Vertical versus horizontal: theory and practice of urban densification in evolving metropolises

The urban growth, its continuous use of land and the associated problem of soil sealing force urban expansions to search for a sustainable densification. The paper attempts to explore and compare the urban conditions' growth on the fringes of two cities in Asia and Europe - Shenzhen and Vienna - as two opposite realities defining different strategies to control the urban expansion: while Shenzhen use the verticality to create new space, Vienna works on the horizontality and the regeneration, generating a neighbor’s contiguity in the urban areas. The paper discusses and illustrates the two possibilities for dense built environments -horizontality and verticality in the metropolitan form-, as opposite yet possible strategies to achieve dense built environments qualifying urban spaces, infrastructures, buildings. To this aim Hong Kong, and Vienna are compared, to understand differences and attempt at responding to the central research question: Is it possible to identify an optimal urban form? Buildings’ and neighborhood’s typologies have been observed to aim at this understanding. Even though general conclusions cannot be drawn from specific case studies, is the authors' considered opinion that urban textures in the built environments are very much connected with and their successful evolution depends on the strict relation with humans and their activities (working, living, entertaining and dwelling). In this context, appropriate strategies for urban densification, in their different forms, might represent an effective path to meet the new conflicting challenges of sustainability and rapid urban growth

Animal welfare and Ethics course for post-graduate at Veterinary School: how to improve assessment methodologies with a bottom up approach

[EN] Animal Welfare, with its strong ethical component, is increasingly central to public debate and in all sectors dealing with animals has become a key expertise to acquire. This paper presents a post-graduate level course on animal welfare and ethics assessment delivered by the Veterinary School of Padua University, Italy. The course was delivered at Garda Zoological Park, Italy, allowing students to do an experience with wildlife in a peculiar management system. Teachers used an inquiry-based approach to lead students ‘construct’ their experience in welfare assessment. At the end of the course students, divided into groups, had to develop a protocol for the assessment of the animal welfare of a species in the zoo. The analysis of these final works and a pre-test and post-test questionnaires were used to assess the effectiveness of the course. Results highlighted a growing awareness of the complexity of assessment methodologies and more attention on animal based indicators. Students found difficulties using a bottom-up approach but were satisfied at the end of the course. Improvements can be done to promote reflections on reasons to assess animal welfare and its ethical component, on the utility of such assessment and on a balanced use of tools and methodologies.Ferrante, L.; Normando, S.; Florio, D.; De Mori, B. (2017). Animal welfare and Ethics course for post-graduate at Veterinary School: how to improve assessment methodologies with a bottom up approach. En Proceedings of the 3rd International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 1147-1155. https://doi.org/10.4995/HEAD17.2017.55351147115

Cycling Induced by Electrical Stimulation Improves Motor Recovery in Postacute Hemiparetic Patients

Background and Purpose—This study assessed whether cycling induced by functional electrical stimulation (FES) was more effective than passive cycling with placebo stimulation in promoting motor recovery and walking ability in postacute hemiparetic patients.Methods—In a double-blind, randomized, controlled trial, 35 patients were included and randomized to receive FES-induced cycling training or placebo FES cycling. The 4-week treatment consisted of 20 sessions lasting 25 minutes each. Primary outcome measures included the leg subscale of the Motricity Index and gait speed during a 50-meter walking test. Secondary outcomes were the Trunk Control Test, the Upright Motor Control Test, the mean work produced by the paretic leg, and the unbalance in mechanical work between paretic and nonparetic legs during voluntary pedaling. Participants were evaluated before training, after training, and at 3- to 5-month follow-up visits.Results—No significant differences were found between groups at baseline. Repeated-measures ANOVA (P<0.05) revealed significant increases in Motricity Index, Trunk Control Test, Upright Motor Control Test, gait speed, and mean work of the paretic leg after training and at follow-up assessments for FES-treated patients. No outcome measures demonstrated significant improvements after training in the placebo group. Both groups showed no significant differences between assessments after training and at follow-up. A main effect favoring FES-treated patients was demonstrated by repeated-measures ANCOVA for Motricity Index (P<0.001), Trunk Control Test (P=0.001), Upright Motor Control Test (P=0.005), and pedaling unbalance (P=0.038).Conclusions—The study demonstrated that 20 sessions of FES cycling training significantly improved lower extremity motor functions and accelerated the recovery of overground locomotion in postacute hemiparetic patients. Improvements were maintained at follow-up

“You Need to Set a Daily Schedule”: Understanding Successful Aging via Three-Sided Viewpoints

This study aimed to identify the constructs related to successful aging in the context of engagement in social and productive activities. A qualitative design was used to explore three viewpoints on the aging period with 9 focus groups (3 each for adults 65 years or older, older adults' family members, and health professionals) and 18 interviews with older adults (older adults Mage = 71.7 years, Standard Deviation = 4.62). The transcripts were analyzed using constructivist grounded theory principles. Three categories were identified for successful aging: (a) engagement with life, including social participation, fixed/flexible schedule, time, and meaningful occupation; (b) self-management abilities, including producing daily schedules, independence, and initiation/striving toward goals; and (c) diversity among older adults, including their views on retirement, being active or not, and their dreams/values/goals. Considering the diverse nature of older adults, recognizing the importance of life engagement and self-management abilities emphasizes the necessity for an occupation-based, self-tailored approach to enable successful aging

Investigating Visual Perception Impairments through Serious Games and Eye Tracking to Anticipate Handwriting Difficulties

Dysgraphia is a learning disability that causes handwritten production below expectations. Its diagnosis is delayed until the completion of handwriting development. To allow a preventive training program, abilities not directly related to handwriting should be evaluated, and one of them is visual perception. To investigate the role of visual perception in handwriting skills, we gamified standard clinical visual perception tests to be played while wearing an eye tracker at three difficulty levels. Then, we identified children at risk of dysgraphia through the means of a handwriting speed test. Five machine learning models were constructed to predict if the child was at risk, using the CatBoost algorithm with Nested Cross-Validation, with combinations of game performance, eye-tracking, and drawing data as predictors. A total of 53 children participated in the study. The machine learning models obtained good results, particularly with game performances as predictors (F1 score: 0.77 train, 0.71 test). SHAP explainer was used to identify the most impactful features. The game reached an excellent usability score (89.4 +/- 9.6). These results are promising to suggest a new tool for dysgraphia early screening based on visual perception skills

A biofeedback cycling training to improve locomotion: a case series study based on gait pattern classification of 153 chronic stroke patients

<p>Abstract</p> <p>Background</p> <p>The restoration of walking ability is the main goal of post-stroke lower limb rehabilitation and different studies suggest that pedaling may have a positive effect on locomotion. The aim of this study was to explore the feasibility of a biofeedback pedaling treatment and its effects on cycling and walking ability in chronic stroke patients. A case series study was designed and participants were recruited based on a gait pattern classification of a population of 153 chronic stroke patients.</p> <p>Methods</p> <p>In order to optimize participants selection, a k-means cluster analysis was performed to subgroup homogenous gait patterns in terms of gait speed and symmetry.</p> <p>The training consisted of a 2-week treatment of 6 sessions. A visual biofeedback helped the subjects in maintaining a symmetrical contribution of the two legs during pedaling. Participants were assessed before, after training and at follow-up visits (one week after treatment). Outcome measures were the unbalance during a pedaling test, and the temporal, spatial, and symmetry parameters during gait analysis.</p> <p>Results and discussion</p> <p>Three clusters, mainly differing in terms of gait speed, were identified and participants, representative of each cluster, were selected.</p> <p>An intra-subject statistical analysis (ANOVA) showed that all patients significantly decreased the pedaling unbalance after treatment and maintained significant improvements with respect to baseline at follow-up. The 2-week treatment induced some modifications in the gait pattern of two patients: one, the most impaired, significantly improved mean velocity and increased gait symmetry; the other one reduced significantly the over-compensation of the healthy limb. No benefits were produced in the gait of the last subject who maintained her slow but almost symmetrical pattern. Thus, this study might suggest that the treatment can be beneficial for patients having a very asymmetrical and inefficient gait and for those that overuse the healthy leg.</p> <p>Conclusion</p> <p>The results demonstrated that the treatment is feasible and it might be effective in translating progresses from pedaling to locomotion. If these results are confirmed on a larger and controlled scale, the intervention, thanks to its safety and low price, could have a significant impact as a home- rehabilitation treatment for chronic stroke patients.</p

Evidence for the Role of Intracellular Water Lifetime as a Tumour Biomarker Obtained by In Vivo Field-Cycling Relaxometry

This project has received funding from the European UnionQs Horizon 2020 research and innovation programme under grant agreement No 668119 (project “IDentIFY”), and it was performed in the framework of the Consorzio CIRCMSB and of COST Action AC15209 (EURELAX)Peer reviewedPublisher PD

Medium-term patient's satisfaction after primary total knee arthroplasty: enhancing prediction for improved care

Background: Patient-reported satisfaction after total knee arthroplasty (TKA) is low compared to other orthopedic procedures. Although several factors have been reported to influence TKA outcomes, it is still challenging to identify patients who will experience dissatisfaction five years after surgery, thereby improving their management. Indeed, both perioperative information and follow-up questionnaires seem to lack statistical predictive power. Hypothesis: This study aims to demonstrate that machine learning can improve the prediction of patient satisfaction, especially when classical statistics fail to identify complex patterns that lead to dissatisfaction. Patients and methods: Patients who underwent primary TKA were included in a Registry that collected baseline data and clinical outcomes at different follow-ups. The patients were divided into satisfied and dissatisfied groups based on a satisfaction questionnaire administered five years after surgery. Satisfaction was predicted using linear statistical models compared to machine learning algorithms. Results: A total of 147 subjects were analyzed. Regarding statistics, significant differences between satisfaction levels started emerging only six months after the intervention, and the classification was close to random guessing. However, machine learning algorithms could improve the prediction by 72% soon after the intervention, and an improvement of 178% was possible when including follow-ups up to one year. Discussion: This study demonstrates the feasibility of a registry-based approach for monitoring and predicting satisfaction using ML algorithms. Level of evidence: III