Experimental and numerical investigation of capillary flow in SU8 and PDMS microchannels with integrated pillars

Microfluidic channels with integrated pillars are fabricated on SU8 and PDMS substrates to understand the capillary flow. Microscope in conjunction with highspeed camera is used to capture the meniscus front movement through these channels for ethanol and isopropyl alcohol, respectively. In parallel, numerical simulations are conducted, using volume of fluid method, to predict the capillary flow through the microchannels with different pillar diameter to height ratio, ranging from 2.19 to 8.75 and pillar diameter to pitch ratio, ranging from 1.44 to 2.6. The pillar size (diameter, pitch and height) and the physical properties of the fluid (surface tension and viscosity) are found to have significant influence on the capillary phenomena in the microchannel. The meniscus displacement is non-uniform due to the presence of pillars and the non-uniformity in meniscus displacement is observed to increase with decrease in pitch to diameter ratio. The surface area to volume ratio is observed to play major roles in the velocity of the capillary meniscus of the devices. The filling speed is observed to change more dramatically under different pillar heights upto 120 mu m and the change is slow with further increase in the pillar height. The details pertaining to the fluid distribution (meniscus front shapes) are obtained from the numerical results as well as from experiments. Numerical predictions for meniscus front shapes agree well with the experimental observations for both SU8 and PDMS microchannels. It is observed that the filling time obtained experimentally matches very well with the simulated filling time. The presence of pillars creates uniform meniscus front in the microchannel for both ethanol and isopropyl alcohol. Generalized plots in terms of dimensionless variables are also presented to predict the performance parameters for the design of these microfluidic devices. The flow is observed to have a very low Capillary number, which signifies the relative importance of surface tension to viscous effects in the present study

Impact of Maternal Air Pollution exposure on children's lung health: An Indian perspective

© 2018 by the authors. Air pollution has become an emerging invisible killer in recent years and is a major cause of morbidity and mortality globally. More than 90% of the world's children breathe toxic air every day. India is among the top ten most highly polluted countries with an average PM 10 level of 134 μg/m 3 per year. It is reported that 99% of India's population encounters air pollution levels that exceed the World Health Organization Air Quality Guideline, advising a PM 2.5 permissible level of 10 μg/m 3 . Maternal exposure to air pollution has serious health outcomes in offspring because it can affect embryonic phases of development during the gestation period. A fetus is more prone to effects from air pollution during embryonic developmental phases due to resulting oxidative stress as antioxidant mechanisms are lacking at that stage. Any injury during this vulnerable period (embryonic phase) will have a long-term impact on offspring health, both early and later in life. Epidemiological studies have revealed that maternal exposure to air pollution increases the risk of development of airway disease in the offspring due to impaired lung development in utero. In this review, we discuss cellular mechanisms involved in maternal exposure to air pollution and how it can impact airway disease development in offspring. A better understanding of these mechanisms in the context of maternal exposure to air pollution can offer a new avenue to prevent the development of airway disease in offspring

Distributed Synthesis in Continuous Time

We introduce a formalism modelling communication of distributed agents strictly in continuous-time. Within this framework, we study the problem of synthesising local strategies for individual agents such that a specified set of goal states is reached, or reached with at least a given probability. The flow of time is modelled explicitly based on continuous-time randomness, with two natural implications: First, the non-determinism stemming from interleaving disappears. Second, when we restrict to a subclass of non-urgent models, the quantitative value problem for two players can be solved in EXPTIME. Indeed, the explicit continuous time enables players to communicate their states by delaying synchronisation (which is unrestricted for non-urgent models). In general, the problems are undecidable already for two players in the quantitative case and three players in the qualitative case. The qualitative undecidability is shown by a reduction to decentralized POMDPs for which we provide the strongest (and rather surprising) undecidability result so far

Implementation of artificial intelligence based ensemble models for gully erosion susceptibility assessment

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The Rarh Bengal region in West Bengal, particularly the eastern fringe area of the Chotanagpur plateau, is highly prone to water-induced gully erosion. In this study, we analyzed the spatial patterns of a potential gully erosion in the Gandheswari watershed. This area is highly affected by monsoon rainfall and ongoing land-use changes. This combination causes intensive gully erosion and land degradation. Therefore, we developed gully erosion susceptibility maps (GESMs) using the machine learning (ML) algorithms boosted regression tree (BRT), Bayesian additive regression tree (BART), support vector regression (SVR), and the ensemble of the SVR-Bee algorithm. The gully erosion inventory maps are based on a total of 178 gully head-cutting points, taken as the dependent factor, and gully erosion conditioning factors, which serve as the independent factors. We validated the ML model results using the area under the curve (AUC), accuracy (ACC), true skill statistic (TSS), and Kappa coefficient index. The AUC result of the BRT, BART, SVR, and SVR-Bee models are 0.895, 0.902, 0.927, and 0.960, respectively, which show very good GESM accuracies. The ensemble model provides more accurate prediction results than any single ML model used in this study

Minimal Flavour Violation for Leptoquarks

Scalar leptoquarks, with baryon and lepton number conserving interactions, could have TeV scale masses, and be produced at colliders or contribute to a wide variety of rare decays. In pursuit of some insight as to the most sensitive search channels, We assume that the leptoquark-lepton-quark coupling can be constructed from the known mass matrices. We estimate the rates for selected rare processes in three cases: leptoquarks carrying lepton and quark flavour, leptoquarks with quark flavour only, and unflavoured leptoquarks. We find that leptoquark decay to top quarks is an interesting search channel.Comment: 17 pages, 2 figures, minor changes and references adde

Sequential multiplex PCR assay for determining capsular serotypes of colonizing S. pneumoniae

Asymptomatic nasopharyngeal carriage represents an important biological marker for monitoring pneumococcal serotype distribution and evaluating vaccine effects. Serotype determination by conventional method (Quellung reaction) is technically and financially challenging. On the contrary, PCR-based serotyping represents a simple, economic and promising alternative method.Evaluation StudiesJournal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Durability of Mortar Incorporating Ferronickel Slag Aggregate and Supplementary Cementitious Materials Subjected to Wet–Dry Cycles

This paper presents the strength and durability of cement mortars using 0–100% ferronickel slag (FNS) as replacement of natural sand and 30% fly ash or ground granulated blast furnace slag (GGBFS) as cement replacement. The maximum mortar compressive strength was achieved with 50% sand replacement by FNS. Durability was evaluated by the changes in compressive strength and mass of mortar specimens after 28 cycles of alternate wetting at 23 °C and drying at 110 °C. Strength loss increased by the increase of FNS content with marginal increases in the mass loss. Though a maximum strength loss of up to 26% was observed, the values were only 3–9% for 25–100% FNS contents in the mixtures containing 30% fly ash. The XRD data showed that the pozzolanic reaction of fly ash helped to reduce the strength loss caused by wet–dry cycles. Overall, the volume of permeable voids (VPV) and performance in wet–dry cycles for 50% FNS and 30% fly ash were better than those for 100% OPC and natural sand

A comparative analysis of the information content in long and short SAGE libraries

BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a powerful tool to determine gene expression profiles. Two types of SAGE libraries, ShortSAGE and LongSAGE, are classified based on the length of the SAGE tag (10 vs. 17 basepairs). LongSAGE libraries are thought to be more useful than ShortSAGE libraries, but their information content has not been widely compared. To dissect the differences between these two types of libraries, we utilized four libraries (two LongSAGE and two ShortSAGE libraries) generated from the hippocampus of Alzheimer and control samples. In addition, we generated two additional short SAGE libraries, the truncated long SAGE libraries (tSAGE), from LongSAGE libraries by deleting seven 5' basepairs from each LongSAGE tag. RESULTS: One problem that occurred in the SAGE study is that individual tags may have matched to multiple different genes – due to the short length of a tag. We found that the LongSAGE tag maps up to 15 UniGene clusters, while the ShortSAGE and tSAGE tags map up to 279 UniGene clusters. Both long and short SAGE libraries exhibit a large number of orphan tags (no gene information in UniGene), implying the limitation of the UniGene database. Among 100 orphan LongSAGE tags, the complete sequences (17 basepairs) of nine orphan tags match to 17 genomic sequences; four of the orphan tags match to a single genomic sequence. Our data show the potential to resolve 4–9% of orphan LongSAGE tags. Finally, among 400 tSAGE tags showing significant differential expression between AD and control, 79 tags (19.8%) were derived from multiple non-significant LongSAGE tags, implying the false positive results. CONCLUSION: Our data show that LongSAGE tags have high specificity in gene mapping compared to ShortSAGE tags. LongSAGE tags show an advantage over ShortSAGE in identifying novel genes by BLAST analysis. Most importantly, the chances of obtaining false positive results are higher for ShortSAGE than LongSAGE libraries due to their specificity in gene mapping. Therefore, it is recommended that the number of corresponding UniGene clusters (gene or ESTs) of a tag for prioritizing the significant results be considered

Plasma pTau181 predicts cortical brain atrophy in aging and Alzheimer's disease.

BACKGROUND: To investigate the association of plasma pTau181, assessed with a new immunoassay, with neurodegeneration of white matter and gray matter cross-sectionally and longitudinally, in aging and Alzheimer's disease. METHODS: Observational data was obtained from the Alzheimer's Disease Neuroimaging Initiative, in which participants underwent plasma assessment and magnetic resonance imaging. Based on their clinical diagnosis, participants were classified as cognitively unimpaired and cognitively impaired. Linear regressions and linear mixed-effect models were used to test the cross-sectional and longitudinal associations between baseline plasma pTau181 and neurodegeneration using voxel-based morphometry. RESULTS: We observed a negative correlation at baseline between plasma pTau181 and gray matter volume in cognitively unimpaired individuals. In cognitively impaired individuals, we observed a negative association between plasma pTau181 and both gray and white matter volume. In longitudinal analyses conducted in the cognitively unimpaired group, plasma pTau181 was negatively correlated with gray matter volume, starting 36 months after baseline assessments. Finally, in cognitively impaired individuals, plasma pTau181 concentrations were negatively correlated with both gray and white matter volume as early as 12 months after baseline, and neurodegeneration increased in an incremental manner until 48 months. CONCLUSIONS: Higher levels of plasma pTau181 correlate with neurodegeneration and predict further brain atrophy in aging and Alzheimer's disease. Plasma pTau181 may be useful in predicting AD-related neurodegeneration, comparable to positron emission tomography or cerebrospinal fluid assessment with high specificity for AD neurodegeneration