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Increasing availability of personal data opened new possibilities for technologies that support individuals' reflection, increase their self-awareness, and inform their future choices. Personal informatics, chiefly concerned with investigating individuals' engagement with personal data, has become an area of active research within Human-Computer Interaction. However, more recent research has argued that personal informatics solutions often place high demands on individuals and require knowledge, skills, and time for engaging with personal data. New advances in Machine Learning (ML) and Artificial Intelligence (AI) can help to reduce the cognitive burden of personal informatics and identify meaningful trends using analytical engines. Furthermore, introducing ML and AI can enable systems that provide more direct support for action, for example through predictions and recommendations. However, there are many open questions as to the design of personal informatics technologies that incorporate ML and AI. In this workshop, we will bring together an interdisciplinary group of researchers in personal informatics, ML, and AI to outline the design space for intelligent personal informatics solutions and develop an agenda for future research in this area.

As data centers proliferate, their energy intensity deserves close attention. Always-on operations and growing usage for cloud and other backend processes make servers the fundamental driver of data center energy use. Yet servers’ power draw under real-world conditions is poorly understood. This paper explores characteristics of volume servers that affect energy use, quantifying differences in power draw between higher-performing Standard Performance Evaluation Corporation (SPEC) and ENERGY STAR servers and that of a typical server. First, we establish general characteristics of the US installed base, before reporting hardware configurations from a major online retail website. We then compare idle power across three datasets (one unique to this paper) and explain their differences via the hardware characteristics to which power draw is most sensitive. We find idle server power demand to be significantly higher than benchmarks from ENERGY STAR and the industry-released SPEC database, and SPEC server configurations—and likely their power scaling—to be atypical of volume servers. Next, we examine power draw trends among high-performing servers across their load range to consider whether these trends are representative of volume servers, before inputting average idle power load values into a recent national server energy use model. Lastly, results from two surveys of IT professionals illustrate the incidence of more efficient equipment and operational practices in server rooms/closets. Future work should include server power field measurements in data centers of different sizes, accounting for variations in configurations and setting changes post-purchase, as well as investigating the linkage between time and server energy efficiency.

Axon initial segments (AISs) generate action potentials and regulate the polarized distribution of proteins, lipids, and organelles in neurons. While the mechanisms of AIS Na+ and K+ channel clustering are understood, the molecular mechanisms that stabilize the AIS and control neuronal polarity remain obscure. Here, we use proximity biotinylation and mass spectrometry to identify the AIS proteome. We target the biotin-ligase BirA* to the AIS by generating fusion proteins of BirA* with NF186, Ndel1, and Trim46; these chimeras map the molecular organization of AIS intracellular membrane, cytosolic, and microtubule compartments. Our experiments reveal a diverse set of biotinylated proteins not previously reported at the AIS. We show many are located at the AIS, interact with known AIS proteins, and their loss disrupts AIS structure and function. Our results provide conceptual insights and a resource for AIS molecular organization, the mechanisms of AIS stability, and polarized trafficking in neurons.

RationalePrimary graft dysfunction (PGD) is a form of acute lung injury that occurs after lung transplantation. The definition of PGD was standardized in 2005. Since that time, clinical practice has evolved, and this definition is increasingly used as a primary endpoint for clinical trials; therefore, validation is warranted.ObjectivesWe sought to determine whether refinements to the 2005 consensus definition could further improve construct validity.MethodsData from the Lung Transplant Outcomes Group multicenter cohort were used to compare variations on the PGD definition, including alternate oxygenation thresholds, inclusion of additional severity groups, and effects of procedure type and mechanical ventilation. Convergent and divergent validity were compared for mortality prediction and concurrent lung injury biomarker discrimination.Measurements and main resultsA total of 1,179 subjects from 10 centers were enrolled from 2007 to 2012. Median length of follow-up was 4 years (interquartile range = 2.4-5.9). No mortality differences were noted between no PGD (grade 0) and mild PGD (grade 1). Significantly better mortality discrimination was evident for all definitions using later time points (48, 72, or 48-72 hours; P

BACKGROUND. The ABO histo-blood group is defined by carbohydrate modifications and is associated with risk for multiple diseases, including acute respiratory distress syndrome (ARDS). We hypothesized that genetically determined blood subtype A1 is associated with increased risk of ARDS and markers of microvascular dysfunction and coagulation. METHODS. We conducted analyses in 3 cohorts of critically ill trauma and sepsis patients (n = 3710) genotyped on genomewide platforms to determine the association of the A1 blood type genotype with ARDS risk. We subsequently determined whether associations were present in FUT2-defined nonsecretors who lack ABO antigens on epithelium, but not endothelium. In a patient subgroup, we determined the associations of blood type with plasma levels of endothelial glycoproteins and disseminated intravascular coagulation (DIC). Lastly, we tested whether blood type A was associated with less donor lung injury recovery during human ex vivo lung perfusion (EVLP). RESULTS. The A1 genotype was associated with a higher risk of moderate to severe ARDS relative to type O in all 3 populations. In sepsis, this relationship was strongest in nonpulmonary infections. The association persisted in nonsecretors, suggesting a vascular mechanism. The A1 genotype was also associated with higher DIC risk as well as concentrations of thrombomodulin and von Willebrand factor, which in turn were associated with ARDS risk. Blood type A was also associated with less lung injury recovery during EVLP. CONCLUSION. We identified a replicable association between ABO blood type A1 and risk of ARDS among the critically ill, possibly mediated through microvascular dysfunction and coagulation. FUNDING. NIH HL122075, HL125723, HL137006, HL137915, DK097307, HL115354, HL101779, and the University of Pennsylvania McCabe Fund Fellowship Award., Introduction Acute respiratory distress syndrome (ARDS) is a common complication of critical illness characterized by lung inflammation, epithelial and endothelial dysfunction, alveolar capillary leak, and microthrombosis (1, 2). Clinically, it [...]

Social networks have become important objects of study in recent years. Social media marketing has, for example, greatly benefited from the vast literature developed in the past two decades. The study of social networks has taken advantage of recent advances in machine learning to process these immense amounts of data. Automatic emotional labeling of content on social media has, for example, been made possible by the recent progress in natural language processing. In this work, we are interested in the influence maximization problem, which consists of finding the most influential nodes in the social network. The problem is classically carried out using classical performance metrics such as accuracy or recall, which is not the end goal of the influence maximization problem. Our work presents an end-to-end learning model, SGREEDYNN, for the selection of the most influential nodes in a social network, given a history of information diffusion. In addition, this work proposes data visualization techniques to interpret the augmenting performances of our method compared to classical training. The results of this method are confirmed by visualizing the final influence of the selected nodes on network instances with edge bundling techniques. Edge bundling is a visual aggregation technique that makes patterns emerge. It has been shown to be an interesting asset for decision-making. By using edge bundling, we observe that our method chooses more diverse and high-degree nodes compared to the classical training. [ABSTRACT FROM AUTHOR]

Future small satellites will demand high-performance on-board electronics, requiring sophisticated approaches to heat rejection beyond simply increasing the radiator surface area. An interesting alternative approach is to increase the surface temperature of the radiator, using a heat pump. In this study, calculations were carried out to compute the theoretical radiator size reduction potential enacted by having a heat pump as part of a satellite's thermal management system. The practical likelihood of a 'typical' vapor compression cycle (VCC) heat pump satisfying theoretical requirements was considered. In agreement with theoretical calculations, employing a 'typical' VCC heat pump could either increase or decrease the required radiator surface area. The choice of heat pump and its design is therefore crucial. A heat pump with a large temperature lift is essential for satellite radiator cooling applications, with the coefficient of performance (COP) being less important. Even with a low COP, such as 2.4, a 'typical' heat pump providing a large temperature lift, close to 60 °C, could reduce the satellite's radiator surface area by a factor close to 1.4. This is a significant potential reduction. The decision on whether to pursue this approach compared to alternatives, such as deployable radiators, should consider the relative complexity, cost, weight, size, reliability, etc., of the two options. The focus of this study is VCC heat pumps; however, the results provide performance targets for less mature heat pump technologies, e.g., caloric devices, which could ultimately be applied in space. [ABSTRACT FROM AUTHOR]

Objective: The next generation prosthetic hand that moves and feels like a real hand requires a robust neural interconnection between the human minds and machines. Methods: Here we present a neuroprosthetic system to demonstrate that principle by employing an artificial intelligence (AI) agent to translate the amputee’s movement intent through a peripheral nerve interface. The AI agent is designed based on the recurrent neural network (RNN) and could simultaneously decode six degree-of-freedom (DOF) from multichannel nerve data in real-time. The decoder’s performance is characterized in motor decoding experiments with three human amputees. Results: First, we show the AI agent enables amputees to intuitively control a prosthetic hand with individual finger and wrist movements up to 97-98% accuracy. Second, we demonstrate the AI agent’s real-time performance by measuring the reaction time and information throughput in a hand gesture matching task. Third, we investigate the AI agent’s long-term uses and show the decoder’s robust predictive performance over a 16-month implant duration. Conclusion & significance: Our study demonstrates the potential of AI-enabled nerve technology, underling the next generation of dexterous and intuitive prosthetic hands. [ABSTRACT FROM AUTHOR]

Some psychologists may be interested in working collaboratively with clergy and yet may not know where to start. What kinds of collaborative projects are possible? A qualitative analysis of 77 narratives offered by psychologists and clergy involved in collaboration revealed that collaboration between psychologists and clergy currently takes place in at least four contexts; mental health services, parish life, community concerns, and academics. Reported obstacles to collaboration are also described. Essential attitudes for psychologists interested in collaborating with clergy include respecting clergy as professionals, willingness to venture out from traditional professional settings, and exploring innovative collaborative possibilities.

If a patient adheres to religious values and practices, should the treating psychologist get input from a clergyperson? How frequent is clergy-psychologist collaboration? What obstacles impede such collaboration? An exploratory survey questionnaire was sent to 200 clergy, 200 psychologists interested in religious issues, and 200 psychologists selected without regard to religious interests or values. Four themes were assessed: types of collaborative activities, frequency of collaboration, obstacles to collaboration, and ways to enhance collaboration. Strategies for promoting clergy - psychologist collaboration include challenging unidirectional referral assumptions, building trust through proximity and familiarity, and considering the importance of shared values and beliefs.

Simulated annealing (SA) is a robust, stable, but computationally costly method for solving ill-posed image-restoration problems. We describe the use of a backprojection operator that identifies those regions of an object estimate that have the greatest likelihood of being in error at each step of the SA process. This reduces computational time by concentrating the computing effort of SA on those pixels most effective in reducing the reconstruction error. The performance of an area-adaptive SA algorithm is evaluated for the restoration of images blurred by a simple pillbox space-invariant and a biconical space-variant point-spread function typical of a depth-measuring optical system.

Many choice problems often involve multiple attributes which are mentally challenging, because only one attribute is neatly sorted while others could be randomly arranged. We hypothesize that perceiving approximately monotonic trends across multiple attributes is key to the overall interpretability of sorted results, because users can easily predict the attribute values of the next items. We extend a ranking principal curve model to tune monotonic trends in attributes and present Imma Sort to sort items by multiple attributes simultaneously by trading-off the monotonicity in the primary sorted attribute to increase the human predictability for other attributes. We characterize how it performs for varying attribute correlations, attribute preferences, list lengths and number of attributes. We further extend Imma Sort with ImmaAnchor and ImmaCenter to improve the learnability and efficiency to search sorted items with conflicting attributes. We demonstrate usage scenarios for two applications and evaluate its learnability, usability, interpretability, and user performance in prediction and search tasks. We find that Imma Sort improves the interpretability and satisfaction of sorting by $\geq 2$ ≥ 2 attributes. We discuss why, when, where, and how to deploy Imma Sort for real-world applications. [ABSTRACT FROM AUTHOR]

Electronic skins are essential for real-time health monitoring and tactile perception in robots. Although the use of soft elastomers and microstructures have improved the sensitivity and pressure-sensing range of tactile sensors, the intrinsic viscoelasticity of soft polymeric materials remains a long-standing challenge resulting in cyclic hysteresis. This causes sensor data variations between contact events that negatively impact the accuracy and reliability. Here, we introduce the Tactile Resistive Annularly Cracked E-Skin (TRACE) sensor to address the inherent trade-off between sensitivity and hysteresis in tactile sensors when using soft materials. We discovered that piezoresistive sensors made using an array of three-dimensional (3D) metallic annular cracks on polymeric microstructures possess high sensitivities (> 107 Ω ⋅ kPa-1), low hysteresis (2.99 ± 1.37%) over a wide pressure range (0-20 kPa), and fast response (400 Hz). We demonstrate that TRACE sensors can accurately detect and measure the pulse wave velocity (PWV) when skin mounted. Moreover, we show that these tactile sensors when arrayed enabled fast reliable one-touch surface texture classification with neuromorphic encoding and deep learning algorithms. [ABSTRACT FROM AUTHOR]

Sparse Mobile Crowdsensing (MCS) has become a compelling approach to acquire and infer urban-scale sensing data. However, participants risk their location privacy when reporting data with their actual sensing positions. To address this issue, we propose a novel location obfuscation mechanism combining $\epsilon $ -differential-privacy and $\delta $ -distortion-privacy in Sparse MCS. More specifically, differential privacy bounds adversaries’ relative information gain regardless of their prior knowledge, while distortion privacy ensures that the expected inference error is larger than a threshold under an assumption of adversaries’ prior knowledge. To reduce the data quality loss incurred by location obfuscation, we design a differential-and-distortion privacy-preserving framework with three components. First, we learn a data adjustment function to fit the original sensing data to the obfuscated location. Second, we apply a linear program to select an optimal location obfuscation function. The linear program aims to minimize the uncertainty in data adjustment under the constraints of $\epsilon $ -differential-privacy, $\delta $ -distortion-privacy, and evenly-distributed obfuscation. We also design an approximated method to reduce the required computation resources. Third, we propose an uncertainty-aware inference algorithm to improve the inference accuracy for the obfuscated data. Evaluations with real environment and traffic datasets show that our optimal method reduces the data quality loss by up to 42% compared to the state-of-the-art methods with the same level of privacy protection; the approximated method incurs < 3% additional quality loss than the optimal method, but only needs < 1% of the computation time. [ABSTRACT FROM AUTHOR]

OD bundling is a promising method to identify key origin-destination (OD) patterns, but the bundling can mislead the interpretation of actual trajectories traveled. We present OD Morphing, an interactive OD bundling technique that improves geographical faithfulness to actual trajectories while preserving visual simplicity for OD patterns. OD Morphing iteratively identifies critical waypoints from the actual trajectory network with a min-cut algorithm and transitions OD bundles to pass through the identified waypoints with a smooth morphing method. Furthermore, we extend OD Morphing to support bundling at interaction speeds to enable users to interactively transition between degrees of faithfulness to aid sensemaking. We introduce metrics for faithfulness and simplicity to evaluate their trade-off achieved by OD morphed bundling. We demonstrate OD Morphing on real-world city-scale taxi trajectory and USA domestic planned flight datasets. [ABSTRACT FROM AUTHOR]

Taxi sharing is a promising approach to reducing energy consumptions, utilizing limited taxi resources efficiently while preserving the interest of individuals. The existing studies mostly fail to locate a pick-up/drop-off point for each individual passenger in scheduling the sharing route. Besides, they can hardly provide personalized services. To this end, we propose a new taxi-sharing system called Flexi-Sharing to provide flexible and personalized taxi sharing services. It considers the nearby alternative pick-up/drop-off locations and schedules a flexible sharing route with the maximum reduced travel distance by letting passengers walk a short distance. For a sharing request, Flexi-Sharing generates the sharing schedule consisting of a set of companions, the shortest sharing route and the best pick-up/drop-off locations by maximizing the satisfaction of involved passengers. Extensive experiments are conducted using a one-month taxi trajectory data collected in Chengdu, China. Experimental results show that Flexi-Sharing achieves 60% sharing rate and reduces 28 000 km travel distances per hour in the city, which are 15% higher and 16% longer than those of the method that delivers passengers at exact requested locations, respectively. Flexi-Sharing also promises a satisfactory system response time and provides superior sharing experiences. [ABSTRACT FROM AUTHOR]

This paper proposes a novel task allocation framework, PSTasker, for participatory sensing (PS), which aims to maximize the overall system utility on PS platform by coordinating the allocation of multiple tasks. While existing studies mainly optimize the task allocation from the perspective of the task organizer (e.g., maximizing coverage or minimizing incentive cost), PSTasker further considers diverse factors on the participants' side, including user work bandwidth, user availability, devices' sensor configuration, task completion likelihood, and mobility pattern. Furthermore, by considering the heterogeneity in three dimensions (i.e., task, time, and space), it adopts a novel model to measure task sensing quality and overall system utility. In PSTasker, it first calculates the utlity of a given task allocation plan by jointly fusing different participant-side factors into one unified estimation function, and then employs an iterative greedy process to optimize the task allocation. Extensive evaluations based on real-world mobility traces demonstrate that PSTasker outperforms the baseline methods under various settings. [ABSTRACT FROM AUTHOR]

Background: Coarctation of the aorta is a congenital cardiac defect characterized by a narrowing of the proximal thoracic aorta. Despite excellent long-term results, surgical repair is rarely complicated by recoarctation.Methods/results: We describe a case with the longest time to reintervention to date, featuring surgical repair of delayed aortic recoarctation and pseudoaneurysm 53 years after the initial operation.Discussion: This case emphasizes the need for lifelong surveillance in this patient population and exemplifies a multidisciplinary approach in evaluating treatment options of complex aortic pathology, including open and endovascular considerations. [ABSTRACT FROM AUTHOR]

A review of the article "Two Distinct Secretory Pathways for Differential Kv2.1 Localization in Neurons," by Brian Christopher Lim and Cheng-Hsin Liu, which appeared in the "Journal of Neuroscience" on May 2, 2018, is presented.

OBJECTIVES:Pancreatic cystic neoplasms (PCNs) are being detected with increased frequency. The aims of this study were to determine the incidence of malignancy and develop an imaging-based system for prediction of malignancy in PCN.METHODS:We conducted a retrospective cohort study of patients ≥18 years of age with confirmed PCN from January 2005 to December 2010 in a community-based integrated care setting in Southern California. Patients with history of acute or chronic pancreatitis were excluded. Malignancy diagnosed within 3 months of cyst diagnosis was considered as pre-existing. Subsequent incidence of malignancy during surveillance was calculated based on person-time at risk. Age- and gender-adjusted standardized incidence ratio (SIR) was calculated with the non-cyst reference population. Recursive partitioning was used to develop a risk prediction model based on cyst imaging features.RESULTS:We identified 1,815 patients with confirmed PCN. A total of 53 (2.9%) of patients were diagnosed with cyst-related malignancy during the study period. The surveillance cohort consisted of 1,735 patients with median follow-up of 23.4 months. Incidence of malignancy was 0.4% per year during surveillance. The overall age- and gender-adjusted SIR for pancreatic malignancy was 35.0 (95% confidence level 26.6, 46.0). Using recursive partitioning, we stratified patients into low (<1%), intermediate (1-5%), and high (9-14%) risk of harboring malignant PCN based on four cross-sectional imaging features: size, pancreatic duct dilatation, septations with calcification as well as growth. Area under the receiver operator characteristic curve for the prediction model was 0.822 (training) and 0.808 (testing).CONCLUSIONS:Risk of pancreatic malignancy was lower than previous reports from surgical series but was still significantly higher than the reference population. A risk stratification system based on established imaging criteria may help guide future management decisions for patients with PCN. [ABSTRACT FROM AUTHOR]

Background: Opportunities for trainees to learn the basics of papillotomy prior to performance on patients is desirable. A papillotomy scoring scale provides objective assessment of papillotomy performance. Aim: To determine the effects of teaching and simulation practice on papillotomy performance using disposable papillae and the endoscopic retrograde cholangio-pancreatography (ERCP) mechanical simulator (EMS). Method: Trainees attended workshops with didactic talks on how to perform the "perfect" biliary papillotomy. They performed artificial papillotomy on a series of blank (baseline cut) and lined (learning cut) papillae marked with the perfect biliary axis using the eMs. An exit evaluation involved a papillotomy on a second blank (test cut) papilla. Video recording of the simulation practices were reviewed and scored blindly using the published papillotomy scoring scale modified for eMs practice. The scores for baseline and test blank cuts were compared. Trainees also responded to pre- and post-practice questionnaire surveys on their understanding and confidence in performing a biliary papillotomy and the credibility of simulator papillotomy practice. Results: The papillotomy performance of 32 trainees at 7 workshops was analyzed. There was a significant improvement in papillotomy score from 7.0 (6.0-8.0) to 8.5 (8.0-9.0) [Median (25%-75% interquartile range), Wilcoxon signed-rank test, p<0.05] when the baseline and test cuts were compared. There were significant improvements in post-practice score on understanding, confidence and credibility. Conclusion: Didactic teaching and simulation practice demonstrates improvement in trainees' papillotomy performance using artificial papillae with the EMS. The impact of simulation practice as a valid education adjunct on clinical performance deserves further evaluation. [ABSTRACT FROM AUTHOR]