Knowledge Of Processes Research Articles

Methodological Features of the Integration of Biological Knowledge and Ethical Concepts in the Educational Process

Methodological Features of the Integration of Biological Knowledge and Ethical Concepts in the Educational Process

Software Process Improvement by Managing Situational Method Engineering Knowledge

Organizational processes have been recognized as valuable knowledge assets. Situational Method Engineering (SME) processes are particularly valuable as they are used for engineering other processes: SME processes help construct bespoke Software Development Methodologies (SDMs) for specific software-engineering project situations. Every SDM has a Software Development Process (SDP) at its heart, which specifies the activities that should be performed throughout the project, the products that should be produced, and the people that should be involved. Existing SME methods suffer from certain weaknesses that are rooted in loss of knowledge within their processes; for instance, the method engineers' experience, which is a kind of tacit knowledge, is not properly captured and utilized in these processes. Managing SME process knowledge helps alleviate these weaknesses through reusing the software developers' experience and maintaining the method engineers' knowledge. We propose an evaluation framework that can be used for assessing an SME method's ability to manage process knowledge. We also provide a model that guides the improvement of existing SME methods in their support for Knowledge Management (KM), and also helps engineer new SME methods that provide adequate KM support. We have assessed the applicability of the proposed evaluation framework and improvement model by using them to enhance eight prominent SME methods, and also by applying them to four industrial case studies.

A multi-method approach to drafting candidate entrustable professional activities for a general internal medicine residency programme.

Entrustable professional activities (EPAs) are units of concrete daily clinical tasks that trainee physicians should be able to handle with increasing autonomy during their postgraduate training. EPAs are gaining international recognition as an essential component of competency-based medical training programmes. The process of developing EPAs for a nationwide training programme is complex and requires an in-depth understanding of EPAs as a concept and good knowledge of appropriate development processes. This article provides a detailed description of the methodology and results of a multi-step approach for developing a list of candidate EPAs for Switzerland's postgraduate training programme in general internal medicine (GIM). We took a multi-step approach including a systematic review of international literature, four national focus groups, a national consensus process using a RAND appropriateness method, and a quality check of the selected candidate EPAs using EQual criteria. These steps generated a final list of 247 candidate EPAs in general internal medicine that were submitted for the national consensus process. After two rounds of rating, experts agreed on the appropriateness for general internal medicine postgraduate training of 225 candidate EPAs. Twenty-two were deemed inappropriate, and disagreement persisted only for two EPAs. This multi-step programme is one of the few describing in detail the process of developing a list of EPAs and providing evidence of validity at each step. The clinical breadth of our candidate EPAs, together with the detailed description of our methodology, could serve as a useful starting point from which medical education specialists or clinicians could develop or revise applicable lists of EPAs, particularly for postgraduate training programmes in either general internal medicine or family medicine.

Status and future developments for downstream processing of biological products: Perspectives from the Recovery XIX yield roundtable discussions.

Governments and biopharmaceutical organizations aggressively leveraged expeditious communication capabilities, decision models, and global strategies to make a COVID-19 vaccine happen within a period of 12 months. This was an unusual effort and cannot be transferred to normal times. However, this focus on a single vaccine has also led to other treatments and drug developments being sidelined. Society expects the pharmaceutical industry to provide an uninterrupted supply of medicines. However, it is often overlooked how complex the manufacture of these compounds is and what logistics are required, not to mention the time needed to develop new drugs. The overarching theme, therefore, is patient access and how we can help ensure access and extend it to low- and middle-income countries. Despite unceasing efforts to make medications available to all patient populations, this must never be done at the expense of patient safety. A major fraction of the costs in biopharmaceutical manufacturing are for drug discovery, process development, and clinical studies. Infrastructure costs are very difficult to quantify because they often depend on whether a greenfield facility or an existing, depreciated facility is used or adapted for a new product. To accelerate process development concepts of platform process and prior knowledge are increasingly leveraged. While more traditional protein therapeutics continue to dominate the field, we are also experiencing the exciting emergence and evolution of other therapeutic formats (bispecifics, tetravalent mAbs, antibody-drug conjugates, enzymes, peptides, etc.) that offer unique treatment options for patients. Protein modalities are still dominant, but new modalities are being developed that can be learned from including advanced therapeutics-like cell and gene therapies. The industry must develop a model-based strategy for process development and technologies such as continuous integrated biomanufacturing must be adopted. The overall conclusion is that the pandemic pace was unsustainable, focused on vaccine delivery at the expense of other modalities/disease targets, and had implications for professional and personal life (work-life balance). Routinely reducing development time from 10 years to 1 year is nearly impossible to achieve. Environmental aspects of sustainable downstream processing are also described.

SPARQL Optimization Using Re-ordering Joining Patterns with Surrogate Key Concept and Subset Patterns

Semantic web data resides on the web in the form of knowledge graphs known as RDF graphs and searching around the web has been always a crucial task. For the data retrieval of RDF data of the semantic web, SPARQL query language has been used which in turn is based on triple patterns and joins. Optimization of SPARQL query has been a problematic concern for decades due to the large amount of triple patterns associated with RDF data. Although several researchers have put a lot of effort into the optimization of SPARQL query, it is difficult to understand the concept from scratch due to its diversified nature. This paper analyses various optimization techniques for the SPARQL query used with the semantic web to process knowledge graphs. These techniques include join-based, heuristic-based, rule-based, and indexing-based approaches for optimization. This paper will help researchers in this domain to easily get into the core concept of SPARQL execution along with various optimization approaches used for query processing, which can help in various other domains like linked open data and information retrieval. In this paper, an optimization algorithm HSOA (hybrid SPARQL optimization algorithm) has been proposed, which comprises the features of index-based, cost-based, and triple reordering-based optimization approaches. The proposed hybrid algorithm has been designed specifically for n-triple RDF data, which comprises subset patterns, and surrogate key concepts. The results produced by the proposed algorithm are encouraging and have also been tested and compared with the benchmark dataset and SPARQL queries like LUBM, BSBM, and SP2Bench.

Homeostasis imbalance process ontology: a study on COVID-19 infectious processes.

One significant challenge in addressing the coronavirus disease 2019 (COVID-19) pandemic is to grasp a comprehensive picture of its infectious mechanisms. We urgently need a consistent framework to capture the intricacies of its complicated viral infectious processes and diverse symptoms. We systematized COVID-19 infectious processes through an ontological approach and provided a unified description framework of causal relationships from the early infectious stage to severe clinical manifestations based on the homeostasis imbalance process ontology (HoIP). HoIP covers a broad range of processes in the body, ranging from normal to abnormal. Moreover, our imbalance model enabled us to distinguish viral functional demands from immune defense processes, thereby supporting the development of new drugs, and our research demonstrates how ontological reasoning contributes to the identification of patients at severe risk. The HoIP organises knowledge of COVID-19 infectious processes and related entities, such as molecules, drugs, and symptoms, with a consistent descriptive framework. HoIP is expected to harmonise the description of various heterogeneous processes and improve the interoperability of COVID-19 knowledge through the COVID-19 ontology harmonisation working group.

Empowering Unskilled Production Systems Consultants through On-the-Job Training Support: A Digital Triplet Approach

This study aims to experimentally confirm whether knowledge that has been challenging to transfer through traditional on-the-job training (OJT) can be effectively transferred by introducing a formalized OJT approach that describes the improvement process knowledge of skilled production systems consultants, facilitating imitation by unskilled consultants. We adopted the Digital Triplet (D3) concept, an extension of the authors’ digital twin framework to intelligent activities, aligning with our study objectives. Recognizing the difficulty and inadequacy of knowledge transfer in production systems consulting OJT, we propose an OJT support method integrating a decision-making modeling approach for skilled consultants’ processes based on the Generalized Production Systems Consulting Process Model (GCPM) from prior literature into traditional OJT methods involving self-learning and direct instruction. This method enables the construction of a domain-specific GCPM, formalizing the improvement process flow implemented by skilled consultants and linking it to production improvement expertise and tools. In a case study focused on energy-saving improvement, we constructed and tested a domain-specific GCPM’s efficacy in facilitating the transfer of difficult-to-transfer knowledge. The results indicate that domain-specific GCPM facilitates such knowledge transfer, including specialized improvement, knowledge utilization, rationale, and adaptation to specific cases.

Links between parental monitoring and parent-adolescent conflict: A multimodal test of bidirectional relations.

During adolescence, youth increase in both independence and conflict with parents. Parents vary in how much they know about their adolescents' whereabouts and activities and how they acquire this information (i.e., the sources of what parents know). We probed how parental knowledge of adolescents' whereabouts and activities-and their information sources-relates to (a) domains of parent-adolescent conflict (fighting about, or having different beliefs about, daily life topics) and (b) parent and adolescent attachment-related behavior during a conflict discussion task. Using the Actor-Partner Interdependence Model, we tested links between parental knowledge and its sources and conflict processes. Eighty-seven adolescents (Mage = 15.18; 55% female) and parents completed surveys about parental knowledge and its sources (i.e., parental solicitation of adolescents' activities, adolescent disclosure to parents about their activities) and separate interviews on conflict domains. A subset of parent-adolescent dyads (n = 65) interacted for 5 min about an adolescent-identified conflict topic. Different beliefs about daily life topics related to parental knowledge: parents' reports of greater different beliefs about daily life topics predicted less knowledge of adolescents' activities/whereabouts, solicitation, and disclosure, for both parent and adolescent reports of these domains. For adolescents, greater different beliefs related to less solicitation and disclosure. Only adolescent reports of parental knowledge, solicitation, and disclosure predicted attachment-related behaviors both dyad members displayed during the conflict discussion task. Findings reveal links between parental knowledge of adolescents' activities and conflict processes and demonstrate dyadic interdependence between parental knowledge of adolescents' activities and conflict processes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Aerosols in the central Arctic cryosphere: satellite and model integrated insights during Arctic spring and summer

Abstract. The central Arctic cryosphere is influenced by the Arctic amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss, and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) datasets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW-retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterized by long-range transport of anthropogenic aerosols in the Arctic, GC underestimates the AOD in the vicinity of Alaska in comparison with AEROSNOW retrieval. At the same time, it overestimates the AOD along the Bering Strait, northern Europe, and the Siberian central Arctic sea-ice regions, with differences of −12.3 % and 21.7 %, respectively. By contrast, GC consistently underestimates AOD compared with AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea-ice region, where it is −10.6 %. Conversely, GC tends to overestimate AOD along the Siberian and Greenland marginal sea-ice zones by 19.5 % but underestimates AOD along the Canadian Archipelago by −9.3 %. The differences in summer AOD between AEROSNOW data products and GC-simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models in order to constrain its effects on cloud condensation nuclei, on ice nucleating particles, and on the radiation budget over the central Arctic sea ice during the developing AA period.

Negative rivalry in use: toward a knowledge-sharing perspective in the digital economy era

Purpose This study aims to introduce and prove the existence of negative rivalry in use, which should be an integral part of goods taxonomy, from the perspective of knowledge sharing and further present the critical role of knowledge sharing in the digital economy era by reviewing the literature, theoretical analysis and real-world cases. It also aims to open a new door for re-recognizing knowledge sharing through an interdisciplinary framework. Design/methodology/approach This study proves the existence of negative rivalry through both theoretical analysis (4-E model) and real-world cases, especially the cases of Tesla and ChatGPT, and puts up new reasons for knowledge sharing in the era of digital economy through interdisciplinary methods. Findings The authors find out that there are many new phenomena beyond the spectrum of current goods taxonomy, especially beyond the priori understanding of rivalry in use. Digital platforms such as ChatGPT should have been “used up” in no time, for they have attracted so massive users according to (positive) rivalry in use, or should have been unchanged at most according to non-rivalry in use. But what we see is their rapid upgrading with the help of billions of users. The reason is that negative rivalry in use has completely been neglected. The authors find out that the process of knowledge sharing unveils the unrecognized attribute of rivalry in use, i.e. negative rivalry in use, which serves as the fundamental driving force of the breathtaking growth of all kinds of digital platforms. Originality/value This study originally put up a 4-E model of goods’ rivalry in use, the brand new term, i.e. negative rivalry in use, and proves its existence and working mechanism from the perspective of knowledge sharing. With the introduction of negative rivalry in use, the traditional four-type goods classification model is extended into a six-type model, which may be a sound marginal contribution, to the best of the authors’ knowledge. The study may reshape people’s mindsets on goods usage, especially knowledge management, into a more open-sharing model because it shows that there is very likely a positive-sum game instead of a zero- or negative-sum game for shared knowledge per se and its platform in the process of knowledge sharing in the era of digital economy.

Analyzing the Role of Problem Finding in the Creative Design with Regard to the Effect of Prior Knowledge in the Design Process

Statement of the problem. Despite many researches in the field of design process, there is still mostly the main reliance of the design process on ‘solving the problem’, and designers are evaluated based on their ability to provide the solution. In fact, creativity is defined in ‘quality of the solution’. Results. However, what is less discussed is the ‘problem-finding’. considering that the design problem – unlike problems in other fields – is vague and ill-defined, and is not predetermined; Also, as prior knowledge of the designer is so effective in all stages of the design process and can hinder creativity, due to the desiner’s reference to his own previous experience, so problem finding should be considered as one of the important abilities of a designer. In this regard, students should also be taught to be creative in the problem-finding phase, and teachers should not provide the design problem in a completely defined and fixed way. Conclusions. This research believes that creativity does not occur only in the ideation phase, and the problem finding should be considered as an integral and essential part of the creative design process, whether in professional contexts or education. If the designer can find a novel problem, or see the existing problems from a new angle, it can be expected that there will be no fixation, and creativity will happen in the design.

Determinants of bacterial survival and proliferation in blood.

Bloodstream infection is a major public health concern associated with high mortality and high healthcare costs worldwide. Bacteremia can trigger fatal sepsis whose prevention, diagnosis and management have been recognized as a global health priority by the World Health Organization. Additionally, infection control is increasingly threatened by antimicrobial resistance, which is the focus of global action plans in the framework of a One Health response. In-depth knowledge of the infection process is needed to develop efficient preventive and therapeutic measures. The pathogenesis of bloodstream infection is a dynamic process resulting from the invasion of the vascular system by bacteria, which finely regulate their metabolic pathways and virulence factors to overcome the blood immune defenses and proliferate. In this review, we highlight our current understanding of determinants of bacterial survival and proliferation in the bloodstream and discuss their interactions with the molecular and cellular components of blood.

Inclusive peer review: Reflections on an adapted citizens' jury with people with learning disabilities

AbstractBackgroundInclusive research is widely accepted as an essential part of the process to democratise knowledge creation and dissemination. However, while peer review is an important part of academic publishing, the potential to include people with learning disabilities in this element of the research process has not previously been explored using a deliberative approach.MethodsAccessibility adaptations were made to the citizens' jury approach enabling people with learning disabilities to participate. Sixteen adults with mild to moderate learning disabilities were recruited to participate in the adapted citizens' jury. Jury members took part in capacity‐building workshops to develop their knowledge of research and research processes. Six expert witnesses presented evidence to the citizens' jury and were questioned on aspects of inclusive research, representation, peer review and academic publishing processes. Facilitators supported citizens' jury members to reflect on the evidence presented and to develop recommendations for inclusive peer review.FindingsThe citizens' jury was an effective inclusive research approach in this case. Jurors made recommendations related to the question of inclusive peer review: inclusive reviews should be done by groups rather than individuals; the research under review must be in accessible formats and on relevant topics; reviewers need sufficient time to conduct reviews; and diverse groups of people with learning disabilities should be involved.ConclusionsPeople with learning disabilities appreciate the importance of peer review but do not necessarily want to participate in it. This jury suggested creative approaches to disseminating, reviewing and engaging with research, including building more opportunities for dialogue between researchers and self‐advocates. The adapted citizens' jury was a novel and effective method of supporting deliberation on this topic but other approaches to including the views and experiences of those with more severe learning disabilities should be explored.

Aplikasi Survei Kepuasan Peserta Diklat Berbasis Mobile Untuk Meningkatkan Pelayanan Diklat

Balai Diklat Keuangan Medan There is an Organizing and Learning sector which is tasked with carrying out learning related to State finances, facilitating the implementation of the Learning system and facilitating technical support for implementing learning needs analysis, learning evaluation, certification and competency tests as well as providing assistance services for implementing knowledge processes and learning organizations in the work area of the Financial Education and Training Center. This research was created to create a mobile-based training participant satisfaction survey system to improve training services. The aim is to improve training services that can be accessed easily by training participants. With the survey application, participant satisfaction data can be accessed and analyzed in real-time and this application makes the work of organizers easier in calculating satisfaction surveys and can provide data to the head of the Financial Training Center quickly. By using the waterfall method with Likert Scale calculations, this research produces an efficient information system through the stages of needs analysis, design, implementation, testing, maintenance and Likert scale calculations. The results obtained from this research are that the participant satisfaction survey application can make it easier for organizers to calculate survey results and make it easier for offices to improve office quality quickly.

Machine-Learning-Based Kinetic-Free Hybrid Gray-Box Model to Predict Sulfuric-Acid-Catalyzed Esterification Reaction.

The sulfuric-acid-catalyzed esterification reaction of 2-butanol and propionic anhydride is a vital industrial process. In this paper, several experiments are conducted via reaction calorimetry to validate that both sulfuric and propionic acids have discernible catalytic effects on the reaction. This finding complicates the accurate description of the reaction kinetics through traditional methods. So this paper turns to a kinetic-free black-box model, Gaussian process regression (GPR) model via 24 experiments, as a more adaptable approach. Besides, the best GPR model is combined with traditional heat balance model to generate a hybrid gray-box model, which can give complete knowledge of reaction process. The hybrid gray-box model finally achieves maximum root-mean-square error (RMSE) of 0.0069 for conversion, 0.6535 for temperature, and 10.6087 for heat flow rate, underscoring its pretty good predictive ability.

Knowledge management drivers and its results: a quantitative study in a public higher education institution

PurposeThe purpose of this study was to evaluate the influence of knowledge management (KM) drivers on perceived KM results in a public higher education institution. A structured theoretical model based on leadership, people, processes, knowledge processes, technology, learning and KM results was developed and tested.Design/methodology/approachA survey was conducted with the employees of a public higher education institution where an administrative reform was initiated. A valid sample of 257 respondents was obtained. The data were obtained from the application of a structured questionnaire based on the KM drivers and their results. A five-point Likert-type scale was used to measure respondents' answers. The main data analysis technique was structural equation modeling.FindingsThe results indicate knowledge processes, leadership and people factors have a positive and significant impact on KM results. On the other hand, organizational processes, technology and learning factors were not significant. However, the service length of servants in the institution influences the perception of knowledge drivers.Practical implicationsPublic institutions should be attentive to people with more time of service because they may have difficulties with technological advances, reorganization of processes and adaptation to new ways of sharing knowledge.Originality/valueThis study advances on the analysis of KM results in the public sector and tests the moderation effect of time of service.

A semantic reasoning-based emergency rescue assistant decision method for maritime accidents involving chemicals

Maritime accidents involving chemicals (MAICs) constitute a unique category of marine emergency characterized by low frequency, high risk, and complex disposal challenges. These accidents often entail fires, explosions, and pollutant leakage, demanding effective emergency responses. The success of MAICs rescue operations relies on multiple factors, encompassing the structural features of the involved vessel, personnel, cargo, marine environment, and the availability of resources and response procedures. Proficiency in various professional fields, including ship transportation, chemistry, firefighting, and environmental science, is essential for informed decision-making. This paper addresses the need for a standardized description of knowledge in the MAICs emergency rescue decision-making process, aiming to enhance practical application frequency and decision-making efficiency. Employing ontology theory, the approach involves structurally modeling the knowledge of MAICs emergency rescue, constructing an ontology model, and establishing a decision rule base. Validating the proposed method, the emergency response to the “Longqing 1″ accident is examined as a case study, illustrating its potential for supporting MAICs emergency rescue decision-making. The application of ontology theory in this context holds both theoretical and practical significance. It facilitates the sharing, reuse, and expansion of knowledge in the emergency rescue field, providing crucial technical support for intelligent decision-making in MAICs emergencies.

Feature-weight and cluster-weight learning in fuzzy c-means method for semi-supervised clustering

Semi-supervised clustering aims to guide the clustering by utilizing auxiliary information about the class labels. Among the semi-supervised clustering categories, the constraint-based approach uses the available pairwise constraints in some steps of the clustering procedure, usually by adding new terms to the objective function. Considering this category, Semi-supervised FCM (SSFCM) is a semi-supervised version of the fuzzy c-means algorithm, which takes advantage of fuzzy logic and auxiliary class distribution knowledge. Despite the performance enhancement caused by incorporating this extra knowledge in the clustering process, semi-supervised fuzzy approaches still suffer from some problems. All the data attributes in the feature space are assumed to have equal importance in the cluster formation, while some features may be more informative than others. Thus the feature importance issue is not addressed in the semi-supervised category. This paper proposes a novel Semi-Supervised Fuzzy c-means approach, which is designed based on Feature-Weight, and Cluster-Weight learning, named SSFCM-FWCW. Inspired by the SSFCM, a fuzzy objective function is presented, which is composed of (1) a semi-supervised term representing the external class knowledge; (2) a feature weighting; and (3) a cluster weighting. Both feature weights and cluster weights are determined adaptively during the clustering. Considering these two techniques leads to insensitivity to the initial center selection, insensitivity to noise, and consequently helps to form an optimal clustering structure. Experimental comparisons are carried out on several benchmark datasets to evaluate the proposed approach's performance, and promising results are achieved. The Matlab implementation source code of the proposed method is publicly accessible at https://github.com/Amin-Golzari-Oskouei/SSFCM-FWCW.

Scales of plant stewardship in the precontact Pacific Northwest, USA

Numerous oral histories and substantial ethnographic evidence illustrate how plant species, communities, and even landscapes were extensively managed and cared for by ancestral communities in the Pacific Northwest. Camas ( Camassia spp.) is one such cultural keystone plant, common from the Pacific Ocean to the Rocky Mountains, with numerous records describing its role as a staple food for many Northwest peoples. Supporting deep time archeological evidence for such management or stewardship practices, however, has remained elusive. In this paper we analyze archived collections of archeological camas bulbs from 11 sites across the Willamette Valley, Oregon to demonstrate people began preparing camas within earth ovens by approximately 8000 calendar years before present and deliberately harvesting sexually mature camas plants circa 3500 calendar years before present. We compare these findings with climatological, palynological, and fire history reconstructions to discuss stewardship strategies for camas and associated plant communities through time at the population, community, and landscape levels. These findings confirm and expand upon Indigenous knowledges as well as offer time-tested methods for cultural keystone conservationists seeking to revitalize traditional plant stewardship practices throughout this region and beyond. This “camas case study” also offers another example of a human-plant symbiotic relationship, expanding our knowledge of plant food pathways, processes, and mutualisms.

Anaerobic biodegradation of perfluorooctane sulfonate (PFOS) and microbial community composition in soil amended with a dechlorinating culture and chlorinated solvents

Perfluorooctane sulfonate (PFOS), one of the most frequently detected per- and polyfluoroalkyl substances (PFAS) occurring in soil, surface water, and groundwater near sites contaminated with aqueous film-forming foam (AFFF), has proven to be recalcitrant to many destructive remedies, including chemical oxidation. We investigated the potential to utilize microbially mediated reduction (bioreduction) to degrade PFOS and other PFAS through addition of a known dehalogenating culture, WBC-2, to soil obtained from an AFFF-contaminated site. A substantial decrease in total mass of PFOS (soil and water) was observed in microcosms amended with WBC-2 and chlorinated volatile organic compound (cVOC) co-contaminants — 46.4 ± 11.0 % removal of PFOS over the 45-day experiment. In contrast, perfluorooctanoate (PFOA) and 6:2 fluorotelomer sulfonate (6:2 FTS) concentrations did not decrease in the same microcosms. The low or non-detectable concentrations of potential metabolites in full PFAS analyses, including after application of the total oxidizable precursor assay, indicated that defluorination occurred to non-fluorinated compounds or ultrashort-chain PFAS. Nevertheless, additional research on the metabolites and degradation pathways is needed. Population abundances of known dehalorespirers did not change with PFOS removal during the experiment, making their association with PFOS removal unclear. An increased abundance of sulfate reducers in the genus Desulfosporosinus (Firmicutes) and Sulfurospirillum (Campilobacterota) was observed with PFOS removal, most likely linked to initiation of biodegradation by desulfonation. These results have important implications for development of in situ bioremediation methods for PFAS and advancing knowledge of natural attenuation processes.