Miracle-dz/UniFAR-FTUs huggingface dataset:
Proximate Composition of Whey from South West Nigeria

Whey samples from major small scale and individual soft cheese producing areas of South West Nigeria were subjected to analysis for their proximate compositions, and their proximate composition related to their functional properties in terms of acid stability, emulsification, aeration, foaming ability and gelling ability. The results of the analysis revealed that the protein content ranges from 0.36% to 0.46%, indicative of the ability of whey to produce foam, gel on heating, resist shear and denaturation on heating. Fat content obtained for each of the 4 different samples of whey is 0.26%, indicative of emulsification property and reduced foaming ability. Lactose content ranges from 3.98% to 4.06%. Sugar is an important factor in gel formation when used in combination with pectin. Ash content ranges from 0.84% to 0.95%, indicative of high ionic strength, the calcium content being an important factor in gel formation with low methoxyl pectin which forms thermo reversible gels with calcium. Lactic acid content ranges from 0.27% to 0.36%, indicative of acid coagulation for the manufacture of the cheese. pH in all the 4 different samples of whey is 5.9, an indication of acid stability and a condition necessary for gel formation. There were no significant differences (p<0.05) between the samples from the 4 different locations, in their moisture, protein, fat, lactose, ash and acidity contents when subjected to statistical analysis.
An Efficient Soft Set Approach for Association Rule Mining Using Constraints

: Here propose a new approach for finding association rule mining. In our proposed methodology we apply Soft set theory with constraints for finding the association rule. In previous paper a Soft set approach is used to find the association rule. In soft set approach first the transactional database is transferred into the Boolean valued information system because soft set is apply only on the Boolean valued information system and then uses the concept of parameter co-occurrence in a transaction we define the association rule. In this method the input is transactional database that contains the redundant and missing information therefore the final result generated is not accurate and contains some redundant information. To deal with such condition and to produce result that is free from such redundant result we propose a new approach which is based on Soft set theory with constraints that is used to deal with redundant and uncertain data that is present in transaction database.
AMERICAN JOURNAL OF BIOLOGICAL AND PHARMACEUTICAL RESEARCH

The design of the ophthalmic delivery system that enhances the bioavailability and to increase the residence time with improved mechanical properties and mucoadhesive properties has to be prepared in order to overcome the problems associated with the conventional ophthalmic solutions i.e., these conventional formulations eliminate rapidly after administration and cannot provide and maintain an adequate concentration of the drug in the pre corneal area and In order to avoid the rapid dilution, formulations with an increased viscosity have been evaluated. Among them, the thermo sensitive in situ gelforming formulations, which undergo phase transition from liquid to semisolid gel upon exposure to physiological environments, seem to be a promising tool. Thermo sensitive in situ gelling and mucoadhesive ophthalmic drug delivery system is designed by employing poloxamer407 as thermo gelling agent under physiological conditions in the ocular environment it under gones sol to gel phase transistion. The mucoadhesive material includes carbopol, chitosan, hydroxypropylcellulose (HPC), polycarbophil, polyvinylpyrrolidone (PVP) in various ratios inoder to obtain optimum muchoadhesive which plays a vital role in enhancing bioavailability.
An Efficient Diseases Classifier based on Microarray Datasets using Clustering ANOVA Extreme Learning Machine (CAELM)

Cancer is a group of diseases distinguished by unregulated growth and spread of cells which has become one of the most dangerous diseases. As a result of the victims of cancer are increasing steadily, the necessity is increasing to find classification techniques for cancer diseases. The present study is aimed to obtain better results of the classification model with high accuracy. Herein, we proposed a method of developing an efficient classifier based on microarray datasets. Moreover, we focused on accuracy, dimensionality reduction and fast classification issues. The proposed method Clustering ANOVA Extreme Learning Machine (CAELM) is a hybrid approach based on Extreme Leaning Machine with RBF kernel function. This hybrid approach consist of two phases: data preprocessing (normalization and genes selection) and data classifying. K-mean clustering was utilized as a method for clustering microarray datasets into three groups, then ANOVA were applied to analysis of variance between this groups to pick out the significant genes which were used in classification process. In case combining clustering with statistical analysis (CAELM) a much better classification accuracy is given of 95,94,100% for leukemia ,prostate and ovarian respectively . In addition, the proposed approach reduced time complexity with good performance.
An Analysis of the Relationship Between Electric Power Consumption and Economic Growth in D8 Countries. Asian J. Soc. Econ. Sci. 2 (3): 40-45.;

In today’s world, achieving the highest economic growth possible is an issue which has drawn much attention on the part of both economists and politicians especially in the developing countries. Energy as one of the most important factors in production, alongside with workforce and capital, plays a significant role in enhancing production and economic growth. Among all alternative energy forms and energy carriers, electricity enjoys the highest diversity of use, Minimizing the costs of energy consumption in industry leads to economic growth and development. Moreover, due to its natural effectiveness, and cleanness and lower pollution rate, as well as easy transmission, electricity has always been sought for the world over. However, this popularity brings along some basic questions. For instance, can electricity consumption induce more production and economic growth in developing countries? Or does economic growth in itself entail a boost in electricity consumption? To address these questions, this study aims at analyzing this relationship in the D8 group in the 1971-2010 interval using Pooled Mean Group Estimation of Dynamic Heterogeneous Panels (PMGE). The results show a mutual relationship between electricity consumption and economic growth. In other words, in D8 countries, electricity consumption and economic growth interact and complement each other.
Traumatic brain edema and survival - Effective role ofPentoxifylline

The study sought to confirm, the presence of harmful biomarker and free radical of trau-matic brain edema, malondialdehyde (MDA) in high levels within the brain tissue and plas-ma of brain injured as compared to normal brain tissue, and also its detrimental effect on brain, clinically. At the same time the study analyses the free radical – scavenging role of a pharmacological antioxidant agent called pentoxifylline, in terms of lowering the plasma levels of MDA and thereby clinical improvement. Biochemical estimation of plasma levels of malondialdehyde at regular intervals in all patients with traumatic brain edema showed de-creasing trend in plasma levels of patients (cases) receiving therapeutic doses of pharmacol-ogical agent, pentoxifylline. While as no change in high plasma levels of MDA was observed in traumatic brain edema patients (controls) on routine treatment (antiedema measures). This is an analysis of case – control study of 108 patients of traumatic brain edema, evalu-ated clinically by Glasgow coma scale (GCS) score, radiologically by serial computerized tomographic (CT) scans of the brain and biochemically by measuring plasma MDA levels in both, the cases (receiving pentoxifylline) and the controls (routine treatment). The youngest patient was 21 years of age, the oldest 66 years and most patients were in the age group of 21 to 45.There were only 12 female patients, six from each group. High morbidity was observed in both the groups, cases (pentoxifylline-group) and controls (control-group) but a mortality of 52.5% was observed in control-group of patients as compared to zero mortality in pen-toxifylline - group. This study confirms the beneficial role of pentoxifylline in patients of traumatic brain edema by antagonizing a product of lipid peroxidation, malondialdehyde.
REVERSIBLE PATCH BASED TEXTURE SYNTHESIS FROM A STEGOSYNTHETIC SOURCE IMAGE

: We propose a novel approach for steganography using a reversible texture synthesis from a stegosynthetic source image. This involves resampling of the original source image in order to hide the existence of secret message. We weave the texture synthesis process into steganography to conceal secret messages without leaving the chance for hacking. This allows us to extract the secret messages and source texture from a stego synthetic texture. This provides substantial benefits and provides an opportunity to extend various steganographic applications. Generally, Steganography is the science of hiding the existence of messages within images. In our paper, a patch based sampling is used to hide the existence of secret messages. From a stego synthetic source image, splitted into patches, secret messages are hidden in any of the patches, typically hard for unauthorized users to conceal the hidden message. The secret key is revealed only to the dedicated group of registered users, using a reversible steganographic algorithm. The source texture can be recovered using our proposed algorithm.
Cursor Movement in Real Time using Hand Gesture Recognition

This paper proposes a method for cursor movements by Classifiers. Purpose of this paper is to reduce the external hardware and to interact with the computer. The system consists of two modules namely, gesture recognition and control of cursor movements. Gesture attained using neural net training to the cascade Haar classifiers. Supervised neural net training helps in removing non-gesture pattern that helps to classify a frame as a gesture. The frame from the video recorded using web cam is given as input. Based on the extracted features, from the frame the cursor movements are controlled. This method improves the computational speed and also the effectiveness of communication. The tool used here is OpenCV 1.0 under Visual Studio 2008.
A Robust Image Steganography Technique Using Quantized Range Table And Local Area Pixel Value Differencing

— Steganography is a way of hiding the information transmitting from sender to receiver and making the communication invisible. To enlarge the capacity of hidden secret information and to produce indistinguishable stego-image from original image with human eye, a new steganographic approach using quantized range table using perfect square number and local area pixel value differencing is proposed in this paper. Our research provides a new viewpoint that if we choose the proper width for each range and use the proposed method, we can obtain better image quantity and higher capacity. In addition, we offer a theoretical analysis to show our method is well defined. The experiment results also show the proposed scheme has better image quantity and higher capacity.
Limited Usefulness of In Vitro Toxicity Data in Hazard Identification of Nanomaterials

With the increasing use and development of engineered nanomaterials in electronics, pesticides, consumer products, and chemical and pharmaceutical industries, there is a growing concern about their potential risks to humans and the environment. The toxic effects of most nanomaterials have not been characterized, but it is generally believed that nanoparticles can have toxicological properties that differ from their bulk materials. A challenge facing hazard identification and safety assessment of engineered nanomaterials is the diversity and complexity of the types of materials with varying physicochemical properties, many of which can affect their toxicity by different mechanisms [1].
Survey on MPPT Techniques in Photovoltaic Solar Energy Systems

_Tracking of the maximum power point of a photovoltaic array is usually an essential part of PV systems. In general, PV generation systems have two major problems; the conversion efficiency of electric power generation is low, and the amount of electric power generated by solar arrays changes continuously with weather conditions. Moreover, the solar cell I-V characteristic is nonlinear and varies with irradiation and temperature. There is a unique point on the I-V or P-V curve of the solar array called MPP, at which the entire PV system operates with maximum efficiency and produces its maximum output power. The location of the MPP is not known, but can be located, either through calculation models, or by search algorithms. Therefore MPPT techniques are needed to maintain the PV array‟s operating point at its MPP. In this paper, some of the most popular techniques are surveyed which are used in their work by most of the authors.
Real Time Driver Drowsiness Detection system using Image processing

: According to various studies and investigations it is noticed that one of the major cause behind the road accidents is driver’s drowsiness. Thus, countermeasure device is currently essential in many fields for sleepiness related accident prevention. Real-time driver drowsiness system alerts users when they are falling asleep. The project is designed to combat narcolepsy and microsleep. Microsleep strikes quickly. Users probably don’t even realize that they are in the process of falling asleep, and almost certainly don’t notice that eye blinking for longer than usual. The implemented project is mainly based on three components 1) Face and Eye detection: Performs scale invariant detection using Haar Cascade Classifier perform through a webcam. 2) Eye feature extraction: Eye features are extracted using Hough Circle and 3) Extract single eye and perform drowsiness detection on it. Whereas the complete system is implemented on Raspberry Pi which uses a webcam to monitor user’s eye blink rate and average blink duration to detect drowsiness. The project is designed for a car safety which helps prevent accidents caused by the driver getting drowsy.
Robotic Arm Manipulation Using Shape and Color Based On Visual Servoing

The robot arm is an ongoing computer vision project for which many enhancements have been done during the last years; the aim of the paper is to present a system for controlling a robot arm, based on image processing and recognition. One of the common task performed in an industries are picking and placing of the object from one place to another place, hence the aim of our project is to pick and place the object by vision system. Vision system determines the random scattered object on the plane and picks the object by the gripper of the Robotic Arm and places it in a particular location. Without the vision system, it is difficult for the Robotic Arm to detect the colored object. The Arm Edge robot arm is made to pick and place the object based on color thresholding and shape analysis based on Principal Component analysis (PCA).
Associations of intellectual ability, inhibitory control, impulsiveness, cognitive flexibility and functional impairment in adults with ADHD Symptoms

Introduction: Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder with persistent levels of inattention, hyperactivity or impulsivity. Recommendations for ADHD diagnosis involve: six or more symptoms (or five considering adults), early childhood onset, presence of symptoms in two or more contexts and presence of functional impairment. Cognitive deficits, that affect inhibitory control, cognitive flexibility and impulsiveness, are present in ADHD and affect the course of the disorder. On the other hand, intellectual skill is a factor of protection to improve the development in people with ADHD. This article explores how traits relate to functional impairments are relevant to ADHD description in terms of behavioral expression of the cognitive profile. Method: Forty-nine adults, between 20 and 68 years old, with symptoms of inattention and hyperactivity/impulsivity compatible with ADHD, with more than 4 years of schooling and absence of chronic illness, took part of this study. We collected data using screening instruments (ASRS-18, MMSE, and WASI) and main instruments (FDT, BIS-11, and EPF-ADHD). Results: The results have shown that higher intellectual indexes were associated with lower frequencies of academic impairment, while higher impulsivity levels, cognitive flexibility difficulties and inhibitory control, were associated with academic and social impairment. Conclusion: The results show that cognitive deficits were associated to impairment, in different life areas, of people with ADHD, and that some factors, as intellectual abilities, may prevent impairment in ADHD.
Biochemical characterization and antimicrobial susceptibility trends of Proteus mirabilis isolated from patients suspected with urinary tract infections attending Sickbay Hospital, Zaria, Kaduna, Nigeria

The research study on the biochemical characterization and antibiogram pattern of Proteus mirabilis isolated from patient suspected with urinary tract infections attending Sickbay hospital Ahmadu Bello University, Zaria was carried out. A total of 100 urine samples were collected from patients suspected with urinary tract infections, and screened for Proteus mirabilis using standard microbiological methods, out of which 20(20%) tested positive. The result shows that Streptomycin 20(100%), Erythromycin 17(85%), Ciprofloxacin 14(70%), and Sparfloxacin 15(75%) have the highest activity against the isolated Proteus mirabilis. While Proteus mirabilis recorded high resistance to Amoxicillin 20(100%), Tetracycline 19(95%), and Zinnacef 16(80%). The isolated Proteus mirabilis showed multiple drug resistance ability to the antibiotics used. It is concluded that all the antimicrobial agents that were found to be active against the test organisms can be used as the first-line drugs of choice for the treatment of urinary tract infections caused by Proteus mirabilis. Those antimicrobial agents that showed relative inactivity against the isolated Proteus mirabilis should be discouraged in the treatment of infections caused by the bacterium.
Review on Anthocyanins as herbal pH indicators

In the acid-base titrations, standard synthetic indicators are used to exhibit color change at different pH intervals. Anthocyanins (natural color pigments) in plants exhibit color changes with pH variations. The aim of this study is to investigate the activity of plant extracts, Rosa indica and Rubus occidentalis, to replace the synthetic indicators. Synthetic indicators cause chemical and environmental pollution, are toxic, expensive and rarely available. Methanolic extracts of Rosa indica and Rubus occidentalis exhibit sharp and intense color change in comparison to the standard synthetic indicators phenolphthalein and methyl orange. Herbal indicators are pollution-free, non-toxic, easily available and cost-effective.
Multimodal Image Fusion in Clinical Research

With the advancement in medical imaging, far reaching changes are perceptible in clinical analysis. Most of the diagnosed medical evaluation is a resultant of imaging or it is in close synchronization with imaging techniques. This promotes the need to closely read, evaluate and collaborate images. Medical image fusion is a technique to collaborate the clinical images acquired from one or many modalities. Multimodal image analysis during fusion well capitalizes the strength of each medical modality. Incorporating the features from multimodal input images thus holds added potential to abet better-quality diagnosis. Medical image fusion is an intricate task specially when high quality fused image, possessing all relevant information and reasonable operating speed is aimed. Many efforts have been undertaken in this field resulting in diverse research approaches. Image fusion can be performed using medical images obtained from single modality or from multiple modalities. This paper has been designed collaborating the work based on multimodal medical images in multiscale image fusion domain. When the same region, organ or a tissue is captured from various different perceptions, complimentary information is maximized and diagnostic value is reinforced. The fusion framework using Mexican Hat wavelet is proposed using adaptive median filtering detailing each executable fusion block. The Fusion techniques, pre and post processing aspects and evaluation mechanisms are illustrated from literature. The drifts of researchers from single processing to multiple processing hybrid techniques are discussed. The medical modality aspects are detailed. These may provide as a valuable reference to understand the image fusion trade-offs comprehensively with future viabilities.
Specifying CPU Requirements for HPC Applications via ML Techniques

---------------------------------------------------------------------- ABSTRACT ------------------------------------------------------------ Resource distribution in data centers is difficult for service providers because of the structures of usage and condition setup decisions. Customers encounter issues to anticipate the amount of CPU and memory required for job execution, and henceforth are not ready to assess when work yield shall be accessible to plan for next analyses. Systems that utilize cluster scheduler structures to gauge job execution time exists in the literature. Notwithstanding, we have seen that such methods are not appropriate for anticipating CPU utilization. In this paper, we assist customers to figure out their applications CPU usage utilizing machine learning (ML) techniques. We analyze how scheduler can be utilized to predict CPU utilization through ML techniques, and its evaluation on two frameworks containing an enormous number of user jobs.
Study of Cationic Interference in the Determination of Mercury By Cold Vapor Atomic Absorption Spectroscopy

The interference due to different Cations in the analysis of Mercury by Cold Vapor Atomic Absorption Spectroscopy (CVAAS) at trace levels has been investigated and presented in this report in this report. There is always a chance of interference due to several factors in a quantitative analysis. Different cations (Na+, Fe2+ , Zn2+,Cr3+,Co2+,Ni2+,Cu2+ ) were examined as possible interferents in the analysis of mercury by CVAAS under specific conditions. Some cations did not have any impact, while present in the detection of mercury, whereas others had a marked influence on the analytical results and can be suggested as possible interfering agents for this method of Hg analysis. Using single standard calibration with a 10ppb Hg solution, varying concentrations of different metal solutions, having same Hg concentrations as those of the standard solution, have been analyzed by CVAAS. The cations that interfered in the quantitative determination of mercury were further checked, by employing finer differences concentrations of the interferent. Sodium concentration was checked up to 50,000ppm because it is present in marine samples in higher concentrations.