Probable Position Research Articles

Quest for optimal quantum resetting: Protocols for a particle on a chain.

In the classical context, it is well known that, sometimes, if a search does not find its target, it is better to start the process anew. This isknown as resetting. The quantum counterpart of resetting also indicates speeding up the detection process by eliminating the dark states, i.e., situations in which the particle avoids detection. In this work, we introduce the most probable position resetting (MPR) protocol, in which, at a given resetting step, resets are done with certain probabilities to the set of possible peak positions (where the probability of finding the particle is maximum) that could occur because of the previous resets and followed by uninterrupted unitary evolution, irrespective of which path was taken by the particle in previous steps. In a tight-binding lattice model, there exists a twofold degeneracy (left and right) of the positions of maximum probability. The survival probability with optimal restart rate approaches0 (detection probability approaches1) when the particle is reset with equal probability on both sides path independently. This protocol significantly reduces the optimal mean first-detected-passage time (FDT), and itperforms better even if the detector is far apart compared to the usual resetting protocolsin which the particle is brought back to the initial position. We propose a modified protocol, an adaptive two-stage MPR, by making the associated probabilities of going to the right and left a function of steps. In this protocol, we see a further reduction of the optimal mean FDT and improvement in the search process when the detector is far apart.

Heatmap-Based Active Shape Model for Landmark Detection in Lumbar X-ray Images.

Medical staff inspect lumbar X-ray images to diagnose lumbar spine diseases, and the analysis process is currently automated using deep-learning techniques. The detection of landmarks is necessary in the automatic process of localizing the position and identifying the morphological features of the vertebrae. However, detection errors may occur owing to the noise and ambiguity of images, as well as individual variations in the shape of the lumbar vertebrae. This study proposes a method to improve the robustness of landmark detection results. This method assumes that landmarks are detected by a convolutional neural network-based two-step model consisting of Pose-Net and M-Net. The model generates a heatmap response to indicate the probable landmark positions. The proposed method then corrects the landmark positions using the heatmap response and active shape model, which employs statistical information on the landmark distribution. Experiments were conducted using 3600 lumbar X-ray images, and the results showed that the landmark detection error was reduced by the proposed method. The average value of maximum errors decreased by 5.58% after applying the proposed method, which combines the outstanding image analysis capabilities of deep learning with statistical shape constraints on landmark distribution. The proposed method could also be easily integrated with other techniques to increase the robustness of landmark detection results such as CoordConv layers and non-directional part affinity field. This resulted in a further enhancement in the landmark detection performance. These advantages can improve the reliability of automatic systems used to inspect lumbar X-ray images. This will benefit both patients and medical staff by reducing medical expenses and increasing diagnostic efficiency.

Updating the First CHIME/FRB Catalog of Fast Radio Bursts with Baseband Data

In 2021, a catalog of 536 fast radio bursts (FRBs) detected with the Canadian Hydrogen Intensity Mapping Experiment (CHIME) radio telescope was released by the CHIME/FRB Collaboration. This large collection of bursts, observed with a single instrument and uniform selection effects, has advanced our understanding of the FRB population. Here we update the results for 140 of these FRBs for which channelized raw voltage (“baseband”) data are available. With the voltages measured by the telescope’s antennas, it is possible to maximize the telescope sensitivity in any direction within the primary beam, an operation called “beamforming.” This allows us to increase the signal-to-noise ratios of the bursts and to localize them to subarcminute precision. The improved localizations are also used to correct the beam response of the instrument and to measure fluxes and fluences with an ∼10% uncertainty. Additionally, the time resolution is increased by 3 orders of magnitude relative to that in the first CHIME/FRB catalog, and, applying coherent dedispersion, burst morphologies can be studied in detail. Polarization information is also available for the full sample of 140 FRBs, providing an unprecedented data set to study the polarization properties of the population. We release the baseband data beamformed to the most probable position of each FRB. These data are analyzed in detail in a series of accompanying papers.

Determining the breaking points of the trend in long-term changes of air temperature in Barentsburg (Svalbard)

Changes in the average annual surface air temperature (SAT) in Barentsburg (Svalbard) for the period 1899-2022 are considered. The SAT increases at an average rate of 0.34°C/10 years. The warming process is not continuous and consists of two periods of cooling and two periods of warming. Statistical methods have been used to establish the most probable position of the breaking points of the SAT trend: 1917, 1938, and 1968. The recent (“modern”) warming in the region began in the late 1960s, but since 1988, its intensity has doubled.

Probability distribution maps of deposited energy with sub-pixel resolution for Timepix3 detectors

The Medipix3 Collaboration has developed the Timepix3 chip, which can provide information about individual particles interacting with a hybrid pixelated semiconductor detector. The Timepix3 generates a data packet including time and energy information for each pixel receiving a charge above the discriminator threshold. From a set of such packages generated by one particle the total deposited energy and the sub-pixel center of mass (c.m) position of the interaction can be calculated. However, sub-threshold losses will distort both the measured energy and c.m calculation. This work aims to generate probability maps for the most probable initial interaction position and energy for a given detected cluster. The correction maps were calculated for different energies and sub-pixel c.m positions. It is crucial to realistically simulate the front-end response of the Timepix3 detector to be able to match and understand the experimental data and generate accurate probability maps. The correction maps from the simulations using the simulation tool Allpix 2 are applied to experimental data utilizing an Am-241 source to irradiate a Minipix Timepix3, leading to sub-pixel resolution and improved energy resolution for Timepix3 detectors.

Order and Disorder in Mixed (Si, P)–N Networks Sr2SiP2N6:Eu2+ and Sr5Si2P6N16:Eu2+

AbstractIn the field of nitride phosphors, which are crucial for phosphor‐converted light‐emitting diodes, mixed tetrahedral networks hold a significant position. With respect to the wide range of compositions, the largely unexplored (Si, P)–N networks are investigated as potential host structures. In this work, two highly condensed structures, namely Sr2SiP2N6 and Sr5Si2P6N16 are reported to address the challenges that arise from the similarities of the network‐forming cations Si4+ and P5+ in terms of charge, ionic radius, and atomic scattering factor, a multistep workflow is employed to elucidate their structure. Using single‐crystal X‐ray diffraction, energy‐dispersive X‐ray spectroscopy (EDX), atomic‐resolution scanning transmission electron microscopy (STEM)‐EDX maps, and straightforward crystallographic calculations, it is found that Sr2SiP2N6 is the first ordered, and Sr5Si2P6N16 the first disordered, anionic tetrahedral (Si, P)–N network. After doping with Eu2+, Sr2SiP2N6:Eu2+ shows narrow cyan emission (λmax = 506 nm, fwhm = 60 nm/2311 cm−1), while for Sr5Si2P6N16:Eu2+ a broad emission with three maxima at 534, 662, and 745 nm upon irradiation with ultraviolet light is observed. An assignment of Sr sites as probable positions for Eu2+ and their relation to the emission bands of Sr5Si2P6N16:Eu2+ is discussed.

Probabilistic indoor tracking of Bluetooth Low-Energy beacons

We construct a practical and real-time probabilistic framework for fine target tracking. In our scenario, a Bluetooth Low-Energy (BLE) device navigating in the environment publishes BLE packets that are captured by stationary BLE sensors. The aim is to accurately estimate the live position of the BLE device emitting these packets. The framework is built upon a hidden Markov model (HMM), the components of which are determined with a combination of heuristic and data-driven approaches. In the data-driven part, we rely on the fingerprints formed priorly by extracting received signal strength indicators (RSSI) from the packets. These data are then transformed into probabilistic radio-frequency maps that are used for measuring the likelihood between an RSSI data and a position. The heuristic part involves the movement of the tracked object. Having no access to any inertial information of the object, this movement is modeled with Gaussian densities with variable model parameters that are to be determined heuristically. The practicality of the framework comes from the associated small parameter set used to discretize the components of the HMM. By tuning these parameters, such as the grid size of the area, the mask size and the covariance of the Gaussian; a probabilistic filtering becomes tractable for discrete state spaces. The filtering is then performed by the forward algorithm given the instantaneous sequential RSSI measurements. The performance of the system is evaluated by taking the mean squared errors of the most probable positions at each time step to their corresponding ground-truth positions. We report the statistics of the error distributions and see that we achieve promising results. The approach is also finally evaluated by its runtime and memory usage.

Pentagon, Hexagon, or Bridge? Identifying the Location of a Single Vanadium Cation on Buckminsterfullerene Surface.

Buckminsterfullerene C60 has received extensive research interest since its discovery. In addition to its interesting intrinsic properties of exceptional stability and electron-accepting ability, the broad chemical tunability by decoration or substitution on the C60-fullerene surface makes it a fascinating molecule. However, to date, there is uncertainty about the binding location of such decorations on the C60 surface, even for a single adsorbed metal atom. In this work, we report the gas-phase synthesis of the C60V+ complex and its in situ characterization by mass spectrometry and infrared spectroscopy with the help of quantum chemical calculations and molecular dynamics simulations. We identify the most probable binding position of a vanadium cation on C60 above a pentagon center in an η5-fashion, demonstrate a high thermal stability for this complex, and explore the bonding nature between C60 and the vanadium cation, revealing that large orbital and electrostatic interactions lie at the origin of the stability of the η5-C60V+ complex.

Bandgap structure in elastic metamaterials with curvy Bezier beams

This Letter discusses elastic metamaterials incorporating curved beams in their architecture. Through employing Bezier splines, we reveal a wide versatility of geometrical designs of the unit cells and the consequent programmability of bandgap structures. By analyzing more than ten thousand possible specimens altogether, we highlight the similarity between dynamic properties of metamaterials formed by curves with different geometries defined via three variables only that correspond to the coordinates of control points of the Bezier spline. In particular, we establish the importance of such parameter as effective curve length in defining the probable positions of bandgaps. This study shows, in particular, that the bandgap ratio can reach 71% for metamaterials with proposed curved beams—a noticeable contrast with no bandgaps in their counterpart with straight elements. The employment of the deep learning model enables us to effectively predict passband–stopband structure in such metamaterials with satisfactory accuracy, potentially accelerating the design of metamaterials assembled from versatile unit cells.

Comparative analysis for variation of skeletal and dental parameters in bilateral cleft palate in central India population – A Nemoceph study

Introduction: An area of dentistry called orthodontics focuses on repositioning crooked teeth and regulating facial development. Orthodontists and oral surgeons use cephalometric analysis as a planning tool for their patient care. Conventional film-based radiography equipment has been replaced with direct digital devices, which have advantages such as reduced patient radiation exposure, immediate radiographic image generation, the removal of the need for darkrooms, and simple image sharing. The second-most typical craniofacial abnormality that results in birth abnormalities is cleft lip and palate. Such patients frequently do not receive cephalometric testing because of their hypoplastic growth and limited development. Research is needed to help plan a standard treatment regimen, perform orthognathic operations, and use a low-radiation analysis technique. Objectives: To evaluate skeletal and dental parameters for cleft lip and palate using Down analysis, Steiner's analysis, and Tweed's analysis using Nemoceph. Methods: Around 50 cases from cleft lip and palate and non-cleft lip and palate will be selected from the orthodontics department of Sharad Pawar Dental College and Hospital. Steiner's, Down's, and Tweed's analyses will be evaluated using Nemoceph. Further analysis will be conducted using the observational data from the readings. There will be millimetre-based measurements made. Comparative analysis will be done with one-way ANOVA and post hoc statistics and regression analysis will be done for association of demographic variables. Expected outcomes: This study will use the nasion as a stable landmark to evaluate point A in cleft lip and palate patients, making it easier to perform normal cephalometric analysis. This will enable the evaluation of the probable position of point A for performing cephalometric analysis in orthodontics.

Modeling spatial patterns in a moving crowd of people using data-driven approach—A concept of Interplay Floor Field

On the basis of data-driven methodology, especially velocity correlations of pedestrians moving in a crowd, we have proposed a new model of pedestrian dynamics with an easy-adjustable space discretization. The model is based on Cellular Automata (CA) with an adaptive lattice and takes into account proxemics patterns among pedestrians. The proposed model uses agents located on the CA lattice, constructed using the concept of Floor Field (FF), namely, a set of gradient potential fields influencing the movement of agents. In the model, we have proposed three kinds of such fields: Static FF—responsible for navigation to agents’ Points of Interest (POIs), Wall FF—a repulsive influence with obstacles, and Interplay FF—to model agents’ volume and proxemics effects. The third field, which models mutual relations between pedestrians taking into account the rules of proxemics is an added value in the area of crowd modeling and simulation.During the creation of the proposed model, we have based on a set of experimental data provided by Jülich Supercomputing Centre and our previous analysis of spatial patterns and velocity correlations. Thus, the proposed model includes, among other things the most probable positions of the nearest neighbors in a crowd—including the shape of “the forbidden zone” around a pedestrian and the finding of rules explaining observed mutual spatial relations between neighbors in a crowd. In the described model the cell size is an adjustable parameter, with available values from 1 cm to 50 cm. It is possible with the usage of embodied agents which always occupy only one cell of Cellular Automata, actual pedestrian volume is modeled with the Interplay FF. An interesting property of the model is that changing the cell size does not involve changing the rules of the model, e.g. its transition function.

Building protein structure-specific rotamer libraries.

Identifying the probable positions of the protein side-chains is one of the protein modelling steps that can improve the prediction of protein-ligand and protein-protein interactions. Most of the strategies predicting the side-chain conformations use predetermined dihedral angle lists, also called rotamer libraries, that are usually generated from a subset of high-quality protein structures. Although these methods are fast to apply, they tend to average out geometries instead of taking into account the surrounding atoms and molecules and ignore structures not included in the selected subset. Such simplifications can result in inaccuracies when predicting possible side-chain atom positions. We propose an approach that takes into account both of these circumstances by scanning through sterically accessible side-chain conformations and generating dihedral angle libraries specific to the target proteins. The method avoids the drawbacks of lacking conformations due to unusual or rare protein structures and successfully suggests potential rotamers with average RMSD closer to the experimentally determined side-chain atom positions than other widely used rotamer libraries. The technique is implemented in open-source software package rotag and available at GitHub: https://www.github.com/agrybauskas/rotag, under GNU Lesser General Public License.

Attracting Cavities 2.0: Improving the Flexibility and Robustness for Small-Molecule Docking.

Molecular docking is a computational approach for predicting the most probable position of a ligand in the binding site of a target macromolecule. Our docking algorithm Attracting Cavities (AC) has been shown to compare favorably to other widely used docking algorithms [Zoete, V.; et al. J. Comput. Chem. 2016, 37, 437]. Here we describe several improvements of AC, making the sampling more robust and providing more flexibility for either fast or high-accuracy docking. We benchmark the performance of AC 2.0 using the 285 complexes of the PDBbind Core set, version 2016. For redocking from randomized ligand conformations, AC 2.0 reaches a success rate of 73.3%, compared to 63.9% for GOLD and 58.0% for AutoDock Vina. Due to its force-field-based scoring function and its thorough sampling procedure, AC 2.0 also performs well for blind docking on the entire receptor surface. The accuracy of its scoring function allows for the detection of problematic experimental structures in the benchmark set. For cross-docking, the AC 2.0 success rate is about 30% lower than for redocking (42.5%), similar to GOLD (42.8%) and better than AutoDock Vina (33.1%), and it can be improved by an informed choice of flexible protein residues. For selected targets with a high success rate in cross-docking, AC 2.0 also achieves good enrichment factors in virtual screening.

Financial Statement Analysis of Apple Inc.

The motive behind choosing APPLE INC. is the curiosity to find out what do they do uniquely to have such a huge brand value and popularity across the globe. The brand value created by them is unmatchable in their competitive domain and they continue to keep up to the expectations their customers have on them. The research was carried out by first collecting data about the financial statements of Apple Inc. from their official website and then calculating different relevant ratios and metrics for final analysis. The results obtained were carefully analysed and the financial position or the probable position of the company was depicted at appropriate places. At the end of the research, we will be able to have an overview of Apple’s performance during the choose year as well have say on its future performance as well as about the path ahead of the company.

Huffman Encoding with White Tailed Eagle Algorithm-based Image Steganography Technique

Since the Internet is a medium for transporting sensitive data, the privacy of the message transported has become a major concern. Image steganography has become a prominent tool for hiding data to ensure privacy during transfer. An efficient steganography system is essential to accomplish the best embedding capacity and maintain the other parameters at a satisfying level. Image encryption systems provide a secure and flexible system to maintain the privacy of image conversion and storage in the transmission system. Many existing image steganography methods can be attacked by various techniques, or do not support many image formats for embedding. To resolve these shortcomings, this study presents the Huffman Encoding with White Tailed Eagle Algorithm-based Image Steganography (HEWTEA-IS) technique, aiming to achieve secrecy with no compromise in image quality. The HEWTEA-IS method uses Discrete Wavelet Transform (DWT) for the decomposition of images into different subbands, and Huffman encoding to determine the embedding bits on the decomposed blocks and offer an additional layer of security. Moreover, the WTEA resolves the problem of imperceptibility by identifying the optimal probable position in the cover image for embedding secret bits. The proposed algorithm was simulated and examined in terms of different measures, and an extensive experimental analysis ensured that it is superior to other methods in several aspects.

Innovative sensorless dual-axis solar tracking system using particle filter

Renewable energy (RE), particularly solar photovoltaic (PV) systems, is a promising alternative to traditional energy sources for worldwide electricity generation. In recent years, PV generation capacity has increased rapidly due to a considerable reduction in installation costs. Nevertheless, in PV systems, energy generation is significantly less than the installed capacity due to the PV modules’ orientation. Hence, this study proposes an innovative solar tracking system to enhance PV energy generation. Previous research classified solar tracking systems into two categories: sensor-based and sensorless solar tracking systems. However, tracking performance inevitably deteriorates when implementing sensor-based solar tracking systems in low-visibility conditions. Conversely, sensorless solar tracking systems require substantial historical meteorological data based on geographic location and complex mathematical models estimating the sun’s position, increasing computational complexity. This study aims to overcome these difficulties by proposing a sensorless dual-axis solar tracking system that does not require historical meteorological data, complex mathematical models, and sun position sensors to track the sun’s position. Particle filter (PF), a robust sampling-based tracking algorithm, is applied to develop an innovative solar tracking strategy. Initially, a set of samples (also called particles) is generated as inputs to PF corresponding to the proposed tracking system’s orientation angles: daily and elevation angles. Next, PV power is captured as a measurement of each particle, and a weight associated with the PV power is estimated to represent each particle’s relative significance. Furthermore, each particle is estimated and updated recursively, considering its measurement to determine the sun’s probable position. The tracking strategy is terminated once the particles’ weights are equal, indicating that the optimal position has been achieved (convergence). A comparative study is conducted over 60 days under various weather conditions to evaluate the proposed tracking system’s performance compared with that of a fixed flat-plate system. The experimental results indicate that the proposed tracking system improves energy generation performance (after accounting for operational energy consumption) by 20.1% compared with the fixed flat-plate system.

A Quest for Better Strategy in Pediatric Intraosseous Placement Using Radiographic Measurements in Patients Younger Than 2 Years.

Intraosseous (IO) needles are used to obtain vascular access in pediatric patients during emergent situations. Recent literature has raised concern about high rates of IO malposition in younger children. Despite the widespread use of IO access in the pediatric population, there is scarce evidence regarding the ideal needle length or optimal access site. This study uses a radiographic approach to determine the appropriate IO needle length and access site to minimize the risk of malposition in children younger than 2 years. Radiographs of the lower extremities were obtained from the electronic database from a single tertiary care center. Using lateral views, anteroposterior measurements were obtained at 2 axial planes, located 1 cm superior to distal femur physis and 1 cm inferior to distal tibia physis. Based on the measurements, we calculated the probable needle tip positions if the needle was placed to the hub at the skin level using the EZ-IO (Teleflex Ltd, Wayne, PA) preset needle sizes. For subjects younger than 6 months, the 25-mm needle minimized malposition in the femur site with a 45.7% appropriate position rate, and the 15-mm needle minimized malposition in the tibia site with a 57.1% appropriate position rate. For the older age groups, we did not find a standard needle that would consistently minimize malposition in the femur site. For the tibia site, the 25-mm needle minimized malposition risk, with appropriate position rates of 81.0%, 87.5%, and 91.1% in the 6- to 12-month, 13- to 18-month, and 19- to 24-month groups, respectively.

Alizarin as a potential protector of proteins against damage caused by hydroperoxyl radical

Alizarin is a natural anthraquinone molecule with moderate antioxidative capacity. Some earlier investigations indicated that it can inhibit osteosarcoma and breast carcinoma cell proliferation by inhibiting of phosphorylation process of ERK protein (extracellular signal-regulated kinases). Several mechanisms of deactivation of one of the most reactive oxygen species, hydroperoxyl radical, by alizarin are estimated: hydrogen atom abstraction (HAA), radical adduct formation (RAF), and single electron transfer (SET). The plausibility of those mechanisms is estimated using density functional theory. The obtained results indicated HAA as the only thermodynamically plausible mechanism. For that purpose, two possible mechanistic pathways for hydrogen atom abstraction are studied in detail: hydrogen atom transfer (HAT) and proton-coupled electron transfer (PCET). Water and benzene are used as models of solvents with opposite polarity. To examine the difference between HAT and PCET is used kinetical approach based on the Transition state theory (TST) and determined rate constants (k). Important data used for a distinction between HAT and PCET mechanisms are obtained by applying the Quantum Theory of Atoms in Molecules (QTAIM), and by the analysis of single occupied molecular orbitals (SOMOs) in transition states for two examined mechanisms. The molecular docking analysis and molecular dynamic are used to predict the most probable positions of binding of alizarin to the sequence of ApoB-100 protein, a protein component of plasma low-density lipoproteins (LDL). It is found that alizarin links the nitrated polypeptide forming the π-π interactions with the amino acids Phenylalanine and Nitrotyrosine. The ability of alizarin to scavenge hydroperoxyl radical when it is in a sandwich structure between the polypeptide and radical species, as the operative reaction mechanism, is not significantly changed concerning its antioxidant capacity in the absence of polypeptide. Therefore, alizarin can protect the polypeptide from harmful hydroperoxyl radical attack, positioning itself between the polypeptide chain and the reactive oxygen species.

A comparative DFT study on Al- and Si- doped single-wall carbon nanotubes (SWCNTs) for Ribavirin drug sensing and detection

In this work, we have presented a comparative study on Ribavirin (RBV) drug sensing and detection on the pristine and functionalized single-wall carbon nanotubes (f-SWCNTs) by Density Functional Theory (DFT) method. The pristine and metal-doped zigzag (4,0) and (6,0) SWCNTs were first considered for the RBV adsorption. All the probable positions of RBV adsorption were investigated to find which one is energetically favourable. The topology analysis of the Quantum theory of atoms in a molecule (QTAIM) with non-covalent interactions (NCI-RDG), Frontier molecular orbitals (FMO), Density of states (DOS), and non-linear optical (NLO) analysis were carried out to understand the molecular structure, electrical, electronic and optical properties of complexes. The charge analysis indicates that charge transfer is from the adsorbed RBV to the pristine and metal-doped (4,0) and (6,0) SWCNTs. The highest values of adsorption energies for Al-, Si-doped and pristine (4,0) SWCNTs were determined as −34.688, −87.999 and −10.382 kcal/mol, respectively, whereas corresponding values for metal-doped and pristine (6,0) SWCNTs are about −43.592, −20.661 and −12.414 kcal/mol, respectively. The results suggest that those bare and metal-doped (4,0) SWCNTs and (6,0) Si-SWCNTs can serve as promising sensors in practical applications to detect, recognize and carrier RBV drug for its medicinal drug delivery applications. Based on the NLO properties of (6,0) Si-SWCNTs and pristine (6,0) SWCNT (with an acceptable recovery time of 279s and first hyper polarizability value of β = 229.25 × 10−30 cm5 esu−1), those nanotubes may be possible candidates to be used as the optoelectronic sensor for RBV drug. The appropriate short length of nanotubes was obtained.

Shortcomings of shear wall design as per IS:13920–2016

Reinforced concrete shear walls are almost routinely used in multi-storeyed buildings due to their increased strength, stiffness, and ductility considerations. Shear walls are typically stiffer than regular frame elements. Hence, are subjected to more lateral forces during response to earthquakes. Reinforced concrete walls subjected to compression along with flexure are similar to columns and hence need similar methodology. For a section subjected to compression and flexure, two equilibrium conditions namely force and moment equilibrium equations needs to be solved for any specific load combination. This being a cumbersome and complex proposition, design charts, similar to columns should be used for shear wall design. However, IS 13920:2016 provides closed form expressions for estimation of moment capacity of rectangular RC walls without boundary elements combining these two equilibrium equations by using certain assumption and simplifications which are not conforming to the fundamental philosophies of limit state method as per IS 456–2000. These closed form expressions have several limitations and constraints and the equations are not valid for all the probable positions of neutral axis. In the present work the shortcomings of the codal methodology of shear wall design have been highlighted and method of development of proper design aids for shear wall design have been outlined.