Fractal dimension analysis of stock prices of selected resulting companies after mergers and acquisitions.

This study focuses on the short-run wealth of listed firms' shareholders. Currently, all of the resulting organizations offer competitive pricing tactics to create a superior environment for our ongoing establishment. Some time ago, it was noted that a merger occurred, although some functions and technology integration remained with the previous structure. In this paper, it has been discovered that merger and acquisition deals have an impact on the firm's value; in other words, we can view it as shareholders' wealth or unit depending on the stock price after the announcement of merger and acquisition deals in the short term. Furthermore, we focused on influencing variables on stock prices after the announcement of merger and acquisition transactions, which is measured as a percentage change in the stock prices of the listed resulting firms. Furthermore, this research is based on secondary data sources from reputable organizations. It primarily uses the NSE database and website to evaluate announcements and stock prices of the twenty-nine publicly traded companies. Markets respond to investors' emotions and market expertise. When acquirers have a strong market position, market capitalization rises in other segments. However, it is declining due to a lack of supportive finances. To determine the impact of merger and acquisition announcement deals on stock price changes, average abnormal return and cumulative average abnormal return with the capital asset pricing model (CAPM) (CAPM reaction to changes) were used to identify the acquiring company's stock price reaction. We investigated its impact on the fluctuation of share prices posted on stock exchanges using fractal interpolation functions. This is due to greater investment by acquirer businesses in target companies as well as investor expectations for specific stock market strongholds.

Analogue and structure based approaches for modelling HIV-1 integrase inhibitors.

A set of 220 inhibitors belonging to different structure classes and having HIV-1 integrase activity were collected along with their experimental pIC50 values. Geometries of all the inhibitors were fully optimized using B3LYP/6-31 + G(d) level of theory. These ligands were docked against 4 different HIV-1 integrase receptors (PDB IDs: 4LH5, 5KRS, 3ZSQ and 3ZSV). 30 docked poses were generated for all 220 inhibitors and ligand interaction of the first docked pose and the docked pose with the highest score were analysed. Residue GLU170 of 4LH5 receptor shows the highest number of interactions followed by ALA169, GLN168, HIS171 and ASP167 residues. Hydrogen bonding and stacking are mainly responsible for the interactions of these inhibitors with the receptor. We performed Molecular Dynamics (MD) simulation to observe the root-mean-square deviation (RMSD), for measure the average change of displacement between the atoms for a particular frame with respect to a reference and The Root Mean Square Fluctuation (RMSF) for characterization of local changes along the protein chain of the docked complexes. Analogue based models were generated to predict the pIC50 values for integrase inhibitors using various types of descriptors such as constitutional, geometrical, topological, quantum chemical and docking based descriptors. The best models were selected on the basis of statistical parameters and were validated by training and test set division. A few new inhibitors were designed on the basis of structure activity relationship and their pIC50 values were predicted using the generated models. All the designed new inhibitors a very high potential and may be used as potent inhibitors of HIV integrase. These models may be useful for further design and development of new and potent HIV integrase inhibitors.Communicated by Ramaswamy H. Sarma.

A systematic survey of RUM process parameter optimization and their influence on part characteristics of nickel 718.

This research is focused on the drilling of Nickel based super alloy with diamond metal core drill and identified the significant parameters of rotary ultrasonic machining that optimise the machining rate (MR) and surface quality. Four general parameters: workpiece material, workpiece thickness, tool material, and tool size; and four RUM parameters: tool rotational, feed rate, ultrasonic power rating, and abrasive grit size of the tool were tested against and surface quality of the cut. The results indicated that the maximum value of MR of 0.8931mm3/sec is acquired at higher level of tool rotation, feed rate, ultrasonic power and moderate level of abrasive grit size of diamond. The minimum surface roughness (Ra) 0.554 µm is observed at higher level of rotational rotation, Moderate value of feed rate, ultrasonic power and diamond abrasive grit size. In addition, for single-objective and multi-objective functions, the particle swarm optimization (PSO) approach is used to find the optimum values for process parameters. Furthermore, a scanning electron microscope is also utilized to check the machined surface after RUM. It is concluded that microcracks are observed on the machined surface.

Performability evaluation, validation and optimization for the steam generation system of a coal-fired thermal power plant.

The present paper talks over performability evaluation for a steam generation system of a Coal Fired Thermal Power Plant (CFTPP) using the concept of the Markov method. A steam generation system provides a suitable amount of steam for the sound functioning of the plant. The system comprises five subsystems, i.e., High-Pressure Heater, Economizer, Boiler Drum, Water Tubes, and Super Heater.  First, the transition diagram of the concerned system is designed based on the state probabilities of various subsystems. The differential equations are derived based on the mnemonic rule. After that, the performability model is developed by using the normalizing condition. The performability levels for various subsystems are obtained by placing the appropriate value of failure and repair rates in the developed model. The performability of each subsystem is evaluated based on performability matrices. It is observed that the economizer subsystem is most critical in which the availability increased from 0.7640 to 0.8827, i.e. (11.87 %). In contrast, boiler drum is the least crucial subsystem with availability enhanced from 0.8627 to 0.8657 (i.e., 0.3 %). The results show that the economizer subsystem must be given top priority, and the boiler drum be given the least priority from the maintenance outlook. The performability levels obtained through the Markov method are compared with those obtained through the Artificial Neural Network to validate. Moreover, machine learning (artificial neural network) and optimization technique (particle swarm optimization) is also employed to check the adequacy of the results and optimized process parameters.•The aim of the present study is evaluate the performance of steam generation system of a coal fired thermal power plant.•The probabilistic approach (i.e. Makov Method) is used to formulate the transition diagram of the steam generation system. Then, the first-order differential equations are obtained using the mnemonic rule and further solved recursively.•The results show that the economizer system must be given top priority, and the boiler drum subsystem must be given the least priority from the maintenance outlook.

Mechanical conflict caused by a cell-wall-loosening enzyme activates de novo shoot regeneration.

Cellular heterogeneity is a hallmark of multicellular organisms. During shoot regeneration from undifferentiated callus, only a select few cells, called progenitors, develop into shoot. How these cells are selected and what governs their subsequent progression to a patterned organ system is unknown. Using Arabidopsis thaliana, we show that it is not just the abundance of stem cell regulators but rather the localization pattern of polarity proteins that predicts the progenitor's fate. A shoot-promoting factor, CUC2, activated the expression of the cell-wall-loosening enzyme, XTH9, solely in a shell of cells surrounding the progenitor, causing different mechanical stresses in these cells. This mechanical conflict then activates cell polarity in progenitors to promote meristem formation. Interestingly, genetic or physical perturbations to cells surrounding the progenitor impaired the progenitor and vice versa. These suggest a feedback loop between progenitors and their neighbors for shoot regeneration in the absence of tissue-patterning cues.

Genome Editing and Designer Crops for the Future.

Domestication spanning over thousands of years led to the evolution of crops that are being cultivated in recent times. Later, selective breeding methods were practiced by human to produce improved cultivars/germplasm. Classical breeding was further transformed into molecular- and genomics-assisted breeding strategies, however, these approaches are labor-intensive and time-consuming. The advent of omics technologies has facilitated the identification of genes and genetic determinants that regulate particular traits allowing the direct manipulation of target genes and genomic regions to achieve desirable phenotype. Recently, genome editing technologies such as meganucleases (MN), zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and CRISPR (clustered regularly interspaced short palindromic repeats)/CRISPR-Associated protein 9 (Cas9) have gained popularity for precise editing of genes to develop crop varieties with superior agronomic, physiological, climate-resilient, and nutritional traits. Owing to the efficiency and precision, genome editing approaches have been widely used to design the crops that can survive the challenges posed by changing climate, and also cater the food and nutritional requirements for ever-growing population. Here, we briefly review different genome editing technologies deployed for crop improvement, and the fundamental differences between GE technology and transgene-based approach. We also summarize the recent advances in genome editing and how this radical expansion can complement the previously established technologies along with breeding for creating designer crops.

Identification of suitable reference genes for expression profiling studies using qRT-PCR in an important insect pest, Maruca vitrata.

BACKGROUND: Maruca vitrata is one of the potential insect pests that cause devastating losses to legume cultivation worldwide. Gene functional studies facilitate dissecting the molecular mechanisms underlying the infection process and enable devising appropriate molecular strategies to control this insect pest. Expression profiling using quantitative real-time PCR (qRT-PCR) provides insights into the functional characterization of target genes; however, ideal reference genes should be deployed in such studies to nullify the background variation and improve the accuracy of target gene expression. An ideal reference gene should have a stable expression across developmental stages, biological conditions, tissues, or experimental conditions. METHODS AND RESULTS: Given this, the stability of eight candidate reference genes was evaluated in M. vitrata at different developmental stages, diets, and sexes by qRT-PCR method, and the data was analyzed using four independent algorithms, namely GeNorm, NormFinder, BestKeeper, and ΔCt, and one comprehensive algorithm, RefFinder. CONCLUSION: The analysis showed that RP49 and RPL13 were the best suitable reference genes for studying target gene expression at different developmental stages. Further, the study identified RP49 and RPL24, and GAPDH and RPL24 as the ideal reference genes in M. vitrata fed with different diets and sexes, respectively. The reference genes reported in the present study will ensure the accuracy of target gene expression, and thus, will serve as an important resource for gene functional studies in M. vitrata.

Hormonal crosstalk in regulating salinity stress tolerance in graminaceous crops.

Soil salinity is one of the major threats that pose challenges to global cereal productivity and food security. Cereals have evolved sophisticated mechanisms to circumvent stress at morpho-physiological, biochemical, and molecular levels. Salt stress cues are perceived by the roots, which trigger the underlying signaling pathways that involve phytohormones. Each phytohormone triggers a specific signaling pathway integrated in a complex manner to produce antagonistic, synergistic, and additive responses. Phytohormones induce salt-responsive signaling pathways to modulate various physiological and anatomical mechanisms, including cell wall repair, apoplastic pH regulation, ion homeostasis, root hair formation, chlorophyll content, and leaf morphology. Exogenous applications of phytohormones moderate the adverse effects of salinity and improve growth. Understanding the complex hormonal crosstalk in cereals under salt stress will advance the knowledge about cooperation or antagonistic mechanisms among hormones and their role in developing salt-tolerant cereals to enhance the productivity of saline agricultural land. In this context, the present review focuses on the mechanisms of hormonal crosstalk that mediate the salt stress response and adaptation in graminaceous crops.

Performance evaluation of friction stir welding using machine learning approaches.

The aim of the present study is to evaluate the potential of sophisticated machine learning methodologies, i.e. Gaussian process (GPR) regression, support vector machining (SVM), and multi-linear regression (MLR) for ultimate tensile strength (UTS) of friction stir welded joint. Three regression models are developed on the above methodologies. These models are projected to study the incongruity between the experimental and predicted outcomes and preferred the preeminent model according to their evaluation parameter performances. Out of 25 readings, 19 readings are selected for training models whereas remaining is used for testing models. Input process parameters consist of rotational speed (rpm), and feed rate (mm/min) whereas UTS is considered as output. Two kernel functions i.e. Pearson VII (PUK) and radial based kernel function (RBF) are used with both GPR and SVM regression. It is concluded that the GPR approach works better than SVM and MLR techniques. Therefore, GPR approach is used successfully for predicting the UTS of FS welded joint.

Oxidation of Cr(III) in tannery sludge to Cr(VI): field observations and theoretical assessment.

Sludge, soil and leachate samples collected from a chromium-contaminated tannery waste dumping site in Kanpur, India, were found to contain considerable amounts of Cr(VI), despite the fresh tannery sludge containing little or no Cr(VI). Literature reports suggested that dry Cr(III) precipitates could be converted to Cr(VI) when heated in the presence of oxygen. Also, Cr(III) in aqueous phase could be oxidized through interaction with manganese dioxide (MnO2) surface to Cr(VI). Measurement of manganese in the sludge samples collected from the site showed concentrations up to 0.6 mg/g. Based on equilibrium calculations, it was determined that both dry phase Cr(III) oxidation by atmospheric oxygen and aqueous phase Cr(III) oxidation by MnO2 surface were thermodynamically feasible. It was further suggested that in aqueous phase, manganese may act effectively as an electron transporter between Cr(III) and dissolved oxygen during Cr(III) oxidation, leading to regeneration of MnO2 solid phase. Further, as dissolved Cr(III) is oxidized, dissolution of Cr(OH3) will take place to maintain the equilibrium between the dissolved and solid phases of Cr(III). In the pH range of 3-10, and at oxygen partial pressure (P(O2)) of 10(-6) atm or higher, equilibrium conditions stipulate nearly complete conversion of Cr(III) to Cr(VI). At P(O2) of 10(-20) atm or lower, very little Cr(VI) is expected to be present under equilibrium conditions. In the intermediate P(O2) regions, incomplete dissolution of the Cr(OH3) solid phase and only partial conversion of chromium from +3 to the +6 oxidation state is expected, especially at lower pH values.