Miracle-dz/UniFAR-FTUs huggingface dataset:
2D QSAR STUDY OF INDOLE DERIVATIVES AS SELECTIVE COX-2 INHIBITORS

The NSAIDs are popular in reducing acute and chronic inflammation as they have no abuse liability. QSAR (Quantitative structureactivity relationship) approach is a very useful and widespread technique for drug design. 2D QSAR models are based on descriptors derived from a twodimensional graph representation of a molecule. The 2D QSAR study was performed on selected twenty-four compounds from synthesized indole derivatives for elucidating the structural requirements for COX-2 inhibition using multiple linear regression method. Statistically, significant models were generated using VLife Molecular Design Suite 3.5 software. The physicochemical parameters contributed significantly to biological activity. Amongst all the models generated, model 3 was found to be best with high r 2 (squared correlation coefficient) of 0.9382. Model is robust as q 2 (crossvalidated squared correlation coefficient) value is also high as 0.8557 with good predictive power as indicated by pred_r 2 = 0.7443. The model showed two alignment independent (AI) descriptors T_2_O_0 and T_2_N_7 as well as two physicochemical descriptors –ve Potential Surface Area and SA Most Hydrophobic contributing for activity. The present study may prove to be helpful in the development and optimization of existing indole derivatives as antiinflammatory agents with selective COX-2 inhibition. INTRODUCTION: NSAIDs inhibit cyclooxygenase (COX), the enzyme responsible for the conversion of arachidonic acid to prostaglandins. COX exists in 2 isoforms. COX-1 is a ubiquitous constitutive isozyme producing prostaglandins responsible for homeostatic functions such as maintenance of GI mucosal integrity. COX-2 is largely a cytokine-induced isozyme producing prostaglandins that mediate pain and inflammation 1 . NSAIDs inhibit both COX-1 and COX-2 to
Visualization of Sentences for Children with Intellectual Challenges

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Children with intellectual challenges face difficulties in thinking, communication and socialization. However, advances in computer technologies have facilitated their learning and social activities. Computerassisted teaching approaches provide a flexible learning platform for those children. Delay in language acquisition is one of the major problems faced by those children and it is one of the main reasons for their lack of academic success. Visualizing the verbal content present in their learning materials will improve language comprehension. This paper proposes a simple text-to-scene conversion system for assisting the education of intellectually challenged children.
A New Efficient Approach for Designing Intelligence Interleaver

-In communication system for removing burst error various algorithms, techniques are used. This paper contains designing of interleaving based on Artificial Intelligence state space search technique i.e. Breadth first search (BFS) and Depth first search (DFS), which gives number of possible solution, from the number of solution designer choose best solution. This algorithm is totally different from traditional algorithm. This algorithm takes more time than conventional algorithm but designer
Internet Heavy usage and its Influence on Academic Achievement of University Students

: This study focused on the influence of Internet heavy usage on academic achievement of university students. A student was considered a heavy Internet user when he or she was using the Internet for more than three hours daily. Internet usage was deemed to encompass the general Internet use and the use of all software applications that derive from the Internet, for example the use of social networking sites such as Facebook, Instagram, WhatsApp, Twitter and Skype; whether for positive or negative use.Logistic regression model under the framework of structural equation modelling was moved to check for both the direct and indirect effects of the independent variable(s) on the dependent variable (academic achievement). The study found that students who use the Internet in harmony with the aim of their study were more likely to attain higher academic achievement compared to light or average users. Therefore, students should avoid obsessive passionate use of the Internet, which is strongly correlated with academic achievement degradation. Accordingly, university students should be sensitized to use the Internet in harmony with the aim and objectives of their university studies; particularly that modern educational system increasingly relies on the Internet to enhance learning effective ness as a means of increasing the odds of academic success.
On Entropy and Informative Distance in a Time Interval

Measures of uncertainty in past and residual lifetime distributions have been proposed in the information-theoretic literature. Di Crescenzo and Longobardi [4] and Ebrahimi and Pellerey [7] introduced past and residual entropy functions. Misagh and Yari [11] and Sunoj et al. [15] proposed the interval entropy functions as useful dynamic measures of uncertainty for two sided truncated random variables. In this paper, we aim to study the use of interval entropy in characterization of distribution functions. Furthermore, we presented an informative distance which are based on a time interval and are more general than the well-known Kullback-Leibler divergence measure. The newly proposed measures are consistent in that they are valid in both past and residual lifetimes.
Distribution of Carbon Stock by Land in Banyuasin Regency, South Sumatra

Land use and land cover changes impact on carbon losses in terrestrial areas. The loss of carbon increase carbon dioxide (CO 2 ) in the atmosphere which is the major cause of global warming. Intensive land use and land cover changes took place in Banyuasin Regency from 2004-2014 led to changes in carbon stock distribution in the area. This study aimed to know how the distribution of carbon pools by land that occur in Banyuasin Regency. Research includes land use change, the amount of carbon stock changes, carbon balance and CO 2 emissions/sequestration. The study was conducted from June 2015 to February 2016. The method used was the method that calculates land use change and land cover in 2004-2009 and 2009-2014, calculation of carbon stocks using allometric equations and destructive sampling methods, and Carbon/CO 2 emissions/sequestration calculations using stock difference method. The results showed that during the period 2004-2014 the carbon balance moved toward the negative direction. Average carbon stock per hectare was 338.28 tons while average carbon loss was 0.45% per year. CO 2 sequestration amounted to 29.298. 966 tons while the emission was 118,044,141 tons, of which net emission was 88,745,175 tons. The average CO 2 emitted from above ground carbon pools, necromass carbon pools, litter carbon pools and belowrground carbon pools was 7 tons ha -1 yr -1 , while CO 2 emissions from soil organic C pools was 0.61 ton ha -1 yr -1 . Emission sources were dominated by changes in land use and land cover of peat swamp forests, secondary mangrove forests, primary mangrove forests and secondary swamp forests. While the source of sequestration came from changes in Rubber monoculture on peat, palm oil plantations, rubber monoculture, and shrubs. Key Words: Land use and land cover, carbon pool distribution, CO 2 emissions/sequestration
Dynamic Resource Provisioning in Datacenters using Profitability-aware VM Placement

: With the ever-spreading user-base in cloud datacenters, it has become increasingly challenging to satisfy each user’s service demand. Resource requirements or service demands of cloud users are embedded in virtual machines (VM). Virtual machines are software extensions of physical machines such that a single physical machine can generate a number of virtual machines and hence, can service multiple users. VM placement is the task of allocating a VM to a chosen physical machine (PM) such that the resource demands of that VM are satisfied by the physical machine. An effective VM placement aims at balancing load in the datacenter thereby avoids unnecessary VM migrations and improves the performance of a datacenter. Bin packing has been widely used as a technique for VM placement in the variations of first-fit, best-fit and/or worst-fit. This paper proposes a novel VM placement technique which ensures that the profits to the cloud service provider are maximized, establishes fairness and service availability to the cloud user by dynamically placing a virtual machine to the best available physical machine using the concept of clusters. Our VM placement strategy avoids unnecessary migrations in the datacenter by balancing load on all the physical machines present inside a cluster. A comparison, of the proposed technique with First-Fit bin packing placement technique, highlights a better time efficiency and resources utilization in the present work.
PHYTOREMEDIATION OF PHARMACEUTICAL PRODUCTS

ABSTRACT: Objective: This study focuses on application of phytoremediation technology in remediation of some pharmaceutical products like antibiotics (ciprofloxacin) and hormones (progesterone and estrogen). Methods: Cicer arientum is well studied and documented plant for phytoremediation of heavy metals, in specific. Here we tried to focus this potential of this plant for the pharmaceutical products by UV-VIS Spectrophotometric method in Hoagland-Arnon solution. Results: The results implies that Cicer arientum can be used for phytoremediation of pharmaceutical products with an average of 60% of the pollutant being remediated. Conclusion: The percentage remediation of pollutants are 60, 64.66 and 63.3 of Ciprofloxacin, progesterone and estrogen, respectively by Cicer arientum. Keywords: Antibiotics, hormones, Cicer arientum , UV spectrophometre , pharmaceutical products.
A Two Phase Fair Dynamic Job Assignment Strategy for Cloud Environment

— The Scheduling optimization mechanism in heterogeneous cloud is a NP-hard Type problem where all incoming jobs are to be arranged and mapped in such an efficient order with respect to available resources so that it could provide maximum, fair and flexible utilization of resources. As cloud system is almost heavily loaded all the time with a large number of requests that are coming at a regular or irregular interval from different sources. So it becomes necessary to take care so that a proper pattern for job assignment and grouping among jobs is created otherwise it may cause a strong risk to system performance resulting in sudden failure of system resources , as well as some serious problems like starvation and problems due to job communication. In this paper we have provided a solution for proper task ordering, arrangement of jobs and further for scheduling in dynamic cloud environment. We have used a different strategy for job scheduling in cloud environment which involves Linear Job Rearrangement Scheme for best Job ordering and Granularity Size based fair dynamic Job scheduling policy which is strongly beneficial for overall system balanced performance
Lean Six Sigma Application for Sustainable Production : A Case Study for Margarine Production in Zimbabwe 88

Lean Six Sigma is an integration of two World Class Manufacturing improvement philosophies(Lean Manufacturing and Six Sigma) that help organizations improve their performance and competitiveness. The principles are applied to margarine manufacturing. The Value Stream Mapping tool is used to map the processes and the Six Sigma’s Define, Measure, Analyze, Improve and Control (DMAIC) methodology applied to attain improvements. The Current State Map (CSM) is drawn and using the DMAIC methodology, the Future State Map (FSM) is drawn. The production line ultimately achieves improvements in cycle times and in Value Added time ratio from 39% to 94%. There are envisaged improvements of up to 86% on cycle times for individual processes.
Urbanisation Effect on the Occurrence of Urban Heat Island over Kano Metropolis, Nigeria

The Urban Heat Island (UHI) effect is a phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in surrounding rural areas happening majorly as a result of urbanisation and industrialisation. The effect of urbanisation on the occurrence of UHI in Kano metropolis was investigated. Landsat images of the study area for the years of 1986, 1998, 2006 and 2016 sourced from the archives of the United States Geological Survey (USGS) were utilised in this study. Land Surface Temperature (LST) and Land Use/Land Cover (LULC) maps for the years of 1986, 1996, 2006 and 2016 were estimated using Model Maker in Earth Resource Development Assessment System (ERDAS) Imaging 14 software. The urban city centre exhibit higher surface temperatures compared to its sub-urban counterparts thus, indicating the presence of the Surface UHI over Kano Metropolis. Urbanisation accounted for 80.5% increment in the LST of Kano Metropolis, thus indicating a very strong positive relationship between urbanisation and UHI. Conclusively, urbanisation is identified as the major factor that leads to the occurrence of surface UHI in Kano Metropolis. Recommendations include afforestation programmes, adoption of green and cool roofing technologies, proper spacing between houses, and accommodation of green areas and open spaces and continuous monitoring of weather events. Index Terms -Urbanisation, Urban Heat Island, Temperature, Atmospheric, Surface, Industrialisation ————————————————————
Hypoglycemic, Hepatoprotective and Hypolipidemic Effects of Pleurotus ostreatus in Alloxan-Induced Hyperglycemic Rats

Diabetes mellitus refers to a group of metabolic diseases characterized by high blood sugar (hyperglycemia) levels, which result from defects in insulin secretion, or action, or both. It is a potentially morbid condition with high prevalence worldwide, thus, the disease constitutes a major health concern. According to Wild et al., at least 171 million people worldwide suffered from diabetes as at the year 2000 (i.e about 2.8% of the population). In the year 2001, Beretta stated that according to the World Health Organization (WHO), there were approximately 160,000 diabetic patients worldwide, and the number has doubled in the last few years and is expected to double once again in year 2025. As a major health problem, diabetes is predisposed markedly by increased cardiovascular mortality and serious mortality related to development of nephropathy, neuropathy and retinopathy. Chemicals and biochemical hypoglycemic agents like insulin, tolbutamide, phenformin, troglitazone, metformin, rosiglitazone and repaglinide, are the mainstay of treatment of diabetes and are effective in controlling hyperglycemia but they have harmful side effects and fail to significantly alter the course of diabetic complication. Reports have shown that hyperlipidemia which often lead to coronary heart disease are associated with diabetes mellitus. This accounts for the treatment of lipid disorders as a part of diabetes management. Studies have also revealed that the activities of liver damage markers such as serum alanine
AGE GROUP CLASSIFICATION USING FACE FEATURES

Most of the facial features recognition, say for an example, character, gender and expression has been broadly envisioned. Programmed age assessment and prediction of future expressions have once in a while been examined. With the increase in age of human beings, we can see some gradual changes in their facial features. This paper aims to give a procedure to gauge age gathering that makes use of facial features. This procedure takes account of three stages: 1. Location, 2. Feature Extraction and 3. Classification. The geometric components of face pictures such as face edge, wrinkle topography, left eye to right eye separation, eye to nose separation, eye to jaw separation and eye to lip separation are calculated. By considering the surface and shape data, age grouping is done making use of K-Means bunching calculation. Age features are further ordered progressively based on the gathered data making use of K-Means bunching calculation. The acquired results are pretty vast and efficient. This paper can further be utilized for anticipating future confronts, arranging gender orientation, and expression recognition from images of the various faces.
Dual Modality : Mammogram and Ultrasound Feature Level Fusion for Characterization of Breast Mass

1 Abstract—detection of abnormalities in breast is done in different phases using different modalities and different biomedical techniques. These techniques and modalities are able to furnish morphological, metabolic and functional information of breast. Integrating these information assists in clinical decision making. But it is difficult to retrieve all these information from single modality. Multimodal techniques supply complementary information for improved therapy planning. This work concentrates on early detection of breast cancer which characterises the breast mass as malignant or benign by investigating the features retrieved from dual modalities: mammograms and Ultrasound. Architectural distortion (AD) with Spiculated mass is an important finding for the early detection of breast cancer. Such distortions can be classified as spiculation, retraction, and distortion which can be detected in mammograms. Spiculated masses carry a much higher risk of malignancy than calcifications or other types of masses. The proposed approach is based on the fusion of two modalities at feature extraction level with Z-Score Normalization technique to improve the performance of dual modality. Gabor filters are used to retrieve texture features from region of interest (ROI) of mammograms. Shape and structural features are retrieved from ROI’s of Ultrasound. In addition to that some other discriminative features like denseness texture feature, standard deviation, entropy and homogeneity are also extracted from ROI’s of both modalities. Feature level fusion is then achieved by using a simple concatenation rule. Finally classification is done using Support vector machine (SVM) classifiers to classify breast mass as malignant or benign. Receiver operating characteristic curves (ROC) are used to evaluate the performance. SVM classifiers achieved 95.6% sensitivity in characterising the breast masses using the features retrieved from two modalities.
LDR Image from HDR by Using Fast and Saliency Based Tone-Mapping Algorithm: A Review

- This paper presents a comparatively analysis of the fast and saliency feature based tone mapping technique. After analysis of these techniques we had concluded that fast tone-mapping algorithm is most computationally efficient and easy but there may be some halo artifacts. While in Visual-Salience-based Tone mapping method for High dynamic range images the halo artifacts significantly reduced. Thus salience based tone mapping gives best visual image quality as compared to fast tone mapping method. The visual quality of tone-mapped image, especially attention-salient regions, is improved by the saliency-aware weighting. Experimental results show that the saliency-aware technique produces good results on a variety of high dynamic range images .
Human Ear Segmentation Based on HSV Colorspace

— Human ear due to its consistent behavior over the age, has gained much popularity in recent years among various physiological biometric traits. Among various physiological biometric traits, ear has received much attention in recent years as it has been found to be a reliable biometrics for human recognition The shape of the outer ear is recognized as a valuable means for personal identification. Naturally, an ear biometric system consists of ear detection and ear recognition modules. Human ear detection is concerned with localize human ear in given profile face image. The ear detection system presented in this paper depends on using features based approach and pixel based, consists of two separate phases, the main objective from first phase is for determine the range rule that used for detect skin color area by using a number of images, the second phase consiste of five steps for detects and extracts ear clip area, these steps after read color face image, first step is converting to HSV color space, in second step, the extracted range rule is apply to obtain skin color area, noise removal using median filter is the third step, in fourth step localize the position of skin area in the image and finally remove unnecessary parts and extract ear clip.The proposed system tested on different profile face image randomly selected form internet in two cases (Left profile and Right profile), the background is not the same in all images. In experiments our system has achieved high detection rates (97.56%) to localize and extract a human ear clip.
Aggregation of Data Based on Clusters: A Bayesian Approach

: Wireless sensor networks are increasingly used in many real-time applications now-a-days for collection of data from remote areas. The efficient approach for aggregation of data is of at most concern as the sensor nodes are of limited energy and computational power. In this paper we discuss the cluster based technique along with the Bayesian network approach to overcome this problem. The proposed system adaptively uses a clustering technique. The sensed data from every sensor node is forwarded to the cluster heads which in turn forwards the collected data to the base station. The cluster heads forward the collected data to the base station by an optimal path which is chosen probabilistically by the Bayesian approach.
A Hybrid Model of Wavelet Transform and Artificial Neural Network for Gender Classification

In this study, we propose a system for gender classification from facial images by combining hybrid model of wavelet transform and neural network based on texture, information of colour and shape for achieving optimal classification. We use Daubechies wavelet transform at different levels to decompose the main image into sub images for analysis and feature extraction. The classification is based on feed-forward back propagation neural network. The decomposition coefficients obtained by wavelet transform are used as input vector for neural network. This study uses 500 images of FERET database that include both male and female gender. The experimental results show that the proposed method has more than 91% classification efficiency with both training and testing datasets.