Present-day Techniques Research Articles

Base-metal exploration by using remote sensing, geological, geophysical, and geochemical datasets with clues from ancient mining: A comprehensive review on Aravalli-Delhi Fold Belt, Rajasthan, India

Base metal deposits are present in different continents with evidences of their mining activities during ancient times as mentioned in the historical literature. Aravalli – Delhi Fold Belt (ADFB) in Rajasthan, India is having numerous base metal prospects where ancient mining signages are recorded. Modern-day mining has commenced taking clues from these evidences. Present-day techniques such as remote sensing, geological mapping, geophysical survey, geochemical survey, and exploration/drilling are utilized for the identification of surficial ancient mining features and identification of the mineralized zones. These techniques utilize their unique criteria to get an idea of the mineral association. The integration of all the unique characteristics of modern techniques with the help of weighted overlay analysis, fuzzy logic, multi-criteria overlay analysis, etc. helps to identify the mineral potential zones from the ancient working sites. Their integrated results provide the surficial as well as sub-surficial information of the region that gives a better revelation about the region and helps in decision-making towards the mineralization status of the region. World-over surficial ancient features have been recorded in exploratory sites for base metals, and the case histories where integrated techniques were used for mineral exploration are discussed. Zawar – Dungarpur belt also has the potential for base metals therefore, the boolean approach, weighted overlay, and multi-criteria overlay analysis were performed using remote sensing, structural, and geochemical datasets. The integrated results showed that the head zone and southern broader part near Keekawat have the potential for base metals.

Comparative Analysis of ML Algorithms and Neural Networks to Classify Student Based on Academic Performance

Abstract: In recent years, there has been an interesting surge in interest in both educational data and deep learning. This research proposes a Neural Network (NN) architecture that visually represents the class category to students. This gives information to the school so they can help the pupils who might otherwise fail. A comparative analysis between the suggested model and present-day techniques of machine learning that utilizes the identical dataset. Compared to existing machine learning algorithms, the accuracy of the suggested neural network model is higher.

A systematic study on complementary metal-oxide semiconductor technology (CMOS) and Internet of Things (IOT) for radioactive leakage detection in nuclear plant

Although nuclear power plants produce about 20% of India's power, the risk posed by radioactive leakage is considerable. Radiation leakage detection devices must be installed in all nuclear power plants to ensure that avoidable catastrophes never occur again and that the loss of human life is prevented. A safe atmosphere for inhabitants and workers may be ensured by keeping a consistent radiation level in all applications that use radioactive material. Complementary Metal-Oxide Semiconductor technology, or CMOS, uses complementary and symmetrical MOSFETS for logic-based functions in various applications, such as analog circuits (CMOS sensors). The Internet of Things (IoT) extends the power of the Internet beyond computing devices to a multitude of other things, processes, and environments. The main objective of this paper is to find a better and more creative solution for radioactive leakage detection techniques over present-day techniques. In this paper, the Authors aim to integrate CMOS and IOT applications for radioactive leakage detection methods on an industrial level. Within this paper, we have given brief descriptions of CMOS and IoT with their types, functions, methodology, and applications. CMOS is considered to be the most sophisticated and precise technology that can be employed to measure radiation leaks of all types (alpha rays, beta rays, gamma rays, and neutrons). With the help of IOT, massive disasters can be averted using complex alert systems. A well-coordinated combination of the two technologies has the potential to vastly increase leak detection potential and consistency. The study's major goal is to develop new and improved technology for detecting released radiation in the industry in order to obtain real-time information about the material leaked, as well as the location of the leak and the quantity of leakage that occurred, in order to reduce the danger of a natural catastrophe.

Growth Optimizer for Parameter Identification of Solar Photovoltaic Cells and Modules

One of the most significant barriers to broadening the use of solar energy is low conversion efficiency, which necessitates the development of novel techniques to enhance solar energy conversion equipment design. The correct modeling and estimation of solar cell parameters are critical for the control, design, and simulation of PV panels to achieve optimal performance. Conventional optimization approaches have several limitations when solving this complicated issue, including a proclivity to become caught in some local optima. In this study, a Growth Optimization (GO) algorithm is developed and simulated from humans’ learning and reflection capacities in social growing activities. It is based on mimicking two stages. First, learning is a procedure through which people mature by absorbing information from others. Second, reflection is examining one’s weaknesses and altering one’s learning techniques to aid in one’s improvement. It is developed for estimating PV parameters for two different solar PV modules, RTC France and Kyocera KC200GT PV modules, based on manufacturing technology and solar cell modeling. Three present-day techniques are contrasted to GO’s performance which is the energy valley optimizer (EVO), Five Phases Algorithm (FPA), and Hazelnut tree search (HTS) algorithm. The simulation results enhance the electrical properties of PV systems due to the implemented GO technique. Additionally, the developed GO technique can determine unexplained PV parameters by considering diverse operating settings of varying temperatures and irradiances. For the RTC France PV module, GO achieves improvements of 19.51%, 1.6%, and 0.74% compared to the EVO, FPA, and HTS considering the PVSD and 51.92%, 4.06%, and 8.33% considering the PVDD, respectively. For the Kyocera KC200GT PV module, the proposed GO achieves improvements of 94.71%, 12.36%, and 58.02% considering the PVSD and 96.97%, 5.66%, and 61.20% considering the PVDD, respectively.

Advances in microanalysis: Magnifying the social microscope on mother-infant interactions

Microanalysis is a method for recording and coding interactional behavior. It has been often compared to a social microscope, for its power in detailing the second-by-second dynamics of social interaction. Microanalysis has deep multidisciplinary foundations, that privilege the description of interactions as they naturally occur, with the purpose of understanding the relations between multiple and simultaneous streams of behaviors. In developmental science, microanalysis has uncovered structural and temporal elements in mother-infant interactions, improving our understanding of the effects of mother-infant interpersonal adaptation in the infant’s cognitive and social-emotional development.Detailed manual coding is time intensive and resource demanding, imposing restrictions to sample size, and the ability to analyze multiple behavioral modalities. Moreover, recent increases in the density of multivariate data require different tools. We review present-day techniques that tackle those challenges: (1) sensing techniques for motion tracking and physiological recording; (2) exploratory techniques for detecting patterns from high-density data; and (3) inferential and modeling techniques for understanding contingencies between interactional time series.Two illustrations, from recent developmental research, reveal the power of bringing new lenses to our social microscope: (1) egocentric vision, the use of head mounted cameras and eye-trackers in capturing the infant’s first-person perspective of a social exchange; and (2) daily activity sensing, wearable multimodal sensing that brought mother-infant interaction research to the environments where it naturally unfolds.

Efficient fractional-order modified Harris hawks optimizer for proton exchange membrane fuel cell modeling

An effective harmony between the exploration and exploitation phases in meta-heuristics is an essential design consideration to provide reliable performance on a wide range of optimization problems. This paper proposes a novel approach to enhance the exploratory behavior of the Harris hawks optimizer (HHO) based on the fractional calculus (FOC) memory concept. In the proposed variant of the HHO, a hawk moves with a fractional-order velocity, and the rabbit escaping energy is adaptively tuned based on FOC parameters to avoid premature convergence. As a result, the fractional-order modified Harris hawks optimizer (FMHHO) is proposed. The sensitivity of the algorithm performance vis-a-vis the FOC parameters is addressed, and the best variant is recommended based on twenty-three benchmarks. For validating the quality of the proposed variant, twenty-eight benchmarks of CEC2017 are tested. For evaluating the proposed variant against the other present-day techniques, several statistical measures and non-parametric tests are performed. Moreover, to demonstrate the applicability of the proposed technique, the proton exchange membrane fuel cell (PEMFC) model parameters estimation process is handled based on several measured datasets. In this series of experiments, the FMHHO variant is compared with the standard HHO and the other techniques based on intensive statistical metrics, mean convergence curves, and dataset fitting. The overall outcome shows that the FOC memory property improves the performance of the classical HHO and leads to accurate and robust solutions fitting the measured data.

Opening-up Crépin’s Rose Herbarium by New Technologies: a Pilot Project

The collections of Meise Botanic Garden comprise extensive and varied documentation on the genus Rosa. The library collection contains valuable and often rare 19th century publications about the genus Rosa, frequently with annotations by François Crépin. In addition to this, the archives hold the unpublished manuscripts and thousands of letters from Crépin’s correspondents reflecting the extraordinary scientific network he built up to facilitate the exchange of herbarium collections together with erudite discussions on the taxonomy of the genus Rosa. Crépin exchanged letters with all the important rhodologists of his time, such as E. Burnat, H. Christ, P.A. Déséglise, P.E. Parmentier, H. Takashima, and W. Wirtgen, and also with horticulturists, such as J. Gravereaux. This unique network and diversified patrimony of historical collections took shape over a period of several decades during which Crépin prepared a monograph of the genus Rosa that unfortunately was never finished. Crépin assembled a 19th century herbarium with ca. 40 000 specimens of the genus Rosa. In contrast to other important herbaria, the Crépin collection covers the whole natural area of distribution of Rosa and documents an unparalleled range of Rose taxa. The combination of documentary sources of several different types makes the collections of Meise Botanic Garden extremely valuable. They offer great opportunities for multidisciplinary studies by taxonomists and historians with the aim of solving the still insufficiently understood relations between taxa in the genus Rosa. Linking this unique heritage of Meise Botanic Garden with present-day molecular techniques promises rewarding research in the near future. We can conclude that the collections related to Roses are major masterpieces of the Garden. In 2016 the Piaget Foundation, the World Federation of Rose Societies and ‘De Vrienden van de Roos’, supported the Botanic Garden with a grant which allowed us to image 13 000 out of the 40 000 herbarium sheets. The public is invited to help us generate the label data on the Garden’s crowdsourcing platform (https://www.doedat.be/). In this project we tested also the quality of extracted DNA of 96 specimens of the Crépin Herbarium. 69% of the samples yielded with the Nanodrop technology good quality and quantity of DNA and for 29% of the samples it was even possible to amplify the rDNA gene marker ITS (with 650bp). These results are encouraging and illustrate that this historic herbarium could be a useful tool for research on roses.

From Disks to Planets: The Making of Planets and Their Early Atmospheres. An Introduction

From Disks to Planets: The Making of Planets and Their Early Atmospheres. An Introduction

Spin-asymmetric Josephson plasma oscillations

The spin-asymmetric Josephson effect is a proposed quantum-coherent tunnelling phenomenon where Cooper-paired fermionic spin-$\frac{1}{2}$ particles, which are subjected to spin-dependent potentials across a Josephson junction, undergo frequency-synchronized alternating-current Josephson oscillations with spin-dependent amplitudes. Here, in line with present-day techniques in ultracold Fermi gas setups, we consider the regime of small Josephson oscillations and show that the Josephson plasma oscillation amplitude becomes spin-dependent in the presence of spin-dependent potentials while the Josephson plasma frequency is the same for both spin-components. Detecting these spin-dependent Josephson plasma oscillations provides a possible means to establish the yet-unobserved spin-asymmetric Josephson effect with ultracold Fermi gases using existing experimental tools.

In Situ Single-Molecule RNA Genotyping Using Padlock Probes and Rolling Circle Amplification.

Present-day techniques allow for massively parallel and high-throughput characterization of the somatic mutation status of samples. Most of these assays rely on whole specimen extracts, where heterogeneous spatial context of the specimen is lost. This chapter describes an up-to-date protocol for multiplexed, in situ genotyping of RNA in preserved tissue and cell lines, using padlock probes and rolling circle amplification. The presented approach allows for automated quantification of mRNA expression and mutation status, in single cells or in designated specimen areas. Briefly, mRNA is first reverse-transcribed to cDNA. Padlock probes specifically hybridize to the cDNA copy of the allele and become circularized and thereby physically linked to their targets. Following this conversion, padlock probes are copied in situ by rolling circle amplification and labeled with flourophore-conjugated probes, allowing for their detection with conventional fluorescence microscopy.

PHOTOGRAMMETRY-BASED AUTOMATED MEASUREMENTS FOR TOOTH SHAPE AND OCCLUSION ANALYSIS

Abstract. Tooth measurements (odontometry) are performed for various scientific and practical applications, including dentistry. Present-day techniques are being increasingly based on 3D model use that provides wider prospects in comparison to measurements on real objects: teeth or their plaster copies. The main advantages emerge through application of new measurement methods which provide the needed degree of non-invasiveness, precision, convenience and details. Tooth measurements have been always regarded as a time-consuming research, even more so with use of new methods due to their wider opportunities. This is where automation becomes essential for further development and implication of measurement techniques. In our research automation in obtaining 3D models and automation of measurements provided essential data that was analysed to suggest recommendations for tooth preparation – one of the most responsible clinical procedures in prosthetic dentistry – within a comparatively short period of time. The original photogrammetric 3D reconstruction system allows to generate 3D models of dental arches, reproduce their closure, or occlusion, and to perform a set of standard measurement in automated mode.

PHOTOGRAMMETRY-BASED AUTOMATED MEASUREMENTS FOR TOOTH SHAPE AND OCCLUSION ANALYSIS

Tooth measurements (odontometry) are performed for various scientific and practical applications, including dentistry. Present-day techniques are being increasingly based on 3D model use that provides wider prospects in comparison to measurements on real objects: teeth or their plaster copies. The main advantages emerge through application of new measurement methods which provide the needed degree of non-invasiveness, precision, convenience and details. Tooth measurements have been always regarded as a time-consuming research, even more so with use of new methods due to their wider opportunities. This is where automation becomes essential for further development and implication of measurement techniques. In our research automation in obtaining 3D models and automation of measurements provided essential data that was analysed to suggest recommendations for tooth preparation – one of the most responsible clinical procedures in prosthetic dentistry – within a comparatively short period of time. The original photogrammetric 3D reconstruction system allows to generate 3D models of dental arches, reproduce their closure, or occlusion, and to perform a set of standard measurement in automated mode.

PROTEOMIC ANALYSIS OF URINE UNDER CONTROLLED SALT INTAKE IN PROJECT .

Specifics of urine proteome is sensitive to a multitude of factors. One is nutrition or entrance in organism of main nutrients including salt (NaCI). Purpose of the investigation was to study the proteomic composition of healthy human urine in the controlled environment of a 105-day isolation experiment (project <<Mars-500>>) with various levels of salt intake. Analysis was performed using the present-day proteomics techniques based on chromatography-mass spectrometry and bio-informatics options. An attempt was made to correlate changes in processes and physiological systems with the controlled salt intake. As a result, a list of proteins directly responsible for different salt intake during the experiment and then a list of tissues where these proteins express predominantly were compiled; besides, analysis of the processes these proteins are involved in was performed.

Development of a technology for continuous acoustic emission monitoring of in-service damageability of metal in safety-related NPP equipment

Safe operation of the NPP main equipment whose design life has expired requires the development of new approaches to integrity diagnosis and monitoring due to high level of metal ageing.These approaches should be based on nondestructive testing methods which make it possible to inspect equipment not only during the period of repair, but also in conditions of operation when dangerous defects are initiating and growing. One of highly efficient present-day techniques for nondestructive testing suitable for use in the process of operation is acoustic emission method. The paper presents the results of the activities to develop a multi-parameter system for acoustic emission monitoring of the nuclear plant equipment damageability in the process of the unit operation with specific features of the NPP control taken into account. The stages of the activities are described with all factors of impacts on the developed system assessed and taken into account, namely the need for keeping the system serviceable during long-term operation in high-temperature conditions, a complicated geometry of the monitored item, and an increased level of noise, as well as the acquisition and transmission of monitoring data via intranet systems for being processed and displayed online. A series of system tuning experiments conducted in laboratory conditions to refine and validate the selected monitoring techniques are described.

A novel technique for obtaining representative water samples during CO&lt;sub&gt;2&lt;/sub&gt; core-flooding experiments on chalk at reservoir conditions

There is a huge potential for using CO2 gas to recover additional oil after water flooding in reservoir chalk. However, the injection of CO2 into chalk reservoirs will disturb the chemical equilibrium between formation water, injection water and chalk. A proper understanding of these CO2-induced interactions and the resulting changes in the physical properties at representative reservoir conditions is required. Unfortunately, reliable chemical data are rare because data cannot be acquired directly at reservoir conditions with present-day techniques. In published experiments, water samples are in many cases obtained at atmospheric conditions with the aid of a back-pressure regulator. Thus, water samples are not representative of in situ reservoir conditions and if proper care is not taken, the collected data cannot be used to judge the magnitude of the chemical reactions taking place at reservoir conditions. However, in some cases water obtained at laboratory conditions can give information on in situ reservoir conditions by using geochemical speciation models to account for dissolved gases that are lost from the effluents during sampling (Bachu &amp; Adams 2003).

Dual-plane ultrasound flow measurements in liquid metals

An ultrasound measurement system for dual-plane, two-component flow velocity measurements especially in opaque liquids is presented. Present-day techniques for measuring local flow structures in opaque liquids disclose considerable drawbacks concerning line-wise measurement of single ultrasound probes. For studying time-varying flow patterns, conventional ultrasound techniques are either limited by time-consuming mechanical traversing or by the sequential operation of single probes. The measurement system presented within this paper employs four transducer arrays with a total of 100 single elements which allows for flow mapping without mechanical traversing. A high frame rate of several 10 Hz has been achieved due to an efficient parallelization scheme using time-division multiplexing realized by a microcontroller-based electronic switching matrix. The functionality and capability of the measurement system are demonstrated on a liquid metal flow at room temperature inside a cube driven by a rotating magnetic field (RMF). For the first time, the primary and the secondary flow have been studied in detail and simultaneously using a configuration with two crossed measurement planes. The experimental data confirm predictions made by numeric simulation. After a sudden switching on of the RMF, inertial oscillations of the secondary flow were observed by means of a time-resolved measurement with a frame rate of 3.4 Hz. The experiments demonstrate that the presented measurement system is able to investigate complex and transient flow structures in opaque liquids. Due to its ability to study the temporal evolution of local flow structures, the measurement system could provide considerable progress for fluid dynamics research, in particular for applications in the food industry or liquid metal technologies.

Aggregation of Kanamycin A: dimer formation with physiological cations

Global cluster geometry optimization has focused so far on clusters of atoms or of compact molecules. We are demonstrating here that present-day techniques also allow to globally optimize clusters of extended, flexible molecules, and that such studies have immediate relevance to experiment. For example, recent experimental findings point to production of larger clusters of an aminoglycoside closely related to Kanamycin A (KA), together with certain preferred physiological cations, by Pseudomonas aeruginosa. The present study provides first theoretical support for KA clustering, with a close examination of the monomer, the bare dimer, and dimers with sodium and potassium cations, employing global cluster structure optimization, in conjunction with force fields, semiempirical methods, DFT and ab-initio approaches. Interestingly, already at this stage the theoretical findings support the experimental observation that sodium cations are preferred over potassium cations in KA clusters, due to fundamentally different cationic embedding. Theoretically predicted NMR and IR spectra for these species indicate that it should be possible to experimentally detect the aggregation state and even the cationic embedding mode in such clusters.

Fast estimation of common-reflection-surface parameters using local slopes

Present-day techniques to estimate the traveltime parameters of the common-reflection-surface (CRS) stack are tedious, time-consuming, and expensive processes based on local coherence analyses along a large number of trial surfaces. With the 2D CRS method, faster and cheaper determination is possible. The complete set of CRS parameters can be extracted from seismic data by an application of modern local-slope-extraction techniques. The necessary information about the CRS parameters is contained in the slopes of the common-midpoint section at the central point and one or several common-offset sections in its vicinity. We studied two procedures for the CRS parameter extraction technique. Their difference lies in the way the common-offset parameters are determined. One technique requires slope-derivative information (a possible source of instability); the other uses slope information at two different locations and less data redundancy. Testing on a synthetic data example proved that the procedures are sufficiently robust to allow for high-quality extraction of all CRS parameters from the extracted slope fields. In this way, the CRS parameter extraction can be sped up by several orders of magnitude as compared to the conventional procedure based on coherence analysis along trial surfaces.

Automated monitoring system for drive motors of gas-compressor units

The present-day techniques for design and development of the embedded systems for monitoring and prediction of a technical condition of MW electrically driven units are examined with a case study at synchronous machines at gas-compressor stations. The statistical analysis of damageability and operational factors of aging of the insulation at stator windings of gas-compressor unit motors is cited. The example of an automated monitoring system for the STD-12 500 synchronous motor, based on innovative electric equipment and an automated process control system (APCS), is shown.

An efficient deterministic secure quantum communication scheme based on cluster states and identity authentication

A novel efficient deterministic secure quantum communication scheme based on four-qubit cluster states and single-photon identity authentication is proposed. In this scheme, the two authenticated users can transmit two bits of classical information per cluster state, and its efficiency of the quantum communication is 1/3, which is approximately 1.67 times that of the previous protocol presented by Wang et al [Chin. Phys. Lett. 23 (2006) 2658]. Security analysis shows the present scheme is secure against intercept-resend attack and the impersonator's attack. Furthermore, it is more economic with present-day techniques and easily processed by a one-way quantum computer.