Opportunities for maser studies with the Square Kilometre Array

The Square Kilometre Array (SKA) is the radio telescope of the next generation, providing an increase in sensitivity and angular resolution of two orders of magnitude over existing telescopes. Currently, the SKA is expected to span the frequency range 0.1-25 GHz with capabilities including a wide field-of-view and measurement of polarised emission. Such a telescope has enormous potential for testing fundamental physical laws and producing transformational discoveries. Important science goals include using H2O megamasers to make precise estimates of H0, which will anchor the extragalactic distance scale, and to probe the central structures of accretion disks around supermassive black holes in AGNs, to study OH megamasers associated with extreme starburst activity in distant galaxies and to study with unprecedented precision molecular gas and star formation in our Galaxy.Comment: 5 pages, to appear in: IAU Symposium 242 Astrophysical Masers and their Environment

Stool frequency recording in severe acute malnutrition ('StoolSAM'); an agreement study comparing maternal recall versus direct observation using diapers.

BACKGROUND: Approximately 50% of the deaths of children under the age of 5 can be attributed to undernutrition, which also encompasses severe acute malnutrition (SAM). Diarrhoea is strongly associated with these deaths and is commonly diagnosed solely based on stool frequency and consistency obtained through maternal recall. This trial aims to determine whether this approach is equivalent to a 'directly observed method' in which a health care worker directly observed stool frequency using diapers in hospitalised children with complicated SAM. METHODS: This study was conducted at 'Moyo' Nutritional Rehabilitation Unit, Queen Elizabeth Central Hospital, Malawi. Participants were children aged 5-59 months admitted with SAM. We compared 2 days of stool frequency data obtained with next-day maternal-recall versus a 'gold standard' in which a health care worker observed stool frequency every 2 h using diapers. After study completion, guardians were asked their preferred method and their level of education. RESULTS: We found poor agreement between maternal recall and the 'gold standard' of directly observed diapers. The sensitivity to detect diarrhoea based on maternal recall was poor, with only 75 and 56% of diarrhoea cases identified on days 1 and 2, respectively. However, the specificity was higher with more than 80% of children correctly classified as not having diarrhoea. On day 1, the mean stool frequency difference between the two methods was -0.17 (SD; 1.68) with limits of agreement (of stool frequency) of -3.55 and 3.20 and, similarly on day 2, the mean difference was -0.2 (SD; 1.59) with limits of agreement of -3.38 and 2.98. These limits extend beyond the pre-specified 'acceptable' limits of agreement (±1.5 stool per day) and indicate that the 2 methods are non-equivalent. The higher the stool frequency, the more discrepant the two methods were. Most primary care givers strongly preferred using diapers. CONCLUSIONS: This study shows lack of agreement between the assessment of stool frequency in SAM patients using maternal recall and direct observation of diapers. When designing studies, one should consider using diapers to determining diarrhoea incidence/prevalence in SAM patients especially when accuracy is essential. TRIAL REGISTRATION NUMBER: ISRCTN11571116 (registered 29/11/2013)

Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?

Learning algorithms become more powerful, often at the cost of increased complexity. In response, the demand for algorithms to be transparent is growing. In NLP tasks, attention distributions learned by attention-based deep learning models are used to gain insights in the models' behavior. To which extent is this perspective valid for all NLP tasks? We investigate whether distributions calculated by different attention heads in a transformer architecture can be used to improve transparency in the task of abstractive summarization. To this end, we present both a qualitative and quantitative analysis to investigate the behavior of the attention heads. We show that some attention heads indeed specialize towards syntactically and semantically distinct input. We propose an approach to evaluate to which extent the Transformer model relies on specifically learned attention distributions. We also discuss what this implies for using attention distributions as a means of transparency.Comment: To appear at FACTS-IR 2019, SIGI

The Prediction Accuracy of Digital Orthodontic Setups for the Orthodontic Phase before Orthognathic Surgery.

The purpose of this study was to verify whether pre-treatment digital setups can accurately predict the tooth positions after presurgical orthodontic treatment has been performed in a 3-dimensional way. Twenty-six patients who underwent a combined orthodontic-orthognathic surgical treatment were included. Pre-treatment digital dental models were merged with cone beam computed tomography (CBCT) scans. One operator fabricated virtual setups to simulate the tooth movements of the presurgical orthodontic treatment. Prior to surgery, digital dental models were merged with the CBCT scans. Differences between de virtual setups and the presurgical dental models were calculated using linear mixed model analyses. Differences in tooth displacements exceeding the boundaries of clinical acceptance (>2 degrees for rotations and >0.6 mm for translations) were found in 75% of the rotational and 52% of translational mean differences in the maxilla and in 74% of the rotational mean differences and 44% of the translational mean differences in the mandible. Significant differences were found for all tooth types and in all tooth displacement directions with significant effects of extractions and surgically assisted rapid maxillary expansion (SARME) procedures. The accuracy of the digital setup is still too limited to correctly simulate the presurgical orthodontic treatment

The effect of lip closure on palatal growth in patients with unilateral clefts

Objectives The objective of this study was to compare maxillary dimensions and growth in newborns with Complete Unilateral Cleft Lip and Palate (UCLP) to healthy newborns before and after cheiloplasty. Additionally, a palatal growth curve is constructed to give more information about the natural growth before surgical intervention. Methods Twenty-eight newborns with complete UCLP were enrolled in this study. Multiple plaster-casts of each child during their first year were collected and grouped in before and after cheiloplasty. A previous developed semi-automatic segmentation tool was used to assess the maxillary dimensions and were compared to a healthy control group. Z-scores were calculated to indicate differences between the two populations and if cheiloplasty had influence on maxillary growth. Furthermore, the prediction model created in a previous study was used to indicate differences between predictions and the outcome in UCLP measurements. The analysis was tested for inter- and intra-observer variability. Results Results show differences in alveolar and palatal shape in UCLP patients in comparison with healthy controls. Prior to cheiloplasty an increased width and alveolar length was observed while the palatal depth was decreased. After cheiloplasty the widths moved towards normal but were still significantly larger

A semi-automatic three-dimensional technique using a regionalized facial template enables facial growth assessment in healthy children from 1.5 to 5.0 years of age.

Objectives To develop a semi-automatic technique to evaluate normative facial growth in healthy children between the age of 1.5 and 5.0 years using three-dimensional stereophotogrammetric images. Materials and Methods Three-dimensional facial images of healthy children at 1.5, 2.0, 2.5, 3.0, 4.0 and 5.0 years of age were collected and positioned based on a reference frame. A general face template was used to extract the face and its separate regions from the full stereophotogrammetric image. Furthermore, this template was used to create a uniform distributed mesh, which could be directly compared to other meshes. Average faces were created for each age group and mean growth was determined between consecutive groups for the full face and its separate regions. Finally, the results were tested for intra- and inter-operator performance. Results The highest growth velocity was present in the first period between 1.5 and 2.0 years of age with an average of 1.50 mm (±0.54 mm) per six months. After 2.0 years, facial growth velocity declined to only a third at the age of 5.0 years. Intra- and inter-operator variability was small and not significant. Conclusions The results show that this technique can be used for objective clinical evaluation of facial growth. Example normative facial averages and the corresponding facial growth between the age 1.5 and 5.0 years are shown. Clinical Relevance This technique can be used to collect and process facial data for objective clinical evaluation of facial growth in the individual patient. Furthermore, these data can be used as normative data in future comparative studies

Phospho-specific flow cytometry for pharmacodynamic monitoring of immunosuppressive therapy in transplantation

Organ transplant recipients frequently suffer from toxicity or from lack of efficacy of immunosuppressive drugs, which can be attributed to individual variations in drug sensitivity. This problem can be resolved by applying pharmacodynamic monitoring that focuses on measuring the biological effects of drugs. Here we discuss the new technique called phospho-specific flow cytometry to monitor the activity of intracellular immune signaling pathways at the single-cell level in whole blood samples. Through this tool the efficacy of immunosuppressive medication can be assessed, novel targets can be identified, and differences in drug sensitivity between cells and patients can be clarified