NUI Maynooth Eprint Archive
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Integrate-and-Differentiate Approach to Nonlinear System Identification
No full textIn this paper, we consider a problem of parametric identification of a piece-wise linear mechanical system described by ordinary differential equations. We reconstruct the phase space of the investigated system from accelerometer data and perform parameter identification using iteratively reweighted least squares. Two key features of our study are as follows. First, we use a differentiated governing equation containing acceleration and velocity as the main independent variables instead of the conventional governing equation in velocity and position. Second, we modify the iteratively reweighted least squares method by including an auxiliary reclassification step into it. The application of this method allows us to improve the identification accuracy through the elimination of classification errors needed for parameter estimation of piece-wise linear differential equations. Simulation of the Duffing-like chaotic mechanical system and experimental study of an aluminum beam with asymmetric joint show that the proposed approach is more accurate than state-of-the-art solutions
Factor structure and symptom classes of ICD-11 complex posttraumatic stress disorder in a South Korean general population sample with adverse childhood experiences
No full textBackground
Adverse childhood experiences (ACE) are known as risk factors for poor adulthood mental health, including ICD-11 posttraumatic stress disorder (PTSD) and complex PTSD (CPTSD). While many studies focused on the association of ACE and CPTSD, examining variant symptom patterns related to ACE is lacking.
Objective
This study aimed to identify the factorial validity of the ICD-11 CPTSD and its distinctive symptom classes in Korean adults with ACE from a representative community sample and examine the risk factors and clinical symptoms that distinguish the CPTSD symptom classes.
Methods
We conducted a cross-sectional retrospective study with the International Trauma Questionnaire data from 800 adult general population with ACE histories. A confirmatory factor analysis, latent class analysis, analysis of variance and multinomial logistic regression were conducted.
Results
Results of confirmatory factor analysis supported a six-factor correlation model, while a two-factor higher-order model with PTSD and disturbances in self-organization (DSO) as correlated constructs also showed excellent fit. A latent class analysis identified six classes, including a distinctive ICD-11 CPTSD and PTSD, additionally a DSO with sense of threat, a DSO, an emotion dysregulation, and a low symptom class, showing distinguished features in ACE patterns, lifetime trauma, depression, somatization, panic disorder, and subtypes of dissociation.
Conclusions
The factorial and discriminant validity of ICD-11 CPTSD for Korean ACE survivors were confirmed. Recognizing the pervasive impact of patterns of ACEs and lifetime trauma would be helpful in access to and delivery of appropriate mental health services. Variation in symptom presentations of CPTSD and the role of dissociation should be of concern, that it may bring complicated life outcomes to people with ACEs
Views and Experiences of People with Intellectual Disabilities to Improve Access to Assistive Technology: Perspectives from India
No full textPurpose: People with intellectual disabilities are deeply affected by health inequity, which is also reflected in their access to and use of assistive technology (AT). Including the perspectives of adults with intellectual disabilities and their caregivers, together with the views of local health professionals, suppliers of AT and policy-makers, this paper aims to provide an overview of factors influencing access to AT and its use by people with intellectual disabilities in Bangalore, a southern region of India.
Method: Face-to-face interviews were conducted with 15 adults with
intellectual disabilities (ranging from mild to profound) and their caregivers,
and with 16 providers of AT. This helped to gain insight into the current use,
needs, knowledge, awareness, access, customisation, funding, follow-up, social inclusion, stigma and policies around AT and intellectual disability.
Results: Access to AT was facilitated by community fieldworkers and services to reach out and identify people with intellectual disabilities. Important barriers
were stigma, and lack of knowledge and awareness among parents. Factors related to continued use were the substantial dependence on the care system to use AT, and the importance of AT training and instructions for the user and the care system.
Conclusion and Implications: The barriers and facilitators related to AT for people with intellectual disabilities differ from other populations in need. The findings of this study can be used to inform and adjust country policies and
frameworks whose aim is to improve access to AT and enhance the participation
of people with intellectual disabilities within their communities
Detecting and describing stability and change in COVID-19 vaccine receptibility in the United Kingdom and Ireland
No full textCOVID-19 continues to pose a threat to global public health. Multiple safe and effective vaccines against COVID-19 are available with one-third of the global population now vaccinated. Achieving a sufficient level of vaccine coverage to suppress COVID-19 requires, in part, sufficient acceptance among the public. However, relatively high rates of hesitance and resistance to COVID-19 vaccination persists, threating public health efforts to achieve vaccine-induced population protection. In this study, we examined longitudinal changes in COVID-19 vaccine acceptance, hesitance, and resistance in two nations (the United Kingdom and the Republic of Ireland) during the first nine months of the pandemic, and identified individual and psychological factors associated with consistent non-acceptance of COVID-19 vaccination. Using nationally representative, longitudinal data from the United Kingdom (UK; N = 2025) and Ireland (N = 1041), we found that (1) COVID-19 vaccine acceptance declined in the UK and remained unchanged in Ireland following the emergence of approved vaccines; (2) multiple subgroups existed reflecting people who were consistently willing to be vaccinated (‘Accepters’: 68% in the UK and 61% in Ireland), consistently unwilling to be vaccinated (‘Deniers’: 12% in the UK and 16% in Ireland), and who fluctuated over time (‘Moveable Middle’: 20% in the UK and 23% in Ireland); and (3) the ‘deniers’ and ‘moveable middle’ were distinguishable from the ‘accepters’ on a range of individual (e.g., younger, low income, living alone) and psychological (e.g., distrust of scientists and doctors, conspiracy mindedness) factors. The use of two high-income, Western European nations limits the generalizability of these findings. Nevertheless, understanding how receptibility to COVID-19 vaccination changes as the pandemic unfolds, and the factors that distinguish and characterise those that are hesitant and resistant to vaccination is helpful for public health efforts to achieve vaccine-induced population protection against COVID-19
A new floating-point adder FPGA-based implementation using RN-coding of numbers
No full textA well-known problem in the computer science area is related to numerical data representation,
which directly affects adder circuits’ design and a reason to have different formats: IEEE Std.
754, Half-Unit-Biased (HUB), and Round-to-Nearest (RN). RN has an advantage that rounding
to nearest is equivalent to a word truncation. It avoids double rounding errors and intermediate
rounding steps with an exact conversion between formats, making it applicable to general
problems. However, there is a lack of research on the hardware implementation of the RN
representation. In this work, we propose hardware architectures for binary and floating-point
adders, analyzing for the latter its performance in terms of error and resource consumption
in FPGAs. To accomplish this, we have developed a one-bit RN-based adder that allows
modular designs, considering an efficient signal propagation to obtain new architectures for
both binary and floating-point single-precision adders. The results open new perspectives for
further applications
The Role of the Circadian System in Attention Deficit Hyperactivity Disorder
No full textAttention deficit hyperactivity disorder
(ADHD) is a common neurodevelopmental
condition characterised by the core symptoms
of inattention, impulsivity and hyperactivity.
Similar to many other neuropsychiatric
conditions, ADHD is associated with very
high levels of sleep disturbance. However, it
is not clear whether such sleep disturbances
are precursors to, or symptoms of, ADHD.
Neither is it clear through which mechanisms
sleep and ADHD are linked. One possible link
is via modulation of circadian rhythms. In this
chapter we overview the evidence that ADHD
is associated with alterations in circadian processes, manifesting as later chronotype and
delayed sleep phase in ADHD, and examine
some mechanisms that may lead to such
changes. We also interrogate how the circadian clock may be a substrate for therapeutic
intervention in ADHD (chronotherapy) and
highlight important new questions to be
addressed to move the field forward
Artificial intelligence in supply chain management: A systematic literature review
No full textThis paper seeks to identify the contributions of artificial intelligence (AI) to supply chain management (SCM)
through a systematic review of the existing literature. To address the current scientific gap of AI in SCM, this
study aimed to determine the current and potential AI techniques that can enhance both the study and practice of
SCM. Gaps in the literature that need to be addressed through scientific research were also identified. More
specifically, the following four aspects were covered: (1) the most prevalent AI techniques in SCM; (2) the potential AI techniques for employment in SCM; (3) the current AI-improved SCM subfields; and (4) the subfields
that have high potential to be enhanced by AI. A specific set of inclusion and exclusion criteria are used to
identify and examine papers from four SCM fields: logistics, marketing, supply chain and production. This paper
provides insights through systematic analysis and synthesis
Multi-Code Multi-Rate Universal Maximum Likelihood Decoder using GRAND
No full textWe present the first fully-integrated universal Max-
imum Likelihood decoder in 40 nm CMOS using the Guessing
Random Additive Noise Decoding (GRAND) algorithm for low-
power applications. The 0.83 mm2 multi-code multi-rate universal
decoder can efficiently decode any code of length up to 128 bits
with 1 μs latency at 68 MHz. Dynamic clock gating leveraging
noise statistics reduces the average power dissipation to 3.75 mW
at 1.1 V or 30.6 pJ/decoded bit with a throughput of 122.6 Mb/s.
Universal decoding reduces hardware footprint, and the design
allows seamless swapping between codebooks with no downtime,
enabling use by multiple applications without switch-over