Search results for: weather variability

Authors: Gabriel Cucato, Marilia Correia, Wagner Domingues, Aline Palmeira, Paulo Longano, Nelson Wolosker, Raphael Ritti-Dias

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Women with peripheral arterial disease (PAD) present lower walking capacity in comparison with men. However, whether cardiovascular regulation is also different between genders is unknown. Thus, the aim of this study was to compare walking capacity and cardiovascular regulation between men and women with PAD. A total of 23 women (66±7 yrs) and 31 men (64±9 yrs) were recruited. Patients performed a 6-minute test and the onset claudication distance and total walking distance were measured. Additionally, cardiovascular regulation was assessed by arterial stiffness (pulse wave velocity and augmentation index) and heart rate variability (frequency domain). Independent T test or Mann-Whitney U test were performed. In comparison with men, women present lower onset claudication distance (108±66m vs. 143±50m; P=0.032) and total walking distance (286±83m vs. 361±91 m, P=0.007). Regarding cardiovascular regulation, there were no differences in heart rate variability SDNN (72±160ms vs. 32±22ms, P=0.587); RMSSD (75±209 vs. 25±22ms, P=0.726); pNN50 (11±17ms vs. 8±14ms, P=0.836) in women and men, respectively. Moreover, there were no difference in augmentation index (39±10% vs. 34±11%, P=0.103); pulse pressure (59±17mmHg vs. 56±19mmHg, P=0.593) and pulse wave velocity (8.6±2.6m\s vs. 9.0±2.7m/s, P=0.580). In conclusion, women have impaired walking capacity compared to men. However, sex differences were not observed on cardiovascular regulation in patients with PAD.

Keywords: exercise, intermittent claudication, cardiovascular load, arterial stiffness

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Authors: Nishal Parbhoo, John B. Dewar, Samantha Gildenhuys

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Rotavirus is the major cause of severe gastroenteritis worldwide in children aged 5 and younger. Death rates are high particularly in developing countries. The mature rotavirus is a non-enveloped triple-layered nucleocapsid containing 11 double-stranded RNA segments. Here a global view on the sequence and structure of the three main capsid proteins, VP7, VP6, and VP2 is taken by generating a consensus sequence for each of these rotavirus proteins, for each species obtained from published data of representative rotavirus genotypes from across the world and across species. The degree of conservation between species was represented on homology models for each of the proteins. VP7 shows the highest level of variation with 14 - 45 amino acids showing conservation of less than 60%. These changes are localized to the outer surface which is exposed to antibodies alluding to a possible mechanism in evading the immune system. The middle layer, VP6 shows lower variability with only 14-32 sites having lower than 70% conservation. The inner structural layer made up of VP2 showed the lowest variability with only 1-16 sites having less than 70% conservation across species. The results correlate with proteins’ multiple structural roles. Although the nucleotide sequences vary due to an error-prone replication and lack of proofreading, the corresponding amino acid sequence of VP2, 6 and 7 remains conserved. Sequence conservation maintained for the virus results in stable protein structures, fit for function. This can be exploited in drug design, molecular studies and biotechnological applications.

Keywords: amino acid sequence conservation, capsid protein, protein structure, vaccine candidate

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

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Authors: Krešimir Begović, Miloš Rydval, Jan Tumajer, Kristyna Svobodová, Thomas Langbehn, Yumei Jiang, Vojtech Čada, Vaclav Treml, Ryszard Kaczka, Miroslav Svoboda

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Environmental changes have increased the frequency and intensity of climatic extremes, particularly hotter droughts, leading to altered tree growth patterns and multi-year lags in tree recovery. The effects of shifting climatic conditions on tree growth are inhomogeneous across species’ natural distribution ranges, with large spatial heterogeneity and inter-population variability, but generally have significant consequences for contemporary forest dynamics and future ecosystem functioning. Despite numerous studies on the impacts of regional drought effects, large uncertainties remain regarding the mechanistic basis of drought legacy effects on wood formation and the ability of individual species to cope with increasingly drier growing conditions and rising year-to-year climatic variability. To unravel the complexity of climate-growth interactions and assess species-specific responses to severe droughts, we combined forward modeling of tree growth (VS-lite model) with correlation analyses against climate (temperature, precipitation, and the SPEI-3 moisture index) and growth responses to extreme drought events from multiple tree-ring parameters (tree-width and blue intensity parameters). We used an extensive dataset with over 1000 tree-ring samples from 23 nature forest reserves across an altitudinal range in Czechia and Slovakia. Our results revealed substantial spatiotemporal variability in growth responses to summer season temperature and moisture availability across species and tree-ring parameters. However, a general trend of increasing spring moisture-growth sensitivity in recent decades was observed in the Scots pine mountain forests and lowland forests of both species. The VS-lite model effectively captured nonstationary climate-growth relationships and accurately estimated high-frequency growth variability, indicating a significant incidence of regional drought events and growth reductions. Notably, growth reductions during extreme drought years and discrete legacy effects identified in individual wood components were most pronounced in the lowland forests. Together with the observed growth declines in recent decades, these findings suggest an increasing vulnerability of Norway spruce and Scots pine in dry lowlands under intensifying climatic constraints.

Keywords: dendroclimatology, Vaganova–Shashkin lite, conifers, central Europe, drought, blue intensity

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Authors: Stephane Laussac, Jacques Piazzola, Gilles Tedeschi

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Estimation of the impact of atmospheric aerosols on the climate evolution is an important scientific challenge. One of a major source of particles is constituted by the oceans through the generation of sea-spray aerosols. In coastal areas, marine aerosols can affect air quality through their ability to interact chemically and physically with other aerosol species and gases. The integration of accurate sea-spray emission terms in modeling studies is then required. However, it was found that sea-spray concentrations are not represented with the necessary accuracy in some situations, more particularly at short fetch. In this study, the WRF-Chem model was implemented on a North-Western Mediterranean coastal region. WRF-Chem is the Weather Research and Forecasting (WRF) model online-coupled with chemistry for investigation of regional-scale air quality which simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. One of the objectives was to test the ability of the WRF-Chem model to represent the fine details of the coastal geography to provide accurate predictions of sea spray evolution for different fetches and the anthropogenic aerosols. To assess the performance of the model, a comparison between the model predictions using a local emission inventory and the physicochemical analysis of aerosol concentrations measured for different wind direction on the island of Porquerolles located 10 km south of the French Riviera is proposed.

Keywords: sea-spray aerosols, coastal areas, sea-spray concentrations, short fetch, WRF-Chem model

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Authors: Aleš Florian, Lenka Ševelová

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Complex sensitivity analysis of stresses in a concrete slab of the real type of rigid pavement made from recycled materials is performed. The computational model of the pavement is designed as a spatial (3D) model, is based on a nonlinear variant of the finite element method that respects the structural nonlinearity, enables to model different arrangements of joints, and the entire model can be loaded by the thermal load. Interaction of adjacent slabs in joints and contact of the slab and the subsequent layer are modeled with the help of special contact elements. Four concrete slabs separated by transverse and longitudinal joints and the additional structural layers and soil to the depth of about 3m are modeled. The thickness of individual layers, physical and mechanical properties of materials, characteristics of joints, and the temperature of the upper and lower surface of slabs are supposed to be random variables. The modern simulation technique Updated Latin Hypercube Sampling with 20 simulations is used. For sensitivity analysis the sensitivity coefficient based on the Spearman rank correlation coefficient is utilized. As a result, the estimates of influence of random variability of individual input variables on the random variability of principal stresses s1 and s3 in 53 points on the upper and lower surface of the concrete slabs are obtained.

Keywords: concrete, FEM, pavement, sensitivity, simulation

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva

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The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.

Keywords: analog ensemble, electricity market, PV forecast, solar energy

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Authors: Yori Gidron, Maartje Mol, Norbert Foudraine, Frits Van Osch, Joop Van Den Bergh, Moshe Farchi, Maud Straus

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Background: The worldwide pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-COV2), which began in 2019, also known as Covid-19, has infected over 136 million people and tragically took the lives of over 2.9 million people worldwide. Many of the complications and deaths are predicted by the inflammatory “cytokine storm.” One way to progress in the prevention of death is by finding a predictive and protective factor that inhibits inflammation, on the one hand, and which also increases anti-viral immunity on the other hand. The vagal nerve does precisely both actions. This study examined whether vagal nerve activity, indexed by heart-rate variability (HRV), predicts survival in patients with Covid-19. Method: We performed a pseudo-prospective study, where we retroactively obtained ECGs of 271 Covid-19 patients arriving at a large regional hospital in The Netherlands. HRV was indexed by the standard deviation of the intervals between normal heartbeats (SDNN). We examined patients’ survival at 3 weeks and took into account multiple confounders and known prognostic factors (e.g., age, heart disease, diabetes, hypertension). Results: Patients’ mean age was 68 (range: 25-95) and nearly 22% of the patients had died by 3 weeks. Their mean SDNN (17.47msec) was far below the norm (50msec). Importantly, relatively higher HRV significantly predicted a higher chance of survival, after statistically controlling for patients’ age, cardiac diseases, hypertension and diabetes (relative risk, H.R, and 95% confidence interval (95%CI): H.R = 0.49, 95%CI: 0.26 – 0.95, p < 0.05). However, since HRV declines rapidly with age and since age is a profound predictor in Covid-19, we split the sample by median age (40). Subsequently, we found that higher HRV significantly predicted greater survival in patients older than 70 (H.R = 0.35, 95%CI: 0.16 – 0.78, p = 0.01), but HRV did not predict survival in patients below age 70 years (H.R = 1.11, 95%CI: 0.37 – 3.28, p > 0.05). Conclusions: To the best of our knowledge, this is the first study showing that higher vagal nerve activity, as indexed by HRV, is an independent predictor of higher chances for survival in Covid-19. The results are in line with the protective role of the vagal nerve in diseases and extend this to a severe infectious illness. Studies should replicate these findings and then test in controlled trials whether activating the vagus nerve may prevent mortality in Covid-19.

Keywords: Covid-19, heart-rate Variability, prognosis, survival, vagal nerve

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Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

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Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

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Authors: Anushka Naidoo, Veron Ramsuran, Maxwell Chirehwa, Paolo Denti, Kogieleum Naidoo, Helen McIlleron, Nonhlanhla Yende-Zuma, Ravesh Singh, Sinaye Ngcapu, Nesri Padayatachi

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Background: Despite efforts to introduce new drugs and shorter drug regimens for drug-susceptible tuberculosis (TB), the standard first-line treatment has not changed in over 50 years. Rifampicin, isoniazid, and pyrazinamide are critical components of the current standard treatment regimens. Some studies suggest that microbiologic failure and acquired drug resistance are primarily driven by low drug concentrations that result from pharmacokinetic (PK) variability independent of adherence to treatment. Wide between-patient pharmacokinetic variability for rifampin, isoniazid, and pyrazinamide has been reported in prior studies. There may be several reasons for this variability. However, genetic variability in genes coding for drug metabolizing and transporter enzymes have been shown to be a contributing factor for variable tuberculosis drug exposures. Objective: We describe the pharmacokinetics of first-line TB drugs rifampicin, isoniazid, and pyrazinamide and assess the effect of genetic variability in relevant selected drug metabolizing and transporter enzymes on pharmacokinetic parameters of isoniazid and rifampicin. Methods: We conducted the randomized-controlled Improving retreatment success TB trial in Durban, South Africa. The drug regimen included rifampicin, isoniazid, and pyrazinamide. Drug concentrations were measured in plasma, and concentration-time data were analysed using nonlinear-mixed-effects models to quantify the effects of relevant covariates and single nucleotide polymorphisms (SNP’s) of drug metabolizing and transporter genes on rifampicin, isoniazid and pyrazinamide exposure. A total of 25 SNP’s: four NAT2 (used to determine acetylator status), four SLCO1B1, three Pregnane X receptor (NR1), six ABCB1 and eight UGT1A, were selected for analysis in this study. Genotypes were determined for each of the SNP’s using a TaqMan® Genotyping OpenArray™. Results: Among fifty-eight patients studied; 41 (70.7%) were male, 97% black African, 42 (72.4%) HIV co-infected and 40 (95%) on efavirenz-based ART. Median weight, fat-free mass (FFM), and age at baseline were 56.9 kg (interquartile range, IQR: 51.1-65.2), 46.8 kg (IQR: 42.5-50.3) and 37 years (IQR: 31-42), respectively. The pharmacokinetics of rifampicin and pyrazinamide was best described using one-compartment models with first-order absorption and elimination, while for isoniazid two-compartment disposition was used. The median (interquartile range: IQR) AUC (h·mg/L) and Cmax (mg/L) for rifampicin, isoniazid, and pyrazinamide were; 25.62 (23.01-28.53) and 4.85 (4.36-5.40), 10.62 (9.20-12.25) and 2.79 (2.61-2.97), 345.74 (312.03-383.10) and 28.06 (25.01-31.52), respectively. Eighteen percent of patients were classified as rapid acetylators, and 34% and 43% as slow and intermediate acetylators, respectively. Rapid and intermediate acetylator status based on NAT 2 genotype resulted in 2.3 and 1.6 times higher isoniazid clearance than slow acetylators. We found no effects of the SLCO1B1 genotypes on rifampicin pharmacokinetics. Conclusion: Plasma concentrations of rifampicin, isoniazid, and pyrazinamide were low overall in our patients. Isoniazid clearance was high overall and as expected higher in rapid and intermediate acetylators resulting in lower drug exposures. In contrast to reports from previous South African or Ugandan studies, we did not find any effects of the SLCO1B1 or other genotypes tested on rifampicin PK. However, our findings are in keeping with more recent studies from Malawi and India emphasizing the need for geographically diverse and adequately powered studies. The clinical relevance of the low tuberculosis drug concentrations warrants further investigation.

Keywords: rifampicin, isoniazid pharmacokinetics, genetics, NAT2, SLCO1B1, tuberculosis

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Authors: Xuewen Chen, Aizhen Liang, Xiaoping Zhang

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To better understand the spatial variability of soil penetration resistance (SPR) and soil water content (SWC) induced by different tillage and crop rotation in a Mollisol of Northeast China, the soil was sampled from the tillage experiment which was established in Dehui County, Jilin Province, Northeast China, in 2001. Effect of no-tillage (NT), moldboard plow (MP) and ridge tillage (RT) under corn-soybean rotation (C-S) and continuous corn (C-C) system on SPR and SWC were compared with horizontal and vertical variations. The results showed that SPR and SWC spatially varied across the ridge. SPR in the rows was higher than inter-rows, especially in topsoil (2.5-15 cm) of NT and RT plots. SPR of MP changed in the trend with the curve-shaped ridge. In contrast to MP, NT, and RT resulted in average increment of 166.3% and 152.3% at a depth of 2.5-17.5 cm in the row positions, respectively. The mean SPR in topsoil in the rows means soil compaction is not the main factor limiting plant growth and crop yield. SPR in the row of RT soil was lower than NT at a depth of 2.5-12.5 cm. The SWC in NT and RT soil was highest in the inter-rows and least in the rows or shoulders, respectively. However, the lateral variation trend of MP was opposite to NT. From the profile view of SWC, MP was greater than NT and RT in 0-20 cm of the rows. SWC in RT soil was higher than NT in the row of 0-20 cm. Crop rotation did not have a marked impact on SPR and SWC. In addition to the tillage practices, the factor which affects SPR greatly was depth but not position. These two factors have significant effects on SWC. These results indicated that the adoption of RT was a more suitable conservation tillage practices than NT in the black soil of Northeast China.

Keywords: row, soil penetration resistance, spatial variability, tillage practice

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Authors: Arafan Traore, Teiji Watanabe

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Conakry, the capital city of the Republic of Guinea, has experienced a rapid urban expansion and population increased in the last two decades, which has resulted in remarkable local weather and climate change, raise energy demand and pollution and treating social, economic and environmental development. In this study, the spatiotemporal variation of the land surface temperature (LST) is retrieved to characterize the effect of urban growth on the thermal environment and quantify its relationship with biophysical indices, a normalized difference vegetation index (NDVI) and a normalized difference built up Index (NDBI). Landsat data TM and OLI/TIRS acquired respectively in 1986, 2000 and 2016 were used for LST retrieval and Land use/cover change analysis. A quantitative analysis based on the integration of a remote sensing and a geography information system (GIS) has revealed an important increased in the LST pattern in the average from 25.21°C in 1986 to 27.06°C in 2000 and 29.34°C in 2016, which was quite eminent with an average gain in surface temperature of 4.13°C over 30 years study period. Additionally, an analysis using a Pearson correlation (r) between (LST) and the biophysical indices, normalized difference vegetation index (NDVI) and a normalized difference built-up Index (NDBI) has revealed a negative relationship between LST and NDVI and a strong positive relationship between LST and NDBI. Which implies that an increase in the NDVI value can reduce the LST intensity; conversely increase in NDBI value may strengthen LST intensity in the study area. Although Landsat data were found efficient in assessing the thermal environment in Conakry, however, the method needs to be refined with in situ measurements of LST in the future studies. The results of this study may assist urban planners, scientists and policies makers concerned about climate variability to make decisions that will enhance sustainable environmental practices in Conakry.

Keywords: Conakry, land surface temperature, urban heat island, geography information system, remote sensing, land use/cover change

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Authors: Sheila R. Pai, Rekha D. Kini, Amrutha Mary

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Objective: To assess and compare the cardiac autonomic activity after mental stress among the wards of normal and hypertensive parents. Methods: The study included 67 subjects, 30 of them had a parental history of hypertension and rest 37 had normotensive parents. Subjects were divided into control group (wards of normotensive parents) and Study group (wards of hypertensive parents). The height, weight were noted, and Body Mass Index (BMI) was also calculated. The mental stress test was carried out. Blood pressure (BP) and electro cardiogram (ECG) was recorded during normal breathing and after mental stress test. Heart rate variability (HRV) analysis was done by time domain method HRV was recorded and analyzed by the time-domain method. Analysis of HRV in the time-domain was done using the software version 1.1 AIIMS, New Delhi. The data obtained was analyzed using student’s t-test followed by Mann-Whitney U-test and P < 0.05 was considered significant. Results: There was no significant difference in systolic blood pressure and diastolic blood pressure (DBP) between study group and control group following mental stress. In the time domain analysis, the mean value of pNN50 and RMSSD of the study group was not significantly different from the control group after the mental stress test. Conclusion: The study thus concluded that there was no significant difference in HRV between study group and control group following mental stress.

Keywords: heart rate variability, time domain analysis, mental stress, hypertensive

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Authors: Mohammed A. Alhoot, Rathika A/P Nagarajan

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Climate change and variability are affecting human health and diseases direct or indirectly through many mechanisms. Change in rain pattern, an increase of temperature and humidity are showing an increased trend in Malaysia. This will affect the biological, physical and chemical component of water through different pathways and will enhance the risk of waterborne diseases. Besides, the warm temperature and humid climate provide very suitable conditions for the growth of pathogenic bacteria. This study is intended to highlight the relationship between the climate changes and the incidence food and water associated infections. Incidences of food and water associated infection and climate data were collected from Malaysian Ministry of health and Malaysian Metrological Department respectively. Maximum and minimum temperature showed high correlation with incidence of typhoid, hepatitis A, dysentery, food poisoning (P value <0.05 significant with 2 tailed / 0.5<[r]). Heavy rainfall does not associated with any outbreaks. Climate change brings out new challenges in controlling food and water associated infections. Adaptation strategies should involve all key stakeholders with a strong regional cooperation to prevent and deal with cross-boundary health crises. Moreover, the role of health care personnel at local, state and national levels is important to ensure the success of these programmes. As has been shown herein, climate variability is an important element influencing the food and water associated epidemiology in Malaysia. The results of this study are crucial to implementing climate changes as a factor to reduce any future outbreaks.

Keywords: climate change, typhoid, hepatitis A, dysentery, food poisoning

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Authors: Nawaf Al-Kharashi, Waseem Al-Talalwah, Shorok Al Dorazi, Roger Soames

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Superior gluteal artery is one of the largest branches of posterior division of the internal iliac artery. It passes between the lumbosacral and first sacral root to escape from the pelvic cavity through the grater sciatic foramen just above the piriformis. The current study includes 41 cadaver investigates the origin and branch of the superior gluteal artery and clarify the clinical significance. In present study, the superior gluteal artery arises from the posterior division of the internal iliac artery directly in 82.5% whereas it arises indirectly as from the sciatic artery in 15.9%. However, it is congenital absence in 1.6% which is compensated by sciatic artery. The sciatic nerve gains vascular supply from superior gluteal artery in two ways either during its course or giving lateral sacral artery in 27% and lumbar branches in 1.6%. It also supplies the adductors group and iliacus via giving obturator artery in 14.3% and in 1.6% respectively. The superior gluteal artery usually passes between lumbosacral trunk and first sacral root in 82.5% whereas it does not passes the sciatic roots as it arises behind them in 15.9%. With a variability of the superior gluteal artery origin, there is a variability of sciatic nerve roots supply. Further, the superior gluteal artery arising from sciatic artery behind the sciatic roots carries a high risk of intra-pelvic bleeding in case of posterior pelvic fracture. Prolonged ligation of the superior gluteal artery which gives lateral sacral artery may result in sciatic neuropathy. Therefore, surgeons have to be aware of the superior gluteal artery variation in origin, course and branches to reduce the iatrogenic faults.

Keywords: internal pudendal artery, inferior gluteal artery, superior gluteal artery, internal iliac artery. sciatic neuropathy, sciatic nerve

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Authors: Nafaa Zaafour

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Located at the north eastern of Algeria, the National Park of El-Kala (PNEK) is a set of landscapes whose bioclimatic stages of vegetation extend from sub-humid to humid. In order to know the soil occupation in this complex, an initiated ecological soil cartography using a stratified sampling plan of vegetation had made, the study area occupies two-thirds of the northern National Park of El Kala, it has been divided into 380 plots of 1km2 of which, 76 were the subject of a detailed floristic inventory and sampling of soils. The inventory of vegetation carried out on different sites has allowed identifying several plant groups that share the soil cover with the following distribution: The group of cork oak, this formation occupies the biggest part of the area, it develops mainly on Incepttisols, Alfisols and Mollisols; The group of kermes oak, occupies a large area, it grows on Mollisols and Alfisols; The group of maritime pine, it occupies the same soils as the Kermes Oak; The group of Mirbeck oak, installed on Regosols, it is located in the Eastern part, on the Algerian-Tunisian border; The group of eucalyptus, it grows mainly on Inceptisols, Mollisols of, and Vertisols; The group of wetland, it grows along the banks of lakes and rivers, which primarily develops on Histosols soil Mollisols and Vertisols; The cultures, distributed mainly around the lakes occupy several soil types on Histosols, the Inceptisols, Mollisols of, and Vertisols. This great diversity of vegetation is linked not only to the soil variability but also to climate, hydrological and geological variability.

Keywords: Algeria, cartography, soil, vegetation

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Authors: Luisa Kynast

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It is obvious that buildings and infrastructure are highly impacted by climate change (CC). Both, design and material of buildings need to be resilient to weather events in order to shelter humans, animals, or goods. As well as buildings and infrastructure are exposed to weather events, the construction process itself is generally carried out outdoors without being protected from extreme temperatures, heavy rain, or storms. The production process is restricted by technical limitations for processing materials with machines and physical limitations due to human beings (“outdoor-worker”). In future due to CC, average weather patterns are expected to change as well as extreme weather events are expected to occur more frequently and more intense and therefore have a greater impact on production processes and on the construction businesses itself. This research aims to examine this impact by analyzing an association between responses to CC and financial performance of businesses within the construction industry. After having embedded the above depicted field of research into the resource dependency theory, a literature review was conducted to expound the state of research concerning a contingent relation between climate change adaptation measures (CCAM) and corporate financial performance for construction businesses. The examined studies prove that this field is rarely investigated, especially for construction businesses. Therefore, reports of the Carbon Disclosure Project (CDP) were analyzed by applying content analysis using the software tool MAXQDA. 58 construction companies – located worldwide – could be examined. To proceed even more systematically a coding scheme analogous to findings in literature was adopted. Out of qualitative analysis, data was quantified and a regression analysis containing corporate financial data was conducted. The results gained stress adaptation measures as a response to CC as a crucial proxy to handle climate change impacts (CCI) by mitigating risks and exploiting opportunities. In CDP reports the majority of answers stated increasing costs/expenses as a result of implemented measures. A link to sales/revenue was rarely drawn. Though, CCAM were connected to increasing sales/revenues. Nevertheless, this presumption is supported by the results of the regression analysis where a positive effect of implemented CCAM on construction businesses´ financial performance in the short-run was ascertained. These findings do refer to appropriate responses in terms of the implemented number of CCAM. Anyhow, still businesses show a reluctant attitude for implementing CCAM, which was confirmed by findings in literature as well as by findings in CDP reports. Businesses mainly associate CCAM with costs and expenses rather than with an effect on their corporate financial performance. Mostly companies underrate the effect of CCI and overrate the costs and expenditures for the implementation of CCAM and completely neglect the pay-off. Therefore, this research shall create a basis for bringing CC to the (financial) attention of corporate decision-makers, especially within the construction industry.

Keywords: climate change adaptation measures, construction businesses, financial implication, resource dependency theory

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Authors: Zhen Li, Chang Liu, Ping Zhang

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These Glaciers are thought of as natural water reservoirs and are of vital importance to hydrological models and industrial production, and glacial changes act as significant indicators of climate change. The glacier snowline can be used as an indicator of the equilibrium line, which may be a key parameter to study the effect of climate change on glaciers. Using Google Earth Engine, we select optical satellite imageries and implement the Otsu thresholding method on a near-infrared band to detect snowline altitudes (SLAs) of 26 glaciers in three regions of the eastern Tibetan Plateau. Three different study regions in the eastern Tibetan Plateau have different climate regimes, which are Sepu Kangri (SK, maritime glacier), Bu’Gyai Kangri (BK, continental glacier) and west of Qiajajima (WQ, continental glacier), along a latitudinal transect from south to north. We analyzed the effects of climatic factors on the SLA changes from 1995 to 2016. SLAs are fluctuating upward, and the rising values are 100 m, 60 m, and 34 m from south to north during the 22 years. We also observed that the climatic factor that affects the variability of SLA gradually changes from precipitation to temperature from south to north. The northern continental glaciers are mainly affected by temperature, and the southern maritime glaciers affected by precipitation. Owing to the influence of primary climatic factors, continental glaciers are found to have higher SLAs on the south slope, while maritime glaciers have higher SLAs on the north slope.

Keywords: climate change, glacier, snowline altitude, tibetan plateau

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Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

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The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

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Authors: Michael Dolgin, Oz Hamtzani, Talma Kushnir

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A literature review has shown that while parents of children with cancer experience increased levels of psychological distress associated with their child's medical condition, considerable variability in parental adjustment is evident. Of the factors that may account for this variability, little attention has been devoted to the simultaneous interaction of three coping constructs and their role in parental adjustment: (1) Coping techniques employed, (2) Repertoire of coping techniques, and (3) Flexibility in applying coping techniques. While these constructs have been studied individually in relation to adjustment in general, studies to date have not included them together within a single conceptual model and research design and evaluated them in a clinical population. The objective of the current study was to determine how these three coping technique constructs interact to impact parental adjustment to pediatric cancer. A cross-sectional sample of 145 parents of children in active cancer treatment completed standardized measures of coping techniques, repertoire, flexibility, and parental distress. A hierarchical multiple regression analysis demonstrated that 37% of the variance in parental distress was predicted by the use of avoidance-focused coping techniques [F(1,118)=69.843, p<.001], with an additional 3% predicted by coping repertoire [F(2,117)=7.63, p=.00] for a total of 40% variance explained. Coping flexibility was found to mediate the relationship between coping repertoire and parental distress. These findings suggest that coping techniques employed by parents (problem/emotion-focused vs. avoidance-focused), as well as coping repertoire, significantly impact parental adjustment. Flexibility in applying coping techniques within one’s coping repertoire further contributes to parental adjustment. Implications for further study and clinical intervention will be presented.

Keywords: coping techniques, repertoire, flexibility, adjustment

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Authors: Višnjica Vučetić, Mislav Anić, Jelena Bašić, Petra Sviličić, Ivana Tomašević

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The Agroclimatic Atlas of Croatia (Atlas) for the periods 1981–2010 and 1991–2020 is monograph of six chapters in digital form. Detailed descriptions of particular agroclimatological data are given in separate chapters as follows: agroclimatic indices based on air temperature (degree days, Huglin heliothermal index), soil temperature, water balance components (precipitation, potential evapotranspiration, actual evapotranspiration, soil moisture content, runoff, recharge and soil moisture loss) and fire weather indices. The last chapter is a description of the digital methods for the spatial interpolations (R and GIS). The Atlas comprises textual description of the relevant climate characteristic, maps of the spatial distribution of climatological elements at 109 stations (26 stations for soil temperature) and tables of the 30-year mean monthly, seasonal and annual values of climatological parameters at 24 stations. The Atlas was published in 2021, on the seventieth anniversary of the agrometeorology development at the Meteorological and Hydrological Service of Croatia. It is intended to support improvement of sustainable system of agricultural production and forest protection from fire and as a rich source of information for agronomic and forestry experts, but also for the decision-making bodies to use it for the development of strategic plans.

Keywords: agrometeorology, agroclimatic indices, soil temperature, water balance components, fire weather index, meteorological and hydrological service of Croatia

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Authors: Shailja Thakur

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In this paper it is shown that how farmers are suffering from all sides including vagaries of weather then price fluctuations, demand supply constraints, poor soil health etc. Also the ICT can prove to be of great help if incorporated rightly into Indian agriculture. Some innovative ways to reward farmers and distribution of subsidies to them can improve the current scenario.

Keywords: cost of farming, information and communication technology, innovative steps, roof gardening, vermicomposting

Procedia PDF Downloads 291

Authors: Akinola Ikudayisi, Josiah Adeyemo

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The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.

Keywords: irrigation, principal component analysis, reference evapotranspiration, Vaalharts

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Authors: Geminne Manzano, Porfirio Aliño, Clairecynth Yu, Lilibeth Salvador-Reyes, Viviene Santiago

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Many marine benthic organisms produce secondary metabolites that serve as ecological roles to different biological and environmental factors. The secondary metabolites found in these organisms like algae, sponges, tunicates and worms exhibit variation at different scales. Understanding the chemical variation can be essential in deriving the evolutionary and ecological function of the secondary metabolites that may explain their patterns. Ecological surveys were performed on two collection sites representing from two Philippine marine biogeographic regions – in Oriental Mindoro located on the West Philippine Sea (WPS) and in Zamboanga del Sur located at Celebes Sea (CS), where a total of 39 Xestospongia sp. sponges were collected using SCUBA. The sponge samples were transported to the laboratory for taxonomic identification and chemical analysis. Biological and environmental factors were investigated to determine their relation to the abundance and distribution patterns and its spatial variability of their secondary metabolite production. Extracts were subjected to thin-layer chromatography and anti-proliferative assays to confirm the presence of Renieramycin-M and to test its cytotoxicity. The blue sponges were found to be more abundant on the WPS than in CS. Both the benthic community and the fish community in Oriental Mindoro, WPS and Zamboanga del Sur, CS sites are characterized by high species diversity and abundance and a very high biomass category. Environmental factors like depth and monsoonal exposure were also compared showing that wave exposure and depth are associated with the abundance and distribution of the sponges. Renieramycin-M presence using the TLC profiles between the sponge extracts from WPS and from CS showed differences in the Reniermycin-M presence and the presence of other functional groups were observed between the two sites. In terms of bioactivity, different responses were also exhibited by the sponge extracts coming from the different region. Different responses were also noted on its bioactivity depending on the cell lines tested. Exploring the influence of ecological parameters on the chemical variation can provide deeper chemical ecological insights in the knowledge and their potential varied applications at different scales. The results of this study provide further impetus in pursuing studies into patterns and processes of the chemical diversity of the Philippine blue sponge, Xestospongia sp. and the chemical ecological significance of the coral triangle.

Keywords: chemical ecology, porifera, renieramycin-m, spatial variability, Xestospongia sp.

Procedia PDF Downloads 192

Authors: Drew Commandeur, Ryan Brodie, Sandra Hundza, Marc Klimstra

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The amplitude of raw electromyography (EMG) is affected by recording conditions and often requires normalization to make meaningful comparisons. Bioelectric methods normalize with an EMG signal recorded during a standardized task or from the experimental protocol itself, while biomechanical methods often involve measurements with an additional sensor such as a force transducer. Common bioelectric normalization techniques for treadmill walking include maximum voluntary isometric contraction (MVIC), dynamic EMG peak (EMGPeak) or dynamic EMG mean (EMGMean). There are several concerns with using MVICs to normalize EMG, including poor reliability and potential discomfort. A limitation of bioelectric normalization techniques is that they could result in a misrepresentation of the absolute magnitude of force generated by the muscle and impact the interpretation of EMG between functionally disparate groups. Additionally, methods that normalize to EMG recorded during the task may eliminate some real inter-individual variability due to biological variation. This study compared biomechanical and bioelectric EMG normalization techniques during treadmill walking to assess the impact of the normalization method on the functional interpretation of EMG data. For the biomechanical method, we normalized EMG to a target torque (EMGTS) and the bioelectric methods used were normalization to the mean and peak of the signal during the walking task (EMGMean and EMGPeak). The effect of normalization on muscle activation pattern, EMG amplitude, and inter-individual variability were compared between disparate cohorts of OLD (76.6 yrs N=11) and YOUNG (26.6 yrs N=11) adults. Participants walked on a treadmill at a self-selected pace while EMG was recorded from the right lower limb. EMG data from the soleus (SOL), medial gastrocnemius (MG), tibialis anterior (TA), vastus lateralis (VL), and biceps femoris (BF) were phase averaged into 16 bins (phases) representing the gait cycle with bins 1-10 associated with right stance and bins 11-16 with right swing. Pearson’s correlations showed that activation patterns across the gait cycle were similar between all methods, ranging from r =0.86 to r=1.00 with p<0.05. This indicates that each method can characterize the muscle activation pattern during walking. Repeated measures ANOVA showed a main effect for age in MG for EMGPeak but no other main effects were observed. Interactions between age*phase of EMG amplitude between YOUNG and OLD with each method resulted in different statistical interpretation between methods. EMGTS normalization characterized the fewest differences (four phases across all 5 muscles) while EMGMean (11 phases) and EMGPeak (19 phases) showed considerably more differences between cohorts. The second notable finding was that coefficient of variation, the representation of inter-individual variability, was greatest for EMGTS and lowest for EMGMean while EMGPeak was slightly higher than EMGMean for all muscles. This finding supports our expectation that EMGTS normalization would retain inter-individual variability which may be desirable, however, it also suggests that even when large differences are expected, a larger sample size may be required to observe the differences. Our findings clearly indicate that interpretation of EMG is highly dependent on the normalization method used, and it is essential to consider the strengths and limitations of each method when drawing conclusions.

Keywords: electromyography, EMG normalization, functional EMG, older adults

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Authors: Khlifa El Atrash, Gabriel Assaf

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Most developing countries use volumetric analysis in designing asphalt mixtures, which can also be upgraded in hot arid weather. However, in order to be effective, it should include many important aspects which are materials, environment, and method of construction. The overall intent of the work reported in this study is to test different asphalt mixtures while taking into consideration the environment, type and source of material, tools, equipment, and the construction method. In this study, several tests were conducted on many samples that were carefully prepared under the expected traffic loads and temperatures in a dry hot climate. Several asphalt concrete mixtures were designed using two different binders. These mixtures were analyzed under two types of tests - Complex Modulus and Rutting test - to evaluate the hot mix asphalt properties under the represented temperatures and traffic load in Libya. These factors play an important role to improve the pavement performances in a hot climate weather based on the properties of the asphalt mixture, climate, and traffic load. This research summarized some recommendations for making asphalt mixtures used in hot dry areas. Such asphalt mixtures should use asphalt binder which is less affected by pavement temperature change and traffic load. The properties of the mixture, such as durability, deformation, air voids and performance, largely depend on the type of materials, environment, and mixing method. These properties, in turn, affect the pavement performance. Therefore, this study is aimed to develop a method for designing an asphalt mixture that takes into account field loading, various stresses, and temperature spectrums.

Keywords: volumetric analysis, pavement performances, hot climate, asphalt mixture, traffic load

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Authors: Petra Hypšová, Martin Seitl

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One of the challenges of forensic psychology is to detect deception during a face-to-face interview. In addition to the classical approaches of monitoring the utterance and its components, detection is also sought by observing behavioral and physiological changes that occur as a result of the increased emotional and cognitive load caused by the production of distorted information. Typical are changes in facial temperature, eye movements and their fixation, pupil dilation, emotional micro-expression, heart rate and its variability. Expanding technological capabilities have opened the space to detect these psychophysiological changes and behavioral manifestations through non-contact technologies that do not interfere with face-to-face interaction. Non-contact deception detection methodology is still in development, and there is a lack of studies that combine multiple non-contact technologies to investigate their accuracy, as well as studies that show how different types of lies produced by different interviewers affect physiological and behavioral changes. The main objective of this study is to apply a specific non-contact technology for deception detection. The next objective is to investigate scenarios in which non-contact deception detection is possible. A series of psychophysiological experiments using infrared thermal imaging, eye tracking and behavioral analysis with FaceReader 9.0 software was used to achieve our goals. In the laboratory experiment, 16 adults (12 women, 4 men) between 18 and 35 years of age (SD = 4.42) were instructed to produce alternating prepared and spontaneous truths and lies. The baseline of each proband was also measured, and its results were compared to the experimental conditions. Because the personality of the examiner (particularly gender and facial appearance) to whom the subject is lying can influence physiological and behavioral changes, the experiment included four different interviewers. The interviewer was represented by a photograph of a face that met the required parameters in terms of gender and facial appearance (i.e., interviewer likability/antipathy) to follow standardized procedures. The subject provided all information to the simulated interviewer. During follow-up analyzes, facial temperature (main ROIs: forehead, cheeks, the tip of the nose, chin, and corners of the eyes), heart rate, emotional expression, intensity and fixation of eye movements and pupil dilation were observed. The results showed that the variables studied varied with respect to the production of prepared truths and lies versus the production of spontaneous truths and lies, as well as the variability of the simulated interviewer. The results also supported the assumption of variability in physiological and behavioural values during the subject's resting state, the so-called baseline, and the production of prepared and spontaneous truths and lies. A series of psychophysiological experiments provided evidence of variability in the areas of interest in the production of truths and lies to different interviewers. The combination of technologies used also led to a comprehensive assessment of the physiological and behavioral changes associated with false and true statements. The study presented here opens the space for further research in the field of lie detection with non-contact technologies.

Keywords: emotional expression decoding, eye-tracking, functional infrared thermal imaging, non-contact deception detection, psychophysiological experiment

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Authors: Mohd Yussni Hashim, Mohd Nazrul Roslan, Shahruddin Mahzan Mohd Zin, Saparudin Ariffin

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Fiber cross-sectional area value is a crucial factor in determining the strength properties of natural fiber. Furthermore, unlike synthetic fiber, a diameter and cross-sectional area of natural fiber has a large variation along and between the fibers. This study aims to determine the main and interaction effects of alkali treatment conditions that influence kenaf bast fiber mean cross-sectional area. Three alkali treatment conditions at two different levels were selected. The conditions setting were alkali concentrations at two and ten w/v %; fiber immersed temperature at room temperature and 1000C; and fiber immersed duration for 30 and 480 minute. Untreated kenaf fiber was used as a control unit. Kenaf bast fiber bundle mounting tab was prepared according to ASTM C1557-03. The cross-sectional area was measured using a Leica video analyzer. The study result showed that kenaf fiber bundle mean cross-sectional area was reduced 6.77% to 29.88% after alkali treatment. From the analysis of variance, it shows that the interaction of alkali concentration and immersed time has a higher magnitude at 0.1619 compared to alkali concentration and immersed temperature interaction that was 0.0896. For the main effect, alkali concentration factor contributes to the higher magnitude at 0.1372 which indicated the decrease pattern of variability when the level changed from lower to the higher level. Then, it was followed by immersed temperature at 0.1261 and immersed time at 0.0696 magnitudes.

Keywords: natural fiber, kenaf bast fiber bundles, alkali treatment, cross-sectional area

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Authors: Muhammad Fezan Afzal, Asad Abbas, Imran Khan, Salma Imtiaz

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Software Product Line (SPL) paradigm is used for the development of the family of software products that share common and variable features. Feature model is a domain of SPL that consists of common and variable features with predefined relationships and constraints. Multiple SPLs consist of a number of similar common and variable features, such as mobile phones and Tabs. Reusability of common and variable features from the different domains of SPL is a complex task due to the external relationships and constraints of features in the feature model. To increase the reusability of feature model resources from domain engineering, it is required to manage the commonality of features at the level of SPL application development. In this research, we have proposed an approach that combines multiple SPLs into a single domain and converts them to a common feature model. Extracting the common features from different feature models is more effective, less cost and time to market for the application development. For extracting features from multiple SPLs, the proposed framework consists of three steps: 1) find the variation points, 2) find the constraints, and 3) combine the feature models into a single feature model on the basis of variation points and constraints. By using this approach, reusability can increase features from the multiple feature models. The impact of this research is to reduce the development of cost, time to market and increase products of SPL.

Keywords: software product line, feature model, variability management, multi-SPLs

Procedia PDF Downloads 48