Pattern Recognition and Its Application in Solar Radiation Forecasting

As intermittent renewable energy sources such as wind and solar proliferate, the power systems operation and planning become more complicated due to increased uncertainties and variabilities. Accurate forecasting of these sources facilitates planning and operating the electric grid to integrate wind/solar power more reliably and efficiently. The neural network learning process can be disrupted by anomalies of wind/solar time-series data, which results in less accurate forecasting. By processing and analyzing wind/solar time-series data, machine learning and pattern recognition methods such as data clustering and classification can significantly enhance the forecast accuracy. This chapter reviews the various machine learning and pattern recognition methods proposed in the literature for time-series forecasting of solar radiation

Gundelia: A systematic review of medicinal and molecular perspective

Gundelia (Gundelia tournefortii L.) is a member of the Asteraceae (Compositae) family which grows in the semi-desert areas of Iran, Jordan, Palestine, Syria, Iraq, Syria, Azerbaijan, Armenia, Anatolia and other countries. Traditionally, G. tournefortii (L.) is used for treatment of liver diseases, diabetes, chest pain, heart stroke, gastric pain, vitiligo, diarrhea and bronchitis. It is also reported to have hypoglycaemic, laxative, sedative, anti-inflammatory, anti-parasite, antiseptic and emetic effects. It has enhanced gingivas and removed water from patients having spleenomegaly. Compounds found in gundelia proved to have several pharmacological effects, e.g. antibacterial, anti-inflammatory, hepatoprotective, antioxidant, antiplatelet and hypolipemic activities. The observed pharmacological properties indicated a close association of these effects with infectious diseases, digestive disorders, high blood pressure and cancer. In traditional medicine, this plant has been prescribed in many disorders; therefore, clinical trials on the compounds of gundelia seem essential. This study gives an overview of traditional uses of gundelia, irrespective of pharmacological studies on its effects. © 2013 Asian Network for Scientific Information

Evaluation of salinity tolerance of three olive (Olea europaea L.) cultivars

Tarom region of Zanjan province is one of the olive production centers in Iran, which faced a crisis of salinity stress following the salinization of water resources. The selection of salinity tolerant cultivars using pivotal characteristics is one of the interesting challenges. This study was conducted to investigate the behavior of ‘Zard’, ‘Abou-satl’, and ‘Arbequina’ cultivars in the context of using marginal waters. Therefore, one-year-old self-rooted plants of these cultivars were potted and irrigated with 2, 5, 8, and 12 dS/m saline water for three months in the greenhouse, and certain physiological and morphological features were studied. The results show that ‘Zard’ and ‘Abou-Satl’ cultivars tolerated salinity of 8 and 12 dS/m, maintained their photosynthesis in medium salinity (5 dS/m), and grew well in these conditions. In contrast, the ‘Arbequina’ cultivar exhibited extreme susceptibility to salinity. In the high salinities, there was a lower slope in the increase of Na+ concentration in the leaves of the ‘Zard’ cultivar. Also wet and dry biomass in this cultivar decreased much less than the others. A more severe reduction in the transpiration of the ‘Zard’ cultivar indicated better efficiency of water retention mechanisms and high water use efficiency. The photosynthesis rate of ‘Zard’ and ‘Abou-Satl’ cultivars were less affected under salinity stress. They reduced the accumulation of Na+ and increased the K+ concentration in leaves. These two cultivars had suitable responses to salinity and were recommended for planting in regions affected by salinity

Catachrestic Divergence:

“The Monkey Puzzle” is one of the most interesting as well as intimidatingly complex poems of Marianne Moore. It envelops Moore’s attitude as an objectivist poet moving towards the relationship between language and the world. The scarce critical attention it has received does not reflect the high status it should have in Moore’s oeuvre. The present paper builds on the body of research that does exist, and from there moves on to a detailed analysis of the poem in an attempt to show how a catachrestic divergence from significatory processes is at work all throughout this poem. The reinterpretation of the poem through a focus on its  catachrestic bounciness will not only shed light on some of its most complex imagery, but will also show how a philosophical filament runs through the whole poem and invites the readers to trespass the boundaries of the significatory walls drawn around our imagination.

An Algorithm to Extract the Defective Areas of Potato Tubers Infected with Black Scab Disease Using Fuzzy C Means Clustering for Automatic Grading

Estimating the surface area of defects of diseased potatoes is a key factor in the automatic grading of this product. In this article, an algorithm has been developed using fuzzy clustering method and image processing functions to estimate the defective areas of potato tubers infected with black scab disease. Fuzzy clustering, which is an unsupervised method, was used to segment color images and extract defective areas of potatoes, and image processing functions have been used to extract the total area of potatoes. In the segmentation method based on fuzzy clustering, the data matrix related to potato images were divided into separate clusters in a fuzzy way, in which the boundaries of the clusters are defined in a fuzzy way instead of being definite and specific. The results showed that this algorithm is very efficient for extracting black scab disease and can be used to extract the amount of diseases that can be used for automatic grading of this product based on the American standards

The Muslim Religiosity-Personality Measurement Inventory (MRPI)'s religiosity measurement model: towards filling the gaps in religiosity research on Muslims

Since the advent of religiosity as a field of scientific inquiry, it has been under the domain of psychologists of religion. The approach taken toward conceptualizing religiosity, therefore, has always been one purported to be of religious universalism. However, the overwhelming majority of religiosity instruments to date have fallen under the rubric of Christianity and the study of Christian people. As the desire to learn more about the religious life of the non-Christian traditions and people spreads, there is an increasing need for religiosity concepts and instruments to reflect these particular religious traditions. The role of religious worldview, therefore, is a major consideration in the instrumentation of religiosity, as worldview provides an underlying philosophical foundation for the operationalization of religiosity concepts, constructs and items. As the preponderance of religiosity instrumentation to date has been grounded in the Judeo-Christian religious worldview, existing religiosity instrumentation is also reflective of it, and as such, does not adequately represent the uniqueness of other non-Judeo-Christian worldviews such as the Islamic tawhidic worldview. As such, the Current study aimed to provide a general overview of religiosity conceptualization in general, along with some of the major gaps in religiosity research for Muslims. In response, the paper concludes with the presentation of a basic religiosity model rooted in the tawhidic worldview of Islam, upon which the Muslim Religiosity-Personality Inventory (MRPI) was based

A Bit-Vector Differential Model for the Modular Addition by a Constant and its Applications to Differential and Impossible-Differential Cryptanalysis

ARX algorithms are a class of symmetric-key algorithms constructed by Addition, Rotation, and XOR. To evaluate the resistance of an ARX cipher against differential and impossible-differential cryptanalysis, the recent automated methods employ constraint satisfaction solvers to search for optimal characteristics or impossible differentials. The main difficulty in formulating this search is finding the differential models of the non-linear operations. While an efficient bit-vector differential model was obtained for the modular addition with two variable inputs, no differential model for the modular addition by a constant has been proposed so far, preventing ARX ciphers including this operation from being evaluated with automated methods. In this paper, we present the first bit-vector differential model for the $n$-bit modular addition by a constant input. Our model contains $O(\log_2(n))$ basic bit-vector constraints and describes the binary logarithm of the differential probability. We describe an SMT-based automated method that includes our model to search for differential characteristics of ARX ciphers including constant additions. We also introduce a new automated method for obtaining impossible differentials where we do not search over a small pre-defined set of differences, such as low-weight differences, but let the SMT solver search through the space of differences. Moreover, we implement both methods in our open-source tool \texttt{ArxPy} to find characteristics and impossible differentials of ARX ciphers with constant additions in a fully automated way. As some examples, we provide related-key impossible differentials and differential characteristics of TEA, XTEA, HIGHT, LEA, SHACAL-1, and SHACAL-2, which achieve better results compared to previous works

A Bit-Vector Differential Model for the Modular Addition by a Constant

ARX algorithms are a class of symmetric-key algorithms constructed by Addition, Rotation, and XOR, which achieve the best software performances in low-end microcontrollers. To evaluate the resistance of an ARX cipher against differential cryptanalysis and its variants, the recent automated methods employ constraint satisfaction solvers, such as SMT solvers, to search for optimal characteristics. The main difficulty to formulate this search as a constraint satisfaction problem is obtaining the differential models of the non-linear operations, that is, the constraints describing the differential probability of each non-linear operation of the cipher. While an efficient bit-vector differential model was obtained for the modular addition with two variable inputs, no differential model for the modular addition by a constant has been proposed so far, preventing ARX ciphers including this operation from being evaluated with automated methods. In this paper, we present the first bit-vector differential model for the n-bit modular addition by a constant input. Our model contains O(log_2(n)) basic bit-vector constraints and describes the binary logarithm of the differential probability. We also represent an SMT-based automated method to look for differential characteristics of ARX, including constant additions, and we provide an open-source tool ArxPy to find ARX differential characteristics in a fully automated way. To provide some examples, we have searched for related-key differential characteristics of TEA, XTEA, HIGHT, and LEA, obtaining better results than previous works. Our differential model and our automated tool allow cipher designers to select the best constant inputs for modular additions and cryptanalysts to evaluate the resistance of ARX ciphers against differential attacks

Plasma levels of vascular endothelial growth factor and its soluble receptor in non-alcoholic fatty liver disease

Introduction: Non-alcoholic fatty liver disease (NAFLD) is a clinical pathologic condition, which leads to inflammation events in hepatocytes. The objective of present study was to compare the plasma levels of VEGF and sVEGFR-1 as inflammation factors in overweight and obese children and adolescents with and without NAFLD. Materials and Methods: A total sample of 70 overweight and obese children and adolescents (37 boys and 33 girls) were recruited from those admitted to a nutrition clinic in Mashhad, northeastern Iran. The presence of NAFLD was determined by FibroScan, ultrasound and elevation of liver enzyme. Plasma VEGF and sVEGFR1 were also determined for each individual. Results: VEGF levels (log transformed) showed a significant stepwise increase from “zero” to “first”, “second” and “third” grades (P tren

A novel splice site variant in the LDLRAP1 gene causes familial hypercholesterolemia

Background: familial hypercholesterolemia (FH), a hereditary disorder, is caused by pathogenic variants in the LDLR, APOB, and PCSK9 genes. This study has assessed genetic variants in a family, clinically diagnosed with FH. Methods: A family was recruited from MASHAD study in Iran with possible FH based on the Simon Broom criteria. The DNA sample of an affected individual (proband) was analyzed using whole exome sequencing, followed by bioinformatics and segregation analyses. Results: A novel splice site variant (c.345-2A>G) was detected in the LDLRAP1 gene, which was segregated in all affected family members. Moreover, HMGCR rs3846662 g.23092A>G was found to be homozygous (G/G) in the proband, probably leading to reduced response to simvastatin and pravastatin. Conclusion: LDLRAP1 c.345-2A>G could alter the phosphotyrosine-binding domain, which acts as an important part of biological pathways related to lipid metabolism