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To capture the airspeed-dependent dynamics of flexible aircraft, high-order aeroservoelastic systems can generally be expressed as linear parameter-varying (LPV) models. This paper presents a comprehensive model order reduction and control design process for grid-based LPV systems, and takes the flexible aircraft FLEXOP as an example for verification. The LPV model order reduction method is extended from projection-based linear time-invariant methods through construction of continuous transformations. The corresponding algorithm can be programmed to automatically perform the model order reduction for LPV systems and simultaneously ensure the state consistency between grid points and the continuity of state-space data interpolation. By applying this method, a 680th-order high-fidelity LPV model of the FLEXOP aircraft is reduced to a control-oriented model with only 19 states. Considering that the frequencies of rigid-body and flexible modes are close under certain parameter conditions, an integrated design approach for rigid-flexible coupling control is employed in this paper. Instead of separately designing a baseline rigid-body flight controller and a flutter suppression controller for each unstable flexible mode, a parameter-dependent dynamic output-feedback controller is designed. The resulting controller effectively expands the flutter-free flight envelope, ensuring rigid-body attitude and velocity tracking performance while stabilising the two originally unstable flutter modes.
Using National Healthcare Safety Network data, an interrupted time series of intravenous antimicrobial starts (IVAS) among hemodialysis patients was performed. Annual adjusted rates decreased by 6.64% (January 2012–March 2020) and then further decreased by 8.91% until December 2021. IVAS incidence trends have decreased since 2012, including during the early COVID-19 pandemic.
This chapter outlines future research directions to advance understanding of sexual minority and gender diverse (SMGD) individuals and their relationships by advocating for the examination of cultural and legal contexts that shape SMGD experiences across nations. Additionally, this chapter argues that future research should address minority stress processes and resilience factors, with attention to couple-level outcomes and mechanisms connecting stigma to health and incorporate intersectionality to elucidate how multiple marginalized identities interact. Methodological considerations for future research are also presented. Lastly, this chapter discusses translational priorities including community outreach, tailored interventions and programs, legal advocacy utilizing research evidence, educational initiatives, and technology-enabled solutions tailored for SMGD individuals. This chapter concludes with an integrated perspective on open questions, methods, and real-world applications to guide the next phase of research and practice aimed at promoting justice and well-being for SMGD individuals globally.
The ability to understand and speak more than one language (i.e., bilingualism) may provide benefits to preserving social cognition against normal age-related deteriorations. This study examined how variations in bilingual language experience influence theory-of-mind (ToM) understanding in late adulthood. One hundred and five cognitively healthy older adults (Mage = 66.23 years, range = 56–79) and 80 young adults (Mage = 22.03 years, range = 19–30), who were bilingual speakers, completed a ToM task battery, a self-report questionnaire on their language background, and a battery of general cognition assessments. We found an overall age-related decline in ToM, where older adults made more errors in inferring others’ mental states compared with young adults. Importantly, an earlier L2 age of acquisition (L2AoA) predicted better ToM performance among older adults, over and above the effects of age, education, and general cognition. The results suggest that early bilingual acquisition may enhance social cognitive processes during development and contribute to intact ToM abilities in older adult bilinguals.
In recent years, the rapid convergence of artificial intelligence (AI) and low-altitude flight technology has driven significant transformations across various industries. These advancements have showcased immense potential in areas such as logistics distribution, urban air mobility (UAM) and national defense. By adopting the AI technology, low-altitude flight technology can achieve high levels of automation and operate in coordinated swarms, thereby enhancing efficiency and precision. However, as these technologies become more pervasive, they also raise pressing ethical or moral concerns, particularly regarding privacy, public safety, as well as the risks of militarisation and weaponisation. These issues have sparked extensive debates. In summary, while the integration of AI and low-altitude flight presents revolutionary opportunities, it also introduces complex ethical challenges. This article will explore these opportunities and challenges in depth, focusing on areas such as privacy protection, public safety, military applications and legal regulation, and will propose strategies to ensure that technological advancements remain aligned with ethical or moral principles.
In this retrospective study examining the treatment of low-risk AmpC-producing Enterobacterales bacteremia during two periods with different microbiology reporting strategies, reporting of ceftriaxone susceptibility was associated with a statistically significant decrease in carbapenem use as definitive therapy compared to when susceptibility was suppressed (21 vs 50%, p < 0.0001).
Unmanned aerial vehicle (UAV) formations for bearing-only passive detection are increasingly important in modern military confrontations, and the array of the formation is one of the decisive factors affecting the detection accuracy of the system. How to plan the optimal geometric array in bearing-only detection is a complex nondeterministic polynomial problem, and this paper proposed the distributed stochastic subgradient projection algorithm (DSSPA) with layered constraints to solve this challenge. Firstly, based on the constraints of safe flight altitude and fixed baseline, the UAV formation is layered, and the system model for bearing-only cooperative localisation is constructed and analysed. Then, the calculation formula for geometric dilution of precision (GDOP) in the observation plane is provided, this nonlinear objective function is appropriately simplified to obtain its quadratic form, ensuring that it can be adapted and used efficiently in the system model. Finally, the proposed distributed stochastic subgradient projection algorithm (DSSPA) combines the idea of stochastic gradient descent with the projection method. By performing a projection operation on each feasible solution, it ensures that the updated parameters can satisfy the constraints while efficiently solving the convex optimisation problem of array planning. In addition to theoretical proof, this paper also conducts three simulation experiments of different scales, validating the effectiveness and superiority of the proposed method for bearing-only detection array planning in UAV formations. This research provides essential guidance and technical reference for the deployment of UAV formations and path planning of detection platforms.
Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).
Aims
We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.
Method
Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.
Results
Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.
Conclusions
We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.
Cannabis use severely affects the outcome of people with psychotic disorders, yet there is a lack of treatments. To address this, in 2019 the National Health Service (NHS) Cannabis Clinic for Psychosis (CCP) was developed to support adults suffering from psychosis to reduce and/or stop their cannabis use.
Aims
Examine outcome data from the first 46 individuals to complete the CCP's intervention.
Method
The sample (N = 46) consisted of adults (aged ≥ 18) with psychosis under the care of the South London and Maudsley NHS Foundation Trust, referred to the CCP between January 2020 and February 2023, who completed their intervention by September 2023. Clinical and functional measures were collected before (T0) and after (T1) the CCP intervention (one-to-one sessions and peer group attendance). Primary outcomes were changes in the Cannabis Use Disorders Identification Test-Revised (CUDIT-R) score and pattern of cannabis use. Secondary outcomes included T0–T1 changes in measures of delusions, paranoia, depression, anxiety and functioning.
Results
A reduction in the mean CUDIT-R score was observed between T0 (mean difference = 17.10, 95% CI = 15.54–18.67) and T1, with 73.91% of participants achieving abstinence and 26.09% reducing the frequency and potency of their use. Significant improvements in all clinical and functional outcomes were observed, with 90.70% being in work or education at T1 compared with 8.70% at T0. The variance in CUDIT-R scores explained between 34 and 64% of the variance in our secondary measures.
Conclusions
The CCP intervention is a feasible strategy to support cannabis use cessation/reduction and improve clinical and functional outcomes of people with psychotic disorders.
During the automatic docking assembly of aircraft wing-fuselage, using monocular camera or dual-camera to monitor the docking stage of the fork-ear will result in an incomplete identification of the fork-ear pose-position and an inaccurate description of the deviation in the intersection holes’ position coordinates. To address this, a quality inspection and error correction method is proposed for the fork-ear docking assembly based on multi-camera stereo vision. Initially, a multi-camera stereo vision detection system is established to inspect the quality of fork-ear docking assembly. Subsequently, a spatial position solution mathematical model of the fork-ear feature points is developed, and a spatial pose determination mathematical model of fork-ear is established by utilised the elliptical cone. Finally, an enhanced artificial fish swarm particle filter algorithm is proposed to track and estimate the coordinate of the fork-ear feature points. An adaptive weighted fusion algorithm is employed to fuse the detection data from the multi-camera and the laser tracker, and a wing pose-position fine-tuning error correction model is constructed. Experimental results demonstrate that the method enhances the effect of the assembly quality inspection and effectively improves the wing-fuselage docking assembly accuracy of the fork-ear type aircraft.
The main purpose of this article is to present the nonlinear unsteady behaviour for jet transport aircraft response to serious atmosphere turbulence in cruise flight and to provide the appropriate mitigation concepts for pilots in the pilot training course of the IATA – Loss of Control In-flight (LOC-I) program. The flight data of a twin-jet and a four-jet transport aircraft encountered serious atmosphere turbulence are the study cases for this article. This study uses flight data mining and fuzzy-logic modeling of artificial intelligence techniques to establish nonlinear unsteady aerodynamic models. Since the rapid change of aerodynamic characteristics in turbulence, so the study uses decoupled longitudinal and lateral-directional motion to identify various eigenvalue motion modes of nonlinear unsteady behaviour through digital 6-DOF flight simulation. It is found that the changes of the main flight variables in the aerodynamic scene and flight environment of the two aircraft are different, but the profiles of five eigenvalue motion modes are actually similar. Those similar eigenvalue motion modes can formulate preventive actions related to the flight handling quality for safe and efficient control by pilots to execute the flight tasks. The one with a large drop height during the ups and downs motion between the two is chosen to construct the movement mechanism of nonlinear unsteady behaviours. The assessments of dynamic stability characteristics of nonlinear unsteady behaviour based on the approaches of oscillatory motion and eigenvalue motion modes related to loss of control will be demonstrated in this article. To develop preventive actions, the situation awareness response to the induced mutation of nonlinear unsteady behaviour on the pilot’s operations will be a further research task in the future.
Previous studies in rodents suggest that mismatch between fetal and postnatal nutrition predisposes individuals to metabolic diseases. We hypothesized that in nonhuman primates (NHP), fetal programming of maternal undernutrition (MUN) persists postnatally with a dietary mismatch altering metabolic molecular systems that precede standard clinical measures. We used unbiased molecular approaches to examine response to a high fat, high-carbohydrate diet plus sugar drink (HFCS) challenge in NHP juvenile offspring of MUN pregnancies compared with controls (CON). Pregnant baboons were fed ad libitum (CON) or 30% calorie reduction from 0.16 gestation through lactation; weaned offspring were fed chow ad libitum. MUN offspring were growth restricted at birth. Liver, omental fat, and skeletal muscle gene expression, and liver glycogen, muscle mitochondria, and fat cell size were quantified. Before challenge, MUN offspring had lower body mass index (BMI) and liver glycogen, and consumed more sugar drink than CON. After HFCS challenge, MUN and CON BMIs were similar. Molecular analyses showed HFCS response differences between CON and MUN for muscle and liver, including hepatic splicing and unfolded protein response. Altered liver signaling pathways and glycogen content between MUN and CON at baseline indicate in utero programming persists in MUN juveniles. MUN catchup growth during consumption of HFCS suggests increased risk of obesity, diabetes, and cardiovascular disease. Greater sugar drink consumption in MUN demonstrates altered appetitive drive due to programming. Differences in blood leptin, liver glycogen, and tissue-specific molecular response to HFCS suggest MUN significantly impacts juvenile offspring ability to manage an energy rich diet.
The Aerospace Integration Research Centre (AIRC) at Cranfield University offers industry and academia an open environment to explore the opportunities for efficient integration of aircraft systems. As a part of the centre, Cranfield University, Rolls-Royce, and DCA Design International jointly have developed the Future Systems Simulator (FSS) for the purpose of research and development in areas such as human factors in aviation, single-pilot operations, future cockpit design, aircraft electrification, and alternative control approaches. Utilising the state-of-the-art modularity principles in simulation technology, the FSS is built to simulate a diverse range of current and novel aircraft, enabling researchers and industry partners to conduct experiments rapidly and efficiently. Central to the requirement, a unique, user-experience-centred development and design process is implemented for the development of the FSS. This paper presents the development process of such a flight simulator with an innovative flight deck. Furthermore, the paper demonstrates the FSS’s capabilities through case studies. The cutting-edge versatility and flexibility of the FSS are demonstrated through the diverse example research case studies. In the final section, the authors provide guidance for the development of an engineering flight simulator based on lessons learned in this project.
Schizophrenia spectrum disorders are brain diseases that are developmental dementias (dementia praecox). Their pathology begins in utero with psychosis most commonly becoming evident in adolescence and early adulthood. It is estimated they afflict the U.S. population at a prevalence rate of approximately 0.8%. Genetic studies indicate that these brain diseases are about 80% determined by genes and about 20% determined by environmental risk factors. Inheritance is polygenic with some 270 gene loci having been identified as contributing to the risk for schizophrenia. Interestingly, many of the identified gene loci and gene polymorphisms are involved in brain formation and maturation. The identified genetic and epigenetic risks give rise to a brain in which neuroblasts migrate abnormally, assume abnormal locations and orientations, and are vulnerable to excessive neuronal and synaptic loss, resulting in overt psychotic illness. The illness trajectory of schizophrenia then is one of loss of brain mass related to the number of active psychotic exacerbations and the duration of untreated illness. In this context, molecules such as dopamine, glutamate, and serotonin play critical roles with respect to positive, negative, and cognitive domains of illness. Acutely, antipsychotics ameliorate active psychotic illness, especially positive signs and symptoms. The long-term effects of antipsychotic medications have been debated; however, the bulk of imaging data suggest that antipsychotics slow but do not reverse the illness trajectory of schizophrenia. Long-acting injectable antipsychotics (LAI) appear superior in this regard. Clozapine remains the “gold standard” in managing treatment-resistant schizophrenia.
Soluble Intercellular Adhesion Molecule-1 (sICAM-1) has emerged as an inflammatory biomarker of many essential functions. We investigated the level of sICAM-1 influenced by Clonorchis sinensis (C. sinensis) co-infection in chronic hepatitis B (CHB) patients to explore the degree of liver tissue inflammation and liver function damage after co-infection. The study included data from patients with C. sinensis mono-infection (n=27), hepatitis B virus (HBV) mono-infection (n=32), C. sinensis and HBV co-infection (n=24), post-hepatitis B liver cirrhosis (n=18), post-hepatitis B liver cirrhosis co-infected with C. sinensis (n=16), and healthy controls (n=39). The level of sICAM-1 was measured with specific enzyme-linked immunosorbent assay method. Compared to the healthy control group, all the experimental groups had significantly higher serum sICAM-1 levels. The levels of sICAM-1 in co-infected groups were significantly higher compared to the mono-infection groups and were positively correlated with the levels of glutamate aminotransferase (ALT) and aspartate aminotransferase (AST). Our research findings confirmed that co-infection could exacerbate liver tissue inflammation and liver function damage in patients, could raise the sICAM-1 level, and may lead to the chronicity of HBV infection. These results provide clues for pathological mechanism study and formulating treatment plans.
Society of Thoracic Surgeons Congenital Heart Surgery Database is the largest congenital heart surgery database worldwide but does not provide information beyond primary episode of care. Linkage to hospital electronic health records would capture complications and comorbidities along with long-term outcomes for patients with CHD surgeries. The current study explores linkage success between Society of Thoracic Surgeons Congenital Heart Surgery Database and electronic health record data in North Carolina and Georgia.
Methods:
The Society of Thoracic Surgeons Congenital Heart Surgery Database was linked to hospital electronic health records from four North Carolina congenital heart surgery using indirect identifiers like date of birth, sex, admission, and discharge dates, from 2008 to 2013. Indirect linkage was performed at the admissions level and compared to two other linkages using a “direct identifier,” medical record number: (1) linkage between Society of Thoracic Surgeons Congenital Heart Surgery Database and electronic health records from a subset of patients from one North Carolina institution and (2) linkage between Society of Thoracic Surgeons data from two Georgia facilities and Georgia’s CHD repository, which also uses direct identifiers for linkage.
Results:
Indirect identifiers successfully linked 79% (3692/4685) of Society of Thoracic Surgeons Congenital Heart Surgery Database admissions across four North Carolina hospitals. Direct linkage techniques successfully matched Society of Thoracic Surgeons Congenital Heart Surgery Database to 90.2% of electronic health records from the North Carolina subsample. Linkage between Society of Thoracic Surgeons and Georgia’s CHD repository was 99.5% (7,544/7,585).
Conclusions:
Linkage methodology was successfully demonstrated between surgical data and hospital-based electronic health records in North Carolina and Georgia, uniting granular procedural details with clinical, developmental, and economic data. Indirect identifiers linked most patients, consistent with similar linkages in adult populations. Future directions include applying these linkage techniques with other data sources and exploring long-term outcomes in linked populations.
Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.
Methods
We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.
Results
The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).
Conclusion
The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.
The goal of this chapter is to show the reader a systematic approach to the assessment and treatment of aggression and violence arising from psychosis and a review of evidence-based pharmacological interventions for aggression and violence arising from impulsivity in the context of traumatic brain injury or neurocognitive disorder. In turn, we consider an algorithmic approach to the assessment and treatment of psychotically driven aggression and violence, the approach to treatment-resistance in schizophrenia spectrum disorders, data-supported treatment of aggression and violence related to traumatic brain injury, and, finally, data-supported pharmacological treatment of aggression and violence in the context of major neurocognitive disorder.
Through a combination of laboratory experiments and theoretical models, we investigate the interaction of a mean upwelling through a closed basin with a vertical buoyancy flux. The fluid is mixed by a horizontally oscillating rake, which either traverses the whole basin or which oscillates just near one vertical boundary. We first review the steady state and demonstrate that, in both mixing regimes, the vertical density profile across the basin is controlled by the steady-state balance between the upward advective and diffusive fluxes of salinity as described by the classical model introduced by Munk (Deep-Sea Res., vol. 13, issue 4, 1966, pp. 707–730). However, with boundary mixing, we show that both the upwelling and the buoyancy transport are localised to the mixing zone near the boundary, and the interior fluid is stagnant. We then develop a model to describe the transient evolution of the system if there is either a discrete increase or gradual decrease to the buoyancy flux. In the boundary mixing case, the change in the buoyancy flux at the lower boundary leads to a change in the buoyancy of the fluid in the boundary mixing region, and this induces a transient, buoyancy-driven flow in the boundary region in addition to the steady upwelling. In turn, an equal and opposite vertical flow develops in the interior, and this leads to a change in the density stratification of the interior fluid as the system adjusts to a new equilibrium. However, in our experiments, there is no vertical mixing in the interior and interior fluid may upwell or downwell dependent on the change to the buoyancy forcing. We discuss the implications of our results for the transport and mixing in the deep ocean, and the associated interpretation of field experiments.