Recent Trends in Sensor-based Activity Recognition

This seminar introduces recent trends in sensor-based activity recognition technology. Technology to recognize human activities using sensors has been a hot topic in the field of mobile and ubiquitous computing for many years. Recent developments in deep learning and sensor technology have expanded the application of activity recognition to various domains such as industrial and natural science fields. However, because activity recognition in the new domains suffers from various real problems such as the lack of sufficient training data and complexity of target activities, new solutions have been proposed for the practical problems in applying activity recognition to real-world applications in the new domains. In this seminar, we introduce recent topics in activity recognition from the viewpoints of (1) recent trends in state-of-the-art machine learning methods for practical activity recognition, (2) recently focused domains for human activity recognition such as industrial and medical domains and their public datasets, and (3) applications of activity recognition to the natural science field, especially in animal behavior understanding.Maekawa T., Xia Q., Otsuka R., et al. Recent Trends in Sensor-based Activity Recognition. Proceedings - IEEE International Conference on Mobile Data Management 2023-July, 36 (2023); https://doi.org/10.1109/MDM58254.2023.00018

Notch1 and Notch3 Instructively Restrict bFGF-Responsive Multipotent Neural Progenitor Cells to an Astroglial Fate

AbstractNotch1 has been shown to induce glia in the peripheral nervous system. However, it has not been known whether Notch can direct commitment to glia from multipotent progenitors of the central nervous system. Here we present evidence that activated Notch1 and Notch3 promotes the differentiation of astroglia from the rat adult hippocampus-derived multipotent progenitors (AHPs). Quantitative clonal analysis indicates that the action of Notch is likely to be instructive. Transient activation of Notch can direct commitment of AHPs irreversibly to astroglia. Astroglial induction by Notch signaling was shown to be independent of STAT3, which is a key regulatory transcriptional factor when ciliary neurotrophic factor (CNTF) induces astroglia. These data suggest that Notch provides a CNTF-independent instructive signal of astroglia differentiation in CNS multipotent progenitor cells

Successful Treatment of Caesarean Scar Pregnancies by Local Treatment Only

Background. Caesarean scar pregnancy (CSP) is a rare ectopic pregnancy associated with life-threatening complications. To date, no therapeutic protocols have been established. Sono-guided local methotrexate (MTX) injection is a relatively easy and low-invasive treatment. Additional systemic MTX is sometimes needed for CSP cases, especially when β-subunit human chorionic gonadotropin (β-hCG) levels are >20,000 mIU/ml at diagnosis. We report on six cases of CSP treated with local MTX injection, five of which received combined local treatment. Methods. Under intravenous anesthesia, six CSPs including a case with β-hCG levels >20,000 mIU/ml received MTX injection to the gestational sac. Five cases received gestational sac aspiration. Three cases had additional local potassium chloride injection and one case had a saline injection aiming at the fetal heart beat concurrent with MTX injection. MTX was administered weekly if β-hCG levels stayed beyond the expected values. Outcomes. All cases achieved β-hCG normalization without additional systemic MTX, with one case having a successful pregnancy after treatment. Conclusion. Sono-guided local MTX injection with concurrent local treatment might be a potentially effective approach for CSP cases. The accumulation of further cases is necessary to confirm this

Recent Trends in Sensor-based Activity Recognition

Maekawa T., Xia Q., Otsuka R., et al. Recent Trends in Sensor-based Activity Recognition. Proceedings - IEEE International Conference on Mobile Data Management 2023-July, 36 (2023); https://doi.org/10.1109/MDM58254.2023.00018.This seminar introduces recent trends in sensor-based activity recognition technology. Technology to recognize human activities using sensors has been a hot topic in the field of mobile and ubiquitous computing for many years. Recent developments in deep learning and sensor technology have expanded the application of activity recognition to various domains such as industrial and natural science fields. However, because activity recognition in the new domains suffers from various real problems such as the lack of sufficient training data and complexity of target activities, new solutions have been proposed for the practical problems in applying activity recognition to real-world applications in the new domains. In this seminar, we introduce recent topics in activity recognition from the viewpoints of (1) recent trends in state-of-the-art machine learning methods for practical activity recognition, (2) recently focused domains for human activity recognition such as industrial and medical domains and their public datasets, and (3) applications of activity recognition to the natural science field, especially in animal behavior understanding

Empagliflozin in Patients with Chronic Kidney Disease

Background The effects of empagliflozin in patients with chronic kidney disease who are at risk for disease progression are not well understood. The EMPA-KIDNEY trial was designed to assess the effects of treatment with empagliflozin in a broad range of such patients. Methods We enrolled patients with chronic kidney disease who had an estimated glomerular filtration rate (eGFR) of at least 20 but less than 45 ml per minute per 1.73 m(2) of body-surface area, or who had an eGFR of at least 45 but less than 90 ml per minute per 1.73 m(2) with a urinary albumin-to-creatinine ratio (with albumin measured in milligrams and creatinine measured in grams) of at least 200. Patients were randomly assigned to receive empagliflozin (10 mg once daily) or matching placebo. The primary outcome was a composite of progression of kidney disease (defined as end-stage kidney disease, a sustained decrease in eGFR to < 10 ml per minute per 1.73 m(2), a sustained decrease in eGFR of & GE;40% from baseline, or death from renal causes) or death from cardiovascular causes. Results A total of 6609 patients underwent randomization. During a median of 2.0 years of follow-up, progression of kidney disease or death from cardiovascular causes occurred in 432 of 3304 patients (13.1%) in the empagliflozin group and in 558 of 3305 patients (16.9%) in the placebo group (hazard ratio, 0.72; 95% confidence interval [CI], 0.64 to 0.82; P < 0.001). Results were consistent among patients with or without diabetes and across subgroups defined according to eGFR ranges. The rate of hospitalization from any cause was lower in the empagliflozin group than in the placebo group (hazard ratio, 0.86; 95% CI, 0.78 to 0.95; P=0.003), but there were no significant between-group differences with respect to the composite outcome of hospitalization for heart failure or death from cardiovascular causes (which occurred in 4.0% in the empagliflozin group and 4.6% in the placebo group) or death from any cause (in 4.5% and 5.1%, respectively). The rates of serious adverse events were similar in the two groups. Conclusions Among a wide range of patients with chronic kidney disease who were at risk for disease progression, empagliflozin therapy led to a lower risk of progression of kidney disease or death from cardiovascular causes than placebo