Miracle-dz/UniFAR-FTUs huggingface dataset:
International Journal of Current Research in

The Indian elephant (Elephas maximus) is one of three recognized subspecies of the Asian elephant and native to mainland Asia. Since 1986, Elephas maximus has been listed as Endangered by IUCN. The Elephas maximus are an ecologically and economically important species in many Indian habitats. However, illegal hunting, poaching, habitat destruction and other factors, especially in wild elephant populations. The present study highlights regarding the designing of species-specific primers based on mitochondrial DNA (mtDNA) D-loop and 12S ribosomal ribonucleic acid standardized protocol. The designed species-specific primers helped to identify suspected wild sample as Elephas maximus (Elephant) and also provide a viable scientific evidence to prove the forensic studies. Accepted: 17 December 2015 Available Online: 06 January 2016
IMPROVING TWO-WAY JOIN PROCESSING USING BLOOM FILTER INTERSECTION IN MAP REDUCE

Big Data Analysis is at the heart of modern enterprise and scientific research. To analyze this very large-scale data, MapReduce has become an attractive model for this kind of data. However, this model is not designed to perform join operations with multiple entries. Although many studies on join algorithms like Bloomjoin in MapReduce have been explored, but a lot of non-joining data is still being generated and transmitted over the network. This research will provide us with a model to solve this problem by making an intersection filter based on the Bloom Filter to eliminate disjoint elements between two sets of input data. Two methods are proposed to model the filter. To apply the filter in a join operation, a MapReduce job will be adjusted consistently, attempting not to increase the associated costs. Therefore, thanks to the intersection filter, the operation of the joins minimizes the cost of disk I/O. Finally, the study carried out proved its effectiveness by comparing with the existing solutions on the costs of the joins of the two approaches.
An Improved Daubechies Wavelet based Image Compression methods

: Real time transmission of images through handheld mobile or convenient devices requires an image coding algorithm to reduce the redundancies among the image in the form of pixels at the very low bit rate. Large number of successful wavelet based image coding algorithm has been proposed in the literature. These algorithms are mainly classified into zero tree and zero block approaches. Zero tree algorithm make use of inter sub bands correlations existing among different sub bands of an image. The inefficiency of zero block lies in that they do not take care of inter sub bands correlation existing among different sub bands. Here present an implementation of a wavelet coder based algorithm. The above methods are used in many applications for compression and decompression of an image. The techniques are compared by using daubechies wavelet family for performance measuring parameter like higher compression ratio, bits per pixel and the amount of time required at every stage after the decomposition of an image. The comparative analysis was done using the four methods with the results are mentioned in this paper.
HAEMATOLOGICAL AND BIOCHEMICAL CHANGES IN PRE AND POST TREATMENT OF BUCCAL MUCOSA CARCINOMA PATIENTS

Oral squamous cell carcinoma is one of the leading causes of mortality in India. The various haematological and biochemical changes including liver enzymes imbalance occur in cancer treatment. The careful monitoring of serum biochemical and haematological changes had very important role in prognosis of disease. Therefore, the present study aimed to study haematological and biochemical changes in pre and post treatment of buccal mucosa carcinoma patients. In study, totally 198 buccal mucosa carcinoma subjected were included from both genders. We observed the Haematological parameters (level of completer haemogram, differential leucocytes count), biochemical and liver function parameters in pre and post treatment of subjects. The serum biochemical and haematological levels were lower in post treatment groups than before treatment of subjects, whereas glucose level did not show significant changes. Hence, the subjects did not affected by diabetics. Most of subjects had anaemic, treatment severely affected bone marrow. However, these changes were exists statistically significant by paired samples t-test at p˂0.001. The biochemical and haematological changes were additional risk for subjects. Thus, these changes will help the prognosis and proper monitoring of the cancer subjects. INTRODUCTION: Oral cavity squamous cell carcinoma is one of the leading causes of cancer related death in developing countries particularly India. 1 A total of 274,300 new cases recorded worldwide in 2002; almost two thirds were in developing countries. The high risk in Indian population was related to the popularity of pan tobacco (combination of betel leaf, lime, areca nut and sun cured tobacco) chewing in the region. 2 Inflammatory cytokines could promote the production of white blood cells (WBC’s). QUICK RESPONSE CODE DOI: 10.13040/IJPSR.0975-8232.7(7). 3002-06 Article can be accessed online on: www.ijpsr. com DOI link: http://dx.doi. org/10.13040/IJPSR.0975-8232.7 (7). 3002-06 Bone marrow produces both red blood cells and white blood cells from the same precursor of stem cells. Therefore, the up regulation of WBC’s causes fewer stem cells to differentiate into red blood cells. This may be an important cause for the effective inhibition of erythropoiesis, even when erythropoietin levels were normal. 3 Ernest reported that cytokines suppressed erythropoiesis by affecting red cell production and impaired iron utilization in cancer patients. Thus, ion had an important role in cancer treatment. 4 Cancer therapeutics such as radio and chemotherapies act as alkalising agents and lead to progressive depletion of hematopoietic stem cells in the bone marrow. This may lead to long-term anaemia, which make the treatment less effective. Overall, the presence of anemia in cancer patients increased the relative risk of death by 65%. Anemia
Pelvic lymphadenectomy as a component of interval cytoreduction for ovarian cancer: is there a benefit? A pilot study

Background: Management strategy in ovarian cancer includes a combination of cytoreductive surgery and chemotherapy. Interval cytoreductive surgery has been shown to be oncologically non-inferior to primary cytoreduction with the additional benefit of reduced morbidity. Lymphadenectomy as a component of cytoreductive surgery has been controversial with an unproven therapeutic benefit. Methods: Records of patients with a histological diagnosis of ovarian cancer and treated with interval cytoreduction were evaluated. Disease related, pathological and treatment data collected for analysis. Results: The study included 32 patients with a mean age of 56 years (41-76). Serous papillary tumors (42%) were the predominate histology and the majority were in stage III disease (84%). Optimal cytoreduction was achieved in 93%. The mean nodal harvest was 9.8 nodes with left pelvic dissection yielding slightly more nodes than the right (4.5 vs 5.2). Nodal positivity was observed in just one patient (3%). A total of 314 were nodes examined with only 2 (0.6%) yielding persistent disease. The nodal positivity yield tested as a categorical variable by the binomial test returned P=0.0001. Conclusions: It is possible to omit pelvic nodal dissection during interval cytoreduction in otherwise optimally cytoreduced patients particularly when imaging and intraoperative assessment are not suggestive of pelvic nodal metastasis.
International Journal of Current Research in

Article Info Given the adverse effects of air pollution on human health, a lot of studies have empirically investigated the causal effect of air pollution on health. However, no study has considered how fine particulate matter interacts with GDP per capita to affect cancer mortality. This study therefore uses data for 20 OECD countries to estimate the conditional effect of air pollution on cancer mortality. To this end, a fixed effect panel regression model which takes both country and time fixed effects into consideration is estimated. The conditional causal effect of fine particulate matter was found to be negative 0.22 and significant at 1% level. Accepted: 30 July 2017 Available Online:20 August 2017
Koroner Arter Kalsiyum Skor İndeksi ile Karotis ve Yüzeyel Femoral Arterlerin İntima Media Kalınlıkları Arasındaki İlişkinin Değerlendirilmesi

Objective: To investigate the relationship between intima-media thicknesses (IMT) of carotid and superficial femoral arteries and coronary artery calcium index quantified using Agatston score. Materials and Methods: Cardiac multidetector computed tomography (MDCT) angiography of 75 patients were included in the study. Coronary artery calcium scores were measured using a workstation. Calcium scores were calculated according to the Agatston method. Bilateral carotid artery and superficial femoral artery IMTs were obtained by B-mode ultrasound. All patients were divided into three groups according to Agatston scores. 25 patients with 0 Agatston score were included to first group. 25 patients with 1-100 and 25 patients with more than 101 Agatston score were included to second and third group, respectively. Oneway Anova, t test and Post HocTukey HSD test were used for statistical analysis. Values of P< 0.05 were considered statistically significant. Results: There was a significant relationship between carotid artery and superficial femoral artery IMTs and coronary artery calcium score index. Increased calcium scores were related with increasing IMTs. Conclusion: Increased carotid artery and superficial femoral artery IMTs relates with coronary artery calcium scores. Superficial femoral artery IMT measurement is reliable tool comparable to carotid artery IMT measurement.
Evaluation of Early Loading Versus Immediate Loading of Dental Implants: A Comparative Study

Citation: Ahmed M Elmarakby. , et al. “Evaluation of Early Loading Versus Immediate Loading of Dental Implants: A Comparative Study”. EC Dental Science 19.1 (2020): 01-12. Abstract Background: Success and failure of dental implant depends on multiple factors. Stability could be the most important factor in implant success feature. Aim of the Study: To assessments the early loading versus immediate loading of dental implants. Patient and Methods: Patients with missing posterior mandibular teeth was the subject of the study. Patient was selected from the outpatient clinics at faculty of dental medicine, Al-Azhar University. Inclusion criteria included: Male and female patients with missing mandibular posterior teeth. Patient’s age was ranged from 20 to 40 years old. Patient was free from any systemic disease that affect bone healing. Good oral hygiene measures. Normal occlusion, no parafunctional habits. Adequate bone volume and density. Exclusion criteria: Patients with an uncontrolled medically compromised state. Patients with systemic diseases affecting bone integrity; osteoporosis or Paget's disease of bone. Patients with bad oral hygienic measures. Clinical examination of the per implant soft tissue will be done using gingival index, plaque index, and pocket depth immediately post-operative, at 3, 6, and 9 months after the operation. Conclusion: Within the limitation of the present study, the results showed a significant difference between the early loading versus immediate loading of dental implants at the posterior partially edentulous mandible when using different restorations.
NOVEL SYSTEM FOR IMAGE RE-RANKING USING QUERY-SPECIﬁC SEMANTIC SIGNATURES

: Picture re-positioning, as a powerful approach to enhance the aftereffects of online picture seek, has been embraced by momentum business web crawlers, for example, Bing and Google. Given an inquiry catchphrase, a pool of pictures is first recovered in view of literary data. By requesting that the client select a question picture from the pool, the rest of the pictures are re-positioned in view of their visual likenesses with the inquiry picture. A noteworthy test is that the likenesses of visual highlights don't well relate with pictures' semantic implications which translate clients' pursuit expectation. As of late individuals proposed to coordinate pictures in a semantic space which utilized traits or reference classes firmly identified with the semantic implications of pictures as premise. Notwithstanding, taking in a widespread visual semantic space to describe exceedingly various pictures from the web is troublesome and wasteful. In this paper, we propose a novel picture re-positioning structure, which naturally disconnected learns distinctive semantic spaces for various question watchwords. The visual highlights of pictures are anticipated into their related semantic spaces to get semantic marks. At the online stage, pictures are re-positioned by looking at their semantic marks acquired from the semantic space indicated by the question watchword. The proposed question particular semantic marks fundamentally enhance both the exactness and productivity of picture re-positioning. The first visual highlights of thousands of measurements can be anticipated to the semantic marks as short as 25 measurements. Trial comes about demonstrate that 25-40 percent relative change has been accomplished on re-positioning precisions contrasted and the best in class techniques.
Design Of Low Power High Density SRAM Bit Cell

- Power and area minimization is a critical concern for modern electronic industry. Low power SRAMs are essential in today's electronic gadgets as the demand of battery operated portable devices is increased. This work is the design of a SRAM bit cell for minimizing the area and power consumption. Basic SRAM cell is considerably more complex and occupies a larger area as compared to DRAM cell. Proposed work has a 4 transistor SRAM with approximately 40% less power consumption than that of conventional 6T SRAM. The area also reduced by 35%. 4T SRAM cell have a single access transistor to perform the read write operation. Cadence Virtuoso simulation in standard 180nm CMOS technology confirms all results obtained from this work.
An effective method for high purity genomic DNA extraction from N

Wen-Jin Ma 1, 2 , Xue-Feng Chen 1, *,Wen-Jin Lou 3 , Huan Liu 1 , Bo Wang 2 , Qian Wu 3 , Yu Zhao 2 , Tao Peng 2 and Peng Chen 4, * 1 School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, China 2 The Institute of Gansu Province Light Industrial Scientific Research, Lanzhou 730000, China 3 Gansu Provincial Academic Industrial for Medical Research, Lanzhou 620100, China 4 School of Pharmacy, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, PR China * Corresponding author: Xue-Feng Chen, School of Food and Biological Engineering, Shaanxi University of Science and Technology, 710021, Xi’an, People’s Republic of China, Tel/Fax: +86-29-86168293, E-mail: chxf2002xue@163.com. Peng Chen, School of Pharmacy, Lanzhou University, Donggang West Road No. 199, Lanzhou, 730020, PR China , Tel/Fax: +86-0931-8915686, E-mail: chenpeng@lzu.edu. cn. SCIREA Journal of Agriculture
Data Analytics for Cardiotocography Data Using Principal Component Analysis

With growing congenital anamelies in recent years detection of heart problems in fetus has become critical. Cardiotocography test assists doctors in such dignosis followed by cure. Here analytics of cardiotocography data is presented in details.Understanding ,cleaning and preprocessing the data is one of the the foremost part for any researcher,In this work data is cleaned,preprocessed,normalized, Also the attributes are selected by using the Chi-square test. Colinearity problem is addressed using Principle component analysis.Such analytics and prepro-cessing will help in machine learning or allied models for predict-ing precise diagnosis at an early stage
MAPREDUCE WORKLOAD FOR DYNAMIC JOB ORDERING AND SLOT CONFIGURATION

MAPREDUCE is a widely used computing model for large scale data processing in cloud computing. A MapReduce job consists of a set of map and reduces tasks, where reduce tasks are performed after the[29] map tasks. Hadoop [21], an open source implementation of MapReduce, has been deployed in large clusters containing thousands of machines by companies such as Amazon and Facebook. In th at clusterand data center environments, MapReduce and Hadoop are used to support batch processing for jobs submitted from multiple users (i.e., MapReduce workloads). Despite many research efforts devoted to improvingthe performance of a single MapReduce job (e.g., [3], [21],[11]), there is relatively little [29]attention paid to the system performance of MapReduce workloads. Therefore, in [21] they tries to improve [29][30]the performance of MapReduce workloads.Makespan and total completion time (TCT) are two key performance metrics. Generally, makespan is defined as the time period since the start of the first job until the completion of the last job for a set of jobs[21]. It considers[31] the computation time of jobs and is often used to measure the performance and utilization efficiency of a system[22]. In contrast, total completion time is referred to as the sum of completed time periods for all jobs since the start of the first job[21]. It is a generalized makespan with queuing time (i.e., waiting time) included. We can use it to measure the satisfaction of the system from a single job’s perspective through dividing[21] In [21]they target at one subset of production MapReduce workloads that consist of aset of independent jobs (e.g., each of jobs processes distinct data sets with no dependency between each other) with different approaches. For dependent jobs(i.e.MapReduce workflow), one MapReduce can only start only when its previous dependent jobs finish the computation subject to the input-output data dependency[21]. In [21]contrast, for independent jobs, there is an overlap computationbetween two jobs, i.e., when the current job completes its map-phase computation and starts its reduce-phase computation, the next job can begin to perform its map-phase computation
Uncertain Data

Traditional machine learning algorithms assume that data are exact or precise. However, this assumption may not hold in some situations because of data uncertainty arising from measurement errors, data staleness, and repeated measurements etc., these kinds of uncertainty have to be handled cautiously, or else the mining results could be unreliable or even wrong. In this paper, we focus on classifying uncertain data by classification and prediction algorithm called setBase. This algorithm introduces new measures for generating, pruning and optimizing. Probability distribution function and uncertain data intervals are computed by this kind of algorithm . Based on these new measures, the optimal splitting attribute and splitting value can be identified and used for classification and prediction. Uncertainty in both numerical and categorical data can be processed by this measure. Our experimental results show that setBase has excellent performance even when data is highly uncertain.
Soft and Hard Dental Tissues Laser Er : YAG Laser : From Fundamentals to Clinical Applications

The breakthrough for dental laser systems came in the mid 1990’s. Among the various laser types with corresponding wavelengths, Er:YAG laser systems quickly began establishing themselves as compact and versatile additions to the dentist’s repertoire, predominantly for performing hard tissue applications. Research has shown that their wavelengths are ideally suited for both soft and hard tissue procedures due to their high absorption in water and hydroxyapatite. Therefore Er:YAG laser is considered one of the most versatile with regard to the number of possible treatment options, as their wavelength can be effectively used in the field of soft and hard tissue surgery, periodontics, endodontics, implantology, cavity preparation, and tooth whitening. The versatility of the instrument, combined with the latest achievements in Er:YAG laser technology, compact design and affordability, should appeal to dental professionals seeking to optimize the procedures they currently perform and expand the number of services they offer which is the main aim of the current review.
A Novel Cross Layer Approach for Minimizing Energy Utilization for Mobile Wireless Sensor Networks

Wireless Sensor Networks (WSNs) consist of densely distributed sensor nodes with embedded low computational power CPU, limited storage and low power radios. WSNs are widely used to monitor environmental conditions, such as temperature, sound, and vibration and pressure, in disaster relief, home monitoring etc. One major disadvantage in Mobile WSNs suffers from over head of control packet and decreases the sent packet ratio. This leads to consume more energy. The paper introduces a cross-layer operation model that can increase the utilization of energy and provide high throughput of MWSNs. The model integrates four layers in the network operation: 1) application (location of node); 2) network (flooding); 3) medium access control (MAC); and 4) physical layers. The location of the mobile nodes is implanted in the routing operation after the discovery of route. The location information is then utilized by the MAC layer transmission power control to adjust the transmission range of the node. This is used to minimize the power utilized by the network interface to reduce the energy consumption of the node(s). The model employs a mechanism to minimize the neighbour discovery broadcasts to the active routes only. Reducing control packet broadcasts between the nodes reduces the network’s consumed energy. Through simulation-based evaluations, the proposed model outperforms the conventional operation of IEEE 802.15. 4-based network and the energy efficient and QoS aware multipath routing protocol in terms of energy consumption by roughly 10%, twice less control packet overhead, end-to-end delays and comparative packet delivery ratios.
Pricing Vulnerable Options under Stochastic Asset and Liability

In this paper pricing for vulnerable options is investigated. The discussed payoff function mainly derives from the Klein and the Ammann credit risk frameworks. Three stochastic processes, namely the underlying stock price, the asset value of the option writer, and the liability value of the option writer, are suitably modeled. Under the suggested payoff function, closed-form solutions for vulnerable European options are derived; moreover, adapting the Rubinstein’s approach, a general binomial pyramid algorithm for vulnerable options pricing is constructed.