We consider a bounded domain $\Omega$ of $\mathbb{R}^N$, $N\ge3$, $h$ and $b$
continuous functions on $\Omega$. Let $\Gamma$ be a closed curve contained in
$\Omega$. We study existence of positive ...solutions $u \in
H^1_0\left(\Omega\right)$ to the perturbed Hardy-Sobolev equation: $$ -\Delta
u+h u+bu^{1+\delta}=\rho^{-\sigma}_\Gamma u^{2^*_\sigma-1} \qquad \textrm{ in }
\Omega, $$ where $2^*_\sigma:=\frac{2(N-\sigma)}{N-2}$ is the critical
Hardy-Sobolev exponent, $\sigma\in 0,2)$, $0< \delta<\frac{4}{N-2}$ and
$\rho_\Gamma$ is the distance function to $\Gamma$. We show that the existence
of minimizers does not depend on the local geometry of $\Gamma$ nor on the
potential $h$. For $N=3$, the existence of ground-state solution may depends on
the trace of the regular part of the Green function of $-\Delta+h$ and or on
$b$. This is due to the perturbative term of order ${1+\delta}$.
As foundation doctors, we have often found ourselves informing patients that a certain aspect of their medical information cannot be immediately found, either because it is on an electronic system we ...cannot access, or it is in a hospital that is unlinked to our own. Unsurprisingly, this frequently leaves patients flabbergasted and confused. We started to wonder: if patients' data are entered onto an electronic system: where do those data go? If medical data are searched for, where do those data come from? Why are there so many hidden sources of information that clinicians cannot access? In an ever-increasing digital sphere, electronic data will be the future of holistic health and social care planning, impacting every clinician's day-to-day role. From electronic healthcare records to the use of artificial intelligence solutions, this article will serve as an introduction to how data flows in modern healthcare systems.
We consider a bounded domain \(\Omega\) of \(\mathbb{R}^N\), \(N\ge3\), \(h\) and \(b\) continuous functions on \(\Omega\). Let \(\Gamma\) be a closed curve contained in \(\Omega\). We study ...existence of positive solutions \(u \in H^1_0\left(\Omega\right)\) to the perturbed Hardy-Sobolev equation: $$ -\Delta u+h u+bu^{1+\delta}=\rho^{-\sigma}_\Gamma u^{2^*_\sigma-1} \qquad \textrm{ in } \Omega, $$ where \(2^*_\sigma:=\frac{2(N-\sigma)}{N-2}\) is the critical Hardy-Sobolev exponent, \(\sigma\in 0,2)\), \(0< \delta<\frac{4}{N-2}\) and \(\rho_\Gamma\) is the distance function to \(\Gamma\). We show that the existence of minimizers does not depend on the local geometry of \(\Gamma\) nor on the potential \(h\). For \(N=3\), the existence of ground-state solution may depends on the trace of the regular part of the Green function of \(-\Delta+h\) and or on \(b\). This is due to the perturbative term of order \({1+\delta}\).
Background: Electronic Health Records hold detailed longitudinal information about each patient's health status and general clinical history, a large portion of which is stored within the ...unstructured text. Existing approaches focus mostly on structured data and a subset of single-domain outcomes. We explore how temporal modelling of patients from free text and structured data, using deep generative transformers can be used to forecast a wide range of future disorders, substances, procedures or findings. Methods: We present Foresight, a novel transformer-based pipeline that uses named entity recognition and linking tools to convert document text into structured, coded concepts, followed by providing probabilistic forecasts for future medical events such as disorders, substances, procedures and findings. We processed the entire free-text portion from three different hospital datasets totalling 811336 patients covering both physical and mental health. Findings: On tests in two UK hospitals (King's College Hospital, South London and Maudsley) and the US MIMIC-III dataset precision@10 0.68, 0.76 and 0.88 was achieved for forecasting the next disorder in a patient timeline, while precision@10 of 0.80, 0.81 and 0.91 was achieved for forecasting the next biomedical concept. Foresight was also validated on 34 synthetic patient timelines by five clinicians and achieved relevancy of 97% for the top forecasted candidate disorder. As a generative model, it can forecast follow-on biomedical concepts for as many steps as required. Interpretation: Foresight is a general-purpose model for biomedical concept modelling that can be used for real-world risk forecasting, virtual trials and clinical research to study the progression of disorders, simulate interventions and counterfactuals, and educational purposes.
Background and Aims: Human papillomavirus (HPV) is a known cause of cervical cancer which is the second-most common cancer among women worldwide. HPV vaccination is a primary prevention to reduce the ...occurrence of cervical cancer. This study assessed knowledge, attitude and uptake of HPV vaccine among female undergraduates in Lagos State Polytechnic (LASPOTECH). Methods: A descriptive cross-sectional survey was conducted among 400 female undergraduates of LASPOTECH in August 2018. Participants were selected using a multi-stage sampling technique and data was collected with a pretested, self-administered, semi-structured questionnaire. Univariate and bivariate analyses were conducted using IBM SPSS version 20. Statistically significant level was set at P ≤ 0.05. Results: Mean age of respondents was 21.3 ± 2 years. Only 11 (3%) of the respondents had good knowledge of HPV and the vaccine. However, majority of the respondents 356 (92.7%) had positive attitude towards uptake of HPV vaccine. Only 10 (2.6%) of the respondents had received a single dose of HPV vaccine. Age, level of study and number of sexual partners of the respondents were statistically significantly associated with knowledge and attitude towards the HPV vaccine (P ≤ 0.05). The most common reason stated by the respondents for none uptake of HPV vaccine was lack of information. Conclusion: Knowledge and uptake of HPV vaccination among the respondents were poor. However, majority had positive attitude towards uptake of the vaccine. It is recommended that information on HPV and the vaccine should be made available to increase the knowledge and the uptake among female undergraduates in Lagos State.
Low-Back Pain (LBP) is a common public health problem that is often worsened by maladaptive beliefs and disability. Thus, necessitating the need for availability of outcome measures to assess these ...sequelae among patients with chronic LBP. This study aimed to cross-culturally adapt and determine the psychometric properties of the Yoruba version of the ODI (ODI-Y).
The ODI-Y was cross-culturally adapted following the process involving forward translation, synthesis, backward translation, expert review, and pilot testing. Internal consistency and test-retest reliability of the ODI-Y were determined using the Cronbach's alpha and intra-class correlation. Other psychometric properties explored included the factor structure, convergent validity, standard error of measurement and the minimal detectable change.
One hundred and thirty-six patients with chronic LBP took part in the validation of the ODI-Y; 86 of these individuals took part in the test-retest reliability (within 1-week interval) of the translated instrument. The mean age of the respondents was 50.5±10.6years. The ODI-Y showed a high internal consistency, with a Cronbach's alpha (α) of 0.81. Test-retest of the Yoruba version of the ODI within 1-week interval yielded an Intra-Class Correlation coefficient of 0.89. The ODI-Y yielded a three-factor structure which accounted for 61.56% of the variance. Correlation of ODI-Y with the visual analogue scale was moderate (r = 0.30; p = 0.001). The standard error of measurement and minimal detectable change of the ODI-Y were 2.0 and 5.5.
The ODI was adapted into the Yoruba language and proved to have good psychometric properties that replicated the results of other obtainable versions. We recommend it for use among Yoruba speaking patients with LBP.
Thermal power plants utilizing gas and/or fuel oil are widespread globally and are fast replacing coal-fired plants in many regions. In this study, we investigated the impact of Egbin thermal power ...station (a gas and oil-fired plant situated in Lagos State, Nigeria) on physico-chemical characteristics and trace metals concentration of the proximal lagoon water, sediment, soil and biota. Temperature of the water ranged from 29.7 to 30.1 °C and reflected the influence of the power plant operations. Dissolved oxygen ranged from 5 to 8 mg/L, increasing steadily with distance away from the power plant. Highest concentration of As, Cd, Cr, Hg, Pb and Zn were measured in water and corresponding sediment from sampling point closest to the power plant. Furthermore, concentration of As, Cd, Cr and Pb in the lagoon water decreased steadily with distance away from the plant, strongly indicating that their levels in the lagoon are influenced by operations of the power plant. Atmospheric deposition of pollutants was responsible for Cr presence in proximal soil samples. Analysis of trace metals in biota species obtained from the lagoon provide evidence of bioaccumulation of Cd, Pb, Hg and Zn in crabs (
Callinectes amnicola
) and shrimps (
Penaeus notalis
), important sources of protein for inhabitants of coastal communities in the area. In addition to revealing a route of human exposure to sub-lethal doses of potentially harmful metallic elements, the study would be useful in predicting the impact of gas and oil-fired power plants in other geographical regions.
•Incineration of solid wastes containing Covid-19 face masks was studied.•Face masks increased the production of particulate matters from waste incineration.•Face masks caused emission of poisonous ...CO gas above environmental safe limit.•Face masks did not alter the nature of PAH compounds released by waste incineration.•Cd, Pb, As and Cu concentrations increased in ash residues due to face masks’ presence.
The COVID-19 pandemic caused the disposal of an unprecedentedly huge amount of medical face masks, part of which were burnt or incinerated alongside other solid wastes. In this study, we investigated how the presence of the common medical masks may have altered the nature and quantities of pollutants normally associated with the burning of solid wastes. It was found that the addition of increasing amount of face masks (at 1.82%, 3.71% and 5.67% by mass) to solid wastes had no influence on the types of pyrogenic PAHs (polycylic aromatic hydrocarbons) present in the combustion residues. However, presence of the masks at 5.67% led to a drastic reduction in PAHs concentration (∑16PAHs = 0.83 ± 0.047 mg/kg, compared to the concentration measured when the face masks were not incorporated, ∑16PAHs = 4.65 ± 0.23 mg/kg). Mixtures containing 3.71% and 5.67% of masks caused increases in total suspended particulate matter (TPM) by 475.6% and 796.4%, respectively. Presence of the masks at 3.71% and 5.67% also led to emission of poisonous carbon (II) oxide gas above the environmental safe limit of 29 mg/m3. Furthermore, addition of face masks led to higher concentrations of highly toxic metals (As, Cd, Pb and Cu) in the combustion residues of the solid wastes. Overall, this study demonstrates that medical face masks are better incinerated separately, rather than combining them with regular solid wastes. The findings are invaluable for ongoing management of used face masks in health facilities around the world, and in event of any future global or regional pandemic.
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