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In the past thirty years many mining projects in Chile and Peru have used: (i) polymeric geomembranes and (ii) design-and-build cutoff trenches, plastic concrete slurry walls, and grout curtain systems to control seepage at tailings storage facilities (TSFs). Geosynthetics are a viable alternative at a TSF dam for clay cores or impermeable materials, mainly because of their marked advantages in cost, installation, and construction time. This article describes the use of geosynthetics liners and cutoff trench–plastic concrete slurry walls–grout curtain systems in TSF dams in Chile and Peru mining, with the objective to decrease seepage to the environment, considering different dam material cases such as: cycloned tailings sand dams, borrow dams, and mine waste rock dams. Finally, this article discusses aspects of geosynthetic technology acceptance in the local regulatory frameworks, lessons learned, and advances. It focuses on the use and implementation of geosynthetics in TSFs in Chile and Peru, which have some of the highest TSF dams in the world, as well as a wet environment, dry environment, extreme topography, and severe seismic conditions. These conditions constitute a challenge for manufacturers, engineers, and contractors, who must achieve optimal technical solutions, while being environmentally aware and economic.

Approximately 40-70% of people with Parkinson's disease (PD) fall each year, causing decreased activity levels and quality of life. Current fall-prevention strategies include the use of pharmacological and non-pharmacological therapies. To increase the accessibility of this vulnerable population, we developed a multidisciplinary telemedicine program using an Information and Communication Technology (ICT) platform. We hypothesized that the risk for falling in PD would decrease among participants receiving a multidisciplinary telemedicine intervention program added to standard office-based neurological care. To determine the feasibility and cost-effectiveness of a multidisciplinary telemedicine intervention to decrease the incidence of falls in patients with PD. Ongoing, longitudinal, randomized, single-blinded, case-control, clinical trial. We will include 76 non-demented patients with idiopathic PD with a high risk of falling and limited access to multidisciplinary care. The intervention group (n = 38) will receive multidisciplinary remote care in addition to standard medical care, and the control group (n = 38) standard medical care only. Nutrition, sarcopenia and frailty status, motor, non-motor symptoms, health-related quality of life, caregiver burden, falls, balance and gait disturbances, direct and non-medical costs will be assessed using validated rating scales. This study will provide a cost-effectiveness assessment of multidisciplinary telemedicine intervention for fall reduction in PD, in addition to standard neurological medical care. In this challenging initiative, we will determine whether a multidisciplinary telemedicine intervention program can reduce falls, as an alternative intervention option for PD patients with restricted access to multidisciplinary care. ClinicalTrials.gov Identifier: NCT04694443.

PurposeTo assess the validity, reliability, and responsiveness of the Spanish version of the Expanded Prostate cancer Index Composite (EPIC) with 26 items.MethodsMulticentric longitudinal study of patients diagnosed with localized or locally advanced prostate cancer (any T, any N, M0) treated with active surveillance, surgery, external radiotherapy, or brachytherapy. The EPIC-50 was administered initially to the cohort (n = 324 patients), until it was replaced in November 2019 by the EPIC-26 (n = 543), in both groups before treatment and 12 months after. We assessed confirmatory factor analysis (CFA), reliability with Cronbach’s alpha coefficient, criterion validity with the intraclass correlation coefficient (ICC), and responsiveness by testing a priori hypotheses on deterioration effect size (ES).ResultsThe CFA confirmed the five-domain structure of the EPIC-26 proposed by the original instrument (comparative fit index = 0.95). The agreement between EPIC-50 (gold standard) and EPIC-26 domains was excellent (ICC > 0.90). Cronbach’s alpha was > 0.7 in almost all domains, and the floor effect was near zero, although ceiling effect was higher than 50% in urinary incontinence and bowel domains. Hypothesized changes between before and 12 months after treatment were confirmed: ES > 0.8 in both urinary incontinence and sexual domains among patients who underwent surgery; and ES ranging 0.44–0.48 for bowel and sexual domains in patients treated with external radiotherapy.ConclusionThe Spanish version of the EPIC-26 has demonstrated adequate metric properties, similar to those of the original version, with acceptable goodness-of-fit indices, good criterion validity, reliability, and responsiveness to detect changes after radical prostatectomy or external radiotherapy.

Background and purpose Adopting telemedicine (TM) enables improved access to specialized care and reduces barriers. The aim was to assess the cost‐utility of a coadjutant multidisciplinary TM programme for fall prevention compared to standard in‐office visits for individuals with Parkinson's disease (PD). Methods This was an 8‐month single‐blind randomized controlled trial. TM and control groups received in‐office visits and standard management care at baseline, 4 and 8 months. In addition, the TM group received remote multidisciplinary visits for 4 months. Gait, motor and non‐motor symptoms, daily living activities, balance and frailty were measured using PD‐recommended rating scales and wearable sensors. Clinical characteristics were compared at each visit using baseline scores, gender and age as covariates. The incremental cost‐effectiveness ratio (ICER) and quality‐adjusted life years (QALYs) were calculated at each visit. Results Fifty patients were included: 25 patients in the TM group (48% males, mean age 71.1 ± 9.0 years) and 25 patients in the control group (52% males, mean age 69.2 ± 9.4 years). Compared to controls, in the TM group similar QALYs were found but, in contrast, significant improvements in daily living activities, depression, apathy, freezing of gait, balance, quality of life and frailty (all p values <0.05). The use of coadjutant TM intervention in addition to in‐office visits was efficient for depression, apathy, freezing of gait, balance and frailty with ICERs, ranging from 91.55 € for non‐motor symptoms to 1677.4 € for frailty. Conclusions Telemedicine could be considered an efficient coadjutant intervention for PD, especially for non‐motor symptoms, enhancing health outcomes and accessibility.

Phytoliths can be an important source of information related to environmental and climatic change, as well as to ancient plant use by humans, particularly within the disciplines of paleoecology and archaeology. Currently, phytolith identification and categorization is performed manually by researchers, a time-consuming task liable to misclassifications. The automated classification of phytoliths would allow the standardization of identification processes, avoiding possible biases related to the classification capability of researchers. This paper presents a comparative analysis of six classification methods, using digitized microscopic images to examine the efficacy of different quantitative approaches for characterizing phytoliths. A comprehensive experiment performed on images of 429 phytoliths demonstrated that the automatic phytolith classification is a promising area of research that will help researchers to invest time more efficiently and improve their recognition accuracy rate.

The consolidation of telerehabilitation for the treatment of many diseases over the last decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises and proper corporal movements online should also be mentioned. The focus of this paper is on a telerehabilitation system for patients suffering from Parkinson’s disease in remote villages and other less accessible locations. A full-stack is presented using big data frameworks that facilitate communication between the patient and the occupational therapist, the recording of each session, and real-time skeleton identification using artificial intelligence techniques. Big data technologies are used to process the numerous videos that are generated during the course of treating simultaneous patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for automated evaluation of corporal exercises, which is of immense help to the therapists in charge of the treatment programs.

A natural way of handling imbalanced data is to attempt to equalise the class frequencies and train the classifier of choice on balanced data. For two-class imbalanced problems, the classification success is typically measured by the geometric mean (GM) of the true positive and true negative rates. Here we prove that GM can be improved upon by instance selection, and give the theoretical conditions for such an improvement. We demonstrate that GM is non-monotonic with respect to the number of retained instances, which discourages systematic instance selection. We also show that balancing the distribution frequencies is inferior to a direct maximisation of GM. To verify our theoretical findings, we carried out an experimental study of 12 instance selection methods for imbalanced data, using 66 standard benchmark data sets. The results reveal possible room for new instance selection methods for imbalanced data.