Miracle-dz/UniFAR-FTUs huggingface dataset:
The Use of Macroarray as a Simple Tool to Follow the Metabolic Profile of Lactobacillus plantarum during Fermentation

This study focused on defining the differences in L. plantarum gene expression levels in different media and in different growth phases using an easy and cost-efficient monitoring of gene expression. A macroarray based on a group of selected L. plantarum genes, 178 genes belonging to 18 main groups, printed onto a nitrocellulose filter was designed in this work. Using the macrofilters designed, the expression of a selected set of L. plantarum genes was assayed in synthetic MRS medium and in extracted carrot juice. To compare the potential differences of starter gene expression in hygienic and contaminated cultivation media, the L. plantarum strain was cultivated in both sterile and contaminated (yeast and Escherichia coli) MRS and carrot juice. The number of genes found to be regulated as a function of growth was clearly higher in MRS-based growth medium than in carrot juice, In carrot juice, expression of the gene encoding malolactic enzyme (MLE), which makes L. plantarum an advantageous microbe in e.g. wine making, was found to be upregulated in logarithmic phase of growth. The current study demonstrated that macroarrays printed on nitrocellulose filters with simple robotic systems can be analyzed by standard laboratory equipment and methods usually available in molecular laboratories. Using this technology, rapid and cost-efficient analysis of genome function of L. plantarum can be carried out e.g. in developing regions, where lactic acid fermentation of food and feed matrices is a common practice.
A study upon the influence of age and way of feeding upon the quality of the rabbit meat.

In this study we establish if the age and rising conditions of the animal have a significant effect upon the quality of the analyzed meat (pH, texture, colour, freshness). We led the studies in controlled commercial conditions including the same rabbit species of different ages and with different ways of feeding. The solving of the freshness inconsequence problem is a priority in the meat industry. The satisfaction obtained while eating is the result of the interaction of this trait with other factors such as the taste and juiciness. The analyzing methods used in our study were the determination of the mineral substances with the X rays spectroscope (EDX960HS), the determination of the pH and of the acidity and humidity of rabbit meat. The animal’s age and degree of fatness influence a lot the meat consistency. In this way the young animal’s meat is less consistent than that of the adult animals and so the fat meat has a finer consistency than the light meat in the latter the conjunctive tissue between predominating muscular fibers or different muscles. The juiciness of the meat depends on the species, race, age and degree of fatness of the animal. The young animals have a more juicy meat in comparison with the adult animals due to the fineness of the muscle fibers and the high water consistency.
M-PNC: Multi-hop physical layer network coding for shared paths in vehicular networks

In wireless networks, spectral efficiency is an important issue due to limited available bandwidth. Traditionally, when a receiver collects simultaneous transmissions, packets collide and the much meaningful information cannot be retrieved. Thus, through suitable scheduling, simultaneous transmissions to the receiver are avoided. However, in physical layer network coding, simultaneous transmissions are allowed and the combined signal is equivalent of XOR operation on air. A path from a source to a destination in unicast routing in VANET is called a flow; multiple flows may have common road segments. There will be heavy contention in such shared road segments resulting in lower throughput, lower packet delivery ratio and higher end to end delay. In this paper, we propose a multihop physical layer network coding structure to be used by multiple flows of unicast routing paths. We analyze throughput, end-to-end delay and coding gain with respect to number of routing flows and number of forwarders involved in network coding.
Ieee Workshop on Machine Learning for Signal Processing Soon: Self Organising Oscillator Networks for Use in Clustering Problems

The Self-Organising Oscillator Network (SOON) is a comparatively new clustering algorithm (11: t h a t has received relatively little attention 50 far. The SOON is distance based, meaning that clustering behaviour is different in a number of ways that can be beneficial. This paper examines the effect of adjusting the cont.101 parameters of the SOON with two widely different datasets which represent two different types of real-world dsta; the first is a communicat,ions signal dataset representing one modulat,ion scheme under a wriet,y of noise conditions. The second is a biological dataset taken from microarray experiments on t,he Cell-cycle of yeast. The modulat,ion scheme data is relati\lely easy t o cluster at high SNR, however at lower SKR. the clustering problem becomes much more difficult, as the separat,ion between the cluster reduces. The paper demonstrates that the SOON is a viable tool to analyse these problems, and can add many useful insights to the dat,a, that may not alxays he availalile using other clustering methods.
Heterogeneous Environment Aware Streaming Graph Partitioning

With the increasing availability of graph data and widely adopted cloud computing paradigm, graph partitioning has become an efficient pre-processing technique to balance the computing workload and cope with the large scale of input data. Since the cost of partitioning the entire graph is strictly prohibitive, there are some recent tentative works towards streaming graph partitioning which run faster, are easily parallelized, and can be incrementally updated. Most of the existing works on streaming partitioning assume that worker nodes within a cluster are homogeneous in nature. Unfortunately, this assumption does not always hold. Experiments show that these homogeneous algorithms suffer a significant performance degradation when running at heterogeneous environment. In this paper, we propose a novel adaptive streaming graph partitioning approach to cope with heterogeneous environment. We first formally model the heterogeneous computing environment with the consideration of the unbalance of computing ability (e.g., the CPU frequency) and communication ability (e.g., the network bandwidth) for each node. Based on this model, we propose a new graph partitioning objective function that aims to minimize the total execution time of the graph-processing job. We then explore some simple yet effective streaming algorithms for this objective function that can achieve balanced and efficient partitioning result. Extensive experiments are conducted on a moderate sized computing cluster with real-world web and social network graphs. The results demonstrate that the proposed approach achieves significant improvement compared with the state-of-the-art solutions.
Region control for robots driven by series elastic actuators

Series elastic actuators (SEAs) are known to offer a number of advantages such as high force/torque fidelity, low impedance, and tolerance to shocks, which make it suitable for the applications involving human-robot interaction. In existing SEA-driven robot systems, the control objective is usually specified as a predefined trajectory or an impedance model that describes the relationship between the desired motion of robot and the external force, and controllers are always activated to regulate the desired motion or the desired impedance model. In this paper, a region control scheme is proposed for robots driven by SEAs, where the control objective is specified as a region, instead of trajectory or desired impedance. The region control has the advantage of flexibility, in the sense that the robot is able to move freely inside the desired region and thus compliant with the environment or physical interactions with humans. Though the overall dynamics that includes both actuator and robot dynamics is a fourth-order system, the proposed control method does not require the high-order derivatives or the construction of any observer. Experimental results are presented to demonstrate the effectiveness of the proposed control method.
A Modified Aodv Protocol to Detect and Prevent The Wormhole: A Hybrid Approach

In MANET mobile node is responsible for route establishment using wireless link where each node behave like both as a host and router. MANET encounter by number of security threat because of its open untrusted environment with little security arrangement, whether security over MANET is not to be enhance up to satisfactory level because of its characteristics. Among all of security threat worm hole is consider to be a very serious security threat over MANET. In worm hole two selfish node which is geographically very far away to each other, makes tunnel between each other to hide their actual location and try to believe that they are true neighbours and makes conversation through the wormhole tunnel. Recently research will focus over wormhole detection and prevention but existing technique having lower network overhead, lower battery power consumption in order to longer survival of network with fast response. In this paper a dynamic wormhole detection and prevention technique AODVWWP has been proposed which is based on an hybrid model that encapsulate location ,neighbour node and hop count method.
Digital Beamforming for High Resolution Wide Swath SAR Imaging

Synthetic Aperture Radar (SAR) is a well- proved instrument for remote sensing. Multi-aperture SAR- systems allow for digital beamforming on receive that will enable a wide swath SAR with high azimuth resolution. In classic multi-aperture systems, stringent requirements are imposed on sensor velocity and PRF to ensure uniform sampling of the synthetic aperture. This paper shows that an unambiguous reconstruction of the SAR signal is also possible in case of such a non-optimum PRF. For this, an innovative reconstruction algorithm is derived, which en- ables a recovery of the unambiguous Doppler spectrum also in case of a non-uniform sampling of the synthetic aperture. Further, the influence of perturbations on the reconstruc- tion is presented and general system aspects are discussed.
Structural Analysis of Metabolites of Asiatic Acid and Its Analogue Madecassic Acid in Zebrafish Using LC/IT-MSn

Although zebrafish has become a significant animal model for drug discovery and screening, drug metabolism in zebrafish remains largely unknown. Asiatic acid (AA) and madecassic acid (MA), two natural pentacyclic triterpenoids mainly obtained from Centella asiatica (L.) Urban, have been found to possess many pharmacological effects. This study is to probe the metabolic capability of zebrafish via investigation of the drug metabolism of AA and MA in zebrafish, using a sensitive LC/IT-MSn method. In addition, the main fragmentation pathways of AA and MA were reported for the first time. Nineteen metabolites of AA and MA were firstly identified after zebrafish was exposed to the drug, which all were the phase I metabolites and mainly formed from hydroxylation, dehydrogenation, hydroxylation and dehydrogenation, dihydroxylation and dehydrogenation, and dehydroxylation reaction. The results indicated that zebrafish possessed strong metabolic capacity, and the metabolites of AA and MA were formed via similar metabolic pathways and well matched with the known metabolic rules in vivo and in vitro, which supports the widely use of this system in drug metabolism research. This investigation would also contribute to the novel information on the structural elucidation, in vivo metabolites and metabolic mechanism of pentacyclic triterpenoids.
Discontinuous Galerkin immerse finite volume element method for elliptic interface problems

By choosing the trial function space to the immersed finite element space and the test function space to be piecewise constant function space, we develop a discontinuous Galerkin immersed finite volume element method to solve the elliptic interface problems. The existence and uniqueness of the discrete scheme is proved, and an optimal energy-norm error estimate and L2-norm estimate for the numerical solution are obtained.
A dead-reckoning scheme for skid-steered vehicles in outdoor environments

A dead-reckoning scheme appropriate for skid-steered mobile robots is introduced to serve in a wider scheme for simultaneous localization and map-building. It is based on internal sensors (inertial data and odometry) only. The information from an experimentally derived kinematic model and an onboard inertial navigation system (INS), after a necessary pre-filtering stage, is fused using a simple and fast modified Kalman filter. We verify our approach with large scale experiments in outdoors structured environments and variable terrains, following paths with steep turns and variable velocity.
The Growth in U . S . Wheat Food Demand

U.S. food use (demand) accounted for 27 percent of total disappearance in 1980/81, and is projected to rise to 36 percent by the year 2000. As food use captures an increasing share of total disappearance, estimating its magnitude becomes even more important in determining total wheat demand for the United States. Because there are many classes of wheat used to produce a wide variety of “wheat-based” food products, wheat-by-class food demand equations are developed to estimate total U.S. wheat food demand.
Simulation and Optimization of High-Power Semiconductor Lasers and Modules

Depending on their application high-power semiconductor laser devices have to be optimized with respect to various design parameters. We discuss the simulation and optimization of the device performance with respect to electrical and thermal properties, output power, wavelength stability, and device reliability using the example of our latest pump-laser generation that has been developed and qualified to support the high-end market of erbium-doped fiber amplifiers. Modeled and measured device properties are compared at each design step. Based on an overall optimization of the device performance fiber Bragg grating (FBG) stabilized telecom-grade pump-laser modules have been realized yielding 750 mW fiber-coupled light output power.
Optimal Portfolio Selection with Transaction Costs and Finite Horizons

We examine the optimal trading strategy for a CRRA investor who maximizes the expected utility of wealth on a finite date and faces transaction costs. Closed-form solutions are obtained when this date is uncertain. We then show a sequence of analytical solutions converge to the solution to the problem with a deterministic finite horizon. Consistent with the common life-cycle investment advice, the optimal trading strategy is found to be horizon dependent and largely buy and hold. Moreover, it might be optimal for the investor in our model not to buy any stock, even when the risk premium is positive. Further analysis of the optimal policy is also provided. Copyright 2002, Oxford University Press.
Robust person tracking in real scenarios with non-stationary background using a statistical computer vision approach

This paper presents a novel approach to robust and flexible person tracking using an algorithm that combines two powerful stochastic modeling techniques: The first one is the technique of so-called Pseudo-2D Hidden Markov Models (P2DHMMs) used for capturing the shape of a person with an image frame, and the second technique is the well-known Kalman-filtering algorithm, that uses the output of the P2DHMM for tracking the person by estimation of a bounding box trajectory indicating the location of the person within the entire video sequence. Both algorithms are cooperating together in an optimal way, and with this cooperative feedback, the proposed approach even makes the tracking of persons possible in the presence of background motions, for instance caused by moving objects such as cars, or by camera operations as, for example, panning or zooming. We consider this as major advantage compared to most other tracking algorithms that are mostly not capable of dealing with background motion. Furthermore, the person to be tracked is not required to wear special equipment (e.g. sensors) or special clothing. We therefore believe that our proposed algorithm is among the first approaches capable of handling such a complex tracking problem. Our results are confirmed by several tracking examples in real scenarios, shown at the end of the paper and provided on the web server of our institute.
A Complete Automation of Unit Testing for JavaScript Programs

Problem statement: Program testing is expensive and labor intensive, often consuming more than half of the total development costs, and yet it is frequently not done well and the results are not always satisfactory. The objective of this paper is to present an automatic test data generation tool that aims to completely automate unit testing of JavaScript functions. The methodology: In order to use the proposed tool, the tester annotates the files that contain the class to be tested. Moreover, the tester must specify the test data coverage criterion to be used, either branch coverage or mutation analysis. However, the tool is then integrated into the JavaScript compiler and test generation is invoked by a command line option. Also, the code to be tested is parsed into an abstract syntax tree from which the test tool generates a program dependency graph for the function under test. However, if mutation analysis coverage is required, the abstract syntax tree for a meta-mutant program is also generated. To provide guidance for the test data search, the function under test instrumented in accordance with the coverage criterion. Branch predicate expressions are always instrumented, in the case of mutation coverage, mutated statements are also instrumented. Compilation then continues from the modified abstract syntax tree to generate instrumented executables that were loaded into the test data search module. Results: The experiment done in our study by using the proposed tool for branch coverage shows that the most effective result for string equality was obtained using the edit distance fitness function, while no significant difference was found in the fitness function for string ordering. Through exhaustive mulation coverage 8% are found to be equivalent. Conclusion: By having a complete automation it reduces the cost of software testing dramatically and also facilitates continuous testing. It is reported that at least 50% of the total software development costs is due to testing, and 10-15% of development time is wasted due to frequent stops for regression testing. Automation will also help get rid of cognitive biases that have been found in human testers. Acknowledgment: The researcher would like to express their gratitude to the anonymous referees for their valuable and helpful comments and suggestions in improving the study.
Studies in pricing and competition in regulated pharmaceutical markets.

This PhD thesis studies three aspects of competition in pharmaceutical markets using data from the EU, and recommends appropriate policies to address inefficiencies. The first study examines the effect of patent expiry on originator drug prices in the presence of price regulation. Using econometric panel data methods, I find that neither generic entry nor generic market penetration affect the prices of originator drugs downwards. Instead, prices of originator drugs often appear to increase post-generic entry. Findings suggest that no savings to health services should be expected post-patent expiry if the originator product is dispensed, and any savings occur solely from generic uptake. The second study examines whether generic entry leads to a switch in total consumption (both originator and generic) from an off-patent branded molecule to a different in-patent molecule of the same therapeutic class. Using panel data analysis, I find that a switch in consumption post-patent expiry took place for the first ACE inhibitor which went off-patent, and in some cases for the second and third product. Such a switch leads to increased costs because it removes any substitution power from health authorities. The third study examines the effects of parallel trade on price competition. The topic is first approached from a game-theoretic point of view, predicting that parallel trade does not trigger price competition. Descriptive statistics demonstrate differences, if any, between prices of locally sourced and parallel traded products in the presence of different regulatory policies. Finally, the econometric analysis shows that there is upward price convergence in the presence of parallel trade. However, some regulatory interventions may lead to a spread between prices of locally sourced products and parallel traded products. Findings suggest that parallel trade should not always be considered a cost-containment mechanism and other ways to address rising pharmaceutical expenditures should be considered.
Changes of exchange rate behavior during and after crisis

: This study extends earlier analysis, in which behavior of daily exchange rates during the global crisis was compared to that before crisis. We repeat similar comparison for data set extended until the end of April 2010, use ARMA/ARMAX and GARCH models with stock indices as additional regressors, for volatility and returns of EURPLN, EURUSD, USDPLN exchange rates. Marked increase in volatility during crisis, negatively affected quality of models. After crisis volatility and returns seem to stabilize, hence exchange rate risk seems to decline gradually. There is a slight improvement in quality of models after the crisis.
Finding the Number of Fuzzy Clusters by Resampling

Recently several papers studied resampling approaches to determine the number of clusters in prototype-based clustering. The core idea underlying these approaches is that with the right choice for the number of clusters basically the same cluster structures should be obtained from subsamples of the given data set, while a wrong choice should produce considerably varying cluster structures. In this paper we investigate whether these approaches can be transferred to fuzzy clustering. It turns out that they are applicable to fuzzy clustering as well, but that not all relative cluster evaluation measures that work for crisp clustering can also be used for fuzzy clustering.