Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of cold-induced antioxidant activity on frost resistance in androgenic Festulolium genotypes

The aim of the study was: (i) to state if selected in the field conditions androgenic Festulolium genotypes are diverse in frost tolerance, and (ii) to investigate if changes in anitoxidant activity could be recognized as a physiological marker of this type tolerance. Antioxidative system induced by prehardening (12°C) and hardening (2°C) temperatures was investigated in 6 androgenic genotypes generated from a Festuca pratensis × Lolium multiflorum (2n = 4x = 28) amphidiploid hybrid (four genotypes derived from the F 1 hybrids, and two genotypes derived from the Festulolium cultivar ‘Rakopan’). The electrolyte leakage, frost resistance expressed as the values of temperature causes 50% damages (LT 50 ), the activities of superoxide dismutase (SOD), catalase (CAT), non-specific peroxidase (PX) and ascorbate peroxidase (APX) were measured. The results obtained indicated weak diversity of frost tolerance among studied androgenic genotypes. Only the one genotype was chosen as the most resistant to frost, while the other genotypes demonstrated no significant differences in values of LT 50 coefficient recorded after hardening. Prehardening temperature of 12°C caused an increase in cell membrane permeability in all genotypes studied. After hardening ion leakage from cells declined up to the control level. Generally, cold activated SOD, PX and APX in leaves of the genotypes studied, and inhibited strongly CAT activity. The most frost tolerant genotype was characterized by high PX activity after hardening process. Abbreviations: APX – ascorbate peroxidase, CAT – catalase, EDTA – ethylenediaminetatraacetic acid, LT 50 – letal temperature causing 50% membrane cell damages, NBT – nitroblue tetrazolium, PPFD – photosynthetic photon flux density [μmol m -2 s -1 ], PX – non-specific peroxidase, RH – relative humidity, ROS – reactive oxygen species, SE – standard error, SOD – superoxide dismutase
Extreme Learning Machine for SOC Estimation of Lithium-ion battery Using Gravitational Search Algorithm

This paper develops a state of charge (SOC) estimation model for a lithium-ion battery using an improved extreme learning machine (ELM) algorithm. ELM is suitable for SOC estimation since ELM algorithm has fast estimation speed, good generalization performance, and high accuracy. However, the performance of ELM is highly dependent on training accuracy and number of neurons in a hidden layer. Hence, gravitational search algorithm (GSA) is applied to improve the ELM computational intelligence by searching for the optimal value hidden layer neurons. The optimal ELM based GSA model does not require internal battery knowledge and mathematical model for SOC estimation. The model robustness is validated at different temperatures using different EV drive cycles. The performance of ELM-GSA model is verified with two popular neural network methods; back-propagation neural network (BPNN) and radial basis function neural network (RBFNN). The results are evaluated using different error rates and computation cost. The results demonstrate that the ELM-GSA model offers high accuracy and low SOC error rate than BPNN-GSA and RBFNN-GSA models. Furthermore, a detailed comparative study between the proposed model and existing SOC strategies is conducted which also demonstrates the superiority of the proposed model.
School of Hospitality Management and Tourism 2006-0101 Process Modeling for Simulation

This paper discusses shortfalls in relation to the requirements gathering phases of simulation. While many developments have taken place around supporting the model coding task of simulation, there are few tools available to assist in the requirements gathering phase. This is surprising as it has been reported by several researchers that the requirements phase can absorb twice as much resources as the coding phase. There are numerous process modeling tools available (over 100) that can and have been used to support the requirements phase of simulation. This paper provides a selective review of some of the most important in relation to simulation. A conclusion from this review is that none of the tools available adequately supports the requirements gathering phase of simulation. It is proposed that a process modeling tool be developed specifically to support simulation requirements gathering. The design objectives in the development of the tool are: (1) It should be capable of capturing a detailed description of a Discrete Event System; (2) It should have a low modeling burden and therefore be capable of being used by non specialists; (3) It should present modeling information at a high semantic level so that manufacturing personnel can rationalize with it; (4) It should have good visualization capabilities; (5) It should support project teamwork. Based on these design objectives a proposed simulation process modeling tool called Simulation Activity Diagrams (SAD) is presented.
Scalable Monocular SLAM by Fusing and Connecting Line Segments with Inverse Depth Filter

In this paper we propose a fast and robust line-based approach to monocular SLAM. It relies on a novel inverse depth representation of lines capable of tracking line segments in long image consequences. Tracked lines through frames provide crucial directional and positional knowledge for boosting localization performance, and they are more informative in charactering environments than points especially for urban outdoor and indoor scenes. The developed two-parameter inverse depth representation of lines is applicable for Kalman filter to achieve an efficient solver due to its linearity, which has lower computational cost compared to binary descriptors. This filter is also harmonious with inverse depth filter of points, both of which are incorporated under a unified minimization framework to enhance the performance of monocular SLAM. Real world monocular sequences have demonstrated that the proposed SLAM system outperforms the state-of-the-art and produces accurate results in both indoor and outdoor scenes.
Resonance phenomena at the long wave run-up on the coast

Run-up of long waves on a beach consisting of three pieces of constant but different slopes is studied. Linear shallow-water theory is used for incoming impulse evolution, and nonlinear corrections are obtained for the run-up stage. It is demonstrated that bottom profile influences the run-up characteristics and can lead to resonance effects: increase of wave height, particle velocity, and number of oscillations. Simple parameterization of tsunami source through an earthquake magnitude is used to calculate the run-up height versus earthquake magnitude. It is shown that resonance effects lead to the sufficient increase of run-up heights for the weakest earthquakes, and a tsunami wave does not break on chosen bottom relief if the earthquake magnitude does not exceed 7.8.
Causation analysis between stock price and exchange rate: Pre and post crisis study on Malaysia

The furore and chaos created by the Asian financial crisis have ignited many studies on numerous subjects, and it is believed that the crisis has changed the way nations being administered and policies formed and implemented especially those regarding monetary and fiscal policies. Johansen (1991) cointegration method was used and the period was divided into two sub periods, albeit pre crisis and post crisis. The results obtained are similar with a number of past literatures pointing to no long run relationship between stock price and exchange rate for both periods.
Title Mindfulness-Based Childbirth and Parenting Education : Promoting Family Mindfulness During the Perinatal Period Permalink

We present the conceptual and empirical foundation and curriculum content of the Mindfulness-Based Childbirth and Parenting (MBCP) program and the results of a pilot study of n = 27 pregnant women participating in MBCP during their third trimester of pregnancy. MBCP is a formal adaptation of the Mindfulness-Based Stress Reduction program and was developed and refined over the course of 11 years of clinical practice with 59 groups of expectant couples. MBCP is designed to promote family health and well-being through the practice of mindfulness during pregnancy, childbirth, and early parenting. Quantitative results from the current study include statistically significant increases in mindfulness and positive affect, and decreases in pregnancy anxiety, depression, and negative affect from preto post-test (p \ .05). Effect sizes for changes in key hypothesized intervention mediators were large (d [ .70), suggesting that MBCP is achieving its intended effects on maternal well-being during pregnancy. Qualitative reports from participants expand upon the quantitative findings, with the majority of participants reporting perceived benefits of using mindfulness practices during the perinatal period and early parenting. Our future research will involve conducting a randomized controlled trial of MBCP to test effects on psychophysiological stress mechanisms and to examine effects on birth outcomes, family relationship quality, and child development outcomes.
ANALYSIS OF HEAT PIPE OPERATING PARAMETERS BY RESPONSE SURFACE METHODOLOGY USING COPPER NANOFLUID AS WORKING FLUID

The performance of a heat pipe is analysed using Response Surface Methodology (RSM) with various input parameters namely heat input, angle of inclination, filling ratio, concentration of copper nanofluid and flow rate of coolant in the condenser over the output response i.e. the thermal efficiency of the heat pipe. The experimental design is developed based on Box - Behnken design method. The influence of vital input parameters and interaction among them are investigated using analysis of variance (ANOVA). The proposed mathematical model in this study has proven to fit and in line with experimental values with a 95% confidence interval.
Missing Sample Estimation Based on High-Order Sparse Linear Prediction for Audio Signals

The restoration of click degraded audio signals is important to achieve acceptable audio quality in many old audio media. Restoration by missing sample estimation based on conventional linear prediction has been extensively researched and used; however, it is hampered by the limitations of the linear prediction model. Recently, it has been shown that high-order sparse linear prediction offers better representation of music and voiced speech over conventional linear prediction. In this paper, the use of high-order sparse linear prediction for missing sample estimation of click degraded audio signals is proposed. The paper also explores a possible computational time saving by combining the high- order sparse linear prediction coefficient determination and filtering operations. Evaluation with different types of speech and audio data show that the proposed method achieves an improvement in SNR over conventional linear prediction based filtering for all considered speech and audio data types.
ON THE FATE OF UNSTABLE CIRCUMBINARY PLANETS: TATOOINE’S CLOSE ENCOUNTERS WITH A DEATH STAR

Circumbinary planets whose orbits become unstable may be ejected, accreted, or even captured by one of the stars. We quantify the relative rates of these channels, for a binary of secondary star’s mass fraction 0.1 with an orbit of 1 AU. The most common outcome is ejection, which happens ∼80% of the time. If binary systems form circumbinary planets readily and sloppily, this process may fill the Milky Way with free-floating planets. A significant fraction of the time, ∼20%, the unstable planet strikes the primary or secondary. We tracked whether a Jupiter-like planet would undergo tidal stripping events during close passages, and find that these events are rarely strong enough to capture the planet, although this may be observable via free-floating planets that are heated or spun-up by this process.
Potential of Amazonian Isolates of Metarhizium to Control Immatures of Bactrocera carambolae (Diptera: Tephritidae)

Summary This study shows the potential of Amazonian isolates of Metarhizium Sorokin to control immatures of Bactrocera carambolae Drew & Hancock (Diptera: Tephritidae), a quarantine pest present in Brazil. Our results reveal the effectiveness of an isolate of Metarhizium anisopliae (Metsch.) Sorokin to control immatures of B. carambolae, suggesting the potential for direct application of this isolate onto the soil to reduce populations of the pest.
A Recommendation Technique Based on the Social Networks and Sequential Behaviors

Collaborative filtering is one of the most successful method for recommendation. But it also has disadvantages such as cold-start problems and data sparseness which influence the result of recommendation. The probability Matrix Factorization Technique is one of the method of model based CF and it always ignore the relationship of users. Sequential behaviors is often one of the most important factor which is easy to be ignored. In this paper, in order to solving the problems of collaborative filtering, we not only consider the effect on the user rating matrix but also take the social networks and time factor into account. Putting these important factors in the PMF model is an effective way for making recommendation.
Solution of fuzzy differential equations

Hybrid system is a dynamic system that exhibits both continuous and discrete dynamic behavior. The hybrid differential equations have a wide range of applications in science and engineering. The hybrid systems are devoted to modeling, design, and validation of interactive systems of computer programs and continuous systems. Hybrid fuzzy differential equations (HFDEs) is considered by Kim et al. [11]. In the present paper it is shown that the example presented by Kim et al. in the Case I is not very accurate and in the Case II, is incorrect. Namely, the exact solution proposed by the authors in the Case II are not solutions of the given HFDE. The correct exact solution is also presented here, together with some results for characterizing solutions of FDEs under Hukuhara differentiability by an equivalent system of ODEs. Then, the homotopy analysis method (HAM) is applied to obtained the series solution of the HFDEs. Finally, we illustrate our approach by a numerical example.
Two fast temperature sensors for probing of the atmospheric boundary layer using small remotely piloted aircraft (RPA)

Abstract. Two types of temperature sensors are designed and tested: a thermocouple and a fine wire resistance thermometer. The intention of this study is to figure out which kind of measurement principle is in general more suited for atmospheric boundary layer meteorology with small remotely piloted aircraft (RPA). The sensors are calibrated in a NIST traceable climate chamber and validated in flight against tower measurements, radiosondes and remote sensing. The sensors have a measurement range of at least −10–50 °C, an absolute RMS error of less than ±0.2 K which is stable over the lifetime of the sensors, and a resolution of about 0.01 K. Both devices are tested for typical errors like radiation error and adiabatic heating, as well as for their dynamic response. Spectral resolutions of up to approximately 10 Hz can be obtained with both sensors, which makes them suitable for turbulence measurement. Their low cost of less than 100 EUR in pure hardware is a major advantage for research with small RPA.
Condition Monitoring in a Power Module Using On-State Resistance and Case Temperature

Power electronics are widely used in energy conversion systems due to their high efficiency. Finding and replacing the defective power electronic modules timely by monitoring the ageing state of devices can greatly improve the security of power converters and reduce the loss caused by the device failure. Packaging-related fatigue has been identified as one of the main causes of the failures of power electronic modules. This paper proposes a method to monitor the fatigue inside a module by identifying the increase of internal on-state resistance under a certain operation conditions due to the device packaging-related fatigue. Multiple physical field model results show that the junction temperature increases with the thermal resistance, which causes an increase in the on-state resistance. Therefore, the healthy state of power modules can be diagnosed by comparing the difference of the on-state resistance before and after ageing in the same case temperature, which can be measured directly. Experiments and simulations are conducted to demonstrate the concept and verify the method.
Single Photon Extraction for FACT’s SiPMs allows for Novel IACT Event Representation

Imaging Atmospheric Cherenkov Telescopes provide large gamma-ray collection areas > 10^4 m^2 and successfully probe the high energetic gamma-ray sky by observing extensive air showers during the night. The First G-APD Cherenkov Telescope (FACT) explores silicon based photoelectric converters (called G-APDs or SiPMs) which provide more observation time with strong moonlight, a more stable photon gain over years of observations, and mechanically simpler imaging cameras. So far, the signal extraction methods used for FACT originate from sensors with no intrinsic quantized responses like photomultiplier tubes. This standard signal extraction is successfully used for the long time monitoring of the gamma-ray flux of bright blazars. However, we now challenge our classic signal extraction and explore single photon extraction methods to take advantage of the highly stable and quantized single photon responses of FACT's SiPM sensors. Instead of having one main pulse with one arrival time and one photon equivalent extracted for each pixel, we extract the arrival times of all individual photons in a pixel’s time line which opens up a new dimension in time for representing extensive air showers with an IACT. In this contribution, we will introduce our novel IACT event representation which is a list of single photon arrival times for each pixel (Photon-Stream). We will discuss our single photon extractor, its performance and its limitations. We will present example events where we identify individual, single air shower Cherenkov photons in the pool of individual, single night sky background photons.
Trip Travel Time Forecasting Based on Selective Forgetting Extreme Learning Machine

Travel time estimation on road networks is a valuable traffic metric. In this paper, we propose a machine learning based method for trip travel time estimation in road networks. The method uses the historical trip information extracted from taxis trace data as the training data. An optimized online sequential extreme machine, selective forgetting extreme learning machine, is adopted to make the prediction. Its selective forgetting learning ability enables the prediction algorithm to adapt to trip conditions changes well. Experimental results using real-life taxis trace data show that the forecasting model provides an effective and practical way for the travel time forecasting.
Modifying the ADM1 Model to Predict the Operation of an Anaerobic Digester Co-digesting Municipal Sludge with Bakery Waste

Anaerobic Digestion Model Number1 (ADM1) was modified in order to predict accurately the impact of co-digesting bakery waste (BW) with municipal sludge (MS). BW is an industrial waste (300,000 gallons per day in USA) that contains a high concentration of organic matter (carbohydrates, low lipids and non-detected proteins). BW is an easily biodegradable substrate for creating a favorable microorganism growth environment, which enhances the biogas production needed for wastewater facilities. The modified ADM1 successfully predicted changes in pH, volatile fatty acids (VFA), propionic acid and methane gas production. The ADM1 outputs were compared to experimental batch reactor results of actual BW addition percentages in order to validate the model. Stability of the digestion process was achieved until the ratio range of 37-40% BW: 60-63% MS, and the digestion processes were inhibited at higher ratios of BW. This research provides an alternative to BW management through utilizing the BW to enhance methane production.
Effects of warm sea–surface temperature anomalies on the blue petrel at the Kerguelen Islands

Several long–term studies on Southern Ocean seabirds and seals have suggested a possible link between major declines in breeding performance and El Niño Southern Oscillation events. We report that the breeding performances and body condition of the blue petrel (Halobaena carulea) on the Kerguelen Islands is depressed by episodic, warm sea–surface temperatures (SSTs) in the winter before breeding. Lagged cross correlations between SSTs in the Kerguelen sector and the Southern Oscillation Index indicate that warm SSTs were found south of Kerguelen Islands within a year of, and between 4.2 and 5.4 years after, an El Niño event took place. These results can be discussed with respect to the recently described Antarctic Circumpolar Wave that drives climatic anomalies eastward around the Southern Ocean.
On the time-frequency reassignment of interfering modes in multicomponent FM signals

The paper presents a first attempt to correct the time-frequency reassignment of a multicomponent signal having non separable individual components. In particular, the case of a 2-components signal has been investigated in depth. It has been proved that the integral (along frequencies) of the spectrogram is still a multicomponent signal with specific instantaneous frequencies. As a result, the spectrogram of this signal allows us to disentangle the frequencies and recover the missing information in the non separability region. Preliminary results show that the proposed method is able to correctly reassign the information in the interference region by separating the two individual components, with a very moderate computational effort.
Exploring ICT practices through Echo 360

This paper reports the findings from a pilot study that investigated the use, by two learning and teaching technologists, of Information and Communication Technology (ICT), an automated lecture-capture system (Echo 360), to support their daily practices. Data sources included computer activity records extracted from the participants’ computers at their work areas via the use of Echo 360. Data were analysed using an interpretive approach resulting in three themes: (a) the advantages and the strengths of using screen capture (or ‘screencasting’) as a method in research; (b) the notion of ‘multitasking’ in the process of ICT use; (c) the understanding of ‘human-computer’ interaction in today’s higher education. Through monitoring the navigation of the users’ actions within the computers’ interfaces in real time, the screen capture provided an accurate account of how participants used their computer technologies and what they were doing with them. The screen capture data revealed the sense of ‘digital literacy’ among the participants and the findings therefore provided insights into ideas about how to develop a more structural ICT support system for academic teaching staff. Such support would be beneficial to promote the use of ICT among academic teaching staff in the processes of teaching, learning and researching. The findings of this study, however, raised questions about the role played by technologies in advancing the research in higher education, and they highlighted a possible limitation in academic-orientated use of computer technologies by academic teaching staff. In short, this pilot study is framed by the question “How do the assumptions and expectations of technologies’ use held by academic teaching staff influence their daily practice, and vice versa? ” https://doi.org/10.26803/ijlter.17. 1.2