Surrogate-assisted parallel tempering for Bayesian neural learning

Due to the need for robust uncertainty quantification, Bayesian neural learning has gained attention in the era of deep learning and big data. Markov Chain Monte-Carlo (MCMC) methods typically implement Bayesian inference which faces several challenges given a large number of parameters, complex and multimodal posterior distributions, and computational complexity of large neural network models. Parallel tempering MCMC addresses some of these limitations given that they can sample multimodal posterior distributions and utilize high-performance computing. However, certain challenges remain given large neural network models and big data. Surrogate-assisted optimization features the estimation of an objective function for models which are computationally expensive. In this paper, we address the inefficiency of parallel tempering MCMC for large-scale problems by combining parallel computing features with surrogate assisted likelihood estimation that describes the plausibility of a model parameter value, given specific observed data. Hence, we present surrogate-assisted parallel tempering for Bayesian neural learning for simple to computationally expensive models. Our results demonstrate that the methodology significantly lowers the computational cost while maintaining quality in decision making with Bayesian neural networks. The method has applications for a Bayesian inversion and uncertainty quantification for a broad range of numerical models.Comment: Engineering Applications of Artificial Intelligenc

Designing and Molecular Modeling Studies on Novel Bisindole-imidazopyridine Against Adrenocarcinoma

Adrenocarcinoma is an uncontrolled growth of epithelial cells originating in the ducts or breast lobules. EGFR or Epidermal growth factor receptor is a transmembrane protein with cytoplasmic kinase activity that transduces important growth factor signaling from the extracellular milieu to the cell. 45 bisindole-imdazopyridine analogues were obtained from the literature. Free-wilson QSAR studies were erformed on the given data set. Compounds were designed on the basis of QSAR studies. Further, Molecular docking studies were performed on the designed compounds to check the binding affinity on the protein. After that Drug-likeliness and ADMET studies were performed on the selected molecules. The results revealed that the selected analogues can be used against the treatment of adrenocarcinoma. Keywords: Adrenocarcinoma, bisindole-imidazopyridine, QSAR, Molecular Docking, ADME studies

Potential of Aegilops sp. for Improvement of Grain Processing and Nutritional Quality in Wheat (Triticum aestivum)

Wheat is one of the most important staple crops in the world and good source of calories and nutrition. Its flour and dough have unique physical properties and can be processed to make unique products like bread, cakes, biscuits, pasta, noodles etc., which is not possible from other staple crops. Due to domestication, the genetic variability of the genes coding for different economically important traits in wheat is narrow. This genetic variability can be increased by utilizing its wild relatives. Its closest relative, genus Aegilops can be an important source of new alleles. Aegilops has played a very important role in evolution of tetraploid and hexaploid wheat. It consists of 22 species with C, D, M, N, S, T and U genomes with high allelic diversity relative to wheat. Its utilization for wheat improvement for various abiotic and biotic stresses has been reported by various scientific publications. Here in, for the first time, we review the potential of Aegilops for improvement of processing and nutritional traits in wheat. Among processing quality related gluten proteins; high molecular weight glutenins (HMW GS), being easiest to study have been explored in highest number of accessions or lines i.e., 681 belonging to 13 species and selected ones like Ae. searsii, Ae. geniculata and Ae. longissima have been linked with improved bread making quality of wheat. Gliadins and low molecular weight glutenins (LMW GS) have also been extensively explored for wheat improvement and Ae. umbellulata specific LMW GS have been linked with wheat bread making quality improvement. Aegilops has been explored for seed texture diversity and proteins like puroindolins (Pin) and grain softness proteins (GSP). For nutrition quality improvement, it has been screened for essential micronutrients like Fe, Zn, phytochemicals like carotenoids and dietary fibers like arabinoxylan and β-glucan. Ae. kotschyi and Ae. biuncialis transfer in wheat have been associated with higher Fe, Zn content. In this article we have tried to compile information available on exploration of nutritional and processing quality related traits in Aegilops section and their utilization for wheat improvement by different approaches

Structural Health Monitoring of Existing Reinforced Cement Concrete Buildings and Bridge Using Nondestructive Evaluation with Repair Methodology

Sustainable development means the utilization of resources at a rate less than the rate at which they are renewing. In India infrastructure industry is growing rapidly due to globalization and raising awareness. In the present study, challenges faced by countries like India are to sustain the existing expectations with limited resources available. Reinforced Concrete (RC) structure may suffer several types of defects that may jeopardize their service life. This chapter deals with condition assessment and repair of RCC (G+3) building situated at Northern part of the country. There are various techniques available for repair and rehabilitation of reinforced concrete structures. From a maintenance point of view, it is essential to take up the strength assessment of an existing structure. So, to find out the reason behind the deterioration of the concrete structures some of the NDT and partially destructive technique are used. The NDT tests conducted during this study are Rebound Hammer, Ultra-sonic Pulse Velocity, Concrete resistivity Meter, Ferro-scanning and Carbonation, etc. This chapter helps to explains, how identified the different parameters of distress building like strength, density, level of corrosion and amount of reinforcement. On basis of these results, apply a repair methodology to revert back the strength parameters of the buildings

Procjena dvadeset nemetričkih karakteristika zubne krune u različitim vrstama malokluzija na uzorku iz Indije, populacija New Delhija

Background: Dental phenotype shows variation in the form of various metric and non-metric traits, primarily due to gene-environment interplay. It gives an insight into the evolutionary trends, ancestry, and food habits. Recently, it has been explored for genetic affinity with several growth anomalies and development of craniofacial skeleton which is also responsible for dental and skeletal malocclusions. Objectives: The current study aims to investigate the non-metric dental crown traits (NDCTs) using Arizona State University Dental Anthropology system (ASUDAS) in different types of malocclusions in Delhi, National Capital Region (NCR) population. Materials and methods: The study design was observational and retrospective. The total sample comprised of 240 pairs of dental casts divided into four equal groups of 60 subjects each (30 male and 30 female), based on malocclusion. The four groups of malocclusions were: Angle’s Class I, Class II division 1, Class II division 2, Class III. The investigator was blinded for patient ID and sex before recording the data. The data for cast were recorded by three observers independently in a modified malocclusion- non-metric dental crown traits (M-NDCT) anthropological variants chart and statistically analyzed for association with different malocclusions and sex. Results: Significant differences were found in the expression of several NDCTs (both in presence and scoring) in different malocclusions. Class I malocclusion showed predominantly winging, shoveling –upper central and lateral incisor, protostylid, hypoconulid absence in lower second molar, and cusp number. Class II malocclusion showed double shoveling, interrupted groove, tuberculum dentale, canine mesial ridge, premolar accessory cusp, Carabelli’s trait, lingual cusp vari-ation, and seventh cusp in the lower left first molar. Class III malocclusion showed the absence of hypocone in upper second molar, deflecting wrinkle, distal trigonid crest, and Y groove in left lower second molar. Besides, sexual dimorphism was seen in shoveling –upper central and lateral incisor, canine mesial ridge, Carabelli’s trait, 3-cusp in upper second molar, and cusp number. Conclusions: Significant association was found between non-metric dental traits and malocclusions (Class I, Class division 1, Class II division 2, and Class III). Significant sex-linked differences were also found. Further studies can be performed at multicenter pan-India level or across ethnicities with a standard robust protocol and a large sample.Uvod: Dentalni fenotip pokazuje varijacije u obliku različitih metričkih i nemetričkih svojstava, uglavnom zbog međudjelovanja gena i okoline. Daje uvid u evolucijske trendove, podrijetlo i prehrambene navike. Nedavno je istražen njegov genetski afinitet s nekoliko anomalija rasta i razvoja kraniofacijalnog kostura koji je također odgovoran za dentalne i skeletne malokluzije. Ciljevi: U ovoj studiji autori istražuju nemetričke značajke zubne krune (NDCTs) korištenjem sustava dentalne antropologije Državnoga sveučilišta u Arizoni (ASUDAS) u različitim vrstama malokluzija u populaciji Delhija (regija glavnoga grada – NCR). Materijali i metode: Dizajn studije bio je promatrački i retrospektivan. Ukupni uzorak činilo je 240 pari gipsanih modela podijeljenih u četiri jednake skupine od po 60 ispitanika (30 muškaraca i 30 žena) na temelju malokluzije. Četiri skupine malokluzija bile su: Angleova klasa I, klasa II / 1, klasa II / 2 i klasa III. Istraživaču su bili nepoznati ID-i pacijenta i spol prije snimanja podataka. Podatke za gipsane modele očitala su tri neovisna promatrača u modificiranoj tablici antropoloških varijanti malokluzije – nemetričke značajke zubne krune (M-NDCT) radi povezanosti s različitim malokluzijama i spolom. Rezultati: Pronađene su znatne razlike u ekspresiji nekoliko NDCT-a (i u prisutnosti i u bodovanju) kod različitih malokluzija. Nepravilna okluzija klase I pokazala je pretežno rotirane gornje središnje sjekutiće, lopataste sjekutiće – gornji središnji i lateralni inciziv, protostilid, odsutnost hipokonulida u donjem drugom kutnjaku i broj kvržica. Klasa II malokluzije pokazala je dvostruki lopatasti sjekutić, isprekidanu brazdu, tuberculum dentale, mezijalni greben očnjaka, dodatnu kvržicu pretkutnjaka, Carabellijevo svojstvo, varijaciju lingvalne kvržice i sedmu kvržicu u donjemu lijevom prvom kutnjaku. Malokluzija klase III pokazala je odsutnost hipokonusa u gornjemu drugom kutnjaku, deflektirajuću boru, distalnu crista trigonida i Y-utor u lijevomu donjem drugom kutnjaku (26,7 %). Uz to, spolni dimorfizam uočen je u lopatastim sjekutićima – gornji središnji i lateralni sjekutić, mezijalni greben očnjaka, Carabellijevo svojstvo, tri kvržice u gornjemu drugom kutnjaku i broj kvržice. Zaključci: Pronađena je značajna povezanost između nemetričkih karakteristika zuba i malokluzija (klasa I, klasa 2/ 1, klasa II /2 i klasa III). Također su pronađene značajne spolno povezane razlike. Buduće studije mogu se provesti na multicentričnoj sveindijskoj razini sa standardnim robusnim protokolom i velikim uzorkom

Air Quality Prediction - A Study Using Neural Network Based Approach

India is the 7th largest country by area and 2nd most populated country in the world. The reports prepared by IQAir revels that India is 3rd most polluted country after Bangladesh and Pakistan, on the basis of fine particulates (PM2.5) concentration for the year 2020. In this article, the quality of air in six Indian cities is predicted using data-driven Artificial Neural Network. The data was taken from the 'Kaggle' online source. For six Indian cities, 6139 data sets for ten contaminants (PM2.5, PM10, NO, NO2, NH3, CO, SO2, O3, C6H6 and C7H8) were chosen. The datasets were collected throughout the last five years, from 2016 to 2020, and were used to develop the predictive model. Two machine learning model are proposing in this study namely Artificial Intelligence (AI) and Gaussian Process Regression (GPR) The R-value of ANN and GPR models are 0.9611 and 0.9843 sequentially. The other performance indices such as RMSE, MAPE, MAE of the GPR model are 21.4079, 7.8945% and 13.5884, respectively. The developed model is quite useful to update citizens about the predicted air quality of the urban spaces and protect them from getting affected by the poor ambient air quality. It can also be used to find the proper abatement strategies as well as operational measures

Super-resolution imaging reveals resistance to mass transfer in functionalized stationary phases

Chemical separations are costly in terms of energy, time, and money. Separation methods are optimized with inefficient trial-and-error approaches that lack insight into the molecular dynamics that lead to the success or failure of a separation and, hence, ways to improve the process. We perform super-resolution imaging of fluorescent analytes in four different commercial liquid chromatography materials. Surprisingly, we observe that chemical functionalization can block over fifty percent of the porous interior of the material, rendering it inaccessible to small molecule analytes. Only in situ imaging unveils the inaccessibility when compared to the industry-accepted ex situ characterization methods. Selectively removing some of the functionalization with solvent restores pore access without significantly altering the single-molecule kinetics that underlie the separation and agree with bulk chromatography measurements. Our molecular results determine that commercial stationary phases, marketed as fully porous, are over-functionalized and provide a new avenue to characterize and direct separation material design from the bottom-up

MX2 gene mRNA expression as potential biomarker for early pregnancy diagnosis in cattle

Early pregnancy diagnosis is vital for economic sustainability of dairy farms and maintaining the reproductive efficiency of the herd. There are many techniques including progesterone assay, pregnancy specific proteins and interferon stimulated genes have been explored for early pregnancy diagnosis but, they are associated with varying level of efficacy. In the present experiment, interferon stimulated gene (Myxovirus resistance gene 2/MX2) expression pattern was used as a potential biomarker for early pregnancy in cattle. The association of MX2 gene expression in relation to progesterone assay was studied to explore its potential use as biomarker of early pregnancy. The plasma progesterone concentration in conceived animals on day 7 (2.26±0.19 ng/ml), 17 (5.42±0.35 ng/ml) and 21(6.38±0.39 ng/ml) was recorded to be significantly higher as compared to respective values in non-conceived animals, i.e. 1.55±0.09 ng/ml, 4.14±0.14 ng/ml and 0.81±0.06 ng/ml. The sudden decrement in plasma progesterone concentration after day 17th discriminates conceived and non-conceived animals. MX2 expression levels were observed to spike in blood due to release of interferon tau (τ) after implantation of embryo. The relative mRNA expression of MX2 gene showed a 9.5 to 28.64-fold higher expression on 17 days post insemination in pregnant animals as compared to non-pregnant animals. Thus, MX2 gene can be used as a reliable biomarker for the early detection of pregnancy

Epidemiology of injuries from fire, heat and hot substances : global, regional and national morbidity and mortality estimates from the Global Burden of Disease 2017 study

Background Past research has shown how fires, heat and hot substances are important causes of health loss globally. Detailed estimates of the morbidity and mortality from these injuries could help drive preventative measures and improved access to care. Methods We used the Global Burden of Disease 2017 framework to produce three main results. First, we produced results on incidence, prevalence, years lived with disability, deaths, years of life lost and disability-adjusted life years from 1990 to 2017 for 195 countries and territories. Second, we analysed these results to measure mortality-to-incidence ratios by location. Third, we reported the measures above in terms of the cause of fire, heat and hot substances and the types of bodily injuries that result. Results Globally, there were 8 991 468 (7 481 218 to 10 740 897) new fire, heat and hot substance injuries in 2017 with 120 632 (101 630 to 129 383) deaths. At the global level, the age-standardised mortality caused by fire, heat and hot substances significantly declined from 1990 to 2017, but regionally there was variability in age-standardised incidence with some regions experiencing an increase (eg, Southern Latin America) and others experiencing a significant decrease (eg, High-income North America). Conclusions The incidence and mortality of injuries that result from fire, heat and hot substances affect every region of the world but are most concentrated in middle and lower income areas. More resources should be invested in measuring these injuries as well as in improving infrastructure, advancing safety measures and ensuring access to care.Peer reviewe