes such as people, organization, location names, etc. In this paper, we provide a comprehensive survey on existing deep learning architectures used in the CoNLL-2003 NER task. We first introduce the basic deep learning models employed in the NER task followed by reviewing the prominent deep learning NER architectures. Furthermore, the present study throws light upon top factors impacting NER performance which includes the design choices of deep-learning-based NER architecture, and the significance of incorporating character-level information, additional lexical features, external training data, etc. while training the NER model.

Septage management is a challenging task across India as more than 44% of the population depends on septic tanks for human waste management. Septage collected from Chennai city, India, was found to be rich in nutrients even though the total solids content (

Aggregation of Tau, a natively unfolded protein, is responsible for tauopathies, a class of neurodegenerative disorders. An active peptide sequence containing 20 amino acids is selected from the Ta...