Miracle-dz/UniFAR-FTUs huggingface dataset:
A Tool-Supported Methodology for Ontology-Based Knowledge Management

A methodology for introducing an ontology-based KM solution into enterprises is described which extends and improves the CommonKADS methodology by introducing — among others — specific guidelines for developing and maintaining the respective ontology. Special emphasis is put on a stepwise construction and evaluation of the ontology. The methodology is supported by a tool, “OntoKick”, that supports ontology engineers in early stages, i.e. the kickoff phase of ontology development.
Determinants of sleep quality in middle‐aged women with fibromyalgia syndrome

The objectives of this study were: (i) to compare the sleep quality at home of patients with fibromyalgia with that of healthy controls; and (ii) to examine the factors associated with sleep quality in patients with fibromyalgia. In addition to anthropometric measures, 75 women with fibromyalgia and 48 healthy controls completed standardized questionnaires that assessed sleep quality, functional impairment (Fibromyalgia Impact Questionnaire), depression, anxiety and physical activity level. Comparisons between groups, correlation coefficients and a series of hierarchical multiple regressions were performed. The global Pittsburgh Sleep Quality Index scores were worse in patients with fibromyalgia than in the controls. This result was partly explained by the Fibromyalgia Impact Questionnaire score. For the patients with fibromyalgia, the results of the first model that tested the importance of demographic factors were not statistically significant. In the disease‐related model, the duration of symptoms and symptom severity contributed to poor sleep quality. A measurement of physical activity participation and the sum of the skinfold thickness were added to the demographic factors. In the psychological model, the level of anxiety contributed to poor sleep quality. When all variables were entered simultaneously, the level of physical activity, duration of symptoms and symptom severity remained significant determinants of sleep quality. In conclusion, our results showed that the symptoms associated with fibromyalgia contributed to poor overall sleep quality in patients compared with healthy subjects. The findings also suggest that the duration of symptoms, symptom severity and especially a sedentary lifestyle contributed to decreased sleep quality in patients with fibromyalgia.
Improved technique for determining complex permittivity with the transmission/reflection method

The transmission/reflection method for complex permittivity and permeability determination is studied. The special case of permittivity measurement is examined in detail. Robust algorithms for permittivity determination that eliminate the ill-behaved nature of the commonly used procedures at frequencies corresponding to integer multiples of one-half wavelength in the sample are presented. An error analysis yielding estimates of the errors incurred due to the uncertainty in scattering parameters, length measurement, and reference plane position is presented. Equations for determining complex permittivity independent from reference plane position and sample length are derived. >
Antimicrobial Peptide Resistance Mechanisms of Gram-Positive Bacteria

Antimicrobial peptides, or AMPs, play a significant role in many environments as a tool to remove competing organisms. In response, many bacteria have evolved mechanisms to resist these peptides and prevent AMP-mediated killing. The development of AMP resistance mechanisms is driven by direct competition between bacterial species, as well as host and pathogen interactions. Akin to the number of different AMPs found in nature, resistance mechanisms that have evolved are just as varied and may confer broad-range resistance or specific resistance to AMPs. Specific mechanisms of AMP resistance prevent AMP-mediated killing against a single type of AMP, while broad resistance mechanisms often lead to a global change in the bacterial cell surface and protect the bacterium from a large group of AMPs that have similar characteristics. AMP resistance mechanisms can be found in many species of bacteria and can provide a competitive edge against other bacterial species or a host immune response. Gram-positive bacteria are one of the largest AMP producing groups, but characterization of Gram-positive AMP resistance mechanisms lags behind that of Gram-negative species. In this review we present a summary of the AMP resistance mechanisms that have been identified and characterized in Gram-positive bacteria. Understanding the mechanisms of AMP resistance in Gram-positive species can provide guidelines in developing and applying AMPs as therapeutics, and offer insight into the role of resistance in bacterial pathogenesis.
A Topology Adjustment Algorithm for P2P Systems

In order to improve the Peer-to-Peer (P2P) network resource locating efficiency and isolate malicious peers, a topology adjustment algorithm for unstructured P2P networks is proposed. TTL (time-to-live) value for each neighbor has been set up and adjusted; specific information on the query path is recorded; a topology adjustment algorithm is given. The topology adjustment algorithm is evaluated by peer shortest path, simulation and analysis show that the topology adjustment algorithm can isolate malicious peers to the network edge, and improve service quality of P2P networks.
Speech enhancement based on adaptive wavelet denoising on multitaper spectrum

Classical speech enhancement algorithms often require a good estimation of the short-time power spectrum using, for instance, the periodogram methods. However, it is well known that traditional periodogram methods are prone to induce large variance, hence produces the "musical noise" after enhancement. To alleviate this problem, multitaper spectrum (MTS) estimators with wavelet denoising were proposed. In this paper, we investigate the properties of the MTS of noisy speech signals. We find that, in the log MTS domain, the variance of noise varies according to the magnitude of the underlying speech spectrum. It implies that when applying wavelet denoising to the log MTS, the constant threshold used in the traditional methods is not appropriate. Based on this observation, we further develop a wavelet denoising method with adaptive threshold for estimating power spectrum using multitaper. Simulation results show that the spectrum estimated using the proposed method is consistently more accurate than the traditional uniform thresholding methods. Hence, it further improves the current speech enhancement algorithms using the MTS approaches.
SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop

Summary: Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner. SeqPigscripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig’s scalability over many computing nodes and illustrate its use with example scripts. Availability and Implementation: Available under the open source MIT license at http://sourceforge.net/projects/seqpig/ Contact: andre.schumacher@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online.
Energy-efficient collaborative sensing with mobile phones

Mobile phones with a rich set of embedded sensors enable sensing applications in various domains. In this paper, we propose to leverage cloud-assisted collaborative sensing to reduce sensing energy consumption for mobile phone sensing applications. We formally define a minimum energy sensing scheduling problem and present a polynomial-time algorithm to obtain optimal solutions, which can be used to show energy savings that can potentially be achieved by using collaborative sensing in mobile phone sensing applications, and can also serve as a benchmark for performance evaluation. We also address individual energy consumption and fairness by presenting an algorithm to find fair energy-efficient sensing schedules. Under realistic assumptions, we present two practical and effective heuristic algorithms to find energy-efficient sensing schedules. It has been shown by simulation results based on real energy consumption (measured by the Monsoon power monitor) and location (collected from the Google Map) data that collaborative sensing significantly reduces energy consumption compared to a traditional approach without collaborations, and the proposed heuristic algorithm performs well in terms of both total energy consumption and fairness.
Optimization of the maximum power point tracking method for peak-current controlled flyback micro-inverter

The Maximum power point tracking (MPPT) algorithms are widely used in micro-inverters to maximize the PV panel's output power. The perturb and observe (P&O) algorithm is the most commonly used method due to its simple implementation. However, since the switching frequency of the BCM micro-inverter is variable, the switching duty ratio or the panel voltage could not be simply used as the perturbed signal. In this paper, it is shown that the current reference amplitude value can be utilized to implement the P&O function. Besides, an improved adaptive-step method is also proposed to alleviate the tradeoff problem between faster response and steady-state oscillations. The design considerations of some parameters like sampling interval and perturb step limitations are also given in this paper. Simulation and experimental results are provided to validate the proposed techniques.
Myristyl Trimethyl Ammonium Bromide and Octadecyl Trimethyl Ammonium Bromide Are Surface-Active Small Molecule Dynamin Inhibitors that Block Endocytosis Mediated by Dynamin I or Dynamin II

Dynamin is a GTPase enzyme involved in membrane constriction and fission during endocytosis. Phospholipid binding via its pleckstrin homology domain maximally stimulates dynamin activity. We developed a series of surface-active small-molecule inhibitors, such as myristyl trimethyl ammonium bromide (MiTMAB) and octadecyltrimethyl ammonium bromide (OcTMAB), and we now show MiTMAB targets the dynamin-phospholipid interaction. MiTMAB inhibited dynamin GTPase activity, with a Ki of 940 ± 25 nM. It potently inhibited receptor-mediated endocytosis (RME) of transferrin or epidermal growth factor (EGF) in a range of cells without blocking EGF binding, receptor number, or autophosphorylation. RME inhibition was rapidly reversed after washout. The rank order of potency for a variety of MiTMAB analogs on RME matched the rank order for dynamin inhibition, suggesting dynamin recruitment to the membrane is a primary cellular target. MiTMAB also inhibited synaptic vesicle endocytosis in rat brain nerve terminals (synaptosomes) without inducing depolarization or morphological defects. Therefore, the drug rapidly and reversibly blocks multiple forms of endocytosis with no acute cellular damage. The unique mechanism of action of MiTMAB provides an important tool to better understand dynamin-mediated membrane trafficking events in a variety of cells.
Viremia and Nasal and Rectal Shedding of Rotavirus in Gnotobiotic Pigs Inoculated with Wa Human Rotavirus

ABSTRACT Respiratory symptoms with rotavirus shedding in nasopharyngeal secretions have been reported in children with and without gastrointestinal symptoms (Zheng et al., 1991, J. Med. Virol. 34:29-37). To investigate if attenuated and virulent human rotavirus (HRV) strains cause upper respiratory tract infections or viremia in gnotobiotic pigs, we inoculated them with attenuated or virulent HRV intranasally, intravenously, or orally or via feeding tube (gavage) and assayed virus shedding. After oral or intranasal inoculation with attenuated HRV, the pigs remained asymptomatic, but 79 to 95% shed virus nasally and 5 to 17% shed virus rectally. After inoculation by gavage, no pigs shed virus nasally or rectally, but all pigs seroconverted with antibodies to HRV. No viremia was detected through postinoculation day 10. Controls inoculated intranasally with nonreplicating rotavirus-like particles or mock inoculated did not shed virus. In contrast, 100% of pigs inoculated with virulent HRV (oral, intranasal, or gavage) developed diarrhea, shed virus nasally and rectally, and had viremia. The infectivity of sera from the viremic virulent HRV-inoculated pigs was confirmed by inoculating gnotobiotic pigs orally with pooled HRV-positive serum. Serum-inoculated pigs developed diarrhea and fecal and nasal virus shedding and seroconverted with serum and intestinal HRV antibodies. Pigs inoculated intravenously with serum or intestinal contents from the viremic virulent HRV-inoculated pigs developed diarrhea, virus shedding, and viremia, similar to the orally inoculated pigs. This study provides new evidence that virulent HRV causes transient viremia and upper respiratory tract infection in addition to gastrointestinal infection in gnotobiotic pigs, confirming previous reports of rotavirus antigenemia (Blutt et al., Lancet 362:1445-1449, 2003). Our data also suggest that intestinal infection might be initiated from the basolateral side of the epithelial cells via viremia. Additionally, virus shedding patterns indicate a different pathogenesis for attenuated versus virulent HRV.
Optimum design of 3R robot manipulador by using Improved Differential Evolution implemented in parallel computation

In recent decades the great interest in Evolutionary Algorithms (EAs) has boosted their development leading to a significant improvement in their efficiency and applicability. Thus, EAs have been applied to solve optimization problems in different areas of knowledge. A promising optimization method known as Differential Evolution (DE), which belongs to the class of AEs, has attracted the attention of researchers. The DE algorithm is simple, robust and efficient. However, by testing with classical optimization problems noticed that sometimes the results obtained with DE are not as satisfactory as expected or that in many cases the algorithm ends the search for the optimal solution prematurely. Recently, with the advancement and greater availability of computer technology, the scientific community has been thinking about the implementation of optimization algorithms in parallel in order to reduce the processing time. The main objective of this paper is to present an improvement of the Differential Evolution optimization method, proposing modifications to the basic algorithm by using shuffled complex and making it able to work with parallel computing. The proposed methodology is applied to the optimal design of an orthogonal 3R robot manipulator that takes into account the characteristics of its workspace. For this purpose, a multi-objective optimization problem is formulated to obtain the optimal geometric parameters for the robot. The maximum workspace volume, the maximum system stiffness and the optimum dexterity are considered as the multi-objective functions. The results show that the procedure represents a promising alternative for the type of problem presented above.
In Search for a Full Vision: Writing Representations of African American Adolescent Girls

Self-exploration and self-representation are key developmental tasks during adolescence yet, these are further complicated for African American adolescent girls who are positioned in a society that has given them mixed and often times, distorted images associated with Black girlhood (Muhammad, 2012). While there is a rich and lengthy literary history of African American women writing to represent their lives (Foster, 1993; Royster, 2000; Wall, 2005), the current research landscape is saturated with how others have represented African American girls or research focused on pathologies. These research literatures are typically written absent of the girls’ voices and do not offer enough insight into how African American adolescent girls represent themselves. Instead, they paint an incomplete, unclear picture connected to their selfhood and into representing who they are. To respond to this incomplete picture of African American girls, this study examined how they represented themselves within their writings. Taking a historical orientation to a case study methodology (Merriam, 1998; Yin, 2009), African American women’s writings and the literacy enactments found in nineteenth century African American literary societies were examined to frame a four-week literacy collaborative designed to nurture the identities and literacies of eight African American adolescent girls. The following research questions guided the inquiry: 1) How do African American adolescent girls represent themselves through their writings? 2) Which factors within a literacy collaborative contribute to representations within their writings? Findings show that the girls wrote across similar platforms of African American women historically which included writing to represent self, to resist or counter ascribed representations and writing toward social change (Peterson, 1995; Royster, 2000). The girls wrote multiple and complex representations which included ethnic, gender, intellectual, kinship, sexual, individual and community representations. The primary contextual factors of the literacy collaborative that contributed to their self-representations included the use of mentor text, having the freedom to write openly and without apology, and uninterrupted writing time. The findings suggest the girls’ writings served as hybrid spaces for the girls to explore, make sense of, and express different manifestations of self.
Cooperation and Forward-Looking Behavior in Hawk-Dove Games in Endogenous Networks: Experimental Evidence I

In this paper, we present the experimental results of our investigation of network formation and the distribution of actions in a population of players whose members may select their partners in a bilateral 2x2 Hawk-Dove base game. In the population game, exploitive Hawk behavior leads to ineciency while cooperative Dove behavior leads to ecient outcomes. The experiment was conducted in continuous time such that participants could change their base game action and their partners at any point in time. For this type of strategic interaction we introduce a strategy adaptation rule (anticipatory better-reply rule, ABR) for players with limited foresight and a related stability criterion (reaction-anticipating stable, RAS), both of which assume that players take other players’ linking reactions into account when deciding on their strategies. A comparison of the ABR vs. the better-reply rule and the RAS vs. the Nash equilibrium ultimately reveals that the ABR and RAS are in better accord with our data. Moreover, we nd that cooperative Dove behavior yielded higher payos than hawkish behavior.
Weighted factorization

Factorization methods use linear subspace constraints to recover 3D rigid structures from 2D motion. Usually, these methods give equal weight to the contribution of each region (or feature) to the estimates of the 3D structure. In this paper, we accommodate different confidence weights for the 2D motion parameter estimates of each region, by rewriting the problem as the factorization of a modified matrix. This incurs no additional computational cost.
Development of Heterogeneous Parallel Genetic Simulated Annealing Using Multi-Niche Crowding

— In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from local optima. The concept of hierarchical parallel GA is employed to parallelize GSA for the optimization of multimodal functions. In addition, multi-niche crowding is used to maintain the diversity in the population of the parallel GSA (PGSA). The performance of the proposed algorithms is evaluated against a standard set of multimodal benchmark functions. The multi-niche crowding PGSA and normal PGSA show some remarkable improvement in comparison with the conventional parallel genetic algorithm and the breeder genetic algorithm (BGA).
An Optimization Approach of Deriving Bounds between Entropy and Error from Joint Distribution: Case Study for Binary Classifications

In this work, we propose a new approach of deriving the bounds between entropy and error from a joint distribution through an optimization means. The specific case study is given on binary classifications. Two basic types of classification errors are investigated, namely, the Bayesian and non-Bayesian errors. The consideration of non-Bayesian errors is due to the facts that most classifiers result in non-Bayesian solutions. For both types of errors, we derive the closed-form relations between each bound and error components. When Fano’s lower bound in a diagram of “Error Probability vs. Conditional Entropy” is realized based on the approach, its interpretations are enlarged by including non-Bayesian errors and the two situations along with independent properties of the variables. A new upper bound for the Bayesian error is derived with respect to the minimum prior probability, which is generally tighter than Kovalevskij’s upper bound.
Decentralized Primary Frequency Control in Power Networks

We augment existing generator-side primary frequency control with load-side control that are local, ubiquitous, and continuous. The mechanisms on both the generator and the load sides are decentralized in that their control decisions are functions of locally measurable frequency deviations. These local algorithms interact over the network through nonlinear power flows. We design the local frequency feedback control so that any equilibrium point of the closed-loop system is the solution to an optimization problem that minimizes the total generation cost and user disutility subject to power balance across entire network. With Lyapunov method we derive a sufficient condition ensuring an equilibrium point of the closed-loop system is asymptotically stable. Simulation demonstrates improvement in both the transient and steady-state performance over the traditional control only on the generators, even when the total control capacity remains the same.
Automatic Device-Transparent RSS-Based Indoor Localization

Signal strength variation across diverse devices is a major problem with RSS-based indoor localization systems. This paper aims to solve this problem by considering two factors: the instability of collected RSS samples and linear shift of RSS patterns collected by different devices. We propose different techniques to handle the uncertainty of samples. Furthermore, we propose an automatic linear transformation algorithm that relies on the linear relationship across diverse devices. The algorithm finds the set of nearest neighbor fingerprints for an online point through a series of linear transformations. A localizer engine is then used to detect user's location. The proposed system is automatic, has low computational complexity and does not require any training period. Experimental results indicate the proposed system is reliable with very high positional accuracy.