Knowledge Of Processes Research Articles

Network and structural analysis of quail mucins with expression pattern of mucin 1 and mucin 4 in the intestines of the Iraqi common quail (Coturnix coturnix).

In avian and other species, mucins (MUCs) play a crucial role in the gastrointestinal tract (GIT), and constitute a large group of O-glycosylated glycoproteins, are glycoconjugate proteins. MUCs present in two forms: (1) membrane-attached on cell surfaces to repel external threats and (2) detachable, gel-forming proteins in the soluble form. In quail GIT, the specific types of MUCs that are expressed remain largely unknown. We investigated the expression of MUC1 and MUC4 MUCs in the GIT of Iraqi common quails and conducted network and structural analyses of all known MUC types across quail breeds. Histological and gene expression analyses of MUC1 and MUC4 were conducted using fresh small intestine and large intestine samples from 10 quails. Using the STRING Database, Chimera software, and PrankWeb-ligand binding site prediction tool, network and structural analyses of all reported types of quail MUCs were conducted. Most intestinal MUCs in quails were acidic, with few neutral MUCs detectable through Alcian blue and periodic acid-schiff stains. Acidic MUCs were more expressed in the duodenum, ileum, cecum, and colon, whereas neutral MUCs were more expressed in the jejunum. MUC1 and MUC4 messenger RNA expression was significantly higher in the jejunum and colon than in the duodenum and ileum. The analysis of the network revealed that MUC 1, 15, 16, and 24 formed homologous networks, while MUC 2, 4, 5, and 6 formed heterologous networks. Specific MUC combinations, including MUC5A-MUC6, MUC5A-MUC5B, and MUC5B-MUC6, show higher intermolecular hydrogen bond formation affinity. MUC15, MUC16, and MUC24 showed minimal interaction with other MUC types. Among the analyzed MUCs, MUC5B, and MUC6 had the highest probability for binding, while MUC2, MUC4, and MUC5A showed lower probabilities despite greater numbers of binding sites. This study's results offer significant insights into quails' MUCs' composition, expression, network interactions, and binding sites, advancing knowledge of MUC-related processes in gastrointestinal physiology and their potential connection to gastrointestinal diseases.

Unlocking Innovation from Within: The Power of Tacit Knowledge and Change Adaptability in Indonesian Internal Organisational Innovation Processes

Abstract Research purpose. The study examines how tacit knowledge sharing affects internal organisational innovation by exploring change adaptability as a mediator. Hence, it tries to fill this gap and further explain the role played by tacit knowledge sharing in the entire knowledge management process. Given the mediating effect of change adaptability, this study aims to provide new insight into effective management and sharing tacit knowledge among organisations to improve their innovation processes. Design / Methodology / Approach. This study adopted a quantitative cross-sectional survey design, with Partial Least Squares Structural Equation Modeling (PLS-SEM) as the main statistical technique. Such a method is best applied in this research, where one confirms hypotheses and the relationship between observed and latent variables. The samples were selected based on judgmental non-probability and purposive sampling approaches. The SEM was used in data analysis. It contributed to understanding the relationship of the variables, such as sharing tacit knowledge, change adaptability, and internal organisational innovation. Findings. The study proved that tacit knowledge sharing is highly significant in internal organisational innovation, mediated by change adaptability. Direct effect: Tacit knowledge sharing directly affects the organisational ability to adapt to change and internal innovativeness, thus underpinning its basis. Change adaptability mediates the effect of tacit knowledge sharing on internal organisational innovation, which influences innovation outcomes. Path coefficient analysis confirms the positive influence of tacit knowledge sharing on adaptability to change and innovation. Indirect Effects: Empirical examination has proved the significant mediating effect of change adaptability in leveraging tacit knowledge for innovation. These results suggest that the strategic value of tacit knowledge and adaptability, which will drive sustainable innovation within organisations and support their integration within strategic frameworks, is fully justified. Originality / Value / Practical implications. This is a new model used for the first time to suggest novel contributions and usefulness in understanding the relationship among sharing of tacit knowledge, change adaptability, and innovation at the internal level of the organisation. Tacit knowledge sharing, combined with change adaptability, is a model for internal organisational innovation. Therefore, it fills an important gap in the existing literature: the quantification of adaptability in mediating the effect of tacit knowledge on innovation. The results of this study will provide empirical validation of these relationships and further contribute to the knowledge in practice, particularly by emphasising the mediating role of change adaptability, which has been relatively underexplored. Practically, tacit knowledge sharing within adaptive organisational environments is thus an important call towards effective adaptation to change. The level of enhancement of these dimensions as core competencies through strategies could make a difference in the success of businesses. The importance of adaptability has to be emphasised by training programs and management practices that would provide the same skills. Other important avenues include those that work towards cultivating supportive organisational cultures that would facilitate tacit knowledge exchange, support employee interaction and informal knowledge exchange, and measures to reward innovation efforts. Investment in human resources practices that encourage learning and adaptability will continue to encourage knowledge sharing and innovation, including improving training programs, offering mentorship opportunities, and developing performance management systems that support and reward behaviours around innovation. This study contributes to the literature with a developed framework and empirical examination of the interrelations between tacit knowledge sharing, change adaptability, and innovation. It provides practical strategies that can be of value to the organisation in enhancing innovation capabilities through knowledge management.

Paths to improve voluntary blood donation in mixed public/private blood donation systems such as in Lebanon?

BackgroundThe World Health Organization advocates for the achievement of 100% voluntary non-remunerated blood donation (VNRD) globally by the year 2020. However, until today, little was known in Lebanon regarding its actual rate or influencing factors, particularly donor motivations and behaviors. Therefore, the aim of this study was to assess the knowledge, attitudes, and practices of blood donors in Lebanon. The ultimate goals were to retain first-time donors, encourage them to become regular ones, and facilitate the transition from replacement donation to VNRD. Materials and MethodsA multi-centric cross-sectional study was carried across the five governorates in Lebanon. A self-administered and structured questionnaire was used in this survey. Results were presented in terms of odds ratios, with statistical significance defined at a P value of 0.05 and a 95% confidence interval. Additionally, a benchmarking analysis of the situation of blood donation in Lebanon was also conducted, identifying several areas for improvement. ResultsA total of 620 blood donors participated in this study, with 21.3% being first-time donors and 78.7% repeat donors. While the latter were primarily motivated by self-esteem, solidarity or returning a favor (89%, 77.9% and 78.1%), the main obstacle for becoming regular donors was a lack of initiative (34.6%). Female donors (9.9% of the total) exhibited better knowledge (OR = 2.20, p = 0.011) and were more inclined to donate voluntarily (OR = 1.52, p = 0.048). Conversely, male donors were more likely to be repeat donors, often through replacement donation (OR = 2.95, p = 0.001). ConclusionThere is a significant disparity between the low rate of voluntary donation in Lebanon (22.2%) and the relatively high proportion of donors with adequate knowledge of the donation process (60.5%). Therefore, urgent action by public authorities, based on the evidence based strategies outlined in this article, is crucial to enhancing the voluntary donation rate in Lebanon.

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

The conceptual foundations of the integration of biological knowledge and ethical concepts in the educational process based on the worldview unity of the laws of being in the teaching of natural sciences are revealed. Attention is focused on the fact that the world is built on the basis of general laws of nature, objects of the material world do not have freedom of choice, therefore it is impossible to talk about their ethics or morality. The laws of morality correspond to the general laws of nature, because a person is part of an interconnected world, and his existence and development should not conflict with the development of the system. Freedom of choice enables a person to be creative at all levels of his being. It is justified that cross-cutting content lines of science education must be integrated with universal human values, which gives teaching an ethical direction and affirms ethical meanings in science education. The universal laws of nature, according to which living systems are built and function, have their analogies in moral laws, therefore teaching biology based on analogies between the laws of nature and the laws of morality creates conditions for the spiritual development of the student. A method of acquiring knowledge is proposed, which creates conditions for the development of the inner spiritual world of the individual, and the formation of students' bioethical knowledge not only affects their value orientations, but also the spiritual potential of the individual. Its essence is that when studying a meta-subject, the semantic field of objects of knowledge is located behind the subject at the meta-level, therefore, the results of knowledge are not communicated to the student as material for learning, but are acquired by each individual in his own way. Criteria for selection of bioethical knowledge are outlined. Examples of the integration of biological knowledge and ethical concepts through analogies between them are given. Priority ideas for the formation of bioethical knowledge are singled out: awareness of the integrity and interconnectedness of the world, in which man is assigned an important role as a subject capable of significantly influencing all its links; the moral state of a person depends on its influence on the integrity of the biosphere; the presence of single general laws of formation and development of the natural world and the inner world of man; the possibility of developing and nurturing a moral personality through the disclosure of the ethical essence of the laws of nature.

Separation processes for the treatment of industrial flue gases – Effective methods for global industrial air pollution control

The treatment of flue gases has become a crucial area of interest with the increasing air emissions into the atmosphere from industries involved in combustion of fossil fuels in their operations. In essence, there is a critical need for effective methods of treatment more than ever. Treatment and separation are now a demand for the overall industrial operations to control the rate of flue gas emissions. The major culprit in this wise is power generating industry. The major associated air pollutants are carbon dioxide, sulfur oxides, trace metals, volatile organic compounds, particulate matters, and nitrogen oxides. However, the choice of technologies to be utilized requires more than just knowledge of the separation process, but also a good understanding of the properties of the pollutants. This review explored and evaluated the various separation processes and technologies for the treatment of industrial flue gases for the control of the associated air pollutants. It also analyzed the performance with references to cost and efficiency, the advantages and disadvantages, principles for selection, research direction, and/or potential opportunities in existing separation processes and technologies.

Energy optimization of hydrogen liquefaction process via process knowledge combined with multivariate Coggin's algorithm

Sustainable and cost-effective transportation of hydrogen is one of the major challenges to futuristic hydrogen value chain. Hydrogen, in its produced form, exhibits low energy density and large volume, rendering it highly unsuitable for transportation, particularly over extended distances. Liquefaction is one of the promising approaches to improve hydrogen's energy density and to make it more compact. However, liquefaction is an energy intensive process, raising the cost of transportation. In this study, the specific energy consumption of the hydrogen liquefaction process is aimed to reduce through knowledge-based optimization followed by optimization using the multivariate Coggin's algorithm to improve energy and economic profiles of the process. Design variables, composite curve, exergy, and economic analyses are performed to evaluate and compare the thermodynamic, economic, and environmental feasibility of the optimized process. The results depict a significant reduction (14.3%) in specific energy consumption to 9.40 kW/kgLH2 without increasing process complexity. Further key improvements include a massive drop in refrigerant flowrates (9.2%), annualized cost (m$ 0.15), and annual CO2 emissions (1008.45 tCO2/annum). The largest exergy destruction is observed in CHX-201, reflecting further room for improvement. These results underscore the potential for optimizing hydrogen liquefaction processes to enhance energy efficiency, process economics and environmental impact, providing valuable insights for researchers and industry professionals seeking to advance hydrogen liquefaction technologies. However, challenges remain in the comprehensive evaluation of chemical exergy for ortho- and para-hydrogen and in conducting advanced exergy analyses to further optimize hydrogen liquefaction processes without adding complexity.

Predicting maintenance costs of an IT system using artificial intelligence models

Predictive maintenance is a maintenance policy where the goal is to detect potential future maintenance risks in a system so that the maintenance process can be optimised before system faults occur. This paper describes a deep learning model that does not require domain expertise. Deep learning approaches have several benefits over explicit statistical modelling: (1) they require far less domain-specific knowledge; (2) if the underlying data-generating mechanism of assets changes, a deep learning model would only need to be retrained to learn these new changes; (3) they can capture non-linear and complex multidimensional relationships; and (4) they may outperform rule-based or statistical methods. The paper describes how the model predicts maintenance-relevant events, along with the cost of the upcoming event and the time when it will happen. The paper describes the use of a long short-term memory architecture for our deep learning model. By doing so, the cost values represent a real, quantitative value of the potential maintenance costs in the future of an asset. Event, cost and time prediction are all achieved with high accuracy. This allows for the development of maintenance solutions without the initial high degree of domain process knowledge required. The artificial intelligence model can be used to raise an alarm when the cost values exceed some threshold, when the frequency of high-cost events increases significantly over the lifetime of an asset, or when the expected cost exceeds the cost of maintenance.

Evaluation of Deterioration Degree of Archaeological Wood from Luoyang Canal No. 1 Ancient Ship

This study provides a detailed investigation of archaeological wood samples from the Luoyang Canal No. 1 site, focusing on wood species identification, physical properties, mechanical property analyses, and morphological examination. The identified wood species, belonging to the Ulmus genus, exhibited a 43% decline in compressive strength in waterlogged environments. Further, the wood exhibited increased moisture content, higher porosity, reduced basic density, and elevated shrinkage rates, indicating a mild level of degradation. X-ray diffraction was employed for the observation of cellulose structure, and Fourier transform infrared spectroscopy (FT-IR) demonstrated significant removal of cellulose and hemicellulose components. These findings emphasize the importance of understanding wood degradation mechanisms to evaluate structural integrity and durability in guiding the development of effective preservation strategies for archaeological wood artifacts. Continued research and conservation are crucial to deepen our knowledge of wood deterioration processes and enhance the implementation of preservation techniques.

DISCOURSE: KNOWLEDGE, NEWS, AND FAKE INTERTWINED

Discourse has been a focal point for linguists over an extended period. The multidisciplinary character of the term ‘discourse’ has resulted in diverse approaches aiming to define and explore this phenomenon. The study of various facets of discourse significantly enhances its comprehension. For our understanding, discourse encompasses the following pertinent characteristics: it is a communicative process, a dialogue, an interaction between communicators; it is a structure, a system, a distinct way of representing and perceiving the world, a special language and world, an expression and manifestation of national identity. Discourse implies knowledge, as it includes various types of it. Knowledge and news are closely linked. They are processed in discourse and with the help of it. Any explicit or implicit knowledge and news influence discourse production and comprehension. True and fake information can alter existing types of knowledge and create new ones, influence mental processes, and shape new mental models. The aim of the article is to describe discourse in its close connection with its main constituents – knowledge, news and fake. ‘Fake’ becomes a linguistic and discursive matter. It is associated with the concepts of ‘lie’, ‘deception’, and ‘manipulation’. Corpus data about ‘fake’ and ‘fake news’ give a bigger picture of the overall context of their representation, changes and dynamics in the usage. The widespread influence of fake is provided with the help of mass media. Strategic control of knowledge in the interaction process is achieved through the use of knowledge itself, accordingly, it becomes possible to control knowledge by means of deception and fake. Fake news is a genre of news information and news discourse, it is an integrative type of media text. The main goal of fake news is to deceive and manipulate consciousness of a wide audience. Manipulation entails language to subtly influence recipients, encouraging them covertly to undertake particular actions. Fake news can be studied within news discourse, media discourse, television discourse, manipulative discourse, political discourse, discourse of fake, and other types. Thus, knowledge, news and fake presented in discourse and with the help of it allow to create ‘new knowledge’, shape the audience’s understanding of discourse, make and generate mental models, control and restrict access to certain information, manipulate consciousness of the audience, transform traditional mental attitudes associated with the pursuit of truth.

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.

Development of an Education Material Targeting Patients Undergoing Lower Extremity Amputation due to Severe Limb Ischemia–A Qualitative Study

IntroductionCritical limb-threatening ischemia (CLTI) is associated with a high risk of amputation, yet patients undergoing amputation due to CLTI have little knowledge of the amputation process and the rehabilitation that awaits. The aim of the present study was to develop and validate information material for patients undergoing amputation. MethodsNine participants were included in the study. Two focus group interviews were performed with seven patients who had undergone lower extremity amputation due to CLTI within the past 2 y. Additionally, two individual interviews were carried out. A semistructured interview guide was used, and the interviews were transcribed verbatim and analysed using qualitative content analysis with a deductive approach. ResultsThree themes were identified as essential for the design of the written information: Perspectives on design and formatting, Providing information to enhance participation in care, and Accessibility to information and support. The prototyped information leaflet was perceived as acceptable, useable, relevant, and comprehensible by the participants. ConclusionsFor patients to actively engage in their care, it is vital that their information needs are met and that they are provided with psychosocial support when needed. Written and oral information should be provided by a trusted healthcare professional.

The Dark Side of Robotic Process Automation (RPA): Understanding Risks and Challenges with RPA

SYNOPSIS Auditors and corporate accountants are rapidly adopting robotic process automation (RPA) to assist with accounting tasks. The purpose of this paper is to increase understanding of the risks and challenges associated with RPA. This is particularly important given most existing reports focus on the benefits of using RPA. We interview multiple professionals to ascertain challenges, drawbacks, or pitfalls of using RPA. We identify five key challenges related to RPA usage: (1) RPA is often used as a quick-fix band-aid instead of fixing core system issues, (2) RPA can cause serious control and security issues, (3) the true cost of RPA is often misunderstood and understated, (4) RPA governance is complicated and challenging, and (5) RPA usage can lead to a loss of process knowledge. Raising these issues should allow practitioners to make more informed decisions regarding RPA implementations and help inform them regarding the problematic areas that require better governance.

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.

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

PurposeThis 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/approachThis 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.FindingsThe 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/valueThis 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.