LLukas22/scidocs huggingface dataset:
Myocardial injury after noncardiac surgery and its association with short-term mortality.

BACKGROUND
To identify patients at risk for postoperative myocardial injury and death, measuring cardiac troponin routinely after noncardiac surgery has been suggested. Such monitoring was implemented in our hospital. The aim of this study was to determine the predictive value of postoperative myocardial injury, as measured by troponin elevation, on 30-day mortality after noncardiac surgery.


METHODS AND RESULTS
This observational, single-center cohort study included 2232 consecutive intermediate- to high-risk noncardiac surgery patients aged ≥60 years who underwent surgery in 2011. Troponin was measured on the first 3 postoperative days. Log binomial regression analysis was used to estimate the association between postoperative myocardial injury (troponin I level >0.06 μg/L) and all-cause 30-day mortality. Myocardial injury was found in 315 of 1627 patients in whom troponin I was measured (19%). All-cause death occurred in 56 patients (3%). The relative risk of a minor increase in troponin (0.07-0.59 μg/L) was 2.4 (95% confidence interval, 1.3-4.2; P<0.01), and the relative risk of a 10- to 100-fold increase in troponin (≥0.60 μg/L) was 4.2 (95% confidence interval, 2.1-8.6; P<0.01). A myocardial infarction according to the universal definition was diagnosed in 10 patients (0.6%), of whom 1 (0.06%) had ST-segment elevation myocardial infarction.


CONCLUSIONS
Postoperative myocardial injury is an independent predictor of 30-day mortality after noncardiac surgery. Implementation of postoperative troponin monitoring as standard of care is feasible and may be helpful in improving the prognosis of patients undergoing noncardiac surgery.
RAPPORT Refactoring test code

Two key aspects of extreme programming (XP) are unit testing and merciless refactoring. Given the fact that the ideal test code / production code ratio approaches 1:1, it is not surprising that unit tests are being refactored. We found that refactoring test code is di erent from refactoring production code in two ways: (1) there is a distinct set of bad smells involved, and (2) improving test code involves additional test-speci c refactorings. To share our experiences with other XP practitioners, we describe a set of bad smells that indicate trouble in test code, and a collection of test refactorings to remove these smells. 2000 ACM Computing Classi cation System: D.2.3, D.2.5, D.2.7, D.2.9, K.6.3
Reprogrammable network packet processing on the field programmable port extender (FPX)

A prototype platform has been developed that allows processing of packets at the edge of a multi-gigabit-per-second network switch. This system, the Field Programmable Port Extender (FPX), enables packet processing functions to be implemented as modular components in reprogrammable hardware. All logic on the on the FPX is implemented in two Field Programmable Gate Arrays (FPGAs). Packet processing functions in the system are implemented as dynamically-loadable modules.
Core functionality of the FPX is implemented on an FPGA called the Networking Interface Device (NID). The NID contains the logic to transmit and receive packets over a network, dynamically reprogram hardware modules, and route individual traffic flows. A full, non-blocking, switch is implemented on the NID to route packets between the networking interfaces and the modular components. Modular components of the FPX are implemented on a second FPGA called the Reprogrammable Application Device (RAD). Modules are loaded onto the RAD via reconfiguration and/or partial partial reconfiguration of the FPGA.
Through the combination of the NID and the RAD, the FPX can individually reconfigure the packet processing functionality for one set of traffic flows, while the rest of the system continues to operate. The platform simplifies the development and deployment of new hardware-accelerated packet processing circuits. The modular nature of the system allows an active router to migrate functionality from softare plugins to hardware modules.
EEG-based decoding of error-related brain activity in a real-world driving task.

OBJECTIVES
Recent studies have started to explore the implementation of brain-computer interfaces (BCI) as part of driving assistant systems. The current study presents an EEG-based BCI that decodes error-related brain activity. Such information can be used, e.g., to predict driver's intended turning direction before reaching road intersections.


APPROACH
We executed experiments in a car simulator (N = 22) and a real car (N = 8). While subject was driving, a directional cue was shown before reaching an intersection, and we classified the presence or not of an error-related potentials from EEG to infer whether the cued direction coincided with the subject's intention. In this protocol, the directional cue can correspond to an estimation of the driving direction provided by a driving assistance system. We analyzed ERPs elicited during normal driving and evaluated the classification performance in both offline and online tests.


RESULTS
An average classification accuracy of 0.698 ± 0.065 was obtained in offline experiments in the car simulator, while tests in the real car yielded a performance of 0.682 ± 0.059. The results were significantly higher than chance level for all cases. Online experiments led to equivalent performances in both simulated and real car driving experiments. These results support the feasibility of decoding these signals to help estimating whether the driver's intention coincides with the advice provided by the driving assistant in a real car.


SIGNIFICANCE
The study demonstrates a BCI system in real-world driving, extending the work from previous simulated studies. As far as we know, this is the first online study in real car decoding driver's error-related brain activity. Given the encouraging results, the paradigm could be further improved by using more sophisticated machine learning approaches and possibly be combined with applications in intelligent vehicles.
Motivation to learn: an overview of contemporary theories

OBJECTIVE
To succinctly summarise five contemporary theories about motivation to learn, articulate key intersections and distinctions among these theories, and identify important considerations for future research.


RESULTS
Motivation has been defined as the process whereby goal-directed activities are initiated and sustained. In expectancy-value theory, motivation is a function of the expectation of success and perceived value. Attribution theory focuses on the causal attributions learners create to explain the results of an activity, and classifies these in terms of their locus, stability and controllability. Social- cognitive theory emphasises self-efficacy as the primary driver of motivated action, and also identifies cues that influence future self-efficacy and support self-regulated learning. Goal orientation theory suggests that learners tend to engage in tasks with concerns about mastering the content (mastery goal, arising from a 'growth' mindset regarding intelligence and learning) or about doing better than others or avoiding failure (performance goals, arising from a 'fixed' mindset). Finally, self-determination theory proposes that optimal performance results from actions motivated by intrinsic interests or by extrinsic values that have become integrated and internalised. Satisfying basic psychosocial needs of autonomy, competence and relatedness promotes such motivation. Looking across all five theories, we note recurrent themes of competence, value, attributions, and interactions between individuals and the learning context.


CONCLUSIONS
To avoid conceptual confusion, and perhaps more importantly to maximise the theory-building potential of their work, researchers must be careful (and precise) in how they define, operationalise and measure different motivational constructs. We suggest that motivation research continue to build theory and extend it to health professions domains, identify key outcomes and outcome measures, and test practical educational applications of the principles thus derived.
PTSD symptom reports of patients evaluated for the New Mexico Medical Cannabis Program.

BACKGROUND
New Mexico was the first state to list post-traumatic stress disorder (PTSD) as a condition for the use of medical cannabis. There are no published studies, other than case reports, of the effects of cannabis on PTSD symptoms. The purpose of the study was to report and statistically analyze psychometric data on PTSD symptoms collected during 80 psychiatric evaluations of patients applying to the New Mexico Medical Cannabis Program from 2009 to 2011.


METHODS
The Clinician Administered Posttraumatic Scale for DSM-IV (CAPS) was administered retrospectively and symptom scores were then collected and compared in a retrospective chart review of the first 80 patients evaluated.


RESULTS
Greater than 75% reduction in CAPS symptom scores were reported when patients were using cannabis compared to when they were not.


CONCLUSIONS
Cannabis is associated with reductions in PTSD symptoms in some patients, and prospective, placebo-controlled study is needed to determine efficacy of cannabis and its constituents in treating PTSD.
Beta-trace protein and cystatin c as predictors of major bleeding in non-ST-segment elevation acute coronary syndrome.

BACKGROUND
Beta-trace protein (BTP) and cystatin C (CysC) are novel biomarkers of renal function. We assessed the ability of both to predict major bleeding (MB) in patients with non-ST-segment elevation acute coronary syndromes (NSTE-ACS), compared to other renal function parameters and clinical risk scores.


METHODS AND RESULTS
We included 273 patients. Blood samples were obtained within 24h of admission. The endpoint was MB. During a follow-up of 760 days (411-1,098 days), 25 patients (9.2%) had MB. Patients with MB had higher concentrations of BTP (0.98 mg/L; 0.71-1.16 mg/L vs. 0.72 mg/L, 0.60-0.91 mg/L, P=0.002), CysC (1.05 mg/L; 0.91-1.30 mg/L vs. 0.90 mg/L, 0.75-1.08 mg/L, P=0.003), higher CRUSADE score (39 ± 16 points vs. 29 ± 15 points, P=0.002) and lower estimated glomerular filtration rate (eGFR; 66 ± 27 vs. 80 ± 30 ml·min(-1)·1.73 m(-2), P=0.02) than patients without MB; there was no difference in creatinine level between the groups (P=0.14). After multivariable adjustment, both were predictors of MB, while eGFR and creatinine did not achieve statistical significance. Among subjects with eGFR >60 ml·min(-1)·1.73 m(-2), those with elevated concentrations of both biomarkers had a significantly higher risk for MB. Net reclassification indexes from the addition of BTP and CysC to CRUSADE risk score were 38% and 21% respectively, while the relative integrated discrimination indexes were 12.5% and 3.8%.


CONCLUSIONS
Among NSTE-ACS patients, BTP and CysC were superior to conventional renal parameters for predicting MB, and improved clinical stratification for hemorrhagic risk.
How the Dark Triad traits predict relationship choices

While previous studies have correlated the Dark Triad traits (i.e., narcissism, psychopathy, and Machiavellianism) with a preference for short-term relationships, little research has addressed possible correlations with short-term relationship sub-types. In this online study using Amazon’s Mechanical Turk system (N = 210) we investigated the manner in which scores on the Dark Triad relate to the selection of different mating environments using a budget-allocation task. Overall, the Dark Triad were positively correlated with preferences for short-term relationships and negatively correlated with preferences for a long-term relationship. Specifically, narcissism was uniquely correlated with preferences for one-night stands and friends-with-benefits and psychopathy was uniquely correlated with preferences for bootycall relationships. Both narcissism and psychopathy were negatively correlated with preferences for serious romantic relationships. In mediation analyses, psychopathy partially mediated the sex difference in preferences for booty-call relationships and narcissism partially mediated the sex difference in preferences for one-night stands. In addition, the sex difference in preference for serious romantic relationships was partially mediated by both narcissism and psychopathy. It appears the Dark Triad traits facilitate the adoption of specific mating environments providing fit with people’s personality traits. 2012 Elsevier Ltd. All rights reserved.
Towards Automatic & Personalised Mobile Health Interventions: An Interactive Machine Learning Perspective

Machine learning (ML) is the fastest growing field in computer science and healthcare, providing future benefits in improved medical diagnoses, disease analyses and prevention. In this paper, we introduce an application of interactive machine learning (iML) in a telemedicine system, to enable automatic and personalised interventions for lifestyle promotion. We first present the high level architecture of the system and the components forming the overall architecture. We then illustrate the interactive machine learning process design. Prediction models are expected to be trained through the participants’ profiles, activity performance, and feedback from the caregiver. Finally, we show some preliminary results during the system implementation and discuss future directions. We envisage the proposed system to be digitally implemented, and behaviourally designed to promote healthy lifestyle and activities, and hence prevent users from the risk of chronic diseases. ACM Classification
Spatial hierarchy and OLAP-favored search in spatial data warehouse

Data warehouse and Online Analytical Processing(OLAP) play a key role in business intelligent systems. With the increasing amount of spatial data stored in business database, how to utilize these spatial information to get insight into business data from the geo-spatial point of view is becoming an important issue of data warehouse and OLAP. However, traditional data warehouse and OLAP tools can not fully exploit spatial data in coordinates because multi-dimensional spatial data does not have implicit or explicit concept hierarchy to compute pre-aggregation and materialization in data warehouse. In this paper we extend the traditional set-grouping hierarchy into multi-dimensional data space and propose to use spatial index tree as the hierarchy on spatial dimension. With spatial hierarchy, spatial data warehouse can be built accordingly. Our approach preserve the star schema in data warehouse while building the hierarchy on spatial dimension, and can be easily integrated into existing data warehouse and OLAP systems. To process spatial OLAP query in spatial data warehouse, we propose an OLAP-favored search method which can utilize the pre-aggregation result in spatial data warehouse to improve the performance of spatial OLAP queries. For generality, the algorithm is developed based on Generalized Index Searching Tree(GiST). To improve the performance of OLAP-favored search, we further introduce a heuristic search method which can provide an approximate answer to spatial OLAP query. Experiment result shows the efficiency of our method.
Empirical Findings in Agile Methods

In recent years, the use of, interest in, and controversy about Agile methodologies have realized dramatic growth. Anecdotal evidence is rising regarding the effectiveness of agile methodologies in certain environments and for specified projects. However, collection and analysis of empirical evidence of this effectiveness and classification of appropriate environments for Agile projects has not been conducted. Researchers from four institutions organized an eWorkshop to synchronously and virtually discuss and gather experiences and knowledge from eighteen Agile experts spread across the globe. These experts characterized Agile Methods and communicated experiences using these methods on small to very large teams. They discussed the importance of staffing Agile teams with highly skilled developers. They shared common success factors and identified warning signs of problems in Agile projects. These and other findings and heuristics gathered through this valuable exchange can be useful to researchers and to practitioners as they establish an experience base for better decision making. 1. The rise of Agile Methods Plan-driven methods are those in which work begins with the elicitation and documentation of a “complete” set of requirements, followed by architectural and high level-design development and inspection. Examples of plan-driven methods include various waterfall and iterative approaches, such as the Personal Software Process (PSP) [1]. Beginning in the mid-1990’s, some practitioners found these initial requirements documentation, and architecture and design development steps frustrating and, perhaps, impossible [2]. As Barry Boehm [3] suggests, these plan-driven methods may well start to pose difficulties when change rates are still relatively low. The In Proceedings of Extreme Programming and Agile Methods XP/Agile Universe 2002, pp. 197-207.
Energy-balance studies reveal associations between gut microbes, caloric load, and nutrient absorption in humans.

BACKGROUND
Studies in mice indicate that the gut microbiome influences both sides of the energy-balance equation by contributing to nutrient absorption and regulating host genes that affect adiposity. However, it remains uncertain as to what extent gut microbiota are an important regulator of nutrient absorption in humans.


OBJECTIVE
With the use of a carefully monitored inpatient study cohort, we tested how gut bacterial community structure is affected by altering the nutrient load in lean and obese individuals and whether their microbiota are correlated with the efficiency of dietary energy harvest.


DESIGN
We investigated dynamic changes of gut microbiota during diets that varied in caloric content (2400 compared with 3400 kcal/d) by pyrosequencing bacterial 16S ribosomal RNA (rRNA) genes present in the feces of 12 lean and 9 obese individuals and by measuring ingested and stool calories with the use of bomb calorimetry.


RESULTS
The alteration of the nutrient load induced rapid changes in the gut microbiota. These changes were directly correlated with stool energy loss in lean individuals such that a 20% increase in Firmicutes and a corresponding decrease in Bacteroidetes were associated with an increased energy harvest of ≈150 kcal. A high degree of overfeeding in lean individuals was accompanied by a greater fractional decrease in stool energy loss.


CONCLUSIONS
These results show that the nutrient load is a key variable that can influence the gut (fecal) bacterial community structure over short time scales. Furthermore, the observed associations between gut microbes and nutrient absorption indicate a possible role of the human gut microbiota in the regulation of the nutrient harvest. This trial was registered at clinicaltrials.gov as NCT00414063.
Histologically confirmed hippocampal structural features revealed by 3T MR imaging: potential to increase diagnostic specificity of mesial temporal sclerosis.

BACKGROUND AND PURPOSE
With appropriate selection, temporal lobe epilepsy is potentially curable with surgical intervention achieving seizure freedom in ~80% of individuals. MR imaging-based identification of MTS remains central to the selection process but currently relies on qualitative visual analysis. We sought to determine if new ultrastructural hippocampal details seen on 3T MR imaging had histopathologic correlates and whether these could serve as a useful tool in MTS identification.


MATERIALS AND METHODS
Patients undergoing selective anterior temporal lobectomy (n = 5) were scanned using 3T MR imaging preoperatively. En bloc resections were rescanned and subsequently prepared for histopathologic analysis of all hippocampal layers in the CA1-3 regions. Using a newly identified landmark from 3T FSTIR coronal images in 20 patients with histologically confirmed MTS, blinded studies compared ipsilateral and contralateral sides to generate threshold measurements for application in a fast quantitative analysis tool.


RESULTS
Histopathologic analysis and correlation with 3T imaging of en bloc resections identified the low-intensity signal as the stratum lacunosum. MTS was associated with extensive gliosis throughout the CA1-3 regions, with loss of tissue thickness in the stratum pyramidale most pronounced in CA1. Fast quantitative analysis by using the stratum lacunosum as a landmark provided a test that identifies MTS with a SN of 70% and SP of 85%.


CONCLUSIONS
Here we delineated ultrastructural hippocampal details seen on 3T MR imaging in both the in vivo and ex vivo setting, correlating these with histopathologic features consistent with MTS, and provided preliminary data suggesting their utility in the development of a quantitative analysis assessment tool for application in surgical-candidate selection.
Efficiency and Sequenceability in Fair Division of Indivisible Goods with Additive Preferences

In fair division of indivisible goods, using sequences of sincere choices (or picking sequences) is a natural way to allocate the objects. The idea is the following: at each stage, a designated agent picks one object among those that remain. This paper, restricted to the case where the agents have numerical additive preferences over objects, revisits to some extent the seminal paper by Brams and King [9] which was specific to ordinal and linear order preferences over items. We point out similarities and differences with this latter context. In particular, we show that any Paretooptimal allocation (under additive preferences) is sequenceable, but that the converse is not true anymore. This asymmetry leads naturally to the definition of a “scale of efficiency” having three steps: Pareto-optimality, sequenceability without Paretooptimality, and non-sequenceability. Finally, we investigate the links between these efficiency properties and the “scale of fairness” we have described in an earlier work [7]: we first show that an allocation can be envy-free and non-sequenceable, but that every competitive equilibrium with equal incomes is sequenceable. Then we experimentally explore the links between the scales of efficiency and fairness.