Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterisation of a Bessel beam optical cell sorting system using microspheres

Accurate sorting of specific particles in a mixed population is a desirable capability in the field of biomedical sciences. This enables researchers to purify samples by selecting only the particles of interest. Optical sorting is achieved by using a Bessel beam, which is a non-diffracting, propagation invariant light pattern consisting of concentric rings around a bright central core. This type of beam profile has the ability to employ optical forces in manipulating matter in a sterile environment without physical interaction. The concentric rings enable the simultaneous manipulation of particles of various characteristics in multiple planes due to the different power intensity distributions. Sorting with Bessel beam is an attractive approach using small sample volumes (microliter ranges), which becomes beneficial when working with rare particles of interest and in small samples. In this study a home built Bessel beam optical sorting setup was used to sort polystyrene and silica microspheres of different sizes and refractive indices. Our preliminary results showed that the polystyrene microspheres travelled quicker than the silica type of spheres with the same size due to the high refractive indices. These findings indicate the potential application of sorting different cells with varying refractive indices such as differentiating HIV infected cells from uninfected cells.
Free-breathing MR T1-weighted imaging comparison in a very young pediatric patient population

Poster: "ECR 2012 / C-1661 / Free-breathing MR T1-weighted imaging comparison in a very young pediatric patient population" by: "A. F. Roque, M. Ramalho, V. A. G. Heredia, R. de Campos, R. Azevedo, R. C. Semelka; Chapel Hill, NC/US"
Comparative Study of Classification Algorithms Based On MapReduce Model

— Nowadays Classification is an important data mining problem. Classification Algorithms can be used for classifying the interested users. Today, all focus of the researchers and companies toward to big data. thus, many classification algorithms have been proposed in the past decades. Many of them have very limitation and weakness. One of the most important limitations is the time when we want to use this classification algorithm on the very large datasets which have poor run-time performance and high Computation time and cost. to covers this limitations, many researchers using this classification algorithm based on MapReduce. In this paper, we have studies these classification algorithms. then, we comparison with the traditional models. finally, highlighting the advantages of Mapreduce Models into traditional models.
Recognizing human body in still image.

— Division of human bodies in pictures may be a difficult task that may facilitate different applications, like scene understanding and activity recognition. It has found numerous applications like photograph album making, photo categorization and image recovery. The result can be further applied to various useful applications like part identification which can be more applied to gesture study as well as in track. Extracting human from pictures is still a difficult task because of various real world factors like shading, image clamor, occlusions, and background litter and also because of vast inconsistency of shapes, poses, garments etc. we propose a easy method for automatic retrivation of human bodies from still images. The location, dimensions, and color of the face are used for the localization of the outline, creation of the models for the upper and lower body in keeping with measurement constraints, and assessment of the color. Completely different levels of division graininess are combined to extract the cause with highest potential. The segments that belong to the shape arise through the joint estimation of the foreground and background throughout the part search phases, that alleviates the necessity for precise form matching. The performance of our rule is measured victimization forty pictures (43 persons) from the INRIA person dataset and 163 pictures from the “lab1” dataset, wherever the measured accuracies are eighty nine.52% and 96.68%, severally. Qualitative and quantitative experimental results demonstrate that our methodology outperforms progressive interactive and hybrid top-down/bottom-up approaches.
Screening of Cultivable Protease-Producing Bacteria in Marshy Sediments of Mangrove Forests, Goa, India

Mangroves, the coastal wetland forests are the natural inhabitants of variety of microbes especially halophilic bacteria. These halophilic bacteria are prevalent in ocean sediments and play crucial roles in degradation of sedimentary nitrogenous organic materials. The halophilic microorganisms are loaded with potential hydrolytic enzymes to be used in industrial and/or in many biotechnological processes. The bacterial diversity of mangroves in India and variety of their proteases inhabitants are largely unknown. This ambiguity is ascribed to enclosed ecosystem of mangrove region. This study is an attempt to unearth the expediency of mangrove forest for their variety of proteases. For this, bacterial samples were collected from Marshy Sediments of Mangrove Forests, Goa, India and were screened for proteases. Twenty isolates exhibited the proteolytic activity on Casein agar and Gelatin agar plates containing 3% (w/v) NaCl. All the isolates were identified by morphological and molecular characteristics. 16S rRNA sequence analysis showed their homology to Bacillus sp. Qualitative and quantitative enzyme essays revealed potential proteases from B2 and B3 bacterial strains. This study provided novel insights on the community structure of cultivable protease-producing bacteria in the marshy areas of Mangrove forests of Goa.
A Review on Association Rule mining methods

— –An Association rule mining is one of the most important task for learning meaningful knowledge from large collection of data.Association rule mining is normally performed in generation of frequentItemsets and rule generation in which many researchers presented several efficient algorithms. In this paper,the study includes association rules for mining knowledge and algorithms for association rule mining there are three methods of association rule mining which discuss in this paper that are Apriori, Eclat and FP growth.
Neighbor Coverage-Based Probabilistic Rebroadcast for Increasing Efficiency of Routing in MANETs

: For increasing efficiency in mobile ad-hoc networks (MANETs) containing high mobility of node, it is necessary to avoid frequent link breakages which lead to frequent path failures and route discoveries. In a route discovery, broadcasting is a fundamental and effective data dissemination mechanism, where a mobile node blindly rebroadcasts the first received route request packets unless it has a route to the destination, and thus it causes the broadcast storm problem. In this paper, we propose a neighbor coverage-based probabilistic rebroadcast protocol for reducing routing overhead in MANETs. In order to effectively exploit the neighbor coverage knowledge, we propose a novel rebroadcast delay to determine the rebroadcast order, and then we can obtain the more accurate additional coverage ratio by sensing neighbor coverage knowledge. We also define a connectivity factor to provide the node density adaptation.
An Integrated Method for Supplier Selection in a multi-product and quantity discount environment

Supplier selection or vendor selection is a complicated multi-criteria decision-making including both quantitative and qualitative factors. In order to select the best suppliers it is important to make a trade-off among these factors, some of them may conflict. The buyer should determine two important variables: the number of best suppliers and the amount of purchasing from each selected supplier. In this paper an integrated approach of MultiAttribute Utility Theory (MAUT) and Linear Programming (LP) is proposed for supplier selection problems when a buyer needs more than one product. Also, a Mixed Integer Linear Programming (MILP) approach is applied in a discount environment to determine the best suppliers and to place the optimal order quantities among them. Both cumulative and incremental discounts are taken into account in this study. Two numerical examples are presented for each discount policy to illustrate the application of the recommended models which in a reasonable time reach to an exact solution. [Ali Naimi Sadigh, Hamed Fallah, S. Kamal Chaharsooghi, Hamidreza Eskandari, Fariborz Jolai. An Integrated Method for Supplier Selection in a multi-product and quantity discount environment . Journal of American Science 2011; 7(10):553-560]. (ISSN: 1545-1003). http://www.americanscience. org.
Synchronization of Machine Learning into Electronic Health Records

The introduction of EHR (Electronic Health Record), in the medical field has been under discussion for a while but due to a very low acceptance rate of this technology by physicians, it has proven to be a risky gamble in the successful implementation of EHR. EHR uses data accumulated on the subject’s health to determine tests required, health analysis and real-time records to help the physician provide more accurate and detailed analysis on the subject. Due to Health Information Technology for Economic and Clinical Health (HITECH) there has been an increase in the amount of data accumulation by EHR. The data has great potential because of the large archive of information across the globe, but due to the random collection of data, it has resulted in the development of an unstructured record which has resulted to difficulty in transactions [1]. Even though there has been a large collection of data around the globe, the major issue has been making use of this data in a logical manner for purposeful implementation. The intention behind this paper is how to proceed with the implementation of machine learning in EHR along with its steps in order to analyze the data [2, 3] so that one can understand the pattern generated by the data provided. There are several machine learning algorithms for the
IN VITRO ANTIOXIDANT AND ANTIBACTERIAL ACTIVITY OF ESSENTIAL OIL FROM THE SEEDS OF NEOLITSEA PALLENS (D. DON) MOM & HARA

The essential oil from the seeds of Neolitsea pallens (D. Don) Moms & Hara growing in the Himalayan region is evaluated for its antioxidant activity using test for phenolic, flavanoid content and ferric reducing/antioxidant power assay (FRAP) and antibacterial activity by well diffusion method. The oil has shown 356.1 ± 0.003 mg/ml gallic acid equivalent per 100mg of the oil as total phenolic content and 355 ± 0.014 mg/ml quercetin equivalent per 100 mg of the oil as total flavonoid content. The oil exhibited marked antioxidant activity. The VEAC values were found to be 0.454g/L and 0.538g/L for the essential oil and ascorbic acid respectively. The ZOI for the test bacterial strains at a concentration of 500μg/ml were Gram negative bacteria Pseudomonas aeruginosa424 (7mm), Escherichia coli443 (4mm), Aeromonas hydrophila646 (4mm) and Gram positive bacteria Bacillus subtilis441 (4mm) and Staphylococcus aurieus737 (6mm).
Identification of Fatty Acid Content, Amino Acid Profile and Proximate Composition in Rainbow Trout (Oncorhynchus mykiss)

Rainbow trout (Oncorhynchus mykiss) was analyzed for proximate composition, amino acid and fatty acid profile. Chemical samples composition were determined using Association of Official Analytical Chemists (AOAC) methods. The protein content of rainbow trout was 19.65±1.2 %. The total lipid content was determined 4.46±0.2 %. The ash was measured 1.33±0.1 % rainbow trout flesh. The moisture content was recorded 71.7±1.9 %. Fatty acid composition were determined by gas chromatography, The total saturated fatty acid (SFA), monounsaturated fatty acid (MUFA) and polyunsaturated fatty acid (PUFA) content were 26.3%, 33.8% and 24.62% of total fatty acids, respectively. Finally, eicosapentaenoic acid (C20: 5 n-3) and docosahexaenoic acid C22: 6 n-3) were the dominant PUFAs. The ratio of n3/n6 fatty acids was 2. 06. Furthermore, The amount of essential amino acids was 35.74±0.1 %. Among amino acids, the glutamic acid, the aspartic acid and lysine were the predominant Amino acids by having 11.1 ±0.4 %, 9.53±0.1 %, and 7.72 ±0.1 % values respectively. The measured essential to nonessential (E/NS) ratio for the rainbow trout flesh was 0. 75. The present results demonstrate that rainbow trout fillet contains essential fatty acids particularly eicosapentaenoic acids and docosahexaenoic acids and essential amino acids for promoting good health, prevention and healing of diseases in humans. [Maryam Sabetian, Somayeh Torabi Delshad, Sohrab Moini, Houman Rajabi Islami, and Abbasali Motalebi. Identification of Fatty Acid Content, Amino Acid Profile and Proximate Composition in Rainbow Trout (Oncorhynchus mykiss). Journal of American Science. 2012; 8(4): 670-677]. (ISSN: 1545-1003). http://www.americanscience. org. 90
SURVEY ON SEQUENCE DISCOVERY USING DNA SEQUENCE MINING DATA

— Sequence Mining is one of the most commonly used technique in data mining. Sequence mining is the process of mining frequent patterns from a large datasets. The exiting algorithms have some limitations in predicting frequent patterns, in terms of time, space complexity and accuracy. To overcome these drawbacks, in this paper made a study on existing sequence mining algorithms and generate a new algorithm for generating frequent patterns from the biological sequences (DNA). This paper attempt to locate all the tandem repeats in a DNA sequence. The future scope of this paper is not only predicting the frequent patterns; but will also satisfy some factors such as: space complexity, time and predict accurate solution to the required problem using some algorithms. With the help of these three things into consideration an effective algorithm can be used for predicting the tandem repeat in a given DNA sequence.
Peri-implant Alveolar Bone Augmentation Using Allogeneic Marrow-Derived Stem Cells ; A Pilot Study in the Canine Mandible

Vertical bone augmentation at endosseous implants is a technically challenging procedure that, when successful, can contribute to the biomechanical and esthetic value of implant-supported dental rehabilitations. One approach is the creation of a protected space for host cell ingrowth and subsequent bone formation. The aim of this pilot study performed in the beagle dog model was to examine the feasibility of an alternative approach for concurrent implant placement and vertical bone augmentation using an allogeneic marrow-derived stem cell-based construct without a barrier membrane. Allogeneic marrow-derived stem cells were obtained from iliac crest aspirations from donor animals and subsequent cell culture expansion. Alveolar defects (7 mm long x 4 mm deep) were created six weeks following tooth extraction. Central to the defects, 3.5 x 8 mm endosseous implants were placed at a depth of 4.5 mm. The 3.5 mm of exposed implant was either a) left exposed to the forming blood clot, b) covered with a HA/TCP matrix, c) covered with an allogeneic-stem cell-loaded matrix or d) covered with an autogenous bone graft. After 6 weeks, block sections of the mandible were prepared for histological evaluation of healing. For each implant (2 per test group), three sections were made parallel with the long axis of the implants. The histological appearance of bone was scored for each dental implant at both the implant-host bone interface and the implant-regenerated bone interface. The results demonstrated that allogeneic stem cell-loaded devices supported the formation of a bone-to-implant interface along the entire vertical augmentation surface of the implants and along the bone-to-graft interface. Vertical augmentation was also achieved using autogenous bone. However, in the absence of allogeneic stem cells or in the absence of any matrix graft, bone regeneration failed to occur. This initial success with vertical alveolar bone augmentation at dental implants using an MSC-based tissue engineering approach suggests a number of avenues to improve or simplify current regenerative therapies in dentistry.
Interpreting Blood Perfusion Variations in Laser Doppler Imaging

We report on the feasible application of a motion based temporal template algorithm, the motion history image (MHI) on laser Doppler imaging (LDI) to follow blood perfusion variations. MHI was implemented on the LDI data to visualize perfusion changes during an arterial occlusion in a healthy subject. MHI effectively illustrated the locations where perfusion evolves with time. MHI rely on a rather simple algorithm that generates a static image template using a buffer of a temporal sequence of images, reflecting a temporal evolution of the perfusion changes. To help the clinicians and researchers, MHI can be tested on LDI data for the analysis of perfusion fluctuations.
Bio Technology: An Indian Journal

Introduction Succinate dehydrogenase (Succinate dehydrogenase, also called SDH) is a flavin enzymes enzyme. It is the inner mitochondrial membrane-bound enzyme, a membrane-bound enzyme. It is one of the hub linking oxidative phosphorylation and electron transfer, can provide a variety of electron in respiratory chain for eukaryotic and prokaryotic cell mitochondria, it is a sign of mitochondrial enzymes. As a key enzyme involved in the citric acid cycle, it is a reflection of succinate dehydrogenase mitochondrial function marker enzyme (marker enzyme) one. Its activity is generally run as an evaluation index of the degree citric acid cycle [1]. The research for it may have important significance for the evaluation of sperm mitochondrial function, researcher’s induced pathological process Cow-one deficiency [2,3].
Plasmid instability : measurement and use in antimicrobial action

The discovery of antibiotics in the early 20th century revolutionised medicine, but quickly bacteria began to demonstrate resistance to these agents. Antibiotic resistance is still on the increase, and soon, if this trend continues, bacterial infections may not be treatable with antibiotics. In an effort to prevent this occurring, the search for novel antibiotics is under way and new antibiotic targets are being considered. One target that has not been studied in depth is the partitioning systems of bacterial plasmids. Disruption of plasmid partition would prevent effective plasmid inheritance, which, in the case of resistance plasmids, would render the host cell antibiotic sensitive. The aim of this study was to determine whether plasmid partitioning is a viable target for a new antibiotic. A series of plasmids that contained genetically altered partitioning systems was used, which provided a range of plasmid stabilities. The plasmids all conferred antibiotic resistance on the host cell, allowing the effect of plasmid instability on a population grown in the presence of antibiotics to be determined. Several different methods of cell culture were used. Simple batch culture experiments allowed the observation that few plasmid-free cells were produced from cells containing plasmids that had a functional system. In contrast, plasmids containing a faulty system were found to be rapidly lost from the host cells. Steady-state chemostat culture was used to provide a simple model of a clinical infection. The formation of equilibria between plasmid-free and plasmid-bearing cells was observed, and the cultures contained a large proportion of plasmid-free cells when the experiments involved unstable plasmids. The slow growth rate of cultures in the chemostat was seen to dramatically affect the inheritance of plasmids relying on random distribution. Finally, cultures were subjected to washout in order to determine their maximum specific growth rate (µmax). While the results from these experiments are not entirely conclusive, there is a strong indication that the growth rate of cultures containing unstable plasmids grown in the presence of antibiotics is reduced.
Preparation of intranasal pregabalin microspheres: In vitro, ex vivo and in vivo pharmacodynamic evaluation

Background and Objective: Although, pregabalin shows high oral absorption, greater intrinsic efficacy to prevent seizure activity, its delayed transport across the blood-brain barrier limits the use in emergency epileptic seizures. Due to the particular anatomical features of the nasal cavity, intranasal (IN) administration has been explored as a means of preferential drug delivery to the brain. The objective of the present study was to improve therapeutic efficacy through IN administration of pregabalinloaded mucoadhesive microspheres. Materials and Methods: Chitosan-based mucoadhesive microspheres were prepared by ionotropic gelation method using glutaraldehyde as a crosslinking agent. Effect of chitosan concentration, glutaraldehyde concentration, and the stirring speed was investigated for the formation of microspheres. The physicochemical properties of microspheres, including particle size, zeta potential, drug content, entrapment efficiency, swelling index, and morphology were examined using suitable tools. Ex vivo bioadhesion, biocompatibility, and drug permeation were determined using sheep nasal mucosa. Anticonvulsant effect of pregabalin-loaded microspheres was investigated in pentylenetetrazole (PTZ) induced seizures in mice through IN administration. Results: Pregabalin-loaded chitosan microspheres were spherical shape 18.2–24.35 μm mean diameter, positive zeta potential, 80% entrapment efficiency, and 87.29% ex vivo drug permeation. The results of in vivo studies clearly indicated the greater anticonvulsant effect pregabalin in PTZ-induced seizures by IN route as compared to its peripheral administration. Conclusion: Thus, IN administration of pregabalin via mucoadhesive microspheres may be appropriate and valuable drug delivery system for the chronic and acute attacks of epileptic seizures.
Low Power Design of Standard Digital Gate Design Using Novel Sleep Transistor Technique

of power during the inactive state of circuits for a given area. Hence with the successive growth of the technology leakage power in an integrated circuit is also increasing. Abstract : In the nanometer range design technologies static power consumption is very important issue in present peripheral devices. In the CMOS based VLSI circuits technology is scaling towards down in respect of size and achieving higher operating speeds. We have also considered these parameters such that we can control the leakage power. As process model design are getting smaller the density of device increases and threshold voltage as well as oxide thickness decrease to maintain the device performance. In this article two novel circuit techniques for reduction leakage current in NAND and NOR inverters using novel sleepy and sleepy property are investigated. We have proposed a design model that has significant reduction in power dissipation during inactive (standby) mode of operation compared to classical power gating methods for these circuit techniques. The proposed circuit techniques are applied to NAND and NOR inverters and the results are compared with earlier inverter leakage minimization techniques. All low leakage models of inverters are designed and simulated in Tanner Tool environment using 65 nm CMOS Technology (1volt) technologies. Average
Soft clustering: An overview

— Document clustering has been extensively investigated as a methodology for improving document retrieval process. In Traditional clustering algorithm each documents belongs to exactly one cluster & hence cannot detect the multiple themes of a document where as soft clustering algorithm each document can belong to multiple clusters. This paper gives a comparative study of hard clustering & soft clustering algorithm.