Generalization Error in Deep Learning

Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing. However, alongside their state-of-the-art performance, it is still generally unclear what is the source of their generalization ability. Thus, an important question is what makes deep neural networks able to generalize well from the training set to new data. In this article, we provide an overview of the existing theory and bounds for the characterization of the generalization error of deep neural networks, combining both classical and more recent theoretical and empirical results

High precision magnetoencephalography reveals increased right-inferior frontal gyrus beta power during response conflict

Flexibility of behavior and the ability to rapidly switch actions is critical for adaptive living in humans. It is well established that the right-inferior frontal gyrus (R-IFG) is recruited during outright action-stopping, relating to increased beta (12–30 Hz) power. It has also been posited that inhibiting incorrect response tendencies and switching is central to motor flexibility. However, it is not known if the commonly reported R-IFG beta signature of response inhibition in action-stopping is also recruited during response conflict, which would suggest overlapping networks for stopping and switching. In the current study, we analyzed high precision magnetoencephalography (hpMEG) data recorded with multiple within subject recording sessions (trials n > 10,000) from 8 subjects during different levels of response conflict. We hypothesized that a R-IFG-triggered network for response inhibition is domain general and therefore also involved in mediating response conflict. We tested whether R-IFG showed increased beta power dependent on the level of response conflict. Using event-related spectral perturbations and linear mixed modeling, we found that R-IFG beta power increased for response conflict trials. The R-IFG beta increase was specific to trials with strong response conflict, and increased R-IFG beta power related to less error. This supports a more generalized role for R-IFG beta, beyond simple stopping behavior towards response switching

Battery electric long-haul trucks in Europe: Public charging, energy, and power requirements

Electric battery trucks (BETs) have the potential to significantly reduce emissions from heavy-duty vehicles. However, adopting BETs for long-haul operations depends on the availability of sufficient charging infrastructure. In this study, we use a trip chain model to assess the charging requirements for BETs in long-haul operations in Europe in 2030. Our model accounts for truck driving regulations and different stop types. We find that the number of overnight chargers (50–100 kW) required is 4–5 times higher than the number of megawatt chargers (0.7–1.2 MW) needed to support a BET share of 15% in long-haul operations. We estimate that approximately 40,000 overnight and 9,000 megawatt chargers are required, with an average of eight overnight and two megawatt chargers per charging area serving an average of two and 11 BETs daily, respectively. These findings provide insights for planning charging infrastructure for BETs in long-haul operations in Europe

Convergence towards an asymptotic shape in first-passage percolation on cone-like subgraphs of the integer lattice

In first-passage percolation on the integer lattice, the Shape Theorem provides precise conditions for convergence of the set of sites reachable within a given time from the origin, once rescaled, to a compact and convex limiting shape. Here, we address convergence towards an asymptotic shape for cone-like subgraphs of the $\Z^d$ lattice, where $d\ge2$. In particular, we identify the asymptotic shapes associated to these graphs as restrictions of the asymptotic shape of the lattice. Apart from providing necessary and sufficient conditions for $L^p$- and almost sure convergence towards this shape, we investigate also stronger notions such as complete convergence and stability with respect to a dynamically evolving environment.Comment: 23 pages. Together with arXiv:1305.6260, this version replaces the old. The main results have been strengthened and an earlier error in the statement corrected. To appear in J. Theoret. Proba

A Review of Big Data in Road Freight Transport Modeling: Gaps and Potentials

Road transport accounted for 20% of global total greenhouse gas emissions in 2020, of which 30% come from road freight transport (RFT). Modeling the modern challenges in RFT requires the integration of different freight modeling improvements in, e.g., traffic, demand, and energy modeling. Recent developments in \u27Big Data\u27 (i.e., vast quantities of structured and unstructured data) can provide useful information such as individual behaviors and activities in addition to aggregated patterns using conventional datasets. This paper summarizes the state of the art in analyzing Big Data sources concerning RFT by identifying key challenges and the current knowledge gaps. Various challenges, including organizational, privacy, technical expertise, and legal challenges, hinder the access and utilization of Big Data for RFT applications. We note that the environment for sharing data is still in its infancy. Improving access and use of Big Data will require political support to ensure all involved parties that their data will be safe and contribute positively toward a common goal, such as a more sustainable economy. We identify promising areas for future opportunities and research, including data collection and preparation, data analytics and utilization, and applications to support decision-making

Pharmacokinetic and pharmacodynamic modelling after subcutaneous, intravenous and buccal administration of a high-concentration formulation of buprenorphine in conscious cats

The aim of this study was to describe the joint pharmacokinetic-pharmacodynamic model and evaluate thermal antinociception of a high-concentration formulation of buprenorphine (Simbadol™) in cats

PERFORMA SIMPLIFIED ACUTE PHYSIOLOGY SCORE 3 SEBAGAI PREDIKTOR MORTALITAS PADA UNIT RAWAT INTENSIF KARDIOVASKULAR

Background: Severity of illness scoring systems has gained increasing popularity in Intensive Care Units (ICUs) since 1980s. Physicians used them for predicting mortality and assessing illness severity in clinical trials. The Simplified Acute Physiology Score 3 (SAPS 3) is the only score that can predict hospital mortality within an hour of admission to ICU. Although this scoring systems has been widely used in ICUs, they have not been commonly applied in Intensive Cardiovascular Care Units (ICVCUs) since the population is quite different especially in disease subset. Therefore, the objective of this study was to evaluate the parameters in the SAPS 3 scoring system performance for predicting mortality in ICVCU population.Methods: This was an observational study with cross-sectional approach using secondary data from RAICOM (Registry of Acute and Intensive Cardiovascular Care on Outcome) taken from September 2013 – September 2014 in the ICVCU National Cardiovascular Centre Harapan Kita, Jakarta, Indonesia. The secondary data were collected, analysed, and matched with SAPS 3 variables. All missing and invalid data were excluded. All data was processed and the SAPS 3 score was calculated in each patient. Multivariate analysis with logistic regression was conducted to evaluate the significance of the parameters in predicting mortality. Discrimination was assessed by area under the receiver operator characteristic curve (AUROC). Calibration was assessed by Hosmer-Lemeshow goodness-of-fit test through calculating the ratio of observed?to?expected numbers of deaths.Results: A total of 233 patients were included in this study and the observed hospital mortality was 16.7% (39/233). The patients enrolled were divided into survivors and nonsurvivors. Bivariate analyses of SAPS 3 variables showed intra-hospital location before ICVCU admission, use of vasoactive agents, reasons for ICVCU admission, infection, Glasgow Coma Score (GCS), creatinine level, and platelet count were significantly different between nonsurvivors than survivors (P<0.05). The SAPS 3 score was significantly higher in nonsurvivors than survivors. The AUC (95% confidence intervals [CIs]) for SAPS 3 score was 0.752 (0.669–0.835). The Hosmer?Lemeshow goodness?of?fit test for SAPS 3 demonstrated a Chi?square test score of 1.729, P = 0.943. Multivariate logistic regression was conducted for all variables that were probably correlated to prognosis. Eventually, intermediate ward as intra-hospital location before ICVCU admission was selected as an independent risk factors for predicting mortality (OR 4.165; 95% CI 1.462-11.864; P=0.008), whereas surprisingly the presence of community-acquired pneumonia (CAP) before ICVCU admission was a protective factor from hospital mortality (OR 0.224; 95% CI 0.068-0.730; P=0.013).Conclusion: Parameters in the SAPS 3 score system exhibited satisfactory performance in discrimination. In predicting hospital mortality, these parameters also showed good calibration for estimating hospital mortality. Intermediate ward as intra-hospital location before ICVCU admission appeared to be independently associated with mortality whereas patients with CAP comorbid as a protective factor against mortality. Despite the good result of this study, there are still plenty room of improvement for developing similar score in the future specifically for ICVCU population

Inattentive Consumers in Markets for Services

In an experiment on markets for services, we find that consumers are likely to stick to default tariffs and achieve suboptimal outcomes. We find that inattention to the task of choosing a better tariff is likely to be a substantial problem in addition to any task and tariff complexity effect. The institutional setup on which we primarily model our experiment is the UK electricity and gas markets, and our conclusion is that the new measures by the UK regulator Ofgem to improve consumer outcomes are likely to be of limited impact

Module-Based Analysis of Robustness Tradeoffs in the Heat Shock Response System

Biological systems have evolved complex regulatory mechanisms, even in situations where much simpler designs seem to be sufficient for generating nominal functionality. Using module-based analysis coupled with rigorous mathematical comparisons, we propose that in analogy to control engineering architectures, the complexity of cellular systems and the presence of hierarchical modular structures can be attributed to the necessity of achieving robustness. We employ the Escherichia coli heat shock response system, a strongly conserved cellular mechanism, as an example to explore the design principles of such modular architectures. In the heat shock response system, the sigma-factor σ(32) is a central regulator that integrates multiple feedforward and feedback modules. Each of these modules provides a different type of robustness with its inherent tradeoffs in terms of transient response and efficiency. We demonstrate how the overall architecture of the system balances such tradeoffs. An extensive mathematical exploration nevertheless points to the existence of an array of alternative strategies for the existing heat shock response that could exhibit similar behavior. We therefore deduce that the evolutionary constraints facing the system might have steered its architecture toward one of many robustly functional solutions