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

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

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

Classification of Hyper MV -algebras of Order 3

In this paper, we investigated the number of hyper MV -algebrasof order 3. In fact, we prove that there are 33 hyper MV -algebras oforder 3, up to isomorphism

Current Status of Gil-Vernet Trigonoplasty Technique

Significant controversy exists regarding vesicoureteral reflux (VUR) management, due to lack of sufficient prospective studies. The rationale for surgical management is that VUR can cause recurrent episodes of pyelonephritis and long-term renal damage. Several surgical techniques have been introduced during the past decades. Open anti-reflux operations have high success rate, exceeding 95%, and long durability. The goal of this article is to review the Gil-Vernet trigonoplasty technique, which is a simple and highly successful technique but has not gained the attention it deserves. The mainstay of this technique is approximation of medial aspects of ureteral orifices to midline by one mattress suture. A unique advantage of Gil-Vernet trigonoplasty is its bilateral nature, which results in prevention from contralateral new reflux. Regarding not altering the normal course of the ureter in Gil-Vernet procedure, later catheterization of and retrograde access to the ureter can be performed normally. There is no report of ureterovesical junction obstruction following Gil-Vernet procedure. Gil-Vernet trigonoplasty can be performed without inserting a bladder catheter and drain on an outpatient setting. Several exclusive advantages of Gil-Vernet trigonoplasty make it necessary to reconsider the technique role in VUR management

Biokemijske značajke hidatidne tekućine cista Echinococcus granulosus podrijetlom iz čovjeka i životinja u Iranu.

A comparative study on the biochemical parameters in hydatid cyst fluids of sheep, goat, camel, cattle and human cystic forms of Echinococcus granulosus has been made in Iran. Quantitative variations in the levels of glucose, calcium and creatinine in the cystic fluids of camels were found with hydatid fluids of sheep, goat, cattle and humans. These differences were statistically significant (P<0.05). Similarities in the biochemical composition in hydatid cyst fluids of sheep, goat, cattle and humans suggest the existence of sheep strains of E. granulosus and differences in the biochemical composition in hydatid cyst fluids of camel with other domestic animals and humans suggest the existence of camel strains of E. granulosus in Iran.Provedeno je komparativno istraživanje biokemijskih pokazatelja hidatidne tekućine iz cista Echinococcus granulosus u ovaca, koza, deva, goveda i čovjeka u Iranu. Dokazana su kvantitativna kolebanja u nalazima glukoze, kalcija i kreatinina u cističnoj tekućini kod deva u odnosu na ovce, koze, govedo i čovjeka. Razlike su bile statistički značajne (P<0,05). Sličnosti u biokemijskom sastavu hidatidne tekućine u ovaca, koza, goveda i čovjeka ukazuju na prisutnost cista E. granulosus podrijetlom iz ovce dok razlike u biokemijskom sastavu hidatidnih tekućina deve i ostalih domaćih životinja i čovjeka ukazuju na prisutnost cista E. granulosus podrijetlom iz deve

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

On medial filters of BE-algebras

In this paper, the notion of a medial filter in a BE-algebra is defined, and the theory of filters in BE-algebras is developed. These filters are very important for the study of congruence relations in BE-algebras. Moreover, the relationships between implicative filters,  medial filters and  normal filters are investigated