A Side of Data With My Robot

It is increasingly recognized that older adults with cancer represent a diverse cohort of patients and that other comorbidities may have an equal impact on survival and quality of life as any diagnosis of malignancy. Competing risk has consequently emerged as an important concept in the design and reporting of geriatric oncology trials. We performed a systematic review of phase II and III oncology trials for systemic therapy in older patients with solid organ malignancy from the year 2000 until April 30, 2017. Forty-one trials including 7864 patients were identified for evaluation. Only 15 trials (36.6%) employed disease-related end points to account for death from other causes, and only one study used statistical analysis that addressed competing risk. Seventeen studies (41.5%) of trials included some assessment of comorbidity or frailty. Twenty-one trials (51.2%) included any assessment of quality of life. This review demonstrates clear areas for improvement for future studies and highlights the need for careful consideration of trial design, data collection, and appropriate statistical methodology for reporting of competing risks in geriatric oncology trials.

Pesticides are among the most serious risks to the health of agricultural workers and surrounding rural communities. Occupational exposure to pesticides occurs while applying, mixing, washing contaminated clothes and empty containers etc. and through different exposure routes. The Rotterdam Convention is a multilateral agreement aiming at protecting human health and environment from the risks of hazardous pesticides and other chemicals that are still on trade and, for this reason, widely used in agriculture. To support developing countries and economies in transition, there is a specific article for detecting problems with certain pesticide formulations in the field. Under this framework, good experience has been gained in collecting data on occupational exposure to pesticides in the field, with a particular focus on vulnerable groups (women, children, young workers, seasonal workers) and in different regional contexts such as in the Eastern Europe, Caucasus and Central Asia and in Africa. To provide guidance to Parties, a tool for monitoring and reporting pesticide poisoning incidents (Severely Hazardous Pesticide Formulation – SHPF toolkit) has been developed with information on methodologies for data collection, examples of incident reporting systems and several awareness-raising materials. Reporting on pesticide incidents to the Rotterdam Convention has the advantage of making those incidents known to the world by sharing information with other countries which experience the same problems with specific pesticide formulations and allowing them to see if risk management measures are properly taken into account at national level.

Life cycle assessments of recycled material used in roadways are currently not well understood or well documented. The Recycled Materials Resource Center’s (RMRC) research is aimed at quantitatively determining the environmental and economic benefits of using recycled material in road construction. Two case studies were performed to analyze the impacts of incorporating recycled material in the reconstruction of two major roadways using life cycle assessment (LCA) and life cycle cost analysis (LCCA) tools. Results from both roads show that the use of recycled materials reduces energy and water consumption, greenhouse gas emissions, and cost. Because typical roadway construction projects do not separately track the extensive use of recycled materials, the RMRC was unable to utilize the LCA and LCCA technology in the first roadway’s analysis without making significant assumptions for the inputs. To clarify and verify some of these assumptions, the second roadway project was undertaken. This second case study is being studied to determine a better methodology for data collection with fewer assumptions, in addition to assessing the benefits of recycled material use. The methodology for data collection and analysis developed through the second project can be used to conduct LCAs and LCCA for future highway construction projects with greater confidence.

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The main focus of this thesis is the use of high-throughput sequencing technologies in functional genomics (in particular in the form of ChIP-seq, chromatin immunoprecipitation coupled with sequencing, and RNA-seq) and the study of the structure and regulation of transcriptomes. Some parts of it are of a more methodological nature while others describe the application of these functional genomic tools to address various biological problems. A significant part of the research presented here was conducted as part of the ENCODE (ENCyclopedia Of DNA Elements) Project. The first part of the thesis focuses on the structure and diversity of the human transcriptome. Chapter 1 contains an analysis of the diversity of the human polyadenylated transcriptome based on RNA-seq data generated for the ENCODE Project. Chapter 2 presents a simulation-based examination of the performance of some of the most popular computational tools used to assemble and quantify transcriptomes. Chapter 3 includes a study of variation in gene expression, alternative splicing and allelic expression bias on the single-cell level and on a genome-wide scale in human lymphoblastoid cells; it also brings forward a number of critical to the practice of single-cell RNA-seq measurements methodological considerations. The second part presents several studies applying functional genomic tools to the study of the regulatory biology of organellar genomes, primarily in mammals but also in plants. Chapter 5 contains an analysis of the occupancy of the human mitochondrial genome by TFAM, an important structural and regulatory protein in mitochondria, using ChIP-seq. In Chapter 6, the mitochondrial DNA occupancy of the TFB2M transcriptional regulator, the MTERF termination factor, and the mitochondrial RNA and DNA polymerases is characterized. Chapter 7 consists of an investigation into the curious phenomenon of the physical association of nuclear transcription factors with mitochondrial DNA, based on the diverse collections of transcription factor ChIP-seq datasets generated by the ENCODE, mouseENCODE and modENCODE consortia. In Chapter 8 this line of research is further extended to existing publicly available ChIP-seq datasets in plants and their mitochondrial and plastid genomes. The third part is dedicated to the analytical and experimental practice of ChIP-seq. As part of the ENCODE Project, a set of metrics for assessing the quality of ChIP-seq experiments was developed, and the results of this activity are presented in Chapter 9. These metrics were later used to carry out a global analysis of ChIP-seq quality in the published literature (Chapter 10). In Chapter 11, the development and initial application of an automated robotic ChIP-seq (in which these metrics also played a major role) is presented. The fourth part presents the results of some additional projects the author has been involved in, including the study of the role of the Piwi protein in the transcriptional regulation of transposon expression in Drosophila (Chapter 12), and the use of single-cell RNA-seq to characterize the heterogeneity of gene expression during cellular reprogramming (Chapter 13). The last part of the thesis provides a review of the results of the ENCODE Project and the interpretation of the complexity of the biochemical activity exhibited by mammalian genomes that they have revealed (Chapters 15 and 16), an overview of the expected in the near future technical developments and their impact on the field of functional genomics (Chapter 14), and a discussion of some so far insufficiently explored research areas, the future study of which will, in the opinion of the author, provide deep insights into many fundamental but not yet completely answered questions about the transcriptional biology of eukaryotes and its regulation.

LiDAR point cloud-based place recognition (LPR) in unstructured natural environments remains an open challenge with limited existing research. To address the limitations of unstructured environments, such as sparse structural features, uneven point cloud density, and significant viewpoint variations, we present BSPR-Net, a dual-branch point cloud feature extraction approach for point cloud place recognition, which consists of a BEV - projection rotation - invariant convolution branch and a point cloud sparse convolution branch. This design enhances the representation capability of geometric structural features while aggregating rotation-invariant characteristics of point clouds, thereby better addressing the challenge of large viewpoint disparities in reverse-revisited unstructured environments. The proposed network was tested on multiple reverse-revisited sequences of the Wild-Places data set, a benchmark for unstructured natural environment place recognition. It achieved a maximum F1 score of 85.46 %, exceeding other classical methods by more than 4 %. The ablation experiments further confirmed the effectiveness of each module in improving place recognition performance.

We contribute HAA500 1 , a manually annotated human-centric atomic action dataset for action recognition on 500 classes with over 591K labeled frames. To minimize ambiguities in action classification, HAA500 consists of highly diversified classes of fine-grained atomic actions, where only consistent actions fall under the same label, e.g., "Baseball Pitching" vs "Free Throw in Basketball". Thus HAA500 is different from existing atomic action datasets, where coarse-grained atomic actions were labeled with coarse action-verbs such as "Throw". HAA500 has been carefully curated to capture the precise movement of human figures with little class-irrelevant motions or spatiotemporal label noises.The advantages of HAA500 are fourfold: 1) human-centric actions with a high average of 69.7% detectable joints for the relevant human poses; 2) high scalability since adding a new class can be done under 20–60 minutes; 3) curated videos capturing essential elements of an atomic action without irrelevant frames; 4) fine-grained atomic action classes. Our extensive experiments including cross-data validation using datasets collected in the wild demonstrate the clear benefits of human-centric and atomic characteristics of HAA500, which enable training even a baseline deep learning model to improve prediction by attending to atomic human poses. We detail the HAA500 dataset statistics and collection methodology and compare quantitatively with existing action recognition datasets.

Humanoid robotic manipulation in unstructured environments is a challenging problem. Limited perception, communications and environmental constraints present challenges that prevent fully autonomous or purely teleoperated robots from reliably interacting with their environment. In order to achieve higher reliability in manipulation we present an approach involving remote human supervision. Strengths from both human operator and humanoid robot are leveraged through a user interface that allows the operator to perceive the remote environment through an aggregated worldmodel based on onboard sensing, while the robot can efficiently receive perceptual and semantic information from the operator. A template based manipulation approach has been successfully applied to the Atlas humanoid robot; we show real world footage of the results obtained in the DARPA Robotics Challenge Trials 2013.

Residual neuromuscular blockade is common and associated with increased risk of airway obstruction, hypoxemia, and postoperative pulmonary complications.1 Sugammadex reverses moderately deep rocuronium-induced blockade 7 times faster and deep blockade 17 times faster than neostigmine, and only 13 patients need to be treated with sugammadex rather than neostigmine to avoid residual neuromuscular blockade.2 However, despite this strong biologic rationale for a reduction in postoperative pulmonary complications with sugammadex, evidence from large well-conducted multicenter studies is lacking.In this issue of Anesthesiology, Kheterpal et al.3 report the results of the largest observational study to date investigating the association between choice of reversal agent and postoperative pulmonary complications (the sugammadex versus neostigmine for reversal of neuromuscular blockade and postoperative pulmonary complications [STRONGER] study). They included 45,712 adults admitted to 12 academic and community hospitals in the United States for elective noncardiac surgery. Of these, 22,856 patients received sugammadex and 22,856 patients received neostigmine for reversal of rocuronium or vecuronium. The incidence of a composite of pneumonia, respiratory failure, pneumothorax, and other major pulmonary complications was 3.5% in the sugammadex group and 4.8% in the neostigmine group (adjusted odds ratio, 0.70; 95% CI, 0.63–0.77; number needed to treat 77 to avoid a major pulmonary complication in one patient in this population). Given the millions of people at risk, the suffering of patients who experience postoperative pulmonary complications, and the financial implications for the healthcare system, this 30% reduction could be practice-changing if it is true.Kheterpal et al. took several steps to reduce the pitfalls associated with observational studies. Because of the cost, services and providers often restrict the use of sugammadex to patients with risk factors for postoperative pulmonary complications (i.e., obesity, pulmonary disease, deep neuromuscular blockade).4 To mitigate this bias, the neostigmine patients underwent surgery between 2014 and 2015, before sugammadex was approved for use in the United States. To make the two groups as similar as possible, patients were matched on the basis of age, sex, obesity, and comorbidities and surgeries associated with postoperative pulmonary complications. Statistical adjustments were made for preoperative and intraoperative factors showing significant imbalance between the sugammadex- and neostigmine-treated groups. Sensitivity analyses were conducted to determine whether changes to the types of patients included or the coding of postoperative pulmonary complications made a difference to the results, and to determine how susceptible the results were to confounding by unmeasured or unknown factors. The investigators achieved balance between the two groups in many important known confounding factors; their results were stable in a wide range of sensitivity analyses, and the results had low susceptibility to residual confounding. Nevertheless, Kheterpal et al. acknowledge that their observational study lacks the power of a large randomized, controlled trial to produce a definitive result.If a large randomized, controlled trial were to be conducted, what would it look like? A traditional randomized, controlled trial would compare sugammadex and neostigmine under ideal conditions.5 The patients would be carefully selected to reduce variability. Perioperative drug administration, temperature management, and ventilation would be protocolized, and quantitative neuromuscular monitoring would be used. Masked study drugs would be administered at a specified state of recovery. Tracheal extubation would only be allowed when strict criteria were met. This careful control would minimize the incidence of postoperative pulmonary complications overall and the difference between the two groups, because all patients would be properly reversed before extubation. Well in excess of 10,000 patients would be required, making this one of the largest and most costly perioperative trials to date.In the real world, quantitative neuromuscular monitoring and extubation after adequate reversal are not routine.1,3 Even sustained quality improvement programs are unable to completely change practice.6 A pragmatic trial testing sugammadex and neostigmine under real-world conditions is therefore justified. Quantitative neuromuscular monitoring would be available and encouraged, but not mandated. A wide variety of patients would be included. Perioperative care would remain at the discretion of anesthesia providers. Unmasked medications would be used, with randomization results revealed to anesthesia providers at the end of surgery. Data collection methodology would be similar to that used by Kheterpal et al. (i.e., electronic medical records, administrative databases, and/or registries). The impact of increased variability would likely be moderated by lower rates of residual neuromuscular blockade in the sugammadex group.2 The results of a pragmatic trial would be generalizable to routine practice in the United States and around the world if sugammadex was more affordable.Sugammadex remains an expensive drug, out of the reach of many patients and health services that may benefit from its use.4 Because the current evidence base is inadequate,2 Kheterpal et al. recommend that future evaluations of sugammadex include a cost–benefit analysis.3 This analysis should be based not only on the current price and existing use: it should also model the situation in which sugammadex is cheap but volume is high. This may reveal a win–win situation for the manufacturer, health services, and patients, and an obligation on all sides to make sugammadex more widely available.Economics aside, should we wait for the results of a large pragmatic trial before we change our practice? Sugammadex is the best available reversal agent, especially in the real world where appropriate monitoring is not the norm1 and hard to enforce.6 There is a very strong rationale that a lower incidence of residual blockade will lead to fewer postoperative pulmonary complications. High-quality observational trials, such as that of Kheterpal et al., suggest a clinically meaningful effect with a number needed to treat that would be even more acceptable if sugammadex were less expensive. Large pragmatic trials are desirable, because they provide the most reliable evidence to guide practice. In the absence of such a trial, choosing sugammadex in combination with quantitative neuromuscular monitoring with the intent of reducing the risk of postoperative pulmonary complication is justifiable.The author is not supported by, nor maintains any financial interest in, any commercial activity that may be associated with the topic of this article.

Artificial Intelligence in the American Healthcare Industry: Looking Forward to 2030

Darkness, Datafication, and Provenance as an Illuminating Methodology

This thesis deals with the analysis and understanding of drivers’ behaviours under car-following. The aim is to enhance the modelling tools toward the development of new ADAS (Advanced Driving Assistance System) logics, characterized by a more human-like behaviour. After having introduced the argument of the thesis (and motivated the work) and having recalled the state of the art most relevant in the field of car-following (as well as in the instruments for observing car-following in the real world), the thesis evolves toward three main sections: actual observation of real-world data and collection of the datasets to be employed for theoretical analysis; theoretical enhancements and propositions; applications to ACC (Adaptive Cruise Control), as a relevant field for ADAS. The data employed in this work have been collected in three different field surveys, two of them carried out in Italy and the other in the United Kingdom. In all cases data have been collected by instrumented vehicles, equipped in such a way to observe and record car-following trajectories. Data have been framed into different theoretical paradigms in order to both validate each theory and to establish the links between these theories. Links have been established both in a formal way (through theoretical investigation) and in a data-driven way. The considered theoretical paradigm for modelling car-following follows different approaches: one is based on the psycho-physical approach and two others are based on an engineering-inspired approach. In particular, the considered psycho-physical approach has been the Action Point theory (Wiedemann, 1974); a revised version of the paradigm, more compliant with the original version of Barbosa (1961) and Todosoiev (1963) has been proposed and justified with reference to the collected data. The first engineering paradigm has been based on a state-space approach. The proposed approach has been shown to be consistent with the Action Point theory. The parameters of the model have been estimated by means of the collected data and the obtained results have been discussed; they are consistent with observations and justify the adopted model. The other engineering model is based on a linear approximation (at any time t, in a discrete-time approach) of the response of the follower to the leader’s stimuli. Also the linear model is shown to be a very good approximation of the observed data; moreover, it has been shown to lead to an harmonic oscillation around the desired spacing at steady-state. This oscillation is consistent with both the Action Point theory and (partially) with the proposed state-space approach. The linear model is particularly suitable for real-time ACC-oriented application; thus it is the model employed in section 4 of this work, where a fully-adaptive ACC system is developed, able to actuate a driving-style actually consistent with driver’s expectations and preferences.

SUMMARYSeismic hazard assessment (SHA) requires earthquake events characterized in terms of the moment magnitude (Mw) scale both in the earthquake catalogues and in the ground motion databases (SHA data sets). However, published Mw estimates for the same event may actually differ due to the adoption of different computation methods, input data, or seismic networks. The main objective of this paper is to develop a novel strategy to assign a unique Mw value for each earthquake and unified to an Mw reference data set that can be applied to low-to-moderate seismicity regions (Mw < 4.5) such as Metropolitan France, the target region of our study. The strategy consists of first collecting all Mw estimated directly by spectral or temporal inversion in a large area of the European–Mediterranean zone, including regional and specific studies in our target region. Then, the sources of Mw estimates are ranked in five different categories, from global to specific studies. A GCMT (Global Centroid Moment Tensor project) standard Mw value is recomputed and a quality flag is assigned depending on the level of the information provided by the sources. Mw estimates are then compared at the European–Mediterranean scale with those provided by the CMT services, chosen as reference. Mw estimates are subsequently corrected for their systematic deviations by progressively including lower magnitude estimates as one moves from high ranked categories to lower ones at each step of the unification procedure. In this work, the collected data set contains 6752 Mw estimates of 4454 shallow events (depth < 40 km) that occurred between 1963 and 2019 and computed by 34 sources (bulletins, publications,…, etc). A unified Mw value could be attributed to 185 events (2.36 ≤ Mw ≤ 5.35) in France and neighbouring regions and 3351 events (3.06 ≤ Mw ≤ 7.57) in the European–Mediterranean region. Finally, we showed that this Mw data set is consistent with European SHA data sets but leads to slightly larger Mw values compared to the French SHA data sets. We also noted that some variability still subsist in Mw data set compared to the existing SHA data sets, especially for Mw < 5.0. This new unified Mw data set is a first step toward the building of future catalogues. It will contribute to greatly improve the coherence of Mw definitions in the next generation of SHA data sets for both metropolitan France and Europe.

The major sources of abundant data is constantly expanding with the available data collection methodologies in various applications—medical, insurance, scientific, bio-informatics and business. These data sets may be distributed geographically, rich in size and as well as dimensions also. To analyze these data sets to find out the hidden patterns, it is required to download the data to a centralized site which is a challenging task in terms of the limited bandwidth available and computationally also expensive. The covariance matrix is one of the method to estimate the relation between any two dimensions. In this paper we propose a communication efficient algorithm to estimate the covariance matrix in a distributed manner. The global covariance matrix is computed by merging the local covariance matrices using a distributed approach. The results show that it is exactly same as centralized method with good speed-up in terms of computation. The reason for speed-up is because of the parallel construction of local covariances and distributing the cross covariances among the nodes so that the load is balanced. The results are analyzed by considering Mfeat data set on the various partitions which addresses the scalability also.

A gripper is described for manipulation in natural, unstructured environments. The specific manipulation task is to pick up surface material such as pebbles or small rocks in a natural terrain. The application is to give autonomous sampling capabilities to an autonomous vehicle for planetary exploration. The authors describe the task analysis process that led to the selection of a configuration with three soft fingers. They carry out a complete analysis of the stability of a grasp for this gripper including an analysis of the deformation of the fingers at the points of contact. The implementation of a grasp selection algorithm is described, and results on three-dimensional representations of objects computed from range data are presented. >