Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of heavy metals in tomato (Solanum lycopersicum) leaves, fruits and soil samples collected from Asaba metropolis, Southern Nigeria.

Soil, tomato leaves and tomato fruits collected from Asaba metropolis were digested and analyzed for metals such as lead, copper, cadmium, nickel, zinc, chromium, manganese, arsenic, iron, selenium and cobalt. The aforementioned metals were determined using atomic absorption spectrophotometry (AAS). The results obtained revealed that all the metals were detected and there were metal variations. Metal concentration in soil samples exceeded those of tomato leaves. Also, tomato leaves metals were higher than those values obtained in tomato fruits. This is an indication that the soil was pollution to the tomato leaves and fruits. The highest concentrations were found to lead and iron. Keyword: Heavy metal, contamination, concentration, environment, vegetation, bioaccumulation.
Limited feedback design in MIMO-OFDMA system using zero-forcing beamforming

In this paper, we consider amount of feedback and resource allocation for a downlink in MIMO-OFDMA system. The amount of feedback data increases with the number of user, subcarrier, antenna numbers rise. In order to limit the feedback date in a fix level, a prefixed threshold based feedback is proposed. The value of CSNR is feedbacked only when the channel gain is greater than the threshold. Simulation results show that the whole program can significantly reduce the feedback date and the computational complexity while obtaining the better system capacity.
A preliminary study on the use of differential evolution for adjusting the position of examples in nearest neighbor classification

Nearest neighbor is one of the most successfully used techniques for performing classification and pattern recognition tasks. Its simplicity and effectiveness justify the use of this technique in certain domains but it however presents several drawbacks referring to time response, noise sensitivity and storage requirements. Several solutions have been proposed in order to alleviate these problems, such as improving the technique for speeding up or carrying out a data reduction process. Prototype generation is a suitable process for data reduction that allows to fit a data set for nearest neighbor classification. Position adjustment of prototypes is a successful technique within the prototype generation methodology. Evolutionary algorithms are adaptive methods based on natural evolution that may be used for search and optimization. Position adjustment of prototypes can be viewed as a search problem, thus it could be solved using evolutionary algorithms. In this paper, we perform a preliminary study on the use of differential evolution algorithms to the prototype generation problem. Differential evolution models are compared with other algorithms for adjusting the position of prototypes and the results are contrasted through non-parametrical statistical tests. The results show that some differential evolution models consistently outperform previously proposed methods.
Brain structural plasticity in survivors of a major earthquake.

BACKGROUND Stress responses have been studied extensively in animal models, but effects of major life stress on the human brain remain poorly understood. The aim of this study was to determine whether survivors of a major earthquake, who were presumed to have experienced extreme emotional stress during the disaster, demonstrate differences in brain anatomy relative to individuals who have not experienced such stressors. METHODS Healthy survivors living in an area devastated by a major earthquake and matched healthy controls underwent 3-dimentional high-resolution magnetic resonance imaging (MRI). Survivors were scanned 13-25 days after the earthquake; controls had undergone MRI for other studies not long before the earthquake. We used optimized voxel-based morphometry analysis to identify regional differences of grey matter volume between the survivors and controls. RESULTS We included 44 survivors (17 female, mean age 37 [standard deviation (SD) 10.6] yr) and 38 controls (14 female, mean age 35.3 [SD 11.2] yr) in our analysis. Compared with controls, the survivors showed significantly lower grey matter volume in the bilateral insula, hippocampus, left caudate and putamen, and greater grey matter volume in the bilateral orbitofrontal cortex and the parietal lobe (all p < 0.05, corrected for multiple comparison). LIMITATIONS Differences in the variance of survivor and control data could impact study findings. CONCLUSION Acute anatomic alterations could be observed in earthquake survivors in brain regions where functional alterations after stress have been described. Anatomic changes in the present study were observed earlier than previously reported and were seen in prefrontal-limbic, parietal and striatal brain systems. Together with the results of previous functional imaging studies, our observations suggest a complex pattern of human brain response to major life stress affecting brain systems that modulate and respond to heightened affective arousal.
Integration of Living Cells with Silicon Microstructures for MEMS Applications

For many years biological and silicon-based structures were considered incompatible because of the difficulties to engineer an effective interface connecting the two systems. Recent developments in surface chemistry, bioengineering and cell biology enabled the creation of extracellular clues to guide the attachment and growth of cells on silicon structures. We have developed a photolithography-based method, which was compatible with standard silicon manufacturing steps, to pattern self-assembled monolayers (SAMs) on glass or silicon substrates to guide cell attachment, pattern formation and differentiation. In order to demonstrate the effectiveness of our method to create functional cellular networks on silicon microstructures we have registered the surface patterns with substrate embedded micro electrodes to allow long-term recording of activity of the cells or electrical stimulation. These hybrid biological/silicon-based systems can find applications in functional pharmacological screening, toxin detection, as disease models or in robotics.
Workﬂow Technology

This chapter is concerned with workﬂow, its systems, its models, its problems and promises. Workﬂow management systems assist in the speciﬁcation, modeling, and enactment of structured work processeswithin organizations.Thesesystemsare a specialtypeof collaboration technology which we describe as “organizationally aware groupware”. Since the turn of the decade, over 200 new workﬂow products have been introduced into the world market. This chapter motivates and deﬁnes the concepts of workﬂow. Examples are presented from existing products and prototypes. Finally, we explore some of the current inhibitors and research issues in this fast growing domain.
An experimental implementation of traffic control for IP networks

The Integrated Services Packet Networks are designed to offer new network services to a wide variety of applications. The architecture behind the new services consists primarily of a packet scheduler, a packet classifier, admission control, and a reservation establishment protocol. This paper describes a complete implementation of this Traffic Control extensions. We also designed and implemented a kernel interface which permits to send Quality of Service (QoS) requests to the network layer. We explain how the elements of the architecture work in concert and which mechanisms we use to guarantee a requested amount of bandwidth. Our scheduler uses a variant of the Class Based Queuing mechanism (CBQ) of Sally Floyd and Van Jacobsen [6]. For the reservation signaling and establishment we use RSVP [2]. Finally this paper provides a performance evaluation of the proposed mechanisms.
The boundary state formalism and conformal invariance in off-shell string theory

In this note we present a generalization of the boundary state formalism for the bosonic string that allows us to calculate the overlap of the boundary state with arbitrary closed string states. We show that this generalization exactly reproduces world-sheet sigma model calculations, thus giving the correct overlap with both on- and off-shell string states, and that this new boundary state automatically satisfies the requirement for integrated vertex operators in the case of non-conformally invariant boundary interactions
An active-set approach for OFDM PAR reduction via tone reservation

Common to all orthogonal frequency division multiplexing (OFDM) systems is a large peak-to-average-power ratio (PAR), which can lead to low power efficiency and nonlinear distortion at the transmit power amplifier. Tone reservation uses other unused or reserved tones to design a peak-cancelling signal that lowers the PAR of a transmit OFDM block. In contrast to previous methods, the new active-set method proposed here converges very quickly toward a minimum-PAR solution at a lower computational cost. An efficient real-baseband algorithm is well suited for discrete multitone (DMT) modulation over twisted-pair copper wiring, where some subchannels may have an insufficient SNR to reliably send data. The real PAR problem occurs in the analog signal before the power amplifier, and results focus on this figure of merit. The performance of oversampling before applying PAR reduction is analyzed, and results show that this is necessary to sufficiently handle the analog PAR problem. An extension of the real-baseband technique can be applied to complex-baseband signals to help reduce PAR in wireless and broadcast systems. By sacrificing 11 out of 256 OFDM tones (4.3%) for tone reservation, over 3 dB of analog PAR reduction can be obtained for a wireless system.
Integrated Structure and Control Parameters Optimization for an Automotive Active Suspension System via LMIs

An automotive active suspension system composes of a mechanical structure and a feedback controller. Conventionally, these two elements are designed sequentially, with the controller design subsequent to that of the mechanical structure design. The traditional design method cannot obtain the global optimum performances for the system. This paper presents an approach to integrate structural and control parameters optimization for an automotive active suspension system via LMIs, for the effectiveness of the proposed integrated optimization method to improve riding and safety performance was proved by simulation studies.
A SPARQL Endpoint Profiler for an Efficient Question Answering System

A question answering (QA) system querying SPARQL endpoints must know which endpoints have data to match a triple pattern of a given question. To develop a system that locates endpoints more efficiently, we propose a tool to collect several metadata of a SPARQL endpoint using SPARQL queries only. The metadata include IRIs of explicitly declared classes (i.e., objects of the rdf:type predicate) as well as the number of triples whose subject and object belong to the respective classes. In addition, our tool counts triples whose objects are literals or any IRIs not appearing as the subject of the rdf:type predicate. The result is in RDF format using Vocabulary of Interlinked Datasets (VoID), Service Description (SD), and a newly developed vocabulary. We have collected data from various SPARQL endpoints and have provided them from our SPARQL endpoint. QA systems can easily utilize these data to improve their efficiency in finding endpoints by obtaining endpoints preemptively.
An RSSI-based scheme for sybil attack detection in wireless sensor networks

A sybil node impersonates other nodes by broadcasting messages with multiple node identifiers (ID). In contrast to existing solutions which are based on sharing encryption keys, we present a robust and lightweight solution for sybil attack problem based on received signal strength indicator (RSSI) readings of messages. Our solution is robust since it detects all sybil attack cases with 100% completeness and less than a few percent false positives. Our solution is lightweight in the sense that alongside the receiver we need the collaboration of one other node (i.e., only one message communication) for our protocol. We show through experiments that even though RSSI is time-varying and unreliable in general and radio transmission is non-isotropic, using ratio of RSSIs from multiple receivers it is feasible to overcome these problems
Connectionist Approaches to the Use of Markov Models for Speech Recognition

Previous work has shown the ability of Multilayer Perceptrons (MLPs) to estimate emission probabilities for Hidden Markov Models (HMMs). The advantages of a speech recognition system incorporating both MLPs and HMMs are the best discrimination and the ability to incorporate multiple sources of evidence (features, temporal context) without restrictive assumptions of distributions or statistical independence. This paper presents results on the speaker-dependent portion of DARPA's English language Resource Management database. Results support the previously reported utility of MLP probability estimation for continuous speech recognition. An additional approach we are pursuing is to use MLPs as nonlinear predictors for autoregressive HMMs. While this is shown to be more compatible with the HMM formalism, it still suffers from several limitations. This approach is generalized to take account of time correlation between successive observations, without any restrictive assumptions about the driving noise.
Incorporating Multi-Criteria Ratings in Recommendation Systems

Recommendation systems utilize information techniques to the problem of helping users find the items they would like. Example applications include the recommendation systems for movies, books, CDs and many others. As recommendation systems emerge as an independent research area, the rating structure plays a critical role in recent studies. Among many alternatives, the collaborative filtering algorithms are generally accepted to be successful to estimate user ratings of unseen items and then to derive proper recommendations. In this paper, we extend the concept of single criterion ratings to multi-criteria ones, i.e., an item can be evaluated in many different, aspects. Since there are usually conflicts among different criteria, the recommendation problem cannot be formulated as an optimization problem any more. Instead, we propose to use data query techniques to solve this multi-criteria recommendation problem.
Bioinformatics Applications Note Sequence Analysis the Uea Srna Workbench: a Suite of Tools for Analysing and Visualizing next Generation Sequencing Microrna and Small Rna Datasets

RNA silencing is a complex, highly conserved mechanism mediated by small RNAs (sRNAs), such as microRNAs (miRNAs), that is known to be involved in a diverse set of biological functions including development, pathogen control, genome maintenance and response to environmental change. Advances in next generation sequencing technologies are producing increasingly large numbers of sRNA reads per sample at a fraction of the cost of previous methods. However, many bioinformatics tools do not scale accordingly, are cumbersome, or require extensive support from bioinformatics experts. Therefore, researchers need user-friendly, robust tools, capable of not only processing large sRNA datasets in a reasonable time frame but also presenting the results in an intuitive fashion and visualizing sRNA genomic features. Herein, we present the UEA sRNA workbench, a suite of tools that is a successor to the web-based UEA sRNA Toolkit, but in downloadable format and with several enhanced and additional features. Availability: The program and help pages are available at http://srna
Localized Patterns in Periodically Forced Systems

Spatially localized, time-periodic structures are common in pattern-forming systems, appearing in fluid mechanics, chemical reactions, and granular media. We examine the existence of oscillatory localized states in a PDE model with single frequency time dependent forcing, introduced in [A. M. Rucklidge and M. Silber, SIAM J. Appl. Math., 8 (2009), pp. 298--347] as a phenomenological model of the Faraday wave experiment. In this study, we reduce the PDE model to the forced complex Ginzburg--Landau equation in the limit of weak forcing and weak damping. This allows us to use the known localized solutions found in [J. Burke, A. Yochelis, and E. Knobloch, SIAM J. Appl. Dyn. Syst. , 7 (2008), pp. 651--711]. We reduce the forced complex Ginzburg--Landau equation to the Allen--Cahn equation near onset, obtaining an asymptotically exact expression for localized solutions. We also extend this analysis to the strong forcing case, recovering the Allen--Cahn equation directly without the intermediate step. We find exc.
A Near-optimal User Ordering Algorithm for Non-iterative Interference Alignment Transceiver Design in MIMO Interfering Broadcast Channels

Interference alignment (IA) has recently emerged as a promising interference mitigation technique for interference networks. In this letter, we focus on the IA non-iterative transceiver design problem in a multiple-input-multiple-output interfering broadcast channel (MIMO-IBC), and observed that there is previously unexploited flexibility in different permutations of user ordering. By choosing a good user ordering for a pre-determined IA inter-channel-interference allocation, an improved transceiver design can be accomplished. In order to achieve a more practical performance-complexity tradeoff, a suboptimal user ordering algorithm is proposed. Simulation shows the proposed suboptimal user ordering algorithm can achieve near-optimal performance compared to the optimal ordering while exhibiting only moderate computational complexity.
Implementation of a fast method for measuring psychophysical tuning curves

Abstract Objective: To implement a fast method for measuring psychophysical tuning curves (PTCs) for use in clinical applications, such as assessment of frequency selectivity and detection of dead regions in the cochlea. Design: The method is based on that described by 17 and has been implemented in software that can be run on a PC with a good-quality sound card. In addition to the main narrowband noise masker, a lowpass noise masker can be generated to prevent detection of a distortion band corresponding to the simple difference tone. Results: The software includes a routine for measuring the absolute threshold at the signal frequency and includes methods for estimating the frequency at the tip of the PTC. A PTC can typically be determined in about three minutes. A small amount of practice (two to three runs) may be required to achieve stable results. Conclusions: The software implementation allows PTCs to be measured quickly without a requirement for specialised equipment. Sumario Objetivo: Implementar un método rápido para medir las curvas psicofisiológicas de sintonía (PTC) para su uso en aplicaciones clínicas tales como la evaluación de la selectividad frecuencial y la detección de zonas muertas de la cóclea. Diseño: El método se basa en la descripción de 17 y ha sido implementado en un software que puede correr en una PC con una buena tarjeta de sonido. Además de tener un enmascarador con ruido de banda ancha principal, se puede generar un enmascarador con ruido pasa-bajo, para prevenir la detección de una banda de distorsión, que corresponde al tono simple de diferencia. Resultados: El software incluye una rutina para medir el umbral absoluto a la frecuencia de la señal e incluye métodos para estimar la frecuencia en la punta de la PTC. Típicamente se puede determinar una PTC en unos tres minutos. Es necesaria un poco de práctica (dos o tres turnos) para lograr resultados estables. Conclusiones: la implementación del software permite medir PTC rápidamente sin requerir equipo especializado.
Discovering implicit constraints in design

Abstract Designers who are experts in a given design domain are well known to be able to Immediately focus on “good designs,” suggesting that they may have learned additional constraints while exploring the design space based on some functional aspects. These constraints, which are often implicit, result in a redefinition of the design space, and may be crucial for discovering chunks or interrelations among the design variables. Here we propose a machine-learning approach for discovering such constraints in supervised design tasks. We develop models for specifying design function in situations where the design has a given structure or embodiment, in terms of a set of performance metrics that evaluate a given design. The functionally feasible regions, which are those parts of the design space that demonstrate high levels of performance, can now be learned using any general purpose function approximator. We demonstrate this process using examples from the design of simple locking mechanisms, and as in human experience, we show that the quality of the constraints learned improves with greater exposure in the design space. Next, we consider changing the embodiment and suggest that similar embodiments may have similar abstractions. To explore convergence, we also investigate the variability in time and error rates where the experiential patterns are significantly different. In the process, we also consider the situation where certain functionally feasible regions may encode lower dimensional manifolds and how this may relate to cognitive chunking.
Mutations in ampG or ampD Affect Peptidoglycan Fragment Release from Neisseria gonorrhoeae

ABSTRACT Neisseria gonorrhoeae releases peptidoglycan fragments during growth. The majority of the fragments released are peptidoglycan monomers, molecules known to increase pathogenesis through the induction of proinflammatory cytokines and responsible for the killing of ciliated epithelial cells. In other gram-negative bacteria such as Escherichia coli, these peptidoglycan fragments are efficiently degraded and recycled. Peptidoglycan fragments enter the cytoplasm from the periplasm via the AmpG permease. The amidase AmpD degrades peptidoglycan monomers by removing the disaccharide from the peptide. The disaccharide and the peptide are further degraded and are then used for new peptidoglycan synthesis or general metabolism. We examined the possibility that peptidoglycan fragment release by N. gonorrhoeae results from defects in peptidoglycan recycling. The deletion of ampG caused a large increase in peptidoglycan monomer release. Analysis of cytoplasmic material showed peptidoglycan fragments as recycling intermediates in the wild-type strain but absent from the ampG mutant. An ampD deletion reduced the release of all peptidoglycan fragments and nearly eliminated the release of free disaccharide. The ampD mutant also showed a large buildup of peptidoglycan monomers in the cytoplasm. The introduction of an ampG mutation in the ampD background restored peptidoglycan fragment release, indicating that events in the cytoplasm (metabolic or transcriptional regulation) affect peptidoglycan fragment release. The ampD mutant showed increased metabolism of exogenously added free disaccharide derived from peptidoglycan. These results demonstrate that N. gonorrhoeae has an active peptidoglycan recycling pathway and can regulate peptidoglycan fragment metabolism, dependent on the intracellular concentration of peptidoglycan fragments.