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Railroad is one of the primary modes to transport hazardous materials (hazmat) in North America. For instance, Canadian railroads carried around 50 million tons of hazmat in 2018. Given the inherent danger of trains carrying hazmat, this study aimed at exploring a novel way towards mitigation of the associated risk. This study sought to investigate whether proper rail track infrastructure investment can mitigate the risk from hazmat shipments. To this end, a methodology was developed and then applied to the Canadian railroad network. The proposed three-step methodology captured the differing perspectives of rail carriers and regulatory agencies, and entailed (1) ascertaining the risk-level of various yards and links in the given railroad network, (2) specifying potential candidates for infrastructure investment, and (3) finding the optimum set of investment decisions. The proposed methodology was then applied to the Canadian railroad network to demonstrate that significant risk-reduction can be achieved by adding alternative rail-links around the riskiest locations (i.e. the network hot-spots), and also to show that risk-reduction function is non-linear with non-monotonous behavior. The study showed the possibility of significant hazmat risk reduction through alternative rail-links that could take traffic away from the network hot-spots. The methodology and the results from the Canadian case can be used by railroad companies and policy makers to estimate the value of potentially risk-reducing infrastructure investments.

Suspended sediment load is an indicator of erosion in watersheds. Therefore, accurately estimating the daily suspended sediment load (DSSL) is an important issue in river engineering. In this research, Artificial Neural Networks (ANN), Genetic Expression Programming (GEP) intelligent models, and the traditional Sediment rating curve (SRC) model were used to estimate DSSL in the Kasilian and Rood Zard watersheds in Iran. The input data to the models included instantaneous flow discharge (Q), average daily flow discharge (Qi), average daily flow discharge with a delay of three days (Qi-1,Qi-2,Qi-3), average daily precipitation (Pi), and average daily precipitation with a delay of three days (Pi-1,Pi-2,Pi-3); the output data was DSSL. In this research, the selforganizing map (SOM) artificial neural network was used for data clustering, and gamma test (GT) methods were used to obtain the best combination of input variables to intelligent models. The results showed that the best models for estimating DSSL in the Kasilian and Rood Zard watersheds were respectively the ANN model with an activation function of tangent sigmoid with the best combination of input variables (Qi-1,Qi-2,Qi-3,Pi,Pi-1,Pi-2,Pi-3) and the GEP model with the input variables Qi,Qi-1,Qi-2,Pi,Pi-1,Pi-2,Pi-3. The statistical values of the ANN-tangent sigmoid model for the Kasilian watershed were MAE=231.4 (ton day-1), RMSE=578.6 (ton day-1), NSE =0.98, and R²=0.98; these values for the GEP model in the Rood Zard watershed were MAE=475.7 (ton day-1), RMSE=1671.9 (ton day-1), NSE=0.99, and R²=0.99. The SRC model in the Kasilian watershed with R²=0.34 and NSE=0.08 and the Rood Zard watershed with R²=0.59 and NSE=-0.11 showed the low accuracy of this model in estimating DSSL. [ABSTRACT FROM AUTHOR]

Tessier clefts are skeletal and soft tissue abnormalities of a neonate's facial structures. They could be classified as syndromic and non-syndromic clefts, which can be attributed to disruptions in fetal development and genetic mutations, respectively. Reported cases of these clefts typically document the presence of additional abnormalities associated with these clefts. In this systematic review, we analyzed reports of Tessier clefts accompanied by cardiovascular anomalies, as one of the commonly encountered anomalies. We systematically searched PubMed (MEDLINE), Scopus, Web of Science, Science Direct, and Google Scholar. We selected and included case reports, case series, and case reviews on patients with Tessier cleft and cardiovascular anomalies. The critical appraisal of the included studies was performed by two independent investigators using the Consensus-based Clinical Case Reporting Guideline Development (CARE) checklist. Overall, 20 reports (18 case reports and 2 case series) were eligible for inclusion in this review. Tessier clefts 3 and 30 were the most commonly observed. In addition, the most prevalent cardiovascular anomalies consisted of the ventricular septal defect (VSD), double-outlet right ventricle, and atrial septal defect (ASD). Most of the patients received cosmetic and cardiovascular surgeries. However, some were not proper candidates for cardiovascular surgery because of their unstable condition and therefore did not survive. Conclusion: Regardless of the focus placed on the cleft and subsequent plastic surgery procedures in these cases, it is important to prioritize other abnormalities that may be associated with mortality. A complete cardiovascular system and associated disorders assessment should be performed before facial cosmetic surgeries. What is Known: • Tessier clefts are congenital defects in the soft tissues and bones of the face and like many other congenital defects, they are accompanied by defects in other parts of the body. • In the current literature, the emphasis is on clefts and the cosmetic issues rather than the coinciding defects, particularly cardiovascular anomalies. What is New: • Review the cardiovascular anomalies that are commonly encountered in patients with Tessier clefts. [ABSTRACT FROM AUTHOR]

This study was conducted in a company that produces palm oil-based products such as cooking oil and margarine. The study aimed to encounter defects in packaging pouches. This study integrated the overall equipment effectiveness (OEE) with the six sigma DMAIC method. The OEE was performed to measure the efficiency of the machine. Three factors were measured in OEE: availability, performance, and quality. These factors were calculated and compared to the OEE world-class value. Then, the Multiple Linear Regression was performed using SPSS to determine the correlation between measurement variables toward the OEE value. Lastly, the six sigma method was implemented through the DMAIC approach to find the solution and improve the packaging quality. Supposing the recommendations are implemented, the OEE is expected to increase from 82% to 85%, with availability ratio, performance ratio, and quality ratio at, 99%, 86%, and 99.8%, respectively. [ABSTRACT FROM AUTHOR]

The changing and intensifying landscape of global, national, and local disaster risks, driven by socio-political, environmental, and technological shifts, underscores the critical need for risk assessment by international agencies and governments. The Risk Matrix, introduced in 1995, has been widely used for risk assessment in different contexts, lauded for its simplicity and effectiveness. This model relies on the core risk components of consequence and likelihood, making it a favored tool for risk managers. To enhance the precision of risk assessment, various adaptations and extensions of the risk matrix have emerged; while some indirectly address resilience aspects, none explicitly integrate resilience into the matrix. This paper explores the risk matrix and its extensions, advocating for the inclusion of resilience in risk assessment. It introduces an empirical approach to quantify resilience, through a survey targeting small and medium-sized businesses in Southern Ontario, Canada. By developing two types of risk matrices--one with resilience considerations and one without--our work demonstrates how resilience alters risk prioritization, highlighting the importance of preparedness. This research underscores the pivotal role of resilience in risk assessment and urges its explicit integration into risk matrices to enhance accuracy and efficacy. Through practical examples and empirical data, the paper builds a compelling case for the central role of resilience in modern risk assessment practices. [ABSTRACT FROM AUTHOR]

Due to the limited number and sparse distribution of meteorological and hydrometric stations in most watersheds, the runoff estimation based on these stations may not be accurate. However, the accurate determination of the Antecedent Soil Moisture (ASM) in watersheds can improve the accuracy of runoff forecasting. The objective of this study is to utilize the ASM derived from satellite imagery to enhance the accuracy of runoff estimation in a mountainous watershed. In this study, a range of Remote Sensing (RS) data, including surface biophysical and topographic features, climate data, hydrometric station flow data, and a ground-based measured SM database for the Balikhli-Chay watershed in Iran, were utilized. The Soil Conservation Service Curve Number (SCS-CN) method was employed to estimate runoff. Two approaches were used for estimating the ASM: (1) using the precipitation data recorded in ground stations, and (2) using the SM data obtained from satellite images. The accuracy of runoff estimation was then calculated for these two scenarios and compared. The mean Nash–Sutcliffe statistic was found to be 0.63 in the first scenario and 0.74 in the second scenario. The inclusion of ASM derived from the satellite imagery in the precipitation–runoff model resulted in a 51% increase in the accuracy of runoff estimation compared to using precipitation data recorded in ground stations. These findings have significant implications for improving the accuracy of ASM and runoff modeling in various applications. [ABSTRACT FROM AUTHOR]

Migraine headaches are highly prevalent, affecting 15% of the population. However, despite many studies to determine this disease's mechanism and efficient management, its pathophysiology has not been fully elucidated. There are suggested hypotheses about the possible mediating role of mast cells, immunoglobulin E, histamine, and cytokines in this disease. A higher incidence of this disease in allergic and asthma patients, reported by several studies, indicates the possible role of brain mast cells located around the brain vessels in this disease. The mast cells are more specifically within the dura and can affect the trigeminal nerve and cervical or sphenopalatine ganglion, triggering the secretion of substances that cause migraine. Neuropeptides such as calcitonin gene-related peptide (CGRP), neurokinin-A, neurotensin (NT), pituitary adenylate-cyclase-activating peptide (PACAP), and substance P (SP) trigger mast cells, and in response, they secrete pro-inflammatory and vasodilatory molecules such as interleukin-6 (IL-6) and vascular endothelial growth factor (VEGF) as a selective result of corticotropin-releasing hormone (CRH) secretion. This stress hormone contributes to migraine or intensifies it. Blocking these pathways using immunologic agents such as CGRP antibody, anti-CGRP receptor antibody, and interleukin-1 beta (IL-1ß)/interleukin 1 receptor type 1 (IL-1R1) axis-related agents may be promising as potential prophylactic migraine treatments. This review is going to summarize the immunological aspects of migraine. [ABSTRACT FROM AUTHOR]

Introduction: Over consumption of salt adversely affects health and is associated with some diseases. Salt over consumption has been reported to be higher in Asian countries including Iran. This research aimed to identify the facilitative factors of reduced salt consumption among 20–65 year-old women to develop effective educational interventions. Methods: This research used qualitative content analysis. We included 42 (31 women aged 20–65 years residing in Hamidia, Yazd and 11 healthcare providers) using Purposeful sampling method. Data were collected through focal group discussions (three groups of 6) and in-depth semi-structured individual interviews with 24 Participants. Data analysis was done using Graneheim and Lundman's approach. Results: Motivators and facilitators were extracted. The former consisted of sub-categories: physical fitness and healthcare, obtaining others' approval, family cooperation and support, internal motivators, contextual motivators and healthcare staff support. Sub-categories of the latter were gaining more information from different instructions, willingness to acquire self-protection skills and nutritional advice. These factors affected to reduce the salt intake among women. Conclusion: In the light of the qualitative results of motivating and facilitating factors, it is essential to enhance internal motivators and increase access to information via different communicative channels in community including schools, medical care providers and public associations. It is also necessary to pave the way for more family and medical staff support, provide appropriate educational and advertising programs, raise women's awareness and change their attitude and behavior with this concern. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is believed to be an impressive factor in hydrological process, agricultural productivity, and monitoring dangerous outcomes of climate changes. The present study aimed to monitor and recognize the pattern of spatial and temporal variation of SMAP soil moisture in five subcatchments of Simineh-Zarrineh catchment in northwest of Iran from 2015 to 2017. Precipitation data of 35 meteorological stations and 287 soil moisture points were derived from the SMAP and used to monitor SM variations in the time scale. The results indicated that the SM variations are subject to precipitation variations throughout the monthly scale in the catchment. In all the seasons of this period, SM was found to have a decreasing trend from north to south of the catchment. On the contrary, no such constant pattern was observed from east to west. Oscillation SM patterns in this period were completely coordinated with the precipitation pattern. The determination coefficient between monthly SMAP soil moisture and precipitation for each subcatchment was 0.9, 0.83, 0.7, 0.84, and 0.71 for Bokan, Saqqez, Takab, Saeinqaleh, and Miandoab subcatchments, respectively. Spatial variability of standard deviation for SM values was used to find the amount of deviation from the average value during dry and wet seasons. The results revealed that in the seasonal scale, northwestern (0.067 to 0.069 cm³.cm³) and eastern parts (0.057 to 0.061 cm³.cm³) of the study area had higher values of the SM standard deviations in autumn. Additionally, according to the findings, a high value of standard deviation was observed in autumn because of irregular precipitation events and fluctuation of the temperature. [ABSTRACT FROM AUTHOR]

Background and Objective: Metabolic syndrome, especially prediabetes, is one of the most common health problems due to incomplete glucose metabolism that has a direct relationship with lifestyle. This study was conducted to determine the factors that enable and nurture physical activity in women with prediabetes based on the PEN-3 model. Material and Method: This descriptive-analytical study was conducted on 41 prediabetic women aged 30–65 years and 9 service providers in health centers. Data were collected from a semi-structured individual interview based on the PEN-3 model. The Graneheim and Lundman method was used to analyze the data. Results: During data analysis, two main themes that include enabling factors and nurturing factors in the domain of physical activity and 6 classes including enablers (positive, negative, and existential) and nurturers (positive, negative, and existential) were extracted from the data content. Conclusion: By determining enablers and nurturers, the providers of services can facilitate the participation of prediabetic women in physical activity by applying positive social and structural effects and also to eliminate negative environmental conditions. [ABSTRACT FROM AUTHOR]

Soil moisture is an influential parameter in land surface hydrology and precise soil moisture data that can help researcher to realize the climate changes and land-atmosphere interactions. A initial struggle for the utilize of soil moisture data from satellite sensors is their reliability. It is important to appraise the dependability of those data before they can be regularly used at a global or local scale. In this study, the satellite soil moisture data was evaluated from the Soil Moisture Active/Passive (SMAP) over Simineh-Zarrineh Catchment in Bokan region, NW of Iran. A total of 287 soil samples as ground-based observations in the time period of 03 April to 03 December 2017 were taken for SMAP data validation. Results showed that the satellite data and in situ observation has a good correlation, with a mean correlation (r) value of 0.63 in total. This correlation level showed that, commonly, the SMAP soil moisture products over Simineh-Zarrineh Catchment (Bokan) have great quality, and it would be valuable for versatile utilization, including monitoring of land surface, weather prediction, modeling of hydrological process, soil loess monitoring, and climate studies. The results reveal that the remotely sensed data demonstrate the good correlation with in situ observation across the dry land with mean correlation (r) values of 0.67 throughout the time period. Particularly, SMAP soil moisture reveal a constant structure for obtain the spatial distribution of surface soil moisture. Additional researches are necessary for well realizing the SMAP data. [ABSTRACT FROM AUTHOR]

Interrill erodibility can be affected by soil aggregates, especially by those aggregate size classes that are dominant in the soil. In the Water erosion Prediction Project (WEPP) model, interrill soil erodibility (K i ) is estimated using very fine sand content. Despite that some studies have indicated an effect of aggregate stability on the K i , information on the relationship between the aggregate size class and K i and factors controlling it, particularly in semi-arid region is limited. This study was conducted to determine the variation of K i for different aggregate size classes under various rainfall intensities and evaluation of the WEPP model in estimating the K i for different aggregate fractions. Five aggregate size classes (0.25–2, 2–4.75, 4.75–5.6, 5.6–9.75 mm, and 9.75–12.7 mm) were separated from a sandy clay loam soil sampled in an agricultural land and put in laboratory flumes of 100 cm × 50 cm. The flumes were placed on a 9% slope and exposed to ten sequential rainfall simulations varying from 10 to 60 mm h −1 for 30 min. The K i of each aggregate size classes was determined using the interrill sediment delivery rate and compared this with the values estimated using WEPP. All physicochemical properties were also determined in the aggregate size classes. Organic matter content in the aggregate size classes was very low (0.65–0.73%) and didn't show strong relationships with the aggregate stability and hydraulic conductivity, whereas clay was major factor controlling determining these properties for the different aggregate fractions. Significant differences were found among the aggregate size classes in clay content ( P  < 0.05), aggregate stability measured using both wet-sieving method ( P  < 0.05) and water drop test method P  < 0.05, saturated hydraulic conductivity (K s ), and measured K i ( P  < 0.05). The measured K i was about 34 and 90 times bigger than the estimated K i for the fine aggregates and coarse aggregates, respectively. The fine aggregates showed higher susceptibility to interrill detachment with increasing rainfall intensity as compared with the coarse aggregates. Significant decrease was observed in the measured K i with increasing the aggregate size which was associated with increases in clay content, aggregate stability and K s . The stability of aggregates against raindrop impact (CND) was an important indicator describing the effect of aggregate size on the interrill erodibility in semi-arid soils. Therefore, this indicator can be taken into account as a soil structure measure to develop a proper equation for estimating interrill erodibility (K i ) for agricultural lands. The minimum use of tillage practices is essential to prevent aggregate breakdown and control interrill erosion in semi-arid regions. [ABSTRACT FROM AUTHOR]

Land abandonment is widespread in the Mediterranean mountains. The impact of agricultural abandonment results in a shift in ecosystem evolution due to changes in soil erosion, but little is known about long-term soil and water losses. This paper uses 11 years of measurements in two paired plots (abandoned vs control) with four subplots to determine how soil and water losses evolved after abandonment within an agricultural parcel. For two years (2004–2005) both plots were under tillage, and after 2006 one plot was abandoned. The monitored plots measured runoff and sediment concentration after each rainfall event. The results show that during the two years after abandonment there was an increase in sediment yield followed by a decrease. Once the field was abandoned, a sudden increase in runoff (× 2.1 times) and sediment concentration (× 1.2 times) was found due to the lack of vegetation and tillage. After one year, the sediment concentration and, after two years, the runoff rates were lower in the abandoned than in the tilled plots. This short transition period ended in contrasting responses between the control and abandoned plot as the impact of abandonment resulted in 21 times less sediment yield after nine years of abandonment. This occurred despite the fact that the year after the abandonment the abandoned plot had 2.9 times more erosion due to low vegetation recovery and the development of a soil crust. Agriculture land abandonment resulted in lower erosion rates over the long term, but showed an increase in soil and water losses over the short term (two years). Therefore, in the first two years after abandonment there is a particular need to apply nature-based soil and water conservation strategies to prevent soil erosion. [ABSTRACT FROM AUTHOR]

Objective: Problem-solving ability is one of the most important means of family stability that enables the families to understand their roles, functions, and performances. Self-efficacy deficiency in problem-solving runs through many families. This qualitative study was conducted to investigate and describe how couples solve problems in their families. Method: This study was conducted to detect couples' self-efficacy deficiency in problem-solving using purposive sampling method. Several deep semi-structured interviews based on McMaster model and observations were conducted by nine family therapists and psychiatrists on four couples (eight persons) living in Yazd (Iran). The interviews were performed, audio-recorded, and transcribed verbatim. The analysis was interpreted through directed content analysis methods. Results: Families in Yazd (Iran) made some attempts to solve their problems, but their efforts were not enough, and thus they suffered from self-efficacy deficiency, which included 8 categories. The main theme distilled from the data of 17 participants was self-efficacy deficiency, which included the following categories: avoidance, insolvency, interference from others, ineffective self-treatment, behavioral problems, stubbornness, superficiality, and denial . Conclusion: It is of paramount importance to identify self-efficacy deficiency in families and promote problem- solving programs to increase family stability. In the present study, the main deficiencies in problem-solving were detected. [ABSTRACT FROM AUTHOR]

Check dams can be used as a source of information for studies on sediment characteristics and soil particle erodibility. In this study, sediment yield and grain size distribution (GSD) were measured in twenty small catchments draining into a rock check dam in NW Iran for different runoffs during 2010–2011. Significant correlations were found between sediment yield and slope steepness, vegetation cover and soil erodibility factor (K) of the catchments. The erodibility of soil particles was determined using the comparison of GSD between sediment and original soil. Clay was the most erodible soil particle which showed 2.05 times more percentage in sediment than the original soil. The erodibility of soil particles were strongly affected by the rainfall erosivity (EI 30 ). Check dams showed more effectiveness in trapping coarse particles (sand and gravel). The effectiveness of check dams in trapping coarse particles enhanced with increase in the remaining capacity of check dams. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular diseases are the world’s leading cause of mortality. These diseases are rooted in an unhealthy lifestyle. In order to confront this subject, it is essential to identify several risk factors that contribute to heart disease (HD) in people with different attitudes, values, beliefs, expectations and motivations. This study was therefore an attempt to explain the adaptive experiences of children whose parents were involved in myocardial infarction since they were more likely subjected to get the so-called disease. Objective: To identify the risk factors and to clear ambiguity using a qualitative research method from the experiences of people at risk of the above mentioned disease. Methods: This qualitative study was a directed content analysis. Eighteen children (above 18 years old) of parents with a history of myocardial infarction participated, and were chosen with purposive sampling and the highest diversity. Data were collected through deep and semi structure interviews based on Protection Motivation Theory (PMT) from March to November 2015, and were analyzed along with their data collection and with usage of Lundman and Graneheim method. Interviews were conducted in non-stressful conditions with a place and time agreement. Results: During content analysis process, 220 codes were extracted. After reviewing several times and summarizing, the codes were categorized based on similarity and proportion, and finally 12 subcategories and three categories were elicited including efforts to perform self-care in order to prevent HD, poor life style as a factor not to do preventive HD and health continuation with positive changes in life style. Conclusions: Most participants, despite intending to do self-care behaviors to prevent HD, due to factors such as time constraint, high costs, laziness, impatience and prioritizing other life affairs, did not pay attention to their health. Therefore, providing the training programs with an emphasis on life skills can play an important role in reducing perceived response cost and promoting health. [ABSTRACT FROM AUTHOR]

Modeling sediment yield is a complex task because of the nonlinearity of natural processes intervening at slope and basin scale. In this study slope steepness, vegetation cover, and soil properties along with sediment yield were studied in 20 pasture micro-catchments in a semi-arid region, NW Iran in order to understand and predict sediment yield. The micro-catchments included only one first-order gully and drain toward a rock check dam in the outlet. The sediment yield of each micro-catchment was calculated using the measurement of sediment mass in the check dams for a 16-year period (1994-2010). Relationships between sediment yield and drainage characteristics were analyzed using correlation matrix and multiple linear regression method. Based on the results, sediment yield in the micro-catchments varied from 0.29 Mg ha−1 y−1 to 14.81 Mg ha−1 y−1, with an average of 5.04 Mg ha−1 y−1. It was significantly related to slope steepness, vegetation cover, and soil organic matter using a linear regression equation ( R2 = 0.87, p < 0.001). The slope, vegetation, and soil organic matter explained about 44%, 23%, and 20% of total variance in sediment yield, respectively. The spatial validation of the model using data from eight different micro-catchments located nearby showed that the model efficiency is 0.94. Therefore, the model can be used for predicting sediment yield in this and similar study area, with a high degree of accuracy. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Soil erosion by water is a three-phase process that consists of detachment of soil particles from the soil mass, transportation of detached particles either by raindrop impact or surface water flow, and sedimentation. Detachment by raindrops is a key component of the soil erosion process. However, little information is available on the role of raindrop impact on soil losses in the semi-arid regions where vegetation cover is often poor and does not protect the soil from rainfall. The objective of this study is to determine the contribution of raindrop impact to changes in soil physical properties and soil losses in a semiarid weakly-aggregated agricultural soil. Soil losses were measured under simulated rainfalls of 10, 20, 30, 40, 50, 60 and 70 mm h − 1 , and under two conditions: i) with raindrop impact; and, ii) without raindrop impact. Three replications at each rainfall intensity and condition resulted in a total of 42 microplots of 1 m × 1.4 m installed on a 10% slope according to a randomized complete block design. The contribution of raindrop impact to soil loss was computed using the difference between soil loss with raindrop impact and without raindrop impact at each rainfall intensity. Soil physical properties (aggregate size, bulk density and infiltration rate) were strongly damaged by raindrop impact as rainfall intensity increased. Soil loss was significantly affected by rainfall intensity under both soil surface conditions. The contribution of raindrop impact to soil loss decreased steadily with increasing rainfall intensity. At the lower rainfall intensities (20–30 mm h − 1 ), raindrop impact was the dominant factor controlling soil loss from the plots (68%) while at the higher rainfall intensities (40–70 mm h − 1 ) soil loss was mostly affected by increasing runoff discharge. At higher rainfall intensities the sheet flow protected the soil from raindrop impact. [ABSTRACT FROM AUTHOR]

Accurate information on soil moisture (SM) is critical in various applications including agriculture, climate, hydrology, soil and drought. In this paper, various predictive relationships including regression (Multiple Linear Regression, MLR), machine learning (Random Forest, RF; Triangular regression, Tr) and spatial modeling (Inverse Distance Weighing, IDW and Ordinary kriging, OK) approaches were compared to estimate SM in a semi-arid mountainous watershed. In developing predictive relationship, Remote Sensing datasets including Landsat 8 satellite imagery derived surface biophysical characteristic, ASTER digital elevation model (DEM) derived surface topographical characteristic, climatic data recorded at the synoptic station and in situ SM data measured at Landsat 8 overpass time were utilized, while in spatial modeling, point-based SM measurements were interpolated. While 70%(calibration set) of the measured SM data were used for modeling, 30%(validation set) were used to evaluate modeling accuracy. Finally, the SM uncertainty maps were created for different models based on a bootstrapping approach. Among the environmental parameter sets, land surface temperature (LST) showed the highest impact on the spatial distribution of SM in the region at all dates. Mean R2(RMSE) between measured and modeled SM on three dates obtained from the MLR, RF, IDW, OK, and Tr models were 0.70(1.97%), 0.72(1.92%), 0.59(2.38%), 0.59(2.27%) and 0.71(1.99%), respectively. The results showed that RF and IDW produced the highest and lowest performance in SM modeling, respectively. Generally, the performance of RS-based models was higher than interpolation models for estimating SM due to the influence from combination of topographic parameters and surface biophysical characteristics. Modeled SM uncertainty with different models varies in the study area. The highest uncertainty in SM modeling was observed at the north part of the study area where the surface heterogeneity is high. Using RS data increased the accuracy of SM modeling because they can capture the surface biophysical characteristics and topographical properties heterogeneity. Unlabelled Image • Spectral and spatial based approaches were used to map soil moisture. • Spectral models were superior than interpolation models to estimate soil moisture. • Combined topographic & surface biophysical characters supported higher performance. • Higher surface heterogeneity made soil moisture estimation more uncertain. • Land surface temperature showed the highest impact on soil moisture distribution. [ABSTRACT FROM AUTHOR]

Modeling and mapping of soil properties are critical in many environmental, climatic, ecological and hydrological applications. Digital soil mapping (DSM) techniques are now commonly applied to predict soil properties with limited data by developing predictive relationships with environmental covariates. Most studies derive covariates from a digital elevation model (named static covariates). Many works also include single-day remotely sensed satellite imagery. However, multitemporal satellite images can capture information about soil properties over time and bring additional information in predicting soil properties in DSM. We refer to covariates derived from multitemporal satellite images as dynamic covariates. The objective of this study was to assess the performance of DSM when using terrain derivatives (static covariates), single-date remotely sensed satellite indices (limited dynamic covariates), multitemporal satellite indices (dynamic covariates), and combinations of terrain derivatives and satellite indices (covariate fusion) as covariates in predicting soil properties and estimating uncertainty. Three soil properties are considered in this study: organic carbon (OC), sand content, and calcium carbonate equivalent (CCE). Inclusion of single and/or multitemporal remotely sensed satellite indices improved the prediction of soil properties over traditionally used terrain indices. Significant improvements were observed in the prediction of soil properties using two models, Cubist and random forest (RF). The increase in the R2 values for Cubist and RF were 126% and 78% for OC, 110% and 54% for sand, and 87% and 32% for CCE. The RMSE decreased by 34% and 27% for OC, 25% and 12% for sand, and 39% and 19% for CCE, when compared to the terrain indices only model. This also reduced the uncertainty of estimation and mapping. These clearly showed the advantage of using multitemporal satellite data fusion rather than simply using static terrain indices for DSM of soil properties to deliver a great potential in improving soil modeling and mapping for many applications. Unlabelled Image • We introduced dynamic & static environmental covariates (ECs) for digital soil mapping. • Dynamic EC improved soil prediction over static ECs including terrain indices. • Multi-date satellite images captured the variations from change in soil properties. • Multi-date satellite images also reduced the uncertainty in prediction and mapping. • Combination of dynamic and static ECs had a larger influence on soil prediction. [ABSTRACT FROM AUTHOR]

In this letter, a compact microstrip lowpass filter (LPF) is designed using serial connecting of two modified asymmetric hairpin resonators. The proposed design is consists of four open‐circuited stubs that are used to suppress spurious harmonics in the stopband. The proposed filter has wide‐stop band with attenuation level better than −28 dB from 2.16 up to 26.1 GHz and sharp roll‐off. The proposed LPF has −3 dB cutoff frequency equal to 2.11 GHz, wide stopband width around 12th harmonic suppression and insertion loss less than 0.1 dB at about 85% of the passband. The excellent agreement is observed between the simulated results and measured values of the fabricated LPF. [ABSTRACT FROM AUTHOR]

The aim of the present study was to experimentally investigate the interaction between a low replacement ratio of different nano-particles (SiO2, Al2O3, clay, and CaCO3) and aminosilane in the matrices of cement paste and mortar. Results showed that the optimum content of aminosilane for improving the 28-day compressive strength of cement mortar was 0.75% (by weight of the total binder). The utilization of nano-SiO2 and nano-clay particles improved the strengths of the cement mortar containing hybrid systems of nano-particles/aminosilane at early (7days) and middle curing ages (28 and 91days). The 28-day compressive strength enhancement of cement mortar with hybrid systems of nano-SiO2/aminosilane and nano-clay/aminosilane was about 19% and 20%, respectively. Additionally, the application of aminosilane with nano-CaCO3 and nano-Al2O3 particles showed lower efficacy on mechanical performance of the cement-based composites in comparison with nano-clay and nano-SiO2. Despite the fact that the utilization of aminosilane with and without different nano-particles enhanced the flowability of the cement paste and mortar, it reduced the electrical resistivity of the cement mortar. In this regard, the minimum electrical resistivity was achieved for specimens with only aminosilane. This reduction was about 19.5% for samples containing 0.75% aminosilane for a curing time of 28days. [ABSTRACT FROM AUTHOR]