Third-party Software Research Articles

OpenQP: A Quantum Chemical Platform Featuring MRSF-TDDFT with an Emphasis on Open-Source Ecosystem.

The OpenQP (Open Quantum Platform) is a new open-source quantum chemistry library developed to tackle sustainability and interoperability challenges in the field of computational chemistry. OpenQP provides various popular quantum chemical theories as autonomous modules such as energy and gradient calculations of HF, DFT, TDDFT, SF-TDDFT, and MRSF-TDDFT, thereby allowing easy interconnection with third-party software. A scientifically notable feature is the innovative mixed-reference spin-flip time-dependent density functional theory (MRSF-TDDFT) and its customized exchange-correlation functionals such as the DTCAM series of VAEE, XI, XIV, AEE, and VEE, which significantly expand the applicability scope of DFT and TDDFT. OpenQP also supports parallel execution and is optimized with BLAS and LAPACK for high performance. Future enhancements such as extended Koopman's theorem (EKT)-MRSF-TDDFT and spin-orbit coupling (SOC)-MRSF-TDDFT will further expand OpenQP's capabilities. Additionally, a Python wrapper PyOQP is provided that performs tasks such as geometry optimization, conical intersection searches, and nonadiabatic coupling calculations, among others, by prototyping the modules of the OpenQP library in combination with third-party libraries. Overall, OpenQP aligns with modern trends in high-performance scientific software development by offering flexible prototyping and operation while retaining the performance benefits of compiled languages like Fortran and C. They enhance the sustainability and interoperability of quantum chemical software, making OpenQP a crucial platform for accelerating the development of advanced quantum theories like MRSF-TDDFT.

The Semantic Function of Modern Chinese “Negation + X” Modal Words Based on Communication Technology and Big Data Corpus

The semantic function of modern Chinese “negation + X” modal words based on communication technology and big data corpus has gained wide attention. As the basis of SOA architecture, Web services provide the key resources for worldwide information transfer and information sharing with their characteristics of loose coupling, platform independence, and data exchange without additional support from third-party hardware and software. However, along with the popularization and improvement of Web service technology, the number and types of Web services in the Internet are also increasing massively, and there are a large number of Web services with various functions, quality and granularity. Therefore, how to quickly and accurately discover Web services that satisfy users’ query requests from a large and complex set of services has become a critical problem to be solved in the current Web service discovery research. Based on the real corpus, this paper analyzes the similarities and differences in the semantic functions of modern Chinese “negation + X” modal words by combining lexicalization and grammatization, cognitive linguistics, systemic functional grammar and other related theories. The experimental results demonstrate that the model is designed for automatic annotation of semantic word classes, and the annotation algorithm based on the hidden horse model, combined with the Viterbi algorithm based on dynamic programming, achieves a correct rate of 94.3% in the closed test and 89.1% in the open test despite the small size of the training corpus and severe data sparsity, and the model fitting effect meets the dynamic expectations.

Near-Infrared Autofluorescence Signatures of Single- vs Multigland Disease in Primary Hyperparathyroidism

The success of parathyroidectomy depends on accurate intraoperative localization and identification of all diseased glands in parathyroid exploration based on surgeon expertise to prevent persistent hyperparathyroidism. Near-infrared autofluorescence (NIRAF) imaging has recently emerged as a promising adjunctive intraoperative tool for localizing parathyroid glands; however, its potential utility in the assessment of parathyroid glands has yet to be established. To analyze the differences in NIRAF signatures of parathyroid glands in single vs multiple glands in primary hyperparathyroidism (pHPT). This prospective diagnostic study analyzed in vivo NIRAF images of parathyroid glands obtained during parathyroidectomies between November 18, 2019, and December 31, 2023, at a single tertiary referral center. Pixel intensities of the images were measured using third-party software. Patients who underwent parathyroidectomy for sporadic pHPT using a second-generation NIRAF imaging device were included. Patients with multiple endocrine neoplasm disorders were excluded. In vivo NIRAF images obtained during the procedures were analyzed. Near-infrared autofluorescence imaging during parathyroidectomy. The primary outcomes were the autofluorescence intensity and heterogeneity of single adenomas and multigland disease (ie, double adenomas and 3- or 4-gland hyperplasia) in sporadic pHPT. Normalized autofluorescence intensity was calculated by dividing the mean pixel intensity of the parathyroid gland by the background tissue. A heterogeneity index was calculated by dividing the standard deviation by the mean pixel intensity of the gland. The secondary outcome was the visibility of each parathyroid gland on NIRAF imaging before it became apparent to the naked eye during exploration. A total of 1287 in vivo NIRAF images obtained from 377 patients (median [IQR] age, 66 [56-73] years; 299 female [79.3%]) were analyzed. Of all patients, 230 (61.0%) had a single adenoma, 91 (24.1%) had double adenomas, and 56 (14.9%) had 3- or 4-gland hyperplasia. A mean (SD) of 3.4 (1.1) parathyroid glands were identified in the procedures. A comparison of 581 diseased glands (45.1%) and 706 normal glands (54.9%) showed a lower median normalized autofluorescence intensity of 2.09 (95% CI, 1.07-4.01) vs 2.66 (95% CI, 1.43-4.20; effect size = 0.36) and higher heterogeneity index of 0.18 (95% CI, 0.07-0.41) vs 0.11 (95% CI, 0.01-0.27; effect size = 0.45), respectively. Of diseased glands, single adenomas (233 [40.1%]) vs double adenomas (187 [32.2%]) and 3- or 4-gland hyperplasia (161 [27.7%]) had a lower median autofluorescence intensity of 1.92 (95% CI, 1.02-4.44) vs 2.22 (95% CI, 1.10-3.97; effect size = 0.21), respectively. On receiver operating characteristic analysis, the optimal autofluorescence intensity threshold to differentiate between single adenomas vs multigland disease was 2.14, with a sensitivity of 64.4%, specificity of 58.1%, and area under the curve of 0.626. These findings suggest that parathyroid glands in single- vs multigland disease may exhibit different autofluorescence characteristics. Although the effect size was modest, the differences identified should be kept in mind when assessing the parathyroid glands during surgical exploration.

PUPAID: A R + ImageJ pipeline for thorough and semi-automated processing and analysis of multi-channel immunofluorescence data

PUPAID is a workflow written in R + ImageJ languages which is dedicated to the semi-automated processing and analysis of multi-channel immunofluorescence data. The workflow is designed to extract fluorescence signals within automatically-segmented cells, defined here as Areas of Interest (AOI), on whole multi-layer slides (or eventually cropped sections of them), defined here as Regions of Interest (ROI), in a simple and understandable yet thorough manner. The included (but facultative) R Shiny-based interactive application makes PUPAID also suitable for scientists who are not fluent with R programming. Furthermore, we show that PUPAID identifies significantly more cells, especially in high-density regions, as compared to already published state-of-the-art methods such as StarDist or Cellpose. For extended possibilities and downstream compatibility, single cell information is exported as FCS files (the standardized file format for single cell-based cytometry data) in order to be openable using any third-party cytometry analysis software or any analysis workflow which takes FCS files as input.

Correlation Between Near-Infrared Autofluorescence Properties and Sestamibi Uptakes of Parathyroid Glands in Primary Hyperparathyroidism.

Near-infrared autofluorescence (NIRAF) characteristics of parathyroid glands in primary hyperparathyroidism (pHPT) vary, with unclarity regarding the underlying mechanism. Similarly, 99mTc-sestamibi uptake in diseased parathyroid glands is variable. There is a suggestion that oxyphilic cell content may influence both imaging modalities. This study aims to analyze the relationship between NIRAF imaging characteristics, 99mTc-sestamibi uptake, and cellular composition in pHPT. Retrospective analysis of an Institutional Review Board-monitored prospective database. Single tertiary referral center. NIRAF characteristics of parathyroid glands of patients with pHPT between 2019 and 2024 were compared with 99mTc-sestamibi scan findings from a prospective database. Using third-party software, brightness intensity and heterogeneity index (HI) of the glands were calculated. A subgroup of parathyroid glands obtained from consecutive patients with pHPT in 2020 to 2021 underwent histological analysis. A total of 428 patients with 638 diseased parathyroid glands were analyzed. Forty-seven percent of the glands showed an uptake on 99mTc-sestamibi scans. The brightness intensity of the NIRAF signals from parathyroid glands that were seen versus not seen on sestamibi was 2.1 versus 2.3 (P = .002) and HI 0.18 versus 0.17 (P = .35), respectively. On multivariate analysis, low autofluorescence intensity, high gland volume, and single adenoma were associated with detectability on 99mTc-sestamibi scan (P < .0001). Intraglandular adipose tissue content was lower in diseased glands that were detected on 99mTc-sestamibi scans (0% vs 5%, P < .0001). Our findings indicate an inverse relationship between autofluorescence intensity and detectability on 99mTc-sestamibi scans and a lack of correlation between different cell types and autofluorescence properties.

Software supply chain security: a systematic literature review

ABSTRACT In recent years, software supply chain security has attracted significant research attention. This research subject is concerned both with the security of infrastructures used to build software and deliver it to end users and with the security of software that contains external dependencies such as third-party packages and libraries, and its chief goal is to ensure that no vulnerabilities are introduced in the path between developers and users. This paper presents a Systematic Literature Review to identify knowledge gaps in software supply chain security. For this, we considered studies published between 2012 and 2023 in the search engines of IEEE Xplore, ACM Digital Library, Engineering Village, Scopus, and arXiv. Of the 2051 studies obtained in the primary survey, only 85 are relevant for this research. Analyzing the studies, we observed gaps such as little discussion of software supply chains that involve cloud components, few proposals focused on the software distribution process, and a lack of use of threat modeling frameworks to help identify threats to the supply chain and validate the results.

SPRank─A Knowledge-Based Scoring Function for RNA-Ligand Pose Prediction and Virtual Screening.

The growing interest in RNA-targeted drugs underscores the need for computational modeling of interactions between RNA molecules and small compounds. Having a reliable scoring function for RNA-ligand interactions is essential for effective computational drug screening. An ideal scoring function should not only predict the native pose for ligand binding but also rank the affinity of the binding for different ligands. However, existing scoring functions are primarily designed to predict the native binding modes for a given RNA-ligand pair and have not been thoroughly assessed for virtual screening purposes. In this paper, we introduce SPRank, a combination of machine-learning and knowledge-based scoring functions developed through a weighted iterative approach, specifically designed to tackle both binding mode prediction and virtual screening challenges. Our approach incorporates third-party docking software, such as rDock and AutoDock Vina, to sample flexible ligands against an ensemble of RNA structures, capturing the conformational flexibility of both the RNA and the ligand. Through rigorous testing, SPRank demonstrates improved performance compared to the tested scoring functions across four test sets comprising 122, 42, 55, and 71 nucleic acid-ligand complexes. Furthermore, SPRank exhibits improved performance in virtual screening tests targeting the HIV-1 TAR ensemble, which highlights its advantage in drug discovery. These results underscore the advantages of SPRank as a potentially promising tool for the RNA-targeted drug design. The source code of SPRank and the data sets are freely accessible at https://github.com/Vfold-RNA/SPRank.

COMPARISON OF MESSAGE PASSING SYSTEMS IN CONTEXT OF ADAPTIVE LOGGING METHOD

Computer software is an important part of technological progress. As it becomes more and more complex and sophisticated, so does the need to protect it. Apart from typical information security aspects of integrity, availability and confidentiality, the scale and complexity of modern computer systems require a high level of control and observability. The main goal of this research is to build upon the foundations laid by the general idea of an adaptive logging method and introduce the next iteration of its design in the form of an appropriate message passing system to be used to propagate required changes to corresponding implementation in an effective and performant manner. Four different message passing system models are introduced, based on different technologies such as RabbitMQ message broker, communication channels in PostgreSQL database management system, general web server architecture and Linux-based process signaling interface. For each of those an overview description and graphical model is presented. Finally, the resulting comparison is conducted, comparing aspects such as reliance on third-party software, communication medium, error surface increase and authentication related considerations. As a result, the design based on process signaling approach is determined to be the most suitable for adaptive logging method, as it does not introduce any third-party software (and as such affects error surface in a somewhat negligible manner), binds directly to an observed application, is built using low level concepts that should be present in multiple different platforms and programming languages and should be able to reuse authentication logic that is already used when accessing computational machine where observed program is executed.

Leveraging the Apple Ecosystem: Easy Viewing and Sharing of Three-dimensional Perforator Visualizations via iPad/iPhone-based Augmented Reality

Summary: We introduce a novel technique using augmented reality (AR) on smartphones and tablets, making it possible for surgeons to review perforator anatomy in three dimensions on the go. Autologous breast reconstruction with abdominal flaps remains challenging due to the highly variable anatomy of the deep inferior epigastric artery. Computed tomography angiography has mitigated some but not all challenges. Previously, volume rendering and different headsets were used to enable better three-dimensional (3D) review for surgeons. However, surgeons have been dependent on others to provide 3D imaging data. Leveraging the ubiquity of Apple devices, our approach permits surgeons to review 3D models of deep inferior epigastric artery anatomy segmented from abdominal computed tomography angiography directly on their iPhone/iPad. Segmentation can be performed in common radiology software. The models are converted to the universal scene description zipped format, which allows immediate use on Apple devices without third-party software. They can be easily shared using secure, Health Insurance Portability and Accountability Act–compliant sharing services already provided by most hospitals. Surgeons can simply open the file on their mobile device to explore the images in 3D using “object mode” natively without additional applications or can switch to AR mode to pin the model in their real-world surroundings for intuitive exploration. We believe patient-specific 3D anatomy models are a powerful tool for intuitive understanding and communication of complex perforator anatomy and would be a valuable addition in routine clinical practice and education. Using this one-click solution on existing devices that is simple to implement, we hope to streamline the adoption of AR models by plastic surgeons.

YADE - An extensible framework for the interactive simulation of multiscale, multiphase, and multiphysics particulate systems

This contribution presents the key elements of YADE, an extensible open-source framework for dynamic simulations. During the past 19 years, YADE has evolved from “Yet Another Dynamic Engine” to a versatile multiscale and multiphysics solver, counting a large, active, and growing community of users and developers. The computationally intense parts of the source code are written in C++, using flexible object models that allow for easy implementation of new features. The source code is wrapped in Python, equipping the software with an interactive kernel used for rapid and concise scene construction, simulation control, post-processing, and debugging. The project, including documentation and examples, is hosted on https://yade-dem.org, while the source code is freely available on GitLab. Over the last decade, YADE has expanded in terms of capabilities thanks to the contribution of many developers from different fields of expertise, including soil and rock mechanics, chemical engineering, physics, bulk material handling, and mineral processing. The rapid growth of YADE can be attributed to (1) the careful and robust design of the framework core, (2) a continuous integration pipeline with fully embedded thorough tests which are executed upon each merge request, ensuring stable compilation for various operating systems, and (3) user-friendliness, facilitated by the Python interface, detailed documentation, and rigorous user support. In this paper, we review the main features of YADE, highlighting its versatility in terms of applications, its flexibility in terms of code development, as well as recent improvements in terms of computational efficiency. Program summaryProgram Title: YADE - Yet Another Dynamic EngineCPC Library link to program files:https://doi.org/10.17632/n4f5fw97rd.1Developer's repository link:https://gitlab.com/yade-dev/trunkLicensing provisions: GNU General Public License 2Programming language: C++, PythonNature of problem: Numerical simulation of many-particle systems requires accurate models for particle-to-particle interactions, efficient contact detection between objects of various shapes, and robust time integration. In addition, the flow of fluids, thermal effects, as well as other coupled problems in the presence of particles are found in many fundamental and practical applications and they need dedicated computational tools. YADE provides a computational framework to perform such simulations using the discrete element method and multiple extensions of it.Solution method:YADE simulates particulate systems using the Discrete Element Method (DEM) in a flexible platform combining C++ and Python. It provides a large variety of shape and interaction models, an explicit time-integration scheme, and many post-processing tools. YADE features dedicated solvers for both fluid and heat fluxes at the pore scale, and it supports couplings with third-party software such as Escript (finite element method) and OpenFOAM (computational fluid dynamics).

Brain-Computer Interface Integration With Extended Reality (XR): Future, Privacy And Security Outlook

The Brain-Computer Interface (BCI) is a rapidly evolving technology set to revolutionize our perception of the Internet of Things (IoT). BCI facilitates direct communication between the brain and external devices, enabling the control or interaction of devices without physical intervention. BCI technology is becoming more sophisticated, allowing third-party software embedded in emerging technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) to access sensors that read brain activity. These can be grouped under the umbrella term Extended Reality (XR). While BCI technology is disrupting the way data is collected, interpreted, and utilized within IoT networks, it is important to consider the potential privacy and security threats that it poses. Previous and not-so-recent cybersecurity research only scratched the surface in terms of security and privacy aspects of the then-emerging neural and brain-connecting technologies. However, recent advances in reconstructing language, music tracks, and imagery solely based on decoding neural signals pose a significant risk of mental privacy invasion and cybersecurity abuse. In this paper, we present an analysis of the potential threats posed by the integration of BCI with VR, AR, and MR. We analyze the involvement of major technological players in shaping BCI and XR advancements, examining the potential for these technologies to create detailed user profiles and reshape the monetization of user data in the ever-more-aggressive data-driven economy. We also outline a position view on the cybersecurity aspects that are not related to privacy and profiling per se, for example, cybersecurity attacks on the brain (e.g., ``brain rewriting'' attacks) facilitated by potentially vulnerable XR-BCI devices and software. The paper concludes by emphasizing the need for further research on the privacy and security implications of XR-BCI integration and inviting deeper exploration of the topic beyond theoretical papers and toward a more applied experimental setup.

Online Retail of Derived Psychoactive Cannabis Products: Age and Shipping Restrictions

PurposeThe 2018 US Farm Bill's definition of hemp resulted in the proliferation of derived psychoactive cannabis products (DPCPs), which appeal to some youth. Despite the importance of restricting youth access, few studies have systematically examined the DPCP retail environment, particularly their online accessibility. MethodsIn May 2023, Google incognito mode was used to search "buy delta thc." Among the first 100 results, data were collected from the 20 most trafficked websites that sold and delivered DPCPs. For each site, we documented the following policy-relevant information: 1) age verification measures for site entry and purchase attempts, 2) adult signature reportedly required upon delivery, and 3) shipping restrictions. ResultsOverall, 14 websites (70%) required individuals to indicate their age. Most websites (n = 13, 65%) did not verify age at attempted purchase, nor indicated that an adult signature was required upon delivery (n = 15, 75%). Only three websites (15%) had rigorous age verification procedures during checkout that included contact information as well as an image of their photo ID, which would then be validated through a third-party software. None required age verification upon both purchase and delivery. Thirteen websites (65%) mentioned state shipping restrictions; four of these provided conflicting information across different sections of the website. DiscussionAs the e-commerce landscape continues to evolve, clearer regulations regarding DPCP online retail sales and related enforcement are needed. In particular, measures are needed to enforce shipping restrictions and prevent youth access, including increasing the rigor of age verification.

Survey of techniques to detect common weaknesses in program binaries

Software vulnerabilities resulting from coding weaknesses and poor development practices are common. Attackers can exploit these vulnerabilities and impact the security and privacy of end-users. Most end-user software is distributed as program binaries. Therefore, to increase trust in third-party software, researchers have built techniques and tools to detect and resolve different classes of coding weaknesses in binary software. Our work is motivated by the need to survey the state-of-the-art and understand the capabilities and challenges faced by binary-level techniques that were built to detect the most important coding weaknesses in software binaries. Therefore, in this paper, we first show the most critical coding weaknesses for compiled programming languages. We then survey, explore, and compare the static techniques that were developed to detect each such coding weakness in software binaries. Our other goal in this work is to discover and report the state of published open-source implementations of static binary-level security techniques. For the open-source frameworks that work as documented, we independently evaluate their effectiveness in detecting code vulnerabilities on a suite of program binaries. To our knowledge, this is the first work that surveys and independently evaluates the performance of state-of-the-art binary-level techniques to detect weaknesses in binary software.

Inter-species Transcriptomic Analysis Reveals a Constitutive Adaptation Against Oxidative Stress for the Highly Virulent Leptospira Species.

Transcriptomic analyses across large scales of evolutionary distance have great potential to shed light on regulatory evolution but are complicated by difficulties in establishing orthology and limited availability of accessible software. We introduce here a method and a graphical user interface wrapper, called Annotator-RNAtor, for performing interspecies transcriptomic analysis and studying intragenus evolution. The pipeline uses third-party software to infer homologous genes in various species and highlight differences in the expression of the core-genes. To illustrate the methodology and demonstrate its usefulness, we focus on the emergence of the highly virulent Leptospira subclade known as P1+, which includes the causative agents of leptospirosis. Here, we expand on the genomic study through the comparison of transcriptomes between species from P1+ and their related P1- counterparts (low-virulent pathogens). In doing so, we shed light on differentially expressed pathways and focused on describing a specific example of adaptation based on a differential expression of PerRA-controlled genes. We showed that P1+ species exhibit higher expression of the katE gene, a well-known virulence determinant in pathogenic Leptospira species correlated with greater tolerance to peroxide. Switching PerRA alleles between P1+ and P1- species demonstrated that the lower repression of katE and greater tolerance to peroxide in P1+ species was solely controlled by PerRA and partly caused by a PerRA amino-acid permutation. Overall, these results demonstrate the strategic fit of the methodology and its ability to decipher adaptive transcriptomic changes, not observable by comparative genome analysis, that may have been implicated in the emergence of these pathogens.

115 Time-driven Activity-based Costing for ACDF: An Automated and Scalable Solution

INTRODUCTION: Understanding the true (intraoperative) cost to the hospital when neurosurgeons perform anterior cervical discectomy and fusion (ACDF) is critical as we move towards value-based purchasing. METHODS: Total cost was divided into direct and indirect costs. Individual costs were obtained by direct observation, electronic medical records, and through querying multiple departments (business operations, sterile processing, plant operations, and pharmacy). Timestamps for all involved personnel and material resources were documented. Total intraoperative costs were estimated for all ACDFs from 2017 and 2022. RESULTS: A total of 959 patients underwent anterior cervical fusions between 2017 and 2022 (one-level: n = 400, 41.7%; two-level: n = 407, 42.4%; three-level: n = 139, 14.5%; greater than three-level: n = 13, 1.4%). The most common pre-operative diagnosis was myelopathy (n=586, 61.1%), followed by radiculopathy (n = 256, 26.7%). The average total intraoperative cost per case was $5,970 ± $2,137; $7,542 ± $3,119; $8,958 ± $3,096; and $9,297 ± $2,633 for one-, two-, three-, and greater than three-level fusions, respectively. The major cost contributors were supply costs ($4,745, 66%) and personnel costs ($2,417; 34%). Total intraoperative costs displayed more variation with two-level ACDFs as compared to other fusions. Total supply cost, particularly implant cost ($3,399 ± $2,161), followed by total personnel cost (2,417 ± $917) was responsible for most of the observed total cost variability across all anterior cervical fusions. CONCLUSIONS: TDABC is a feasible and scalable methodology for understanding the true intraoperative costs of ACDF, without having to rely on proprietary third-party software. The most common reason for surgery was myelopathy, followed by radiculopathy. The major cost contributors were supply and personnel costs. Two-level ACDFs appeared to display more total cost variability as compared to other fusions. Implant costs, followed by personnel costs, appeared to be responsible for cost variation across all anterior cervical fusions.

EVOLUTION OF RENDERING BASED ON RADIANCE FIELDS. THE PALERMO CASE STUDY FOR A COMPARISON BETWEEN NERF AND GAUSSIAN SPLATTING

Abstract. In recent years there has been a rapid diffusion of new digitization methodologies based on radiance fields and the implementation of new rendering processes and learning systems based on neural networks. The article focuses on these new tools and how they can be used for the knowledge and dissemination of Cultural Heritage. A case study is then described regarding the video acquisition of a noble chapel of the Cemetery of Santa Maria dei Rotoli in Palermo to promote knowledge of ‘fragile’ artefacts, exposed to the risk of radical transformation or degradation, and thus protecting their conservation. The research aims to compare the first results obtained through the NeRF and Gaussian Splatting methodology which constitute the current state of the art of this type of processing; both the source algorithms (Nerfacto and 3D Gaussian Splatting) and the Luma AI web app were used, and data management was studied using third-party software such as Blender 3D, Unreal Engine 5.0 and the playcanvas game engine. The results obtained with this case study are of particular interest, above all for the processing of data useful for the visualization of heritage starting from unconventional acquisitions.

Commissioning and implementing a Quality Assurance program for dedicated radiation oncology MRI scanners.

ACR and AAPM task group's guidelines addressing commissioning for dedicated MR simulators were recently published. The goal of the current paper is to present the authors' 2-year experience regarding the commissioning and introduction of a QA program based on these guidelines and an associated automated workflow. All mandatory commissioning tests suggested by AAPM report 284 were performed and results are reported for two MRI scanners (MAGNETOM Sola and Aera). Visual inspection, vendor clinical or service platform, third-party software, or in-house python-based code were used. Automated QA and data analysis was performed via vendor, in-house or third-party software. QATrack+ was used for QA data logging and storage. 3D geometric distortion, B0 inhomogeneity, EPI, and parallel imaging performance were evaluated. Contrasting with AAPM report 284 recommendations, homogeneity and RF tests were performed monthly. The QA program allowed us to detect major failures over time (shimming, gradient calibration and RF interference). Automated QA, data analysis, and logging allowed fast ACR analysis daily and monthly QA to be performed in 3h. On the Sola, the average distortion is 1mm for imaging radii of 250mm or less. For radii of up to 200mm, the maximum, average (standard deviation) distortion is 1.2 and 0.4mm (0.3mm). Aera values are roughly double the Sola for radii up to 200mm. EPI geometric distortion, ghosting ratio, and long-term stability were found to be under the maximum recommended values. Parallel imaging SNR ratio was stable and close to the theoretical value (ideal g-factor). No major failures were detected during commissioning. An automated workflow and enhanced QA program allowed to automatically track machine and environmental changes over time and to detect periodic failures and errors that might otherwise have gone unnoticed. The Sola is more geometrically accurate, with a more homogenous B0 field than the Aera.

Analisis Forensik Pada Instagram dan Tik Tok Dalam Mendapatkan Bukti Digital Dengan Menggunakan Metode NIST 800-86

Crime is currently increasing with the development of this smartphone, one of which is the crime of using social media. Instagram and Tik Tok are one of the most widely used social media applications in this era. The more users of this social media, it does not rule out the emergence of crimes against fellow users of this social media. Every activity carried out on social media, including criminal acts, leaves evidence or digital traces; whether deleted or not, all will be visible. Digital forensics is the study of how to obtain digital evidence obtained from digital devices. This study aims to determine the process of finding digital evidence on Instagram and Tik Tok social media applications that are accessed via smartphones using the National Institute of Standards and Technology (NIST) method. The stages in this digital forensic method include Collection, Examination, Analysis, and Reporting to obtain digital evidence on Instagram and TikTok using tools in the form of third-party software, namely MOBILedit Forensic Express, Autopsy, and FTK Imager tools. With the final result for the Instagram application tools, MOBILedit Forensic Express is able to acquire evidence with a percentage of 0.02%, for autopsy tools at 40%, and FTK Imager with a percentage of 57%. In the Tiktok application itself, MOBILedit Forensic Express gets a percentage of 27%, while an autopsy is 29%, and the last is the FTK Imager tool with a percentage of 71%. In this study, the FTK Imager tool is superior in the acquisition of evidence between the two tools.

Data-centric workloads with MPI_Sort

Sorting is a fundamental task in computing and plays a central role in information technology. The advent of rack-scale and warehouse-size data processing shaped the architecture of data analysis platforms towards supercomputing. In turn, established techniques on supercomputers have become relevant to a wider range of application domains. This work is concerned with multi-way mergesort with exact splitting on distributed memory architectures. At its core, our approach leverages a novel and parallel algorithm for multi-way selection problems. Remarkably concise, the algorithm relies on MPI_Allgather and MPI_ReduceScatter_block, two collective communication schemes that find hardware support in most high-end networks. A software implementation of our approach is used to process the Terabyte-size Data Challenge 2 signal, released by the SKA radio telescopes organization. On the supercomputer considered herein, our approach outperforms the state of the art by up to 2.6X using 9,216 cores. Our implementation is released as a compact open source library compliant to the MPI programming model. By supporting the most popular elementary key types, and arbitrary fixed-size value types, the library can be straightforwardly integrated into third-party MPI-based software.

Research on Aerospace Software Quality Improvement Based on Software Test Data Analysis

This paper addresses the issue of underutilized software test data in current aerospace software quality management. Through analyzing the current third-party software evaluation process, the paper proposes to optimize software evaluation process and management to enhance software development quality and software test quality. The paper proposes an aerospace software quality improvement framework based on software test data analysis, which provides a reference scheme for aerospace software quality management. Overall, the paper emphasizes the importance of software test data analysis in improving aerospace software quality and provides a comprehensive solution for addressing problems identified in aerospace software quality management.