A method for forecasting visibility at Hindon

At present the approach to forecasting visibility is synoptic and personal experience of the weather forecaster. The month of December typically a winter month, is associated with poor visibility. Aviators require visibility forecast in terms of a definite quantitative value at a specific place in specific time frame. Therefore, in this study an attempt is made to develop a suitable model for forecasting visibility in December at a place Hindon near Delhi in a quantitative manner. In the development process of forecasting visibility, different approaches such as auto-regression, multiple regression, climatology and persistence have been attempted. The models are developed using seven years (1984-90) data of December. The model is evaluated with the independent data sets from the recent years 1994-95. It is found that climatology-persistence method provides better results as compared to the multiple regression and auto-regression methods. The developed model provided positive skill scores as high as 70% on development as well as independent data sets.

Super-resolved 3D mapping of molecular orientation with vibrational techniques

When a sample has an anisotropic structure, it is possible to obtain different information, when changing polarization of incident light. Using polarized light of a single vibrational band to determine the in-plane orientation and internal ordering of a sample is a typical practice in materials science. Acquiring mapping data at four different polarizations with a stationary sample than just at two polarizations offers much more insight into the sample structure with proper mathematical treatment. A concurrent analysis of two vibrational bands with perpendicular transition moment orientations allows the understanding of the orientational ordering in three dimensions. We show here, to the best of our knowledge, the first application of concurrent analysis to IR spectromicroscopy data and obtain orientation angles of a model spherulite polycaprolactone sample. Moreover, we show that this method can be easily applied to high resolution, diffraction limited FT-IR and Raman imaging and even to sub-diffraction limit O-PTIR imaging. Due to the non-tomographic experimental approach, no image distortion is visible and nanometer scale orientation domains can be observed. 3D bond orientation maps will enable in-depth characterization of sample structure in a quantitative manner enabling more precise control of their physicochemical properties and function.

Super-resolved 3D mapping of molecular orientation with vibrational techniques

When a sample has an anisotropic structure, it is possible to obtain different information, when changing polarization of incident light. Using polarized light of a single vibrational band to determine the in-plane orientation and internal ordering of a sample is a typical practice in materials science. Acquiring mapping data at four different polarizations with a stationary sample than just at two polarizations offers much more insight into the sample structure with proper mathematical treatment. A concurrent analysis of two vibrational bands with perpendicular transition moment orientations allows the understanding of the orientational ordering in three dimensions. We show here, to the best of our knowledge, the first application of concurrent analysis to IR spectromicroscopy data and obtain orientation angles of a model spherulite polycaprolactone sample. Moreover, we show that this method can be easily applied to high resolution, diffraction limited FT-IR and Raman imaging and even to sub-diffraction limit O-PTIR imaging. Due to the non-tomographic experimental approach, no image distortion is visible and nanometer scale orientation domains can be observed. 3D bond orientation maps will enable in-depth characterization of sample structure in a quantitative manner enabling more precise control of their physicochemical properties and function.

Impact of inquiry-based English teaching through digital applications on primary schoolchildren's reading comprehension and autonomy in pandemic situation

Considering the urgency of integrating technologies in the contemporary classrooms, the aim of the presented study has been shaped to outline the impact of inquiry-based English language teaching through digital applications on primary learners’ reading comprehension and autonomy development during a pandemic outbreak of COVID-19. The research context has been designed in a quantitative manner to analyze experiment results and compare control and treatment group learners’ reading comprehension and academic achievement levels as well as to measure primary schoolchildren’s level of autonomy before and after the treatment. The subjects’ autonomy level, curiosity and interest in reading through digital applications before and after the experiment have been evaluated through pre and post-experimental questionnaires. Learning processes of two experimental and two control groups were compared to create four research contexts for the study. Discrepancy between inquiry-based teaching through a digital library and a traditional way of teaching reading has been emphasized in the study results. The obtained data has been analyzed using SPSS to compare the academic performance results. The study revealed that inquiry-based English language teaching through digital applications highly enhanced the primary learners’ academic performance in reading and increased their motivation level to study independently.

Complementary use of stable isotopes and fatty acids for quantitative diet estimation of sympatric predators, the Antarctic pack-ice seals

The quantitative use of stable isotopes (SIs) for trophic studies has seen a rapid growth whereas fatty acid (FA) studies remain mostly qualitative. We apply the Bayesian tool MixSIAR to both SI and FA data to estimate the diet of three sympatric predators: the crabeater (Lobodon carcinophaga), Weddell (Leptonychotes weddellii) and leopard seal (Hydrurga leptonyx). We used SI data of their vibrissae and FA data of their outer blubber to produce comparable diet estimates for the same individuals. Both SI and FA models predicted the same main diet components, although the predicted proportions differed. For the crabeater seal, both methods identified krill, Euphausia superba, as the main, and almost exclusive, food item, although the FA model estimated a slightly lower proportion, potentially due to the low lipid content of krill compared to the fish species used in the model. For the Weddell seal the FA model identified the fish Pleuragramma antarcticum as the most important prey, whereas the SI model was not able to distinguish among prey species, identifying a ‘fish-squid’ group as the main diet component. For the leopard seal, both models identified krill as the main contributor; however, the predicted proportions for the secondary sources differed. Although vibrissae and outer blubber may not represent the same timeframe, the use of MixSIAR with FA data provides diet estimates comparable to those obtained with SI data, thus, both approaches were complimentary. The use of both biotracers offers a feasible option to study diets of wild animals in a quantitative manner.

A journey through mapping space: characterising the statistical and metric properties of reduced representations of macromolecules

A mapping of a macromolecule is a prescription to construct a simplified representation of the system in which only a subset of its constituent atoms is retained. As the specific choice of the mapping affects the analysis of all-atom simulations as well as the construction of coarse-grained models, the characterisation of the mapping space has recently attracted increasing attention. We here introduce a notion of scalar product and distance between reduced representations, which allows the study of the metric and topological properties of their space in a quantitative manner. Making use of a Wang–Landau enhanced sampling algorithm, we exhaustively explore such space, and examine the qualitative features of mappings in terms of their squared norm. A one-to-one correspondence with an interacting lattice gas on a finite volume leads to the emergence of discontinuous phase transitions in mapping space, which mark the boundaries between qualitatively different reduced representations of the same molecule. Graphicabstract

Improving Estimates of Natural Resources Using Model-Based Estimators: Impacts of Sample Design, Estimation Technique, and Strengths of Association

Natural resource managers need accurate depictions of existing resources to make informed decisions. The classical approach to describing resources for a given area in a quantitative manner uses probabilistic sampling and design-based inference to estimate population parameters. While probabilistic designs are accepted as being necessary for design-based inference, many recent studies have adopted non-probabilistic designs that do not include elements of random selection or balance and have relied on models to justify inferences. While common, model-based inference alone assumes that a given model accurately depicts the relationship between response and predictors across all populations. Within complex systems, this assumption can be difficult to justify. Alternatively, models can be trained to a given population by adopting design-based principles such as balance and spread. Through simulation, we compare estimates of population totals and pixel-level values using linear and nonlinear model-based estimators for multiple sample designs that balance and spread sample units. The findings indicate that model-based estimators derived from samples spread and balanced across predictor variable space reduce the variability of population and unit-level estimators. Moreover, if samples achieve approximate balance over feature space, then model-based estimates of population totals approached simple expansion-based estimates of totals. Finally, in all comparisons made, improvements in estimation were achieved using model-based estimation over design-based estimation alone. Our simulations suggest that samples drawn from a probabilistic design, that are spread and balanced across predictor variable space, improve estimation accuracy.

CAOSS and transcendence: Modeling role-dependent constituent meanings in compounds

Many theories on the role of semantics in morphological representation and processing focus on the interplay between the lexicalized meaning of the complex word on the one hand, and the individual constituent meanings on the other hand. However, the constituent meaning representations at play do not necessarily correspond to the free-word meanings of the constituents: Role-dependent constituent meanings can be subject to sometimes substantial semantic shift from their corresponding free-word meanings (such as -bill in hornbill and razorbill, or step- in stepmother and stepson). While this phenomenon is extremely difficult to operationalize using the standard psycholinguistic toolkit, we demonstrate how these as-constituent meanings can be represented in a quantitative manner using a data-driven computational model. After a qualitative exploration, we validate the model against a large database of human ratings of the meaning retention of constituents in compounds. With this model at hand, we then proceed to investigate the internal semantic structure of compounds, focussing on differences in semantic shift and semantic transparency between the two constituents.

Discordance of PD-L1 Expression at the Protein and RNA Levels in Early Breast Cancer

We aimed to assess if the discrepant prognostic information between Programmed Death Ligand 1 (PD-L1) protein versus mRNA expression in early breast cancer (BC) could be attributed to heterogeneity in its expression. PD-L1 protein and mRNA expression in BC tissue microarrays from two clinical patient cohorts were evaluated (105 patients; cohort 1: untreated; cohort 2: neoadjuvant chemotherapy-treated). Immunohistochemistry (IHC) with SP142, SP263 was performed. PD-L1 mRNA was evaluated using bulk gene expression and RNA-FISH RNAscope®, the latter scored in a semi-quantitative manner and combined with immunofluorescence (IF) staining for the simultaneous detection of PD-L1 protein expression. PD-L1 expression was assessed in cores as a whole and in two regions of interest (ROI) from the same core. The cell origin of PD-L1 expression was evaluated using multiplex fluorescent IHC. IHC PD-L1 expression between SP142 and SP263 was concordant in 86.7% of cores (p < 0.001). PD-L1 IF/IHC was weakly correlated with spatial mRNA expression (concordance 54.6–71.2%). PD-L1 was mostly expressed by lymphocytes intra-tumorally, while its stromal expression was mostly observed in macrophages. Our results demonstrate only moderate concordance between the various methods of assessing PD-L1 expression at the protein and mRNA levels, which may be attributed to both analytical performance and spatial heterogeneity.

Application Notes: APD Handwash Android App – A tool for evaluating the effectiveness of handwashing

Handwashing is a basic infection control practice that needs to be performed correctly to be effective. In the ongoing COVID-19 pandemic, its correct practice is emphasized by public health institutions. However, turning a practice into a habit requires acceptance for adoption of the twenty-second proper procedure to which difficulty remains. To promote and convince the average user, we developed the “APD Handwash app” as a home-use demonstration/education tool to the pitfalls and need of proper handwashing practices through the detection of assigned clean or dirty areas on the hand in a quantitative manner to provide a gauge to the effectiveness of washing when used before and after washing.