5,455 research outputs found
The Newsvendor Problem: Review and Directions for Future Research
In this paper, we review the contributions to date for analyzing the newsvendor problem. Our focus is on examining the specific extensions for analyzing this problem in the context of modeling customer demand, supplier costs, and the buyer risk profile. More specifically, we analyze the impact of market price, marketing effort, and stocking quantity on customer demand; how supplier prices can serve as a coordination mechanism in a supply chain setting; integrating alternative supplier pricing policies within the newsvendor framework; and how the buyer’s risk profile moderates the newsvendor order quantity decision. For each of these areas,we summarize the current literature and develop extensions. Finally, we also propose directions for future research
SmartTennisTV: Automatic indexing of tennis videos
In this paper, we demonstrate a score based indexing approach for tennis
videos. Given a broadcast tennis video (BTV), we index all the video segments
with their scores to create a navigable and searchable match. Our approach
temporally segments the rallies in the video and then recognizes the scores
from each of the segments, before refining the scores using the knowledge of
the tennis scoring system. We finally build an interface to effortlessly
retrieve and view the relevant video segments by also automatically tagging the
segmented rallies with human accessible tags such as 'fault' and 'deuce'. The
efficiency of our approach is demonstrated on BTV's from two major tennis
tournaments.Comment: 10 pages, 4 figures, NCVPRIPG 2017 Accepted Paper (Best Paper Award
Winner
Hybrid-DC Electric Springs for DC Voltage Regulation and Harmonic Cancellation in DC Microgrids
DC electric springs (DCES) are emerging technologies for the (i) regulation of mains voltage against the intermittent renewable generations and (ii) harmonic cancellation in dc microgrids. When conventional converter topologies (e.g., half-bridge or full-bridge converter) are adopted as DCES, the battery storage of the DCES has to process both the dc power and the ac harmonic power. The pulsating ac power can severely reduce the lifetime of the battery. To address this issue, a hybrid-DCES (H-DCES) is proposed in this paper to perform (i) and (ii) in a decoupled manner. With a modified topology and control method, the H-DCES can divert the ac current to the ground and retains the function of manipulating noncritical load for dc voltage regulation. The immediate benefits of this H-DCES are the reduction of storage capacity and a prolonged lifetime of the battery. Both the operating principle and the mathematical model of the proposed H-DCES are analyzed in this paper. A prototype of the H-DCES is practically tested in a 48-V dc grid. The experimental results show that the H-DCES can realize the decoupled operation of dc voltage regulation and harmonic cancellation. Simulation studies further demonstrate that the H-DCES requires less storage capacity than its counterparts
Smart Loads for Improving the Fault-Ride-Through Capability of Fixed-Speed Wind Generators in Microgrids
In this paper, the smart load formed by the back-to-back electric springs (ES-B2B) is evaluated for improving the fault-ride through (FRT) capability of the wind turbine generation system (WTGS) with fixed speed induction generator (FSIG) for the first time. The characteristic of the ES-B2B in providing fast reactive power compensation is found to be highly useful in recovering the rotor speed of FSIGs when a fault event occurs. This is a new function in addition to the original function of stabilizing mains voltage against renewable generations. A simple and yet effective controller is then developed for the ES-B2B in order to ensure fast response. The ES-B2B based smart load and the proposed control have been tested in Matlab/Simulink and Real-Time Digital Simulator (RTDS) for the evaluation of i) the reactive power compensation capability of ES-B2B, ii) the effectiveness of the proposed control of ES-B2B for FRT support, and iii) a comparison of distributed ES-B2Bs with centralized STATCOM in providing distributed FRT support in different grid topologies
Treatment of insomnia in myasthenia gravis-A prospective study on non-benzodiazepine hypnotics in the treatment of myasthenia gravis patients with insomnia
Objectives: This study aimed to evaluate the efficacy and safety of non-benzodiazepine hypnotics in the treatment of myasthenia gravis (MG) patients with insomnia.
Methods: This is a prospective longitudinal study. Outpatients who met the criteria for stable MG and insomnia diagnosis according to the International Classification of Sleep Disorders (third edition) were included in the study. They took a regular dose of non-benzodiazepine hypnotics (zolpidem 10 mg per night or zopiclone 7.5 mg per night) based on their own preferences. Patients received psychotherapy (including sleep health education) and were followed up for 4–5 weeks. Cases with lung diseases, respiratory disorders, or inappropriate use of hypnotic medications were excluded. The primary outcome is the difference in total Pittsburgh Sleep Quality Index (PSQI) score between baseline and the end of follow-up period. Secondary outcomes include the difference in Myasthenia Gravis Activities of Daily Living (MG-ADL) score, 7-item Generalized Anxiety Disorder Questionnaire (GAD-7), and the Patient Health Questionnaire-9 (PHQ-9) between baseline and the end of follow-up period and the safety of medication.
Results: A total of 75 MG patients with insomnia were included in this study. After 4–5 weeks of treatment, the total PSQI score and MG-ADL score were lower than baseline (p < 0.01). No patients had an increased MG-ADL score. The incidence rate of adverse events was 16.0% (12 cases), including dizziness (6 cases, 8.0%), drowsiness (3 cases, 4.0%), fatigue (2 cases, 2.7%), and nausea (1 case, 1.3%), all of which were mild. No patients had new onset breathing disorders.
Conclusion: Non-benzodiazepine hypnotics are safe and effective for stable MG patients who need insomnia treatment
Effect of grass pollen immunotherapy on clinical and local immune response to nasal allergen challenge
Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics
In [1], we have explored the theoretical aspects of feature selection and evolutionary algorithms. In this chapter, we focus on optimization algorithms for enhancing data analytic process, i.e., we propose to explore applications of nature-inspired algorithms in data science. Feature selection optimization is a hybrid approach leveraging feature selection techniques and evolutionary algorithms process to optimize the selected features. Prior works solve this problem iteratively to converge to an optimal feature subset. Feature selection optimization is a non-specific domain approach. Data scientists mainly attempt to find an advanced way to analyze data n with high computational efficiency and low time complexity, leading to efficient data analytics. Thus, by increasing generated/measured/sensed data from various sources, analysis, manipulation and illustration of data grow exponentially. Due to the large scale data sets, Curse of dimensionality (CoD) is one of the NP-hard problems in data science. Hence, several efforts have been focused on leveraging evolutionary algorithms (EAs) to address the complex issues in large scale data analytics problems. Dimension reduction, together with EAs, lends itself to solve CoD and solve complex problems, in terms of time complexity, efficiently. In this chapter, we first provide a brief overview of previous studies that focused on solving CoD using feature extraction optimization process. We then discuss practical examples of research studies are successfully tackled some application domains, such as image processing, sentiment analysis, network traffics / anomalies analysis, credit score analysis and other benchmark functions/data sets analysis
Gas capture processes
Copyright © 2020 by the authors. The increasing trends in gas emissions have had direct adverse impacts on human health and ecological habitats in the world. A variety of technologies have been deployed to mitigate the release of such gases, including CO2, CO, SO2, H2S, NOx and H2. This special issue on gas-capture processes collects 25 review and research papers on the applications of novel techniques, processes, and theories in gas capture and removal
Performance deficits of NK1 receptor knockout mice in the 5 choice serial reaction time task: effects of d Amphetamine, stress and time of day.
Background
The neurochemical status and hyperactivity of mice lacking functional substance P-preferring NK1 receptors (NK1R-/-) resemble abnormalities in Attention Deficit Hyperactivity Disorder (ADHD). Here we tested whether NK1R-/- mice express other core features of ADHD (impulsivity and inattentiveness) and, if so, whether they are diminished by d-amphetamine, as in ADHD. Prompted by evidence that circadian rhythms are disrupted in ADHD, we also compared the performance of mice that were trained and tested in the morning or afternoon.
Methods and Results
The 5-Choice Serial Reaction-Time Task (5-CSRTT) was used to evaluate the cognitive performance of NK1R-/- mice and their wildtypes. After training, animals were tested using a long (LITI) and a variable (VITI) inter-trial interval: these tests were carried out with, and without, d-amphetamine pretreatment (0.3 or 1 mg/kg i.p.). NK1R-/- mice expressed greater omissions (inattentiveness), perseveration and premature responses (impulsivity) in the 5-CSRTT. In NK1R-/- mice, perseveration in the LITI was increased by injection-stress but reduced by d-amphetamine. Omissions by NK1R-/- mice in the VITI were unaffected by d-amphetamine, but premature responses were exacerbated by this psychostimulant. Omissions in the VITI were higher, overall, in the morning than the afternoon but, in the LITI, premature responses of NK1R-/- mice were higher in the afternoon than the morning.
Conclusion
In addition to locomotor hyperactivity, NK1R-/- mice express inattentiveness, perseveration and impulsivity in the 5-CSRTT, thereby matching core criteria for a model of ADHD. Because d-amphetamine reduced perseveration in NK1R-/- mice, this action does not require functional NK1R. However, the lack of any improvement of omissions and premature responses in NK1R-/- mice given d-amphetamine suggests that beneficial effects of this psychostimulant in other rodent models, and ADHD patients, need functional NK1R. Finally, our results reveal experimental variables (stimulus parameters, stress and time of day) that could influence translational studies
A large geometric distortion in the first photointermediate of rhodopsin, determined by double-quantum solid-state NMR
Double-quantum magic-angle-spinning NMR experiments were performed on 11,12-C-13(2)-retinylidene-rhodopsin under illumination at low temperature, in order to characterize torsional angle changes at the C11-C12 photoisomerization site. The sample was illuminated in the NMR rotor at low temperature (similar to 120 K) in order to trap the primary photointermediate, bathorhodopsin. The NMR data are consistent with a strong torsional twist of the HCCH moiety at the isomerization site. Although the HCCH torsional twist was determined to be at least 40A degrees, it was not possible to quantify it more closely. The presence of a strong twist is in agreement with previous Raman observations. The energetic implications of this geometric distortion are discussed
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