Human Robot Interaction and Usability Studies for a Smart Wheelchair

We build on previous work [12], [14] on the development of a computer controlled wheelchair equipped with a suite of sensors and a novel interface for human-robot interaction. In this paper, we present experimental results and usability studies for the wheelchair. The architecture for human-robot interaction is hierarchical, with the lowest level corresponding to trajectory control, the intermediate level being behavioral and the highest level involving the composition of behaviors and navigation. Our experimental results illustrate the benefits of a shared-control paradigm where the human operator selects the appropriate hehavior(s) or goals while the software is responsible for executing behaviors and generating safe trajectories. Experiments with human users highlight advantages of augmentation in wheelchairs

Revolutionizing physics: a comprehensive survey of machine learning applications

In the context of the 21st century and the fourth industrial revolution, the substantial proliferation of data has established it as a valuable resource, fostering enhanced computational capabilities across scientific disciplines, including physics. The integration of Machine Learning stands as a prominent solution to unravel the intricacies inherent to scientific data. While diverse machine learning algorithms find utility in various branches of physics, there exists a need for a systematic framework for the application of Machine Learning to the field. This review offers a comprehensive exploration of the fundamental principles and algorithms of Machine Learning, with a focus on their implementation within distinct domains of physics. The review delves into the contemporary trends of Machine Learning application in condensed matter physics, biophysics, astrophysics, material science, and addresses emerging challenges. The potential for Machine Learning to revolutionize the comprehension of intricate physical phenomena is underscored. Nevertheless, persisting challenges in the form of more efficient and precise algorithm development are acknowledged within this review

Evidence-based Review on the Use of Proton Therapy in Lymphoma From the Particle Therapy Cooperative Group (PTCOG) Lymphoma Subcommittee.

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Institutional entrepreneurship, governance, and poverty: Insights from emergency medical response servicesin India

We present an in-depth case study of GVK Emergency Management and Research Institute, an Indian public–private partnership (PPP), which successfully brought emergency medical response to remote and urban settings. Drawing insights from the case, we investigate how the organization established itself through institutional entrepreneurship using a process conceptualized as opportunity framing, entrenchment, and propagation. The case and context highlight the need for innovation in organizational design and governance modes to create a new opportunity that connects state actors, private healthcare providers, and the public at large. We consider the role of open innovation and novel business models in creating these service platforms. The implications of our findings for the literature on PPPs, institutional entrepreneurship, inclusive and open innovation, and organizational design in base of the pyramid contexts are discussed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Local Therapy Improves Overall Survival in Patients With Newly Diagnosed Metastatic Prostate Cancer

© 2017 Wiley Periodicals, Inc. BACKGROUND: The role of local therapy, in the form of radiation therapy (RT) or radical prostatectomy(RP), and its association on outcomes is not well established in patients with metastatic prostate cancer. METHODS: Using the National Cancer Database (NCDB), we evaluated patterns of care and outcomes among patients diagnosed with metastatic prostate cancer from 2004 to 2013 treated with local therapy (RP, intensity-modulated radiation therapy [IMRT], or 2D/3D-conformal radiation therapy [CRT]). The association between local therapy, co-variates, and outcomes was assessed in a multivariable Cox proportional hazards model and Propensity score (PS) matching was performed to balance confounding factors. Survival was estimated using the Kaplan–Meier method. RESULTS: Among the 1,208,180 patients in the NCDB with prostate cancer, 6,051 patients met the inclusion criteria. No local therapy was used in 5,224 patients, while 622 (10.3%), 52 (0.9%), 153 (2.5%) patients received RP, IMRT, and 2D/3D-CRT, respectively. Use of local therapy was associated with younger age (≤70), lower co-morbidity score, lower T-stage, Gleason score \u3c8, node-negative status, private, and Medicare insurance, higher income quartile, and treatment at comprehensive or academic/research programs (P \u3c 0.05). Five-year overall survival for patients receiving local therapy was 45.7% versus 17.1% for those not receiving local therapy (P \u3c 0.01). In multivariate analysis, RP (HR = 0.51; 95%CI, 0.45–0.59, P \u3c 0.01) and IMRT (HR = 0.47; 95%CI, 0.31–0.72, P \u3c 0.01) were independently associated with superior overall survival. After PS-matching, the use of local therapy (RP or IMRT) remained significantly associated with overall survival (HR = 0.35; 95%CI, 0.30–0.41, P \u3c 0.01). CONCLUSIONS: The use of RP and IMRT, to treat the primary disease, was associated with improvements in overall survival for patients with metastatic prostate cancer. We have identified patient-specific variations in the use of local therapy that may be tested in subsequent prospective clinical trials to improve patient outcomes in this setting. Prostate 77: 559–572, 2017. © 2017 Wiley Periodicals, Inc

Trends in active surveillance for very low-risk prostate cancer: do guidelines influence modern practice?

© 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. As recommended by current NCCN guidelines, patients with very low-risk prostate cancer may be treated with active surveillance (AS), but this may be underutilized. Using the National Cancer Database (NCDB), we identified men (2010–2013) with biopsy-proven, very low-risk prostate cancer that met AS criteria as suggested by Epstein (stage ≤ T1c; Gleason score (GS) ≤ 6; PSA \u3c 10; and ≤2 [or \u3c33%] positive biopsy cores) and aged ≤76, and low comorbidity index (Charlson-Deyo score = 0). For those patients meeting this criteria, we performed generalized estimation equation (GEE) method with incorporation of correlation in patients clustered within facility to determine the likelihood of undergoing AS. Among the 448 773 patients in the NCDB with low-risk prostate cancer, 40 839 patients met the inclusion criteria. AS was utilized in 5798 patients (14.2%), while within the very low-risk patients receiving treatment, up to 52.2% received radical prostatectomy. In univariate analyses, AS utilization was associated with older age, uninsured status (compared to private insurance), farther distance from facility, academic/research institutions and particularly in the New England region (all P \u3c 0.01). After adjustments of other predictors in multivariate analysis, patients preferentially received AS if they were older (all OR\u27s \u3e 1 compared to younger groups), uninsured (vs. any insurance type, OR\u27s \u3e 1); or treated at academic/research center (OR \u3e 1). The overall use of AS increased from 11.6% (2010) to 27.3% (2013). We found a low, but rising rate of AS in a nationally representative group of very low-risk prostate cancer patients. Disparities in the use of AS may be targeted to improve adherence to national guidelines

Clinicopathologic Significance of Excision Repair Cross-Complementation 1 Expression in Patients Treated With Breast-Conserving Surgery and Radiation Therapy

Purpose: The excision repair cross-complementation 1 (ERCC1) enzyme plays a rate-limiting role in the nucleotide excision repair pathway and is associated with resistance to platinum-based chemotherapy in cancers of the head and neck and the lung. The purpose of this study was to evaluate the clinicopathologic and prognostic significance of ERCC1 expression in a cohort of early-stage breast cancer patients treated with breast conservation therapy. Methods and Materials: Paraffin specimens from 504 women with early-stage breast cancer treated with breast conservation therapy were constructed into tissue microarrays. The array was stained for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) and ERCC1. This was then correlated with clinicopathologic factors and outcomes data. Results: ERCC-1 expression was evaluable in 366 cases (72%). In this group, 32% and 38% of patients received adjuvant chemotherapy and hormonal therapy, respectively. Increased ERCC-1 expression was found to be correlated with ER positivity (p \u3c 0.005), lower T stage (p \u3c 0.017), nodal negativity (p \u3c 0.013), age \u3e50 (p \u3c 0.006), reduced use of adjuvant chemotherapy (p \u3c 0.02), and increased use of adjuvant hormonal therapy (p \u3c 0.004). ERCC1 expression did not correlate with locoregional recurrence-free survival, distant metastasis-free survival, cause-specific survival, or overall survival. In patients who were both ERCC1-negative and -positive, the use of chemotherapy predicted for worse distant metastasis-free survival (p = 0.05 and p = 0.07, respectively) but not cause-specific survival or overall survival. Conclusions: Although ERCC1 expression did not predict for outcome measures in this dataset, overexpression correlated with favorable prognostic factors such as ER positivity, lower T stage, nodal negativity, and age \u3e50. To our knowledge, this is the first study investigating ERCC1 expression in patients receiving adjuvant radiation therapy for breast cancer. © 2010 Elsevier Inc. All rights reserved