General Public Research Articles

SHORYUKEN: An open-source software package for calculating nonlocal exchange interactions in nanowires

We present the open-source software package, SHORYUKEN (Streamlined High-level Operations in Real-space to Yield, Understand, and Keep Exchange in Nanowires), for calculating nonlocal exchange interactions in nanowires with arbitrary geometries, sizes, doping densities, and compositions. In addition to enabling new calculations of nonlocal exchange, the SHORYUKEN software package is a significant enhancement of our previous HADOKEN code and includes new algorithmic improvements as well as an improved treatment of surface states for nanowires with intrinsic polarization. Our calculations show that the inclusion of nonlocal exchange can have significant effects on the eigenenergy spectrum, number of occupied states, and distribution of electrons within these nanosystems. The SHORYUKEN software package is the first open-source code for calculating nonlocal exchange to predict electron gas formation in nanowire systems with arbitrary cross-sectional geometries. Program summaryProgram Title: SHORYUKENCPC Library link to program files:https://doi.org/10.17632/f77p84pbcv.1Licensing provisions: GNU General Public License 3Programming language: MATLABNature of problem: The SHORYUKEN code calculates nonlocal exchange interactions of electrons in nanowires by solving modified nonlocal exchange and Poisson-like equations self-consistently on a finite element grid. The software package is capable of performing calculations for core-multishell nanowires with arbitrary cross-sectional shapes.Solution method: iterative solution of the Schrödinger-Poisson equations with nonlocal exchange using finite element methods and sparse matrix linear algebra

Supplemental Material for Is the Goal Intrinsic or Extrinsic? Examining Self-Determination Theory Researchers’ and the General Publics’ Perceptions of Exercise Goals

Supplemental Material for Is the Goal Intrinsic or Extrinsic? Examining Self-Determination Theory Researchers’ and the General Publics’ Perceptions of Exercise Goals

Attitudes of the Portuguese population towards advance directives: an online survey

BackgroundAdvance directives (ADs) were implemented in Portugal in 2012. Although more than a decade has passed since Law 25/2012 came into force, Portuguese people have very low levels of adherence. In this context, this study aimed to identify and analyse the attitudes of people aged 18 or older living in Portugal towards ADs and to determine the relationships between sociodemographic variables (gender/marital status/religion/level of education/residence/whether they were a health professional/whether they had already drawn up a living will) and people’s attitudes towards ADs.MethodsAn online cross-sectional analytical study was conducted using a convenience sample. For this purpose, a request (email) that publicized the link to a –form—which included sociodemographic data and the General Public Attitudes Toward Advance Care Directives (GPATACD) scale—was sent to 28 higher education institutions and 30 senior universities, covering all of mainland Portugal and the islands (Azores and Madeira). The data were collected between January and February 2023.ResultsA total of 950 adults from completed the online form. The lower scores (mean 1 and 2) obtained in most responses by applying the GPATACD scale show that the sample of the Portuguese population has a very positive attitude towards ADs. The data showed that women, agnostics/atheists, health professionals and those who had already made a living will had more positive attitudes (p < 0.001) towards ADs. There were no statistically significant differences in the attitudes of the Portuguese population sample towards ADs in relation to marital status, education level, and residence.ConclusionThe results obtained enable us to confirm that this sample of the Portuguese population has a positive attitude towards ADs. We verify that there are certain fringes of this sample with certain sociodemographic characteristics (women, agnostics/atheists, health professionals and those who had already made a living will) that have a more positive attitude towards ADs. This data could facilitate the implementation and adjustment of relevant measures, particularly in the field of health education and aimed at groups with less favourable attitudes, to increase the effectiveness of voluntary exercise of citizens’ autonomy in end-of-life care planning.

IJCM_157A: Knowledge, attitude and disposal practices of unused and expired medicines among general public in Kundrathur primary health centre area of Madras Medical College.

Background: Unfortunately, not all medications that go in to the hand of the consumers get consumed; large quantities remain unused or expire which is a public safety issue, leading to potential accidental poisoning, misuse, and overdose. Although the National Formulary of India, specifies guidelines for the proper disposal of medicines, yet most of the people are not aware of these guidelines and the importance to follow them. Even though there are many studies exploring the fate of unused and expired drugs, most of them are conducted in healthcare setups like hospitals. There is a need to explore the awareness of disposal practices among General Public. Objective: 1) To assess the knowledge, attitude and disposal practices of unused and expired medicines. 2) To assess perception regarding measures to be taken to improve awareness for disposal practices of unused and expired medicines. Methodology: Community based Cross-sectional study conducted among 230 participants in Kundrathur Primary Health Centre area. Systematic random sampling method was used to select individual household. Data collected through face-face interview using Prevalidated structured questionnaire, entered in Epicollect5 and analyzed in SPSS software. Results: A total of 232individuals participated in the study, of which 180(78%) were female,182(80%) were literate, and the participant’s mean age was 42.7±17. It was observed that 43%,91% and 13%of the participants exhibited good knowledge, a positive attitude, and good practice. The majority of individuals (78% &amp; 89%) preferred to dispose of unused and expired medicines in the household trash. Most participants said that mass media, including radio, television, and newspapers, might raise awareness. Conclusion: This study shows that public awareness and behaviour about the proper disposal of unused and expired drugs need to be improved. The implementation of drug take-back initiatives will enable people to securely return any unused or expired medicines.

An Overview of the Effect of Rising Traffic and Congestion in Bangalore on the Lives of General Public

Abstract: Bangalore, India's Silicon Valley, is experiencing widespread traffic congestion, which has a significant impact on the urban environment of the city. This study looks at the complex effects of traffic congestion on public health, social well-being, economic productivity, and air quality in Bangalore's metropolitan environment. By conducting a thorough examination of extant literature and statistics, the research clarifies the adverse consequences of traffic congestion, including elevated levels of air pollution, an increase in traffic accidents, extended travel times, and reduced productivity. The research also looks at possible mitigating measures, such as bettering the infrastructure for public transit, enacting congestion pricing plans, encouraging the use of alternate forms of transportation, and implementing clever urban design techniques. Policymakers can create successful measures to address traffic congestion by having a thorough understanding of the intricate relationship between the two.

SMATool: Strength of materials analysis toolkit

The study of the strength of materials is a cornerstone in material science and engineering, playing a critical role in shaping the progress and application of materials in diverse industrial sectors. The strength of a material is meticulously examined to understand the behavior of the material under different stress conditions and environments, thereby guiding material selection and structural design. Herein, we introduce the SMATool, a computational toolkit for the efficient calculation and analysis of material strength at both zero and finite temperatures for 3D, 2D, 1D, and tubular 2D-based nanostructures and nanotubes, as well as 1D nanoribbons. The toolkit is capable of calculating tensile, shear, ultimate, yield, and indentation (Vickers' hardness) strengths in various dimensions, as well as the energy storage capacity. We conducted several calculations both at zero and finite temperatures to validate the accuracy and reliability of the developed software. The results show that the SMATool package provides accurate predictions that align with existing data on material strength. SMATool integrates seamlessly with widely used electronic structure codes like VASP and Quantum Espresso, providing a user-friendly interface catering to academic researchers and industry professionals. SMATool is useful for either the exploration of the strength of materials or high-throughput new material design. SMATool is open-source and available on GitHub at SMATool@github and at Zenodo at 10.5281/zenodo.10780514. Program summaryProgram Title: SMAToolCPC Library link to program files:https://doi.org/10.17632/fnkzfsg7t7.1Licensing provisions: GNU General Public License, version 3Programming language: Python 3Nature of problem: Developing a comprehensive framework to accurately determine the strength of materials is crucial in various engineering and scientific disciplines. This involves developing a robust and efficient computational toolkit to predict the strength of a material under different loading conditions, including tension, compression, shear, and indentation.Solution method:SMATool effectively addresses the challenge of accurately simulating the mechanical properties of materials by leveraging advances in ab initio methods, including density functional theory and molecular dynamics within the atomic simulation environment. The SMATool toolkit can efficiently compute various material strengths, such as tensile, shear, ultimate, yield, and indentation (Vickers' hardness) strengths as well as the corresponding energy storage capacity of the material. It is adept at handling a variety of material dimensions, ranging from 1D nanotubes and nanoribbons to 2D and 3D structures, at both zero and finite temperatures. SMATool currently integrates VASP and Quantum Espresso as the stress calculator and is easily adaptable to use other electronic structure codes.Additional comments including restrictions and unusual features:SMATool offers serial and parallel execution. Depending on the system size, the nature of the calculations (zero or finite temperature), and the computing architecture, the computing time can vary from ∼5 minutes to as high as 18 hours.

MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory

Abstract. The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and each reaction is described as a set of edges. MEXPLORER is a community tool published under the GNU General Public License.

A custom detector construction pattern for Geant4 applications

Geant4 Detector Construction Pattern (G4DCP) is a template developed to flexibly construct complex detectors in Geant4 applications. The elements of G4DCP, including G4VUserDetectorConstruction, form an elegant template for detector setups. We construct a sample detector geometry utilizing this template and make the developed code available to the public. Program summaryProgram title: G4DCPCPC Library link to program files:https://doi.org/10.17632/s77f2khsrb.1Developer's repository link:https://github.com/mkandemirr/G4DCP.gitLicensing provisions: GNU General Public License 3Programming language: C++External routines/libraries: Geant4, CMakeNature of problem: Geant4 provides an abstract class, G4VUserDetectorConstruction, for the whole detector construction. Although this makes sense from the run manager's (G4RunManager) standpoint, implementing a single class to create a sophisticated detector results in complicated code and is not a good practice for keeping the code clean and tidy. Therefore, many Geant4 educators recommend splitting the implementation into additional methods or classes. However, no standard solution has been published, and it is left entirely to the users' skills.Solution method: To solve this problem, we propose to use two more abstract class templates in addition to the G4VUserDetectorConstruction class during the detector construction stage. As these two classes have functional similarities to G4VUserDetectorConstruction, they do not cause any complexity for users. On the contrary, they assist users in producing cleaner and reusable code (or modular code).

DiffGR: Detecting Differentially Interacting Genomic Regions from Hi-C Contact Maps

Abstract Recent advances in high-throughput chromosome conformation capture (Hi-C) techniques have allowed us to map genome-wide chromatin interactions and uncover higher-order chromatin structures, thereby shedding light on the principles of genome architecture and functions. However, statistical methods for detecting changes in large-scale chromatin organization such as topologically associating domains (TADs) are still lacking. We proposed a new statistical method, DiffGR, for detecting differentially interacting genomic regions at the TAD level between Hi-C contact maps. We utilized the stratum-adjusted correlation coefficient to measure similarity of local TAD regions. We then developed a nonparametric approach to identify statistically significant changes of genomic interacting regions. Through simulation studies, we demonstrated that DiffGR can robustly and effectively discover differential genomic regions under various conditions. Furthermore, we successfully revealed cell type-specific changes in genomic interacting regions in both human and mouse Hi-C datasets, and illustrated that DiffGR yielded consistent and advantageous results compared with state-of-the-art differential TAD detection methods. The DiffGR R package is published under the GNU General Public License (GPL) ≥ 2 license and is publicly available at https://github.com/wmalab/DiffGR.

Assessing Regional Weather's Impact on Spinal Cord Injury Survivors, Caregivers, and General Public in Miami, Florida.

(1) Background: Climate change is increasing the already frequent diverse extreme weather events (EWE) across geographic locations, directly and indirectly impacting human health. However, current ongoing research fails to address the magnitude of these indirect impacts, including healthcare access. Vulnerable populations such as persons with spinal cord injury (pSCI) face added physiologic burden such as thermoregulation or mobility challenges like closure of public transportation. Our exploratory research assessed commute and transport to healthcare facilities as well as the knowledge, attitudes and behaviors (KAB) of pSCI regarding EWE and climate change when compared to pSCI caregivers (CG) and the general public (GP). (2) Methods: A KAB survey was employed to conduct a cross-sectional assessment of pSCI, CG, and GP in Miami from October through November 2019 using snowball sampling. Descriptive and logistic regression statistical analyses were used. (3) Results: Of 65 eligible survey respondents, 27 (41.5%) were pSCI, 11 (17%) CG, and 27 (41.5%) GP. Overall, pSCI reported EWE, particularly flooding and heavy rain, affecting their daily activities including healthcare appointments, more frequently than CG or GP. The overall models for logistic regression looking at commute to and attendance of healthcare appointments were statistically significant. pSCI self-report being less vulnerable than others, and a large proportion of each group was not fully convinced climate change is happening. (4) Conclusions: This study provided insight to the KAB of 3 population subgroups in Miami, Florida. pSCI are significantly more vulnerable to the effects of regional weather events yet exhibit disproportionate self-perception of their vulnerability. Continued and more comprehensive research is needed to characterize the barriers that vulnerable populations face during weather events.

Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis.

Computer-aided drug design (CADD) is a drug design technique for computing ligand‒receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics. A systematic review of studies published between 2000 and July 20, 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analysed using software such as Excel, VOSviewer, RStudio, and CiteSpace. A total of 2,031 publications were included. These publications primarily originated from 99 countries or regions, led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications. Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modelling, pharmacophore modelling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics direction for future development. Furthermore, this paper will be helpful for better understanding the frontiers and hotspots of CADD.

PHARE: a bioinformatics pipeline for compositional profiling of multiclonal Plasmodium falciparum infections from long-read Nanopore sequencing data.

The emergence of drug-resistant clones of Plasmodium falciparum is a major public health concern, and the ability to detect and track the spread of these clones is crucial for effective malaria control and treatment. However, in endemic settings, malaria infected people often carry multiple P. falciparum clones simultaneously making it likely to miss drug-resistant clones using traditional molecular typing methods. Our goal was to develop a bioinformatics pipeline for compositional profiling in multiclonal P. falciparum samples, sequenced using the Oxford Nanopore Technologies MinION platform. We developed the 'Finding P. falciparum haplotypes with resistance mutations in polyclonal infections' (PHARE) pipeline using existing bioinformatics tools and custom scripts written in python. PHARE was validated on three control datasets containing P. falciparum DNA of four laboratory strains at varying mixing ratios. Additionally, the pipeline was tested on clinical samples from children admitted to a paediatric hospital in the Central African Republic. The PHARE pipeline achieved high recall and accuracy rates in all control datasets. The pipeline can be used on any gene and was tested with amplicons of the P. falciparum drug resistance marker genes pfdhps, pfdhfr and pfK13. The PHARE pipeline helps to provide a more complete picture of drug resistance in the circulating P. falciparum population and can help to guide treatment recommendations. PHARE is freely available under the GNU Lesser General Public License v.3.0 on GitHub: https://github.com/Fippu/PHARE.

Comparing the Perspectives of Generative AI, Mental Health Experts, and the General Public on Schizophrenia Recovery: Case Vignette Study.

The current paradigm in mental health care focuses on clinical recovery and symptom remission. This model's efficacy is influenced by therapist trust in patient recovery potential and the depth of the therapeutic relationship. Schizophrenia is a chronic illness with severe symptoms where the possibility of recovery is a matter of debate. As artificial intelligence (AI) becomes integrated into the health care field, it is important to examine its ability to assess recovery potential in major psychiatric disorders such as schizophrenia. This study aimed to evaluate the ability of large language models (LLMs) in comparison to mental health professionals to assess the prognosis of schizophrenia with and without professional treatment and the long-term positive and negative outcomes. Vignettes were inputted into LLMs interfaces and assessed 10 times by 4 AI platforms: ChatGPT-3.5, ChatGPT-4, Google Bard, and Claude. A total of 80 evaluations were collected and benchmarked against existing norms to analyze what mental health professionals (general practitioners, psychiatrists, clinical psychologists, and mental health nurses) and the general public think about schizophrenia prognosis with and without professional treatment and the positive and negative long-term outcomes of schizophrenia interventions. For the prognosis of schizophrenia with professional treatment, ChatGPT-3.5 was notably pessimistic, whereas ChatGPT-4, Claude, and Bard aligned with professional views but differed from the general public. All LLMs believed untreated schizophrenia would remain static or worsen without professional treatment. For long-term outcomes, ChatGPT-4 and Claude predicted more negative outcomes than Bard and ChatGPT-3.5. For positive outcomes, ChatGPT-3.5 and Claude were more pessimistic than Bard and ChatGPT-4. The finding that 3 out of the 4 LLMs aligned closely with the predictions of mental health professionals when considering the "with treatment" condition is a demonstration of the potential of this technology in providing professional clinical prognosis. The pessimistic assessment of ChatGPT-3.5 is a disturbing finding since it may reduce the motivation of patients to start or persist with treatment for schizophrenia. Overall, although LLMs hold promise in augmenting health care, their application necessitates rigorous validation and a harmonious blend with human expertise.

Responsiveness of inpatient care and provision of dignity: Insights from a patient experience survey in Israel

The paper contributes to the literature on the responsiveness of care, patient dignity, and disparities in the provision of health services. It does so by evaluating indicators of patient responsiveness while focusing on aspects of dignified treatment. The data were taken from the Patient Experience Survey of General Public Hospitals conducted by the Israel Ministry of Health in 2018. The analysis focuses on two indicators of responsiveness (i.e., actual) and three indicators of patient satisfaction with responsiveness (i.e., satisfaction). The analysis reveals that variations of these indicators are associated with patients' sociodemographic attributes and the hospitals' characteristics. However, while the likelihood of the actual provision of responsive care tends to be lower for vulnerable patients, the satisfaction of vulnerable populations with responsiveness tends to be higher. The data also reveal that the likelihood of responsive treatment and patient satisfaction with this tends to be lower for patients hospitalized in smaller hospitals and hospitals located in the periphery. The findings and their meaning are discussed in the context of studies on responsiveness of care, health disparities, dignified treatment, and patient satisfaction with the provision of health services.

PROBLEMS OF COLLABORATIONISM AND RUSSIAN PROPAGANDA IN EDUCATION IN THE TEMPORARILY OCCUPIED TERRITORIES DURING THE RUSSIAN-UKRAINIAN WAR (BASED ON UKRAINIAN MEDIA MATERIALS)

The article examines contemporary reflections in science on the concept and phenomenon of collaborationism. It explores the features of educational individual collaborationism, the reasons for its emergence in the conditions of the Russian-Ukrainian war. The issue of complicity in Ukrainian media emerges as a multifaceted phenomenon in the context of the war’s incompleteness, the passivity of the Ministry of Education, the imperfections of judicial practice and legal norms regarding the motivation and conditions of cooperation with the enemy, material and ideological (propagandistic) components, and so on. In the course of the comparative analysis, it was found out clarified that professional publications almost do not pay attention to educational collaborationism, instead transmitting a counter-propaganda narrative about teacher-heroes, patriots in storytelling materials, who continue to be defenders of Ukraine and role models for their students. General political publications address various issues of cooperation with the occupier in education in informational and analytical genres, performing enlightening, advocacy functions, as well as functions of prevention and criticism of this social phenomenon and contribute to its prevention.

Privacy-Preserving Image Storage on Cloud Using An Unified Cryptographic Authentication Scheme

With the proliferation of several cutting-edge technologies such as the Artificial Intelligence (AI), and Machine Learning (ML), Internet of Things (IoT), cloud technology is gaining colossal popularity in recent years. Despite the general publicity on the theme across the digital world, defending user data kept in the cloud database is the most decisive problem. Recent potential cyber attacks reveal that storing private images entails more unique care related to other types of information on the cloud. As the cloud customer who has kept their images has no control over their data the cloud service provider has to ensure better security against cyber threats. Cryptography algorithms are the best choice to secure pictorial data in the cloud. These techniques transform images into an inarticulate form to keep confidentiality over undependable and vulnerable social media .In this paper, we aim to propose an approach for improving image security on the cloud using cryptography algorithms. We developed a cohesive approach, called Unified Cryptographic Image Authentication (UCIA) to protect user images on a cloud platform. The proposed UCIA approach includes two phases: (i)UCIA engenders a cipher text through a Data Encryption Standard (DES) by providing a key and a message as input, and (ii)UCIA implements a Twofish algorithm to encipher the pictures by applying cipher text. The enciphered picture data is then stored in the cloud database and can be recovered when the customer requests it. The effectiveness of both enciphering and deciphering procedures are analyzed using the evaluation metrics including time for enciphering, deciphering, cloud storage, and enciphering throughput. Experimental results reveal the better performance and strength of the UCIA approach

A unified stochastic particle method with spatiotemporal adaptation for simulating multiscale gas flows

Recently, the Unified Stochastic Particle (USP) method has emerged as a promising approach for multiscale particle simulations, tailored specifically for non-equilibrium gas flow scenarios. However, in typical simulations of multiscale flow fields, the time step and grid size of the original USP method remain constrained by the smallest spatiotemporal scale of local flow field, limiting its true multiscale simulation potential. To overcome this critical issue, this work introduces a spatiotemporal adaptive USP method. Initially, we analyze the sources of errors in the traditional single-scale stochastic particle methods under large time steps, which leads to the derivation of the governing equations of USP. Building upon this foundation, we propose principles that dictate the rational time step and grid size for an arbitrary USP simulation. Subsequently, we introduce a spatiotemporal adaptive approach primarily based on the local gradient length, leading to the development of a USP solver endowed with spatiotemporal adaptability. The universality, reliability, and efficiency of the algorithm have been verified through an examination of three cases: two-dimensional flow over a cylinder, three-dimensional flow over a blunted body, and flow over a scaled X38-like model. This work forms an integral component of the development initiative for the general USP solver—SPARTACUS—with relevant source code being open-source in an online repository under the GNU General Public License (GPL).

Olsson.wl & ROC2.wl: Mathematica packages for transformations of multivariable hypergeometric functions & regions of convergence for their series representations in the two variables case

We present the Olsson.wlMathematica package which aims to find transformations for some classes of multivariable hypergeometric functions. It is based on a well-known method developed by P. O. M. Olsson [1] (1964) to derive the analytic continuations of the Appell F1 double hypergeometric series using the linear transformations of the Gauss F12 hypergeometric function. We provide a brief description of the method of Olsson and demonstrate the use of the commands of the Olsson.wl package using some examples that are presented in the text and in some ancillary Mathematica notebooks. In particular, we reproduce various results of the literature on multivariable hypergeometric functions and show practical applications of this package in the derivation of novel formulas. In the context of high energy physics, we also demonstrate how it can be used to disentangle some known results about the analytic continuation of some series representations of the one-loop pentagon in multi-Regge kinematics and D=6−2ϵ. We also provide a companion package, called ROC2.wl, which is dedicated to the derivation of the regions of convergence of double hypergeometric series. This package can be used independently of Olsson.wl. Program summaryProgram Title:Olsson.wlCPC Library link to program files:https://doi.org/10.17632/gc63xzwzz5.1Licensing provisions: GNU General Public License v3.0.Programming language: Wolfram Mathematica version 11.3 and beyond.Nature of problem: To find the transformation formulas of multivariable hypergeometric series appearing in Feynman integral calculus.Solution method: Mathematica implementation of the method of Olsson [1]. The method uses the transformation theory of lower variable hypergeometric functions to find the transformation formulas of higher variable hypergeometric functions.Companion package:ROC2.wl, which is a Mathematica package used inside Olsson.wl and can also be used as a standalone package. The package is used to find the region of convergence of double hypergeometric functions, using Horn's theorem.

Privacy-Preserving Image Storage on Cloud Using An Unified Cryptographic Authentication Scheme

With the proliferation of several cutting-edge technologies such as the Artificial Intelligence (AI), and Machine Learning (ML), Internet of Things (IoT), cloud technology is gaining colossal popularity in recent years. Despite the general publicity on the theme across the digital world, defending user data kept in the cloud database is the most decisive problem. Recent potential cyber attacks reveal that storing private images entails more unique care related to other types of information on the cloud. As the cloud customer who has kept their images has no control over their data the cloud service provider has to ensure better security against cyber threats. Cryptography algorithms are the best choice to secure pictorial data in the cloud. These techniques transform images into an inarticulate form to keep confidentiality over undependable and vulnerable social media .In this paper, we aim to propose an approach for improving image security on the cloud using cryptography algorithms. We developed a cohesive approach, called Unified Cryptographic Image Authentication (UCIA) to protect user images on a cloud platform. The proposed UCIA approach includes two phases: (i)UCIA engenders a cipher text through a Data Encryption Standard (DES) by providing a key and a message as input, and (ii)UCIA implements a Twofish algorithm to encipher the pictures by applying cipher text. The enciphered picture data is then stored in the cloud database and can be recovered when the customer requests it. The effectiveness of both enciphering and deciphering procedures are analyzed using the evaluation metrics including time for enciphering, deciphering, cloud storage, and enciphering throughput. Experimental results reveal the better performance and strength of the UCIA approach.

ElasTool v3.0: Efficient computational and visualization toolkit for elastic and mechanical properties of materials

Efficient computation and visualization of elastic and mechanical properties are crucial in the selection of materials and the design of new materials. The ElasTool v3.0 toolkit marks a significant advancement in the computational analysis and visualization of elastic and mechanical properties of materials, essential in material selection and design. This enhanced version extends beyond standard calculations like elastic tensor, Young's modulus, bulk modulus, and Poisson's ratio. It introduces capabilities for computing minimum thermal conductivity, linear compressibility, rendering the Christoffel equation, and elastic energy density. Notably, it integrates advanced visualization tools, including compatibility with Plotly and Elate web platforms for interactive web-based property exploration. A key feature of ElasTool v3.0 is the implementation of second-order elastic constants (SOECs) for tubular 2D-based nanostructures and nanotubes. Leveraging high-efficiency strain-matrix sets (OHESS), the toolkit now facilitates efficient computation of elastic constants and mechanical properties at both zero and finite temperatures for 1D, 2D, and 3D dimensions. ElasTool is openly accessible on GitHub: https://github.com/elastool. Program summaryProgram Title: ElasTool v3.0CPC Library link to program files:https://doi.org/10.17632/9hpgmspfmk.1Licensing provisions: GNU General Public License, version 3Programming language: Python 3Nature of problem: A computational toolkit that can efficiently compute the elastic and mechanical properties of materials using ab initio methods and provide advanced visualization capabilities is crucial to accurate material analysis.Solution method:ElasTool addresses this need by incorporating high-efficiency strain-matrix sets that require only small strain sets with ab initio methods such as density functional theory and molecular dynamics. This package is versatile and adept at calculating elastic constants for both 2D and 3D structures, including tubular 2D-based nanostructures and nanotubes and 1D nanoribbons at zero and finite temperatures. Beyond basic elastic moduli, ElasTool now boasts advanced visualization capabilities and computes additional critical properties such as minimum thermal conductivity, elastic energy density, and linear compressibility. This enhancement transforms ElasTool into a comprehensive tool for accelerated material design and modeling, and advanced visualization, offering both efficiency and depth in material property analysis.Additional comments including restrictions and unusual features:ElasTool is currently integrated with the Vienna Ab initio Simulation Package (VASP). Adapting to other electronic structures is straightforward.ElasTool offers serial and parallel execution. Depending on the system size, the number of strains, the nature of the calculations (zero or finite temperature), and the computing architecture, the computing time can vary from a minute to as long as 15 hours.