The factory of the future is steering away from conventional assembly line production with sequential conveyor technology, towards flexible assembly lines, where products dynamically move between work-cells. Flexible assembly lines are significantly more complex to plan compared to sequential lines. Therefore there is an increased need for autonomously generating flexible robot-centered assembly plans. The novel Autonomous Constraint Generation (ACG) method presented here will generate a dynamic assembly plan starting from an initial assembly sequence, which is easier to program. Using a physics simulator, variations of the work-cell configurations from the initial sequence are evaluated and assembly constraints are autonomously deduced. Based on that the method can generate a complete assembly graph that is specific to the robot and work-cell in which it was initially programmed, taking into account both part and robot collisions. A major advantage is that it scales only linearly with the number of parts in the assembly. The method is compared to previous research by applying it to the Cranfield Benchmark problem. Results show a 93% reduction in planning time compared to using Reinforcement Learning Search. Furthermore, it is more accurate compared to generating the assembly graph from human interaction. Finally, applying the method to a real life industrial use case proves that a valid assembly graph is generated within reasonable time for industry.
Background: The genetic disorder tuberous sclerosis complex (TSC) is frequently accompanied by the development of neuropsychiatric disorders, including autism spectrum disorder and intellectual disability, with varying degrees of impairment. These co-morbidities in TSC have been linked to the structural brain abnormalities, such as cortical tubers, and recurrent epileptic seizures (in 70-80% cases). Previous transcriptomic analysis of cortical tubers revealed dysregulation of genes involved in cell adhesion in the brain, which may be associated with the neurodevelopmental deficits in TSC. In this study we aimed to investigate the expression of one of these genes - cell-adhesion molecule contactin-3. Methods: Reverse transcription quantitative polymerase chain reaction for the contactin-3 gene (CNTN3) was performed in resected cortical tubers from TSC patients with drug-resistant epilepsy (n = 35, age range: 1-48 years) and compared to autopsy-derived cortical control tissue (n = 27, age range: 0-44 years), as well as by western blot analysis of contactin-3 (n = 7 vs n = 7, age range: 0-3 years for both TSC and controls) and immunohistochemistry (n = 5 TSC vs n = 4 controls). The expression of contactin-3 was further analyzed in fetal and postnatal control tissue by western blotting and in-situ hybridization, as well as in the SH-SY5Y neuroblastoma cell line differentiation model in vitro. Results: CNTN3 gene expression was lower in cortical tubers from patients across a wide range of ages (fold change = - 0.5, p < 0.001) as compared to controls. Contactin-3 protein expression was lower in the age range of 0-3 years old (fold change = - 3.8, p < 0.001) as compared to the age-matched controls. In control brain tissue, contactin-3 gene and protein expression could be detected during fetal development, peaked around birth and during infancy and declined in the adult brain. CNTN3 expression was induced in the differentiated SH-SY5Y neuroblastoma cells in vitro (fold change = 6.2, p < 0.01). Conclusions: Our data show a lower expression of contactin-3 in cortical tubers of TSC patients during early postnatal period as compared to controls, which may affect normal brain development and might contribute to neuropsychiatric co-morbidities observed in patients with TSC.
This work provides a data-oriented overview of the rapidly growing research field covering machine learning (ML) applied to predicting electrochemical corrosion. Our main aim was to determine which ML models have been applied and how well they performed depending on the corrosion topic considered. From an extensive review of corrosion articles presenting comparable performance metrics, a ‘Machine learning for corrosion database’ was created, guiding corrosion experts and model developers in their applications of ML to corrosion. Potential research gaps and recommendations are discussed, and a broad perspective for future research paths is provided.
Background Tuberous sclerosis complex (TSC)–associated neuropsychiatric disorders (TAND) is an umbrella term for the behavioural, psychiatric, intellectual, academic, neuropsychological and psychosocial manifestations of TSC. Although TAND affects 90% of individuals with TSC during their lifetime, these manifestations are relatively under-assessed, under-treated and under-researched. We performed a comprehensive scoping review of all TAND research to date (a) to describe the existing TAND research landscape and (b) to identify knowledge gaps to guide future TAND research. Methods The study was conducted in accordance with stages outlined within the Arksey and O’Malley scoping review framework. Ten research questions relating to study characteristics, research design and research content of TAND levels and clusters were examined. Results Of the 2841 returned searches, 230 articles published between 1987 and 2020 were included (animal studies = 30, case studies = 47, cohort studies = 153), with more than half published since the term TAND was coined in 2012 (118/230; 51%). Cohort studies largely involved children and/or adolescents (63%) as opposed to older adults (16%). Studies were represented across 341 individual research sites from 45 countries, the majority from the USA (89/341; 26%) and the UK (50/341; 15%). Only 48 research sites (14%) were within low–middle income countries (LMICs). Animal studies and case studies were of relatively high/high quality, but cohort studies showed significant variability. Of the 153 cohort studies, only 16 (10%) included interventions. None of these were non-pharmacological, and only 13 employed remote methodologies (e.g. telephone interviews, online surveys). Of all TAND clusters, the autism spectrum disorder–like cluster was the most widely researched (138/230; 60%) and the scholastic cluster the least (53/200; 27%). Conclusions Despite the recent increase in TAND research, studies that represent participants across the lifespan, LMIC research sites and non-pharmacological interventions were identified as future priorities. The quality of cohort studies requires improvement, to which the use of standardised direct behavioural assessments may contribute. In human studies, the academic level in particular warrants further investigation. Remote technologies could help to address many of the TAND knowledge gaps identified.
The hobo syndrome (i.e., the wanderlust someone posits to frequently change employers) has a behavioural (i.e., frequent job-quitting behaviour) and an attitudinal dimension (i.e., attitudes towards frequent job-quitting). Across two studies, we examine both dimensions across 348 career starters. By doing so, we expand our understanding of Ghiselli’s hobo syndrome in two ways: (a) we explore the effect of both ‘bright’- and ‘dark’-side personality traits on each dimension of the hobo syndrome, and (b) using longitudinal research, we shed light on the role of each dimension of the hobo syndrome in predicting actual job-quitting behaviour. Data for both studies were gathered through a survey and LinkedIn. Results of regression analyses show that psychopathy is associated with both dimensions of the hobo syndrome. Conversely, openness to experience is only associated with the attitudinal dimension, while agreeableness and extraversion are only associated with the behavioural dimension. Finally, we find that only the behavioural dimension is associated with the length of tenure with the first employer, suggesting that one’s intentions to frequent job-quitting are more important in predicting one’s actual job-quitting behaviour than one’s attitudes towards frequent job-quitting.
Background A previous European Headache Federation (EHF) guideline addressed the use of monoclonal antibodies targeting the calcitonin gene-related peptide (CGRP) pathway to prevent migraine. Since then, randomized controlled trials (RCTs) and real-world evidence have expanded the evidence and knowledge for those treatments. Therefore, the EHF panel decided to provide an updated guideline on the use of those treatments. Methods The guideline was developed following the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) approach. The working group identified relevant questions, performed a systematic review and an analysis of the literature, assessed the quality of the available evidence, and wrote recommendations. Where the GRADE approach was not applicable, expert opinion was provided. Results We found moderate to high quality of evidence to recommend eptinezumab, erenumab, fremanezumab, and galcanezumab in individuals with episodic and chronic migraine. For several important clinical questions, we found not enough evidence to provide evidence-based recommendations and guidance relied on experts’ opinion. Nevertheless, we provided updated suggestions regarding the long-term management of those treatments and their place with respect to the other migraine preventatives. Conclusion Monoclonal antibodies targeting the CGRP pathway are recommended for migraine prevention as they are effective and safe also in the long-term.
We perform a simultaneous test for several rational and behavioral factors known to affect the uptake of life annuities in a sample of Americans. We also investigate whether analysts’ short-term stock market expectations affect the decision to annuitize retirement wealth. We find that facing such expectations without trusting them lowers the purchase of annuities. Moreover, we find that individuals who trusted financial analysts’ expectations were less likely to purchase annuities. We attribute these findings to the availability heuristic and present bias, respectively. Finally, we discuss the mediating role of annuity antipathy. Our results provide guidance for policy-makers and annuity providers and offer venues for future research.
Modern sealing components are used in a wide range of industrial processes. The recent global attention for reducing emission of environmentally harmful substances motivates gasket manufacturers to quantify the performance of sealing gaskets. We investigate the use of fiber Bragg grating sensors for measuring seating stress on a spiral wound gasket. The fiber-optic sensors are integrated in the gasket, following a particular instrumentation strategy. The instrumented gaskets are first installed in a standardized flange following a state-of-the-art installation protocol. Then, the gaskets are unloaded with a particular unloading strategy to simulate sealing performance loss. We compare the load in the mounting bolts during the (un)loading procedure with the response of the FBG sensors in the gasket and find a high correlation. We thus evidence the potential of fiber-optic sensors for measurements during installation as well as monitoring of sealing gaskets serving the accountability of these components.
Spruce is the most resistant type of lignocellulosic material to anaerobic digestion. Different parts of spruce tree, i.e., leaves, wood, branches, bark, fruit, and mixtures of these parts, were pretreated using the leading pretreatments, i.e., concentrated phosphoric acid, dilute sulfuric acid, and ethanolic organosolv pretreatment, to improve biogas production. The pretreatment effects on methane yield from both solid and liquid fractions of the pretreatments were evaluated. Different parts of the tree showed different behaviors. The maximum methane yields from the pretreated solids were obtained after phosphoric acid pretreatment, which yielded methane yields of 211.7 and 225.5 mL per g volatile solids (VS) of pretreated spruce leaves and mixture, respectively. The improvements were related to opened-up structure, crystallinity reduction, and delignification. Sulfuric acid pretreatment improved biomethane yield from liquids, but not solids. Moreover, organosolv pretreatment improved the yield from solids, but not wood, bark, and the mixture. The maximum methane production yield was 245.3 NmL CH4/gVS which was obtained from the organosolv liquor of spruce leaves. The highest overall methane production (252.9 L per Kg) was gained from the whole solid and liquid fractions from organosolv pretreatment of leaves. This methane yield corresponded to 2.4-fold improvement compared to that of the untreated leaves (107 NmL CH4/gVS). Thus, leaves and branches are less recalcitrant parts and do not need severe pretreatment, while bark and wood are the most recalcitrant parts and required severe pretreatment like concentrated phosphoric acid. Moreover, the mixture of all parts also required severe pretreatment for efficient biogas production.
Multivariate functions emerge naturally in a wide variety of data-driven models. Popular choices are expressions in the form of basis expansions or neural networks. While highly effective, the resulting functions tend to be hard to interpret, in part because of the large number of required parameters. Decoupling techniques aim at providing an alternative representation of the nonlinearity. The so-called decoupled form is often a more efficient parameterisation of the relationship while being highly structured, favouring interpretability. In this work two new algorithms, based on filtered tensor decompositions of first order derivative information are introduced. The method returns nonparametric estimates of smooth decoupled functions. Direct applications are found in, i.a. the fields of nonlinear system identification and machine learning.
In this paper, oppositeness in spherical buildings is used to define an EKR-problem for flags in projective and polar spaces. A novel application of the theory of buildings and Iwahori-Hecke algebras is developed to prove sharp upper bounds for EKR-sets of flags. In this framework, we can reprove and generalize previous upper bounds for EKR-problems in projective and polar spaces. The bounds are obtained by the application of the Delsarte-Hoffman coclique bound to the opposition graph. The computation of its eigenvalues is due to earlier work by Andries Brouwer and an explicit algorithm is worked out. For the classical geometries, the execution of this algorithm boils down to elementary combinatorics. Connections to building theory, Iwahori-Hecke algebras, classical groups and diagram geometries are briefly discussed. Several open problems are posed throughout and at the end.
In order for the Internet Governance ecosystem to work effectively, it requires a variety of expertise and advice from different sectors and backgrounds. Drawing on the public Internet Governance Forum (IGF) participation lists from 2006 to 2019, this paper analyses how individual participants chose to identify themselves in the given frameworks applied across the IGFs, and how they ‘travel’ through the Internet Governance ecosystem over successive fora. Identifying 18,968 unique IGF participants from 2006 to 2019, representing 7326 unique organisations, this paper thus provides an unprecedented level of detail as to who is present in multistakeholder discussions. It sets the scene for a more reflective discussion on the inclusivity and effectiveness of the multistakeholder model pursued at the IGF and engages with literature in the field of stakeholder mobility and stakeholder interests, opening up potential for further research on the legitimacy of multistakeholderism.
Bioethanol was produced from wheat straw by a concentrated alkali pretreatment at specific conditions with a yield of 88 g ethanol per 1 kg of dry straw. To economically improve the bioethanol production process and valorize residual waste, the lignin-rich solid waste particles were isolated from the pretreatment waste liquid and characterized, and finally employed to reinforce starch-based biodegradable film. The solid waste particles were characterized by chemical analysis, dynamic light scattering (DLS), field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). As bioethanol byproducts, they have mainly contained 88 wt% lignin. The average diameter of the uniform spherical shape extracted particles was determined to be 160 nm by DLS and FESEM. The presence of syringyl and guaiacyl rings were conducted by FTIR. Due to their suitable mechanical performance and thermal resistance, the lignin nanoparticles were employed as reinforcement for green biodegradable starch films. To prepare films, suspensions containing starch, glycerol, and different concentrations of lignin (0–30 wt%) were molded by the solution casting process. The starch-lignin composite films were analyzed by mechanical tensile tests, crystallinity analysis, FESEM, and thermal analysis. From the results, it was found that by adding 20 wt% lignin particles, the tensile strength and modulus of the pure starch film were increased from 4.8 and 0.9–8 and 2.4 MPa which can be partially explained due to crystallinity enhancement of film from 29 % to 48.3 %. In addition, the thermal resistance and the hydrophilic property of the composite films were enhanced due to lignin nanoparticle presence. It can be concluded that the isolation of lignin nanoparticles as waste solid in bioethanol production could be considered as a promising stage in the sustainability of second-generation products from the bioethanol production process.
The present work advances the PC-transport approach in the context of Large Eddy Simulation (LES) of turbulent combustion. Accurate modeling of combustion systems requires large kinetic mechanisms. However, realistic high-fidelity simulations of turbulent reacting flows still represent a big challenge on the current computational tools. Therefore, a parameterization of the thermo-chemical state-space using a reduced number of variables is needed. To this end, the potential offered by Principal Component Analysis (PCA) in identifying low-dimensional manifolds is very appealing. The present paper extends the PC-transport approach, coupled with Gaussian Process Regression (GPR), to a lifted methane/air flame in LES. Previous investigations by the authors showed the great potential of the PC-GPR model in the context of Sandia flames. This study investigated some key features of the model: the sensitivity to the training data set and the scaling methods . To this end, two different canonical reactors were used: unsteady counter-flow laminar flames (CFLF) and unsteady perfectly stirred reactor (PSR). Moreover, the authors proposes an approach to address the issue of data density inherent to large numerical data sets, by means of a kernel density weighting of the data set before applying PCA. Finally, a subgrid scale (SGS) closure model was coupled to the PC-transport approach to treat complex turbulence/chemistry interactions.
From 2022 onwards the Post-2020 Global Biodiversity Framework (GBF) of the Convention on Biological Diversity will guide biodiversity conservation actions worldwide, which includes mainstreaming biodiversity into a wide range of activities, sectors and policies. Biodiversity mainstreaming in development cooperation is particularly relevant given the direct dependence of many communities in the Global South on biodiversity and on the benefits it provides. We conducted a Delphi survey among development cooperation practitioners at the aid provider (donor) side, to gain insight into current and future (post-2020 Global Biodiversity Framework) biodiversity mainstreaming and its monitoring. Our results demonstrate that despite efforts towards biodiversity mainstreaming and its monitoring, biodiversity mainstreaming indicators remain inconsistent and difficult to compare. The lack of biodiversity data, as well as their low accessibility and suboptimal use, and the inherent complexity of addressing biodiversity loss are considered key challenges. Respondents indicated that they strongly orient their own biodiversity mainstreaming and monitoring approaches towards international biodiversity governance dynamics. We conclude that, at least on paper, the indicator ambitions of the Post-2020 Global Biodiversity Framework are in line with the expectations and challenges of aid providers with respect to biodiversity mainstreaming. However, future effective mainstreaming of biodiversity requires indicator-based monitoring, exchange of good practices among aid partners, and a continued focus on awareness-raising regarding the linkages between biodiversity conservation and poverty reduction.
Objective To evaluate the effect of irregular screening behaviour on the risk of advanced stage breast cancer at diagnosis in Flanders. Methods All women aged 50–69 who were invited to the organized breast cancer screening and diagnosed with breast cancer before age 72 from 2001 to 2018 were included. All prevalent screen and interval cancers within 2 years of a prevalent screen were excluded. Screening behaviour was categorized based on the number of invitations and performed screenings. Four groups were defined: regular, irregular, only-once, and never attenders. Advanced stage cancer was defined as a stage III + breast cancer. The association between screening regularity and breast cancer stage at diagnosis was evaluated in multivariable logistic regression models, taking age of diagnosis and socio-economic status into account. Results In total 13.5% of the 38,005 breast cancer cases were diagnosed at the advanced stage. Compared to the regular attenders, the risk of advanced stage breast cancer for the irregular attenders, women who participated only-once, and never attenders was significantly higher with ORadjusted:1.17 (95%CI:1.06–1.29) and ORadjusted:2.18 (95%CI:1.94–2.45), and ORadjusted:5.95 (95%CI:5.33–6.65), respectively. Conclusions In our study, never attenders were nearly six times more likely to be diagnosed with advanced stage breast cancer than regular attenders, which was much higher than the estimates published thus far. An explanation for this is that the ever screened women is a heterogeneous group regarding the participation profiles which also includes irregular and only-once attenders. The benefit of regular screening should be informed to all women invited for screening.
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