Composting

Decomposition followed by stabilization of organic substances by biological actions has been taking place in nature from the very beginning of life appeared on our planet. Anthropogenic control and utilization of the process for sanitary disposal and reclamation of organic waste material have been termed composting and the final product is named compost. Microbial community leads the processes of both aerobic and anaerobic composting and converts wastes to a stable form of nutrients. The C/N ratio is the most important factor for decomposition, especially aerobic decomposition. Microorganisms respire two-third of carbon as CO2, and one-third combines with nitrogen in living cell, and huge amount of heat energy is released as end product of aerobic decomposition as compared to anaerobic process. In agricultural world, utilization of human and animal wastes has great importance. Extensive studies on composting were initiated in India. Different composting methods like pit method, heap method, ADCO method, vermicomposting, etc. presently exist in the world. Humus is the end product of composting, and different organic wastes contain macro, micro, and trace elements, which reflect valuable properties for growing vegetation and to the soil itself

Network architecture for prediction of emergence in complex biological systems

Emergence of properties at the system level, where these properties are not observed at the individual entity level, is an important feature of complex systems. Biological system emergent properties have critical roles in the functioning of organisms and the disruptions to normal functioning, and are relevant to the treatment of diseases like cancer. Complex biological systems can be modeled by abstractions in the form of molecular networks like gene regulatory networks (GRNs) and signaling networks with nodes representing molecules like genes and edges representing molecular interactions. The thesis aims at exploring the use of the architecture of these networks to predict emergence of system properties. First, to better infer the network architecture with aspects that can be useful in predicting emergence, we propose a novel algorithm Polynomial Lasso Bagging or PoLoBag for signed GRN inference from gene expression data. The GRN edge signs represent the nature of the regulatory relationships, activating or inhibitory. Our algorithm gives more accurate signed inference compared to state-of-the-art algorithms, and overcomes their weaknesses by also inferring edge directions and cycles. We also show how combining signed GRN architecture with dynamical information in our proposed dynamical K-core method predicts emergent states of the gene regulatory system effectively. Second, we investigate the existence of the bow-tie architectural organization in the GRNs of species of widely varying complexity. Prior work has shown the existence of this bow-tie feature in the GRNs of only some eukaryotes. Our investigation covers GRNs of prokaryotes to unicellular and multicellular eukaryotes. We find that the observed bow-tie architecture is a characteristic feature of GRNs. Based on differences that we observe in the bow-tie architectures across species, we predict a trend in the emergence of the dynamical gene regulatory system property of controllability with varying species complexity. Third, from input genotype data we predict an emergent phenotype at the organism level -- the cancer-specific survival risk. We propose a novel Mutated Pathway Visible Neural Network or MPVNN, designed using prior knowledge of signaling network architecture and additional mutation data-based edge randomization. This randomization models how known signaling network architecture changes for a particular cancer type, which is not modeled by state-of-the-art visible neural networks. We suggest that MPVNN performs cancer-specific risk prediction better than other similar sized NN and non-NN survival analysis methods, while also providing reliable interpretations of the predictions. These three research contributions taken together make significant advances towards our goal of using molecular network architecture for better prediction of emergence, which can inform treatment decisions and lead to novel therapeutic approaches and is of value to computational biologists and clinicians

Functional outcome of patients presenting with isolated medial condyle fractures of femur in a tertiary care hospital

Isolated medial condyle fractures of the femur with an intact lateral condyle are a rare entity. These fractures require prompt diagnosis and anatomical restoration of joint surface to prevent post traumatic arthritis. Till date no suitable implant is available for fixation of these fractures. In this study we have used 4.5 recon plates and CC screws to fix these fractures. We aim to study the functional outcome of these fractures in a group of patients fixed with the above implants. The study was conducted in a group of patients presenting with isolated medial condyle fractures of femur in a tertiary care hospital. An ORIF was done and fractures were fixed with recon plates and lag screws and various parameters were evaluated such as range of motion of knee, average time to weight bearing, Lysholm knee scores, pain perception etc 20 patients were evaluated in the age group of 20-70 in a 5 year period. Majority of the patients had a very good functional range of motion of the knee and nearly 75% achieved union by 12-16 weeks. 70% of the patients had a low VAS score. Overall early diagnosis and prompt anatomical restoration of joint surface in isolated medial condyle fractures of femur led to favourable range of motion of knee, early radiological healing and low VAS score

Bow-tie architecture of gene regulatory networks in species of varying complexity

The gene regulatory network (GRN) architecture plays a key role in explaining the biological differences between species. We aim to understand species differences in terms of some universally present dynamical properties of their gene regulatory systems. A network architectural feature associated with controlling system-level dynamical properties is the bow-tie, identified by a strongly connected subnetwork, the core layer, between two sets of nodes, the in and the out layers. Though a bow-tie architecture has been observed in many networks, its existence has not been extensively investigated in GRNs of species of widely varying biological complexity. We analyse publicly available GRNs of several well-studied species from prokaryotes to unicellular eukaryotes to multicellular organisms. In their GRNs, we find the existence of a bow-tie architecture with a distinct largest strongly connected core layer. We show that the bow-tie architecture is a characteristic feature of GRNs. We observe an increasing trend in the relative core size with species complexity. Using studied relationships of the core size with dynamical properties like robustness and fragility, flexibility, criticality, controllability and evolvability, we hypothesize how these regulatory system properties have emerged differently with biological complexity, based on the observed differences of the GRN bow-tie architectures

Fast loading of a cold mixture of Sodium and Potassium atoms from compact and versatile cold atomic beam sources

We present the design, implementation and detailed experimental characterization of two-dimensional Magneto-optical traps (MOT) of bosonic $^{23}$Na and $^{39}$K atoms for loading the cold atomic mixture in a dual-species 3DMOT with a large number of atoms. We report our various measurements pertaining to the characterisation of the two 2D$^+$MOTs via the capture rate in the 3DMOT and also present the optimised parameters for the best performance of the system of the cold atomic mixture. In the optimised condition, we capture more than $3 \times 10^{10}$ $^{39}$K atoms and $5.8 \times 10^8$ $^{23}$Na atoms in the 3DMOT simultaneously from the individual 2D$^+$MOTs with the capture rate of $5 \times 10^{10}$ atoms/sec and $3.5 \times 10^8$ atoms/sec for $^{39}$K and $^{23}$Na, respectively. We also demonstrate improvements of more than a factor of 5 in the capture rate into the 3DMOT from the cold atomic sources when a relatively high-power ultra-violet light is used to cause light-induced atomic desorption (LIAD) in the 2D$^+$MOT glass cells. The cold atomic mixture would be useful for further experiments on Quantum simulation with ultra-cold quantum mixtures in optical potentials

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe

Measurement of prompt open-charm production cross sections in proton-proton collisions at root s=13 TeV

The production cross sections for prompt open-charm mesons in proton-proton collisions at a center-of-mass energy of 13TeV are reported. The measurement is performed using a data sample collected by the CMS experiment corresponding to an integrated luminosity of 29 nb(-1). The differential production cross sections of the D*(+/-), D-+/-, and D-0 ((D) over bar (0)) mesons are presented in ranges of transverse momentum and pseudorapidity 4 < p(T) < 100 GeV and vertical bar eta vertical bar < 2.1, respectively. The results are compared to several theoretical calculations and to previous measurements.Peer reviewe

Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| &lt; 0.03 at 95% confidence level. [Figure not available: see fulltext.

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

Peer reviewe