Future Performance Improvements Research Articles

Machine Learning in Radiology: Applications Beyond Image Interpretation

Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside of image interpretation long before a fully functional “machine radiologist” is implemented in practice. Here, we describe an overview of machine learning, its application to radiology and other domains, and many cases of use that do not involve image interpretation. We hope that better understanding of these potential applications will help radiology practices prepare for the future and realize performance improvement and efficiency gains.

Modeling linearity and ambipolarity in GFETs on different dielectrics for communication applications

A low voltage pristine graphene FET (GFET) using density functional theory and local density approximation (LDA) has been simulated on different dielectric regions i.e. k = 3.9, 5.0, 9.7 and 25. An enhanced device linearity and ambipolarity in its characteristics was achieved w.r.t. high k dielectric region in a GFET. The high k value of the dielectric region originated due to high capacitance yielded high linearity at low voltage operation below 2 V. The linear region obtained at k = 25 is reported to be highest (0–1.75 V) as compared to the lower dielectric values. Further, the ambipolar characteristics obtained showed most symmetrical characteristics giving similar mobility of 52 and 78 cm2/Vs respectively at a fixed drain bias of 1 V. Moreover, the GFET on highest k value of dielectric region exhibited highest on off ratio as compared to other lower values chosen. This observation provides a route to band gap engineering in graphene devices. Thus, for the same physical dimensions of GFET, the improvement in the device linearity and achieving symmetrical ambipolarity with the enhancement in current density at low voltages can be suggested by the use of high k dielectric region. This understanding of impact of dielectrics has great potential for future performance improvements in nanoelectronic device circuits such as amplifiers and mixers.

The estimation and decomposition of tourism productivity

This paper estimates a total factor productivity index that allows for a rich decomposition of productivity in the tourism industry. We account for two important characteristics: First, the heterogeneity between multiple tourism destinations, and second, the potential endogeneity in inputs. Importantly we develop our index at the macro level, focusing on cross-country comparisons. Using the Bayesian approach, we test the performance of the model across various priors. We rank tourism destinations based on their tourism productivity and discuss the main sources of productivity growth. We also provide long-run productivity measures and discuss the importance of distinguishing between short-run and long-run productivity measures for future performance improvement strategies.

Electronic defects in the halide antiperovskite semiconductor Hg3Se2I2

Halide perovskites have emerged as a potential photoconducting material for photovoltaics and hard radiation detection. We investigate the nature of charge transport in the semi-insulating chalcohalide ${\mathrm{Hg}}_{3}{\mathrm{Se}}_{2}{\mathrm{I}}_{2}$ compound using the temperature dependence of dark current, thermally stimulated current (TSC) spectroscopy, and photoconductivity measurements as well as first-principles density functional theory (DFT) calculations. Dark conductivity measurements and TSC spectroscopy indicate the presence of multiple shallow and deep level traps that have relatively low concentrations of the order of ${10}^{13}\ensuremath{-}{10}^{15}\phantom{\rule{0.16em}{0ex}}\mathrm{c}{\mathrm{m}}^{\ensuremath{-}3}$ and capture cross sections of $\ensuremath{\sim}{10}^{\ensuremath{-}16}\phantom{\rule{0.16em}{0ex}}\mathrm{c}{\mathrm{m}}^{2}$. A distinct persistent photoconductivity is observed at both low temperatures ($l170\phantom{\rule{0.16em}{0ex}}\mathrm{K}$) and high temperatures ($g230$ K), with major implications for room-temperature compound semiconductor radiation detection. From preliminary DFT calculations, the origin of the traps is attributed to intrinsic vacancy defects (${V}_{\mathrm{Hg}}, {V}_{\mathrm{Se}}$, and ${V}_{\mathrm{I}}$) and interstitials (${\mathrm{Se}}_{\mathrm{int}}$) or other extrinsic impurities. The results point the way for future improvements in crystal quality and detector performance.

Design of a Highly Efficient (97.7%) and Very Compact (2.2 kW/dm $^3$) Isolated AC–DC Telecom Power Supply Module Based on the Multicell ISOP Converter Approach

The rising electricity demand of data centers has initiated a development trend toward highly efficient power supplies. Therefore, a multicell converter approach for a telecom rectifier module breaking through the efficiency and power density barriers of traditional single-cell converter systems is presented in this paper. The potential of the multicell approach for high efficiency is derived from fundamental scaling laws of different system performance aspects in dependence of the number of converter cells and the benefits of the interleaving technique. Based on the available degrees of freedom in the design of such a converter system, a comprehensive multiobjective optimization of the entire system with respect to efficiency and power density is performed with detailed component loss and volume models. In order to verify the analytical models and the design procedure, a hardware demonstrator of a 3.3 kW multicell $\text{230}\,V_\text{AC}/\text{48}\, V_\text{DC}$ telecom power supply with $N_{\text{cells}}=6$ isolated converter cells in an input-series output-parallel arrangement is presented with measurement results indicating a maximum efficiency of $\eta =$ 97.7% and a power density of $\rho =$ 2.2 kW/dm3 (= 36 W/in3). Furthermore, different paths for future performance improvements of the multicell arrangement are outlined.

Innovation externalities and the customer/supplier link

Abstract This paper proposes a novel channel through which innovation externalities can affect firm performance. I find cross-sectional evidence that the positive innovation outputs of customer firms increase their supplier profitability as measured by firm ROE. This result is robust to the inclusion of industry fixed effect, a control for both supplier and customer characteristics, such as ROE, advertisement expenditure, capital expenditure, firm age, industry concentration, institutional ownership, dividend yield, and a control for industry spillover or geographical spillover. To identify the causal effect of customer innovation outputs on supplier performance, I study an exogenous shock—State Street Bank and Trust Company v. Signature Financial Group, Inc.—and find that an increase in granted customer patents causes an improvement in future supplier performance. This effect is mainly driven by the demand channel and the knowledge diffusion channel from customers to suppliers.

Effect of calf-raise training on rapid force production and balance ability in elderly men.

This study examined whether home-based, high-speed calf-raise training changes the rate of torque development (RTD) during plantar flexion contractions and balance performance in elderly men. Thirty-four healthy elderly men (73 ± 5 yr) were randomly assigned to a training or control group (n = 17 in each group). The subjects in the training group completed 8 wk (3 times/wk) of home-based bilateral calf-raise training using body mass. Before and after the intervention, RTD during plantar flexion contractions and center-of-pressure (COP) displacement during single-leg standing were measured. Surface electromyographic amplitude of the triceps surae and tibialis anterior during the strength and single-leg standing was measured. Clinical magnitude-based inferences were used to interpret the training effect, with the smallest worthwhile effect assumed to be 0.2 of the baseline SD. The peak RTD increased 21% (90% confidence limits, ±19%) relative to the control group, which was accompanied by corresponding changes of the medial gastrocnemius (MG) and soleus (SOL) activations. The effect on COP displacement was possibly trivial (0%, ±13%), whereas substantial reduction in the MG (-19%, ±15%) and SOL (-25%, ±13%) activations during standing was observed. Our findings indicate that calf-raise training at home, performed without special equipment or venue, induces a substantial increase in the plantar flexors' rapid force-generating capability and triceps surae activations. Although the training effect on standing balance performance was not substantial, observed changes in the triceps surae activations during standing are expected to contribute to future balance performance improvement.NEW & NOTEWORTHY Calf-raise training with the intent to move rapidly, without special equipment or venue, induces an improvement of explosive plantar flexion force, which is attributable to neuromuscular rather than musculotendinous adaptations. Although the training effect on balance performance was trivial, we found a sign of improvement (i.e., neuromuscular adaptations during standing). In conclusion, functional neuromuscular capacity can be enhanced by home-based calf-raise exercise in elderly men, which may protect against mobility loss with aging.

A Neutral pH Aqueous Organic–Organometallic Redox Flow Battery with Extremely High Capacity Retention

We demonstrate an aqueous organic and organometallic redox flow battery utilizing reactants composed of only earth-abundant elements and operating at neutral pH. The positive electrolyte contains bis((3-trimethylammonio)propyl)ferrocene dichloride, and the negative electrolyte contains bis(3-trimethylammonio)propyl viologen tetrachloride; these are separated by an anion-conducting membrane passing chloride ions. Bis(trimethylammoniopropyl) functionalization leads to ∼2 M solubility for both reactants, suppresses higher-order chemical decomposition pathways, and reduces reactant crossover rates through the membrane. Unprecedented cycling stability was achieved with capacity retention of 99.9943%/cycle and 99.90%/day at a 1.3 M reactant concentration, increasing to 99.9989%/cycle and 99.967%/day at 0.75–1.00 M; these represent the highest capacity retention rates reported to date versus time and versus cycle number. We discuss opportunities for future performance improvement, including chemical modification...

Narrabat — прототип сервиса для пересказа новостей в формате стихотворений

Nowadays, news portals are forced to seek new methods of engaging the audience due to the increasing competition in today’s mass media. The growth in the loyalty of news service consumers may further a rise of popularity and, as a result, additional advertising revenue. Therefore, we propose the tool that is intended for stylish presenting of facts from a news feed. Its outputs are little poems that contain key facts from different news sources, based on the texts of Russian classics. The main idea of our algorithm is to use a collection of classical literature or poetry as a dictionary of style. The facts are extracted from news texts through Tomita Parser and then presented in the form similar to a sample from the collection. During our work, we tested several approaches for text generating, such as machine learning (including neural networks) and template-base method. The last method gave us the best performance, while the texts generated by the neural network are still needed to be improved. In this article, we present the current state of Narrabat, a prototype system rephrasing news we are currently working on, give examples of generated poems, and discuss some ideas for future performance improvement.

Investigation into the performance of oil and gas projects

Many oil and gas projects experienced significant cost overruns, which is a major concern for the industry. The objective of this study is to investigate the cost performance of oil and gas projects by analyzing the data of approximately 200 public oil and gas projects. The average cost overrun of the projects is 18% with a standard deviation of 29%. The results also indicate that the error of underestimation is more frequent and greater than that of the overestimation. The projects' cost performance is also examined in terms of project size, type, region, joint venture information, and Final Investment Decision (FID) year. All effects of each factor are tested with statistical methods, and various drivers for cost performances are suggested to explain the differences in cost performance. The findings of this research will provide some guidance and references for future improvement in project performance.

Investigations of Performance and Durability of PtNi-Alloy Based MEAs Utilizing In-Cell Diagnostics

The successful commercialization of Polymer Electrolyte Fuel Cells (PEFCs) system requires highly active oxygen-reduction reaction (ORR) electrocatalysts to meet the cost, performance, and durability targets for automotive applications. Although significant progress has been made in the past decade, Pt/C catalyst has the limitation of high material cost and insufficient ORR activity. Platinum-nickel alloy catalysts with core-shell structure have been demonstrated by multiple research groups to have higher intrinsic ORR activity, which can exceed the U.S. DOE 2015 ORR activity target, and also have promising stability in PEFC conditions [1, 2]. Additionally, Membrane Electrode Assemblies (MEAs) with low loadings of highly active Pt-group metal (PGM) catalysts have already been demonstrated to exceed the high-efficiency target of > 0.3 A/cm2 at 0.8 V [3]; however, the rated-power target of 1 W/cm2 cannot be met with these MEAs due to transport losses that are unique to MEAs with ultra-low catalyst loadings [4, 5]. United Technologies Research Center (UTRC) is a part of a DOE-supported research project, led by Argonne National Laboratory (ANL), focused on improving the understanding, performance, and durability of advanced Pt-alloy catalysts operating in complete PEFCs. In the current study, advanced MEAs with high ORR activity Pt-Ni alloy catalysts and ultra-low Pt loading (total ~ 0.13 mg-Pt/cm2) are prepared by Johnson Matthey Fuel Cells (JMFC) and tested by UTRC. The focus of this talk will be on using a variety of in-cell diagnostics and analysis methods to investigate both the initial performance and durability of these state-of-the-art MEAs. One example diagnostic that will be utilized are Polarization Change Curves (PCCs), which were originally developed for durability studies [6], but can also be used to investigate changes in performance due to operating conditions or MEA composition. For example, Fig 1a is a PCC comparison of the initial performance of the PtNi MEA and a Pt-only MEA, which have similar average catalyst particle size and the same carbon support, metal/carbon ratio, and ionomer/carbon ratio. Clearly, in addition to the differences in catalyst activity, there are also differences in the transport losses between these two different electrocatalysts. The durability of ultra-low Pt loading MEAs will also be discussed. Fig. 1b is a durability example of a PCC result, which is after applying a recent DOE-suggested AST protocol (0.6V-0.95V trapezoid potential cycle, with 700mV/s ramp rate and 6s/cycle). Other diagnostics and analysis beyond PCCs will also be included. The results obtained from these in-cell diagnostics will be used to hypothesize the potential mechanisms responsible for the differences in polarization curves, as well as project possible pathways to future performance and durability improvements. Acknowledgements This work is partially funded by the U. S. Department of Energy (DOE) under contract number DE-AC02-06CH11357. The authors would like to thank their DOE-project colleagues, especially those at ANL and JMFC.

(Invited) Figure of Merit for Carbon Nanotube Photothermoelectric Detectors

Carbon nanotubes (CNTs) have emerged as promising materials for visible, infrared, and terahertz photodetectors. Further development of these photodetectors requires a fundamental understanding of the mechanisms that govern their behavior as well as the establishment of figures of merit for technology applications. Recently, a number of CNT detectors have been shown to operate based on the photothermoelectric effect. Here we present a figure of merit for these detectors, which includes the properties of the material and the device. In addition, we use a suite of experimental characterization methods for the thorough analysis of the electrical, thermoelectric, electrothermal, and photothermal properties of the CNT thin-film devices. Our measurements determine the quantities that enter the figure of merit, and allow us to establish a path towards future performance improvements. Figure 1

Design concepts for diffusive holographic photopolymers

ABSTRACTDiffusive photopolymers are an area of intense recent materials development, spurred by interest in holographic data storage, display holography, and custom diffractive optical elements, among other applications. This review examines a range of photopolymer formulations of academic and commercial interest, and places their design strategies in context via quantitative analysis of the recording fidelity, maximum refractive index change and the degree to which they achieve this limit. Finally, this analysis is extended to estimate the scope of achievable future performance improvements. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016, 54, 1021–1035.

Simultaneous tDCS-fMRI Identifies Resting State Networks Correlated with Visual Search Enhancement.

This study uses simultaneous transcranial direct current stimulation (tDCS) and functional MRI (fMRI) to investigate tDCS modulation of resting state activity and connectivity that underlies enhancement in behavioral performance. The experiment consisted of three sessions within the fMRI scanner in which participants conducted a visual search task: Session 1: Pre-training (no performance feedback), Session 2: Training (performance feedback given), Session 3: Post-training (no performance feedback). Resting state activity was recorded during the last 5 min of each session. During the 2nd session one group of participants underwent 1 mA tDCS stimulation and another underwent sham stimulation over the right posterior parietal cortex. Resting state spontaneous activity, as measured by fractional amplitude of low frequency fluctuations (fALFF), for session 2 showed significant differences between the tDCS stim and sham groups in the precuneus. Resting state functional connectivity from the precuneus to the substantia nigra, a subcortical dopaminergic region, was found to correlate with future improvement in visual search task performance for the stim over the sham group during active stimulation in session 2. The after-effect of stimulation on resting state functional connectivity was measured following a post-training experimental session (session 3). The left cerebellum Lobule VIIa Crus I showed performance related enhancement in resting state functional connectivity for the tDCS stim over the sham group. The ability to determine the relationship that the relative strength of resting state functional connectivity for an individual undergoing tDCS has on future enhancement in behavioral performance has wide ranging implications for neuroergonomic as well as therapeutic, and rehabilitative applications.

Fully inkjet‐printed metal‐oxide thin‐film transistors on plastic

Fully inkjet‐printed, transparent conductive oxide thin‐film transistors on polyimide are demonstrated for the first time integrating SnO2:F source/drain electrodes, ZrO2 gate dielectric, and ZnSnO semiconductor layers. A mobility of ∼0.04 cm2 V−1 s−1 was obtained at a maximum thermal processing temperature of 300 °C. In addition to electrical device characterization, SEM, TEM, and EDX analyses were performed to assess microstructure and chemical composition. Through our analysis, we show that future performance improvements require an increase in source/drain conductivity at lower annealing temperatures, the reduction in film cracking due to thermal stress, and the reduction in intermixing between layers occurring during annealing.

Field validation of habitat suitability models for vulnerable marine ecosystems in the South Pacific Ocean: Implications for the use of broad-scale models in fisheries management

Management of human activities which impact the seafloor in the deep ocean is becoming increasingly important as bottom trawling and exploration for minerals, oil, and gas continue to extend into regions where fragile ecosystems containing habitat-forming deep-sea corals and sponges may be found. Spatial management of these vulnerable marine ecosystems requires accurate knowledge of their distribution. Predictive habitat suitability modelling, using species presence data and a suite of environmental predictor variables, has emerged as a useful tool for inferring distributions outside of known areas. However, validation of model predictions is typically performed with non-independent data. In this study, we describe the results of habitat suitability models constructed for four deep-sea reef-forming coral species across a large region of the South Pacific Ocean using MaxEnt and Boosted Regression Tree modelling approaches. In order to validate model predictions we conducted a photographic survey on a set of seamounts in an un-sampled area east of New Zealand. The likelihood of habitat suitable for reef-forming corals on these seamounts was predicted to be variable, but very high in some regions, particularly where levels of aragonite saturation, dissolved oxygen, and particulate organic carbon were optimal. However, the observed frequency of coral occurrence in analyses of survey photographic data was much lower than expected, and patterns of observed versus predicted coral distribution were not highly correlated. The poor performance of these broad-scale models is attributed to lack of recorded species absences to inform the models, low precision of global bathymetry models, and lack of data on the geomorphology and substrate of the seamounts at scales appropriate to the modelled taxa. This demonstrates the need to use caution when interpreting and applying broad-scale, presence-only model results for fisheries management and conservation planning in data poor areas of the deep sea. Future improvements in the predictive performance of broad-scale models will rely on the continued advancement in modelling of environmental predictor variables, refinements in modelling approaches to deal with missing or biased inputs, and incorporation of true absence data.

Reducing Current Spread by Use of a Novel Pulse Shape for Electrical Stimulation of the Auditory Nerve.

Improving the electrode-neuron interface to reduce current spread between individual electrodes has been identified as one of the main objectives in the search for future improvements in cochlear-implant performance. Here, we address this problem by presenting a novel stimulation strategy that takes account of the biophysical properties of the auditory neurons (spiral ganglion neurons, SGNs) stimulated in electrical hearing. This new strategy employs a ramped pulse shape, where the maximum amplitude is achieved through a linear slope in the injected current. We present the theoretical framework that supports this new strategy and that suggests it will improve the modulation of SGNs’ activity by exploiting their sensitivity to the rising slope of current pulses. The theoretical consequence of this sensitivity to the slope is a reduction in the spread of excitation within the cochlea and, consequently, an increase in the neural dynamic range. To explore the impact of the novel stimulation method on neural activity, we performed in vitro recordings of SGNs in culture. We show that the stimulus efficacy required to evoke action potentials in SGNs falls as the stimulus slope decreases. This work lays the foundation for a novel, and more biomimetic, stimulation strategy with considerable potential for implementation in cochlear-implant technology.

Figure of Merit for Carbon Nanotube Photothermoelectric Detectors.

Carbon nanotubes (CNTs) have emerged as promising materials for visible, infrared, and terahertz photodetectors. Further development of these photodetectors requires a fundamental understanding of the mechanisms that govern their behavior as well as the establishment of figures of merit for technology applications. Recently, a number of CNT detectors have been shown to operate based on the photothermoelectric effect. Here we present a figure of merit for these detectors, which includes the properties of the material and the device. In addition, we use a suite of experimental characterization methods for the thorough analysis of the electrical, thermoelectric, electrothermal, and photothermal properties of the CNT thin-film devices. Our measurements determine the quantities that enter the figure of merit and allow us to establish a path toward future performance improvements.

DO MOTIVATED INSTITUTIONAL INVESTORS MONITOR FIRM PAYOUT AND PERFORMANCE?

AbstractWe document a positive relation between shareholder monitoring and total payout to shareholders using two monitoring proxies that jointly consider an investor's ability and incentive to monitor. We find that this relation is even stronger for firms with poor growth options and with greater potential for agency problems. Unlike traditional proxies, our two proxies do not exhibit any endogeneity with payout policy. We further show that monitoring is positively associated with future improvements in payout and operating performance. These findings are consistent with the prediction that shareholder monitoring leads to higher payout through increased efficiency and reduced agency costs.

High-performance conjugate-gradient benchmark: A new metric for ranking high-performance computing systems

We describe a new high-performance conjugate-gradient (HPCG) benchmark. HPCG is composed of computations and data-access patterns commonly found in scientific applications. HPCG strives for a better correlation to existing codes from the computational science domain and to be representative of their performance. HPCG is meant to help drive the computer system design and implementation in directions that will better impact future performance improvement.