Need for standardization of the measurement of preoperative weight in bariatric surgical patients in the UK: A survey of British Obesity and Metabolic Surgery Society (BOMSS) members

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VideoAnalysis4ALL: An On-line Tool for the Automatic Fragmentation and Concept-based Annotation, and the Interactive Exploration of Videos.

This paper presents the VideoAnalysis4ALL tool that supports the automatic fragmentation and concept-based annotation of videos, and the exploration of the annotated video fragments through an interactive user interface. The developed web application decomposes the video into two different granularities, namely shots and scenes, and annotates each fragment by evaluating the existence of a number (several hundreds) of high-level visual concepts in the keyframes extracted from these fragments. Through the analysis the tool enables the identification and labeling of semantically coherent video fragments, while its user interfaces allow the discovery of these fragments with the help of human-interpretable concepts. The integrated state-of-the-art video analysis technologies perform very well and, by exploiting the processing capabilities of multi-thread / multi-core architectures, reduce the time required for analysis to approximately one third of the video’s duration, thus making the analysis three times faster than real-time processing

VoteLab: A Modular and Adaptive Experimentation Platform for Online Collective Decision Making

Digital democracy and new forms for direct digital participation in policy making gain unprecedented momentum. This is particularly the case for preferential voting methods and decision-support systems designed to promote fairer, more inclusive and legitimate collective decision-making processes in citizens assemblies, participatory budgeting and elections. However, a systematic human experimentation with different voting methods is cumbersome and costly. This paper introduces VoteLab, an open-source and thoroughly-documented platform for modular and adaptive design of voting experiments. It supports to visually and interactively build reusable campaigns with a choice of different voting methods, while voters can easily respond to subscribed voting questions on a smartphone. A proof-of-concept with four voting methods and questions on COVID-19 in an online lab experiment have been used to study the consistency of voting outcomes. It demonstrates the capability of VoteLab to support rigorous experimentation of complex voting scenarios

Designing Digital Voting Systems for Citizens: Achieving Fairness and Legitimacy in Digital Participatory Budgeting

Digital Participatory Budgeting (PB) has become a key democratic tool for resource allocation in cities. Enabled by digital platforms, new voting input formats and aggregation have been utilised. Yet, challenges in achieving fairness and legitimacy persist. This study investigates the trade-offs in various voting and aggregation methods within digital PB. Through behavioural experiments, we identified favourable voting design combinations in terms of cognitive load, proportionality, and perceived legitimacy. The research reveals how design choices profoundly influence collective decision-making, citizen perceptions, and outcome fairness. Our findings offer actionable insights for human-computer interaction, mechanism design, and computational social choice, contributing to the development of fairer and more transparent digital PB systems and multi-winner collective decision-making process for citizens.Comment: Submitted to ACM Digital Government: Research and Practic

Inhibin secretion in women with the polycystic ovary syndrome before and after treatment with progesterone

<p>Abstract</p> <p>Objectives</p> <p>It has been suggested that inhibin secretion is altered in women with the polycystic ovary syndrome (PCOS). However, the contribution of a preceding luteal phase has not been taken into account. The aim of the present study was to investigate whether progesterone in the context of a simulated luteal phase affects basal and FSH-induced inhibin secretion in women with PCOS and elevated LH.</p> <p>Methods</p> <p>Ten women with PCOS and 8 normally cycling women participated in an experimental procedure (Exp) involving the administration of a single injection of recombinant FSH (450 IU sc). In the women with PCOS, the procedure was performed before (Exp 1) and after a 20-day treatment with progesterone (Exp 2), while in the normal women on day 2 of the cycle (Exp 3). Inhibin A and B levels were measured in blood samples taken before and 24 hours after the FSH injection.</p> <p>Results</p> <p>Basal LH levels were significantly higher and inhibin A levels were significantly lower in the PCOS group compared to the control group, while inhibin B levels were comparable in the two groups. In the PCOS group, after treatment with progesterone inhibin A and LH but not inhibin B levels decreased significantly (p < 0.05). After the FSH injection, inhibin A and B levels increased significantly in the women with PCOS (Exp 1 and Exp 2) but not in the control women (Exp 3).</p> <p>Conclusions</p> <p>In women with PCOS, as compared to control women, the dissimilar pattern of inhibin A and inhibin B secretion in response to FSH appears to be independent of a preceding simulated luteal phase. It is possible that compared to normal ovaries, the PCOS ovaries are less sensitive to endogenous LH regarding inhibin A secretion and more sensitive to exogenous FSH stimulation in terms of inhibin A and inhibin B secretion.</p

Prognostic value of follicular fluid 25-OH vitamin D and glucose levels in the IVF outcome

Objectives: The aim of the present study was to measure serum and follicular fluid 25-OH vitamin D and glucose levels in women who underwent IVF-ET treatment and to further investigate whether the circulating 25-OH vitamin D and glucose levels correlate with IVF success. Methods: This prospective observational study included 101 consecutive women who underwent 101 IVF-ICSI ovarian stimulation cycles and were allocated to one of the three groups according to their follicular fluid 25-OH vitamin D concentrations. Group A (n = 31) with less than 20 ng/ml, group B (n = 49) with vitamin levels between 20.1 and 30 ng/ml and group C (n = 21) with more than 30 ng/ml vitamin concentration. Results: Follicular fluid vitamin levels significantly correlated with the quality of embryos in total (r = -0.27, p = 0.027), while the quality of embryos of group C were of lower quality as compared to those of groups A and B (p = 0.009). Follicular fluid glucose levels were lower in women of group C as compared to the respective levels of groups A and B (p = 0.003). Clinical pregnancy rate demonstrated in 14.5% in women of group C and 32.3% and 32.7% in groups A and B, respectively (p = 0.047). Conclusion: The data suggests that excess serum and follicular fluid vitamin levels in combination with decreased follicular fluid glucose levels have a detrimental impact on the IVF outcome

Sensing and Mining Urban Qualities in Smart Cities

The emergence of the Internet of Things in Smart Cities questions how the future citizens will perceive their predominant living and working environments and what quality of living they can experience within it, for instance the level of everyday stress. However, perception and experienced stress levels are challenging metrics to measure and are even more challenging to correlate with an underlying causal-effectual relationship in such stimulus abundant environments. The Internet of Things, enabled by several pervasive and ubiquitous devices such as smart phones and smart sensors, can provide real-time contextual information that can be used by advanced data science methodologies to generate new insights about urban qualities in Smart Cities and how they can be improved. The goal of this study is to show the predominant factors, which influence perceptual qualities of inhabitants in a Smart City equipped with sensing capabilities by the Internet of Things. To serve this goal, a novel data collection process for Smart Cities is introduced that involves (i) environmental data, such noise, dust, illuminance, temperature, relative humidity, (ii) location/mobility data, such as GNSS and citizens density detected via WiFi, and (iii) perceptual social data collected by citizens' responses in smart phones. These fine-grained real-time data can provide invaluable insights about the spatial correlations of the sensor measurements as well as the spatial and citizens' similarity illustrated. The data analysis illustrated reveals significant links between stress level and environmental changes observed

Intravitreal ranibizumab (Lucentis) in the treatment of retinal angiomatous proliferation (RAP).

BACKGROUND: Retinal angiomatous proliferation (RAP) is a distinct variant of neovascular age-related macular degeneration (AMD). The aim of this study is to evaluate the functional and anatomic outcome after intravitreal ranibizumab (Lucentis) treatment in patients with RAP. METHODS: Prospective study of consecutive patients with newly diagnosed or recurrent RAP treated with intravitreal ranibizumab at the Jules Gonin Eye Hospital between March 2006 and December 2007. Baseline and monthly follow-up visits included best-corrected visual acuity (BCVA), fundus exam and optical coherence tomography. Fluorescein and indocyanine green angiography were performed at baseline and repeated at least every 3 months. RESULTS: Thirty-one eyes of 31 patients were treated with 0.5 mg of intravitreal ranibizumab for RAP between March 2006 and December 2007. The mean age of the patients was 82.6 years (SD:4.9). The mean number of intravitreal injections administered for each patient was 5 (SD: 2.4, range 3 to 12). The mean follow up was 13.4 months (SD: 3, range 10 to 22). The baseline mean logMAR BCVA was 0.72 (SD: 0.45) (decimal equivalent of 0.2). The mean logMAR BCVA was improved significantly (P &amp;lt; 0.0001) at the last follow-up to 0.45, SD: 0.3 (decimal equivalent 0.35). The visual acuity (VA) improved by a mean of 2.7 lines (SD 2.5). Mean baseline central macular thickness (CMT) was 376 microm, and decreased significantly to a mean of 224 microm (P &amp;lt; 0.001) at the last follow-up. Mean reduction of CMT was 152 microm (SD: 58). An average of 81.5% of the total visual improvement and 85% of the total CMT reduction occurred during the first post-operative month after one intravitreal injection of ranibizumab. During follow-up, an RPE tear occurred in one eye (3.2%) of the study group. No injection complications or systemic drug-related side-effects were noted during the follow-up period. CONCLUSIONS: Intravitreal ranibizumab injections appeared to be an effective and safe treatment for RAP, resulting in visual gain and reduction in macular thickness. Further long-term studies to evaluate the efficacy of intravitreal ranibizumab in RAP are warranted

Decentralized Optimization of Vehicle Route Planning - A Cross-City Comparative Study

The introduction of connected and autonomous vehicles enables new possibilities in vehicle routing: Knowing the origin and destination of each vehicle in the network can allow for coordinated real-time routing of the vehicles to optimize network performance. However, this relies on individual vehicles being altruistic i.e., willing to accept alternative less-preferred routes. We conduct a study to compare different levels of agent altruism in decentralized vehicles coordination and the effect on the network-level traffic performance. This work introduces novel load-balancing scenarios of traffic flow in real-world cities for varied levels of agent altruism. We show evidence that the new decentralized optimization router is more effective with networks of high load

Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning

Engineering collective adaptive systems (CAS) with learning capabilities is a challenging task due to their multidimensional and complex design space. Data-driven approaches for CAS design could introduce new insights enabling system engineers to manage the CAS complexity more cost-effectively at the design-phase. This paper introduces a systematic approach to reason about design choices and patterns of learning-based CAS. Using data from a systematic literature review, reasoning is performed with a novel application of data-driven methodologies such as clustering, multiple correspondence analysis and decision trees. The reasoning based on past experience as well as supporting novel and innovative design choices are demonstrated