Light Prescriptions Innovators (Spain)

Accurate knowledge of Low-Voltage (LV) distribution topology is critical for reliable operation, advanced monitoring and large-scale integration of distributed energy resources (DERs). In practice, topology records in GIS/NIS are frequently incomplete or outdated, while field verification remains costly. This paper presents a smart-meter (SM)–driven methodology for LV topology mapping that combines a data-trained surrogate model with physics-inspired sensitivity analysis. A feedforward Deep Neural Network (DNN), trained on historical SM measurements spanning diverse operating conditions (including DER-driven net generation), is used as a model-free digital twin to emulate customer-to-voltage relationships. Virtual Network Discovery Events (NDEs) are then generated by applying controlled perturbations within the surrogate to obtain voltage-response signatures that support topology inference without physical intervention. Phase groups are identified through dimensionality reduction and hierarchical clustering, and customer connectivity is inferred from the similarity structure of the resulting voltage-response signatures. The method is applied independently per feeder, enabling scalable execution across multi-feeder LV networks. Validation on six real feeders from an urban Spanish network demonstrates accurate voltage emulation and high-fidelity phase and topology reconstruction using only existing SM infrastructure. • Network Discovery Events enable adaptive low-voltage topology mapping. • Hybrid AI–physics approach enhances low-voltage Digital Twins. • Validated on real Spanish distribution network with high precision.

Breast cancer (BC) is the most prevalent malignancy in women worldwide. Despite most cases being diagnosed in the early stages, patients typically require a multimodal treatment approach. This typically involves a combination of surgery, radiotherapy, systemic treatments (including chemotherapy or immunotherapy), targeted therapy, and endocrine therapy, depending on the disease subtype and the risk of recurrence. Moreover, patients with BC and germline mutations in the breast cancer genes 1 or 2 (BRCA1/BRCA2), (gBRCAm), who are typically young women, often require more aggressive therapeutic interventions. These mutations present unique characteristics that necessitate a distinct treatment approach, potentially influencing the side effect profiles of patients with BC. Regardless of the clear benefit observed with these treatments in terms of reduced recurrence and mortality rates, long-term, treatment-related adverse events occur that negatively affect the health-related quality of life (HRQoL) of BC survivors. Thus, long-term adverse events need to be factored into the treatment decision algorithm of patients with early BC (eBC). Physical, functional, emotional, and psychosocial adverse events can occur and represent a significant concern and a challenge for clinicians, patients, and their families. This review article provides an overview of the various long-term adverse events that patients with eBC may experience, including their associated risk factors, as well as management and prevention strategies. We also explore the evidence of the long-term impact of treatment on the HRQoL of patients with gBRCAm. By providing a comprehensive overview of current evidence and recommendations regarding patients' HRQoL, we aim to equip clinicians with scientific and clinical knowledge and provide guidance to optimize care and improve long-term outcomes.

Acquired hemophilia A is a rare autoimmune disease characterized by inhibitory antibodies against coagulation factor VIII, leading to an increased risk of bleeding. The relevance of this case lies in its high associated morbidity and mortality, and the importance of early diagnosis in both medical and dental practice. We present the clinical case of a 74-year-old Spanish Caucasian patient diagnosed with acquired hemophilia A. The patient was initially treated for progressive edema in the right lower limb, followed by hematomas in the tongue and submandibular region. The diagnosis was confirmed through hematological tests, which revealed a prolonged activated partial thromboplastin time and low coagulation factor VIII activity (2.4%). Treatment with hemostatic agents and corticosteroids was initiated, resulting in a favorable improvement of the hematomas. Acquired hemophilia A requires a multidisciplinary and personalized approach for each patient. Focus should be placed on prevention, early diagnosis, and appropriate treatment to effectively manage this coagulopathy and improve patient outcomes.

Alzheimer's disease (AD) is characterized by impaired inhibitory circuitry and GABAergic dysfunction, which is associated with reduced fast brain oscillations in the gamma band (γ, 30-90Hz) in several animal models. Investigating such activity in human patients could lead to the identification of novel biomarkers of diagnostic and prognostic value. The current study aimed to test a multimodal "Perturbation-based" transcranial Alternating Current Stimulation-Electroencephalography (tACS)-EEG protocol to detect how responses to tACS in AD patients correlate with patients' clinical phenotype. Fourteen participants with mild to moderate dementia due to AD underwent a baseline assessment including cognitive status, peripheral neuroinflammation, and resting-state (rs)EEG. The tACS-EEG recordings included brief (6') tACS blocks of gamma (i.e., 40Hz) stimulation administered through 4 different montages, with Pre/Post 32-Channels EEG for each block. Changes in tACS-EEG and rsEEG γ band power with respect to baseline were adopted as a metric of induction and compared with cognitive scores and neuroinflammatory biomarkers. We found positive correlations between 40Hz-induced γ activity in fronto-central-parietal areas and patient cognitive status and negative ones with neuroinflammatory markers. Participants with greater cognitive impairment exhibited less γ induction and higher peripheral neuroinflammation. The same analysis performed with spectral power from baseline rsEEG resulted in no significant correlations, promoting the value of tACS-based perturbation for capturing individual differences in pathology-related brain features. Our work suggests a link between tACS-induced γ band spectral power and clinical severity, with weaker γ induction corresponding to more severe clinical/cognitive impairment. This study provides preliminary support for the development of novel physiological biomarkers and therapeutic targets based on disease severity.

The presence of plastics in the automotive industry is increasingly significant due to their lightweight nature, which contributes to reducing fuel consumption and CO2 emissions while improving versatility and mechanical properties. Polypropylene (PP) and other polyolefins are among the most commonly used materials, especially for components such as bumpers. The use of composite materials, i.e., a combination of different polymers, improves the properties through synergistic effects, thereby also improving the performance of the final product. In the automotive industry, PP reinforced with 20% talc or CaCO3 is commonly used. The mechanical recycling of polypropylene bumpers is the most common type of recycling. However, challenges arise during this process, such as the presence of impurities like paint, chemical contaminants from previous use, and polymeric impurities from different polymers mixed into the polymer matrix, among others. Paint affects both the aesthetic quality and the mechanical and intrinsic properties of the recycled material. This review aims to analyze the main methods reported in the literature, focusing on those with low environmental impact. Furthermore, these methods are classified according to their capacity, effectiveness, substrate damage, environmental hazards, and economic feasibility. It also aims to offer a comprehensive overview of the mechanical recycling of plastic waste in the automotive industry.