Open Resources Research Articles

Five key actions for redesigning adult skills assessments from learners, employees, and educators

AbstractSummative assessments provide data to evaluate the effectiveness of schools, teachers, and educational policies, contributing to a robust accountability system worldwide. However, educators and scholars argue that summative assessments do not effectively promote ongoing learning, enhance teaching practices, or align with the skills required in the workplace. Furthermore, traditional summative testing approaches lack culturally responsive practices and overlook the diverse needs of adult learners. This article summarizes research conducted through focus groups, interviews, and listening sessions to gain insight into learners’, employees’, and educators’ perceptions of assessment needs in adult education and workforce development in the United States. We conducted six focus groups, four interviews with diverse learners and employees, and two listening sessions with educators and administrators. In-person and online formats were used in Spanish and English. The results indicate that the backgrounds and needs of learners, employees, and educators in this study are diverse, but all agree there is a strong need for open assessment resources for mid- and lower-skilled and culturally diverse learners that provide them with useful information to help them achieve their personal and occupational goals. Educators in this study needed assessment information connected to the standards and curriculum that guide their instruction, and employees and their employers needed tools to identify and train adult learners for in-demand skills within industries and occupations. Assessing adult skills requires addressing these needs by designing tests that focus on learners’ characteristics and goals and are integrated with educators’ and employers’ needs and goals. The research findings suggest that assessments should be personalized to learners, integrated with instruction or job training, and embrace the cultural diversity of the adult learner population better to serve learners, employees, and educators.

Maastrichtian palaeoenvironments and palaeoclimate reconstruction in southern South America (Patagonia, Argentina) based on fossil fungi and algae using open data resources

ABSTRACT The use of non-pollen palynomorphs (NPP), particularly fossil fungi and algae, as palaeobiological proxies for Late Cretaceous palaeoenvironmental and palaeoclimatic reconstructions of warm-to-hot greenhouse conditions, can enhance our understanding of climate change impacts on modern Patagonian environments. This study aimed to reconstruct the Maastrichtian palaeoenvironment and palaeoclimate in the Cañadón Asfalto Basin (CAB, Chubut Province) by testing these NPPs as proxies using the Nearest Living Relative method (NLR). Moreover, using modern ecological requirements from open-source databases, such as GBIF and processing it with an open-source, cross-platform tool like QGIS, linked with Köppen-Geiger shapefiles, provided evidence of climate-driven palaeo-distribution patterns of fungal and algal diversity at CAB. Applying modern ecological requirements and biogeographic distribution data, we reconstructed the palaeoclimate as temperate with evenly distributed precipitation and warm summers, corresponding to the Cfb climate zone in Köppen-Geiger classifications. Additionally, our methodology produced reliable results regarding Cenozoic floras’ physiognomies based on fossil fungi, revealing a transition from sparsely wooded areas with palms and prairies to complex forest ecosystems with palms, deciduous trees, and shrubland. Furthermore, testing Cretaceous algae with the NLR method, for the first time, provided comprehensive insights into past water body characteristics, including trophic state and water quality.

The DoGA consortium expression atlas of promoters and genes in 100 canine tissues

The dog, Canis lupus familiaris, is an important model for studying human diseases. Unlike many model organisms, the dog genome has a comparatively poor functional annotation, which hampers gene discovery for development, morphology, disease, and behavior. To fill this gap, we established a comprehensive tissue biobank for both the dog and wolf samples. The biobank consists of 5485 samples representing 132 tissues from 13 dogs, 12 dog embryos, and 24 wolves. In a subset of 100 tissues from nine dogs and 12 embryos, we characterized gene expression activity for each promoter, including alternative and novel, i.e., previously not annotated, promoter regions, using the 5’ targeting RNA sequencing technology STRT2-seq. We identified over 100,000 promoter region candidates in the recent canine genome assembly, CanFam4, including over 45,000 highly reproducible sites with gene expression and respective tissue enrichment levels. We provide a promoter and gene expression atlas with interactive, open data resources, including a data coordination center and genome browser track hubs. We demonstrated the applicability of Dog Genome Annotation (DoGA) data and resources using multiple examples spanning canine embryonic development, morphology and behavior, and diseases across species.

Baby Open Brains: An Open-Source Repository of Infant Brain Segmentations.

Reproducibility of neuroimaging research on infant brain development remains limited due to highly variable protocols and processing approaches. Progress towards reproducible pipelines is limited by a lack of benchmarks such as gold standard brain segmentations. Addressing this core limitation, we constructed the Baby Open Brains (BOBs) Repository, an open source resource comprising manually curated and expert-reviewed infant brain segmentations. Markers and expert reviewers manually segmented anatomical MRI data from 71 infant imaging visits across 51 participants, using both T1w and T2w images per visit. Anatomical images showed dramatic differences in myelination and intensities across the 1 to 9 month age range, emphasizing the need for densely sampled gold standard manual segmentations in these ages. The BOBs repository is publicly available through the Masonic Institute for the Developing Brain (MIDB) Open Data Initiative, which links S3 storage, Datalad for version control, and BrainBox for visualization. This repository represents an open-source paradigm, where new additions and changes can be added, enabling a community-driven resource that will improve over time and extend into new ages and protocols. These manual segmentations and the ongoing repository provide a benchmark for evaluating and improving pipelines dependent upon segmentations in the youngest populations. As such, this repository provides a vitally needed foundation for early-life large-scale studies such as HBCD.

IntAct Database for Accessing IMEx's Contextual Metadata of Molecular Interactions.

The International Molecular Exchange Consortium (IMEx) has evolved into a vital partnership of open resources dedicated to curating molecular interaction data from the scientific literature. This consortium, which includes IntAct, MINT, MatrixDB, and DIP, is a collaborative effort with a central mission of aggregating detailed molecular interaction experimental evidence in a machine-readable format, supported by controlled vocabularies and standard ontologies. The IntAct molecular interaction database (www.ebi.ac.uk/intact), as an IMEx partner, serves as a valuable portal for accessing IMEx data through user-friendly search options and an array of interactive filters. The resource currently hosts an extensive repository of 1,293,508 binary interactions meticulously captured from 75,098 experiments documented in 23,366 publications (as of the February 2024 release), with this corpora being added to by regular data releases. IMEx curation policy has consistently prioritized a fine-grained data and curation model, with a focus on capturing the relevant experimental details essential for interpreting molecular interaction data effectively. Our curation process is designed to support the generation of interactomes tailored to contexts such as disease-specific or tissue-/cell-type-specific interactomes. These interactions are ranked according to a scoring system based on the Proteomics Standard Initiative Molecular Interaction (PSI MI) standards. This scoring system allows users to assess the degree of confidence in binary interactions, enhancing the value of the data. The resource provides insights into the nature of relationships among interacting partners as defined by the experimental setup and the associated biological context. Interactive filters enable users to navigate these rich, multilayered data, promoting a deeper understanding of biological complexity. Additionally, the IntAct website fosters the creation of networks for collaborative analyses by the scientific community. The recent transformation of the IntAct website, supported by a graph-type database, empowers users to execute custom queries tailored to their specific research interests. This article illustrates the diverse levels of annotations available for interactions and the multiple search options at users' disposal to access data of interest. © 2024 European Molecular Biology Laboratory, European Bioinformatics Institute. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Using Quick Search, network visualization, and filters Support Protocol: Accessing fine annotations from intact: Unlocking the molecular details Alternate Protocol: Using batch search: Querying multiple interactors Basic Protocol 2: Using advanced search: Precision and customization.

Temporal dynamics of land use land cover (LULC) changes and assessment of environmental and climatic parameters using remote sensing and GIS: A case study in Limboti Reservoir, Loha Taluka, Maharashtra, India

In this study, multispectral satellite data from Landsat 4-5 TM and Landsat 8 OLI/TIRS was used to analyse Land Use Land Cover (LULC) change detection and to retrieve environmental parameters. The LULC change detection was done between 2007 and 2021. This study used the supervised classification-maximum likelihood approach in ArcGIS 10.3 software to detect LULC in Loha Taluka, Maharashtra. The taluka was classified into four major LULC classes, viz. water, vegetation, settlement and barren-land. Changes in LULC directly or indirectly will also induce a change in the environmental parameters. Environmental parameters (water surface temperature, chlorophyll-a concentration and total suspended solids) were analysed for Limboti Reservoir. Data were predicted for next two years (2022 and 2023) using multiplicative seasonal decomposition and Holt-Winter’s multiplicative method and trends of each parameter were analysed using Mann-Kendall trend method. For both years, vegetative land was the most extensive LC in Loha Taluka, accounting for more than 60% of the total land area. However, throughout these years, urbanisation was rampant and vegetative land was converted to settlement. In these years, open water resources such as reservoirs, lakes and rivers covered a very small percentage of the total area, which is a serious threat to the ecosystem. As a result, proper water body management is essential; otherwise, these resources will be destroyed and will no longer be able to contribute to the area’s socioeconomic growth. Keywords: Change detection, Chlorophyll content, Land use land cover, Water quality, Water surface temperature

Analyzing Large-Scale Political Discussions on Twitter: The Use Case of the Greek Wiretapping Scandal (#ypoklopes)

In this paper, we study the Greek wiretappings scandal, which was revealed in 2022 and attracted significant attention from the press and citizens. Specifically, we propose a methodology for collecting data and analyzing patterns of online public discussions on Twitter. We apply our methodology to the Greek wiretappings use case and present findings related to the evolution of the discussion over time, its polarization, and the role of the Media. The methodology can be of wider use and replicated to other topics. Finally, we publicly provide an open dataset and online resources with the results.

Implementing national performance indicator ontology: A case study of Botswana's development agendas

This paper presents the National Performance Indicator Ontology (NPIOnto), a knowledge model designed for the semantic representation of national performance indicators (NPIs) and related performance variables to enhance the semantic capabilities of open data. The research addresses the lack of semantic representation for NPIs, particularly within Botswana's development agendas, which impedes the effective use, accessibility, and integration of performance data essential for monitoring and achieving sustainable development goals. NPIOnto was developed through five steps: discovering the ontology purpose, studying the development agenda knowledge domain, developing the conceptual knowledge model, formalizing the conceptual model, and evaluating the formal model's effectiveness in enhancing the semantic capabilities of open data resources. The evaluation, based on practical application in Botswana, demonstrated that NPIOnto significantly improves the accessibility, understandability, interoperability, integrability, and intelligibility of open data. Insights from the Botswana case study indicate that while NPIOnto is tailored to meet Botswana's development agenda needs, it can be adapted for use in other developing countries.

OPEN SOURCE TEXTBOOK AS A RESOURCE FOR THE TEACHING-LEARNING PROCESS OF ALGEBRA IN INITIAL TRAINING OF MATHEMATICS TEACHERS

Objective: To determine the implications of the use of open source text in the teaching-learning process of algebraic structures in the initial teacher training of the mathematics specialty in a state university in Peru. Theoretical Framework: The conceptual and epistemic bases of open learning are systematically addressed through interactive texts, as well as the aspects related to the teaching-learning process in university higher education. Method: The study has a mixed approach, pre-experimental design and correlational level, the target population was mathematics education students and a sample of 46 randomly chosen students, data collection is carried out through a diagnostic questionnaire, another multiple alternative and an interview, in the study sample classes are held through the open source book; then the learning achieved at the conceptual level is evaluated. procedural of algebraic structures. Results and Discussion: In this research it is evident that students did not know the open source online text for the study of mathematics, but they have skills in the use of digital technology; but with the use of the digital book they assimilate the concepts, perform demonstrations and solve problems efficiently, raising their level of motivation towards learning. Thus, the relevant use of open source books significantly improves learning and the development of mathematical competence in students. Research Implications: Strengthening of interactive and personalized activities for a comprehensive training of mathematics content mediated by digital technology, reinforcing in a sustained way the culture and mathematical competence of teachers in initial training. Originality/Value: Implementation of an innovative approach in pedagogical practice, through the use of open resources for the assimilation of mathematical concepts and procedures in a dynamic, efficient and effective way. The value of research is evidenced in the praxis of didactic strategies in the context of the digital age, oriented to the knowledge of algebraic structures by mathematics teachers.

3-generation family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions associated with autism: An open-source catalog of findings.

The relatively few conditions and family member types (e.g., sibling, parent) considered in investigations of family health history in autism spectrum disorder (ASD, or autism) limits understanding of the role of family history in autism etiology. For more comprehensive understanding and hypothesis-generation, we produced an open-source catalog of autism associations with family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions. All live births in Denmark, 1980-2012, of Denmark-born parents (1,697,231 births), and their 3-generation family members were followed through April 10, 2017 for each of 90 diagnoses (including autism), emigration or death. Adjusted hazard ratios (aHR) were estimated via Cox regression for each diagnosis-family member type combination, adjusting for birth year, sex, birth weight, gestational age, parental ages at birth, and number of family member types of index person; aHRs also calculated for sex-specific co-occurrence of each disorder. We obtained 6462 individual family history aHRS across autism overall (26,840 autistic persons; 1.6% of births), by sex, and considering intellectual disability (ID); and 350 individual co-occurrence aHRS. Results are cataloged in interactive heat maps and down-loadable data files: https://ncrr-au.shinyapps.io/asd-riskatlas/ and interactive graphic summaries: https://public.tableau.com/app/profile/diana.schendel/viz/ASDPlots_16918786403110/e-Figure5. While primarily for reference material or use in other studies (e.g., meta-analyses), results revealed considerable breadth and variation in magnitude of familial health history associations with autism by type of condition, family member type, sex of the family member, side of the family, sex of the index person, and ID status, indicative of diverse genetic, familial, and nongenetic autism etiologic pathways. Careful attention to sources of autism likelihood in family health history, aided by our open data resource, may accelerate understanding of factors underlying neurodiversity.

An Overview of Arabic Language Open Educational Resources (OER) for Primary and Secondary Education and Their Use in Offline Environments

Open educational resource (OER) initiatives have opened new avenues for educational opportunities, yet OER adoption levels globally remain low. Two significant obstacles to more widespread adoption of OER are the challenge of internet connectivity that nearly half the world’s population still faces, and the lack of locally-relevant (e.g. in terms of language and curricula) OER resources. This article’s contribution is twofold. First, it presents a qualitative landscape analysis of existing primary- and secondary-level Arabic-language digital OERs and of the initiatives that provide these resources. Second, it details applied research via a case study, wherein appropriate resources identified in the analysis were subsequently curated for inclusion in an offline digital library currently being used in schools in Northeast Syria that offers all Open resources. Results from the landscape analysis indicate a limited quantity of Arabic-language OER content available for primary and secondary education. Furthermore, multiple challenges hinder the adoption of OER in resource-constrained settings. Accordingly, recommendations are made that could help to improve these resources' ability to be used, particularly drawing from the article’s applied case study for examples. Given the case study’s application of providing locally-relevant OER resources in an offline setting, this article provides a real-world example of furthering open e-learning, despite infrastructural, linguistic, and socio-political challenges. As such, it advances research supporting innovative e-learning practice, and should be of interest for scholars and practitioners interested in furthering the adoption of open e-learning in low-resource settings globally.

Computational biomechanics for a standing human body: Modal analysis and simulation.

We develop computational mechanical modeling and methods for the analysis and simulation of the motions of a human body. This type of work is crucial in many aspects of human life, ranging from comfort in riding, the motion of aged persons, sports performance and injuries, and many ergonomic issues. A prevailing approach for human motion studies is through lumped parameter models containing discrete masses for the parts of the human body with empirically determined spring, mass, damping coefficients. Such models have been effective to some extent; however, a much more faithful modeling method is to model the human body as it is, namely, as a continuum. We present this approach, and for comparison, we choose two digital CAD models of mannequins for a standing human body, one from the versatile software package LS-DYNA and another from open resources with some of our own adaptations. Our basic view in this paper is to regard human motion as a perturbation and vibration from an equilibrium position which is upright standing. A linear elastodynamic model is chosen for modal analysis, but a full nonlinear viscoelastoplastic extension is possible for full-body simulation. The motion and vibration of these two mannequin models is analyzed by modal analysis, where the normal vibration modes are determined. LS-DYNA is used as the supercomputing and simulation platform. Four sets of low-frequency modes are tabulated, discussed, visualized, and compared. Higher frequency modes are also selectively displayed. We have found that these modes of motion and vibration form intrinsic basic modes of biomechanical motion of the human body. This view is supported by our finding of the upright walking motion as a low-frequency mode in modal analysis. Such a "walking mode" shows the in-phase and out-of-phase movements between the legs and arms on the left and right sides of a human body, implying that this walking motion is spontaneous, likely not requiring any directives from the brain. Dynamic motions of CAD mannequins are also simulated by drop tests for comparisons and the validity of the models is discussed through Fourier frequency analysis. All computed modes of motion are collected in several sets of video animations for ease of visualization. Samples of LS-DYNA computer codes are also included for possible use by other researchers.

AI Solutions for Accessible Education in Underserved Communities

This paper explores the application of artificial intelligence technology in the field of education, particularly how it can help bridge educational gaps in remote and underserved communities through scalable and accessible learning solutions. The aim of the study is to enhance educational equity and provide personalized learning experiences by utilizing AI technologies such as adaptive learning systems, language processing technologies, and data analytics. The paper analyzes these tools and discusses how they integrate with practical cases like mobile learning platforms, cloud infrastructure, open resources, and collaborative learning to massively distribute educational resources and address global educational inequalities. The research methods include case studies and data analysis, with results indicating that these technologies significantly improve learning efficiency and engagement among students in remote areas. Ultimately, the paper demonstrates the potential of artificial intelligence in promoting global educational equity and offers suggestions for the future development of educational technology. This work is of significant importance to the field of educational technology, providing innovative perspectives and practical solutions for addressing disparities in educational resources.

Brain Charts for the Rhesus Macaque Lifespan.

Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.

Open Resources for Biology Education (ORBE): a resource collection.

In undergraduate life sciences education, open educational resources (OERs) increase accessibility and retention for students, reduce costs, and save instructors time and effort. Despite increasing awareness and utilization of these resources, OERs are not centrally located, and many undergraduate instructors describe challenges in locating relevant materials for use in their classes. To address this challenge, we have designed a resource collection (referred to as Open Resources for Biology Education, ORBE) with 89 unique resources that are primarily relevant to undergraduate life sciences education. To identify the resources in ORBE, we asked undergraduate life sciences instructors to list what OERs they use in their teaching and curated their responses. Here, we summarize the contents of the ORBE and describe how educators can use this resource as a tool to identify suitable materials to use in their classroom context. By highlighting the breadth of unique resources openly available for undergraduate biology education, we intend for the ORBE to increase instructors' awareness and use of OERs.

The architecture of the system of intelligent analysis of competencies for updating university educational programs

The problem of updating educational programs and educational content is closely related to the need to adapt them to the changing conditions of regional labor markets. The solution to the problem is achieved through the collection and analysis of data on the competence requirements of employers for the qualifications of specialists (the data itself can be extracted from job advertisements on open resources on the Internet). The article presents a method of using search robots and text data processing modules to obtain formalized descriptions of competence requirements and compare them by degree of similarity with competence descriptions from educational programs. For a comparative analysis of competency requirements, a clustering method was developed using fuzzy logic and a neural network. The architecture of the collection and intelligent analysis system includes search crawlers, a module for parsing text data with cleaning from information noise, a data consolidation module, a keyword dictionary generation module, a module for synthesizing competency vectors, a clustering module, a distributed registry of formalized descriptions of competencies, etc. The results of the comparative analysis are crucial for assessing the compliance of competencies of specialists trained in regional universities with the requirements of employers in the regions. The assessment allows to develop recommendations for updating educational programs and educational content of an educational institution, as well as to carry out adaptive adjustment of information and educational environment components of higher educational institutions.

Education in the open: Building a network for social action

This paper introduces Fast Food da Politica (FFDP) as a case study of a learning network designed to promote social action in a developing country. Our focus is on exploring FFDP design elements, such as those related to tools, tasks and social organization, and the connections between these elements and valued learning activity. FFDP cleverly (re)purposes popular (board) games as pedagogical tools, which are then customised for the teaching and learning of the mechanisms and functioning of Brazilian political structures. FFDP has taken their political games to game-playing sessions across the country in varied venues – including schools, government organisations, and open sessions at market-street events and public protests. Their games are shared as open learning resources through blueprints and manuals that explain the many ways a game can be played, and which are easily downloadable through their website. FFDP also encourages game users (educators and learners) to come up with and share their own game-playing ideas for reuse. As a result, FFDP has built a repository of games that is constantly evolving, as new ways of using their open resources are captured and packaged for sharing and reuse by others. As a not-for-profit organisation, FFDP has been successfully relying on social media and crowdsourced funding to survive. In this paper, we draw on the ACAD Wireframe to explore the alignment of this network’s design elements at the micro and meso levels, focusing on the ways FFDP combines a strategic educational vision deeply grounded on action for social change, with a curriculum that emphasizes gaming elements and promotes the physicality of materials in learning. At the micro level, the case study examines how the quality of materials support the development of educational innovation, while at the meso level this organization, driven by young women, is building-up a learning network for social action, empowering children, youth and adults to learn about the mechanisms of politics and their civil rights, within the Brazilian context. Overall, this paper offers an inspiring example of a productive learning network in action, where participation and co-creation are fostered through connections between a network of people, ideas, digital and material elements.

A Case for the Use of Open Data as a Tool to Incorporate Socioscientific Topics into Neuroscience Education.

Education scholars have called for an increased focus on developing curricula based on culturally relevant pedagogy (Ladson-Billings, 1995). A key tenet of Ladson-Billings' (1995; 2014) theory of culturally relevant pedagogy is the development of students' sociopolitical consciousness, whereby students feel empowered and encouraged to evaluate and solve real-world interdisciplinary problems. Here, we propose that open science datasets could serve as a valuable tool for neuroscience educators to foster their students' sociopolitical consciousness. Using the open data available through the Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) as a case study, this article will explore how open science can be leveraged as a tool to encourage socioscientific thinking amongst neuroscience students. We overview a collection of lessons created by the Allen Institute's Education & Engagement team that provides a scaffolded exploration of an open science resource through a socioscientific lens. We supplement our discussion of the lessons with feedback from students who completed the lessons during a day-long workshop hosted at the Allen Institute in Seattle, WA. We conclude by reflecting on the future role this type of interdisciplinary, open science-based approach to curricula could have across neuroscience education more broadly.

BBSdb, an open resource for bacterial biofilm-associated proteins.

Bacterial biofilms are organized heterogeneous assemblages of microbial cells encased within a self-produced matrix of exopolysaccharides, extracellular DNA and proteins. Over the last decade, more and more biofilm-associated proteins have been discovered and investigated. Furthermore, omics techniques such as transcriptomes, proteomes also play important roles in identifying new biofilm-associated genes or proteins. However, those important data have been uploaded separately to various databases, which creates obstacles for biofilm researchers to have a comprehensive access to these data. In this work, we constructed BBSdb, a state-of-the-art open resource of bacterial biofilm-associated protein. It includes 48 different bacteria species, 105 transcriptome datasets, 21 proteome datasets, 1205 experimental samples, 57,823 differentially expressed genes (DEGs), 13,605 differentially expressed proteins (DEPs), 1,930 'Top 5% differentially expressed genes', 444 'Threshold-based DEGs' and a predictor for prediction of biofilm-associated protein. In addition, 1,781 biofilm-associated proteins, including annotation and sequences, were extracted from 942 articles and public databases via text-mining analysis. We used E. coli as an example to represent how to explore potential biofilm-associated proteins in bacteria. We believe that this study will be of broad interest to researchers in field of bacteria, especially biofilms, which are involved in bacterial growth, pathogenicity, and drug resistance. Availability and implementation: The BBSdb is freely available at http://124.222.145.44/#!/.

An Efficient Certificateless Anonymous Signcryption Scheme for WBAN.

A Wireless Body Area Network (WBAN), introduced into the healthcare sector to improve patient care and enhance the efficiency of medical services, also brings the risk of the leakage of patients' privacy. Therefore, maintaining the communication security of patients' data has never been more important. However, WBAN faces issues such as open medium channels, resource constraints, and lack of infrastructure, which makes the task of designing a secure and economical communication scheme suitable for WBAN particularly challenging. Signcryption has garnered attention as a solution suitable for resource-constrained devices, offering a combination of authentication and confidentiality with low computational demands. Although the advantages offered by existing certificateless signcryption schemes are notable, most of them only have proven security within the random oracle model (ROM), lack public ciphertext authenticity, and have high computational overheads. To overcome these issues, we propose a certificateless anonymous signcryption (CL-ASC) scheme suitable for WBAN, featuring anonymity of the signcrypter, public verifiability, and public ciphertext authenticity. We prove its security in the standard model, including indistinguishability, unforgeability, anonymity of the signcrypter, and identity identifiability, and demonstrate its superiority over relevant schemes in terms of security, computational overheads, and storage costs.