bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and Application of Computational Methods in Phage Display Technology
Authors: He Bifang , Dzisoo Anthony Mackitz , Derda Ratmir , Huang Jian 
Published: June 2018

Background:
Phage display is a powerful and versatile technology for the identification
of peptide ligands binding to multiple targets, which has been successfully employed in
various fields, such as diagnostics and therapeutics, drug-delivery and material science. The
integration of next generation sequencing technology with phage display makes this methodology
more productive. With the widespread use of this technique and the fast accumulation
of phage display data, databases for these data and computational methods have become an
indispensable part in this community. This review aims to summarize and discuss recent progress
in the development and application of computational methods in the field of phage display.

Methods:
We undertook a comprehensive search of bioinformatics resources and computational
methods for phage display data via Google Scholar and PubMed. The methods and
tools were further divided into different categories according to their uses.

Results:
We described seven special or relevant databases for phage display data, which provided
an evidence-based source for phage display researchers to clean their biopanning results.
These databases can identify and report possible target-unrelated peptides (TUPs),
thereby excluding false-positive data from peptides obtained from phage display screening
experiments. More than 20 computational methods for analyzing biopanning data were also
reviewed. These methods were classified into computational methods for reporting TUPs, for
predicting epitopes and for analyzing next generation phage display data.

Conclusion:
The current bioinformatics archives, methods and tools reviewed here have
benefitted the biopanning community. To develop better or new computational tools, some
promising directions are also discussed.
Formulation, Pharmacokinetic Evaluation and Cytotoxicity of an Enhanced- penetration Paclitaxel Nanosuspension
Authors: Cao Yanping , Wei Zhihao , Li Mengmeng , Wang Haiyan , Yin Li , Chen Dongxiao , Wang Yanfei , Chen Yongchao , Yuan Qi , Pu Xiaohui , Zong Lanlan , Duan Shaofeng 
Published: June 2018

Background:
Improving poorly soluble drugs into druggability was a major problem faced
by pharmaceutists. Nanosuspension can improve the druggability of insoluble drugs by improving the
solubility, chemical stability and reducing the use of additives, which provided a new approach for the
development and application of the insoluble drugs formulation. Paclitaxel (PTX) is a well-known BCS
class IV drug with poor solubility and permeability. Also, many studies have proved that paclitaxel is a
substrate of the membrane-bound drug efflux pump P-glycoprotein (P-gp), therefore it often shows
limited efficacy against the resistant tumors and oral absorption or uptake.

Objective:
To manufacture an enhanced-penetration PTX nanosuspension (PTX-Nanos), and evaluate
the physicochemical property, pharmacokinetics and tissue distribution in vivo and cytotoxic effect
in vitro.

Methods:
PTX-Nanos were prepared by microprecipitation-high pressure homogenization, with a
good biocompatibility amphiphilic block copolymer poly(L-phenylalanine)-b-poly(L-aspartic acid)
(PPA-PAA) as stabilizer.

Results:
The PTX-Nanos had a sustained-dissolution manner and could effectively reduce plasma peak
concentration and extend plasma circulating time as compared to PTX injection, markedly passively
targeting the MPS-related organs, such as liver and spleen. This unique property might enhance treatment
of cancer in these tissues and reduce the side effects in other normal tissues. Moreover, the hybrid
stabilizers could enhance penetration of PTX in PTX-Nanos to multidrug resistance cells.

Conclusion:
To sum up, our results showed that the optimal formula could improve the solubility of
PTX and the stability of the product. The PTX-Nanos developed in this research would be a promising
delivery platform in cancer treatment.
Behavior Models of Voltage Differencing Inverting Buffered Amplifier and Applications in Circuit Analysis
Authors: LI YongAn 
Published: June 2018

Background:
The symbolic nodal analysis acts as a pivotal part of the very large scale
integration (VLSI) design.

Methods:
In this work, based on the terminal relations for the pathological elements and the voltage
differencing inverting buffered amplifier (VDIBA), twelve alternative pathological models for the
VDIBA are presented. Moreover, the proposed models are applied to the VDIBA-based second-order
filter and oscillator so as to simplify the circuit analysis.

Results:
The result shows that the behavioral models for the VDIBA are systematic, effective and
powerful in the symbolic nodal circuit analysis.</P>
Un proyecto de modernidad católico: el Ecuador de García Moreno
Authors: Valero Pacheco Perla Patricia 
Published: June 2018

<p class="p1">Al término de las guerras de independencia en la América Latina continental de 1830, los nuevos gobiernos se enfrentaron al problema de construir Estados y naciones sobre las ruinas del antiguo régimen, después de haber destruido –en palabras de Halperin Donghi– el “botín de los vencedores”. Estos procesos ocurrieron de diversas formas a lo largo y ancho del continente; en este trabajo nos enfocamos de modo particular en las reformas eclesiásticas, en ese proceso de independencia de las iglesias locales, de invención de la Iglesia como institución y su posterior secularización, eventos que van de la mano y se entrecruzan con la construcción de los Estados. Trataremos el caso del Ecuador en la década de 1860, cuando Gabriel García Moreno se convirtió en la cabeza de un gobierno conservador y católico que aplicó reformas galicanas y hasta anticlericales haciendo una alianza con la Santa Sede. </p>
La simultaneidad en la historia global
Authors: Rabasa José 
Published: June 2018

<p class="p1">El trabajo cuestiona que el llamado <em>Mapa de Cuauhtinchan </em>núm. 2, pueda ser analizado, desde el presente y con la carga de valores culturales occidentales, como un mapa en estricto sentido. El propósito de este ensayo es discutir aquellas visiones, como las de Carl Schmitt, que plantean una universalidad de la “apropiación, distribución, y producción” del <em>nomos, </em>apuntando hacia una actitud que apueste por la pluralidad de las formas de representar los distintos espacios tiempos. En este sentido el autor avanza en la manera de proponer distintas categorías que permitan una mejor comprensión de los documentos pictográficos que se produjeron antes y durante la conquista de Mesoamérica y las demás latitudes que fueron colonizadas por los españoles. </p>
In vitro ruminal degradation of neutral detergent fiber insoluble protein from tropical pastures fertilized with nitrogen
Authors: Juárez Lagunes Francisco Indalecio , N. Pell Alice , Blake Robert W. , Montero Lagunes Maribel , Pinos Rodríguez Juan Manuel 
Published: June 2018

The objective was to determine in vitro the NDF insoluble protein (NDIP) extension and degradation rate of four tropical grasses by the potential effect of N fertilization. The grasses (Andropogon gayanus, Brachiaria brizantha, Cynodon plectostachyus and Megathyrsus maximus) that grow in Mexico were used. Each grass was grown in four plots (5×5 m), fertilized (relationship equivalent to 0 and 100 kg N/ha) and clipped 35 d after the N fertilization. A complete randomized block design with factorial arrangement 4×2, and two replicates per treatment was used, where the factors were grass species and N fertilization. Non-protein nitrogen (NPN), buffer insoluble protein (IP), NDIP and acid detergent insoluble protein (ADIP) were performed. Freeze-dried samples were incubated at 0, 1.5, 3, 6, 9, 12, 24, 48 and 96 h. After fermentation, the CP content of the NDF residues was determined. An exponential equation was used to determine the rate of the NDIP disappearance. There was no detectable interaction between type of grass and fertilization level. The NDIP (as %CP) averaged 35 % with a range of 10 to 60 %. The NDIP variation was primarily due to species. The extent and rates of degradation of the NDIP were 70.6 % and 7.1 %/h respectively, with no N-fertilization effect. The NDIP was degraded faster (P≤0.05) than NDF (7.7 vs 5.0 %/h). These data show that the NDIP is ruminally degraded and that this fraction significantly contributes to the rumen nitrogen supply.
Detección de Neospora caninum en ganado lechero sacrificado en Aguascalientes, México
Authors: Medina-Esparza Leticia Esperanza , De Luna-Oseguera Ricardo , Vitela-Mendoza Irene Victoria , Cruz-Vázquez Carlos 
Published: June 2018

Con el objetivo de detectar la presencia de Neospora caninum en tejidos, suero y sangre periférica de ganado lechero sacrificado en rastros de Aguascalientes, México, se colectaron muestras de médula espinal, corazón, hígado, sangre y suero sanguíneo de 71 animales adultos. Las muestras de suero se procesaron mediante la prueba de ELISA para detectar anticuerpos anti-N. caninum, mientras que las otras se sometieron a la prueba de PCR anidado para determinar la frecuencia de ADN del parásito en los diferentes tejidos, así como en sangre. La frecuencia general de animales seropositivos fue de 41 % (29/71; IC 95% 29-53) con un rango de 33 a 57 %. La frecuencia de detección de ADN de N. caninum en sangre fue 44 % (31/71; IC 95% 32-55), con un rango entre 38 y 50 %; en las muestras de médula espinal de 32 % (27/71; IC 95% 27-50), con un rango de 2 a 38 %; en las muestras de corazón, 22 % (16/71; IC 95% 13-34), con un rango de 4 a 33 %; y en las de hígado, 32 % (23/71; IC 95% 22-44), con un rango de 28 a 57 %. La concordancia entre la prueba de ELISA y la de PCR en sangre fue k= 0.36, de ELISA y PCR en tejidos k= 0.07 y de PCR en sangre y PCR en tejidos k= 0.61. Únicamente 11 vacas fueron positivas a las tres pruebas.
Appraisal of the ‘Prospects and Challenges’ of Cloud Computing and Distance Learning in the National Open University of Nigeria
Authors: Touitou Tina C 
Published: June 2018

This paper focuses in examining the distance education, cloud computing and platforms, E- learning and its approaches via cloud computing, benefits and challenges in National Open University (NOUN) in Nigeria.Cloud computing and distance learning are rising speedily and play vital and powerful roles in education and learning in Nigeria today. The use of distance education in learning has come to stay and is being adopted, it needs to be constantly dynamic and innovative. It’s has the potential to transform the way distance education is consumed along with internet resources. It supports the smart phone mobile users to perform their tasks effectively- through paying less cost by utilizing the cloud based applications offered by the cloud service providers. The review of literature shows that the use of cloud computing is the best practice for the present educational situation. Despite the benefits associated with cloud-computing, there are still factors hindering the effective adoption of cloud computing in Nigerian educational system which among others include the epileptic power supply, low bandwidth just to mention a few.Survey study that was conducted by DAMAR &NUHU 2015, that was adopted to authenticate this study, one hundred and seventy (170) students who indicated knowledge on the importance of cloud computing, but were not very satisfied with the confidentiality and accessibility of the services rendered to them in the cloud computing platform. Some of the reasons could be as a result of poor network and lack of confidence using information technology. The paper recommended among others, steady power supply, guarantee service confidentiality, accessibility and more reduction in cost.
A Comparative Study of Various Techniques used for Melanoma Detection
Authors: RAJU K RAINA , Kumar S. Swapna 
Published: June 2018

Skin cancer is one of the most fatal disease. It is easily curable, when it is detected in its beginning stage. Early detection of melanoma through accurate techniques and innovative technologies has the greatest potential for decreasing mortality associated with this disease. Mainly there are four steps for detecting melanoma which includes preprocessing, segmentation, feature extraction and classification. The preprocessing stage will remove all the artifacts associated with the lesion. The exact boundaries of lesion are identified from normal skin through segmentation method. Feature extraction stage is used for calculating and obtaining different parameters of the lesion region. The final stage is to classify the lesion as benign or malignant. In this paper different types of segmentation methods and classification methods are described. Both of these stages are accurately implemented to reach the final detection of the lesion.
RBF Neural Network (RBFNN) using Density Based Clustering for Liver Disorder Dataset
Authors: Godara Sunila , Singh Rishipal , Kumar Sanjeev 
Published: June 2018

Clustering is an unsupervised classification that is the partitioning of a data set in a set of meaningful subsets. Each object in dataset shares some common property- often proximity according to some defined distance measure. In this paper we will extend our previous work [15]. Simple K-means and Proposed makeDensityBased Clustering (MDBC) are embedded in RBF Neural Network (RBFNN). We evaluated the performance of RBFNN using K-Means and Proposed makeDensityBased Clustering on Liver Disorder Dataset. Proposed algorithm is superior to the existing makeDensityBased Clustering algorithm [15], but it is not capable of performing well when it is embedded with RBFNN.
A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment
Authors: Kaur Ramandeep 
Published: June 2018

A lot of research has been done in the field of cloud computing in computing domain. For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony .Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.
Determination of Some Heavy Metals in Milk of Cow Grazing At Selected Areas, of Kaduna Metropolis
Authors: Imam Mahmud Mohammed , Muhammad Zahra , Zakari Amina 
Published: June 2018

In this research work the concentration of zinc, copper, lead, chromium, cadmium, and nickel in cow milk samples obtained from four different grazing areas (kakuri, kudendan, malali, kawo) of Kaduna metropolis. The samples were digested by wet digestion technique .The trace element were determined using bulk scientific model VPG 210 model Atomic Absorption Spectrophotometer (AAS).. The concentration of the determined heavy metal were The result revealed that Cr, Ni and Cd were not detected in milk samples from Kawo, Malali and Kudendan whereas lead (Pb) is detected in all samples and found to be above the stipulated limits of recommended dietary allowance (NRC,1989) given as 0.02mg/day. Cu and Zn are essential elements needed by the body for proper metabolism and as such their deficiency or excess is very dangerous for human health. However, they were found in all samples and are within the recommended limits while Cd (2.13 – 3.15 mg/kg) in milk samples from Kakuri was found to be above such limit (0.5mg/day). Cow milk samples analyzed for heavy metals in this research work pose a threat of lead and cadmium toxicity due to their exposure to direct sources of air, water and plants in these grazing areas, thereby, resulting to a potential health risk to the consumers.
Development of a Novel Lung Cancer Detection Technique based upon Micro Vessel Density Analysis
Authors: Kaur Pawandeep , Bhatia Rekha 
Published: June 2018

In the medical field, Image processing methods are widely used. It is a method for the improvement of image, the image which is obtained after processing is useful for earlier detection and various stages of cancer. In cancer tumors such as lung cancer time factor is the important key point because in the targated images of lung cancer time factor is use to discover the abnormality. Basically the development of numerous uncontrolled cells in the tissues create abnormality which later on leads to tumor in lungs. It is necessary to detect lung cancer in earlier stages, if left untreated its growth may spread into other nearby parts of body. For diagnosis, Patients may undergo several imaging tests such as CT scan, Chest X-ray and PET scan.In the existing recognition and detection techniques the Micro vessel density (MVD) analysis is used from which geometrical features are extracted to detect the tumorin lungs. In alternate to this the Gray level co-occurrence matrix (GLCM) may also be used with the geometrical features of the image to obtain more accurate result of lung cancer detection. GLCM features such as image contrast, homogeneity, dissimilarity, energy and correlation is beneficial to obtain results with higher accuracy. On the basis of significant instrument, novel lung cancer prediction framework will be developed.
Mining Big Data: Its Current Status and Future
Authors: Chouhan Mayushi , Nain Rohit Singh 
Published: June 2018

Organizations create 2.5 Quintilian bytes of data. So much that 90% of the data in the world today has been set up in the last two years alone. What is Big Data? Big Data is large volumes of structured and unstructured data. This data is what organizations collect on a daily basis. The amount of data is not the important part, but the information gathered from that data is the key. Collecting and analyzing Big Data gives organizations enhanced insight, decision making, and process automation. Approximately each one can agree that big data has taken the business world by storm, but what’s next? Will data continue to grow? What technologies will develop around it? Or will big data become a relic as quickly as the next trend — cognitive technology? Fast data? - appears on the horizon. I believe, am that big data is only going to get bigger and those companies that ignore it will be left further and further behind. This paper studies about what is big data, how does it helps organizations to extract information, its tools and technologies and its future.
Hybrid Algorithm for Deforestation Detection Using Satellite Data by Using Support Vector Machine (SVM) Algorithm
Authors: Babu J Suresh , Sudha T. 
Published: June 2018

There are many applications of Remote sensing Satellite images like (astronomy, military, forecasting, and geographical information). Using satellite remote sensing data sets we developed the mapping forest area cover change. This kind of multiple improvement and identifying methods have a Training Data Automation algorithm which is used for advanced vector machines procedure. This TDM technique capable of automatically generating exact image enhanced patches. The obtained high resolute training data allow in producing the dependable forest cover change products with the help of SVM. This process was tested in study areas selected from major forest areas across the globe. In each area, a forest cover change map was produced using a pair of real time Land sat images acquired around 1999 and 2015.
The Impact of Loan Portfolio Diversification on Tunisian Bank’s Profitability
Authors: Belguith Houda , Bellouma Meryem 
Published: June 2018

This paper examines the effect of loan portfolio diversification on Tunisian banks profitability over the period 2000-2015. By using panel data method, our finding, show that focusing on few sectors is more profitable than diversifying bank lending operations. In addition, we find that this negative impact is more pronounced in private banks. However, for foreign banks loan portfolio diversification is found to be positively associated with higher bank profitability. Also, we find support to the hypothesis stating that the positive effect of loan portfolio diversification is more pronounced for credit risky banks.
A Study of Learners in Information Retrieval System in Relation to Learning Parameters
Authors: Hota C P Pavan Kumar , Prasad V Leela 
Published: June 2018

For the last few years, education methodologies are drastically changing as per leaner’s needs. In the current competitive environment, if a learner wants to achieve a good grade in their course work the learner should focus on various parameters as per their learning style. In this paper, we focused mainly on learner-centric approach rather than teacher-centric approach. Learner -centric approach facilitates the leaner to involve in the teaching learning process. In this approach, educationist considers learning curricula, learning theories, learning styles, learning models, learning methods, and learning evaluation to understand learner’s effectively. Educationist can track the involvement of the learner and their progress by various approaches, but learning analytics is a modern approach to understand, focus and analyze learner’s easily with available tools and technologies. In this paper, we focused on learning analytics approach with a group of learners to understand their ability of learning based on cognitive theory and able to find slow and fast learners.
HUMO-LUMO Studies on Methyl Orange Doped ZTS Crystals for Laser Applications
Authors: Suresh G. , Kumar K. Sambath , Ambalavanan P. , Kumaresan P. 
Published: June 2018

Zinc Thiourea Sulphate (ZTS), crystal is a magnificent metal natural compound, which consolidates the upsides of both natural and inorganic materials when contrasted and other customary non-linear optical materials and in this way can be utilized as a part of a more extensive scope of uses. Late endeavors at delivering new recurrence transformation materials have concentrated essentially on expanding the extent of the NLO properties that can recurrence twofold low pinnacle control sources, for example, diode lasers. The thermo gravimetric examination (TGA) and differential warm investigation (DTA) were completed utilizing Seiko warm analyzer at warming rate 20°C/min in air to decide the warm dependability of the compound. ZTS crystals were developed by moderate cooling procedure. This empowers the development of mass gems along all the three bearings at an ideal pH. FTIR examines demonstrate that in the spectra of ZTS there is a move in the recurrence band in the low-recurrence district which uncovers that thiourea shapes sulfur-to-zinc securities in the ZTS crystals. The stability and charge delocalization of the molecule were also studied by natural bond orbital (NBO) analysis. The HOMO-LUMO energies describe the charge transfer takes place within the molecule. Molecular electrostatic potential has been analyzed. The developments try in extensive scale with this enhanced pH qualities is required to yield mass crystal appropriate for laser combination tests and SHG device applications.