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A Dual-Center Observational Review of Hospital-Based Palliative Care in Patients Dying With COVID-19
No full textThe current coronavirus disease 2019 (COVID-19) pandemic has put significant strain on all aspects of health care delivery, including palliative care services. Given the high mortality from this disease, particularly in the more vulnerable members of society, it is important to examine how best to deliver a high standard of end-of-life care during this crisis. This case series collected data from two acute hospitals examining the management of patients diagnosed with COVID-19 who subsequently died (n = 36) and compared this with national and local end-of-life audit data for all other deaths. Our results demonstrated a shorter dying phase (38.25 hours vs. 74 hours) and higher rates of syringe driver use (72% vs. 33% in local audits), although with similar average mediation doses. Of note was the significant heterogeneity in the phenotype of deterioration in the dying phase, two distinct patterns emerged, with one group demonstrating severe illness with a short interval between symptom onset and death and another group presenting with a more protracted deterioration. This brief report suggests a spectrum of mode of dying. Overall, the cohort reflects previously described experiences, with increased frailty (median Clinical Frailty Scale score of 5) and extensive comorbidity burden. This brief report provides clinicians with a contemporaneous overview of our experience, knowledge, and pattern recognition when caring for people with COVID-19 and highlights the value of proactive identification of patients and risk of deterioration and palliation
The Missing Link: Monetary Policy And The Labor Share
No full textThe textbook New-Keynesian (NK) model implies that the labor share is pro-cyclical
conditional on a monetary policy shock. We present evidence that a monetary policy
tightening robustly increased the labor share and decreased real wages during the Great
Moderation period in the US, the Euro Area, the UK, Australia, and Canada. We show
that this is inconsistent not only with the basic NK model, but with medium scale NK
models commonly used for monetary policy analysis and where it is possible to break the
direct link between the labor share and the inverse markup. Our results imply that either
NK models are unable to separate the dynamics of the labor share from the markup, or
that markups do not respond in the way NK models predict
A Dynamic Bayesian Network Approach for Analysing Topic-Sentiment Evolution
No full textSentiment analysis is one of the key tasks of natural language understanding. Sentiment
Evolution models the dynamics of sentiment orientation over time. It can help people have a more profound
and deep understanding of opinion and sentiment implied in user generated content. Existing work mainly
focuses on sentiment classi�cation, while the analysis of how the sentiment orientation of a topic has been
in�uenced by other topics or the dynamic interaction of topics from the aspect of sentiment has been ignored.
In this paper, we propose to construct a Gaussian Process Dynamic Bayesian Network to model the dynamics
and interactions of the sentiment of topics on social media such as Twitter. We use Dynamic Bayesian
Networks to model time series of the sentiment of related topics and learn relationships between them.
The network model itself applies Gaussian Process Regression to model the sentiment at a given time point
based on related topics at previous time.We conducted experiments on a real world dataset that was crawled
from Twitter with 9.72 million tweets. The experiment demonstrates a case study of analysing the sentiment
dynamics of topics related to the event Brexit
An avatar-based system for Arabic sign language to enhance hard-of-hearing and deaf students' performance in a fundamentals of computer programming course.
No full textDifferent studies have shown that deaf and hard of hearing (DHH) students face many difficulties in learning applied disciplines in science, engineering, technology, and mathematics. The development of videos or avatars to aid in the teaching of programming for positively affects DHH students. The use of sign language increases the understanding of DHH, therefore, it will be utilized in the proposed virtual and Augmented reality environment which will hopefully improve students’ performance in learning about computer programming as well as enhance their engagement and facilitate the accessibility of learning for learners suffering from deafness in Saudi Arabia.
This thesis aims to help deaf and hearing-impaired students in Saudi Arabia to tackle applied subjects like computer programming and equip them for careers in the technological field. Computer programming is an integral component in this field that can greatly assist in developing technological solutions.
The study reveals important considerations in the creation of a virtual learning environment for DHH students to learn computer programming and showed that DHH students performed well, understood the topics, and could write a small program. The research methodology shows how to create an avatar for teaching computer programming using Arabic sign language. This gives DHH students opportunities to join the scientific world as they were previously unable to do so. Three expert signers evaluated the proposed Arabic Sign Language (ArSL) dictionary with 450 technological terms and added 114 new signs to the signer dictionary.
Therefore, to make an overall evaluation, Augmented Reality (AR) as a knowledge technology will be applied through the 6 unit of the proposed “Java programming” course. Accordingly, 6 designed flashcards will be used, one flashcard for each course unit to retrieve summarized knowledge discovery of this unit. Also, many tools will be used to support augmented reality such as Vuforia and Unity library
Association of self-reported presenting symptoms and timeliness of help-seeking among adolescents and young adults with cancer
No full textImportance: Evidence relating to the presenting symptoms of adolescent and young adults with
cancer can support the development of early diagnosis interventions.
Objective: To examine common presenting symptoms in adolescents and young adults aged 12–24
years subsequently diagnosed with cancer and potential variation in time to help-seeking by
presenting symptom.
Design: Cross-sectional analysis of the BRIGHTLIGHT cohort. Information on 17 pre-specified
presenting symptoms and the symptom-onset-to-help-seeking interval (patient interval) was
collected through structured face-to-face interviews and linked to national cancer registry data.
Setting: Multi-centre study across English hospitals.
Exposures: Self-reported presenting symptoms.
Main Outcomes and Measures: Frequencies of presenting symptoms and associated ‘symptom
signatures’ by cancer group. Proportion of patients with each presenting symptom whose patient
interval was greater than one month.
Results: The study population consisted of 803 adolescents and young adults with valid symptom
information (55% male, 63% aged 19–24 years, and 88% white ethnicity). The number of symptoms
varied by cancer group: for example, 86% of leukaemia patients presented with two or more
symptoms while only 31% of melanoma patients presented with multiple symptoms. In total, 352
unique symptom combinations were reported, with the 10 most frequent combinations accounting
for 38% of patients.
Lump or swelling was reported by over half the patients (prevalence (95% CI): 52% (49–56%)). Other
common presenting symptoms across all cancers were extreme tiredness (38% (35–42%)),
unexplained pain (35% (32–38%)), night sweats (24% (21–27%)), lymphadenopathy (24% (21–27%)),
and weight loss (24% (21–27%)). The relative frequencies of presenting symptoms also varied by
cancer group; some symptoms (such as lump/swelling) were highly prevalent across several cancer
groups (seen in >50% of patients diagnosed with lymphomas, germ cell tumours, carcinomas, bone
tumours, and soft-tissue sarcomas). Over one in four patients (27%) reported a patient interval
longer than one month: this varied from 6% (fits/seizures) to 43% (recurrent infections).
Conclusions and Relevance: Adolescents and young adults with cancer present with a broad
spectrum of symptoms, some of which are shared across cancer types. The findings point to
discordant presenting symptom prevalence estimates when information is obtained from patient
report versus health records
Sexual Morbidity Assessment in Gynae-oncology follow-up: development of the SWELL-CE (Sexual Well-being after Cervical or Endometrial Cancer) patient reported outcome measure
No full textIndividuals’ intentions to engage in last chance tourism: applying the value-belief-norm model
No full textFor tourism to be entirely sustainable, one cannot travel. This is impossible. This paradox is particularly evident within last chance tourism (LCT), where tourists, seeking experiences with vanishing animals and land/seascapes, can accelerate the decline of those very attractions. Though recent studies hint that those with the highest intentions to visit LCT destinations are also some of the most concerned with climate change, no study has assessed the psychological drivers that may help explain why individuals are increasingly engaging in this paradox. Drawing on the VBN model, this research examines a theoretical framework to assess the psychological drivers behind individuals’ intention to engage in environmentally responsible behavior while traveling and, ultimately, their desire to participate in LCT. Results reveal that a set of environmentally referent cognitions (i.e., values, environmental worldview, awareness of consequences, and ascription of responsibility) lead to personal norms activation, which then influence tourists’ intent to behave in pro-sustainable ways and, ultimately, individuals’ intentions to engage in LCT. Findings are important as they further confirm the benefits of using VBN theory within an LCT context. For practitioners, this research strengthens the appeal of sustainable tourism operations to secure business and receive positive word-of-mouth from potential LCT tourists
The stylistic development of the Grateful Dead : 1965-1973.
No full textThe Grateful Dead formed in 1965 and developed alongside the Haight-Ashbury counterculture in California. The band initially consisted of Jerry Garcia (lead guitar), Bob Weir (Rhythm Guitar), Phil Lesh (bass guitar), Ron ‘Pigpen’ McKernan (keyboard) and Bill Kreutzmann (Drums) and remained active until Garcia’s death in 1995. The Grateful Dead were fundamental to the development of the musical style of the jamband, and their influence continues to be observed widely today.
Whilst the San Francisco countercultural scene has been studied extensively from a sociological perspective, little scholarly attention has hitherto been given to the music itself, with the exception of Graham Boone’s analysis of ‘Dark Star’ and David Malvinni’s book on rock improvisation. Yet the Grateful Dead developed a unique style that combines large improvisations with influences from many popular, traditional and world musical roots, whose study therefore sheds much light on the emergence of jambands from a profusion of styles, and how such extensive poly-instrumental jams can be created. It is therefore of importance to the wider field of popular musicology that this influential and popular musical genre is subject to academic scrutiny and discourse.
This thesis will focus on the musical characteristics that define the Grateful Dead’s early sound from 1965 -1973 through the analysis of selected case studies. It will outline the origins of the Grateful Dead, from their beginnings within the San Francisco scene. Exploration of the historical and cultural context in which their music developed will enable the subsequent analyses to be located within the sociocultural context in which it was shaped
Defeating stochasticity: coalescence timescales of massive black holes in galaxy mergers
No full textThe coalescence of massive black hole binaries (BHBs) in galactic mergers is the primary
source of gravitational waves (GWs) at low frequencies. Current estimates of GW detection
rates for the Laser Interferometer Space Antenna and the Pulsar Timing Array vary by three
orders of magnitude. To understand this variation, we simulate the merger of equal-mass,
eccentric, galaxy pairs with central massive black holes and shallow inner density cusps. We
model the formation and hardening of a central BHB using the Fast Multiple Method as a
force solver, which features a O¹Nº scaling with the number N of particles and obtains results
equivalent to direct-summation simulations. At N � 5�105, typical for contemporary studies,
the eccentricity of the BHBs can vary significantly for different random realisations of the
same initial condition, resulting in a substantial variation of the merger timescale. This scatter
owes to the stochasticity of stellar encounters with the BHB and decreases with increasing N.
We estimate that N � 107 within the stellar half-light radius suffices to reduce the scatter in
the merger timescale to � 10%. Our results suggest that at least some of the uncertainty in
low-frequency GW rates owes to insufficient numerical resolution
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