| 1. |
- Atif, Yacine, 1967-, et al.
(författare)
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A fuzzy logic approach to influence maximization in social networks
- 2020
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Ingår i: Journal of Ambient Intelligence and Humanized Computing. - : Springer. - 1868-5137 .- 1868-5145. ; 11:6, s. 2435-2451
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Tidskriftsartikel (refereegranskat)abstract
- Within a community, social relationships are paramount to profile individuals’ conduct. For instance, an individual within a social network might be compelled to embrace a behaviour that his/her companion has recently adopted. Such social attitude is labelled social influence, which assesses the extent by which an individual’s social neighbourhood adopt that individual’s behaviour. We suggest an original approach to influence maximization using a fuzzy-logic based model, which combines influence-weights associated with historical logs of the social network users, and their favourable location in the network. Our approach uses a two-phases process to maximise influence diffusion. First, we harness the complexity of the problem by partitioning the network into significantly-enriched community-structures, which we then use as modules to locate the most influential nodes across the entire network. These key users are determined relatively to a fuzzy-logic based technique that identifies the most influential users, out of which the seed-set candidates to diffuse a behaviour or an innovation are extracted following the allocated budget for the influence campaign. This way to deal with influence propagation in social networks, is different from previous models, which do not compare structural and behavioural attributes among members of the network. The performance results show the validity of the proposed partitioning-approach of a social network into communities, and its contribution to “activate” a higher number of nodes overall. Our experimental study involves both empirical and real contemporary social-networks, whereby a smaller seed set of key users, is shown to scale influence to the high-end compared to some renowned techniques, which employ a larger seed set of key users and yet they influence less nodes in the social network.
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| 2. |
- Gavali, Hamid, et al.
(författare)
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Outcome of Radical Surgical Treatment of Abdominal Aortic Graft and Endograft Infections Comparing Extra-anatomic Bypass with In Situ Reconstruction : A Nationwide Multicentre Study
- 2021
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Ingår i: European Journal of Vascular and Endovascular Surgery. - : Saunders Elsevier. - 1078-5884 .- 1532-2165. ; 62:6, s. 918-926
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Abdominal aortic graft and endograft infection (AGI) is primarily treated by resection of the infected graft and restoration of distal perfusion through extra-anatomic bypass (EAB) or in situ reconstruction/repair (ISR). The aim of this study was to compare these surgical strategies in a nationwide multicentre retrospective cohort study.Methods: The Swedish Vascular Registry (Swedvasc) was used to identify surgically treated abdominal AGIs in Sweden between January 1995 and May 2017. The primary aim was to compare short and long term survival, as well as complications for EAB and ISR.Results: Some 126 radically surgically treated AGI patients were identified – 102 graft infections and 24 endograft infections – treated by EAB: 71 and ISR: 55 (23 neo-aorto-iliac systems, NAISs). No differences in early 30 day (EAB 81.7% vs. ISR 76.4%, p =.46), or long term five year survival (48.2% vs. 49.9%, p =.87) were identified. There was no survival difference comparing NAIS to other ISR strategies. The frequency of recurrent graft infection during follow up was similar: EAB 20.3% vs. ISR 17.0% (p =.56). Survival and re-infection rates of the new conduit did not differ between NAIS and other ISR strategies. Age ≥ 75 years (odds ratio [OR] 4.0, confidence interval [CI] 1.1 – 14.8), coronary artery disease (OR 4.2, CI 1.2 – 15.1) and post-operative circulatory complications (OR 5.2, CI 1.2 – 22.5) were associated with early death. Prolonged antimicrobial therapy (> 3 months) was associated with reduced long term mortality (HR 0.3, CI 0.1 – 0.9).Conclusion: In this nationwide multicentre study comparing outcomes of radically treated AGI, no differences in survival or re-infection rate could be identified comparing EAB and ISR.
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| 3. |
- Gavali, Hamid, et al.
(författare)
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Semi-Conservative Treatment Versus Radical Surgery in Abdominal Aortic Graft and Endograft Infections
- 2023
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Ingår i: European Journal of Vascular and Endovascular Surgery. - : Elsevier. - 1078-5884 .- 1532-2165. ; 66:3, s. 397-406
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Abdominal aortic graft and endograft infections (AGIs) are rare complications following aortic surgery. Radical surgery (RS) with resection of the infected graft and reconstruction with extra-anatomical bypass or in situ reconstruction is the preferred therapy. For patients unfit for RS, a semi-conservative (SC), graft preserving strategy is possible. This paper aimed to compare survival and infection outcomes between RS and SC treatment for AGI in a nationwide cohort.Methods: Patients with abdominal AGI related surgery in Sweden between January 1995 and May 2017 were identified. The Management of Aortic Graft Infection Collaboration (MAGIC) criteria were used for the definition of AGI. Multivariable regression was performed to identify factors associated with mortality.Results: One hundred and sixty-nine patients with surgically treated abdominal AGI were identified, comprising 43 SC (14 endografts; 53% with a graft enteric fistula [GEF] in total) and 126 RS (26 endografts; 50% with a GEF in total). The SC cohort was older and had a higher frequency of cardiac comorbidities. There was a non-significant trend towards lower Kaplan -Meier estimated five year survival for SC vs. RS (30.2% vs. 48.4%; p = .066). A non-significant trend was identified towards worse Kaplan -Meier estimated five year survival for SC patients with a GEF vs. without a GEF (21.7% vs. 40.1%; p = .097). There were significantly more recurrent graft infections comparing SC with RS (45.4% vs. 19.3%; p < .001). In a Cox regression model adjusting for confounders, there was no difference in five year survival comparing SC vs. RS (HR 1.0, 95% CI 0.6 -1.5).Conclusion: In this national AGI cohort, there was no mortality difference comparing SC and RS for AGI when adjusting for comorbidities. Presence of GEF probably negatively impacts survival outcomes of SC patients. Rates of recurrent infection remain high for SC treated patients.
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| 4. |
- Jiang, Yuning, 1993-
(författare)
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Vulnerability Analysis for Critical Infrastructures
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The rapid advances in information and communication technology enable a shift from diverse systems empowered mainly by either hardware or software to cyber-physical systems (CPSs) that are driving Critical infrastructures (CIs), such as energy and manufacturing systems. However, alongside the expected enhancements in efficiency and reliability, the induced connectivity exposes these CIs to cyberattacks exemplified by Stuxnet and WannaCry ransomware cyber incidents. Therefore, the need to improve cybersecurity expectations of CIs through vulnerability assessments cannot be overstated. Yet, CI cybersecurity has intrinsic challenges due to the convergence of information technology (IT) and operational technology (OT) as well as the crosslayer dependencies that are inherent to CPS based CIs. Different IT and OT security terminologies also lead to ambiguities induced by knowledge gaps in CI cybersecurity. Moreover, current vulnerability-assessment processes in CIs are mostly subjective and human-centered. The imprecise nature of manual vulnerability assessment operations and the massive volume of data cause an unbearable burden for security analysts. Latest advances in machine-learning (ML) based cybersecurity solutions promise to shift such burden onto digital alternatives. Nevertheless, the heterogeneity, diversity and information gaps in existing vulnerability data repositories hamper accurate assessments anticipated by these ML-based approaches. Therefore, a comprehensive approach is envisioned in this thesis to unleash the power of ML advances while still involving human operators in assessing cybersecurity vulnerabilities within deployed CI networks.Specifically, this thesis proposes data-driven cybersecurity indicators to bridge vulnerability management gaps induced by ad-hoc and subjective auditing processes as well as to increase the level of automation in vulnerability analysis. The proposed methodology follows design science research principles to support the development and validation of scientifically-sound artifacts. More specifically, the proposed data-driven cybersecurity architecture orchestrates a range of modules that include: (i) a vulnerability data model that captures a variety of publicly accessible cybersecurity-related data sources; (ii) an ensemble-based ML pipeline method that self-adjusts to the best learning models for given cybersecurity tasks; and (iii) a knowledge taxonomy and its instantiated power grid and manufacturing models that capture CI common semantics of cyberphysical functional dependencies across CI networks in critical societal domains. This research contributes data-driven vulnerability analysis approaches that bridge the knowledge gaps among different security functions, such as vulnerability management through related reports analysis. This thesis also correlates vulnerability analysis findings to coordinate mitigation responses in complex CIs. More specifically, the vulnerability data model expands the vulnerability knowledge scope and curates meaningful contexts for vulnerability analysis processes. The proposed ML methods fill information gaps in vulnerability repositories using curated data while further streamlining vulnerability assessment processes. Moreover, the CI security taxonomy provides disciplined and coherent support to specify and group semanticallyrelated components and coordination mechanisms in order to harness the notorious complexity of CI networks such as those prevalent in power grids and manufacturing infrastructures. These approaches learn through interactive processes to proactively detect and analyze vulnerabilities while facilitating actionable insights for security actors to make informed decisions.
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| 5. |
- Lindström, Anders, 1964-, et al.
(författare)
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User-centered development of a driving simulator for training of emergency vehicle drivers and development of Emergency Vehicle Approaching messaging : a simulator study
- 2020
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Ingår i: Proceedings of 8th Transport Research Arena TRA 2020.
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Konferensbidrag (refereegranskat)abstract
- There is a large risk of accidents in connection with emergency driving and the need for both better possibilities to train emergency vehicle driving and for systems guiding other road users to the right behavior is apparent. The aim of this study was (1) to initiate user-centered development of a driving simulator for training of emergency vehicle drivers and (2) to collect information about how to best communicate Emergency Vehicle Approaching (EVA) messages. The method used is user-involved, iterative development of both the driving scenario and the driving simulator. 104 participants have tried the simulator and responded to a questionnaire. Most difficult for emergency vehicle drivers are vehicles in front suddenly braking and failure in other drivers noticing them. Desired behaviour in other road users is to yield to the right and brake smoothly. The attitude towards communication of Emergency Vehicle (EV) driving is positive, regarding both pre-alerting drivers who are approaching an incident scene and sending out EVA-messages.
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| 6. |
- Lindström, Birgitta, et al.
(författare)
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Message from the TestEd 2020 Chairs
- 2020
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Ingår i: 2020 IEEE 13th International Conference on Software Testing, Verification and Validation Workshops. - : IEEE. - 9781728110752 - 9781728110769
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Lindström, Emma, et al.
(författare)
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SELF-PERCEIVED VOCAL HEALTH AND SOCIAL PARTICIPATION AMONG OLDER ADULTS
- 2023
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Ingår i: Proceedings of Forum Acusticum 2023 - 10th Convention of the European Acoustics Association, EAA 2023. - 9788888942674
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Konferensbidrag (refereegranskat)abstract
- The aim of this study is to investigate the association between self-perceived voice problems and social participation among older adults (65-80 years). A complementary aim was to investigate the association between self-perceived voice problems and physical activity. Method Participants were recruited through social media and asked to complete an online questionnaire. In total, 152 individuals were included, aged 65 to 80 years. The questionnaire consisted of 26 questions: demographic information, vocal health, physical activity and social participation. In this study, the focus is on vocal health and social participation, including physical activity. Questions regarding vocal health were based on Voice Handicap Index (VHI) by Jacobson et al. (1997) and the questions regarding social participation were inspired by Howery and Hand (2019). Results Preliminary analyses show that 57.9% of all participants experienced voice problems. Preliminary results further suggests that there was no significant association between self-perceived vocal health and social participation, but a significant association between self-perceived vocal health and physical activity. The highest levels of social participation were found in the age group 71-75 years.
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| 8. |
- Lindström, Stefan B, Professor, 1974-, et al.
(författare)
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Multivariate lognormal mixture for pulp particle characterization
- 2024
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Ingår i: Cellulose. - : Springer Nature. - 0969-0239 .- 1572-882X. ; 31:3, s. 1843-1854
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Tidskriftsartikel (refereegranskat)abstract
- We present a method for pulp particle characterization based on a truncated lognormal mixture (TLM) model, as motivated by size statistics of organisms. We use an optical fiber analyzer to measure the length–width distribution of kraft-cooked roundwood or sawmill sources, of chemi-thermomechanical pulp (CTMP) samples from roundwood or sawmill sources, and the same CTMP samples after kraft post-processing. Our results show that bimodal TLMs capture salient features of the investigated pulp particle distributions, by decomposition into a large-particle and a small-particle fraction. However, we find that fibers from sawmill sources, which have not undergone mechanical treatment, cannot be described by TLM, likely due to non-random sampling. Within the confines of our dataset, the TLM characterization predicts laboratory sheet properties more effectively than conventional averaging methods for pulp particle size distributions. The TLM characterization is intended as a tool for controlling the pulp production process towards higher product quality, uniformity, and energy efficiency, pending further mill trials for validation.
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| 9. |
- Lindström, Stefan B, Professor, 1974-, et al.
(författare)
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Pulp Particle Classification Based on Optical Fiber Analysis and Machine Learning Techniques
- 2024
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Ingår i: Fibers. - : Multidisciplinary Digital Publishing Institute (MDPI). - 2079-6439. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- In the pulp and paper industry, pulp testing is typically a labor-intensive process performed on hand-made laboratory sheets. Online quality control by automated image analysis and machine learning (ML) could provide a consistent, fast and cost-efficient alternative. In this study, four different supervised ML techniques—Lasso regression, support vector machine (SVM), feed-forward neural networks (FFNN), and recurrent neural networks (RNN)—were applied to fiber data obtained from fiber suspension micrographs analyzed by two separate image analysis software. With the built-in software of a commercial fiber analyzer optimized for speed, the maximum accuracy of 81% was achieved using the FFNN algorithm with Yeo–Johnson preprocessing. With an in-house algorithm adapted for ML by an extended set of particle attributes, a maximum accuracy of 96% was achieved with Lasso regression. A parameter capturing the average intensity of the particle in the micrograph, only available from the latter software, has a particularly strong predictive capability. The high accuracy and sensitivity of the ML results indicate that such a strategy could be very useful for quality control of fiber dispersions.
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| 10. |
- Mannervik, Bengt, et al.
(författare)
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Glutathione Transferases as Efficient Ketosteroid Isomerases
- 2021
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Ingår i: Frontiers in Molecular Biosciences. - : Frontiers Media SA. - 2296-889X. ; 8
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Forskningsöversikt (refereegranskat)abstract
- In addition to their well-established role in detoxication, glutathione transferases (GSTs) have other biological functions. We are focusing on the ketosteroid isomerase activity, which appears to contribute to steroid hormone biosynthesis in mammalian tissues. A highly efficient GST A3-3 is present in some, but not all, mammals. The alpha class enzyme GST A3-3 in humans and the horse shows the highest catalytic efficiency with kcat/Km values of approximately 107 M−1s−1, ranking close to the most active enzymes known. The expression of GST A3-3 in steroidogenic tissues suggests that the enzyme has evolved to support the activity of 3β-hydroxysteroid dehydrogenase, which catalyzes the formation of 5-androsten-3,17-dione and 5-pregnen-3,20-dione that are substrates for the double-bond isomerization catalyzed by GST A3-3. The dehydrogenase also catalyzes the isomerization, but its kcat of approximately 1 s−1 is 200-fold lower than the kcat values of human and equine GST A3-3. Inhibition of GST A3-3 in progesterone-producing human cells suppress the formation of the hormone. Glutathione serves as a coenzyme contributing a thiolate as a base in the isomerase mechanism, which also involves the active-site Tyr9 and Arg15. These conserved residues are necessary but not sufficient for the ketosteroid isomerase activity. A proper assortment of H-site residues is crucial to efficient catalysis by forming the cavity binding the hydrophobic substrate. It remains to elucidate why some mammals, such as rats and mice, lack GSTs with the prominent ketosteroid isomerase activity found in certain other species. Remarkably, the fruit fly Drosophila melanogaster, expresses a GSTE14 with notable steroid isomerase activity, even though Ser14 has evolved as the active-site residue corresponding to Tyr9 in the mammalian alpha class.
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