De Facto Standard Research Articles

Consistency of Bayes factor estimates in Bayesian analysis of variance.

Factorial designs lend themselves to a variety of analyses with Bayesian methodology. The de facto standard is Bayesian analysis of variance (ANOVA) with Monte Carlo integration. Alternative, and readily available methods, are Bayesian ANOVA with Laplace approximation as well as Bayesian t tests for individual effects. This simulation study compared the three approaches regarding ordinal and metric agreement of the resulting Bayes factors for a 2 × 2 mixed design. Simulation results indicate remarkable disagreement of the three methods in certain cases, particularly when effect sizes are small and studies include small sample sizes. Findings further replicate and extend previous observations of substantial variability of ANOVAs with Monte Carlo integration across different runs of one and the same analysis. These observations showcase important limitations of current implementations of Bayesian ANOVA. Researchers should be mindful of these limitations when interpreting corresponding analyses, ideally applying multiple approaches to establish converging results. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Entropy Production and Filling Time in Hydrogen Refueling Stations: An Economic Assessment.

A multi-objective optimization is performed to obtain fueling conditions in hydrogen stations leading to improved filling times and thermodynamic efficiency (entropy production) of the de facto standard of operation, which is defined by the protocol SAE J2601. After finding the Pareto frontier between filling time and total entropy production, it was found that SAE J2601 is suboptimal in terms of these process variables. Specifically, reductions of filling time from 47 to 77% are possible in the analyzed range of ambient temperatures (from 10 to 40 °C) with higher saving potential the hotter the weather conditions. Maximum entropy production savings with respect to SAE J2601 (7% for 10 °C, 1% for 40 °C) demand a longer filling time that increases with ambient temperature (264% for 10 °C, 350% for 40 °C). Considering average electricity prices in California, USA, the operating cost of the filling process can be reduced between 8 and 28% without increasing the expected filling time.

Fine-tuning protein language models boosts predictions across diverse tasks

Prediction methods inputting embeddings from protein language models have reached or even surpassed state-of-the-art performance on many protein prediction tasks. In natural language processing fine-tuning large language models has become the de facto standard. In contrast, most protein language model-based protein predictions do not back-propagate to the language model. Here, we compare the fine-tuning of three state-of-the-art models (ESM2, ProtT5, Ankh) on eight different tasks. Two results stand out. Firstly, task-specific supervised fine-tuning almost always improves downstream predictions. Secondly, parameter-efficient fine-tuning can reach similar improvements consuming substantially fewer resources at up to 4.5-fold acceleration of training over fine-tuning full models. Our results suggest to always try fine-tuning, in particular for problems with small datasets, such as for fitness landscape predictions of a single protein. For ease of adaptability, we provide easy-to-use notebooks to fine-tune all models used during this work for per-protein (pooling) and per-residue prediction tasks.

Alliance A022106: A phase II/III trial of NABPLAGEM vs nab-paclitaxel/gemcitabine as second-line treatment for BRCA1/2 or PALB2 mutant metastatic pancreatic ductal adenocarcinoma (PLATINUM).

TPS4205 Background: Multiple lines of evidence support the use of platinum-based chemotherapy for patients with homologous recombination deficiency-associated pancreatic adenocarcinoma (HRD PDAC; 15-20%). However, the impact of the specific platinum agent used remains uncertain. Mechanistically, oxaliplatin and cisplatin act distinctly on cancer cells, reflected in disparate toxicity profiles and target disease indications; furthermore, preclinical studies have shown that BRCA2-deficient cell lines and mice demonstrate significantly greater sensitivity to cisplatin compared to oxaliplatin. While oxaliplatin, part of the FOLFIRINOX regimen, represents the most commonly used platinum analogue for PDAC, clinical data shows that cisplatin (in combination with gemcitabine) can produce robust response rates (~70%) specifically in patients with germline BRCA/PALB2-mutated metastatic PDAC. We therefore designed a randomized clinical trial (PLATINUM) through the Alliance for Clinical Trials in Oncology cooperative group to assess the optimal chemotherapy regimen in patients with HRD-associated metastatic PDAC following front-line FOLFIRINOX and to test the hypothesis that a platinum switch strategy will be beneficial. Methods: The study consists of a seamless phase II/III design, with the primary endpoint of the phase III component being overall survival. Eligible patients will have metastatic PDAC, a confirmed pathogenic BRCA1/2 or PALB2 mutation (somatic or germline), and demonstrated disease progression on front-line FOLFIRINOX, with or without subsequent PARP inhibitor maintenance. Patients will be randomized 1:1 to receive (1) the de facto standard of gemcitabine plus nab-paclitaxel; or (2) the experimental 3-drug combination of gemcitabine, nab-paclitaxel, and cisplatin (NABPLAGEM), which has been previously studied in non-biomarker-selected patients with advanced biliary tract cancer (SWOG1815) and metastatic PDAC. Both treatment arms will use a once every other week dosing schedule. A total of 100 patients will be enrolled, which provides 90% power to detect an effect size of hazard ratio 0.5 (median OS of 18 vs 9 months) at a one-sided alpha of 0.05. Reports containing efficacy, adverse events, and administrative information will be provided to the Alliance DSMB every 6 months. Planned correlatives include ctDNA analysis for BRCA reversion mutations in all patients, as well as whole genome and transcriptome sequencing in an optional biopsy cohort. This study was activated in December 2023. Clinical trial information: NCT06115499 .

Integration of UML Class Diagrams Based on Semantics and Structure

As a high-level reuse, software design reuse has received more and more attention because of its important impact on the subsequent development stages. Usually, the design models are typically represented as some graphs or diagrams, in which Unified Modeling Language (UML) class diagram is so widely used in software design that it has become the de facto standard. There has been some research on the reuse of UML class diagrams so far, mainly focusing on matching and retrieval. However, it is worth noting that there are many similar class diagrams modeling the same object or some related class diagrams modeling different aspects of the same object in the reuse repository. As a matter of fact, the primary step to achieve a high-quality reuse is to have high-quality software artifacts, so the well-designed UML class diagrams become a necessary resource for software design reuse. Therefore, it is necessary to integrate these class diagrams so that they have stronger modeling ability, and eliminating redundancy is another benefit of the integration. Up to now, there has been little discussion about the integration of class diagrams, so we propose an integration approach based on semantics and structure in this paper. The equivalent elements that can identify the semantically merged parts are defined, and the possible conflict items are listed from both semantic and structural aspects. The integration procedure composed of three stages is proposed, in which an approach combining semantic common class diagrams (SCCDs) and structural common graph sequence (SCGS) is combined to determine the merged parts, the integration issue of heterogeneous class diagrams is considered from the proposed abstract models, and the conflict resolution for each conflict item is described by examples. The experimental results show the effectiveness of our proposed integration approach.

Value-driven industry transformation: Leveraging open-source to establish new standards

Traditional industries face growing pressure to digitally transform. In particular, established organizations must adopt new mindsets and act to remain competitive. To counter the challenges posed by monopolies and new entrants in a diverse and fiercely competitive landscape like Logistics, the Open Logistics Foundation (OLF) plays a pivotal role. It aims at fostering the development of logistics-specific open-source-software (OSS) to establish new digital services setting industry standards and ensuring enhanced connectivity and compatibility. The OLF represents an expanding core-community of dedicated logistics organizations. This core-community collaboratively identifies, selects, and develops relevant OSS for upcoming value-serving digital services and solutions. What sets this approach apart is its departure from the traditional solution-oriented open-source model. Instead of concluding with an OSS community, it starts with a dedicated core-community aiming at setting new widely adopted standards. However, even with this standard-driven approach, designing the right solution can be as challenging as finding a unicorn. To enhance the likelihood of success, this paper designed and evaluated the Minimum Viable core-Community driven Open-Source method (MV-COS). The MV-COS offers a comprehensive and standardized support allowing to holistically craft the vision, stakeholder-specific value propositions, and the corresponding implementation strategy of OSS projects. It prioritizes the early design and assessment of its likelihood to attract and align a critical mass of users which is the fundamental requirement for establishing new de-facto standards. The MV-COS enables to fail fast and iterate early, avoiding the unnecessary expenditure of resources.

Enhanced phylogenetic insights into the microbiome of chronic rhinosinusitis through the novel application of long read 16S rRNA gene amplicon sequencing.

16S rRNA next generation sequencing (NGS) has been the de facto standard of microbiome profiling. A limitation of this technology is the inability to accurately assign taxonomy to a species order. Long read 16S sequencing platforms, including Oxford Nanopore Technologies (ONT), have the potential to overcome this limitation. The paranasal sinuses are an ideal niche to apply this technology, being a low biomass environment where bacteria are implicated in disease propagation. Characterising the microbiome to a species order may offer new pathophysiological insights. Cohort series comparing ONT and NGS biological conclusions. Swabs obtained endoscopically from the middle meatus of 61 CRSwNP patients underwent DNA extraction, amplification and dual sequencing (Illumina Miseq (NGS) and ONT GridION). Agreement, relative abundance, prevalence, and culture correlations were compared. Mean microbiome agreement between sequencers was 61.4%. Mean abundance correlations were strongest at a familial/genus order and declined at a species order where NGS lacked resolution. The most significant discrepancies applied to Corynebacterium and Cutibacterium, which were estimated in lower abundance by ONT. ONT accurately identified 84.2% of cultured species, which was significantly higher than NGS. ONT demonstrated superior resolution and culture correlations to NGS, but underestimated core sinonasal taxa. Future application and optimisation of this technology can advance our understanding of the sinonasal microenvironment.

ASTM and ISO standards in U.S. legal language services

Abstract In the United States, legal language services are shaped by both de jure and de facto standards, which encompass not only the professional profile of court interpreters but also the provision of legal translation and interpreting services. This article investigates the potential influence of ASTM and ISO standards on current language services implementations in U.S. court settings in light of the current configuration of de jure and de facto standards. Specific emphasis is placed on the utility of consensus-based standards such as ASTM and ISO due to the unique configuration of language services, particularly given procurement and bidding practices, which complicate the current legal T&I landscape. Possible avenues for integration of ASTM and ISO standards are explored in light of infrastructure-specific as well as translator- and interpreter-specific requirements. The article concludes with a discussion of the compatibility of standards with current practices in the U.S. legal T&I sector.

Refinement-based Specification and Analysis of Multi-core ARINC 653 Using Event-B

ARINC 653 as the de facto standard of partitioning operating systems has been applied in many safety-critical domains. The multi-core version of ARINC 653, ARINC 653 Part 1-4 (Version 4), provides support for services to be utilized with a module that contains multiple processor cores. Formal specification and analysis of this standard document could provide a rigorous specification and uncover concealed errors in the textual description of service requirements. This article proposes a specification method for concurrency on a multi-core platform using Event-B, and a refinement structure for the complicated ARINC 653 Part 1-4 provides a comprehensive, stepwise refinement-based Event-B specification with seven refinement layers and then performs formal proof and analysis in RODIN. We verify that the errors discovered in the single-core version standard (ARINC 653 Part 1-3) also exist in the ARINC 653 Part 1-4 during the formal specification and analysis.

Analyzing the Standardization Landscape for Identity Management in Public Services – A Standards Review for the IMPULSE Project

The digitalization of public services is one of the major challenges that public administrations are currently facing. Electronic identifications play a major role for a variety of these related services. Due to the impact these services will have on the daily life of citizens, organizations, and the public at large, the social dimensions must be considered equally to the technical ones. To ensure the applicability, trust, and compliance of electronic identity for access to public services, it is necessary to take into account relevant standards collected through an analysis of the state-of-the-art. In general, the literature on integrating standardization in research projects is very rare and potential impacts of standards related to electronic identification have not been assessed yet. The European project IMPULSE has integrated standardization as an essential element and assessed the relevant standardization landscape as one activity. The analysis of the standardization landscape resulted in the identification of nine formal and six de-facto standards that have high relevance for IMPULSE. The process for this analysis and the resulting dashboard will support future projects to effectively consider, analyze and use standards for their projects.

The role of insurers in shaping international cyber-security norms about cyber-war

ABSTRACT Faced with defending against myriad online threats, businesses are increasingly turning to insurers to purchase cyber-insurance policies that will shield them from bearing the full costs of these incidents. Eager not to miss out on the expanding market, insurers have aggressively ramped up their cyber-insurance offerings, and in doing so, have assumed enormous responsibility—and power—as the arbiters of what types of state-sponsored cyber-attacks are covered by insurance. This article argues that insurance companies are influencing multilateral processes and setting de facto standards around responsible state behavior in cyberspace through their policies on risk and liability for serious cyber-operations and “cyber-war.” It approaches this issue through the lens of the 2017 Russian NotPetya cyber-attack which led to significant legal disputes between many insurers and their policyholders about whether Russia’s behavior constituted a “warlike action” and was therefore excluded from insurance coverage under standard war exclusions.

Best Practices for Integrating OAuth in Mobile Applications for Secure Authentication

For safe authentication in mobile apps, OAuth is becoming the de facto standard. Strong and reliable authentication methods are more important than ever before due to the meteoric surge in mobile app use. This need is satisfied by OAuth, which allows for protected resource access while protecting user credentials from prying eyes in third-party apps. In order to guarantee security and a smooth user experience, this abstract details best practices for incorporating OAuth into mobile applications, with an emphasis on critical concerns and tactics. An overview of OAuth's fundamental concepts, such as its authorisation processes, token management, and scope definitions, is provided at the outset of the talk. Use cases include mobile apps that make use of the Authorisation Code Flow with Proof Key for Code Exchange (PKCE) highlight the need of selecting the appropriate OAuth flow. Here is some practical advice on how to put these ideas into practice: make sure the OAuth client is securely registered with the authorisation server, use the device's secure storage facilities to store tokens, and use the right techniques for token expiry and renewal.

Molecular geometric deep learning

Molecular representation learning plays an important role in molecular property prediction. Existing molecular property prediction models rely on the de facto standard of covalent-bond-based molecular graphs for representing molecular topology at the atomic level and totally ignore the non-covalent interactions within the molecule. In this study, we propose a molecular geometric deep learning model to predict the properties of molecules that aims to comprehensively consider the information of covalent and non-covalent interactions of molecules. The essential idea is to incorporate a more general molecular representation into geometric deep learning (GDL) models. We systematically test molecular GDL (Mol-GDL) on fourteen commonly used benchmark datasets. The results show that Mol-GDL can achieve a better performance than state-of-the-art (SOTA) methods. Extensive tests have demonstrated the important role of non-covalent interactions in molecular property prediction and the effectiveness of Mol-GDL models.

Challenging the status quo in invasive species assessment using mechanistic physiologically based demographic modeling

AbstractThe increased incidence of invasive species introductions is a hallmark of global change, but their associated environmental and economic impacts are vastly underestimated. Assessing and managing the impact of invasive species requires understanding their weather driven dynamics as a basis for predicting their potential geographic distribution and relative abundance. Current de-facto standards for invasive species assessment are correlative approaches lacking mechanistic underpinnings, and hence fail to capture the weather driven biology limiting their explanatory and predictive capacity to forewarn policy makers of species invasiveness (i.e., its potential geographic distribution and relative abundance under extant and/or climate change weather). The idiosyncratic time-place nature of biological invasions and the inability of correlative approaches to incorporate biological information call for development of a unifying prospective approach across species. Physiologically based demographic models (PBDMs) provide a holistic basis for assessment of invasive species addressing many limitations of correlative approaches while accommodating higher level of biological complexity using a similar number of parameters. We use the South American tomato pinworm Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) as a case study in the Palearctic and compare the predictions of our PBDM model to those of three analyses based on the correlative CLIMEX model. The PBDM outperformed CLIMEX with comparable CLIMEX predictions only after the pest had reached its potential geographic distribution (i.e., post hoc), using 6–10 vs. 13 parameters, respectively. We suggest creating dedicated laboratories to gather appropriate biological data and developing generalized software to build mechanistic models for assessing invasive species of any taxa.

Self-Supervision for Medical Image Classification: State-of-the-Art Performance with ~100 Labeled Training Samples per Class.

Is self-supervised deep learning (DL) for medical image analysis already a serious alternative to the de facto standard of end-to-end trained supervised DL? We tackle this question for medical image classification, with a particular focus on one of the currently most limiting factor of the field: the (non-)availability of labeled data. Based on three common medical imaging modalities (bone marrow microscopy, gastrointestinal endoscopy, dermoscopy) and publicly available data sets, we analyze the performance of self-supervised DL within the self-distillation with no labels (DINO) framework. After learning an image representation without use of image labels, conventional machine learning classifiers are applied. The classifiers are fit using a systematically varied number of labeled data (1-1000 samples per class). Exploiting the learned image representation, we achieve state-of-the-art classification performance for all three imaging modalities and data sets with only a fraction of between 1% and 10% of the available labeled data and about 100 labeled samples per class.

Supervised Classification of UML Class Diagrams Based on F-KNB

Often most software development doesn’t start from scratch but applies previously developed artifacts. These reusable artifacts are involved in various phases of the software life cycle, ranging from requirements to maintenance. Software design as the high level of software development process has an important impact on the following stages, so its reuse is gaining more and more attention. Unified modeling language (UML) class diagram as a modeling tool has become a de facto standard of software design, and thus its reuse also becomes a concern accordingly. So far, the related research on the reuse of UML class diagrams has focused on matching and retrieval. As a large number of class diagrams enter the repository for reuse, classification has become an essential task. The classification is divided into unsupervised classification (also known as clustering) and supervised classification. In our previous work, we discussed the clustering of UML class diagrams. In this paper, we focus on only the supervised classification of UML class diagrams and propose a supervised classification method. A novel ensemble classifier F-KNB combining both dependent and independent construction ideas is built. The similarity of class diagrams is described, in which the semantic, structural and hybrid matching is defined, respectively. The extracted feature elements are used in base classifiers F-KNN and F-NBs that are constructed based on improved K-nearest neighbors (KNNs) and Naive Bayes (NB), respectively. A series of experimental results show that the proposed ensemble classifier F-KNB shows a good classification quality and efficiency under the condition of variable size and distribution of training samples.

Orthogonal frequency division multiplexing technology based on MATLAB

The subcarriers of an orthogonal frequency division multiplexing (OFDM) system are not identical in the time domain, and their spectra also overlap. As a result, the spectrum is being used effectively. Its effective use of frequency resources and capacity to combat channel fading have made it the de facto technical standard. In wireless communication, numerous pathways in the channel can lead to interference between symbols, known as inter-symbol interference (ISI). This research supplements OFDM systems with some safeguards to eliminate inter-symbol interference. Most traditionally, OFDM symbols have had their post-event sample points duplicated to their beginnings, a process known as Cyclic prefix (CP) padding in the protection interval. In order to further counteract ISI, a protection interval might be added to the beginning of each symbol. An OFDM system's bit error rate (BER) can be decreased by using cyclic prefixes to attenuate inter-code interference. This study explains how OFDM and CP-OFDM work and compares their performance. The primary topic of this study is a contrast between OFDM and CP-OFDM concerning the performance metrics of average symbol error rate (BER) and signal spectrum diagram (PSD).

Publishing Graphs Under Node Differential Privacy

Differential privacy (DP) has become the de facto standard of privacy protection. For graphs, there are two widely used definitions of differential privacy, namely, edge differential privacy (edge-DP) and node differential privacy (node-DP), and node-DP is preferred when the minimal unit of interest is a node. To preserve node-DP, one can develop different methods to answer each specific graph query, or develop a graph publishing method to answer all graph queries. However, no existing works worked on such graph publishing methods. In this work, we propose two methods for publishing graphs under node-DP. One is the node-level perturbation algorithm which modifies the input graph by randomly inserting and removing nodes. The other one is the edge-level perturbation algorithm which randomly removing edges and inserting nodes. Both methods can achieve a flexible privacy guarantee by adjusting the running parameters. We conduct extensive experiments on both real-world and synthetic graphs to show the effectiveness and efficiency of proposed algorithms.

Microservices Container Security Orchestration Framework within Kubernetes and Docker for Business-Critical Applications within Digital Transformation

Container virtualization technology facilitates the creation of microservices-based systems through continuous integration. Container-based apps can be deployed more easily when they use orchestration systems like Kubernetes, which has become the de facto standard. It can be difficult to create effective and precise orchestration systems, nevertheless. The scheduler, a crucial orchestrator task that allocates physical resources to containers, is the subject of this article. Scheduling strategies are developed using several Quality-of-Service metrics. The CI in CI/CD stands for continuous integration. Continuous integration drives the automation in the development and delivery of the code and developers frequently apply code changes. It’s an automated process that allows multiple developers to contribute software components to the same project without integration conflicts. CI also triggers the process of testing the applications automatically upon code commit into the repository. Container virtualization technology facilitates the creation of microservices-based systems through continuous integration. Container-based apps can be deployed more easily when they use orchestration systems like Kubernetes, which has become the de facto standard. It can be difficult to create effective and precise orchestration systems, nevertheless. The scheduler, a crucial orchestrator task that allocates physical resources to containers, is the subject of this article. Scheduling strategies are developed using several Quality of Service metrics.

On Problems in OpenBLAS Library Usage in Productized Code on RISC-V

The boundary element method usage for the numerical simulation in continuum mechanics problems leads to the need to solve a system of linear algebraic equations with a dense matrix. The de facto standards for the interface of functions over dense matrices and vectors software implementations are BLAS/LAPACK. Among the optimized open-source BLAS/LAPACK implementations, only the OpenBLAS library includes optimizations for the widest range of hardware platforms. This library is optimized for Intel, AMD, ARM and RISC-V architectures. The open RISC-V architecture ecosystem is currently actively developing. European supercomputing centers have opened RISC-V competence centers as part of the government's EuroHPC grant support, since solutions based on the ARM architecture are not recognized as part of the European initiative to develop its own technological independence. Currently, companies included in the international RISC-V consortium are developing not only high-performance RISC-V processors, but also AI accelerators, as well as video cards based on RISC-V architecture. OpenBLAS is actively supported and optimized for emerging RISC-V hardware and extensions. However, libraries used in product code are traditionally subject to strict requirements for stability and reliability in order to minimize possible errors and failures in the product. As it turned out, from this point of view, OpenBLAS has a number of problems that we had to solve in order to productize this library. In this article the OpenBLAS test system is described, the problems of testing the LAPACK functionality of the library and ways to solve them are discussed. In addition, the test coverage of the BLAS functionality is analyzed and the results achieved in increasing it are presented. It is planned to contribute the described changes to the OpenBLAS project.