Analysis of the groundwater resource decline in an intramountain aquifer system in Central Iran

The Shahrekord aquifer is located in an intramountain basin in Central Iran (90 km SW of Isfahan) and is the main resource of irrigation water for the intensively developed agriculture in the Shahrekord Plain. Early exploitation of the aquifer started back around 1950 but has intensified severely during the last decades. Irrigation water is provided by three means: spring water is tapped, water is pumped from around 650 wells and in historic times more than 100 karizes (or ghanats, deep underground channels that drain the water table and are accessed by shafts) were constructed and provide an additional source of water. However, groundwater levels have declined severely during the last decade, and although systematic piezometric monitoring already started in 1984, it stayed unclear whether the declining trend is related to increased water demand and exploitation or is due to climatic reasons, as around 2000 a severe drought lasted for three years. In this paper, exploitation and precipitation data are combined with the measured piezometric levels to analyse their relationship and help to understand the observed trend in declining groundwater storage. This aquifer is an example of a system that can easily deliver large amounts of groundwater because of a high transmissivity and considerable thickness, but has, for climatic reasons, a limited recharge. This imbalance makes the present level of exploitation unsustainable

Modélisation numérique du comportement à rupture (peeling-off) de poutres BA renforcées soumises à un essai de flexion 4-points

National audienceLe renforcement de structures ou d'éléments de structure par collage de matériaux composites est une technique actuellement reconnue et utilisée dans le monde entier. Néanmoins, ce type de renforcement peut produire des ruptures non-conventionnelles telles que la rupture par délaminage ou de type peeling-off. Cette dernière résulte du décollement du béton d'enrobage qui reste solidaire du matériau de renforcement. Pour une conception optimale d'un renforcement en flexion par collage, il est important d'être en mesure de prévoir ce type de rupture et d'en tenir compte dans le dimensionnement. Nous nous intéressons donc dans cette étude à ce mécanisme de ruine. Pour cela, nous avons modélisé des poutres BA renforcées sollicitées en flexion 4 points à l'aide d'un code de calcul commercial de type éléments finis, ABAQUS. Les analyses numériques sont de type élasto-plastique et permettent de déterminer le mode de rupture et le niveau de charge correspondant. Nous avons ensuite mené une étude expérimentale sur 15 poutres pour valider notre travail numérique. La confrontation des résultats de la modélisation et des résultats expérimentaux nous permet de conclure que le modèle numérique est capable de prédire le mécanisme de ruine à savoir le peeling-off ainsi que la charge de ruine correspondante

BayMiR: inferring evidence for endogenous miRNA-induced gene repression from mRNA expression profiles

BACKGROUND: Popular miRNA target prediction techniques use sequence features to determine the functional miRNA target sites. These techniques commonly ignore the cellular conditions in which miRNAs interact with their targets in vivo. Gene expression data are rich resources that can complement sequence features to take into account the context dependency of miRNAs. RESULTS: We introduce BayMiR, a new computational method, that predicts the functionality of potential miRNA target sites using the activity level of the miRNAs inferred from genome-wide mRNA expression profiles. We also found that mRNA expression variation can be used as another predictor of functional miRNA targets. We benchmarked BayMiR, the expression variation, Cometa, and the TargetScan “context scores” on two tasks: predicting independently validated miRNA targets and predicting the decrease in mRNA abundance in miRNA overexpression assays. BayMiR performed better than all other methods in both benchmarks and, surprisingly, the variation index performed better than Cometa and some individual determinants of the TargetScan context scores. Furthermore, BayMiR predicted miRNA target sets are more consistently annotated with GO and KEGG terms than similar sized random subsets of genes with conserved miRNA seed regions. BayMiR gives higher scores to target sites residing near the poly(A) tail which strongly favors mRNA degradation using poly(A) shortening. Our work also suggests that modeling multiplicative interactions among miRNAs is important to predict endogenous mRNA targets. CONCLUSIONS: We develop a new computational method for predicting the target mRNAs of miRNAs. BayMiR applies a large number of mRNA expression profiles and successfully identifies the mRNA targets and miRNA activities without using miRNA expression data. The BayMiR package is publicly available and can be readily applied to any mRNA expression data sets

A lumped parameter balance model for modeling intramountain groundwater basins : application to the aquifer system of Shahrekord Plain, Iran

Intramountain basins are the preferred locations for agricultural and socio-economical development in mountain regions. They often consist of considerable subsurface sedimentary fillings which hold an aquifer system suitable for groundwater exploitation. In semi-arid climates with distinct dry and wet seasons, groundwater is the main source of irrigation water in the dry periods. The risk for overdrafting of these basins is realistic when management of exploitation is not based on the water balance of the basin. When the outlet of the basin is narrow, groundwater interaction with surrounding basins is limited and the water balance becomes very sensitive to changes in the balance components, such as increasing pumping rates. This paper presents a lumped parameter water balance model for intramountain basins which incorporates: (1) the water inflow components of diffuse recharge from rainfall, lateral inflow from the surrounding mountains (mountain front recharge) and irrigation return flow on the cultivated land, and (2) the water outflow components as water capture from wells, springs and underground galleries, water loss from evapotranspiration and river and groundwater outflow out of the basin. Although the model has been developed for a specific basin in a semi-arid climate, it can easily be used for other basins in comparable hydrogeological settings. The model has been applied to the Shahrekord basin in central Iran, where intense agricultural activity has required large amounts of groundwater for irrigation in the dry summer months. Consequently piezometric levels have declined nearly continuously during the last decades because of overdrafting. The model has been applied for the period 1990-2004 and some of the water balance components have been estimated by calibrating the model using an optimisation routine. Additionally, some predictive runs have been done with the calibrated model to investigate future development under three different exploitation scenarios

Modélisation de la rupture de type peeling-off pour une poutre BA renforcée

International audienceLe renforcement de structures ou d'éléments de structure par collage de matériaux composites est une technique actuellement reconnue et utilisée dans le monde entier. Néanmoins, ce type de renforcement peut produire des ruptures non-conventionnelles telles que la rupture par délaminage ou de type peeling-off. Cette dernière résulte du décollement du béton d'enrobage qui reste solidaire du matériau de renforcement. Pour une conception optimale d'un renforcement en flexion par collage, il est important d'être en mesure de prévoir ce type de rupture et d'en tenir compte dans le dimensionnement. Nous nous intéressons donc dans cette étude à ce mécanisme de ruine. Pour cela, nous avons modélisé des poutres BA renforcées sollicitées en flexion 4 points. Elles sont modélisées à l'aide d'un code de calcul commercial de type éléments finis, ABAQUS. Les analyses numériques sont de type élasto-plastique et permettent de déterminer le mode de rupture et le niveau de charge correspondant. Pour valider notre modélisation, nous avons réalisé une campagne expérimentale sur 15 poutres. En comparant les résultats de la modélisation et les résultats expérimentaux, nous constatons que le modèle numérique est capable de prédire le mécanisme de ruine à savoir le peeling-off ainsi que la charge de ruine correspondante

Key Factors Affecting on the E-Readiness Assessment for Small and Medium Manufacturing Enterprises to Enter the E-Commerce Market

Due to the increasing growth of information and communication technology and to optimum utilization of its advantages, organizations must to develop their existing capacities. To measure this capacity of any organization, be sure is evaluated, the e-readiness of the organization to enter the e-commerce market. The main objective of this paper is to identify key factors affecting in the Electronic Readiness assessing of SMEs in Shamsabad Industrial City, Tehran to enter the e-commerce market. In this paper to determine this factors after identifying and introduction of variety existing models, concepts; dimensions and indicators of research is extracted and is designed in the form of a questionnaire. Then, using a designed questionnaire is action to gathering insights of academic experts and professional and variety of concepts, dimensions and related indicators is evaluated to E-Readiness assessment. Finally, with regard to the reforms, have been identified key factors affecting the E-Readiness of small and medium manufacturing enterprises

A comparative study of preliminary dosimetry for human based on distribution data in rats with 111In, 90Y, 153Sm, and 177Lu labeled rituximab

Radio immunotherapy is one of the most important and effective therapies for B-cell non Hoddgkin’s lymphoma treatment. Today, anti CD-20 antibodies labeled with beta emitter radionuclides are used in radio immunotherapy. Various radionuclides for labeling anti CD-20 antibodies have been studied and developed for the treatment and diagnosis of malignancies. This paper describes the preparation, bio-distribution and absorbed dose rate of 111In, 90Y, 177Lu, and 153Sm labeled anti CD-20 antibodies (rituximab) in human organs, after injection to rats. The macro cyclic bifunctional chelating agent, N-succinimidyl-1, 4, 7, 10-tetraazacyclododecane-1, 4, 7, 10-tetraacetic acid (DOTA-NHS) for conjugation to antibody, was used to prepare DOTA-rituximab. The conjugates were purified by molecular filtration, the average number of DOTA conjugated per mAb was calculated and total concentration was determined by spectrophotometric method. Radio-labeling was performed at 40 °C for 24 hours. After the quality control studies, the final radioactive solution was injected intravenously into rats through their tail vein. The tissue uptakes of each injection were measured. Then we calculated S values for 177Lu and 153Sm by using specific absorbed fractions and data used in the manner of radio-labeled analysis and dosimetry for humans. The absorbed dose rate of each organ was calculated in the specific time by medical internal radiation dose method with linear approximation in the activity measurements

Artifical neural network models for the analysis of permeable pavement performance.

This dissertation is a numerical modeling study based on the findings of the two installed Permeable Interlocking Concrete Pavements (PICPs) in Louisville, KY and twenty one laboratory models. A new model derived to more accurately predict the captured surface runoff volume by the PICPs using Artificial Neural Networks (ANNs). The proposed model relates rainfall parameters and site characteristics to the runoff volume captured by the permeable pavements. The database used for developing the prediction models is obtained from the collected data of the monitored permeable pavements. The performance of the ANN-based models are analyzed and the results demonstrate that the model results compare satisfactorily with measured values. A parametric study is completed to determine the sensitivity of a variety of parameters on the captured runoff volume. The results indicate that the developed model is capable of estimating the captured runoff by the permeable pavements for different rain events and site characteristics. The ANN model considers all significant contributing factors and provides a more precise volume prediction than the linear model. Clogging, which is mainly caused by sediment deposition, is the other important factor that result in performance failure of PICPs. Measuring Volumetric Water Content (VWC) by Time Domain Reflectometers (TDRs) is an automated method to track the speed of clogging. Monitoring peak VWC during rain events has been used as an indication of clogging progression over the PICP. Five ANN models are developed from the recorded VWC in order to compute the peak VWC from the rainfall parameters and maintenance treatment. A comprehensive set of data including various rain events characteristics obtained from the rain gauge and the conducted maintenance on the PICP are used for training and testing the neural network models. The performances of the ANN models are assessed and the results demonstrate satisfactory model accuracy when compared to the measured values. A parametric study was completed and the results indicate that the models are capable of estimating the peak VWC of the permeable pavements for different locations. The models consider all the contribution factors and provide more precise prediction values than the linear model. Peak 5 minute intensity, the previous rainfall depth, and the cumulative rainfall depth from the installation are the most critical parameters with respect to the hydrologic performance of the PICP. Finally, twenty one model configurations with different combinations of slope, gap size, and joint filling material were built to study clogging progression and permeable pavement performance. In this study, a neural network model was used to predict the clogging progression rate with critical PICP characteristics. The results indicate that the model is accurately predicting the extent of clogging along the length of permeable pavement. Sensitivity analyses are completed and the results suggest surface slope and location as the most influential parameters on the clogging length. Moreover, the prediction model for infiltration edge progression is presented to estimate the rainfall depth with 99% accuracy on testing datasets. By predicting the precise cumulative rainfall depth based on the infiltration edge distance and the PICP specifications, the hydrologic operation for each configuration and at any rainfall depth is accessible. The results demonstrate that surface slope and gap size present the highest influence on the infiltration edge progression. By better understanding the effects of pavements’ specification and site characteristics and selecting the most efficient pavement configuration, improved future design and more effective maintenance operations can be achieved

Analyzing Obstacles to Poetry Comprehension among Persian Language and Literature Students at Dari Department of Jawzjan University

This research delves into the intricacies of poetry dictation challenges faced by students, with a specific focus on the Dari Persian Language and Literature Department at Jawzjan University. Notably, existing studies have predominantly addressed issues arising from incorrect poetry reading, yet a gap exists in understanding the unique problems within this academic environment. The primary objective is to identify and remediate factors impeding accurate and fluent poetry dictation among students. Employing a quantitative approach and Cochran's formula, the study involved 108 randomly selected students from the first, fourth, and fifth semesters in the Dari language and literature department at Jawzjan University, Afghanistan. The research, facilitated through a survey questionnaire developed by the author, employs descriptive statistics in SPSS for data analysis. Key findings reveal critical challenges, including subpar teaching quality of the Persian language in schools (mean score of 2.59), elevated stress and anxiety levels during poetry dictation (mean score of 2.54), inadequate mastery of vocabulary (mean score of 2.48), and a dearth of practice among students (mean score of 2.39). The significance of these findings lies in their potential to substantially enhance poetry dictation skills, providing valuable insights for both educators and students, and addressing the unique challenges within the academic context of Jawzjan Universit