133 research outputs found
Are We Causing Antibiotic Resistance with Antibiotic Abuse? A Study among Dentists
No full textINTRODUCTION: With the invention of any new technology their comes the boon and curse both. The invention and use of antibiotics comes a problem of antibiotic resistance which is much more in extent than treating the infectious disease. Keeping this in mind the WHO in 2011 gave the theme “combat drug resistance- No action today, No cure tomorrow” which was very significant. The present study was done with the aim to know the prescription pattern of antibiotics for various dental procedures by dental practitioners.MATERIALS AND METHODS: A specially prepared questionnaire exclusively designed for the study recording all the required relevant general information and information related to antibiotic prescribing patterns was used for data collection. The questionnaire consisted of three sections. The first part of the questionnaire collected the demographic details of the study population like age, gender, Graduate or postgraduate degree, area of specialization and years of practice. In the second section the Questions related to antibiotics use in certain dental clinical procedures and conditions in apparently healthy people were asked from the participants. In the last section of the questionnaire the participants were asked about the questions related to antibiotics use for certain dental clinical procedures in medically compromised cases.RESULTS: Questionnaire response rate of 73% was recorded. The study showed Augmentin to be the first choice of antibiotic by most of the respondents. The study showed that 64% of the endodontists and 74% of the general dentists prescribed antibiotics during root canal therapy where ideally operative intervention would have sufficed. Overuse of antibiotics for routine scaling and extraction was observed.CONCLUSION: The dental profession as a whole needs to acquire a deeper understanding of the global effects of unnecessary antibiotic prescription. Antibiotics when judiciously used are precise life-saving drugs
Compressive Light Field Reconstruction using Deep Learning
No full textabstract: Light field imaging is limited in its computational processing demands of high
sampling for both spatial and angular dimensions. Single-shot light field cameras
sacrifice spatial resolution to sample angular viewpoints, typically by multiplexing
incoming rays onto a 2D sensor array. While this resolution can be recovered using
compressive sensing, these iterative solutions are slow in processing a light field. We
present a deep learning approach using a new, two branch network architecture,
consisting jointly of an autoencoder and a 4D CNN, to recover a high resolution
4D light field from a single coded 2D image. This network decreases reconstruction
time significantly while achieving average PSNR values of 26-32 dB on a variety of
light fields. In particular, reconstruction time is decreased from 35 minutes to 6.7
minutes as compared to the dictionary method for equivalent visual quality. These
reconstructions are performed at small sampling/compression ratios as low as 8%,
allowing for cheaper coded light field cameras. We test our network reconstructions
on synthetic light fields, simulated coded measurements of real light fields captured
from a Lytro Illum camera, and real coded images from a custom CMOS diffractive
light field camera. The combination of compressive light field capture with deep
learning allows the potential for real-time light field video acquisition systems in the
future.Dissertation/ThesisMasters Thesis Computer Engineering 201
Correction: Pan, J.L. Progress to a Gallium-Arsenide Deep-Center Laser. Materials 2009, 2, 1599-1635
No full textThe author acknowledges that her former graduate students, J. E. McManis and M. Gupta, collected the data in the recent review [1], as indicated by the references therein. [...
Biomedical Image Indexing and Retrieval Descriptors: A Comparative Study
No full textAbstractThis paper focuses on the comparison of two new proposed pattern descriptors i.e., local mesh ternary pattern (LMeTerP) and directional local ternary quantized extrema pattern (DLTerQEP) for biomedical image indexing and retrieval. The standard local binary patterns (LBP) and local ternary patterns (LTP) encode the gray scale relationship between the center pixel and its surrounding neighbors in two dimensional (2D) local region of an image whereas the former descriptor encodes the gray scale relationship among the neighbors for a given center pixel with three selected directions of mess patterns which is generated from 2D image and later descriptor encodes the spatial relation between any pair of neighbors in a local region along the given directions (i.e., 0̊, 45̊, 90̊ and 135̊) for a given center pixel in an image. The novelty of the proposed descriptors is that they use ternary patterns from images to encode more spatial structure information which lead to better retrieval. The experimental results demonstrate the superiority of the new techniques in terms of average retrieval precision (ARP) and average retrieval rate (ARR) over state-of-the-art feature extraction techniques (like LBP, LTP, LQEP, LMeP etc.) on three different types of benchmark biomedical databases
Odontotrypes (Odontotrupes) tawangensis Gupta, Chandra & Hillert, 2016, new species
No full text<i>Odontotrypes</i> (<i>Odontotrupes</i>) <i>tawangensis</i> new species <p>(Figs. 1–19)</p> <p> <b>Type locality.</b> India, Arunachal Pradesh state, Tawang district.</p> <p> <b>Type material.</b> 18 specimens: holotype male labeled: “ India, Arunachal Pradesh state, Tawang district / Sela / 27.523491N, 92.106493E / 5.x.2010 / collected K. Chandra ” in ZSCI [ZSI Registration Number: 21489/H4A]. Allotype female labeled: “NE INDIA W, ARUNACHAL PR / TAWANG Monastery vicinity / 27°35´30´´N 91°51´E; 2700–3000 m / 19.-27.v. 2004 ” in SJCP. Paratypes: “ India, Arunachal Pradesh state / Tawang district / Sela 27.523491N, 92.106493E / 5.x.2010 / collected K. Chandra ” 1 male in ZSCI [ZSI Registration Number: 21490/H4A]; “NE INDIA W, ARUNACHAL PR / TAWANG Monastery vicinity / 27°35´30´´N 91°51´E; 2700– 3000 m / 19.-27.v. 2004 ” 1 male in DKCP, 1 male and 1 female in JSCP, 6 males and 4 females in SJCP, 1 male and 1 female in OHCB.</p> <p> <b>Description of holotype</b> (Fig. 1). Length 20.0 mm, maximum width 9.7 mm, oblong and convex. Dorsally black; vertex and elytra at base with metallic luster; ventral surface black with cuprous tinge especially on mesofemora, metafemora, and anterior part of pronotum.</p> <p>Head (Figs. 2, 4): Labrum truncate anteriorly. Anterior clypeal margin broadly arcuate, clypeal disc distinctly elevated in middle, clypeal surface slightly rugopunctate near lateral margins, elevated areas smooth; area around frontoclypeal junction distinctly depressed, T-shaped, suture distinct. Median suture on vertex indistinct; eye tubercle blunt and distinctly prominent dorsally, in lateral view angular; eye canthus smooth.</p> <p>Pronotum (Figs. 3, 5): Transverse, broadest just posteriad of middle; completely bordered (finely at base); lateral margins rounded, not crenulate; anterior marginal carina moderately elevated and widened in middle. Anterior angles blunt, broadly rounded, sides almost straight in anterior third forming a rounded lateral angle; posterior angles bent 45°. Surface completely smooth in middle with few scattered punctures; anterior concavity reduced, simple depression; lateral fovea small with rugopunctation; surface near lateral margins rugopunctate anteriorly and posteriorly.</p> <p>Scutellum (Fig. 7): Pentagonal, basal margin not bordered, slightly declined inward, surface entirely smooth, yellow border present at each side from meeting point to base.</p> <p>Elytra (Fig. 6): Humeral umbone weakly prominent; base almost equal in length to pronotum, neither margined nor carinate; surface glabrous. Surface with 7 distinct striae clearly indicated between suture and humeral umbone, which gradually disappear towards apex; intervals 3–7 convex and impunctate; lateral side with a continuous carina from humeral umbone to apex.</p> <p>Legs (Figs. 8–9): Profemora black, not shiny, completely smooth; mesofemora and metafemora shiny with 2 rows of setose punctures. Protibiae laterally with 5 teeth including 4 distinct anterior teeth, and 1 weak basal tooth (Fig. 8); on ventral side medially with 7 teeth including 3 anterior, sharp, distinct teeth and 4 blunt, reduced teeth (Fig 9).</p> <p>Macropterous (Fig. 10).</p> <p>Abdominal ventrites shiny, serrate punctate.</p> <p>Aedeagus as in Figs. 11–13 (holotype) and 16–17 (paratypes: India, Arunachal Pradesh, Tawang Monastery vicinity, in DKCP).</p> <p>Measurements (mm): Median length of head (excluding labrum and mandibles) 3.1, distance between frontal tubercles 2.9, anterior margin of clypeus (circumference) 4.1, median length of pronotum (dorsal) 5.3, maximum width 9.6, median length of scutellum 1.3, maximum width 1.7, sutural length of elytra (dorsal) 9.2, maximum width combined 9.7, aedeagus (length) 3.7.</p> <p> <b>Variation</b>. Length 17.0–20.0 mm, width 8.5–9.7 mm. The female differs from male by the less developed clypeal tubercle and the weaker protibial teeth.</p> <p> <b>Distribution</b>. Only known from type locality: Sela, Tawang, Arunachal Pradesh, India (Fig. 15).</p> <p> <b>Etymology.</b> The name <i>tawangensis</i> refers to the type locality of this species, the Tawang district of the state of Arunachal Pradesh.</p> <p> <b>Differential diagnosis.</b> <i>Odontotrypes</i> (<i>Odontotrupes</i>) <i>tawangensis</i> new species is distinguished from the closely related species <i>O</i>. (<i>O</i>.) <i>orichalceus</i> (reported from the Tibetan Plateau of Sikkim) by the unique structure of the aedeagus (Figs. 11–13, 16–17) (right paramere with distinct internal truncate appendix situated subapically and directed inward) and the structure of the elytra (elytral striae are distinct basally, becoming more shallowly apically), and the well-developed metathoracic wings. Based on the keys given by Král <i>et al.</i> (2001) <i>Odontotrypes</i> (<i>O.</i>) <i>tawangensis</i> should be classified in the subgenus <i>Odontotrupes</i>. Species of this subgenus that are distributed in Bhutan and India characteristically have slightly reduced or normal-sized metathoracic wings, namely <i>O.</i> (<i>O.</i>) <i>bhutan</i>, <i>O.</i> (<i>O.</i>) <i>gogona</i>, <i>O.</i> (<i>O.</i>) <i>orichalceus</i>, and <i>O.</i> (<i>O.</i>) <i>tawangensis</i>. According to Král <i>et al.</i> (2001) the distribution ranges of <i>Odontotrypes</i> are relatively small, many of them being endemic to single mountain systems, separated by deep river valleys.</p> <p>The authors wish to thank the director of the Zoological Survey of India, for providing them with the necessary facilities and for his encouragements. The first author is thankful to Paul Schoolmeesters (Belgium) for literature, Baiju Lal (former Officer-in-Charge, Coleoptera Section, Zoological Survey of India), Amitava Mujumder, and Joyjit Ghosh. We also thank Marc Miquel (Queen Mary University of London, United Kingdom) for editing our English text and review the earlier version of manuscript and Stanley Jákl, David Král, and Jan Schneider for access to the specimens examined.</p>Published as part of <i>Gupta, Devanshu, Chandra, Kailash & Hillert, Oliver, 2016, Odontotrypes (Odontotrupes) tawangensis new species (Coleoptera: Geotrupidae) from Arunachal Pradesh, India, pp. 559-566 in Zootaxa 4154 (5)</i> on pages 560-565, DOI: 10.11646/zootaxa.4154.5.4, <a href="http://zenodo.org/record/264799">http://zenodo.org/record/264799</a>
Self-reported oral health and denture satisfaction in partially and completely edentulous patients
No full textContext: Edentulism is a handicap that affects the quality of life and nutrition. Tooth loss leads to functional impairment at the level of the orofacial system, significantly interfering with chewing, swallowing and speech, as well as to temporomandibular joint dysfunction, disorders of intermaxillary relation, and facial physiognomy. Aim: The aim of the study was to explore variables that influence self-reported oral health and denture satisfaction in partially and completely edentulous patients using oral health impact profile for edentulous (OHIP-EDENT). Materials and Methods: A hospital-based study was carried out on the patient's age ranged from 30 to 70 years in the dental college who had been treated with complete dentures and removable partial denture using convenience sampling method. Prevalidated questionnaire consisting of OHIP-EDENT was self-administered to all the study participants. The information about the appetite, perceived general and oral health, and satisfaction from the dentures was recorded using a 4-point Likert scale. Data were collected, entered, and analyzed using SPSS version 20.0. One-way ANOVA was performed to test for comparison between different denture groups. P < 0.05 shows statistically significant difference. Results: When the mean of denture satisfaction level was calculated between different denture group and different domains of OHIP-EDENT, there was no difference found in level of denture satisfaction between different denture groups, i.e., overall denture satisfaction mean in Group 1 was 2.18 ± 0.32, Group 2 has 2.23 ± 0.36, Group 3 has the mean of 2.18 ± 0.42, Group 4 has 2.23 ± 0.67, and P value was 0.810 which shows nonsignificant difference. Conclusion: The results of the present study suggest that the poor self-perceived satisfaction among denture wearers affect their quality of life
Proteome data associated with the leaf senescence in Glycine max
No full textAbstractThe data presented in this article are associated with the article “Coupling of gel-based 2-DE and 1-DE shotgun proteomics approaches to dig deep into the leaf senescence proteome of Glycine max” (R. Gupta, S.J. Lee, C.W. Min, S.W. Kim, K.-H. Park, D.-W. Bae, et al., 2016) [1]. Leaf senescence is one of the important aspects of the life cycle of a plant that leads to the recycling of nutrients from source to sink cells. To understand the leaf senescence-associated proteins, we used a combination of gel-based 2-DE and 1-DE shotgun proteomic approaches. Here, we display the 2-DE, Mass spectrometry, and Gene ontology data related with the leaf senescence in soybean [1]
Satellite to Seafloor - The Global Biogeography of the Elasipodid Holothurians
No full textKnowledge of the environmental factors driving species distributions in the deep-sea is essential for a better understanding of the biogeography of the abyssal benthos. Differences in the niches of elasipodid holothurians appear to exist at the level of species, genera and family. This study analysed the global distributions of elasipodid holothurians from records collected from online Natural History Collection databases, cruise reports and published literature.A comparison of the distribution of four families of elasipodid holothurians, in relation to seven abiotic environmental factors found the families Psychropotidae and Elpidiidae to have the most different environmental distributions. POC flux, intra-annual seasonality and inter-annual variability in POC flux were the best explanatory factors for differences between the families. The Elpidiidae were generally found in areas with greater temporal variability. The potential for biogeographic schemes based upon the ecology of the upper ocean to inform management decisions for the deep sea was also investigated. Results suggest that Longhurst’s ‘case models’ are more closely linked to the distribution of species and genera than Longhurst’s biomes. Results also confirmed that provinces from the same ocean and latitude were more similar in terms of species composition, but that historical factors were equally capable of explaining the observed patterns and must be taken into account.Population genetic studies of two species of Elasipodida; Psychropotes longicauda and Oneirophanta mutabilis were conducted using CO1 and 16S molecular markers. Multiple sympatric lineages were found in the Indian, Pacific and Atlantic Oceans in both species. Differences between sympatric lineages were greater than geographic differences within lineages. The potential for speciation in the Antarctic or Southern Ocean before multiple northwards dispersal events is considered the most plausible explanation for the observed patterns. Oceanic gyres therefore do not appear to be barriers to dispersal in these species.The distributions of the elasipodid holothurians are therefore thought to be controlled by a combination of life-history, dispersal ability, temporal and quantitative variations in food supply and competitive interactions as well as historical processes relating to centres of origin for particular genera
Spatial aliasing removal using deep learning super-resolution
No full textImPhys/Acoustical Wavefield Imagin
A comparative assessment of machine learning and deep learning models for the daily river streamflow forecasting
No full textForecasting river streamflow is crucial for hydrological science and optimal water resources management. In this study, six predictive methods were developed, including three machine learning models—random forest (RF), decision tree (DT), and K-nearest neighbors (KNN)—and three deep learning frameworks comprising convolutional neural networks (CNN), long short-term memory (LSTM), and a hybrid CNN-LSTM model. Two gauging stations on the McKenzie River in the United States (USGS 14162500 and USGS 14163900) were selected as case studies for model performance evaluation. Error metrics including root mean square error (RMSE), mean absolute error (MAE), determination coefficient (R²), and Kling-Gupta efficiency (KGE) were applied. Results demonstrated that the deep learning models consistently outperformed the machine learning methods for river streamflow forecasting at both sites. The hybrid CNN-LSTM model yielded the most accurate predictions. Specifically, the error metrics for the superior CNN-LSTM model during testing stage were as follows: at USGS 14162500, RMSE = 14.68 m³/s, MAE = 6.29 m³/s, R² = 0.930, and KGE = 0.960; at USGS 14163900, RMSE = 22.54 m³/s, MAE = 8.48 m³/s, R² = 0.882, and KGE = 0.935. © The Author(s), under exclusive licence to Springer Nature B.V. 2024
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