| 1. |
- Andersson, K., et al.
(författare)
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High-accuracy sampling of saproxylic diversity indicators at regional scales with pheromones : The case of Elater ferrugineus (Coleoptera, Elateridae)
- 2014
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Ingår i: Biological Conservation. - : Elsevier BV. - 0006-3207 .- 1873-2917. ; 171, s. 156-166
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Tidskriftsartikel (refereegranskat)abstract
- The rare beetle Elater ferrugineus was sampled at 47 sites in the county of Östergötland, Sweden by means of pheromone-baited traps to assess its value as an indicator species for hollow oak stands rich in rare saproxylic beetle species. In addition, Osmoderma eremita was also sampled with pheromone baits. These data were then compared against species survey data collected at the same sites by pitfall and window traps. Both species co-occur with many Red Listed saproxylic beetles, with E. ferrugineus being a somewhat better indicator for the rarest species. The conservation value of a site (measured as Red List points or number of Red Listed species) increased with the number of specimens of E. ferrugineus and O. eremita caught. Accuracy of sampling by means of pheromone trapping turned out to be radically different for the two model species. E. ferrugineus traps put out during July obtained full accuracy after only 6. days, whereas O. eremita traps needed to be out from early July to mid-August in order to obtain full accuracy with one trap per site. By using E. ferrugineus, or preferably both species, as indicator species, accuracy would increase and costs decrease for saproxylic biodiversity sampling, monitoring and identification of hotspots. © 2014 Elsevier Ltd.
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| 2. |
- Andersson, Ken, et al.
(författare)
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Secure Computation on 4G/5G Enabled Internet-of-Things
- 2019
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Ingår i: Wireless Communications & Mobile Computing. - : Hindawi Limited. - 1530-8669 .- 1530-8677. ; 2019, s. 1-1
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Tidskriftsartikel (populärvet., debatt m.m.)abstract
- The rapid development of Internet-of-ings (IoT) techniques in G/ G deployments is witnessing the generation of massive amounts of data which are collected, stored, processed, and presented in an easily interpretable form. Analysis of IoT data helps provide smart services such as smart homes, smart energy, smart health, and smart environments through G and G technologies. At the same time, the threat of the cyberattacks and issues with mobile internet security is becoming increasingly severe, which introduces new challenges for the security of IoT systems and applications and the privacy of individuals thereby. Protecting IoT data privacy while enabling data availability is an urgent but difficult task.
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| 3. |
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| 4. |
- Danielsson, Christian, et al.
(författare)
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Exploration of human, rat, and rabbit embryonic cardiomyocytes suggests K-channel block as a common teratogenic mechanism
- 2013
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Ingår i: Cardiovascular Research. - : Oxford University Press (OUP): Policy B. - 0008-6363 .- 1755-3245. ; 97:1, s. 23-32
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Tidskriftsartikel (refereegranskat)abstract
- Several drugs blocking the rapidly activating potassium (K-r) channel cause malformations (including cardiac defects) and embryonic death in animal teratology studies. In humans, these drugs have an established risk for acquired long-QT syndrome and arrhythmia. Recently, associations between cardiac defects and spontaneous abortions have been reported for drugs widely used in pregnancy (e.g. antidepressants), with long-QT syndrome risk. To investigate whether a common embryonic adverse-effect mechanism exists in the human, rat, and rabbit embryos, we made a comparative study of embryonic cardiomyocytes from all three species. less thanbrgreater than less thanbrgreater thanPatch-clamp and quantitative-mRNA measurements of K-r and slowly activating K (K-s) channels were performed on human, rat, and rabbit primary cardiomyocytes and cardiac samples from different embryo-foetal stages. The K-r channel was present when the heart started to beat in all species, but was, in contrast to human and rabbit, lost in rats in late organogenesis. The specific K-r-channel blocker E-4031 prolonged the action potential in a species- and development-dependent fashion, consistent with the observed K-r-channel expression pattern and reported sensitive periods of developmental toxicity. E-4031 also increased the QT interval and induced 2:1 atrio-ventricular block in multi-electrode array electrographic recordings of rat embryos. The K-s channel was expressed in human and rat throughout the embryo-foetal period but not in rabbit. less thanbrgreater than less thanbrgreater thanThis first comparison of mRNA expression, potassium currents, and action-potential characteristics, with and without a specific K-r-channel blocker in human, rat, and rabbit embryos provides evidence of K-r-channel inhibition as a common mechanism for embryonic malformations and death.
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| 5. |
- Dyrhage, Karl
(författare)
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Multi-omics investigation into bacterial evolution
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The focus of this thesis is the investigation of the evolution and cellular processes of Tuwongella immobilis and Apilactobacillus kunkeei, two bacterial species with different levels of genomic and cellular complexity, using a multi-omics approach.In the first study we examined the proteome of T. immobilis with LC-MS/MS after fractionation by differential solubilisation, yielding fractions corresponding to the cytoplasm, inner membrane, and outer membrane. The experiment was repeated with Escherichia coli and the results were compared. T. immobilis had five times as many predicted cytoplasmic proteins in the most hydrophobic fraction as E. coli. Among these are innovations in the Planctomycetota lineage and protein families that have undergone recent paralogisation followed by domain shuffling, including many enzymes related to information processing.The remaining three studies dealt with honeybee symbiont A. kunkeei. In the first of these, we sequenced and compared the chromosomal and extrachromosomal content of 102 novel A. kunkeei strains. We found that A. kunkeei has an open pangenome and an active set of transposable elements. Within the population we discovered three plasmids between 19.5 and 32.9 kb, one of which codes for enzymes involved in the synthesis of the antimicrobial compound kunkecin A which inhibits growth of the bee pathogen Melisococcus plutonius.In the next study we collected transcriptomic, proteomic, and metabolomic data from two growth phases from A. kunkeei strain A1401 and mapped the results to a metabolic pathway model. Enzymes involved in fermentation of fructose were highly expressed during the exponential growth phase. Enzymes involved in UMP biosynthesis were upregulated during stationary phase, as were protein involved in stress response and detoxification.The last study concerned the secretome of A. kunkeei. We characterised two types of extracellular particles from A. kunkeei strains A1401 and A0901. One type of particle was found to be proteinaceous, while the other type constituted membrane vesicles containing RNA. Comparison of transcriptomic data from the membrane vesicles and whole cells showed that the packing of the RNA was largely untargeted, but with a bias towards highly expressed mRNAs. We suggest that the cell uses membrane vesicles as a mechanism to get rid of superfluous mRNAs after rapid-response overexpression.Together these studies provide insights into the processes driving evolution in T. immobilis and A. kunkeei, and generate several testable hypotheses for future studies.
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| 6. |
- 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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| 7. |
- 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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| 8. |
- Gavali, Hamid, et al.
(författare)
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Semi-Conservative Treatment Versus 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
-
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 definition of AGI. Multivariable regression was performed to identify factors associated with mortality.RESULTS: A total of 169 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 5-year survival for SC versus RS (30.2% vs. 48.4%; p = .066). A non-significant trend was identified towards worse Kaplan-Meier estimated 5-year survival for SC patients with a GEF versus without a GEF (21.7% vs. 40.1%; p = .097). There were significantly more recurrent graft infections comparing SC versus RS (45.4% vs. 19.3%; p < .001). In a Cox regression model adjusting for confounders, there was no difference in 5-year survival comparing SC versus RS (HR 1.0, 95% CI 0.6 - 1.5).CONCLUSION: In this national AGI cohort, we could not identify any mortality difference comparing SC versus RS for AGI when adjusting for comorbidities. Presence of GEF likely negatively impacts survival outcomes of SC patients. Rates of recurrent infection remain high for SC-treated patients.
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| 9. |
- Geli Rolfhamre, Patricia, 1979-
(författare)
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From Penicillin Binding Proteins to Community Interventions : Mathematical and Statistical Models Related to Antibiotic Resistance
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Antibiotic resistance has become a major public health concern and mathematical models are important analytical tools for the understanding, evaluation and prediction of the resistance problem and related control strategies.The risk of emerging antibiotic resistance and selection has rarely been a concern in the design of antibiotic drug dosing regimens. In the first paper, a selection of antibiotic resistant subpopulations for different antibiotic dosing regimens was studied in vitro. The demonstrated complex relationship was influenced by both the rise of new mutants and a postantibiotic effect (PAE) (continued inhibition of bacterial growth after removal of the antibiotic drug). By constructing a mathematical model that incorporated biologically relevant parameters, we were able to assess the risks of resistance development under different dosing strategies.In the second paper, the model for PAEs is further developed to determine the implications for different dosing regimens. The result challenges the conventional notion that long PAEs promote extended drug dosing intervals and it allows new hypotheses to be tested experimentally based on the findings from the theoretical framework.Since PAE experiments often are time-consuming and laborious, very few studies have been reporting variation for this phenomenon. In the third paper, an extension to capture the stochastic behavior of bacterial population growth under drug exposure is made. The stochastic nature of the model is also an important complement to the existing deterministic models on drug dose drug effect relationships.The last paper describes a controlled clinical intervention study aiming at determining whether the frequency of trimethoprim resistance in E. coli can be decreased by a sudden and drastic reduction in trimethoprim use. In addition to evaluating the intervention effect, the model, given estimated parameters, is also used for predicting other interesting outcomes.
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| 10. |
- Gomez-Pinilla, Pedro J., et al.
(författare)
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Effect of melatonin on age associated changes in guinea pig bladder function
- 2007
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Ingår i: Journal of Urology. - : Ovid Technologies (Wolters Kluwer Health). - 1527-3792 .- 0022-5347. ; 177:4, s. 1558-1561
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The incidence of urinary incontinence increases with age but the cause and effect relationship between aging and altered bladder function is poorly understood. It was suggested that melatonin can ameliorate negative effects induced by aging by its free radical scavenging activity and its ability to decrease oxidative stress. We investigated the changes in bladder function evoked by aging and the possible benefits of melatonin treatment on age related bladder disturbances. Materials and Methods: Bladder function was assessed using cystometry in conscious, freely moving female guinea pigs. Animals were grouped according to age as young adults (4 months old) and senescents (18 to 20 months old). A group of senescent animals were treated with 2.5 mg kg(-1) day(-1) melatonin for 21 days. Results: Aging led to increased detrusor activity, as demonstrated by short micturition intervals, decreased bladder capacity and spontaneous contractions during the filling phase. During the voiding phase aged animals showed lower micturition pressures than young adults. Melatonin counteracted the cystometric changes in senescent animals and restored micturition parameters to those of young adults. Conclusions: These results show that in guinea pigs aging induces detrusor overactivity. Melatonin treatment improved age induced changes in bladder function. If similar effects can be demonstrated in humans, melatonin treatment may be a new approach to decrease the impact of age related bladder disorders.
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| 11. |
- Gomez-Pinilla, Pedro J, et al.
(författare)
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Melatonin restores impaired contractility in aged guinea pig urinary bladder
- 2008
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Ingår i: Journal of Pineal Research. - : Blackwell Publishing Ltd. - 1600-079X .- 0742-3098. ; 44:4, s. 416-425
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Tidskriftsartikel (refereegranskat)abstract
- Urinary bladder disturbances are frequent in the elderly population but the responsible mechanisms are poorly understood. This study evaluates the effects of aging on detrusor myogenic contractile responses and the impact of melatonin treatment. The contractility of bladder strips from adult, aged and melatonin-treated guinea pigs was evaluated by isometric tension recordings. Cytoplasmatic calcium concentration ([Ca2+](i)) was estimated by epifluorescence microscopy of fura-2-loaded isolated detrusor smooth muscle cells, and the levels of protein expression and phosphorylation were quantitated by Western blotting. Aging impairs the contractile response of detrusor strips to cholinergic and purinergic agonists and to membrane depolarization. The impaired contractility correlates with increased [Ca2+](i) in response to the stimuli, suggesting a reduced Ca(2+)sensitivity. Indeed, the agonist-induced contractions in adult strips were sensitive to blockade with Y27362, an inhibitor of Rho kinase (ROCK) and GF109203X, an inhibitor of protein kinase C (PKC), but these inhibitors had negligible effects in aged strips. The reduced Ca2+ sensitivity in aged tissues correlated with lower levels of RhoA, ROCK, PKC and the two effectors CPI-17 and MYPT1, and with the absence of CPI-17 and MYPT1 phosphorylation in response to agonists. Interestingly, melatonin treatment restored impaired contractility via normalization of Ca2+ handling and Ca2+ sensitizations pathways. Moreover, the indoleamine restored age-induced changes in oxidative stress and mitochondrial polarity. These results suggest that melatonin might be a novel therapeutic tool to palliate aging-related urinary bladder contractile impairment.
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| 12. |
- Kilbo Edlund, Karl, et al.
(författare)
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Occupational particle exposure and chronic kidney disease: a cohort study in Swedish construction workers.
- 2024
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Ingår i: Journal of Occupational and Environmental Medicine. - : BMJ Publishing Group Ltd. - 1351-0711 .- 1470-7926. ; 81:5, s. 238-243
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Tidskriftsartikel (refereegranskat)abstract
- Increasing epidemiological and experimental evidence suggests that particle exposure is an environmental risk factor for chronic kidney disease (CKD). However, only a few case-control studies have investigated this association in an occupational setting. Hence, our objective was to investigate associations between particle exposure and CKD in a large cohort of Swedish construction workers.We performed a retrospective cohort study in the Swedish Construction Workers' Cohort, recruited 1971-1993 (n=286089). A job-exposure matrix was used to identify workers exposed to nine different particulate exposures, which were combined into three main categories (inorganic dust and fumes, wood dust and fibres). Incident CKD and start of renal replacement therapy (RRT) were obtained from validated national registries until 2021 and analysed using adjusted Cox proportional hazards models.Exposure to inorganic dust and fumes was associated with an increased risk of CKD and RRT during working age (adjusted HR for CKD at age <65 years 1.15, 95%CI 1.05 to 1.26). The elevated risk did not persist after retirement age. Exposure to cement dust, concrete dust and diesel exhaust was associated with CKD. Elevated HRs were also found for quartz dust and welding fumes.Workers exposed to inorganic particles seem to be at elevated risk of CKD and RRT. Our results are in line with previous evidence of renal effects of ambient air pollution and warrant further efforts to reduce occupational and ambient particle exposure.
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| 13. |
- Kindström-Andersson, Karl, et al.
(författare)
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Development of Scenarios as Problem-Space Descriptions in Aerospace Conceptual Design
- 2024
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Ingår i: Aerospace. - 2226-4310. ; 11:7, s. 1-17
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Tidskriftsartikel (refereegranskat)abstract
- In the defense and security domain, scenarios are often descriptions of stakeholder needs, future events, and the environment. They are used for the elicitation of requirements in development of capabilities, organizations, and technical systems. In the conceptual design of aerospace applications, models of scenarios can also represent and communicate a problem-space, enabling trade-space exploration and system effectiveness robustness analysis, which provide valuable input to decision-makers. This study utilizes design science to develop a scenario framework for solution-agnostic representations of a problem-space for use in aerospace conceptual design- and trade-space exploration. A scenario ontology is developed, describing the constituent concepts of scenarios and their relationships, followed by a method for creating scenarios and evaluating their validity. Within the EU project COLOSSUS, it is demonstrated that the scenario framework has utility both for market-pull and technology-push conceptual design. Establishing an ontology for scenarios and a method for creating them as well as evaluating their validity is another step in improving the aerospace conceptual design phase.
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| 14. |
- Kindström Andersson, Karl, et al.
(författare)
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System of systems lessons to be learned in the development of air power for the future : a small state’s perspective
- 2022
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Sweden, as a small alliance free state with powerful neighbors, has a military history of what we nowadays call systems of systems thinking. Since the beginning of the Cold War thishas been expressed in an air force on the forefront of exploiting military innovations, not least with regard to sensor networks, datalinks, information sharing and distributed decision making. How can this history and the lessons learned come to use when future systems and technologies are to be developed to meet the uncertain future and changing threats? How does this fit with current trends such as capability-based approach and system of systemsengineering methodology? What could this mean for the development of the next generation fighter aircraft - after the Gripen E and contemporary aircraft? These questions have been studied from both a government and industry perspective, following the trend in the defense sector of a more intertwined relationship between the two, necessitated by adopting acapability view on aircraft development. This paper presents preliminary lessons identified from a case study on the project Flygvapnet 2000 (FV2000), which preceded the Net Centric Warfare era at the turn of the millennium. The analysis was based on characteristics of best practice systems of systems engineering derived from a review of literature presenting the methodology theory on capability-based approaches for analyzing, acquiring, developing, and managing military capabilities. The findings from this project will contribute to the development of systems of systems engineering methods and will spur proposals for future research.
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| 15. |
- Lantz, Mattias, 1971-, et al.
(författare)
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Gamma spectroscopy methodology for large amounts of environmental samples in Sweden 30 years after the Chernobyl accident
- 2020
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Ingår i: ND 2019. - : EDP Sciences. - 9782759891061
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Konferensbidrag (refereegranskat)abstract
- In a Swedish citizen science project, more than 200 elementary school classes participated in collecting fungi, soil samples, and droppings from deer and wild boar, from all over Sweden. The samples have been sent to a laboratory at Uppsala University where they are being analyzed through gamma spectroscopy with a shielded HPGe detector. The main objective is to scan the samples for 137Cs from the Chernobyl accident and compare the data with measurements from 1986, but uptake of naturally occuring radionuclides like 40K and radon daughters will also be determined. Together with the soil samples, transfer factors will be derived, and correlations for these factors will be sought for different species of fungi and soil types. The potential for correlating the results with different biological processes will also be investigated, in part through the collected animal droppings. This is a work in progress where the present status of the experimental setup and methodology are presented. Issues with the initial approach for corrections are discussed and preliminary results are presented.
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| 16. |
- Malmqvist, Ulf, et al.
(författare)
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Female pig urethral tone is dependent on Rho guanosine triphosphatases and Rho-associated kinase.
- 2004
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Ingår i: Journal of Urology. - : Ovid Technologies (Wolters Kluwer Health). - 1527-3792 .- 0022-5347. ; 171:5, s. 1955-1958
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: Circular smooth muscle of the urethra generates spontaneous myogenic tone of relevance for the maintenance of continence. We tested if Rho guanosine triphosphatases (GTPases) and Rho-associated kinase (ROK) are involved in the generation of urethral tone. MATERIALS AND METHODS: Small circular strips of female pig urethra were dissected out and mounted for recording isometric force. The effect of pharmacological agents known to modulate the activity of Rho GTPases or ROK was examined. The intracellular calcium concentration was measured using fura-2. RESULTS: Urethral tone was abolished by removing extracellular calcium or by adding the calcium antagonist felodipine. The decrease in force was closely related to a decrease in intracellular calcium concentration, indicating that tone depends on membrane associated mechanisms. Toxin B, which inactivates Rho GTPases, and Y 27632, which inhibits ROK, completely abolished tone in the female pig urethra. The latter effect occurred without any change in the intracellular calcium concentration. CONCLUSIONS: The results suggests that urethral tone depends on activity in G-protein coupled pathways and inhibition of this activity is sufficient for urethral tone relaxation. Thus, to our knowledge a new pathway in the generation of urethral tone, which might be acted on by autonomic nerves during micturition, has been identified.
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| 17. |
- Musa, Najihah, et al.
(författare)
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Using Sex Pheromone and a Multi-Scale Approach to Predict the Distribution of a Rare Saproxylic Beetle
- 2013
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 8:6
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Tidskriftsartikel (refereegranskat)abstract
- The European red click beetle, Elater ferrugineus L., is associated with wood mould in old hollow deciduous trees. As a result of severe habitat fragmentation caused by human disturbance, it is threatened throughout its distribution range. A new pheromone-based survey method, which is very efficient in detecting the species, was used in the present study to relate the occurrence of E. ferrugineus to the density of deciduous trees. The latter data were from a recently completed regional survey in SE Sweden recording >120,000 deciduous trees. The occurrence of E. ferrugineus increased with increasing amount of large hollow and large non-hollow trees in the surrounding landscape. Quercus robur (oak) was found to be the most important substrate for E. ferrugineus, whereas two groups of tree species (Carpinus betulus, Fagus sylvatica, Ulmus glabra, vs. Acer platanoides, Aesculus hippocastanum, Fraxinus excelsior, Tilia cordata) were less important but may be a complement to oak in sustaining populations of the beetle. The occurrence of E. ferrugineus was explained by the density of oaks at two different spatial scales, within the circle radii 327 m and 4658 m. In conclusion, priority should be given to oaks in conservation management of E. ferrugineus, and then to the deciduous trees in the genera listed above. Conservation planning at large spatial and temporal scales appears to be essential for long-term persistence of E. ferrugineus. We also show that occurrence models based on strategic sampling might result in pessimistic predictions. This study demonstrates how pheromone-based monitoring make insects excellent tools for sustained feedback to models for landscape conservation management.
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| 18. |
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| 19. |
- Nilsson, Karl-Fredrik, et al.
(författare)
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A probabilistic methodology to determine failure probabilities and acceptance criteria for the KBS-3 inserts under ice-age load conditions
- 2008
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Ingår i: Nuclear Technology. - 0029-5450 .- 1943-7471. ; 163:1, s. 3-14
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Tidskriftsartikel (refereegranskat)abstract
- The Swedish KBS-3 copper-cast iron canister for geological disposal of spent nuclear fuel is in an advanced stage. This paper deals with the cast iron insert that provides the mechanical strength of the canister and outlines an approach to assess the failure probabilities for manufactured canisters at large isostatic pressure (44 MPa) that could occur during future glaciations and first steps to derive acceptance criteria to ensure that failure probabilities are extremely small. The work includes a statistical test program using three inserts to determine the tensile, compression, and fracture properties. Specimens used for material characterization were also investigated by microstructural analysis to determine the microstructure and to classify and size defects. It was found that the material scatter and low ductility were caused by many defect types, but slag defects in the form of oxidation films were the most important ones. These data were then used to compute defect distributions for the probabilistic failure analysis of the KBS-3 canisters. A large number of finite element-analyses of canisters were performed at the maximum design load (44 MPa) covering distributions of material parameters and geometrical features of the canisters. The computed probabilities for fracture and plastic collapse were very low even for material data with low ductility. Two large-scale isostatic compression tests of KBS-3 mock-ups to verify safety margins are also described. The failure occurred at loads above 130 MPa in both cases, indicating a safety margin of at least a factor 3 against the maximum design load. As a result of the project, new acceptance criteria are being proposed for insert geometry and material properties, and the manufacturing process for inserts has been modified to ensure that these criteria are always fulfilled.
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| 20. |
- Stitziel, Nathan O., et al.
(författare)
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Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease
- 2016
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Ingår i: New England Journal of Medicine. - 0028-4793 .- 1533-4406. ; 374:12, s. 1134-1144
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P = 4.2x10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P = 4.0x10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P = 0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P = 0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P = 2.0x10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P = 2.5x10(-7)). CONCLUSIONS We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease.
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| 21. |
- Streng, T., et al.
(författare)
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Distribution and Function of the Hydrogen Sulfide-Sensitive TRPA1 Ion Channel in Rat Urinary Bladder
- 2008
-
Ingår i: European Urology. - : Elsevier BV. - 0302-2838 .- 1873-7560. ; 53:2, s. 391-400
-
Tidskriftsartikel (refereegranskat)abstract
- Objectives: To investigate the distribution of the transient receptor potential (TRP) A1 ion channel in the rat urinary bladder, and to study the effects of hydrogen sulfide (H2S) and known TRPA1 activators on micturition in conscious rats and on heterologously expressed ion channels. Methods: The expression of TRPA1 in urinary bladder was studied with fluorescence immunohistochemistry and real-time PCR in female Sprague-Dawley rats. Cystometric investigations were performed in conscious animals subjected to intravesical administration of sodium hydrogen sulfide (NaHS, donor of H2S), allyl isothiocyanate (AI), and cinnamaldehyde (CA). Fluorometric calcium imaging was used to study the effect of NaHS on human and mouse TRPA1 expressed in CHO cells. Results: TRPA1 immunoreactivity was found on unmyelinated nerve fibres within the urothelium, suburothelial space, and muscle layer as well as around blood vessels throughout the bladder. All TRPA1 immunoreactive nerves fibres also expressed TRPV1 immunoreactivity and vice versa. TRPA1 was also detected in urothelial cells at both transcriptional and protein levels. AI increased micturition frequency and reduced voiding volume. CA and NaHS produced similar changes in urodynamic parameters after disruption of the urothelial barrier with protamine sulfate. NaHS also induced calcium responses in TRPA1-expressing CHO cells, but not in untransfected cells. Conclusions: The expression of TRPA1 on C-fibre bladder afferents and urothelial cells together with the finding that intravesical TRPA1 activators initiate detrusor overactivity indicate that TRPA1 may have a role in sensory transduction in this organ. The study also highlights H2S as a TRPA1 activator potentially involved in inflammatory bladder disease. © 2007.
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| 22. |
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| 23. |
- Ye, Weihua, et al.
(författare)
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Folded Alpha Helical Putative New Proteins from Apilactobacillus kunkeei
- 2024
-
Ingår i: Journal of Molecular Biology. - : Elsevier. - 0022-2836 .- 1089-8638. ; 436:6
-
Tidskriftsartikel (refereegranskat)abstract
- The emergence of new proteins is a central question in biology. Most tertiary protein folds known to date appear to have an ancient origin, but it is clear from bioinformatic analyses that new proteins continuously emerge in all organismal groups. However, there is a paucity of experimental data on new proteins regarding their structure and biophysical properties. We performed a detailed phylogenetic analysis and identified 48 putative open reading frames in the honeybee -associated bacterium Apilactobacillus kunkeei for which no or few homologs could be identified in closely -related species, suggesting that they could be relatively new on an evolutionary time scale and represent recently evolved proteins. Using circular dichroism-, fluorescence- and nuclear magnetic resonance (NMR) spectroscopy we investigated six of these proteins and show that they are not intrinsically disordered, but populate alpha -helical dominated folded states with relatively low thermodynamic stability (0-3 kcal/mol). The NMR and biophysical data demonstrate that small new proteins readily adopt simple folded conformations suggesting that more complex tertiary structures can be continuously re -invented during evolution by fusion of such simple secondary structure elements. These findings have implications for the general view on protein evolution, where de novo emergence of folded proteins may be a common event.
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| 24. |
- Zamora, Juan Carlos, et al.
(författare)
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Considerations and consequences of allowing DNA sequence data as types of fungal taxa
- 2018
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Ingår i: IMA Fungus. - : INT MYCOLOGICAL ASSOC. - 2210-6340 .- 2210-6359. ; 9:1, s. 167-185
-
Tidskriftsartikel (refereegranskat)abstract
- Nomenclatural type definitions are one of the most important concepts in biological nomenclature. Being physical objects that can be re-studied by other researchers, types permanently link taxonomy (an artificial agreement to classify biological diversity) with nomenclature (an artificial agreement to name biological diversity). Two proposals to amend the International Code of Nomenclature for algae, fungi, and plants (ICN), allowing DNA sequences alone (of any region and extent) to serve as types of taxon names for voucherless fungi (mainly putative taxa from environmental DNA sequences), have been submitted to be voted on at the 11th International Mycological Congress (Puerto Rico, July 2018). We consider various genetic processes affecting the distribution of alleles among taxa and find that alleles may not consistently and uniquely represent the species within which they are contained. Should the proposals be accepted, the meaning of nomenclatural types would change in a fundamental way from physical objects as sources of data to the data themselves. Such changes are conducive to irreproducible science, the potential typification on artefactual data, and massive creation of names with low information content, ultimately causing nomenclatural instability and unnecessary work for future researchers that would stall future explorations of fungal diversity. We conclude that the acceptance of DNA sequences alone as types of names of taxa, under the terms used in the current proposals, is unnecessary and would not solve the problem of naming putative taxa known only from DNA sequences in a scientifically defensible way. As an alternative, we highlight the use of formulas for naming putative taxa (candidate taxa) that do not require any modification of the ICN.
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| 25. |
- Abedin, Md. Zainal, et al.
(författare)
-
An Interoperable IP based WSN for Smart Irrigation Systems
- 2017
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Konferensbidrag (refereegranskat)abstract
- Wireless Sensor Networks (WSN) have been highly developed which can be used in agriculture to enable optimal irrigation scheduling. Since there is an absence of widely used available methods to support effective agriculture practice in different weather conditions, WSN technology can be used to optimise irrigation in the crop fields. This paper presents architecture of an irrigation system by incorporating interoperable IP based WSN, which uses the protocol stacks and standard of the Internet of Things paradigm. The performance of fundamental issues of this network is emulated in Tmote Sky for 6LoWPAN over IEEE 802.15.4 radio link using the Contiki OS and the Cooja simulator. The simulated results of the performance of the WSN architecture presents the Round Trip Time (RTT) as well as the packet loss of different packet size. In addition, the average power consumption and the radio duty cycle of the sensors are studied. This will facilitate the deployment of a scalable and interoperable multi hop WSN, positioning of border router and to manage power consumption of the sensors.
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| 26. |
- Abedin, Md. Zainal, et al.
(författare)
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Performance Analysis of Anomaly Based Network Intrusion Detection Systems
- 2018
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Ingår i: Proveedings of the 43nd IEEE Conference on Local Computer Networks Workshops (LCN Workshops). - Piscataway, NJ : IEEE Computer Society. ; , s. 1-7
-
Konferensbidrag (refereegranskat)abstract
- Because of the increased popularity and fast expansion of the Internet as well as Internet of things, networks are growing rapidly in every corner of the society. As a result, huge amount of data is travelling across the computer networks that lead to the vulnerability of data integrity, confidentiality and reliability. So, network security is a burning issue to keep the integrity of systems and data. The traditional security guards such as firewalls with access control lists are not anymore enough to secure systems. To address the drawbacks of traditional Intrusion Detection Systems (IDSs), artificial intelligence and machine learning based models open up new opportunity to classify abnormal traffic as anomaly with a self-learning capability. Many supervised learning models have been adopted to detect anomaly from networks traffic. In quest to select a good learning model in terms of precision, recall, area under receiver operating curve, accuracy, F-score and model built time, this paper illustrates the performance comparison between Naïve Bayes, Multilayer Perceptron, J48, Naïve Bayes Tree, and Random Forest classification models. These models are trained and tested on three subsets of features derived from the original benchmark network intrusion detection dataset, NSL-KDD. The three subsets are derived by applying different attributes evaluator’s algorithms. The simulation is carried out by using the WEKA data mining tool.
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| 27. |
- Abedin, Md. Zainal, et al.
(författare)
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Selection of Energy Efficient Routing Protocol for Irrigation Enabled by Wireless Sensor Networks
- 2017
-
Ingår i: Proceedings of 2017 IEEE 42nd Conference on Local Computer Networks Workshops. - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 9781509065844 - 9781509065837 ; , s. 75-81
-
Konferensbidrag (refereegranskat)abstract
- Wireless Sensor Networks (WSNs) are playing remarkable contribution in real time decision making by actuating the surroundings of environment. As a consequence, the contemporary agriculture is now using WSNs technology for better crop production, such as irrigation scheduling based on moisture level data sensed by the sensors. Since WSNs are deployed in constraints environments, the life time of sensors is very crucial for normal operation of the networks. In this regard routing protocol is a prime factor for the prolonged life time of sensors. This research focuses the performances analysis of some clustering based routing protocols to select the best routing protocol. Four algorithms are considered, namely Low Energy Adaptive Clustering Hierarchy (LEACH), Threshold Sensitive Energy Efficient sensor Network (TEEN), Stable Election Protocol (SEP) and Energy Aware Multi Hop Multi Path (EAMMH). The simulation is carried out in Matlab framework by using the mathematical models of those algortihms in heterogeneous environment. The performance metrics which are considered are stability period, network lifetime, number of dead nodes per round, number of cluster heads (CH) per round, throughput and average residual energy of node. The experimental results illustrate that TEEN provides greater stable region and lifetime than the others while SEP ensures more througput.
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| 28. |
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| 29. |
- Abrams, P, et al.
(författare)
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Muscarinic receptors: their distribution and function in body systems, and the implications for treating overactive bladder
- 2006
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Ingår i: British Journal of Pharmacology. - : Wiley. - 1476-5381 .- 0007-1188. ; 148:5, s. 565-578
-
Forskningsöversikt (refereegranskat)abstract
- 1 The effectiveness of antimuscarinic agents in the treatment of the overactive bladder (OAB) syndrome is thought to arise through blockade of bladder muscarinic receptors located on detrusor smooth muscle cells, as well as on nondetrusor structures. 2 Muscarinic M-3 receptors are primarily responsible for detrusor contraction. Limited evidence exists to suggest that M-2 receptors may have a role in mediating indirect contractions and/or inhibition of detrusor relaxation. In addition, there is evidence that muscarinic receptors located in the urothelium/suburothelium and on afferent nerves may contribute to the pathophysiology of OAB. Blockade of these receptors may also contribute to the clinical efficacy of antimuscarinic agents. 3 Although the role of muscarinic receptors in the bladder, other than M3 receptors, remains unclear, their role in other body systems is becoming increasingly well established, with emerging evidence supporting a wide range of diverse functions. Blockade of these functions by muscarinic receptor antagonists can lead to similarly diverse adverse effects associated with antimuscarinic treatment, with the range of effects observed varying according to the different receptor subtypes affected. 4 This review explores the evolving understanding of muscarinic receptor functions throughout the body, with particular focus on the bladder, gastrointestinal tract, eye, heart, brain and salivary glands, and the implications for drugs used to treat OAB. The key factors that might determine the ideal antimuscarinic drug for treatment of OAB are also discussed. Further research is needed to show whether the M-3 selective receptor antagonists have any advantage over less selective drugs, in leading to fewer adverse events.
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| 30. |
- Adler, Jan-Olof, et al.
(författare)
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A broad range tagging spectrometer for the MAX-laboratory
- 1997
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Ingår i: Nuclear Instruments & Methods in Physics Research. Section A: Accelerators, Spectrometers, Detectors, and Associated Equipment. - 0167-5087. ; 388:1-2, s. 17-26
-
Tidskriftsartikel (refereegranskat)abstract
- A broad range tagging spectrometer together with a new beam transport system for photonuclear experiments at the MAX-laboratory in Lund is described. The spectrometer consists of a quadrupole followed by an Elbek-type dipole and has a large momentum acceptance. It can produce both polarized and unpolarized tagged photons in the energy range 10–80 MeV with an energy resolution of about 300 keV.
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| 31. |
- Adman, Per, et al.
(författare)
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171 forskare: ”Vi vuxna bör också klimatprotestera”
- 2019
-
Ingår i: Dagens nyheter (DN debatt). - Stockholm. - 1101-2447.
-
Tidskriftsartikel (populärvet., debatt m.m.)abstract
- DN DEBATT 26/9. Vuxna bör följa uppmaningen från ungdomarna i Fridays for future-rörelsen och protestera eftersom det politiska ledarskapet är otillräckligt. Omfattande och långvariga påtryckningar från hela samhället behövs för att få de politiskt ansvariga att utöva det ledarskap som klimatkrisen kräver, skriver 171 forskare i samhällsvetenskap och humaniora.
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| 32. |
- Afroze, Tasnim, et al.
(författare)
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Glaucoma Detection Using Inception Convolutional Neural Network V3
- 2021
-
Ingår i: Applied Intelligence and Informatics. - Cham : Springer. ; , s. 17-28
-
Konferensbidrag (refereegranskat)abstract
- Glaucoma detection is an important research area in intelligent system and it plays an important role to medical field. Glaucoma can give rise to an irreversible blindness due to lack of proper diagnosis. Doctors need to perform many tests to diagnosis this threatening disease. It requires a lot of time and expense. Sometime affected people may not have any vision loss, at the early stage of glaucoma. For detecting glaucoma, we have built a model to lessen the time and cost. Our work introduces a CNN based Inception V3 model. We used total 6072 images. Among this image 2336 were glaucomatous and 3736 were normal fundus image. For training our model we took 5460 images and for testing we took 612 images. After that we obtained an accuracy of 0.8529 and a value of 0.9387 for AUC. For comparison, we used DenseNet121 and ResNet50 algorithm and got an accuracy of 0.8153 and 0.7761 respectively.
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| 33. |
- Aggeborn, Linuz, et al.
(författare)
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Does Election Salience Affect Immigrant Voter Turnout?
- 2020
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Faced with rising levels of cross-border migration, many democratic countries have extended local voting rights to non-naturalized immigrants in recent decades. However, the low turnout of enfranchised immigrants in these elections has come as a disappointment to the advocates of such reforms. In this study, we examine whether the low turnout can be explained by the low salience of local elections. Based on a regression discontinuity design and using high-quality Swedish registry data, we find this to be the case. According to our results, the average likelihood of voting increases by 10-20 percentage points once immigrants become eligible to vote in national elections. We demonstrate too that this effect is not driven by the acquisition of citizenship per se, and that the individual characteristics of immigrants cannot explain their overall lower rate of voter turnout.
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| 34. |
- Aggeborn, Linuz, 1986-, et al.
(författare)
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Granting Immigrants the Right to Vote in National Elections : Empirical Evidence from Swedish Administrative Data
- 2024
-
Ingår i: British Journal of Political Science. - : Cambridge University Press. - 0007-1234 .- 1469-2112. ; 54:3, s. 712-729
-
Tidskriftsartikel (refereegranskat)abstract
- Faced with rising levels of cross-border migration, many countries have extended local voting rights to non-citizen residents. However, empirical evidence indicates that voter turnout among non-naturalized immigrants is lower when compared to citizens. This raises the question of how to explain this difference. A common answer is that the low turnout rates of non-citizen residents are primarily due to the socio-economic composition of this group and the challenges involved in adapting to a new political system. An alternative but less discussed possibility is that the low turnout concerns the nature of the elections. Hence, we examine whether the turnout of non-citizens is hampered because they are only allowed to partake in local elections. Based on a regression discontinuity design (RDD) using Swedish administrative data, we find that turnout could increase by 10-20 percentage points if the voting rights of non-citizens were extended to the national level.
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| 35. |
- Ahmed, Faisal, et al.
(författare)
-
An Evolutionary Belief Rule-Based Clinical Decision Support System to Predict COVID-19 Severity under Uncertainty
- 2021
-
Ingår i: Applied Sciences. - Basel, Switzerland : MDPI. - 2076-3417. ; 11:13
-
Tidskriftsartikel (refereegranskat)abstract
- Accurate and rapid identification of the severe and non-severe COVID-19 patients is necessary for reducing the risk of overloading the hospitals, effective hospital resource utilization, and minimizing the mortality rate in the pandemic. A conjunctive belief rule-based clinical decision support system is proposed in this paper to identify critical and non-critical COVID-19 patients in hospitals using only three blood test markers. The experts’ knowledge of COVID-19 is encoded in the form of belief rules in the proposed method. To fine-tune the initial belief rules provided by COVID-19 experts using the real patient’s data, a modified differential evolution algorithm that can solve the constraint optimization problem of the belief rule base is also proposed in this paper. Several experiments are performed using 485 COVID-19 patients’ data to evaluate the effectiveness of the proposed system. Experimental result shows that, after optimization, the conjunctive belief rule-based system achieved the accuracy, sensitivity, and specificity of 0.954, 0.923, and 0.959, respectively, while for disjunctive belief rule base, they are 0.927, 0.769, and 0.948. Moreover, with a 98.85% AUC value, our proposed method shows superior performance than the four traditional machine learning algorithms: LR, SVM, DT, and ANN. All these results validate the effectiveness of our proposed method. The proposed system will help the hospital authorities to identify severe and non-severe COVID-19 patients and adopt optimal treatment plans in pandemic situations.
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| 36. |
- Ahmed, Faisal, et al.
(författare)
-
Comparative Performance of Tree Based Machine Learning Classifiers in Product Backorder Prediction
- 2023. - 1
-
Ingår i: Intelligent Computing & Optimization. - Cham : Springer. ; , s. 572-584
-
Bokkapitel (refereegranskat)abstract
- Early prediction of whether a product will go to backorder or not is necessary for optimal management of inventory that can reduce the losses in sales, establish a good relationship between the supplier and customer and maximize the revenues. In this study, we have investigated the performance and effectiveness of tree based machine learning algorithms to predict the backorder of a product. The research methodology consists of preprocessing of data, feature selection using statistical hypothesis test, imbalanced learning using the random undersampling method and performance evaluating and comparing of four tree based machine learning algorithms including decision tree, random forest, adaptive boosting and gradient boosting in terms of accuracy, precision, recall, f1-score, area under the receiver operating characteristic curve and area under the precision and recall curve. Three main findings of this study are (1) random forest model without feature selection and with random undersampling method achieved the highest performance in terms of all performance measure metrics, (2) feature selection cannot contribute to the performance enhancement of the tree based classifiers, and (3) random undersampling method significantly improves performance of tree based classifiers in product backorder prediction.
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| 37. |
- Ahmed, Faisal, et al.
(författare)
-
Machine Learning-Based Tomato Leaf Disease Diagnosis Using Radiomics Features
- 2023
-
Ingår i: Proceedings of the Fourth International Conference on Trends in Computational and Cognitive Engineering - TCCE 2022. - : Springer Science and Business Media Deutschland GmbH. - 9789811994821 - 9789811994838 ; , s. 25-35
-
Konferensbidrag (refereegranskat)abstract
- Tomato leaves can be infected with various infectious viruses and fungal diseases that drastically reduce tomato production and incur a great economic loss. Therefore, tomato leaf disease detection and identification are crucial for maintaining the global demand for tomatoes for a large population. This paper proposes a machine learning-based technique to identify diseases on tomato leaves and classify them into three diseases (Septoria, Yellow Curl Leaf, and Late Blight) and one healthy class. The proposed method extracts radiomics-based features from tomato leaf images and identifies the disease with a gradient boosting classifier. The dataset used in this study consists of 4000 tomato leaf disease images collected from the Plant Village dataset. The experimental results demonstrate the effectiveness and applicability of our proposed method for tomato leaf disease detection and classification.
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| 38. |
- Ahmed, Mumtahina, et al.
(författare)
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Explainable Text Classification Model for COVID-19 Fake News Detection
- 2022
-
Ingår i: Journal of Internet Services and Information Security (JISIS). - : Innovative Information Science & Technology Research Group. - 2182-2069 .- 2182-2077. ; 12:2, s. 51-69
-
Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence has achieved notable advances across many applications, and the field is recently concerned with developing novel methods to explain machine learning models. Deep neural networks deliver the best performance accuracy in different domains, such as text categorization, image classification, and speech recognition. Since the neural network models are black-box types, they lack transparency and explainability in predicting results. During the COVID-19 pandemic, Fake News Detection is a challenging research problem as it endangers the lives of many online users by providing misinformation. Therefore, the transparency and explainability of COVID-19 fake news classification are necessary for building the trustworthiness of model prediction. We proposed an integrated LIME-BiLSTM model where BiLSTM assures classification accuracy, and LIME ensures transparency and explainability. In this integrated model, since LIME behaves similarly to the original model and explains the prediction, the proposed model becomes comprehensible. The performance of this model in terms of explainability is measured by using Kendall’s tau correlation coefficient. We also employ several machine learning models and provide a comparison of their performances. Therefore, we analyzed and compared the computation overhead of our proposed model with the other methods because the model takes the integrated strategy.
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| 39. |
- Ahmed, Shamim, et al.
(författare)
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A Comparative Analysis of LIME and SHAP Interpreters with Explainable ML-Based Diabetes Predictions
- 2024
-
Ingår i: IEEE Access. - : IEEE. - 2169-3536.
-
Tidskriftsartikel (refereegranskat)abstract
- Explainable artificial intelligence is beneficial in converting opaque machine learning models into transparent ones and outlining how each one makes decisions in the healthcare industry. To comprehend the variables that affect decision-making regarding diabetes prediction that can be accounted for by model-agnostic techniques. In this project, we investigate how to generate local and global explanations for a machine-learning model built on a logistic regression architecture. We trained on 253,680 survey responses from diabetes patients using the explainable AI techniques LIME and SHAP. LIME and SHAP were then used to explain the predictions produced by the logistic regression and Random forest-based model on the validation and test sets.With a discussion of future work, the comparative analysis and discussion of various experimental findings between LIME and SHAP are provided, along with their strengths and weaknesses in terms of interpretation. With a high accuracy of 86% on the test set, we used LR architecture with a spatial attention mechanism, demonstrating the possibility of merging machine learning and explainable AI to improve diabetes prediction, diagnosis, and treatment.We also focus on various applications, difficulties, and probable future directions of machine learning models for LIME and SHAP interpreters.
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| 40. |
- Ahmed, Tawsin Uddin, et al.
(författare)
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A Deep Learning Approach with Data Augmentation to Recognize Facial Expressions in Real Time
- 2022
-
Ingår i: Proceedings of the Third International Conference on Trends in Computational and Cognitive Engineering. - Singapore : Springer Nature. ; , s. 487-500
-
Konferensbidrag (refereegranskat)abstract
- The enormous use of facial expression recognition in various sectors of computer science elevates the interest of researchers to research this topic. Computer vision coupled with deep learning approach formulates a way to solve several real-world problems. For instance, in robotics, to carry out as well as to strengthen the communication between expert systems and human or even between expert agents, it is one of the requirements to analyze information from visual content. Facial expression recognition is one of the trending topics in the area of computer vision. In our previous work, a facial expression recognition system is delivered which can classify an image into seven universal facial expressions—angry, disgust, fear, happy, neutral, sad, and surprise. This is the extension of our previous research in which a real-time facial expression recognition system is proposed that can recognize a total of ten facial expressions including the previous seven facial expressions and additional three facial expressions—mockery, think, and wink from video streaming data. After model training, the proposed model has been able to gain high validation accuracy on a combined facial expression dataset. Moreover, the real-time validation of the proposed model is also promising.
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| 41. |
- Ahmed, Tawsin Uddin, et al.
(författare)
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An Integrated Deep Learning and Belief Rule Base Intelligent System to Predict Survival of COVID-19 Patient under Uncertainty
- 2022
-
Ingår i: Cognitive Computation. - : Springer. - 1866-9956 .- 1866-9964. ; 14:2, s. 660-676
-
Tidskriftsartikel (refereegranskat)abstract
- The novel Coronavirus-induced disease COVID-19 is the biggest threat to human health at the present time, and due to the transmission ability of this virus via its conveyor, it is spreading rapidly in almost every corner of the globe. The unification of medical and IT experts is required to bring this outbreak under control. In this research, an integration of both data and knowledge-driven approaches in a single framework is proposed to assess the survival probability of a COVID-19 patient. Several neural networks pre-trained models: Xception, InceptionResNetV2, and VGG Net, are trained on X-ray images of COVID-19 patients to distinguish between critical and non-critical patients. This prediction result, along with eight other significant risk factors associated with COVID-19 patients, is analyzed with a knowledge-driven belief rule-based expert system which forms a probability of survival for that particular patient. The reliability of the proposed integrated system has been tested by using real patient data and compared with expert opinion, where the performance of the system is found promising.
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| 42. |
- Akkaya, Kemal, et al.
(författare)
-
Message from the demonstrations chair
- 2014
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- It is my pleasure to welcome you to the sixth Demonstration Session at the IEEE Conference on Local Computer Networks (LCN) 2014. We were looking for demonstrations for all topics covered by the main conference as well as all the workshops held in conjunction with the conference. The technical demonstrations were strongly encouraged to show innovative and original research. The main purpose of the demo session is to provide demonstrations that validate important research issues and/or show innovative prototypes.
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| 43. |
- Akter, Mehenika, et al.
(författare)
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Hand-Drawn Emoji Recognition using Convolutional Neural Network
- 2021
-
Ingår i: Proceedings of 2020 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE). - : IEEE. ; , s. 147-152
-
Konferensbidrag (refereegranskat)abstract
- Emojis are like small icons or images used to express our sentiments or feelings via text messages. They are extensively used in different social media platforms like Facebook, Twitter, Instagram etc. We considered hand-drawn emojis to classify them into 8 classes in this research paper. Hand-drawn emojis are the emojis drawn in any digital platform or in just a paper with a pen. This paper will enable the users to classify the hand-drawn emojis so that they could use them in any social media without any confusion. We made a local dataset of 500 images for each class summing a total of 4000 images of hand-drawn emojis. We presented a system which could recognise and classify the emojis into 8 classes with a convolutional neural network model. The model could favorably recognise as well as classify the hand-drawn emojis with an accuracy of 97%. Some pre-trained CNN models like VGG16, VGG19, ResNet50, MobileNetV2, InceptionV3 and Xception are also trained on the dataset to compare the accuracy and check whether they are better than the proposed one. On the other hand, machine learning models like SVM, Random Forest, Adaboost, Decision Tree and XGboost are also implemented on the dataset.
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| 44. |
- Akter, Mehenika, et al.
(författare)
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Mosquito Classification Using Convolutional Neural Network with Data Augmentation
- 2021
-
Ingår i: Intelligent Computing and Optimization. - Cham : Springer Nature. ; , s. 865-879
-
Konferensbidrag (refereegranskat)abstract
- Mosquitoes are responsible for the most number of deaths every year throughout the world. Bangladesh is also a big sufferer of this problem. Dengue, malaria, chikungunya, zika, yellow fever etc. are caused by dangerous mosquito bites. The main three types of mosquitoes which are found in Bangladesh are aedes, anopheles and culex. Their identification is crucial to take the necessary steps to kill them in an area. Hence, a convolutional neural network (CNN) model is developed so that the mosquitoes could be classified from their images. We prepared a local dataset consisting of 442 images, collected from various sources. An accuracy of 70% has been achieved by running the proposed CNN model on the collected dataset. However, after augmentation of this dataset which becomes 3,600 images, the accuracy increases to 93%. We also showed the comparison of some methods with the CNN method which are VGG-16, Random Forest, XGboost and SVM. Our proposed CNN method outperforms these methods in terms of the classification accuracy of the mosquitoes. Thus, this research forms an example of humanitarian technology, where data science can be used to support mosquito classification, enabling the treatment of various mosquito borne diseases.
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| 45. |
- Akter, Nasrin, et al.
(författare)
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Brain Tumor Classification using Transfer Learning from MRI Images
- 2022
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Ingår i: Proceedings of International Conference on Fourth Industrial Revolution and Beyond 2021. - Singapore : Springer. ; , s. 575-587
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Bokkapitel (refereegranskat)abstract
- One of the most vital parts of medical image analysis is the classification of brain tumors. Because tumors are thought to be origins to cancer, accurate brain tumor classification can save lives. As a result, CNN (Convolutional Neural Network)-based techniques for classifying brain cancers are frequently employed. However, there is a problem: CNNs are exposed to vast amounts of training data in order to produce good performance. This is where transfer learning enters into the picture. We present a 4-class transfer learning approach for categorizing Glioma, Meningioma, and Pituitary tumors and non-tumors in this study. The three most prevalent types of brain tumors are glioma, meningioma, and pituitary tumors. Our presented method, which employs the theory of transfer learning, utilizes a pre-trained InceptionResnetV1 method for classifying brain MRI images by extracting features from them using the softmax classifier method. The proposed approach outperforms all prior techniques with a mean classification accuracy of 93.95%. For the evaluation of our method we use kaggle dataset. Precision, recall, and F-score are one of the key performance metrics employed in this study.
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| 46. |
- Akter, Shamima, et al.
(författare)
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A New Crossover Technique to Improve Genetic Algorithm and Its Application to TSP
- 2019
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Ingår i: Proceedings of 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE). - : IEEE. - 9781538691113
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Konferensbidrag (refereegranskat)abstract
- Optimization problem like Travelling Salesman Problem (TSP) can be solved by applying Genetic Algorithm (GA) to obtain perfect approximation in time. In addition, TSP is considered as a NP-hard problem as well as an optimal minimization problem. Selection, crossover and mutation are the three main operators of GA. The algorithm is usually employed to find the optimal minimum total distance to visit all the nodes in a TSP. Therefore, the research presents a new crossover operator for TSP, allowing the further minimization of the total distance. The proposed crossover operator consists of two crossover point selection and new offspring creation by performing cost comparison. The computational results as well as the comparison with available well-developed crossover operators are also presented. It has been found that the new crossover operator produces better results than that of other cross-over operators.
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| 47. |
- Al Arafat, Md. Mahedi, et al.
(författare)
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Neural Network-Based Obstacle and Pothole Avoiding Robot
- 2023
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Ingår i: Proceedings of the Fourth International Conference on Trends in Computational and Cognitive Engineering - TCCE 2022. - : Springer Science and Business Media Deutschland GmbH. - 9789811994821 - 9789811994838 ; , s. 173-184
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Konferensbidrag (refereegranskat)abstract
- The main challenge of any mobile robot is to detect and avoid obstacles and potholes. This paper presents the development and implementation of a novel mobile robot. An Arduino Uno is used as the processing unit of the robot. A Sharp distance measurement sensor and Ultrasonic sensors are used for taking inputs from the environment. The robot trains a neural network based on a feedforward backpropagation algorithm to detect and avoid obstacles and potholes. For that purpose, we have used a truth table. Our experimental results show that our developed system can ideally detect and avoid obstacles and potholes and navigate environments.
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| 48. |
- Al Banna, Md. Hasan, et al.
(författare)
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Attention-based Bi-directional Long-Short Term Memory Network for Earthquake Prediction
- 2021
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 9, s. 56589-56603
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Tidskriftsartikel (refereegranskat)abstract
- An earthquake is a tremor felt on the surface of the earth created by the movement of the major pieces of its outer shell. Till now, many attempts have been made to forecast earthquakes, which saw some success, but these attempted models are specific to a region. In this paper, an earthquake occurrence and location prediction model is proposed. After reviewing the literature, long short-term memory (LSTM) is found to be a good option for building the model because of its memory-keeping ability. Using the Keras tuner, the best model was selected from candidate models, which are composed of combinations of various LSTM architectures and dense layers. This selected model used seismic indicators from the earthquake catalog of Bangladesh as features to predict earthquakes of the following month. Attention mechanism was added to the LSTM architecture to improve the model’s earthquake occurrence prediction accuracy, which was 74.67%. Additionally, a regression model was built using LSTM and dense layers to predict the earthquake epicenter as a distance from a predefined location, which provided a root mean square error of 1.25.
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| 49. |
- Alakärppä, Ismo, et al.
(författare)
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NIMO overall architecture and service enablers
- 2014
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This article describes the architecture and service enablers developed in the NIMO project. Furthermore, it identifies future challenges and knowledge gaps in upcoming ICT service development for public sector units empowering citizens with enhanced tools for interaction and participation. We foresee crowdsourced applications where citizens contribute with dynamic, timely and geographically spread gathered information.
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| 50. |
- Alam, Md. Eftekhar, et al.
(författare)
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An IoT-Belief Rule Base Smart System to Assess Autism
- 2018
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Ingår i: Proceedings of the 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT 2018). - : IEEE. - 9781538682791 - 9781538682807 ; , s. 671-675
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Konferensbidrag (refereegranskat)abstract
- An Internet-of-Things (IoT)-Belief Rule Base (BRB) based hybrid system is introduced to assess Autism spectrum disorder (ASD). This smart system can automatically collect sign and symptom data of various autistic children in realtime and classify the autistic children. The BRB subsystem incorporates knowledge representation parameters such as rule weight, attribute weight and degree of belief. The IoT-BRB system classifies the children having autism based on the sign and symptom collected by the pervasive sensing nodes. The classification results obtained from the proposed IoT-BRB smart system is compared with fuzzy and expert based system. The proposed system outperformed the state-of-the-art fuzzy system and expert system.
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