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Online resources represent an important avenue to identify and support individuals who may be experiencing symptoms of psychosis but have yet to engage in care. Understanding the experiences and needs of this group is critical to inform outreach for early psychosis and improve outcomes by addressing barriers to early treatment.The authors conducted a retrospective, explorative, cross-sectional analysis by using data collected by Mental Health America as part of their online psychosis screening and support program. Data included scores from the Prodromal Questionnaire-Brief, basic demographic information, and respondents' plans for next steps.Of 120,937 respondents, most (82.1%) reported distressing psychosis-like experiences at levels sufficient to merit a referral to specialty care for additional evaluation. However, only 17.1% planned to seek treatment as a next step, with most (53.6%) wanting instead more information. Higher distress was only weakly associated with the plan to seek treatment. In the multivariable analysis, respondents who were younger; lesbian, gay, bisexual, transgender, or queer; or Native American or who had lower income reported the greatest symptom-related distress. Younger and higher-income respondents were less likely to plan to seek treatment next. Across race-ethnicity, African Americans were most likely to plan to seek treatment.Most respondents reported that psychosis-like experiences caused significant distress, but they did not plan to seek treatment next. Addressing this treatment gap requires careful consideration regarding what services individuals want, how services should be presented, and what barriers may limit help seeking. These steps are critical to improve access to early intervention for individuals with psychosis spectrum disorders.

Companies are increasingly required to improve their quality, flexibility and innovation while maintaining or reducing their costs. However, engineering and finance are often handled by different staff groups at different times in the manufacturing process, and by uncoupling engineering and finance, a company runs the risk of overlooking important interactions between the two. A design system that performs engineering and financial analysis simultaneously may, therefore, improve upon the efficiency and effectiveness of the traditional methods, as the existing practice of designing aircraft from a technical perspective without simultaneously considering the impact on overall program value is not optimal in a business sense. A coupled performance/financial framework enables an integrated approach to technical design and programmatic decisions. This work thus seeks to couple aero performance and financial design. Specifically, a multi-objective trade study is conducted to see the impact on the direct operating cost (DOC) and manufacturing cost of parametrically varying aircraft wing thickness to chord ratio along the wing span. While the present process is only partially automated, the purpose is to establish a useful foundation for further developments and to gain insight into the interactions between technical and program design.

ImportanceReducing the duration of untreated psychosis (DUP) is essential to improving outcomes for people with first-episode psychosis (FEP). Current US approaches are insufficient to reduce DUP to international standards of less than 90 days.ObjectiveTo determine whether population-based electronic screening in addition to standard targeted clinician education increases early detection of psychosis and decreases DUP, compared with clinician education alone.Design, Setting, and ParticipantsThis cluster randomized clinical trial included individuals aged 12 to 30 years presenting for services between March 2015 and September 2017 at participating sites that included community mental health clinics and school support and special education services. Eligible participants were referred to the Early Diagnosis and Preventative Treatment (EDAPT) Clinic. Data analyses were performed in September and October 2019 for the primary and secondary analyses, with the exploratory subgroup analyses completed in May 2021.InterventionsAll sites in both groups received targeted education about early psychosis for health care professionals. In the active screening group, clients also completed the Prodromal Questionnaire–Brief using tablets at intake; referrals were based on those scores and clinical judgment. In the group receiving treatment as usual (TAU), referrals were based on clinical judgment alone.Main Outcomes and MeasuresPrimary outcomes included DUP, defined as the period from full psychosis onset to the date of the EDAPT diagnostic telephone interview, and the number of individuals identified with FEP or a psychosis spectrum disorder. Exploratory analyses examined differences by site type, completion rates between conditions, and days from service entry to telephone interview.ResultsTwenty-four sites agreed to participate, and 12 sites were randomized to either the active screening or TAU group. However, only 10 community clinics and 4 school sites were able to fully implement population screening and were included in the final analysis. The total potentially eligible population size within each study group was similar, with 2432 individuals entering at active screening group sites and 2455 at TAU group sites. A total of 303 diagnostic telephone interviews were completed (178 [58.7%] female individuals; mean [SD] age, 17.09 years [4.57]). Active screening sites reported a significantly higher detection rate of psychosis spectrum disorders (136 cases [5.6%], relative to 65 [2.6%]; P P = .03). There was no difference in mean (SD) DUP between groups (active screening group, 239.0 days [207.4]; TAU group 262.3 days [170.2]).Conclusions and RelevanceIn this cluster trial, population-based technology-enhanced screening across community settings detected more than twice as many individuals with psychosis spectrum disorders compared with clinical judgment alone but did not reduce DUP. Screening could identify people undetected in US mental health services. Significant DUP reduction may require interventions to reduce time to the first mental health contact.Trial RegistrationClinicalTrials.gov Identifier: NCT02841956

Childhood psychotic-like experiences (PLEs) are associated with a range of impairments; a subset of children experiencing PLEs will develop psychiatric disorders, including psychotic disorders. A potential distinguishing factor between benign PLEs versus PLEs that are clinically relevant is whether PLEs are distressing and/or persistent. The current study used three waves of Adolescent Brain Cognitive Development℠ (ABCD) study PLEs assessments to examine the extent to which persistent and/or distressing PLEs were associated with relevant baseline risk factors (e.g., cognition) and functioning/mental health service utilization domains. Four groups varying in PLE persistence and distress endorsement were created based on all available data in ABCD Release 3.0, with group membership not contingent on complete data: persistent distressing PLEs (n = 272), transient distressing PLEs (n = 298), persistent non-distressing PLEs (n = 221), and transient non-distressing PLEs (n = 536) groups. Using hierarchical linear models, results indicated youth with distressing PLEs, whether transient or persistent, showed delayed developmental milestones (β = 0.074, 95%CI:0.013,0.134) and altered structural MRI metrics (β = -0.0525, 95%CI:-0.100,-0.005). Importantly, distress interacted with PLEs persistence for the domains of functioning/mental health service utilization (β = 0.079, 95%CI:0.016,0.141), other reported psychopathology (β = 0.101, 95%CI:0.030,0.170), cognition (β = -0.052, 95%CI:0.-0.099,-0.002), and environmental adversity (β = 0.045, 95%CI:0.003,0.0.86; although no family history effects), with the interaction characterized by greatest impairment in the persistent distressing PLEs group. These results have implications for disentangling the importance of distress and persistence for PLEs with regards to impairments, including functional, pathophysiological, and environmental outcomes. These novel longitudinal data underscore that it is often only in the context of distress that persistent PLEs were related to impairments.

BACKGROUND Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis necessitate implementation of ethical data use practices to increase user acceptability and trust. OBJECTIVE Explore EP community partner perspectives on data sharing best practices, including beliefs, attitudes, and preferences for ethical data sharing and how best to present end user license agreements (EULA). METHODS We conducted exploratory, qualitative, focus-group-based study design and content analysis assessing mental health data-sharing and privacy preferences. Data was gathered for the California Early Psychosis Intervention (EPI-CAL) network project in 2020-2021. Focus groups were conducted via video conferencing and assessed three EP groups: clinical staff/providers (n=14), clients (n=6), and family members (n=4). Eligible participants were affiliated with one of 18 EPI-CAL network clinics (i.e., convenience sampling), English-speaking, and able to provide written informed consent and assent (minors). Clinic staff/providers were invited from EPI-CAL clinics. Thirty clients and family members were invited through referral; 20 did not participate. Key themes identified via content analysis of focus group discussions. RESULTS Clinical staff participants (N = 14) were adults (M = 37.9, SD = 9.0), predominantly cisgender female (71%), White (64%), and non-Hispanic (64%). Clients (N = 6) were young adults (M = 23.8, SD = 3.9), predominantly male sex (67%) and non-Hispanic (83%), with no predominant race or gender identity. Family (N = 4) were middle-aged (M = 47.5, SD = 7.8), mostly cisgender female (75%), non-Hispanic (100%), with no predominant race. Participants were acutely aware of widespread third-party sharing across digital domains, risk of breaches, and motives hidden in legal language of EULAs. Consequently, they reported feeling loss of control and lack of protection over their data. These concerns can be mitigated via user-level control for data sharing with third parties and an understandable, transparent EULA including multiple presentation modalities, text at an 8th grade reading level, and clear definition of key terms. CONCLUSIONS Transparent EULAs with user-level control of data sharing are desired by consumers using eHealth technology and result in high data-sharing rates. EULAs designed in a manner consistent with EP consumers' preferences facilitates increased engagement in eHealth technology.

Optimisation is aimed at enhancing aircraft design by identifying the most promising wing planforms at the early stage while discarding the least performing ones. Multiple disciplines must be taken into account when assessing new wing planforms, and a model-based framework is proposed as a way to include mass estimation and longitudinal stability alongside aerodynamics. Optimisation is performed with a particle swarm optimiser, statistical methods are exploited for mass estimation, and the vortex lattice method (VLM) with empirical corrections for transonic flow provides aerodynamic performance. Three surrogates of the aerodynamic model are investigated. The first one is based on radial basis function (RBF) interpolation, and it relies on a precomputed database to evaluate the performance of new wing planforms. The second one is based on an artificial neural network, and it needs precomputed data for a training step. The third one is a hybrid model which switches automatically between VLM and RBF, and it does not need any precomputation. Its switching criterion is defined in an objective way to avoid any arbitrariness. The investigation is reported for a test case based on the common research model (CRM). Reference results are produced with the aerodynamic model based on VLM for two- and three-objective optimisations. Results from all surrogate models for the same benchmark optimisation are compared so that their benefits and limitations are both highlighted. A discussion on specific parameters, such as number of samples for example, is given for each surrogate. Overall, a model-based implementation with a hybrid model is proposed as a compromise between versatility and an arbitrary level of accuracy for wing early-stage design.

Childhood psychotic-like experiences (PLEs) are associated with a range of impairments; a subset of children experiencing PLEs will develop psychiatric disorders, including psychotic disorders. A potential distinguishing factor between benign PLEs versus PLEs that are clinically relevant is whether PLEs are distressing and/or persistent. The current study used three waves of Adolescent Brain Cognitive Development℠ (ABCD) study PLEs assessments to examine the extent to which persistent and/or distressing PLEs were associated with relevant baseline risk factors (e.g., cognition) and functioning/mental health service utilization domains. Four groups varying in PLE persistence and distress endorsement were created based on all available data in ABCD Release 3.0, with group membership not contingent on complete data: persistent distressing PLEs (n = 272), transient distressing PLEs (n = 298), persistent non-distressing PLEs (n = 221), and transient non-distressing PLEs (n = 536) groups. Using hierarchical linear models, results indicated youth with distressing PLEs, whether transient or persistent, showed delayed developmental milestones (β = 0.074, 95%CI:0.013,0.134) and altered structural MRI metrics (β = -0.0525, 95%CI:-0.100,-0.005). Importantly, distress interacted with PLEs persistence for the domains of functioning/mental health service utilization (β = 0.079, 95%CI:0.016,0.141), other reported psychopathology (β = 0.101, 95%CI:0.030,0.170), cognition (β = -0.052, 95%CI:0.-0.099,-0.002), and environmental adversity (β = 0.045, 95%CI:0.003,0.0.86; although no family history effects), with the interaction characterized by greatest impairment in the persistent distressing PLEs group. These results have implications for disentangling the importance of distress and persistence for PLEs with regards to impairments, including functional, pathophysiological, and environmental outcomes. These novel longitudinal data underscore that it is often only in the context of distress that persistent PLEs were related to impairments.

An accurate computation of near-field unsteady turbulent flow around aerofoil is of outstanding importance for aerofoil trailing edge noise source prediction, which is a representative of main contributor to airframe noise and fan noise in modern commercial aircraft. In this study, an embedded large eddy simulation (ELES) is fully implemented in a separation-induced transitional flow over NACA0012 aerofoil at a moderate Reynolds number. It aims to evaluate the performance of the ELES method in aerodynamics simulation for wall-bounded aerospace flow in terms of accuracy, computational cost and complexity of implementation. Some good practice is presented including the special treatments at RANS-LES interface to provide more realistic turbulence generation in LES inflow. A comprehensive validation of the ELES results is performed by comparing with the experimental data and the wall-resolved large eddy simulation results. It is concluded that the ELES method could provide sufficient accuracy in the transitional flow simulations around aerofoil. It is proved to be a promising alternative to the pure LES for industrial flow applications involving wall boundary layer due to its significant computational efficiency.

ObjectiveA potential distinguishing factor between more benign and transient psychotic-like experiences (PLEs) versus PLEs that predict risk for psychiatric disorders is whether the PLEs are sustained and distressing (sustained dPLEs). The current study examined associations of both sustained and transient dPLEs with relevant risk factors (e.g., cognition), use of mental health services, and functional correlates (e.g., school performance) in school-age children.MethodThe current study used three Adolescent Brain Cognitive Development℠ study data waves to create sustained dPLE (n=272), transient dPLE (n=244), and control (n=272) groups. Hierarchical linear models examined whether these groups differed in terms of use of mental health services, functional correlates, family history of mental disorders, other symptoms (e.g., parent-rated psychotic symptoms, internalizing, externalizing symptoms), environmental factors (e.g., adverse childhood events [ACEs]), cognitive functioning, developmental milestone delays, and neuroimaging indices.ResultsSeveral factors were more strongly associated with sustained versus transient dPLEs, including use of mental health services (for sustained vs. controls: d=0.38), drop in grades (d=--.30), other symptoms (i.e., parent-rated psychotic, bipolar, internalizing, externalizing, suicidality; 0.33>dsdsConclusionsThese results have implications for understanding the pathogenesis of dPLEs, including indicating that several factors may distinguish transient from persisting dPLEs in children, including higher symptoms and ACEs, lower executive functioning scores, greater use of mental health services, and worsening school performance.

The fields of psychology and psychiatry are increasingly recognizing the importance of replication efforts. The current study aimed to replicate previous findings examining the construct validity and psychometric properties of a psychotic-like experiences (PLEs) measure in middle childhood using an independent subset of the baseline Adolescent Brain Cognitive Development (ABCD) sample. Using a remainder baseline sample of 7013 nine- to eleven-year-old children with complete data, we examined measurement invariance across race/ethnicity and sex, and examined the associations between the Prodromal Questionnaire Brief-Child Version (PQ-BC) and other measures of PLEs, internalizing symptoms, neuropsychological test performance, and developmental milestones, to determine whether previously obtained results replicated in this nonoverlapping baseline sample subset. The results replicated measurement invariance across ethnicity and sex, and analyses again found higher PQ-BC scores for African American (β = .364, 95% CI = 0.292, 0.435) and Hispanic (β = .255, 95% CI = 0.185, 0.324) groups. We also replicated that higher PQ-BC scores were associated with psychosis risk measures, higher rates of child-reported internalizing symptoms (Distress: β = .378, 95% CI = 0.357,0.398), neuropsychological test performance deficits (eg, working memory; Distress: β = −.069, 95% CI = −0.096, −0.042), and motor (Distress: β = .026, 95% CI = 0.003, 0.049) and speech (Distress: β = .042, 95% CI = 0.018, 0.065) developmental milestone delays. The current results replicated many findings from the original study examining the PQ-BC. We replicated evidence for mean differences in race/ethnicity, and associations with other PLE measures, greater internalizing symptoms, cognitive impairments, and developmental milestone delays. These findings indicate robust and reliable associations between PLEs and hypothesized correlates can be found in middle childhood nonclinical samples.

The advantages of multidisciplinary design are well understood, but not yet fully adopted by the industry where methods should be both fast and reliable. For such problems, minimum computational cost while providing global optimality and extensive design information at an early conceptual stage is desired. However, such a complex problem consisting of various objectives and interacting disciplines is associated with a challenging design space. This provides a large pool of possible designs, requiring an efficient exploration scheme with the ability to provide sufficient feedback early in the design process. This paper demonstrates a generalized optimization framework with rapid design space exploration capabilities in which a Multifidelity approach is directly adjusted to the emerging needs of the design. The methodology is developed to be easily applicable and efficient in computationally expensive multidisciplinary problems. To accelerate such a demanding process, Surrogate Based Optimization methods in the form of both Radial Basis Function and Kriging models are employed. In particular, a modification of the standard Kriging approach to account for Multifidelity data inputs is proposed, aiming to increasing its accuracy without increasing its training cost. The surrogate optimization problem is solved by a Particle Swarm Optimization algorithm and two constraint handling methods are implemented. The surrogate model modifications are visually demonstrated in a 1D and 2D test case, while the Rosenbrock and Sellar functions are used to examine the scalability and adaptability behaviour of the method. Our particular Multiobjective formulation is demonstrated in the common RAE2822 airfoil design problem. In this paper, the framework assessment focuses on our infill sampling approach in terms of design and objective space exploration for a given computational cost.

Recent research on turbomachinery design and analysis for supercritical Carbon Dioxide (sCO2) power cycles has relied on Computational Fluid Dynamics. This has produced a large number of works whose approach is mostly case-specific, rather than of general application to sCO2 turbomachinery design. As opposed to such approach, this work explores the aerodynamic performance of compressor blade cascades operating on air and supercritical CO2 with the main objective to evaluate the usual aerodynamic parameters of the cascade for variable boundary conditions and geometries, enabling ‘full’ or ‘partial’ similarity. The results present both the global performance of the cascades and certain features of the local flow (trailing edge and wake). The discussion also highlights the mechanical limitations of the analysis (forces exerted on the blades), which is the main restriction to applying similarity laws to extrapolate the experience gained through decades of work on air turbomachinery to the new working fluid. This approach is a step towards the understanding and appropriate formulation of a multi-objective optimisation problem for the design of such turbomachinery components where sCO2 is used as the operating fluid. With this objective, the paper aims to identify and analyse what would be expected if a common description of such computational design problems similar to those where air is the working fluid were used.

Current best practice regarding the treatment of negative symptoms of schizophrenia supports the use of psychological interventions in addition to medication. This chapter reviews the literature evaluating different non-pharmacological approaches to treating these symptoms. Meta-analytic studies suggest that social skills training, music therapy, non-invasive brain stimulation, mindfulness, and exercise-based interventions are all effective at improving negative symptoms, relative to treatment as usual (TAU). Effect sizes for these interventions range from small to moderate. The long-term benefits of these interventions are currently unclear, and there has been some debate as to whether the impact of these interventions constitute consistent, clinically meaningful change. Evidence for other therapies such as arts therapies other than music therapy, cognitive behavioural therapies for psychosis, neurocognitive therapies, and family-based interventions is more inconsistent. As a result, primary negative symptoms of schizophrenia can still be considered an important unmet therapeutic need where more research is needed.

Reducing the duration of untreated psychosis (DUP) is a key aim of early psychosis (EP) care. However, substantial variability in how the start and end points of DUP are defined impact its utility in clinical decision-making, and as an outcome measure. In this study, qualitative interviews were conducted with providers to assess how EP services and providers define, operationalize, and measure DUP. Twenty-five providers across 14 clinics were interviewed. Participants emphasized symptom frequency, conviction, distress caused, and impact when determining psychosis onset. DUP endpoint was typically identified as the first assessment in an episode of care that included an accurate diagnosis, leading to specialty EP treatment. Participants proposed a more structured operationalization of DUP, relative to those historically adopted in the literature. Integrating front-line provider perspectives could improve the accuracy of DUP measurement and address the heterogeneity in how the construct is operationalized across research and practice.

Most of the current cost models focus on a particular manufacturing process or a specific maintenance aspect, therefore not providing the whole picture. The main challenge in modelling the manufacturing cost, associated to a new aircraft at the initial design stage, is to examine all the cost features and the way to link them into the decision making process. It is important to understand the cost related to different competing designs, and this can be tackled by including cost estimation in the design process. Estimating the cost at the early design stage is paramount to reduce the life cycle cost of the aircraft. This paper presents the development of a new methodology for the generation of a cost estimation approach for preliminary aircraft design in a multidisciplinary environment. The framework is able to capture the design attributes that drive the cost allowing a designer to assess cost changes with respect to different design configurations. The cost model is built in Excel using a Visual Basic interface and it is integrated within Model Centre platform, where it can be treated as a component of a computational design process. The paper concludes by presenting the results from a real wing trade-off study that includes all the components of a complete design system.

Aim Diagnosing individuals at ultra high risk (UHR) for psychosis can improve early access to treatment, and a two-stage model utilizing self-report screening followed by a clinical interview can be accurate and efficient. However, it is currently unclear which screening cut-offs to adopt with different populations. Methods A systematic review of diagnostic accuracy studies evaluating the Prodromal Questionnaire (PQ) as a preliminary screener for UHR and psychosis was conducted to examine screening effectiveness in different contexts. MedLine, PsycInfo, SCOPUS and ProQuest Dissertations and Abstracts databases were electronically searched, along with a review screen and citation search of key papers. Findings were summarized in a narrative synthesis. Results In total, 14 diagnostic accuracy studies and 45 studies using the PQ as a screening tool for UHR and psychosis were included. In all settings, the 3 different versions of the PQ were all found to accurately identify UHR and full psychosis. Higher cut-off points were required in non-help-seeking samples, relative to general help-seeking populations, which in turn were higher than those needed in samples highly enriched with UHR participants. Conclusion The findings support the use of the PQ as a preliminary screening tool for UHR in different settings; however, higher thresholds in lower UHR-prevalence populations are necessary to minimize false positives. Including the distress criteria, rather than just number of symptoms, may improve screening effectiveness. Different thresholds may be appropriate in different contexts depending on the importance of sensitivity vs specificity. Protocol registration: CRD42016033004.

Investigating the optimum blend of maintenance strategies for a given manufacturing system is a continuing concern amongst maintenance academics and professionals. Recent evidence suggests that little research is conducted on the simulation optimisation of maintenance in industrial systems. This study was designed to make an important contribution to the field of simulation-based optimisation of maintenance by presenting two empirical case studies: a tyre re-treading factory and a petro-chemical plant. It is one of the first to optimise various maintenance strategies simultaneously with their parameters in industrial manufacturing systems while considering production dynamics. Stochastic Discrete Event Simulation models were developed and connected to a Multi-Objective Optimisation engine. Various maintenance strategies were investigated including Corrective Maintenance, Preventive Maintenance, Opportunistic Maintenance and Condition-Based Maintenance. The results of this research suggest that over-looking the optimisation of maintenance on the strategic level may lead to sub-optimal solutions. In addition, it appears that traditional trade-offs between maintenance cost and production throughput are not present in some maintenance systems. This is an interesting observation that requires further investigation and experimentation.

A set of 2-D unsteady Reynolds-averaged Navier–Stokes simulations was performed to examine the potential benefits of changing the inflowand outflowdirections of a synthetic jet, called the bidirectional synthetic jet or bidirectional synthetic jet (BDSJ). The simulations were performed for the so-called NASA 2-D hump configuration to assess the performance of the BDSJ compared to the classical synthetic jet. Three different turbulence models were employed to obtain general trends of the performance of the BDSJ. Three different approaches were also considered regarding the jet exit conditions (namely, the unfixed mass flow rate, unfixed velocity, and unfixed jet area cases) to make a meaningful comparison with the classical synthetic jet. One of the key findings from this study is that the performance of a synthetic jet could improve significantly if the inflow (suction) and outflow (ejection) directions of the jet are optimized separately. The simulation results suggest that the performance of the BDSJ increases as the difference between the inflow and outflow angles of the jet is increased. The results also show that there is little influence of the different parabolic velocity profiles specified at the jet exit on the separation bubble size. All three turbulence models employed predict similar general trends.

Despite promising findings from small-scale studies suggesting that body psychotherapy may be an effective treatment for negative symptoms, these results were not replicated in a recent multisite trial. In this trial a far smaller proportion of women were recruited relative to earlier studies, which may be an issue given the gender mix of the sample evaluated has been found to affect trial outcomes in schizophrenia. Using data from our multisite trial, the interaction between gender and treatment allocation as a predictor of outcomes was examined in 275 participants (72 women and 203 men) randomised to either a body psychotherapy or Pilates group. Negative symptoms were found to significantly reduce in women randomised to the body psychotherapy condition in comparison to Pilates, while no such effect was detected in men. Consistent with the smaller trials, this improvement was found to relate predominantly to expressive deficits. These findings suggest that body psychotherapy may be an effective treatment for negative symptoms in women. These findings emphasise the importance of sample characteristics in determining trial outcome in psychological treatment studies.

Industrial aerodynamic design applications require multiobjective optimization tools able to provide design feedback to the engineers. This is true especially when optimization studies are carried out during the conceptual design stage. The need for fast optimization methods has led to the development of multifidelity methods in a surrogate based optimization environment. Multifidelity tools have the potential to accelerate the design process, primarily due to the lower cost associated with the low fidelity tool. In addition to this, the design stage is shortened as mature and reliable high fidelity design information is provided earlier in the design cycle. Despite this high potential of these methods, there is no explicit comparison available in the literature between multifidelity surrogate based optimization tools for industrial aerodynamic problems. This paper aims at providing a direct comparison between two multiobjective multifidelity surrogate based optimization methods developed by our group. The first approach uses a trust region formulation for efficient multiobjective that does not require gradients. The second is using the concept of expected improvement to perform fast design space exploration based on a novel Kriging modification for multifidelity data. The tools are applied in two aerodynamic design problems: optimization of a high lift configuration in respect to maximum lift maximization and an airfoil design for transonic cruising conditions. These problems feature characteristics of industrial interest. They involve difficult physical analyses in the case of the high lift configuration and a more complex optimization formulation due to the increased dimensionality in the case of the transonic airfoil. Our presented methods are compared against a CFD-based optimization, a surrogate based optimization using only high fidelity data and a multifidelity surrogate based optimization based on Co-Kriging. Early results suggest that the trust region method can quickly provide improved designs leading to an efficient Pareto front. The expected improvement based method shows fast exploration attributes and a wide Pareto front.

The airlines are subjected to the energy crisis and have raised environmental issues at the same time. Future engine technology advances could decrease the effect on the environment and energy consumption. Alternative fuelspotentially assist in the reduction of engine emissions and hence lower the energy-related issues. This study presents analysis of the efficiency of aircraft engines as a function of thrust force, flow of the and specific fuel consumption (SFC) at distinct mixing ratios (40% and 100%) of African natural gas, Algae, Camelina, Jatropa, Diesel, Hydrogen, Synthetic paraffinic kerosene, UK natural gas at cruising altitude. In – house Cranfield University simulation codes, PYTHIA & TURBOMATCH have been used to investigate and model a three-shaft high bypass engine analogous to RB211 - 524. The engine model has been certified and authenticated in commercial aircraft with open works found in the Bio - Synthetic Paraffinic Kerosene test program.Blended fuel of Kerosene & hydrogen (KE+HY) fuels gives values of 331.6 KN,1.2577KG/S, and 6.9512 kg/kwh for net thrust force,the flow of fuel and specific fuel feastingat mingling ratio of 40 % respectively. However, at mixing ratio of 100% Blended fuel of Kerosene & hydrogen (KE+HY) fuels gives values of 339.01 KN, 0.800KG/S, and 4.333 kg/kwh for net thrust, fuel flow, and specific fuel consumption respectively. It is found that blended fuel of Kerosene &hydrogen (KE+HY) fuels give better engine performances as compared to other alternative fuels. However, Kerosene &diesel (KE+DI) fuels have shown a slight reduction in engine performance.

AIM: Specialized early interventions improve outcomes in early psychosis. Experts have proposed a number of essential treatment components. However, it is unclear whether these reflect the views of senior clinic staff charged with implementing this model in practice. METHOD: Twenty-Five senior Early Psychosis clinic staff across California completed a survey indicating which features of early psychosis treatment they considered most important. RESULTS: Components related to the service structure and the need for a prompt, comprehensive assessment and care planning were considered most important, despite the limited evidence base evaluating these aspects of care. Administration of clozapine to treatment-refractory patients and weight gain interventions were considered the least important, despite the relatively strong evidence base supporting these treatment components. CONCLUSION: The findings suggest a bi-directional dissemination gap, where components considered most important by senior providers receive limited research attention, while some areas with supporting evidence may be underappreciated in clinical practice.

The world oil consumption is at the peak where the fuel price is insubstantial and can increase dramatically due to economic, social, and political factors andunprecedentedstability.Since fuel resourcesare scarce, it is an urgent need to find alternative fuel. Biofuel is one of the favorable choices in the market. Algae-based biofuel is the fourth generation of biofuel where it does not compete with the food production and it has myriad of advantages.These abundant algae are easy to cultivate and researchers found that algae-based biofuel is capable of reducing engine emission. This paper modelled the RB211aero-gas turbine engine by utilizing algae-based biofuel with various blended percentageratios at different flight conditions. Cranfield’s University in-house software, PYTHIA,and HEPHAESTUSare used to model the engine performance and emission prediction respectively.PYTHIA programme uses a modified Newton-Raphson convergence technique in the zero-dimensional steady-state model for both design and off-design conditions. Meanwhile, HEPHAESTUSsoftware uses the Zeldovich equations (for NOx) and models the emission by implementing a partially-stirred reactor (PSR) model and perfectly stirred reactor (PSRS) models at different zones in the combustor.Results have shown that thrust force produced is increasing at higher blended percentage ratio of algae biofuel. Through emission analysisprediction, generally,the nitrous oxide emission formation is lower at a higher altitude during the cruising. Results also predicted that higher percentage blended ratio of algae biofuel also reduces the emission formation.

BACKGROUND: According to the dimensional approach to psychosis, psychotic-like experiences (PLEs) lie at the low end of the psychotic symptom continuum. PLEs, and especially distressing PLEs (dPLEs), share multiple risk factors with psychotic disorders, including cognitive impairments and resting state functional connectivity (RSFC) impairments. The current series of studies aimed to better characterize these risk factors in a childhood population, as it is critical to identify risk factors prior to the significant disability that characterizes the psychosis prodrome. Specifically, this presentation will focus on findings from two studies using Adolescent Brain Cognitive Development (ABCD) data examining the phenotypic and neural associations of distressing psychotic-like experiences (dPLEs) in childhood. METHODS: Both studies used data collected from the first wave of the ABCD study, a large-scale study tracking children aged 9-10-years-old recruited from 20 research sites across the United States. In the first study (N=3,984), we examined the associations between childhood dPLEs and several phenotypic factors, including neuropsychological test performance, attainment of developmental milestones, family history of psychosis, and internalizing symptoms. In a second study (N=3,434), we examined the associations between childhood dPLEs and RSFC. This second study examined the associations between within-network RFSC, between-network RSFC, and subcortical RSFC with childhood dPLEs. RESULTS: The first study found evidence that the presence of impaired cognitive functioning (i.e., working memory impairments), developmental milestone delays (i.e., clumsiness), family history of psychosis, and internalizing symptoms, were all associated with increased dPLEs. For the second study, we found evidence that decreased cingulo-opercular (CON), default mode (DMN), and cingulo-parietal (CPAR) network connectivity were all associated with increased dPLEs. These RSFC impairments remained even after accounting for neuropsychological test performance, internalizing symptoms, and family history of psychotic disorder. Furthermore, in terms of subcortical connectivity, both increased CON-cerebellar connectivity and decreased CPAR-cerebellar connectivity were associated with increased dPLEs. CONCLUSIONS: Overall, the results of the current studies indicate that deficits may be detectable prior to the onset of clinically significant symptoms. Examining possible risk markers prior to the clinical expression of psychotic disorders is critical in order to improve early detection strategies. Future efforts will begin to utilize this information regarding predictors of PLEs, and work towards the creation of a calculator predicting risk for the development and maintenance of dPLEs using the ABCD sample.

California's Mental Health Services Act Prevention and Early Intervention funds provide a unique opportunity for counties to initiate programs focused on early intervention in mental health, including early psychosis. To explain the configuration of early psychosis programs and plan for a statewide evaluation, this report provides an overview of California's early psychosis programming, including service composition, funding sources, inclusion criteria, and data collection practices.Following a comprehensive identification process, early psychosis program representatives were contacted to complete the California Early Psychosis Assessment Survey (CEPAS).The response rate to the CEPAS was excellent (97%, 29 of 30 active programs across 24 of 58 counties). Most programs (N=27, 93%) serve individuals with first-episode psychosis between the ages of 12 and 25. Twenty-two programs (79%) provide more than half of the standard components of early psychosis care outlined in the First-Episode Psychosis Service Fidelity Scale. Sixty-four percent of programs collect client-level data at intake and follow up on five or more relevant outcome domains; however, these varied significantly across sites.Substantial variability in services, inclusion criteria, and data recorded was evident across programs. Prior to conducting any large-scale evaluation, these findings highlight the significant challenges in retrospectively evaluating program effectiveness, need to harmonize program data collection methods, and importance of assessing the impact of program variability on outcomes.

During the early stages of any system design, a thorough exploration of the design space can prove to be challenging and computationally expensive. The challenges are further exacerbated when dealing with complex systems, such as an aircraft, due to the high dimensionality of their design space. Arising from the Toyota Product Development System, set-based design allows parallel evaluation of multiple alternative configurations in the early design stages. At the same time, optimisation methods can be employed at later stages to fine-tune the engineering characteristics of design variants. Presented in this paper, is the Augmented set-based Design and OPTimisation (ADOPT) Framework that introduces a novel methodology for integrating the two areas. This allows for a thorough design-space exploration while ensuring the optimality of the selected designs. The framework has been developed using a process-independent and tool-agnostic approach so that it can be applied to the design process of varying kinds of systems. To demonstrate the implementation and potential benefits, the framework has been applied to the design of a generic aircraft fuel system. The results from the case study and the framework itself are discussed, with a number of areas for further development and future work being identified and presented.

Understanding the link between quality of life and symptoms in schizophrenia is important in enhancing the prospect of patient recovery. Only weak associations have been found between subjective quality of life (SQOL) and negative symptoms. However, this may be because many existing symptom assessment scales inadequately assess the experiential deficits of negative symptoms. This study aimed to re-evaluate these findings using the Clinical Assessment Interview for Negative Symptoms (CAINS), which as been designed to capture both the expressive and experiential subdomains of negative symptoms as separate constructs. In this observational study 275 participants with at least moderate negative symptoms were assessed three times over nine months using the CAINS, the Positive and Negative Syndrome Scale (PANSS), and the Manchester Short Assessment of Quality of Life (MANSA). A significant negative association between SQOL and the CAINS experiential subscale was found in the cross-sectional analysis (adj. B = -0.28, 95% CI = -0.44 to -0.12, P = 0.001), and in the change scores (adj. B = -0.13, 95% CI = -0.26 to -0.01, P = 0.032). No associations between SQOL and expressive symptoms, or negative symptoms measured using the PANSS were detected in the multivariable models. These findings suggest that the association between negative symptoms and SQOL is related primarily to experiential deficits, and highlights the importance of measuring the separate subdomains of negative symptoms as distinct constructs. The findings also highlight the impact of negative symptoms and experiential deficits in particular on social outcomes, further emphasising the need to develop new treatments for these symptoms.

The focus of this work is on the modelling of evaporation and spray penetration for alternative fuels. The extension model approach is presented and validated for alternative fuels, namely, Kerosene (KE), Ethanol (ETH), Methanol (MTH), Microalgae biofuel (MA), Jatropha biofuel (JA), and Camelina biofuel (CA). The results for atomization and spray penetration are shown in a time variant condition. Comparisons have been made to visualize the transient behaviour of these fuels. The vapour pressure tendencies are revealed to have significant effects on the transient shape of the evaporation process. In a given time frame, ethanol fuel exhibits the highest evaporation rate and followed by methanol, other biofuels and kerosene. Ethanol also propagates the farthest distance and followed by methanol and kerosene. However, all biofuels have a shorter penetration length in the given time. These give penalty costs to biofuels emissions formation. The influences of initial conditions such as temperature and droplet velocity are also explored numerically. High initial temperature and velocity could accelerate evaporation rate. However, high initial temperature has resulted in low penetration length while high initial velocity produces contrasting results.

BackgroundNegative symptoms of schizophrenia have a severe impact on functional outcomes and treatment options are limited. Arts therapies are currently recommended but more evidence is required.AimsTo assess body psychotherapy as a treatment for negative symptoms compared with an active control (trial registration: ISRCTN84216587).MethodSchizophrenia out-patients were randomised into a 20-session body psychotherapy or Pilates group. The primary outcome was negative symptoms at end of treatment. Secondary outcomes included psychopathology, functional, social and treatment satisfaction outcomes at treatment end and 6-months later.ResultsIn total, 275 participants were randomised. The adjusted difference in negative symptoms was 0.03 (95% CI –1.11 to 1.17), indicating no benefit from body psychotherapy. Small improvements in expressive deficits and movement disorder symptoms were detected in favour of body psychotherapy. No other outcomes were significantly different.ConclusionsBody psychotherapy does not have a clinically relevant beneficial effect in the treatment of patients with negative symptoms of schizophrenia.

Awareness of environmental and economic issues associated with fossil fuel has led to the exploration of alternative fuels for aviation. Analysis and measurements of alternative fuel using real aircraft engines are complex and costly. Thus, evaluation only through computation is an option at present. This paper presents an analysis of aircraft engine emissions, particularly NOx and CO, from the blend of bio-synthetic paraffinic kerosene (bio-SPK) fuel with kerosene using a simplified gas emission model. Three different fuels, namely, a conventional aviation fuel Jet-A, Jatropha bio-SPK and Camelina bio-SPK were tested as pure and as blends with Jet-A. Chemical properties of the tested fuels were introduced into HEPHAESTUS, an in-house gas emission software developed in Cranfield University. HEPHAESTUS was developed based on the physics-based approach by incorporating a number of stirred reactors to predict NOx, CO, UHC and soot. Gaseous emissions generated from kerosene were observed to follow the trends provided by the ICAO databank. The capability of HEPHAESTUS in predicting the NOx and CO level from biofuel is yet to be explored. The level of NOx and CO predicted in this study followed the trends shown in the literature, although they quantitatively differed. Compared to Jet-A, NOx decreased and CO increased as the percentage of Jatropha bio-SPK and Camelina bio-SPK in the mixture increased. NOx reduction was consistent with the reduction in flame temperature because NOx generation considered in the model was dominantly based on thermal NOx. In contrast, increases in CO were due to low flame temperature that led to incomplete combustion. The consistency of the results obtained showed that the computational work performed in this study as an initial step toward the prediction of emission level of biofuels was successful. However, further studies on the experimental work or computational fluid dynamic simulation is essential.

In this work, we investigate the computational design of a typical S-Duct that is found in the literature. We model the design problem as a shape optimization study. The design parameters describe the 3D geometrical changes to the shape of the S-Duct and we assess the improvements to the aerodynamic behavior by considering two objective functions: the pressure losses and the swirl. The geometry management is controlled with the Free-Form Deformation (FFD) technique, the analysis of the flow is performed using steady-state computational fluid dynamics (CFD), and the exploration of the design space is achieved using the heuristic optimization algorithm Tabu Search (MOTS). The results reveal potential improvements by 14% with respect to the pressure losses and by 71% with respect to the swirl of the flow. These findings exceed by a large margin the optimality level that was achieved by other approaches in the literature. Further investigation of a range of optimum geometries is performed and reported with a detailed discussion.

Aim Duration of untreated psychosis, or the time between onset of psychosis symptoms and accurate diagnosis and treatment, is a significant predictor of both initial treatment response and long-term outcomes. As such, efforts to improve rapid identification are key. Because early signs of psychosis commonly emerge in adolescence, schools have the potential to play an important role in the identification of psychosis-spectrum disorders. Methods To illustrate the potential role of schools in this effort, the current paper describes implementation of a psychosis screening tool as part of a larger study focused on reducing the duration of untreated psychosis in Sacramento, CA. Results Clinical considerations related to screening for psychosis in schools, including ethical concerns, logistics, screening population and stigma are addressed. Implementation strategies to address these concerns are suggested. Conclusions Early psychosis screening in the school system could improve early identification, reduce stigma and may represent an important further step towards an integrative system of mental health.

The transition to a secure low-carbon system is raising a set of uncertainties when planning the path to a reliable decarbonised supply. The electricity sector is committing large investments in the transmission and distribution sector upon 2050 in order to ensure grid resilience. The cost and limited flexibility of traditional approaches to 11 kV network reinforcement threaten to constrain the uptake of low-carbon technologies. This paper investigates the suitability and cost-effectiveness of smart grid techniques along with traditional reinforcements for the 11 kV electricity distribution network, in order to analyse expected investments up to 2050 under different DECC demand scenarios. The evaluation of asset planning is based on an area of study in Milton Keynes (East Midlands, United Kingdom), being composed of six 11 kV primaries. To undertake this, the analysis used a revolutionary new model tool for electricity distribution network planning, called scenario investment model (SIM). Comprehensive comparisons of short- and long-term evolutionary investment planning strategies are presented. The work helps electricity network operators to visualise and design operational planning investments providing bottom-up decision support., OFGEM and the Low Carbon Network Fund