scholarly journals Developing a microbial consortium for removing nutrients in dishwasher wastewater: towards a biofilter for its up-cycling

2020 ◽  
Vol 82 (6) ◽  
pp. 1142-1154
Author(s):  
R. Congestri ◽  
S. Savio ◽  
S. Farrotti ◽  
A. Amati ◽  
K. Krasojevic ◽  
...  
Keyword(s):  
Integrated System ◽  
Water Remediation ◽  
Microbial Consortia ◽  
Filamentous Cyanobacterium ◽  
Heterotrophic Microbes ◽  
Domestic Cycle ◽  
Oxygen Evolving ◽  
Short Time ◽  
Better Than ◽  
Trichormus Variabilis

Abstract Microbial consortia are effective biofilters to treat wastewaters, allowing for resource recovery and water remediation. To reuse and save water in the domestic cycle, we assembled a suspended biofilm, a ‘biofilter’ to treat dishwasher wastewater. Bacterial monocultures of both photo- and heterotrophs were assembled in an increasingly complex fashion to test their nutrient stripping capacity. This ‘biofilter’ is the core of an integrated system (Zero Mile System) devoted to reusing and upcycling of reconditioned wastewater, partly in subsequent dishwasher cycles and partly into a vertical garden for plant food cultivation. The biofilter was assembled based on a strain of the photosynthetic, filamentous cyanobacterium Trichormus variabilis, selected to produce an oxygen evolving scaffold, and three heterotrophic aerobic bacterial isolates coming from the dishwasher wastewater itself: Acinetobacter, Exiguobacterium and Pseudomonas spp. The consortium was constructed starting with 16 isolates tested one-to-one with T. variabilis and then selecting the heterotrophic microbes up to a final one-to-three consortium, which included two dominant and a rare component of the wastewater community. This consortium thrives in the wastewater much better than T. variabilis alone, efficiently stripping N and P in short time, a pivotal step for the reuse and saving of water in household appliances.

scholarly journals Contactless Video-Based Heart Rate Monitoring of a Resting and an Anesthetized Pig

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 442
Author(s):  
Meiqing Wang ◽  
Ali Youssef ◽  
Mona Larsen ◽  
Jean-Loup Rault ◽  
Daniel Berckmans ◽  
...  
Keyword(s):  
Heart Rate ◽  
Estimation Error ◽  
Well Being ◽  
Absolute Error ◽  
Mean Value ◽  
Video Data ◽  
Window Functions ◽  
The Face ◽  
Short Time ◽  
Better Than

Heart rate (HR) is a vital bio-signal that is relatively easy to monitor with contact sensors and is related to a living organism’s state of health, stress and well-being. The objective of this study was to develop an algorithm to extract HR (in beats per minute) of an anesthetized and a resting pig from raw video data as a first step towards continuous monitoring of health and welfare of pigs. Data were obtained from two experiments, wherein the pigs were video recorded whilst wearing an electrocardiography (ECG) monitoring system as gold standard (GS). In order to develop the algorithm, this study used a bandpass filter to remove noise. Then, a short-time Fourier transform (STFT) method was tested by evaluating different window sizes and window functions to accurately identify the HR. The resulting algorithm was first tested on videos of an anesthetized pig that maintained a relatively constant HR. The GS HR measurements for the anesthetized pig had a mean value of 71.76 bpm and standard deviation (SD) of 3.57 bpm. The developed algorithm had 2.33 bpm in mean absolute error (MAE), 3.09 bpm in root mean square error (RMSE) and 67% in HR estimation error below 3.5 bpm (PE3.5). The sensitivity of the algorithm was then tested on the video of a non-anaesthetized resting pig, as an animal in this state has more fluctuations in HR than an anaesthetized pig, while motion artefacts are still minimized due to resting. The GS HR measurements for the resting pig had a mean value of 161.43 bpm and SD of 10.11 bpm. The video-extracted HR showed a performance of 4.69 bpm in MAE, 6.43 bpm in RMSE and 57% in PE3.5. The results showed that HR monitoring using only the green channel of the video signal was better than using three color channels, which reduces computing complexity. By comparing different regions of interest (ROI), the region around the abdomen was found physiologically better than the face and front leg parts. In summary, the developed algorithm based on video data has potential to be used for contactless HR measurement and may be applied on resting pigs for real-time monitoring of their health and welfare status, which is of significant interest for veterinarians and farmers.

scholarly journals Rhinovirus prevalence as indicator for efficacy of measures against SARS-CoV-2

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Simo Kitanovski ◽  
Gibran Horemheb-Rubio ◽  
Ortwin Adams ◽  
Barbara Gärtner ◽  
Thomas Lengauer ◽  
...  
Keyword(s):  
Respiratory Viruses ◽  
Emerging Viruses ◽  
Prevalence Data ◽  
Incidence Data ◽  
Bayes Inference ◽  
Current Prevalence ◽  
Highest Density Interval ◽  
Short Time ◽  
Short Time Delay ◽  
Better Than

Abstract Background Non-pharmaceutical measures to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) should be carefully tuned as they can impose a heavy social and economic burden. To quantify and possibly tune the efficacy of these anti-SARS-CoV-2 measures, we have devised indicators based on the abundant historic and current prevalence data from other respiratory viruses. Methods We obtained incidence data of 17 respiratory viruses from hospitalized patients and outpatients collected by 37 clinics and laboratories between 2010-2020 in Germany. With a probabilistic model for Bayes inference we quantified prevalence changes of the different viruses between months in the pre-pandemic period 2010-2019 and the corresponding months in 2020, the year of the pandemic with noninvasive measures of various degrees of stringency. Results We discovered remarkable reductions δ in rhinovirus (RV) prevalence by about 25% (95% highest density interval (HDI) [−0.35,−0.15]) in the months after the measures against SARS-CoV-2 were introduced in Germany. In the months after the measures began to ease, RV prevalence increased to low pre-pandemic levels, e.g. in August 2020 δ=−0.14 (95% HDI [−0.28,0.12]). Conclusions RV prevalence is negatively correlated with the stringency of anti-SARS-CoV-2 measures with only a short time delay. This result suggests that RV prevalence could possibly be an indicator for the efficiency for these measures. As RV is ubiquitous at higher prevalence than SARS-CoV-2 or other emerging respiratory viruses, it could reflect the efficacy of noninvasive measures better than such emerging viruses themselves with their unevenly spreading clusters.

Compound Finish Processes Using Burnishing and Ultrasonic Electrochemical Finishing on Hole-Wall Surface

2008 ◽  
Vol 53-54 ◽  
pp. 3-8
Author(s):  
Pai Shan Pa
Keyword(s):  
Wall Surface ◽  
Machining Time ◽  
High Rotational Speed ◽  
Hole Wall ◽  
Finishing Processes ◽  
Pulsed Direct Current ◽  
Short Time ◽  
Electrochemical Finishing ◽  
Off Time ◽  
Better Than

This study using ultrasonic energy transmitted into the electrolyte to assist in discharging of electrolytic product out of the machining gap in the compound finishing processes of electrochemical finishing and burnishing on hole-wall surface beyond traditional process of holes machining instead of conventional hand or machine polishing. The design finish-tool includes a burnishing-tool and an electrode as a hole-wall surface finish improvement that goes beyond traditional rough boring. In the experiment, the finish-tool travels across the hole-wall surface with continuous or pulsed direct current. The experimental results show that the large supply of current rating is effectively to reach the amount of the material removal and is advantageous to the finishing processes. The average effect of the ultrasonic is more better than the pulsed current while the machining time needs not to be prolonged by the off-time. The finish effect is better with a high rotational speed of the finish-tool because the dregs discharge of electrochemical finishing becomes easier and is also advantageous to the finish. The compound processes of burnishing and ultrasonic electrochemical finishing just require a short time to make the hole-wall surface smooth and bright.

Temperature Dependence of the O2-Oscillation Pattern in the Filamentous Cyanobacterium Oscillatoria chalybea and in Chlorella kessleri

1996 ◽  
Vol 51 (11-12) ◽  
pp. 823-832 ◽  
Author(s):  
K Burda ◽  
P He ◽  
K. P Bader ◽  
G. H Schmid
Keyword(s):  
Transition Temperature ◽  
Temperature Dependence ◽  
Oxygen Evolution ◽  
Filamentous Cyanobacterium ◽  
State Distribution ◽  
Oscillation Pattern ◽  
Chlorella Kessleri ◽  
Temperature Range ◽  
Oscillatoria Chalybea ◽  
Oxygen Evolving

Abstract Five characteristic discontinuities of the pattern of oxygen evolution have been detected for the filamentous cyanobacterium Oscillatoria chalybea in the temperature range of 0°C to 30°C. The temperatures at which these discontinuities occur are: ≈ 5°C, ≈ 11°C, ≈ 15°C, ≈ 21°C and ≈ 25°C. The calculated initial 5-S state distribution, the miss parameter and the fraction of the fast transition S3 → S0+ O2 are affected. The discontinuities are observed at the same transition temperature also for Chlorella kessleri hence are not specific for the cyanobacterium. Based on these studies it is concluded that the not vanishing oxygen signal under the first flash of a flash train in Oscillatoria cannot have its origin in interactions between oxygen-evolving complexes. A decrease of temperature should slow down the expected charge exchanges, improve the oscillations, thus reduce or lower the first two oxygen amplitudes of the oscillatoria pattern. Lowering of the temperautres improves the oscillations but does not lower the first O2 signal of the pattern.

The Applicated Comparation of Three Signal Analytical Methods for Ocean CSEM Signature

2013 ◽  
Vol 798-799 ◽  
pp. 561-564
Author(s):  
Ji Yu Zhou ◽  
Feng Dao Zhou
Keyword(s):  
Frequency Analysis ◽  
Oil And Gas ◽  
Time Frequency Analysis ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Analysis Technique ◽  
Oil And Gas Resources ◽  
Concentration Degree ◽  
Short Time ◽  
Better Than

Sea is rich in oil and gas resources, the marine controlled source electromagnetic method (CSEM) is a kind of method seabed oil gas geophysical technology rising in recent years. Because of the problem of CSEM about the air wave in the shallow water, the research of time-frequnecy analysis technique is used to suppress the air wave in this paper. The basic idea is: because of the CSEM signals speed are different in the air and submarine, so the time which received by the receiving points are also different through these two kinds of ways. Using the time-frequency analysis technique and theoretical calculation, we can determine which part of the signal is spread over the ocean, so as to suppress the air wave effectively. This paper lists several methods of time-frequency analysis, such as Short-time Fourier transform, W-V distribution, Wavelet transform, Hilbert Huang transform. Through the time-frequency graph,we get the conclusion that HHT is better than others in concentration degree,and W-V distribution is better than STFT.Compared with the original signal, the time-frequency graph is the best in using Smooth Puseudo W-V Distribution.I have a detailed analysis about real case in using SPWVD at last.

scholarly journals Optimization of a 12.5 GHz Microstrip Antenna Array Using Taguchi's Method

2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
M. Spasos ◽  
R. Nilavalan ◽  
K. Tsiakmakis ◽  
N. Charalampidis ◽  
S. W. Cheung
Keyword(s):  
Antenna Array ◽  
Microstrip Antenna ◽  
Optimization Methods ◽  
Optimization Method ◽  
Consumer Electronics ◽  
Chemical Production ◽  
Simulation Tools ◽  
Microstrip Antenna Array ◽  
Short Time ◽  
Better Than

This paper presents Taguchi's optimization method implemented in the design of a single feed (without any matching network) microstrip antenna array operating around 12.5 GHz. The proposed optimization method is statistical and is widely used for quality assurance in many fields such as mechanical and chemical production, consumer electronics, services; however it has been underused in the field of electromagnetics. It allows optimization of multiparameter, multitarget complex designs in a very short time in conjunction with advanced simulation tools. The proposed antenna has been fully evaluated under Taghuchi's and PSO's optimization methods, and the experimental results show total Gain of 15 dB, and good matching withS11 better than 20 dB, in the frequency range 12.3 to 12.8 GHz.

scholarly journals A Simple and Efficient Technique to Generate Bounded Solutions for the Multidimensional Knapsack Problem: a Guide for OR Practitioners

2021 ◽  
Vol 15 ◽  
pp. 1650-1656
Author(s):  
Yun Lu ◽  
Bryan McNally ◽  
Emre Shively-Ertas ◽  
Francis J. Vasko
Keyword(s):  
Knapsack Problem ◽  
General Purpose ◽  
Test Problems ◽  
Bounded Solutions ◽  
Multidimensional Knapsack Problem ◽  
Multidimensional Knapsack ◽  
Np Hard Problem ◽  
Programming Software ◽  
Short Time ◽  
Better Than

The 0-1 Multidimensional Knapsack Problem (MKP) is a NP-Hard problem that has important applications in business and industry. Approximate solution approaches for the MKP in the literature typically provide no guarantee on how close generated solutions are to the optimum. This article demonstrates how general-purpose integer programming software (Gurobi) is iteratively used to generate solutions for the 270 MKP test problems in Beasley’s OR-Library such that, on average, the solutions are guaranteed to be within 0.094% of the optimums and execute in 88 seconds on a standard PC. This methodology, called the simple sequential increasing tolerance (SSIT) matheuristic, uses a sequence of increasing tolerances in Gurobi to generate a solution that is guaranteed to be close to the optimum in a short time. This solution strategy generates bounded solutions in a timely manner without requiring the coding of a problem-specific algorithm. The SSIT results (although guaranteed within 0.094% of the optimums) when compared to known optimums deviated only 0.006% from the optimums—far better than any published results for these 270 MKP test instances.

scholarly journals Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation

2020 ◽  
Vol 12 (10) ◽  
pp. 1685 ◽  
Author(s):  
Amin Ullah ◽  
Syed Muhammad Anwar ◽  
Muhammad Bilal ◽  
Raja Majid Mehmood
Keyword(s):  
Premature Ventricular Contraction ◽  
Careful Study ◽  
Spectral Image ◽  
Bundle Branch Block ◽  
Ecg Signals ◽  
The One ◽  
Short Time ◽  
Electrocardiogram Ecg ◽  
Better Than

The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture the heart’s rhythmic irregularities, commonly known as arrhythmias. A careful study of ECG signals is crucial for precise diagnoses of patients’ acute and chronic heart conditions. In this study, we propose a two-dimensional (2-D) convolutional neural network (CNN) model for the classification of ECG signals into eight classes; namely, normal beat, premature ventricular contraction beat, paced beat, right bundle branch block beat, left bundle branch block beat, atrial premature contraction beat, ventricular flutter wave beat, and ventricular escape beat. The one-dimensional ECG time series signals are transformed into 2-D spectrograms through short-time Fourier transform. The 2-D CNN model consisting of four convolutional layers and four pooling layers is designed for extracting robust features from the input spectrograms. Our proposed methodology is evaluated on a publicly available MIT-BIH arrhythmia dataset. We achieved a state-of-the-art average classification accuracy of 99.11%, which is better than those of recently reported results in classifying similar types of arrhythmias. The performance is significant in other indices as well, including sensitivity and specificity, which indicates the success of the proposed method.

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