Smart grids are able to forecast customers' consumption patterns, i.e., their energy demand, and consequently electricity can be transmitted after taking into account the expected demand. To face ...today's demand forecasting challenges, where the data generated by smart grids is huge, modern data-driven techniques need to be used. In this scenario, Deep Learning models are a good alternative to learn patterns from customer data and then forecast demand for different forecasting horizons. Among the commonly used Artificial Neural Networks, Long Short-Term Memory networks-based on Recurrent Neural Networks-are playing a prominent role. This paper provides an insight into the importance of the demand forecasting issue, and other related factors, in the context of smart grids, and collects some experiences of the use of Deep Learning techniques, for demand forecasting purposes. To have an efficient power system, a balance between supply and demand is necessary. Therefore, industry stakeholders and researchers should make a special effort in load forecasting, especially in the short term, which is critical for demand response.
Sunflower seeds, one of the main oilseeds produced around the world, are widely used in the food industry. Mixtures of seed varieties can occur throughout the supply chain. Intermediaries and the ...food industry need to identify the varieties to produce high-quality products. Considering that high oleic oilseed varieties are similar, a computer-based system to classify varieties could be useful to the food industry. The objective of our study is to examine the capacity of deep learning (DL) algorithms to classify sunflower seeds. An image acquisition system, with controlled lighting and a Nikon camera in a fixed position, was constructed to take photos of 6000 seeds of six sunflower seed varieties. Images were used to create datasets for training, validation, and testing of the system. A CNN AlexNet model was implemented to perform variety classification, specifically classifying from two to six varieties. The classification model reached an accuracy value of 100% for two classes and 89.5% for the six classes. These values can be considered acceptable, because the varieties classified are very similar, and they can hardly be classified with the naked eye. This result proves that DL algorithms can be useful for classifying high oleic sunflower seeds.
Identification and monitoring of existing surface water bodies on the Earth are important in many scientific disciplines and for different industrial uses. This can be performed with the help of ...high-resolution satellite images that are processed afterwards using data-driven techniques to obtain the desired information. The objective of this study is to establish and validate a method to distinguish efficiently between water and land zones, i.e., an efficient method for surface water detection. In the context of this work, the method used for processing the high-resolution satellite images to detect surface water is based on image segmentation, using the Quadtree algorithm, and fractal dimension. The method was validated using high-resolution satellite images freely available at the OpenAerialMap website. The results show that, when the fractal dimensions of the tiles in which the image is divided after completing the segmentation phase are calculated, there is a clear threshold where water and land can be distinguished. The proposed scheme is particularly simple and computationally efficient compared with heavy artificial-intelligence-based methods, avoiding having any special requirements regarding the source images. Moreover, the average accuracy obtained in the case study developed for surface water detection was 96.03%, which suggests that the adopted method based on fractal dimension is able to detect surface water with a high level of accuracy.
Technology enables a more sustainable and universally accessible educational model. However, technology has brought a paradox into students’ lives: it helps them engage in learning activities, but it ...is also a source of distraction. During the academic year 2021–2022, the authors conducted a study focusing on classroom distractions. One of the objectives was to identify the main digital distractions from the point of view of students. The study was carried out at an engineering school, where technology is fully integrated in the classroom and in the academic routines of teachers and students. Discussions and surveys, complemented by a statistical study based on bivariate correlations, were used with participating students (n = 105). Students considered digital distractions to have a significant impact on their performance in lab sessions. This performance was mainly self-assessed as improvable. Contrary to other contemporary research, the results were not influenced by the year of study of the subject, as the issue is important regardless of the students’ backgrounds. Professors should implement strategies to raise students’ awareness of the significant negative effects of digital distractions on their performance, as well as to develop students’ self-control skills. This is of vital importance for the use of technology to be sustainable in the long-term.
Mixed reality opens interesting possibilities as it allows physicians to interact with both, the real physical and the virtual computer-generated environment and objects, in a powerful way. A mixed ...reality system, based in the HoloLens 2 glasses, has been developed to assist cardiologists in a quite complex interventional procedure: the ultrasound-guided femoral arterial cannulations, during real-time practice in interventional cardiology. The system is divided into two modules, the transmitter module, responsible for sending medical images to HoloLens 2 glasses, and the receiver module, hosted in the HoloLens 2, which renders those medical images, allowing the practitioner to watch and manage them in a 3D environment. The system has been successfully used, between November 2021 and August 2022, in up to 9 interventions by 2 different practitioners, in a large public hospital in central Spain. The practitioners using the system confirmed it as easy to use, reliable, real-time, reachable, and cost-effective, allowing a reduction of operating times, a better control of typical errors associated to the interventional procedure, and opening the possibility to use the medical imagery produced in ubiquitous e-learning. These strengths and opportunities were only nuanced by the risk of potential medical complications emerging from system malfunction or operator errors when using the system (e.g., unexpected momentary lag). In summary, the proposed system can be taken as a realistic proof of concept of how mixed reality technologies can support practitioners when performing interventional and surgical procedures during real-time daily practice.
Technology enables a more sustainable and universally accessible educational model. However, technology has brought a paradox into students' lives: it helps them engage in learning activities, but it ...is also a source of distraction. During the academic year 2021-2022, the authors conducted a study focusing on classroom distractions. One of the objectives was to identify the main digital distractions from the point of view of students. The study was carried out at an engineering school, where technology is fully integrated in the classroom and in the academic routines of teachers and students. Discussions and surveys, complemented by a statistical study based on bivariate correlations, were used with participating students (n = 105). Students considered digital distractions to have a significant impact on their performance in lab sessions. This performance was mainly self-assessed as improvable. Contrary to other contemporary research, the results were not influenced by the year of study of the subject, as the issue is important regardless of the students' backgrounds. Professors should implement strategies to raise students' awareness of the significant negative effects of digital distractions on their performance, as well as to develop students' self-control skills. This is of vital importance for the use of technology to be sustainable in the long-term.
Background
The COVID‐19 outbreak has resulted in collision between patients infected with SARS‐CoV‐2 and those with cancer on different fronts. Patients with cancer have been impacted by deferral, ...modification, and even cessation of therapy. Adaptive measures to minimize hospital exposure, following the precautionary principle, have been proposed for cancer care during COVID‐19 era. We present here a consensus on prioritizing recommendations across the continuum of sarcoma patient care.
Material and Methods
A total of 125 recommendations were proposed in soft‐tissue, bone, and visceral sarcoma care. Recommendations were assigned as higher or lower priority if they cannot or can be postponed at least 2–3 months, respectively. The consensus level for each recommendation was classified as “strongly recommended” (SR) if more than 90% of experts agreed, “recommended” (R) if 75%–90% of experts agreed and “no consensus” (NC) if fewer than 75% agreed. Sarcoma experts from 11 countries within the Sarcoma European‐Latin American Network (SELNET) consortium participated, including countries in the Americas and Europe. The European Society for Medical Oncology‐Magnitude of clinical benefit scale was applied to systemic‐treatment recommendations to support prioritization.
Results
There were 80 SRs, 35 Rs, and 10 NCs among the 125 recommendations issued and completed by 31 multidisciplinary sarcoma experts. The consensus was higher among the 75 higher‐priority recommendations (85%, 12%, and 3% for SR, R, and NC, respectively) than in the 50 lower‐priority recommendations (32%, 52%, and 16% for SR, R, and NC, respectively).
Conclusion
The consensus on 115 of 125 recommendations indicates a high‐level of convergence among experts. The SELNET consensus provides a tool for sarcoma multidisciplinary treatment committees during the COVID‐19 outbreak.
Implications for Practice
The Sarcoma European‐Latin American Network (SELNET) consensus on sarcoma prioritization care during the COVID‐19 era issued 125 pragmatical recommendations distributed as higher or lower priority to protect critical decisions on sarcoma care during the COVID‐19 pandemic. A multidisciplinary team from 11 countries reached consensus on 115 recommendations. The consensus was lower among lower‐priority recommendations, which shows reticence to postpone actions even in indolent tumors. The European Society for Medical Oncology‐Magnitude of Clinical Benefit scale was applied as support for prioritizing systemic treatment. Consensus on 115 of 125 recommendations indicates a high level of convergence among experts. The SELNET consensus provides a practice tool for guidance in the decisions of sarcoma multidisciplinary treatment committees during the COVID‐19 outbreak.
The COVID‐19 pandemic has caused deferral, modification, or cessation of treatment for patients with cancer. This article presents a consensus on prioritizing recommendations across the continuum of sarcoma patient care.
INTRODUCTIONHaemofiltration paradigms used to manage critically ill patients with a dysregulated inflammatory response (DIR) assess kidney function to monitor its onset, adaptation, and completion. A ...Continuous Venous Hyperfiltration (CONVEHY) protocol is presented, in which a non-specific adsorption membrane (AN69-ST-Heparin Grafted) is used with citrate as an anticoagulant and substitution fluid. CONVEHY uses tools readily available to achieve kidney related and non-related objectives, and it is guided by the monitoring of pathophysiological responses. OBJECTIVESTo compare the response to an AN69-ST-HG membrane when heparin (He, n=5: Standard protocol) or citrate (Ci, n=6: CONVEHY protocol) was used to evaluate whether a larger study into the benefits of this protocol would be feasible. MATERIALS AND METHODSIn a retrospective pilot study, the benefits of the CONVEHY protocol to manage patients with a DIR in a surgical critical care unit (CCUs) were assessed by evaluating the SOFA (Sequential Organ Failure Assessment) (He 11 ± 2.35; Ci 11 ± 3.63: p=0.54) and APACHE II (He 28.60 ± 9.40; Ci 24 ± 8.46: p=0.93) scores. RESULTSNights in hospital (He 35.2 ± 16.3 nights; Ci 9 ± 2.53: p=0.004), hospital admission after discharge from the CCUs (He 40.25 ± 21.82; Ci 13.2 ± 4.09: p=0.063), patients hospitalised >20 days (He 80%; Ci 0%: p=0.048), days requiring mechanical ventilation (He 16 ± 5.66; Ci 4 ± 1.72: p=0.004), and the predicted (55.39 ± 26.13%) versus real mortality in both groups (9.1%: p=0.004). CONCLUSIONSThe CONVEHY protocol improves the clinical responses of patients with DIR, highlighting the potential value of performing larger and confirmatory studies.
The most important challenges in acute promyelocytic leukemia (APL) is preventing early death and reducing long-term events, such as second neoplasms (s-NPLs). We performed a retrospective analysis ...of 2670 unselected APL patients, treated with PETHEMA “chemotherapy based” and “chemotherapy free” protocols. Only de novo APL patients who achieved complete remission (CR) and completed the three consolidation cycles were enrolled into the analysis. Out of 2670 APL patients, there were 118 (4.4%) who developed s-NPLs with the median latency period (between first CR and diagnosis of s-NPL) of 48.0 months (range 2.8–231.1): 43.3 (range: 2.8–113.9) for s-MDS/AML and 61.7 (range: 7.1–231.1) for solid tumour. The 5-year CI of all s-NPLs was of 4.43% and 10 years of 7.92%. Among s-NPLs, there were 58 cases of s-MDS/AML, 3 cases of other hematological neoplasms, 57 solid tumours and 1 non-identified neoplasm. The most frequent solid tumour was colorectal, lung and breast cancer. Overall, the 2-year OS from diagnosis of s-NPLs was 40.6%, with a median OS of 11.1 months. Multivariate analysis identified age of 35 years (hazard ratio = 0.2584;
p
< 0.0001) as an independent prognostic factor for s-NPLs. There were no significant differences in CI of s-NPLs at 5 years between chemotherapy-based vs chemotherapy-free regimens (hazard ratio = 1.09;
p
= 0.932). Larger series with longer follow-up are required to confirm the potential impact of ATO+ATRA regimens to reduce the incidence of s-NPLs after front-line therapy for APL.
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