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Abstract Aims To improve telemonitoring strategies in heart failure patients, there is a need for novel non‐obtrusive sensors that monitor parameters closely related to intracardiac filling pressures. This proof‐of‐concept study aims to evaluate the responsiveness of cardiac kinetic energy (KE) measured with the Kinocardiograph (KCG), consisting of a seismocardiographic (SCG) sensor and a ballistocardiographic (BCG) sensor, during treatment of patients with acute decompensated heart failure. Methods and results Eleven patients with acute decompensated heart failure who were hospitalized for treatment with intravenous diuretics received daily KCG measurements. The KCG measurements were compared with the diameter of the inferior vena cava (IVC) and body weight. Follow‐up stopped at discharge, that is, in the recompensated state. Median (interquartile range) weight and IVC diameter decreased significantly after diuretic treatment [weight 74.5 (67.6–98.7) to 73.3 (66.7–95.6) kg, P = 0.003; IVC diameter 2.47 (2.33–2.99) to 1.78 (1.65–2.47) cm, P = 0.03]. In contrast with BCG measurements, significant changes in median KE measured with SCG were observed during the passive filling phase of the diastole [SGG: 0.48 (0.39–0.60) to 0.69 (0.56–0.84), P = 0.026; BCG: 0.68 (0.46–0.73) to 0.68 (0.59–0.82), P = 0.062], the active filling phase of the diastole [SCG: 0.38 (0.30–0.61) to 0.31 (0.09–0.47), P = 0.016; BCG: 0.29 (0.17–0.39) to 0.26 (0.20–0.34), P = 0.248], and the ratio between the passive and active filling phases [SCG: 2.76 (1.68–5.30) to 5.02 (3.13–10.17), P = 0.006; BCG: 5.87 (3.57–7.55) to 5.27 (3.95–9.43), P = 0.790]. The correlations between changes in KE during the passive and active filling phases, using SCG, and changes in weight or IVC were non‐significant. Systolic KE did not show significant changes. Conclusion KE measured with the KCG using SCG is highly responsive to changes in fluid status. Future research is needed to confirm its accuracy in a larger study population and specifically its application for detection of clinical deterioration in the home‐environment.

A large amount of gas is emitted during underground mining processes, so mining productivity decreases and safety risks increase. Efficient methane drainage from the coal seam and surrounding rocks in underground mines not only improves safety but also leads to higher productivity. Methane drainage must be performed when the ventilation air cannot dilute the methane emissions in the mine to a level below the allowed limits. The cross-measure borehole method is one of the methane drainage methods that involves drilling boreholes from the tailgate roadway to an un-stressed zone in the roof or floor stratum of a mined seam. This is the main method used in Tabas coal mine N 1. One of the effective parameters in this method is the distance between methane drainage stations, which has a direct effect on the length of boreholes required for drainage. This study was based on the measurement of ventilation air methane by methane sensors and anemometers placed at the longwall panel as well as measuring the amount of methane drainage. Moreover, in this study, the obtained and analyzed data were used to determine the suitable distance between methane drainage stations based on the cross-measure borehole method. In a field test, three borehole arrangements with different station distances in Panel E4 of Tabas coal mine N 1 were investigated. Then, the amounts of gas drained from these arrangements were compared with each other. The highest methane drainage efficiency was achieved for distances in the range of 9-12 m between methane drainage stations.

Seismocardiography (SCG), a method for measuring heart-induced chest vibrations, is gaining attention as a non-invasive, accessible, and cost-effective approach for cardiac pathologies, diagnosis, and monitoring. This study explores the integration of SCG acquired through smartphone technology by assessing the accuracy of metrics derived from smartphone recordings and their consistency when performed by patients. Therefore, we assessed smartphone-derived SCG’s reliability in computing median kinetic energy parameters per record in 220 patients with various cardiovascular conditions. The study involved three key procedures: (1) simultaneous measurements of a validated hardware device and a commercial smartphone; (2) consecutive smartphone recordings performed by both clinicians and patients; (3) patients’ self-conducted home recordings over three months. Our findings indicate a moderate-to-high reliability of smartphone-acquired SCG metrics compared to those obtained from a validated device, with intraclass correlation (ICC) > 0.77. The reliability of patient-acquired SCG metrics was high (ICC > 0.83). Within the cohort, 138 patients had smartphones that met the compatibility criteria for the study, with an observed at-home compliance rate of 41.4%. This research validates the potential of smartphone-derived SCG acquisition in providing repeatable SCG metrics in telemedicine, thus laying a foundation for future studies to enhance the precision of at-home cardiac data acquisition.

BackgroundHeart failure (HF) remains a major cause of mortality, morbidity, and poor quality of life. 44% of HF patients present impaired left ventricular ejection fraction (LVEF). Kinocardiography (KCG) technology combines ballistocardiography (BCG) and seismocardiography (SCG). It estimates myocardial contraction and blood flow through the cardiac chambers and major vessels through a wearable device. Kino-HF sought to evaluate the potential of KCG to distinguish HF patients with impaired LVEF from a control group.MethodsSuccessive patients with HF and impaired LVEF (iLVEF group) were matched and compared to patients with normal LVEF ≥ 50% (control). A 60 s KCG acquisition followed cardiac ultrasound. The kinetic energy from KCG signals was computed in different phases of the cardiac cycle (iKsystolic;ΔiKdiastolic) as markers of cardiac mechanical function.ResultsThirty HF patients (67 [59; 71] years, 87% male) were matched with 30 controls (64.5 [49; 73] years, 87% male). SCG ΔiKdiastolic, BCG iKsystolic, BCG ΔiKdiastolic were lower in HF than controls (p

Abstract Aims The kinocardiograph (KCG) is an unobtrusive device, consisting of a chest sensor, which records local thoracic vibrations produced in result of cardiac contraction and ejection of blood into the great vessels [seismocardiography (SCG)], and a lower back sensor, which records micromovements of the body in reaction to blood flowing through the vasculature [ballistocardiography (BCG)]. SCG and BCG signals are translated to the integral of cardiac kinetic energy (iK) and cardiac maximum power (Pmax), which might be promising metrics for future telemonitoring purposes in heart failure (HF). As a first step of validation, this study aimed to determine whether iK and Pmax are responsive to exercise‐induced changes in the haemodynamic load of the heart in HF patients. Methods and results Fifteen patients with stable HF with reduced ejection fraction performed a submaximal exercise protocol. KCG and cardiac ultrasound measurements were obtained both at rest and at submaximal exercise. BCG iK over the cardiac cycle (CC) increased significantly (0.0026 ± 0.0017 to 0.0052 ± 0.0061 mJ.s.; P = 0.01) during exercise, in contrast to a non‐significant increase in SCG iK CC. BCG Pmax CC increased significantly (0.92 ± 0.89 to 2.03 ± 1.95 mJ/s; P = 0.02), in contrast to a non‐significant increase in SCG Pmax CC. When analysing the systolic phase of the CC, similar patterns were found. Cardiac output (CO) ratio (i.e. CO exercise/CO rest) showed a moderate, significant correlation with BCG Pmax CC ratio (r = +0.65; P = 0.008) and with SCG Pmax CC ratio (r = +0.54; P = 0.04). Conclusions iK and Pmax measured with the KCG, preferentially using BCG, are responsive to changes in the haemodynamic load of the heart in HF patients. The combination of the BCG and SCG sensor might be of added value to fully understand changes in haemodynamics and to discriminate between an HF patient and a healthy individual.

Finding an appropriate method with the highest rate of polycyclic aromatic hydrocarbon (PAH) removal from naturally polluted soils is an important research issue. A pot factorial experiment (using contaminated soil samples from the Isfahan Refinery, Iran) was conducted in a 90-day period to compare the following bioremediation strategies: (1) natural attenuation (NA): the inherent ability of soil for bioremediation; (2) bioaugmentation (BA): inoculating soil with PAH degrading microbes Marinobacter hydrocarbonoclasticus; (3) biostimulation (BS): using N, P and K nutrients for the stimulation of bioremediating soil bacteria to achieve the C:N:P ratio of 100:10:1, and(4) bioaugmentation + biostimulation (BS + BA). Treatments NA (22.8%) and BA + BS (63.9%) resulted in the least and the highest rate of PAH removal from the soil. The 2-4 ring compounds had a significantly (P ≤ 0.05) higher rate of degradation than the 5-6 ring compounds. The highest rates were resulted by fluorene (76.41%) and acenaphthylene (72.28%) using the BA + BS treatment. However, the lowest degradation rates were resulted by indeno (1,2,3-cd) pyrene (10.05%), benzo [b] fluoranthene (10.17%), benzo (g, h, i) perylene (12.53%), and benzo [k] fluoranthene (13.67%), using NA treatment. The BA + BS treatments are the most effective method for the bioremediation of PAH polluted soils.

Introduction The identification of potentially mineralized areas has progressed with the use and interpretation of all available exploratory data in the form of mineral potential modeling (MPM) (Yousefi and Nykänen, 2017). Recently, machine learning methods have been a popular research topic in the field of MPM ((Chen and Wu, 2016). Machine learning algorithms that have been used in MPM generally fall into the categories of being supervised or unsupervised. Supervised models, use the location of the known mineral occurrences as training sites (or labeled data). Therefore, these models suffer stochastic bias and error (Zuo and Carranza, 2011). Unsupervised models classify mineral prospectivity of every location based solely on feature statistics of individual evidential data layers ((Abedi et al., 2012). The semi-supervised learning models are a hybrid of supervised and unsupervised learning models that use both labeled and unlabeled data to extract the hidden structure of the data, as well as the relation between the input exploration layers and the output labeled data (Fatehi and Asadi, 2017). The Dehsalm study area forms a part of the Lut metallogenic block of eastern Iran, which is characterized by the subduction zone setting and extensive magmatism (Beydokhti et al., 2015). The objective of this research is to present a prospectivity model to delineate exploration target areas for porphyry Cu-Au mineralization in the study area. For generating a prospectivity model, we used TSVM algorithm, a semi-supervised learning integration technique, to identify the anomalous areas related to the porphyry Cu-Au mineralization. The input layers are selected based on a conceptual model for porphyry Cu-Au mineral system. The performance of the mineral prospectivity maps (MPMs) is evaluated using the various techniques, including the receiver operating characteristic (ROC) curve, an area under curve (AUC) metric. Materials and methods To apply a process-based understanding of porphyry copper-gold deposit system on the mapping of prospectivity, a conceptual model must be first developed (Fatehi and Asadi, 2017). Such a model should depict critical scale-dependent processes involved in the mineral deposit formation, and a mineral system approach can be followed to aid understanding where, when and why mineral deposits form (Parsa et al., 2016). The spatial data sets used to model porphyry Cu-Au prospectivity of the study area include geological, remote sensing, geophysical, and geochemical data. In this study, semi-supervised support vector machine (TSVM) prospectivity technique is utilized to model porphyry Cu-Au target areas. The TSVM is an extension of SVM that uses the unlabeled data to improve the performances of the classifier. The aim of TSVM algorithm is to find the decision hyper-plane subject to maximize the margin distance in labeled and unlabeled data. Result In the present study, TSVM and SVM models were applied to Cu-Au prospectivity modeling in the study area. The models were trained based on the location of known Cu-Au mineralization occurrences and non-deposit location using e1071 package in R open-source statistical software (70% of the labeled data were used in training and 30% in the testing phase of learning in both algorithms). The RBF kernel function were used and the optimal values of the kernel parameters were assessed using a 10-fold cross-validation procedure and the best learning performance was selected by correct classification rate. The output of the models highlighted the target areas for porphyry Cu-Au mineralization in the study area. The receiver operating characteristics (ROC) analysis shows that both models perform well, however, the TSVM model yields the best performance. Discussion To identify exploratory target areas on a regional scale, various supervised and unsupervised approaches have been developed in mineral potential modeling. Supervised methods such as SVM use labeled data to classify exploratory datasets. In this research, a new semi- supervised learning method, TSVM, was applied to model the mineral potential for porphyry Cu-Au mineralization in the Dehsalm exploration zone. The introduced target areas by TSVM method, within the known mineral indices, covered smaller areas than targets identified by SVM model, so planning the detailed exploration phase will be optimal. The result of this research demonstrates the superiority of the semi-supervised learning method in identifying the target areas for planning the exploratory operations. Acknowledgements We would like to thank the Geological Survey of Iran for providing the exploration data used in this research. The financial support of the South Khorasan Industry, Mine & Trade Organization is gratefully thanked. References Abedi, M., Norouzi, G.H. and Bahroudi, A., 2012. Support vector machine for multi-classification of mineral prospectivity areas. Computers & Geosciences, 46: 272–283. https://doi.org/10.1016/j.cageo.2011.12.014 Beydokhti, R.M., Karimpour, M.H., Mazaheri, S.A., Santos, J.F. and Klötzli, U., 2015. U-Pb zircon geochronology, Sr-Nd geochemistry, petrogenesis and tectonic setting of Mahoor granitoid rocks (Lut Block, Eastern Iran). Journal of Asian Earth Sciences, 111: 192–205. https://doi.org/10.1016/j.jseaes.2015.07.028 Chen, Y. and Wu, W., 2016. A prospecting cost-benefit strategy for mineral potential mapping based on ROC curve analysis. Ore Geology Reviews, 74: 26–38. https://doi.org/10.1016/j.oregeorev.2015.11.011 Fatehi, M. and Asadi, H.H., 2017. Data integration modeling applied to drill hole planning through semi-supervised learning: A case study from the Dalli Cu-Au porphyry deposit in the central Iran. Journal of African Earth Sciences, 128: 147–160. https://doi.org/10.1016/j.jafrearsci.2016.09.007 Parsa, M., Maghsoudi, A., Yousefi, M. and Sadeghi, M., 2016. Prospectivity modeling of porphyry-Cu deposits by identification and integration of efficient mono-elemental geochemical signatures. Journal of African Earth Sciences, 114: 228–241. https://doi.org/10.1016/j.jafrearsci.2015.12.007 Yousefi, M. and Nykänen, V., 2017. Introduction to the special issue: GIS-based mineral potential targeting. Journal of African Earth Sciences, 128: 1–4. https://doi.org/10.1016/j.jafrearsci.2017.02.023 Zuo, R. and Carranza, E.J.M., 2011. Support vector machine: a tool for mapping mineral prospectivity. Computers & Geosciences, 37(12): 1967–1975. https://doi.org/10.1016/j.cageo.2010.09.014

Abstract Ballistocardiography (BCG) and Seismocardiography (SCG) assess the vibrations produced by cardiac contraction and blood flow, respectively, by means of micro-accelerometers and micro-gyroscopes. From the BCG and SCG signals, maximal velocities (VMax), integral of kinetic energy (iK), and maximal power (PMax) can be computed as scalar parameters, both in linear and rotational dimensions. Standard echocardiography and 2-dimensional speckle tracking imaging echocardiography were performed on 34 healthy volunteers who were infused with increasing doses of dobutamine (5–10–20 μg/kg/min). Linear VMax of BCG predicts the rates of left ventricular (LV) twisting and untwisting (both p

Abstract Background Kinocardiography (KCG) is a promising new technique used to monitor cardiac mechanical function remotely. KCG is based on ballistocardiography (BCG) and seismocardiography (SCG), and measures 12 degrees-of-freedom (DOF) of body motion produced by myocardial contraction and blood flow through the cardiac chambers and major vessels. Results The integral of kinetic energy ( $$ iK$$ iK ) obtained from the linear and rotational SCG/BCG signals was computed over each dimension over the cardiac cycle, and used as a marker of cardiac mechanical function. We tested the hypotheses that KCG metrics can be acquired using different sensors, and at 50 Hz. We also tested the effect of record length on the ensemble average on which the metrics were computed. Twelve healthy males were tested in the supine, head-down tilt, and head-up tilt positions to expand the haemodynamic states on which the validation was performed. Conclusions KCG metrics computed on 50 Hz and 1 kHz SCG/BCG signals were very similar. Most of the metrics were highly similar when computed on different sensors, and with less than 5% of error when computed on record length longer than 60 s. These results suggest that KCG may be a robust and non-invasive method to monitor cardiac inotropic activity. Trial registration Clinicaltrials.gov, NCT03107351. Registered 11 April 2017, https://clinicaltrials.gov/ct2/show/NCT03107351?term=NCT03107351&draw=2&rank=1 .

Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body’s center of mass and on the chest, respectively. Since their inception, their potential for evaluating cardiovascular health has been studied. However, both BCG and SCG are impacted by respiration, leading to a periodic modulation of these signals. As a result, data processing algorithms have been developed to exclude the respiratory signals, or recording protocols have been designed to limit the respiratory bias. Reviewing the present status of the literature reveals an increasing interest in applying these techniques to extract respiratory information, as well as cardiac information. The possibility of simultaneous monitoring of respiratory and cardiovascular signals via BCG or SCG enables the monitoring of vital signs during activities that require considerable mental concentration, in extreme environments, or during sleep, where data acquisition must occur without introducing recording bias due to irritating monitoring equipment. This work aims to provide a theoretical and practical overview of cardiopulmonary interaction based on BCG and SCG signals. It covers the recent improvements in extracting respiratory signals, computing markers of the cardiorespiratory interaction with practical applications, and investigating sleep breathing disorders, as well as a comparison of different sensors used for these applications. According to the results of this review, recent studies have mainly concentrated on a few domains, especially sleep studies and heart rate variability computation. Even in those instances, the study population is not always large or diversified. Furthermore, BCG and SCG are prone to movement artifacts and are relatively subject dependent. However, the growing tendency toward artificial intelligence may help achieve a more accurate and efficient diagnosis. These encouraging results bring hope that, in the near future, such compact, lightweight BCG and SCG devices will offer a good proxy for the gold standard methods for assessing cardiorespiratory function, with the added benefit of being able to perform measurements in real-world situations, outside of the clinic, and thus decrease costs and time.

Introduction Fluid inclusions are small, usually microscopic, volumes of pore fluid, which are crystallographically trapped in rocks during diagenesis or fracture healing processes. Nowadays, various techniques are used for resource exploration. Application of a fluid inclusion is one of these methods that has been developed for mineral, geothermal, and petroleum reservoir exploration. The study of fluid inclusions represents our most reliable source of information on the temperature, pressure, and fluid composition data of the ore fluid, and it is one of the most important tools for research into the economic geology and genesis of ore deposits (Moon, 1991). To achieve these goals, transparent and polished slabs of rock material are prepared and optically studied with a petrographic microscope. Samples are viewed under transmitted plane-polarized white light as well as under reflected ultraviolet or blue-violet illumination. During the fluid inclusion petrography, the volume fractions of phases are routinely estimated at room temperature to deduce whether assemblages of cogenetic inclusions were originally trapped from a one-phase or a multi-phase pore fluid. In the present research study, the microthermometric properties of the fluid inclusion data through pressure, temperature, and salinity diagrams were computed by geometrical modeling of fluid inclusion (Bakker and Larryn, 2006). The proposed method provides a quick and low cost technique to preliminarily investigate the microthermometric parameters of the fluid inclusion. To evaluate the proposed geometrical model, the Mehdiabad Pb-Zn deposit is selected as the case study. The Mehdiabad Pb-Zn deposit is located at the Yazd-Anarak metallogenic belt, 110 km southeast of Yazd, in the Central Iran structural zone. The host rocks of the deposit consist of lower Cretaceous silty limestone and dolomite. The main occurrences are the Calamine mine (CM), the Black-Hill ore (BHO), the East Ridge (ER) and the Central Valley Orebody (CVOB). The ore body consists of a primary sulfide ore and a supergene non-sulfide ore, the latter one having been mined at CM (Ghasemi, 2007; Rajabi et al., 2012). Materials and methods The shape and geometry of fluid inclusion are one of the most important parameters, which were applied to estimate 3D degree of filling and find the useful information about temperature, pressure, salinity and depth of trapping without using time-consuming and costly heating-cooling operation. Inclusions in normal thick-sections are rotated stepwise and their projected areas and area-fractions are plotted against rotation angle. The outputs are systematically related to inclusion orientation, inclusion shape, and filling degree. The dependency on orientation is minimized when area fractions are measured at the position where the inclusions project their largest total areas. The shape factor is employed to present a new objective classification of inclusion projections, based on the extracted parameters from digital image processing (Bakker and Larryn, 2006). In this research, Mehdiabad Pb-Zn deposit has been chosen to evaluate the proposed method. Based on the fluid inclusion petrography, four fluid inclusion types are observed: 1) L+V; 2) L+L; 3) L; and 4) V; L+V phase is the most popular. After preparing 2D image of sections, 2D and 3D degree of fills were calculated by measuring the areas of total, bubble, and spot of fluid inclusion and computing the third dimension (Z) of fluid inclusion. Four geometrical models of volume fractions are defined, including cylinder, tetragonal prism, truncated cone, hexagon, and ellipsoid (Bakker and Larryn, 2006; Hossein Morshedy et al., 2008). In this case study, 3D proper models of the fluid inclusions are selected, depending on its geometry (hexagonal or ellipsoid). Then 2D degrees of filling (area fraction) is converted to 3D degrees of filling (volume fraction). The geometrical modeling results are well matched with computational outputs. Results and discussion In this research, the ratios of area to volume fractions in geometrical and computational modelling were calculated 0.75 and 0.77, respectively. In the Mehdiabad Pb-Zn deposit, the main geometrical shapes of fluid inclusions were followed up the hexagonal prism with hexagonal pyramids and ellipsoid models. 3D geometrical modeling of fluid inclusion showed vapor fraction, 25% and density, 0.7 g/cm3, which the microthermometric and other parameters were obtained homogenization temperature nearly 100-200 °C (average of 150 °C), pressure between 400-500 ATM, formation temperature about 250-350 °C, salinity within a range of 10 to 15 wt.% NaCl equiv. and depth of mineralization 150-200 m. This finally achieved results have a high similarity with the typical carbonate-hosted Pb-Zn deposit. References Bakker, R.J. and Larryn, W.D., 2006. Estimation of volume fractions of liquid and vapor phases in fluid inclusions, and definition of inclusion shapes. American Mineralogist, 91(1): 635–657. Ghasemi, M., 2007. Genesis of Mehdiabad Pb–Zn deposit and comparing with other Pb–Zn deposits. M.Sc. Thesis, Research Institute for Earth Science, Geological Survey of Iran, Tehran, Iran, 238 pp. (in Persian with English abstract) Hossein Morshedy, A., Mojtahedzadeh, H. and Kohsary, A.H., 2008. Measuring microthermic parameters of fluid inclusion with studying their geometries and models, case study: Mehdiabad Pb–Zn deposit. 15th Symposium of Crystallography and Mineralogy of Iran, Ferdowsi University of Mashhad, Mashhad, Iran. (in Persian with English abstract) Moon, K.J., 1991. Application of fluid inclusions in mineral exploration. Journal of Geochemical Exploration, 42(1): 205–221. Rajabi, A., Rastad, E. and Canet, C., 2012. Metallogeny of Cretaceous carbonate-hosted Zn–Pb deposits of Iran: geotectonic setting and data integration for future mineral exploration. International Geology Review, 54(14): 1649–1672.

Introduction: Seismocardiography (SCG) records cardiac and blood-induced motions transmitted to the chest surface as vibratory phenomena. Evidences demonstrate that acute myocardial ischemia (AMI) profoundly affects the SCG signals. Multidimensional SCG records cardiac vibrations in linear and rotational dimensions, and scalar parameters of kinetic energy can be computed. We speculate that AMI and revascularization profoundly modify cardiac kinetic energy as recorded by SCG.Methods: Under general anesthesia, 21 swine underwent 90 min of myocardial ischemia induced by percutaneous sub-occlusion of the proximal left anterior descending (LAD) coronary artery and subsequent revascularization. Invasive hemodynamic parameters were continuously recorded. SCG was recorded during baseline, immediately and 80 min after LAD sub-occlusion, and immediately and 60 min after LAD reperfusion. iK was automatically computed for each cardiac cycle (iKCC) in linear (iKLin) and rotational (iKRot) dimensions. iK was calculated as well during systole and diastole (iKSys and iKDia, respectively). Echocardiography was performed at baseline and after revascularization, and the left ventricle ejection fraction (LVEF) along with regional left ventricle (LV) wall abnormalities were evaluated.Results: Upon LAD sub-occlusion, 77% of STEMI and 24% of NSTEMI were observed. Compared to baseline, troponins increased from 13.0 (6.5; 21.3) ng/dl to 170.5 (102.5; 475.0) ng/dl, and LVEF dropped from 65.0 ± 0.0 to 30.6 ± 5.7% at the end of revascularization (both p < 0.0001). Regional LV wall abnormalities were observed as follows: anterior MI, 17.6% (three out of 17); septal MI, 5.8% (one out of 17); antero-septal MI, 47.1% (eight out of 17); and infero-septal MI, 29.4% (five out of 17). In the linear dimension, iKLinCC, iKLinSys, and iKLinDia dropped by 43, 52, and 53%, respectively (p < 0.0001, p < 0.0001, and p = 0.03, respectively) from baseline to the end of reperfusion. In the rotational dimension, iKRotCC and iKRotSys dropped by 30 and 36%, respectively (p = 0.0006 and p < 0.0001, respectively), but iKRotDia did not change (p = 0.41). All the hemodynamic parameters, except the pulmonary artery pulse pressure, were significantly correlated with the parameters of iK, except for the diastolic component.Conclusions: In this very context of experimental AMI with acute LV regional dysfunction and no concomitant AMI-related heart valve disease, linear and rotational iK parameters, in particular, systolic ones, provide reliable information on LV contractile dysfunction and its effects on the downstream circulation. Multidimensional SCG may provide information on the cardiac contractile status expressed in terms of iK during AMI and reperfusion. This automatic system may empower health care providers and patients to remotely monitor cardiovascular status in the near future.

Introduction Nowadays, exploration of rare earth element (REE) resources is considered as one of the strategic priorities, which has a special position in the advanced and intelligent industries (Castor and Hedrick, 2006). Significant resources of REEs are found in a wide range of geological settings, including primary deposits associated with igneous and hydrothermal processes (e.g. carbonatite, (per) alkaline-igneous rocks, iron-oxide breccia complexes, scarns, fluorapatite veins and pegmatites), and secondary deposits concentrated by sedimentary processes and weathering (e.g. heavy-mineral sand deposits, fluviatile sandstones, unconformity-related uranium deposits, and lignites) (Jaireth et al., 2014). Recent studies on various parts of Iran led to the identification of promising potential of these elements, including Central Iran, alkaline rocks in the Eslami Peninsula, iron and apatite in the Hormuz Island, Kahnouj titanium deposit, granitoid bodies in Yazd, Azerbaijan, and Mashhad and associated dikes, and finally placers related to the Shemshak formation in Marvast, Kharanagh, and Ardekan indicate high concentration of REE in magmatogenic iron–apatite deposits in Central Iran and placers in Marvast area in Yazd (Ghorbani, 2013). Materials and methods In the present study, the geochemical behavior of rare earth elements is modeled by using multivariate statistical methods in the eastern part of the Marvast placer. Marvast is located 185 km south of the city of Yazd in central Iran between Yazd and Mehriz. This area lies within the southeastern part of the Sanandaj-Sirjan Zone (Alipour-Asll et al., 2012). The samples of 53 wells were analyzed for Whole-rock trace-element concentrations (including REE) by inductively coupled plasma-mass spectrometry (ICP-MS) (GSI, 2004). The clustering techniques such as multivariate statistical analysis technique can be employed to find appropriate groups in data sets. One of the main objectives of data clustering is to maximize both the similarity within each cluster and the difference between clusters, and finally find the structure in the data. Nowadays, cluster analysis is applied in many disciplines: biology, botany, medicine, psychology, geography, marketing, image processing, psychiatry, archaeology, etc. (Everitt et al., 2011). To execute a partitioning algorithm, the principal components analysis (PCA) algorithm is applied for feature selection, feature extraction and dimension reduction. Hierarchical clustering can be utilized to provide a nested sequence of partitions with bottom-up or top-down methods based on similarity. The single linkage and complete linkage are the most popular hierarchical algorithms (Jain et al., 1999; Ji et al., 2007). Results and discussion The REE chondrite-normalized pattern for the eastern area in the Marvast placer represents a high match to the standard pattern of monazite. This pattern shows the positive anomaly of Ce and the negative anomaly of Eu. To determine the distribution of REEs concentration, 2D interpolation maps were plotted in three groups of light, middle, and heavy REEs (LREE, MREE, and HREE), which were indicated in the geochemical anomaly at the south and south-west of the area. The relative ratios of (LREE/HREE) and (Ce/Eu) exposed the high proportion of LREEs to HREEs. In the next section, the hierarchical clustering algorithm was employed to partition the data in the feature and sample levels. The elements portioning demonstrated four separated groups, which can be related to atomic and chemical structures. The studied region was divided into four zones by the clustering approach. The fourth zone confine coincided with the REE anomaly area. Finally, PCA was applied as the multivariate statistical tool to this dataset. Hence three principal components modeled over 90% of the variance. For the first component, the distribution map of load factor has a good agreement with anomaly area. References Alipour-Asll, M., Mirnejad, H. and Milodowski, A.E., 2012. Occurrence and paragenesis of diagenetic monazite in the upper Triassic black shales of the Marvast region, South Yazd, Iran. Mineralogy and Petrology, 104(3-4): 197-210. Castor, S.B. and Hedrick, J.B., 2006. Rare earth elements. In: J.E. Kogel (Editors), Industrial minerals & rocks: commodities, markets, and uses. Society for mining, metallurgy, and exploration, Inc. (SME), Colorado, pp. 769-792. Everitt, B., Landau, S., Leese, M. and Stahl, D., 2011. Cluster Analysis. 5th ed., Wiley Publishing, Hoboken, Geological Survey of Iran (GSI), 2004. Exploration of rare earth element and monazite in the alluvium of the southern Marvast (eastern area). Tehran, 66 pp. (in Persian) Ghorbani, M., 2013. The economic geology of Iran: mineral deposits and natural resources. Springer, London, 569 pp. Jain, A.K., Murty, M.N. and Flynn, P.J., 1999. Data clustering: a review. Association for Computing Machinery computing surveys, 31(3): 264-323. Jaireth, S., Hoatson D.M. and Miezitis Y., 2014. Geological setting and resources of the major rare-earth-element deposits in Australia. Ore Geology Reviews, 62: 72-128. Ji, H., Zeng, D., Shi, Y., Wu, Y. and Wu, X., 2007. Semi-hierarchical correspondence cluster analysis and regional geochemical pattern recognition. Journal of Geochemical Exploration, 93(2): 109-119.

Recent years have witnessed an upsurge in the usage of ballistocardiography (BCG) and seismocardiography (SCG) to record myocardial function both in normal and pathological populations. Kinocardiography (KCG) combines these techniques by measuring 12 degrees-of-freedom of body motion produced by myocardial contraction and blood flow through the cardiac chambers and major vessels. The integral of kinetic energy (iK) obtained from the linear and rotational SCG/BCG signals, and automatically computed over the cardiac cycle, is used as a marker of cardiac mechanical function. The present work systematically evaluated the test–retest (TRT) reliability of KCG iK derived from BCG/SCG signals in the short term (SCG and BCG recordings. Exceptions to this finding were limited to metrics computed in left lateral decubitus position where the TRT reliability was moderate-to-high. Second, we found low-to-moderate long-term TRT reliability for KCG metrics as expected and confirmed by blood pressure measurements. In summary, KCG parameters derived from BCG/SCG signals show high repeatability and should be further investigated to confirm their use for cardiac condition longitudinal monitoring.

Comparing the absorption and translocation efficiency of the nutrients in olive cultivars can lead to the selection of cultivars with higher efficiency. This research was conducted with the aim of comparing the uptake and translocation capacity in 20 olive cultivars (12 domestic and 8 foreign) in a commercial orchard on calcareous soil in a randomized complete block design. Except for copper (Cu), leaf concentration of other elements was within the optimal range. In ʻAmphesis,ʼ high translocation (5.28%) and in ʻAmigdalolia,' high uptake capacity (12.6) caused an increase in leaf phosphorus (P). Leaf K in all cultivars was higher than the deficiency limit (0.77%). In none of the cultivars, leaf sodium (Na) concentration was higher than the toxicity limit (0.2%), it accumulated in the root of ʻZard-Aliabadʼ and ʻShengeh,ʼ and reduced in their leaf. Leaf iron (Fe) concentration of all cultivars was in the sufficient range (>63 mg kg−1) and the highest was in ʻGorgan-Aʼ and ʻZardʼ and the lowest in ʻKazeroon,ʼ ʻArbequinaʼ and ʻMission.ʼ Although the leaf Cu in ʻAmphesisʼ (4.32 mg kg−1) and ʻArbequinaʼ (4.03 mg kg−1) was above the sufficient limit, in the rest of the cultivars it was below this critical limit. The highest leaf manganese (Mn) concentration (61.35 mg kg−1) and the highest Mn translocation percentage (84.59) were in ʻFeshomi.ʼ Among these cultivars, ʻAmphesisʼ was higher than others in terms of P, potassium (K), Cu and zinc (Zn) leaf concentrations and ʻAmigdalolia in terms of P, K and Zn, and in most cases the reason for this is the higher translocation efficiency. [ABSTRACT FROM AUTHOR]

The main objective of this investigation is the consolidation and flexural strength of alpha silicon carbide ceramics produced without additives by spark plasma sintering. Using the design of the experiment method, we optimized temperature and dwell to achieve fully dense silicon carbide bulks. The consolidation process of silicon carbide was analyzed similarly to the creep of bulk ceramics, and it was determined that the activation energy for the densification process was 596 ± 39 kJ/mol, while the stress exponent n was below 2. Bulk additive‐free silicon carbide ceramics gradually increased flexural strength as the temperature rose to 2000°C. The flexural strength at 2000°C was influenced by the loading rate, and under 2.5 mm/min, it reached a maximum of 2.08 GPa. To explain this phenomenon, a deformation mechanisms map was created, indicating that diffusion creep is the most probable mechanism for the strain sensitivity of SiC at 2000°C. Transmission electron microscopy indicated a substantial rise in twin density within the α‐SiC grains at 2000°C, indicating the activation of a previously unreported self‐reinforcing mechanism. [ABSTRACT FROM AUTHOR]

Antiferromagnetic Mn3X (X = Sn, Ge, Ga, and Pt) possessing non-collinear spin structures with Kagome lattices have attracted increasing interest because of their unique properties, such as significant anomalous Hall and magneto-optical Kerr effects. Recent advances in spintronic devices that use non-collinear antiferromagnets have inspired research into various materials for exploiting their potential. In this study, we investigated the magnetic and magneto-transport properties of 1 1 ̄ 00 -oriented epitaxial and polycrystalline Mn3Ge films deposited by magnetron sputtering. Anomalous Hall conductivity monotonically decreases with temperature in an epitaxial Mn3Ge film, whereas the polycrystalline sample demonstrates a different trend. Furthermore, we obtained a large in-Kagome-plane uniaxial magnetic anisotropy of epitaxial Mn3Ge above ambient temperature, thereby leading to higher thermal stability and robustness against the external field. Our results indicate the potential of Mn3Ge for future functional, high-speed, and high-density spintronics devices using antiferromagnets. [ABSTRACT FROM AUTHOR]