Perception of nurse administrators regarding electronic nursing documentation

Background: Nurses represent the largest profession in the healthcare. Always present at patient’s bedside, nurses weave together many facets and create order in the work environment. In addition to providing direct patient care, nurses are also responsible for recording the nursing activities. Handwritten documents however, run a risk of being inconsistent and unstructured often leading to omission of pertinent patient data which may ultimately impact nursing interventions and patient outcomes. Research studies continue to reveal substandard nursing documentation. Hence, nurse administrators today are challenged to achieve; outstanding outcome measures; highest quality quartile ratings for patient care; stellar accreditation performance and various other quality measures. Therefore, development of strategies to improve quality of nursing documentation remains a top priority among nurse administrators. In order to accomplish this, moving from paper to electronic clinical documentation system may be a key tool. For almost two decades, electronic health records have become increasingly popular. Although nurses’ perception regarding electronic nursing documentation is one of the most important indicators of the application of nursing information system, it is however, equally important to explore the perception of nurse administrators regarding electronic nursing documentation. The purpose of this study was to explore the perceptions of nurse administrator’s regarding electronic nursing documentation.Methods: A descriptive study was undertaken to explore the perception of 26 nurse administrators working in a teaching hospital. A valid and reliable perception assessment scale was developed to generate data. The collected data was analysed using descriptive analysis.Results: Findings revealed that nearly half of the nurse administrators reported a moderately favourable perception towards electronic nursing documentation.Conclusions: It was concluded that overall nurse administrators have a positive perception of electronic nursing documentation which would be beneficial in promoting a positive organization climate towards the acceptance of electronic health records.

Terzyme: a tool for identification and analysis of the plant terpenome.

BACKGROUND: Terpenoid hydrocarbons represent the largest and most ancient group of phytochemicals, such that the entire chemical library of a plant is often referred to as its 'terpenome'. Besides having numerous pharmacological properties, terpenes contribute to the scent of the rose, the flavors of cinnamon and the yellow of sunflowers. Rapidly increasing -omics datasets provide an unprecedented opportunity for terpenome detection, paving the way for automated web resources dedicated to phytochemical predictions in genomic data. RESULTS: We have developed Terzyme, a predictive algorithm for identification, classification and assignment of broad substrate unit to terpene synthase (TPS) and prenyl transferase (PT) enzymes, known to generate the enormous structural and functional diversity of terpenoid compounds across the plant kingdom. Terzyme uses sequence information, plant taxonomy and machine learning methods for predicting TPSs and PTs in genome and proteome datasets. We demonstrate a significant enrichment of the currently identified terpenome by running Terzyme on more than 40 plants. CONCLUSIONS: Terzyme is the result of a rigorous analysis of evolutionary relationships between hundreds of characterized sequences of TPSs and PTs with known specificities, followed by analysis of genome-wide gene distribution patterns, ontology based clustering and optimization of various parameters for building accurate profile Hidden Markov Models. The predictive webserver and database is freely available at http://nipgr.res.in/terzyme.html and would serve as a useful tool for deciphering the species-specific phytochemical potential of plant genomes

Bioconversion of Weedy Waste into Sugary Wealth

Efforts put in overriding the inulin abundant invader nastiest category I weeds are infeasible that lead into its impermanent confiscation. Hence, their heedful exploitation is obligatory. These invasive weeds have ample amount of inulin, which serves as a renewable, cheap raw substrate for inulinase production. Therefore, they have enticed intention of many researchers toward exploring more idiosyncratic inulinase producing microbial strains that utilize invasive inulin-rich weeds as substrate for fructose liberation. Plenteous industrial applications of inulinases have marked it distinctly crucial in recent biotechnological epoch. This review thus elaborates the literature on infused footprints embedded by the substituted low calorie healthy sweetener in new advancing fields

Rust (Uromyces viciae-fabae Pers. de-Bary) of Pea (Pisum sativum L.): Present Status and Future Resistance Breeding Opportunities

Uromyces viciae-fabae Pers. de-Bary is an important fungal pathogen causing rust in peas (Pisum sativum L.). It is reported in mild to severe forms from different parts of the world where the pea is grown. Host specificity has been indicated in this pathogen in the field but has not yet been established under controlled conditions. The uredinial states of U. viciae-fabae are infective under temperate and tropical conditions. Aeciospores are infective in the Indian subcontinent. The genetics of rust resistance was reported qualitatively. However, non-hypersensitive resistance responses and more recent studies emphasized the quantitative nature of pea rust resistance. Partial resistance/slow rusting had been described as a durable resistance in peas. Such resistance is of the pre-haustorial type and expressed as longer incubation and latent period, poor infection efficiency, a smaller number of aecial cups/pustules, and lower units of AUDPC (Area Under Disease Progress Curve). Screening techniques dealing with slow rusting should consider growth stages and environment, as both have a significant influence on the disease scores. Our knowledge about the genetics of rust resistance is increasing, and now molecular markers linked with gene/QTLs (Quantitative Trait Loci) of rust resistance have been identified in peas. The mapping efforts conducted in peas came out with some potent markers associated with rust resistance, but they must be validated under multi-location trails before use in the marker-assisted selection of rust resistance in pea breeding programs

Enhancement of CO gas sensing performance by Mn-doped porous ZnSnO3 microspheres

This work reports the synthesis of Mn-doped ZnSnO3 microspheres (Zn1−xMnxSnO3) using a simple co-precipitation method with (x = 0 to 0.15) and characterized for structural, morphological, surface area, and sensing properties. X-ray diffraction (XRD) analysis revealed the face-centered cubic structure of Mn-doped ZnSnO3 samples. Brunauer–Emmett–Teller (BET) analysis demonstrated the variation in surface area from 15.229 m2 g−1 to 42.999 m2 g−1 with x = 0 to 0.15 in Zn1−xMnxSnO3. XPS indicates the change in the defect levels by Mn doping, which plays a crucial role in chemical sensors. Indeed a significant increase (≈311.37%) in CO gas sensing response was observed in the x = 0.10 sample compared to pure ZnSnO3 with a simultaneous reduction in operating temperature from 250 to 200 °C. Moreover, remarkable enhancements in response/recovery times (≈6.6/34.1 s) were obtained in the x = 0.10 sample. The Mn-doped ZnSnO3 could be a promising candidate for CO gas sensing devices used for maintaining air quality

Artificial Light at Night: A Global Threat to Plant Biological Rhythms and Eco-Physiological Processes

Light is crucial environmental factor for primary resource and signalling in plants and provide optimum fitness under fluctuating environments from millions of year. However, due to urbanization, and human development activities lot of excess light generated in environment during night time and responsible for anthropogenic generated pollution (ALAN; artificial night light pollution). This pollution has cause for serious problem in plants as it affects their processes and functions which are under the control of light or diurnal cycle. Plant biorhythms mostly diurnal rhythms such as stomatal movements, photosynthetic activity, and many more metabolic processes are under the control of period of light and dark, which are crucially affected by artificial light at night. Similarly, the crucial plant processes such as pollination, flowering, and yield determining processes are controlled by the diurnal cycle and ALAN affects these processes and ultimately hampers the plant fitness and development. To keep in mind the effect of artificial light at night on plant biorhythm and eco-physiological processes, this chapter will focus on the status of global artificial night light pollution and the responsible factors. Further, we will explore the details mechanisms of plant biorhythm and eco-physiological processes under artificial light at night and how this mechanism can be a global threat. Then at the end we will focus on the ANLP reducing strategies such as new light policy, advanced lightening technology such as remote sensing and lightening utilisation optimisation

Germplasm variability-assisted near infrared reflectance spectroscopy chemometrics to develop multi-trait robust prediction models in rice

Rice is a major staple food across the world in which wide variations in nutrient composition are reported. Rice improvement programs need germplasm accessions with extreme values for any nutritional trait. Near infrared reflectance spectroscopy (NIRS) uses electromagnetic radiations in the NIR region to rapidly measure the biochemical composition of food and agricultural products. NIRS prediction models provide a rapid assessment tool but their applicability is limited by the sample diversity, used for developing them. NIRS spectral variability was used to select a diverse sample set of 180 accessions, and reference data were generated using association of analytical chemists and standard methods. Different spectral pre-processing (up to fourth-order derivatization), scatter corrections (SNV-DT, MSC), and regression methods (partial least square, modified partial least square, and principle component regression) were employed for each trait. Best-fit models for total protein, starch, amylose, dietary fiber, and oil content were selected based on high RSQ, RPD with low SEP(C) in external validation. All the prediction models had ratio of prediction to deviation (RPD) > 2 amongst which the best models were obtained for dietary fiber and protein with R2 = 0.945 and 0.917, SEP(C) = 0.069 and 0.329, and RPD = 3.62 and 3.46. A paired sample t-test at a 95% confidence interval was performed to ensure that the difference in predicted and laboratory values was non-significant

Agro-morphological characterization of lentil germplasm of Indian National Genebank and Development of a core set for efficient utilization in lentil improvement programs

Lentil (Lens culinaris Medik.) is one of the major cool-season pulse crops worldwide. Its increasing demand as a staple pulse has led to the unlocking of diverse germplasm collections conserved in the genebanks to develop its superior varieties. The Indian National Genebank, housed at the Indian Council of Agricultural Research (ICAR)-National Bureau of Plant Genetic Resources, New Delhi, India, currently has 2,324 accessions comprising 1,796 indigenous and 528 exotic collections. This study was conducted to unveil the potential of lentil germplasm by assessing its agro-morphological characteristics and diversity, identifying trait-specific germplasm, and developing a core set. The complete germplasm set was characterized for two years, i.e., 2017-2018 and 2018-2019, and data were recorded on 26 agro-morphological traits. High phenotypic variability was observed for nine quantitative and 17 qualitative traits. A core set comprising 170 accessions (137 Indian and 33 exotic) was derived based on the characterization data as well as geographical origin using a heuristic method and PowerCore software. This core set was found to be sufficiently diverse and representative of the entire collection based on the comparison made using Shannon-Weaver diversity indices and χ2 test. These results were further validated by summary statistics. The core set displayed high genetic diversity as evident from a higher coefficient of variance in comparison to the entire set for individual traits and overall Shannon-Weaver diversity indices (entire: 1.054; core: 1.361). In addition, the total variation explained by the first three principal components was higher in the core set (70.69%) than in the entire collection (68.03%). Further, the conservation of pairwise correlation values among descriptors in the entire and core set reflected the maintenance of the structure of the whole set. Based on the results, this core set is believed to represent the entire collection, completely. Therefore, it constitutes a potential set of germplasm that can be used in the genetic enhancement of lentils

Degeneration in Renal Cells of Freshwater Fish (Channa punctata) under Exposure of Nigrosine Black (Acid Black-2), a Tanning Industry Dye

Nigrosine Black (Acid Black-2) is popularly used in tanning industries and a huge amount of this dye comes out with effluent of tanning industries, this dye reached near water bodies, and what impact produced on their aquatic life not reveal yet, Hence a study was plan to find out the impact of Nigrosine black dye on the renal cell of freshwater fish Channa punctata. Sub-acute and chronic exposure to Nigrocine Black produced significant renal cellular degeneration in fish C. punctata. The 1/20th LC50 (96h) of the Nigrocine Black produced degenerating changes in the kidney tissues of fish. Renal corpuscles were revealing swollen and contained some degenerated RBC and thmbrocytes, which appeared to be cellular debris in Bowman space, due to the rapid destruction of the nuclei of erythrocytes. The liberated hemoglobin and other cytoplasmic materials were also observed, while 1/20th  of LC50 (96hr) of Nigrosine Black produced renal degeneration in Bowman’s capsule and swelling in the glomerulus in the intoxicated fish along with renal tubules atrophy, degeneration  as compared to the control group of fish. The low dose of Nigrosine Black Toxicity in fish produced nephropathy, and nephrosis. While the high dose of Nigrosine black dye produces Glomerulonephritis in experimental fish. The kidney cells of experimental fish are damaged by both doses of Nigrosine Black. The physico-chemical property of aquarium water was kept constant during whole duration of experiment