Abstract:2061 species of higher spore, gymnospermaceous and flowering plants belonging to 144 families and 764 genera have been established in the flora of the region. Herbariums based on a large number of collected plants were prepared and handed over to the Herbarium Found of the Institute of Botany of ANAS. 39 rare, endangered and 17 endemic plant species were identified. The stock of 40 species has decreased noticeably, 16 species are on the verge of extinction there, 5 species are under the threat of complete destruction and 17 species reduce their range in recent years. The composition and structure of the vegetation cover of the region under the influence of a complex of ecological, technogene, zoogenic and anthropogenic factors has changed greatly, where urgent measures for their improvement and protection are required for further use.
Abstract:This research aims to analyze the effects of profit-sharing financing, trade financing, and lease financing on the profit of sharia banks in Indonesia from 2010-2016. This research utilized Vector Error Correction Model (VECM) approach to analyze the data. The research findings present positive effects of profit-sharing financing and lease financing on the profits of sharia banks in Indonesia in the short term. On the other hand, trade financing has negative impacts on the profitability of sharia banks in Indonesia in the short term. For a long-term, there is a long-term relationship among the profit-sharing financing, trade financing, lease financing, and the profitability of sharia banks in Indonesia. In the eighth month, the variable of profit-sharing financing became a variable with the most significant contribution to the profitability of sharia banks in Indonesia among other variables. The research findings recommend sharia banks to manage their financing allocation by considering the economic development to improve socio-economic productivity in either a short term or long term.
Abstract:The susceptibility of the third larval instar of the Oryctes agamemnon to infection and subsequent death by exposure to three native entomopathogenic fungi (NEPF); Beauveria bassiana, Metarhizium anisopliae and Lecanicillium lecanii was determined. Three concentrations of each NEPF isolate were used for dose-response mortality against the 3rd larval instar. Mortality rates of the larvae reached 34.2, 48.1 and 55.5% at the concentrations (104, 106 and 108 conidia/ml) of B. bassiana. M. anisopliae recorded mortalities reached 39.5, 57.4 and 60.8% to the target larvae. Similarly, the accumulated mortality of the 3rd instar larvae recorded 17.4, 26.4 and 29.2% for L. lecanii. The LT50 values of the 3rd instar of O. agamemnon larvae recorded 9.9 and 11.3 days for the two concentrations that achieved 50% mortality for B. bassiana and M. anisopliae respectively. M. anisopliae was the most efficient one, followed by B. bassiana and L. lecanii. The proteolytic activity of the three NEPF was investigated under different factors (incubation periods, temperature and pH). The results showed that the maximum activity of protease produced by B. bassiana, L. lecanii and M. anisopliae was recorded after 6 days of incubation with 28ï¿½C incubation temperature in the medium initially adjusted to pH 6.
Abstract:Objective: Evaluation of tooth rehabilitation with chronic periradicular periodontitis, submitted to endodontic retreatment and filled with PBSï¿½ CIMMO cement as a single endodontic obturator element. As well as propose protocol change in endodontic obturation using biological cement without incorporation of gutta percha. Method: Case Report: patient had a 3.7 tooth with conventional endodontic treatment and chronic periradicular periodontitis. Clinical examination revealed fistula and mobility. Initial tomography examination (Cone Bean tomography) determined the presence of extensive periradicular lesion. After removal of the intra-radicular nucleus, mechanical disbilling and chemical preparation of the root canal with continuous ultrasonic irrigation protocol (CUI) was performed. 5.5 % sodium hypochlorite and ethylene diamino tetraacetic acid surfactant were used as the auxiliary chemical. All channel filling was performed with PBSï¿½ biological cement. After six months, a clinical examination was performed. Absence of fistula and mobility was observed. The tomographic examination of preservation determined a decrease in the periradicular lesion. Conclusion: The protocol advocated in this case report determined reibilation of the tooth 37 and proposes further studies to establish a new biological obturator treatment for teeth affected by chronic periradicular periodontitis.
Abstract:Cloud Computing is an advanced technology for optimizing and innovating business models in organizations. It can be used for providing software and infrastructure services deployed in data centers. Encryption of data and information by data owners and uploading them to the cloud data center leads to different efficiency and secrecy problems. In cloud computing, a user who has authorized credentials should have the ability to access confidential data, such as data owners or cloud providers. In traditional methods of securing data, data are encrypted and stored in a trusted server and their access is controlled by an access control policy. If the cloud server is breached from unauthorized users, the confidentiality of sensitive data will be disclosed. This paper explores an enhanced cloud access control policies over encrypted data using XACML framework and proof of ownership (POW) methodologies. The proposed approach controls the access mechanism over encrypted data by generating a security token for sending responses and receiving user requests for decrypting data based on the previously stored attributes in the XACML policy. The security mechanism will be strengthened by deploying a fingerprint authentication parameter for ensuring confidentiality over untrusted user requests. By applying the cloud access control of XACML framework, the cloud services will perform its agreed functions with preventing data leakage, data loss, and abuse of cloud services.
Abstract:The article deals with the common translation problems and language confusion while teaching future interpreters from Ukrainian into English and vise versa in Ukrainian higher schools. The authors claim that higher educational establishments that train future translators form a deep knowledge of the main (technical or economic) specialty and professional competence of a professional translator, which allows future professionals to work effectively, quickly navigate in a dynamic environment, improve their professional level. High-quality professional training of translators requires constant updating, expansion and improvement of knowledge of foreign languages, and a certain field of activity, which puts before universities new tasks for the training of qualified personnel in the field of translation. The authors emphasize that there are some differences which exist in phonetics, vocabulary, grammar, spelling and punctuation and are difficult to be avoided even the non-professional English interpreter. It has been stated that the acquisition of a second language theoretically cannot be a process of mastering a new system of thinking, but it is only a matter of mastering a new code, which is projected on the code of the native language. In this situation, it is important to try to immerse yourself as deeply as possible in the English-speaking environment, creating artificial conditions in each lesson, to seek to organize conditions close to reality.
Abstract:The use of a Genetic Algorithm to minimize distribution losses in a feeder by optimizing the size and location of DG at an existing radial distribution system representing load with wind generation connected to the substation is presented in this article. Genetic Algorithm (GA) has a range of parameters that must be correctly calibrated in order to achieve accurate performance. This paper\'s work is an attempt to solve this connective problem. The practical radial distribution system is considered with voltage dependent load model.In this article, the optimal location and size of DG is obtained by varying different combinations of GA operators and keeping parameters like population, crossover fraction and generation at constant level. The optimal location and size obtained for minimum loss is executed to observe the effect on active and reactive power loss.The available generation is used in the first case, with the optimal position determined by Genetic Algorithm (GA) and in the second case both the optimal location and size are implemented. According to the test results, there is a 56.49 percent reduction in loss observed if Existing DG is connected at optimal Location as per GA and 91.47 percent reduction in lossobserved when Location and size of DG by GA as compare to Existing DG, respectively. The evolutionary algorithm GA re
Abstract:The present study underscores the investigation on prevalence of tick-borne pathogens of cattle both from hosts as well vectors from this part of India by conventional blood smear examination and through molecular techniques. A total of 1,153 cattle belonging to different age groups, breeds, sex were screened during the period from April, 2020 to March, 2021. Blood smear examination as well as PCR assay were followed to detect tick-borne pathogens in collected samples. The tick species recorded were Rhipicephalus (Boophilus) microplus, Hyalomma anatolicum anatolicum and Haemaphysalis leachi leachi .Overall prevalence of tick-borne pathogens was recorded as 33.30%. Mixed infection with Theileria sp. and Anaplasma sp. was found highest among infected cattle followed by single infection of Anaplasma sp. And Theileria sp. A few samples were only found to be positive for Babesia sp. infection. Significantly higher rate of infection was observed in the female animals. Species-specific PCR revealed different tick-borne pathogens species viz. Babesia bigemina, Theileria orientalis, Theileria annulata, Anaplasma marginale, Anaplasma central and Anaplasma bovis in cattle. Isolated DNA samples from blood and ticks were found positive for Coxiella burnetii and Borrelia burgdorferi sensu lato by PCR assay, albeit at very low percentage. The results clearly indicate that vector-borne haemoprotozoa and rickettsia are prevalent in the study area in apparently healthy animals without showing any obvious symptoms and R.(B.)microplus tick has an endosymbiotic relationship with C. burnetii and B. burgdorferi sensu lato.
Abstract:Recently, measurement of the optical characteristics of vegetation at specific wavelengths has been adopted for N status assessment in various crops. Optical sensing instrumentation can be used to calculate vegetative indices, which are indicators of a plant’s photosynthetic potential and above ground, living biomass. Development of NDVI for prediction of sugar beet yield and quality during the growing season would be of value to producers and industry. During the growing season, monitoring the status of the plant in sugar beet production system will enable farmers to improve nitrogen management. The main objective of this study was to determine in-season nitrogen status in sugar beet using the mobile optical sensor. For this, an experiment was established to determine the effect of nitrogen on root yield, sugar content and α-amino N content using a randomized block design by applying five different rates of nitrogen (0, 60, 90, 120, 150 kgN/ha) for two sugar beet varieties. The amount of 115.64 kg N/ha was determined as economic optimum nitrogen rate when quadratic polynomial model was used to describe the relationship between nitrogen and root yield, sugar content, and α-amino N content. The use of NDVI values were proposed 93 days after sowing at approximately 1486 CGDD.
Abstract:The humans are gifted with capability to differentiate salient objects from the background, the ability of a machine to do so is an important ingredient in the field of Computer Vision. The researchers have not yet been able to propose a model that can match the performance of humans, while saliency in noisy environment can’t be\nseen in near future. In this work, the detection accuracy is maintained even in noisy environments where the features are highly compromised, without capitalizing much of\ncomputation time. The model utilizes the concept of deep learning in denoising the image followed by gathering the information prevailing at the edges and corners of the\nobject in the image. The denoising of an image is done using a convolutional neural network (CNN) consisting of\nCoordinate descent as regularizing function. Various key points are then extracted from the denoised image using three different filters namely multi-scale Gabor, multi-scale\nContrast and multi-scale Harris energy functions. These points are applied to the convolution kernal and loss is\ncalacuted, then backpropagation is applied to fix the network which generates the saliency map. The performance of the proposed model is evaluated using precision, recall,\nF-measure, area under curve (AUC) and computation time using six publicly available image data sets. Experimental results from six different datasets proves that model is robust for any type of noise or mixture of noises.