Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-Input Pseudo-Switch RF Low Noise Amplifier

A dual-input low noise amplifier (DILNA) topology with pseudo-switch capability is presented. This novel solution allows us to avoid the use of the RF switch in all cases in which the LNA input has to be switched alternatively between two different RF sources. This is obtained by duplicating the input stage of the LNA and creating two concurrent stages. In the particular case of 13-GHz radiometric applications, the DILNA circuit has been realized in 90-nm CMOS technology, and the measurement results have shown a noise figure of 2.5 dB, a power gain close to 19 dB from both inputs, an input-output isolation close to -60 dB, and an isolation between the two inputs of about -45 dB at 13 GHz. The power consumption amounts to 17.38 mW from a 1.1-V supply voltage. These results represent one of the best sets of performance among those presented in the literature.
Nanostructured Materials in Optical Fiber Sensing

This work comprehends a review of nanostructured materials employed in the fabrication of optical fiber sen- sors in the last years. The continuous advances in nanofabrication techniques have enabled to manipulate the matter pre- cisely producing well defined nanostructurated coatings or repetitive patterns at nanoscale level. The interactions of light with these nano-organized materials or patterns at the nanoscale level enable to observe interesting phenomena, such as interferometry, fluorescence, absorbance, resonances and many others which can be exploited in the fabrication of sensing devices. A particular case consists of optical fiber sensors, where the light travelling through an optical fiber interacts with the sensitive layer. The properties of the sensitive layer, such as the organization, physical properties, chemical bounds etc. will determine the sensing characteristics of the final device. The utilization of some of the most common nanostruc- tured materials, such as polymers, nanoparticles, metals, metal oxides or biological coatings are reviewed here.
A clustering method for asymmetric proximity data based on bi-links with ε-indiscernibility

In this paper, we propose a clustering method for non-metric proximity data based on the ε-indiscernibility. First, we introduce a hierarchical grouping method based on bi-links, which groups objects when bi-directional links are established between objects that have asymmetric dissimilarities. Next, we incorporate the concept of ε-indiscernibility into the process of establishing bi-directional links in order to allow users to control the level of asymmetry that can be ignored in merging a pair of objects. Experimental results on the soft drink brand switching data showed that this approach may have a possibility of producing better clusters compared to the straightforward use of bi-links.
Identification of Genetic Associations and Functional Polymorphisms of SAA1 Gene Affecting Milk Production Traits in Dairy Cattle

Our initial RNA sequencing (RNA-seq) revealed that the Serum amyloid A1 (SAA1) gene was differentially expressed in the mammary glands of lactating Holstein cows with extremely high versus low phenotypic values of milk protein and fat percentage. To further validate the genetic effect and potential molecular mechanisms of SAA1 gene involved in regulating milk production traits in dairy cattle, we herein performed a study through genotype-phenotype associations. Six identified SNPs were significantly associated with one or more milk production traits (0.00002< P < 0.0025), providing additional evidence for the potential role of SAA1 variants in milk production traits in dairy cows. Subsequently, both luciferase assay and electrophoretic mobility shift assay (EMSA) clearly demonstrated that the allele A of g. -963C>A increased the promoter activity by binding the PARP factor while allele C did not. Bioinformatics analysis indicated that the secondary structure of SAA protein changed by the substitution A/G in the locus c. +2510A>G. Our findings were the first to reveal the significant associations of the SAA1 gene with milk production traits, providing basis for further biological function validation, and two identified SNPs, g. -963C>A and c. +2510A>G, may be considered as genetic markers for breeding in dairy cattle.
A framework for analysing and visualising open source software ecosystems

Nowadays, most empirical studies in open source software evolution are based on the analysis of program code alone. In order to get a better understanding of how software evolves over time, many more entities that are part of the software ecosystem need to be taken into account. We present a general framework to automate the analysis of the evolution of software ecosystems. The framework incorporates a database that stores all relevant information obtained thanks to several mining tools, and provides a unified data source to visualisation tools. One such visualisation tool is integrated in order to get a first quick overview of the evolution of different aspects of the software project under study. The framework is extensible in order to accommodate more and different types of input and output, depending on the needs of the user. We compare our framework against existing solutions, and show how we can use this framework for carrying out concrete ecosystem evolution experiments.
A Novel Astrovirus-Like RNA Virus Detected in Human Stool

Several novel clades of astroviruses have recently been identified in human faecal samples. Here, we describe a novel astrovirus-like RNA virus detected in human stools, which we have tentatively named bastrovirus. The genome of this novel virus consists of 6,300 nucleotides organized in three open reading frames. Several sequence divergent strains were detected sharing 67–93 per cent nucleotide identity. Bastrovirus encodes a putative structural protein that is homologous to the capsid protein found in members of the Astroviridae family (45% amino acid identity). The virus also encodes a putative non-structural protein that is genetically distant from astroviruses but shares some homology to the non-structural protein encoded by members of the Hepeviridae family (28% amino acid identity). This novel bastrovirus is present in 8.7 per cent (35/400) of faecal samples collected from 300 HIV-1-positive and 100 HIV-1-negative individuals suggesting common occurrence of the virus. However, whether the source of the virus is infected human cells or other, for example, dietary, remains to be determined.
Moving Icons, Detection and Distraction

Simple motion has great potential for visually encoding information but there are as yet few experimentally validated guidelines for its use. Two studies were carried out to look at how efficiently simple motion cues were detected and how distracting they were in different task contexts. The results show that motion outperforms static representations and identify certain types of motions which are more distracting and irritating than others.
Representations of Two-Parameter Quantum Groups and Schur-Weyl Duality

We determine the finite-dimensional simple modules for two-parameter quantum groups corresponding to the general linear and special linear Lie algebras gl_n and sl_n, and give a complete reducibility result. These quantum groups have a natural n-dimensional module V. We prove an analogue of Schur-Weyl duality in this setting: the centralizer algebra of the quantum group action on the k-fold tensor power of V is a quotient of a Hecke algebra for all n and is isomorphic to the Hecke algebra in case n\geq k.
Epidemiological analysis of the Eyam plague outbreak of 1665–1666

Plague, caused by the bacterium Yersinia pestis, is one of the deadliest infectious diseases in human history, and still causes worrying outbreaks in Africa and South America. Despite the historical and current importance of plague, several questions remain unanswered concerning its transmission routes and infection risk factors. The plague outbreak that started in September 1665 in the Derbyshire village of Eyam claimed 257 lives over 14 months, wiping out entire families. Since previous attempts at modelling the Eyam plague, new data have been unearthed from parish records revealing a much more complete record of the disease. Using a stochastic compartmental model and Bayesian analytical methods, we found that both rodent-to-human and human-to-human transmission played an important role in spreading the infection, and that they accounted, respectively, for a quarter and three-quarters of all infections, with a statistically significant seasonality effect. We also found that the force of infection was stronger for infectious individuals living in the same household compared with the rest of the village. Poverty significantly increased the risk of disease, whereas adulthood decreased the risk. These results on the Eyam outbreak contribute to the current debate on the relative importance of plague transmission routes.
The real-time monitor system based on LabVIEW

As the most popular workbench of virtual instrument, LabVIEW has been widely used with graphical design and rich function. A monitor system of real-time data acquisition, processing, display, save, over limit alarm is constructed based on LabVIEW in this paper. Include the design of hardware system and software program. The design of software system is introduced emphatically. Illustrate the function of monitoring system with monitor the CO2 concentration indoor. The system also provide a friendly human-machine interface, contemporary, it is easy for system maintenance and function expansion.
Post-Processing for MCMC

Markov Chain Monte Carlo methods (MCMC) can sample from a target distribution and approximate this distribution. MCMC methods employ the apriori known unnormalized target distribution to decide on the acceptance of new states, but not to approximate the final distribution. This paper investigates how the unnormalized target distribution can be used for approximation purposes. It is shown that this function can be used to obtain an unbiased estimate of the target distribution. Under certain circumstances, this approach can greatly reduce the variance of the resulting estimate. A useful side-effect of our estimation method is that the sampling method no longer has to follow the target distribution. Based on this observation, a sampling method with a variable degree of exploration is described that still converges to the target function. Thus, exploration can be performed, thereby improving mixing, without discarding sample points. Both methods are demonstrated in experiments.
Strathprints Institutional Repository (2003) Confidence Intervals for Reliability Growth Models with Small Sample Sizes. Ieee Transactions on Reliability, 52 (2). Pp. 257-262. Issn 0018-9529 Confidence Intervals for Reliability Growth Models with Small Sample Sizes

Strathprints is designed to allow users to access the research output of the University of Strathclyde. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (http://strathprints.strath.ac.uk/) and the content of this paper for research or study, educational, or not-for-profit purposes without prior permission or charge. Purpose: Widen the state of the art. Special math needed for explanations: Probability and statistics. Special math needed to use results: Probability and statistics. Summary and Conclusions Fully Bayesian approaches to analysis can be over ambitious where there exist realistic limitations on the ability of experts to provide prior distributions for all relevant parameters. This research was motivated by situations where expert judgement exists to support the development of prior distributions describing the number of faults potentially inherent within a design but could not support useful descriptions of the rate at which they would be detected during a reliability growth test. 2 This paper develops inference properties for a reliability growth model. The approach considered assumes a prior distribution for the ultimate number of faults that would be exposed if testing were to continue ad infinitum but estimates the parameters of the intensity function empirically. A fixed-point iteration procedure to obtain the Maximum Likelihood Estimate is investigated for bias and conditions of existence. The main purpose for this model is to support inference in situations where failure data are few. A procedure for providing statistical confidence intervals is investigated and shown to be suitable for small sample sizes. An application of these techniques is illustrated through an example.
From MSC and UML to SDL

UML and MSC are widely used by software practitioners. SDL is an ITU standard language for telecommunications software specification. It has a formal semantics, and is supported by several commercial tools, which allow for simulation and validation of SDL design specifications as well as automatic code generation from these specifications. In order to take advantages of the SDL available tools and still use the very popular notations such as UML and MSC, we have developed an approach for specifying distributed systems in UML and MSC. MSCs are used to specify the behavior (scenarios) of the distributed system under consideration. UML, more precisely Class Diagrams and Object Diagrams, are used to specify the architecture of the system. By architecture, we mean the different components of the system and their interconnections. The MSC and UML specifications are translated automatically into a full SDL specification. We introduce our distributed system specification style in UML and its automatic translation into an SDL architecture.
Religion, group threat and sacred values

Sacred or protected values have important influences on decision making, particularly in the context of intergroup disputes. Thus far, we know little about the process of a value becoming sacred or why one person may be more likely than another to hold a sacred value. We present evidence that participation in religious ritual and perceived threat to the group lead people to be more likely to consider preferences as protected or sacred values. Specifically, three studies carried out with Americans and Palestinians show: (a) that the more people participate in religious ritual the more likely they are to report a preference to be a sacred value (Studies 1–3); (b) that people claim more sacred values when they are reminded of religious ritual (Study 2); and (c) that the effect of religious ritual on the likelihood of holding a sacred value is amplified by the perception of high threat to the in-group (Study 3). We discuss implications of these findings for understanding intergroup conflicts, and suggest avenues for future research into the emergence and spread of sacred values.
Pompen en verzuipen

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Poisson Multi-Bernoulli Mixture Filter: Direct Derivation and Implementation

We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multitarget tracking with the standard point target measurements without using probability generating functionals or functional derivatives. We also establish the connection with the <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula> -generalized labeled multi-Bernoulli (<inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula> -GLMB) filter, showing that a <inline-formula><tex-math notation="LaTeX">$\delta$</tex-math></inline-formula>-GLMB density represents a multi-Bernoulli mixture with labeled targets so it can be seen as a special case of PMBM. In addition, we propose an implementation for linear/Gaussian dynamic and measurement models and how to efficiently obtain typical estimators in the literature from the PMBM. The PMBM filter is shown to outperform other filters in the literature in a challenging scenario.
Analysing Telemetry Data with a GIS-Based Vector Structure

Abstract This paper proposes a unique method for plotting field bearing locations, of the kind typically taken by wildlife biologists on free ranging species, directly on a computer-compatible habitat map. We show how to use a GIS data base to identify differential habitat use directly from the polygon formed by each set of bearings. A geometric algorithm is developed to interpret the bearings accurately. The technique avoids the most difficult errors associated with using point locations, namely those due to animal movement, and distance from receiver to transmitter, and is especially useful for habitat preference studies.
Mean field message passing for cooperative simultaneous ranging and synchronization

Many emerging technologies for wireless networks (WNs) require decentralized synchronization and ranging, i.e., distance estimation between neighboring pairs of nodes. Both tasks are related to each other when they are based on time measurements between nodes. Revealing this connection, we present a mean field (MF) message passing algorithm for cooperative simultaneous ranging and synchronization (CoSRAS), which jointly estimates the internode distances and clock parameters in a fully distributed way. It is shown that the use of the MF method reduces the computation and communication efforts compared to other message passing methods. For MF message exchange between nodes, only broadcast communication is required. Our simulation results demonstrate the equivalence in performance with centralized state-of-the-art joint ranging and synchronization algorithms.
The influence of case-based reasoning on principals’ beliefs about teaching with information and communication technologies

Research suggests there are barriers to principals developing new beliefs and understandings that support a vision of teaching with information and communications technology (ICT). Many principals have not taught with the new technologies and are maintaining print based pedagogies while exploring new pedagogies appropriate to the information age. In a previous study (Otto, 2003), the researcher concluded that in order to change principals’ beliefs about teaching with ICTs, it is necessary to confront old beliefs with new beliefs. His case study of three Queensland primary principals highlighted uncertainties amongst practitioners about what those new beliefs should be. That is, the principals were inconsistent in describing the exemplary use of ICTs in classrooms. It was also noted in the study that the “real world” of the classroom imposed limitations on the implementation of practices recommended in the literature and the vision that teachers and principals have of the ideal classroom. A second study is proposed to investigate the influence of case-based reasoning on principals’ beliefs about teaching with ICTs. The design, development, implementation, and institutionalisation of a prototype multi-media project that employs a case library to support Case-Based Reasoning (CBR) principles will be evaluated. The case library will be compiled of case stories derived from contemporary thinking about best practices in teaching with ICTs and the stories of principals in the field.
Data mining - A captured wired traffic approach

Data mining is involved in procedures by which patterns are extracted from data. This process has become increasingly important to map data patterns to useful information that can be used to predict future traffic analyses. Other areas were data mining can be used include: fraud detection, marketing, congestion control, and network expansion consideration. Data mining involves capturing and gathering random data from the flow of information passing through a certain trunk or node and from a statistical point of view, it can only be meaningful if enough samples are gathered. The results achieved from a proper deployment of a data mining method provide valuable insights to how busy a node is, the average one-way and end-to-end delays, and the average size of the packets. This paper contains the results from capturing live wired traffic and analyzing the statistical values.
In vitro comparative study of Bilimbi and Star fruit extracts for Anthelmintic activity

In the present study, aqueous methanolic extract of Bilimbi and aqueous acetone extract of Star fruit were assessed for its anthelminthic activity against adult e arthworms (Pheretima posthuma). Various concentrations of both extracts were tested and results were expressed in terms of time for paralysis and time for death of worms. Albendazole was used as a reference standard. The result revealed that the bilimbi fruit extract was more effective compared to the standard and star fruit extract with 30.50 and 47 minutes for paralysis and death respectively at the concentration of 100mg/ml, that of standard and star fruit was 34.32 and 48.00 and 40.60 and 57.30 minutes for paralysis and death respectively. The comparative study showed that out of the two, bilimbi fruit extract proves to be a better anthelmintic remedy.
Interactive computer-aided code vectorization

Traditionally, programmer learns to write code using arrays and loops to perform complex computation. Languages designed specifically for scientific computation such as Matlab/Octave support vector based operations which are much faster than arrays and loops. However, converting the loop oriented code to a vector based operation requires skilled programmer, takes time, and introduces many errors. This paper presents an easy to use, interactive web application based system that automatically detect for loops that can be automatically vectorized, allowing the programmer to simply selects which for loop to convert into a vector equivalent operation, debug the output and compare the performance gained. The goal is to ease the task of learning and applying code vectorization techniques. We extended Octave with additional operations to automatically detect possible loop vectorization, and implemented a web application that hides the Octave command line complexity by automatically generating necessary Octave command. Therefore, the user is able to use the tool to learn and use code vectorization tool with ease. The system is built with two goals in mind, ease the manual work of vectorizing loop operations, and enable interactive learning of code vectorization concept.
Automatic segmentation of phalanges regions on MR images based on MSGVF snakes

In recent years, medical imaging is important in medical diagnosis for early detection of lesions. However, a large number of images increases the stress to the radiologist. Therefore, CAD (Computer Aided Diagnosis) system is expected to reduce such burden. In diagnostic imaging of phalanges, X-ray photographs, CT (Computed Tomography) are used to evaluate the value of phalanges destruction. Whereby, the MRI (Magnetic Resonance Imaging) that is used mainly to diagnose the lesion in the soft tissue is more effective in a certain case, which is one of the important CAD systems to develop. However, studies on CAD system using MR images are not as much as the studies using CT. In this paper, we propose an automatic segmentation algorithm of phalanges regions on MR images. Although it has three dimensional information, this is the method for two dimensional algorithm. In other words, we propose for each slice of MR Images. Firstly, phalanges regions in MR images are segmented for coarse regions mainly by watershed algorithm. Next, the segmented results from the previous phase are set as the initial contour. Ultimately, the accurate segmentation of the phalanges on MR images are acquired based on MSGVF snakes.