Miracle-dz/UniFAR-FTUs huggingface dataset:
Fogarty® catheter dilatation of veins smaller than 2.5 mm after completion of the anastomosis during arteriovenous fistula creation

Introduction. Risk of failure after surgical creation of the AVF was linked to the diameter and flow dynamics of the vessel that is to be quantified by preoperative ultrasound mapping. We aimed to report our results using a different technique consisting of Fogarty® catheter dilatation of the cephalic vein after completion of the anastomosis. Material and methods. A total of 23 patients, aged between 35 to 70 years, with a cephalic vein diameter of ≤ 2.5 mm received a dilatation technique for arteriovenous creation. Patients having reoperations, aneurysmatic or thrombosed veins and multiple risk factors were not considered eligible and access failure within 60 days was defined as early fistula failure. Results. Mean cephalic vein diameter was 2.03 ± 0.28 mm and mean radial artery diameter was 2.33 ± 0.16 mm. At 15th day visit, 21 of 23 patients (91.3%) had patent arteriovenous fistula. Mean time of follow-up was 7.2 ± 1.67 months and was complete in 20 of 21 patients with a patent fistula. Overall patency was 18/23 (78.2%) in patients with survived AVFs. Conclusion. Fogarty® catheter dilatation of the cephalic vein after completion of the anastomosis during arteriovenous fistula creation is effective and safe in patients with small calibrated veins.
Identifying the Patterns of Hematopoietic Stem Cells Gene Expressions Using Clustering Methods: Comparison and Summary

Clustering algorithms have been used to analyze microarray gene expression data in many recent applications. In this paper, we make a comparison among popularly used clustering methods, including hierarchi- cal clustering with average, complete, and single linkages, k-means cluster- ing, k-means clustering with hierarchical initialization, and self organization map (SOM), by making use of our hemotopietic stem cell (HSC) microar- ray data. To understand the biological pathways from HSC to proliferative multipotent progenitor (MPP), and from MPP to either common lymphoid progenitor (CLP) or common myeloid progenitor (CMP), statistical cluster- ing is an important tool. Our results demonstrated that the HSC microarray data set casts some challenge on clustering algorithms as different clustering algorithms resulted in clusters that were not all consistent. We compared the results by using the total within-cluster sum of squares of dispersions and the biological functions of the genes, and reached the conclusion that k- means clustering with hierarchical average or complete linkage initialization performed the best among all the methods we compared. Our investigation of the clustering methods with HSC microarray data provide a useful ap- proach and guide to medical researchers who use clustering algorithms in analyzing their microarray or related data sets.
of the 4-7 July 2000 – Valencia Spain

The multifactorial rabbit enteropathy has a great importance in rabbit meat production for its economical impact. Our purposes was to estimate the prevalence of different viruses, identified by negative contrast electron microscopy, on samples from rabbits showing either a “generic” enteropathy or lesions referable to mucoid enteropathy-caecal impaction and then to relate their presence with the symptoms and lesions observed. During the period 1982-85 and 1990-99, we examined 1067 samples taken mainly (80%) from rabbits showing catharral, haemorrhagic or necrotic entero-tiflitis; the rest (20%) were showing mucoid enteropathy and caecal impaction. By EM we observed the presence of viral particles in 37.3% of them; rotavirus was identified in 41.9%, coronavirus-like virus in 25.6%, parvovirus in 21.1% and enterovirus-like virus in 10.3% of the positive samples. We also found sporadically adenovirus, calicivirus and reovirus. Often (30 cases) we contemporarily observed in the same sample two or three different viruses in association. The pathogenic role and importance as primary agent of each virus are discussed. Moreover, the availability of the results of microbiological and parasitological analysis carried out in the last triennium allowed to correlate EM observations with the contemporary presence of others pathogenic agents such as rotavirus, enteropathogenic Escherichia coli (EPEC) and Staph. aureus in sucklings rabbits; EPEC, Cl. spiroforme and flagellate protozoa in the others.
Colorization of Medical Images

Colorization is a term used to describe a computerized process for adding color to black and white pictures, movies or TV programs. This process can also be used to convert the gray scale medical images to their colorized version, as color increases the visual appeal of an image and it also makes a medical visualization more attractive. Changes in color are more easily perceived than changes in shades of gray and therefore this procedure makes the interpretation and understanding of the image easier. During colorization process a scalar value representing pixel’s intensity is being replaced by a vector in a given color space. Since the mapping between intensity and color has no inherently correct solution, human interaction and external information usually plays a large role. In this paper we present a novel colorization method based on the morphological distance transformation which considers the image structures to automatically propagate the color inserted into the image by a user. The effectiveness of the algorithm allows to work interactively and to obtain desired results promptly after providing the color information. In the paper we show that the proposed technique allows for high quality colorization of medical images.
Limited thermal conductance of metal-carbon interfaces

The thermal conductance for a series of metal-graphite interfaces has been experimentally measured with time-domain thermoreflectance (TDTR). For metals with Debye temperatures up to ∼400 K, a linear relationship exists with the thermal conductance values. For metals with Debye temperatures in excess of ∼400 K, the measured metal-graphite thermal conductance values remain constant near 60 MW m−2 K−1. Titanium showed slightly higher conductance than aluminum, despite the closeness of atomic mass and Debye temperature for the two metals. Surface analysis was used to identify the presence of titanium carbide at the interface in contrast to the aluminum and gold-carbon interfaces (with no detectable carbide phases). It was also observed that air-cleaved graphite surfaces in contact with metals yielded slightly higher thermal conductance than graphite surfaces cleaved in vacuo. Examination of samples with scanning electron microscopy revealed that the lack of absorbed molecules on the graphite surface resulted in differences in transducer film morphology, thereby altering the interface conductance. Classical molecular dynamic simulations of metal-carbon nanotube thermal conductance values were calculated and compared to the TDTR results. The upper limit of metal-graphite thermal conductance is attributed to the decreased coupling at higher frequencies of the lighter metals studied, and to the decreased heat capacity for higher vibrational frequency modes.
Operational flexibility a model for effective project management

PurposeThis conceptual paper tries to present flexibility as a tool for uncertainty management contributing to effective project management. Design/ methodology/ approach-A literature review on efficiency, effectiveness, uncertainty management and flexibility is done to arrive at a conceptual model. Findings –The concept of flexibility which originated in manufacturing industry in various forms is yet to be introduced in project management body of knowledge as way to manage uncertainty and exploit opportunities to bring effectiveness in project management. Research limitations/implicationsThis paper is conceptual in nature trying to highlight the significance of flexibility in managing uncertainty in construction projects, but lack empirical research to prove the same. Originality/value –The value of this study comes from the fact that project based industries are yet to embrace newer concepts in other industries to manage uncertainty and therefore requests the experts behind PMBOK to study and add flexibility based concepts in project management after testing the same empirically.
How Does Public Service Motivation Among Teachers Affect Student Performance in Schools

The literature expects public service motivation (PSM) to affect performance, but most of the existing studies of this relationship use subjective performance data and focus on output rather than outcome. This article investigates the association between PSM and the performance of Danish teachers using an objective outcome measure (the students’ academic performance in their final examinations). Combining survey data and administrative register data in a multilevel dataset, we are able to control very robustly for the specific characteristics of the students (n = 5,631), the schools (n = 85), and other teacher characteristics (n = 694) besides PSM. We find that PSM is positively associated with examination marks. The result indicates that PSM may be relevant for performance improvements.
Citizenship, accountability and community: the limits of the CSR agenda

The focus of this article on the relationship between companies and local communities derives from a concern that many accounts of corporate responsibility and citizenship overlook this relationship—in particular, relations with poorer communities—as part of a general neglect of the developmental implications of the CSR agenda. Communities are engaging with corporations more routinely now than previously, a trend fostered by the lowering of barriers to trade through global trade accords, attempts to strengthen the rights of foreign investors and broader processes of national liberalization across many parts of the developing world. Increasingly they do so in ways that assume global significance because of new forms of global organizing and the influence of media and telecommunications, which expose companies’ activities to greater scrutiny, as well as the nature of the claims companies themselves now make about their global operations. While there is a long history of firms in the extractive and plantation sectors, being engaged in conflicts and negotiations with communities, these new factors have exposed many more sectors and regions to these political dynamics. It is often assumed that mechanisms for improving the social and environmental conduct of firms, such as codes of conduct, ethical trading initiatives and certification schemes, provide new forms of protection to poorer groups. However, questions are being asked about the extent and effectiveness of such protection, arising from concerns over whether these tools are sufficiently geared towards the needs of the very poorest workers. Similar anxieties attach to the lack of effective international and national regulation of the private sector, and the inaccessibility and underdevelopment of mechanisms of redress and company liability. 1 The purpose of this article is to add some clarity to the discussion about for whom CSR works and under what conditions.
Natural Hazards and Earth System Sciences Seismic hazard assessment – a holistic microzonation approach

The probable mitigation and management issues of seismic hazard necessitate seismic microzonation for hazard and risk assessment at the local level. Such studies are preceded with those at a regional level. A comprehensive framework, therefore, encompasses several phases from information compilations and data recording to analyses and interpretations. The state-of-the-art methodologies involve multi-disciplinary approaches namely geological, seismological, and geotechnical methods delivering multiple perspectives on the prevailing hazard in terms of geology and geomorphology, strong ground motion, site amplification, site classifications, soil liquefaction potential, landslide susceptibility, and predominant frequency. The composite hazard is assessed accounting for all the potential hazard attributing features with relative rankings in a logic tree, fuzzy set or hierarchical concept.
Application of Bio-Inspired Algorithms and Neural Networks for Optimal Design of Fractal Frequency Selective Surfaces

Technological advances in the field of microwave and communication systems and the increase of their commercial applications in recent years have resulted in more stringent requirements for innovative design of microwave passive devices, such as: antennas, filters, power splitters and couplers, frequency selective surfaces, etc. To be competitive in the commercial marketplace, microwave engineers may be using computer-aided design (CAD) tools to minimize cost and design cycle times. Modern CAD tools have become an integral part of the microwave product cycle and demand powerful optimization techniques combined with fast and accurate models so that the optimal solutions can be achieved, eventually guaranteeing first-pass design success. The target of microwave device design is to determine a set of physical parameters to satisfy certain design specifications (Mohamed, 2005).
Generalized Variables and Characteristic Scales

Chemical engineering processes are aggregates of simple chemical and physical processes having mathematical descriptions based on fundamental chemical and physical laws. Establishment of a mathematical model of a certain complex process needs information about the interactions between the simple processes involved. The latter simply means that such complex mechanisms have to permit mathematical descriptions consisting of mathematical operators corresponding to the physical and chemical effects contributing to the processes. In accordance with this standpoint, the basic theoretical models of mass transfer, for instance, contain equations of hydrodynamics, convection–diffusion, and chemical reactions. In many cases, the model construction becomes more complicated owing to the complex hydrodynamic situation (turbulence, fluid motion as drops, bubbles, or through a bed of particles, etc.). Using physical analogies (e.g., between turbulent and molecular diffusion) or average velocity and concentration models, one can solve the modeling problems. Otherwise, if there is a lack of information about the process mechanism, then similarity theory models can be employed. In cases when the information about the process mechanism is completely missing, regression models allow one to create functional relationships.
EVA ’ s and REVA ’ s relative and growing information on benefit predictions in Tehran stock exchange market accepted companies

The current research tries to introduce economic evaluation standards to the users and to increase the EVA’s and REVA’s relative and growing information content on benefit predictions. To reach this goal, the present research was done by testing 6 hypotheses in Tehran Stock Exchange Market during 1996 to 2008. Pearson correlation coefficient, determination coefficient and simple linear and multi-variable regression analyses were used for the data statistical analysis and testing the research hypothesis tests. Results from research hypothesis tests show that there is a significant relation between EVA and REVA on one hand and operating profit on the other. Also, EVA and REVA have increased information content.
Design and Implementation of Real-Time Video Big Data Platform based on Spark Streaming

Video data has gradually become the important component of big data from the monitoring networks, intelligent transportation networks, smart cities or other fields. In this paper, we have used the producer-consumer model of Kafka as the video streaming data acquisition layer, and the real-time processing framework Spark Streaming combined with openCV as data processing layer, and Memory, HDFS or HBase as data storage layer, and Web Technology to display the final results. During transmission process, we have used B-ASE64 encoding and JSON to implements data conversion. Therefore, the framework was designed to achieve data real-time acquisition, data processing, data transcoding, data storage and display. Meanwhile, the face recognition video capture was used as an example to build and test this framework. The relationship among the numbers of Worker nodes, batch slice and the processing efficiency was tested. The test results showed that the framework was feasible and had good real-time processing ability. And the better performance could be achieved by adjusting usage rate of CPU. This research has value for the real-time processing of image recognition, image retrieval and other big data application. But if data is deep mined, deep learning such as CNN will be needed to apply. Recently, SparkNet, a new component of Spark, has provided support for the neural network. SparkNet has made efforts to change the traditional time-consuming training for deep learning to improve greatly the efficiency.
Development of a pan-European Database of Rivers, Lakes and Catchments, in support to the needs of Environmental Policies.

The availability of digital data on river networks, lakes and associated catchments and their characteristics is important for the analysis of environmental pressures and their impact on our water resources. Recent policies, such as the Water Framework Directive require the implementation of river and catchment databases for both the development of River Basin Management Plans and for the reporting to the Commission. GIS tools allow for the combined analysis of digital elevation data and terrain parameters in order to derive part of the required information over extended areas. This article presents a new approach making use of medium resolution digital elevation data (250 m grid cell size) and information on climate, vegetation cover, terrain morphology, soils and lithology to derive river networks and catchments for the European continent. Methods to extract channel networks at continental scale normally use a constant threshold for the critical contributing area, independently of widely varying landscape conditions. As a consequence, the resulting drainage network does not reflect the natural variability in drainage density. To overcome this limitation a landscape characterisation is proposed, resulting in a limited number of landscape types reflecting drainage density. For each landscape type the slope-area relationship is then derived from the digital elevation data and the critical contributing area is determined. In the subsequent channel extraction a dedicated critical contributing area threshold is used for each landscape type. In order to comply with the needs of environmental monitoring, lakes and transitional waters are considered during river and catchment mapping. In addition, monitoring stations are accurately positioned on the river reaches and a dedicated algorithm has been developed to overcome problems of automatic river mapping in flat terrain. The described methodology has been developed and tested for the territory of Italy and is now implemented for the pan-European area. Results are validated comparing the derived data with river and catchment data sets from other sources and at varying scales. Good agreement both in terms of river positioning and drainage density could be demonstrated.
TIME RESPONSE OF TEMPERATURE SENSORS USING NEURAL NETWORKS

Primary coolant RTDs (Resistance Temperature Detector) typically feed the plant’s control and safety systems and must, therefore, be very accurate and have good dynamic performance. The response time of RTDs has been characterized by a single parameter called the Time Constant defined as the time it takes for the sensor output to achieve 63.2 percent of its final value after a step change in temperature. This step change is typically achieved by suddenly immersing the sensor in a rotating tank of water, called Plunge Test. In nuclear reactors, however, plunge testing is inconvenient because nuclear reactor service conditions are difficult to reproduce in the laboratory. An in-situ test method called LCSR - Loop Current Step Response test was developed to measure remotely the response time of RTDs. In the LCSR method, the response time of the sensor is identified by means of the LCSR transformation that involves the dynamic response modal time constants determination using a nodal heat-transfer model. For this reason, this calculation is not simple and requires specialized personnel. This work combines the two methodologies, Plunge test and LCSR test, using Neural Networks. With the use of Neural Networks it will not be necessary to use the LCSR transformation to determine sensor’s time constant and this leads to more robust results.
Islamic revival in Central Asia: The cases of Uzbekistan and Tajikistan

This article presents an overview on the topic of Islam in Central Asia, assuming that it is possible to identify some common trends for the whole area, but also many particularities that depend on their own historical, social and political background, and that will condition the nature of the state's relations with Islam. Denying the hypothesis that the Islamic revival in the 1980's-1990's in Central Asia was a result of external influence of proselytism, and that it simply landed in the region after the downfall of Communist ideology, the author underlines the existence of a deep-rooted local Islam, moderate in nature and alien to political struggle. Nonetheless, we should not think of a cohesive and homogeneous Islam. On the contrary, it is an Islam that has faced strong debates amongst traditionalists and revolutionaries, as well as the different currents, traditions and schools that compete in Central Asia today to attract the interest of the many believers. Traditionalists are guided by a combination of nationalist and Islamic ideas, and they consider national interests to be more important than global Islamic integration. The projects for reviving the Silk Road, which include the construction of roads, bridges, and also feature plans to construct railways that would connect Central Asian countries with Afghanistan, China, Iran and Pakistan will lead to a major development of contacts with the Near East and South Asia, and will increase transportation, commodity and human flows, stimulating at the same time the exchange of ideas. As a consequence, there is a significant increase in the influence of the international Islamic movement in Central Asian countries that is very welcomed by the governments, who are willing to expand official, business, cultural and inter-personal contacts with other Muslim countries. Nonetheless, this is also a gateway for external influence on Central Asian states that could in some way undermine the power of traditional elites. In response, national governments rely on traditionalists and cultivate local forms of Islam. The civil war in Tajikistan was an extreme manifestation of this conflict within Islam, and in this respect, the country becomes the subject of an in-depth analysis from which we can extract some valuable conclusions about the Islamisation process in Central Asian countries. The article also includes the results of surveys conducted by the author in Tajikistan that help us to gauge important topics such as the leadership among Muslim communities, the extent of radicalisation and how to deal with social and economic problems