Miracle-dz/UniFAR-FTUs huggingface dataset:
How many species are infected with Wolbachia? – a statistical analysis of current data

Wolbachia are intracellular bacteria found in many species of arthropods and nematodes. They manipulate the reproduction of their arthropod hosts in various ways, may play a role in host speciation and have potential applications in biological pest control. Estimates suggest that at least 20% of all insect species are infected with Wolbachia. These estimates result from several Wolbachia screenings in which numerous species were tested for infection; however, tests were mostly performed on only one to two individuals per species. The actual percent of species infected will depend on the distribution of infection frequencies among species. We present a meta-analysis that estimates percentage of infected species based on data on the distribution of infection levels among species. We used a beta-binomial model that describes the distribution of infection frequencies of Wolbachia, shedding light on the overall infection rate as well as on the infection frequency within species. Our main findings are that (1) the proportion of Wolbachia-infected species is estimated to be 66%, and that (2) within species the infection frequency follows a ‘most-or-few’ infection pattern in a sense that the Wolbachia infection frequency within one species is typically either very high (>90%) or very low (<10%).
Aberrant promoter hypermethylation of PBRM1, BAP1, SETD2, KDM6A and other chromatin-modifying genes is absent or rare in clear cell RCC

Recent sequencing studies of clear cell (conventional) renal cell carcinoma (ccRCC) have identified inactivating point mutations in the chromatin-modifying genes PBRM1, KDM6A/UTX, KDM5C/JARID1C, SETD2, MLL2 and BAP1. To investigate whether aberrant hypermethylation is a mechanism of inactivation of these tumor suppressor genes in ccRCC, we sequenced the promoter region within a bona fide CpG island of PBRM1, KDM6A, SETD2 and BAP1 in bisulfite-modified DNA of a representative series of 50 primary ccRCC, 4 normal renal parenchyma specimens and 5 RCC cell lines. We also interrogated the promoter methylation status of KDM5C and ARID1A in the Cancer Genome Atlas (TCGA) ccRCC Infinium data set. PBRM1, KDM6A, SETD2 and BAP1 were unmethylated in all tumor and normal specimens. KDM5C and ARID1A were unmethylated in the TCGA 219 ccRCC and 119 adjacent normal specimens. Aberrant promoter hypermethylation of PBRM1, BAP1 and the other chromatin-modifying genes examined here is therefore absent or rare in ccRCC.
Multiple personality disorder from the inside out.

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Influence of vertical mixing on the thermohaline hysteresis: Analyses of an OGCM

The thermohaline hysteresis response to varying North Atlantic freshwater forcing is studied by means of a three-dimensional global ocean general circulation model (OGCM). The influence of vertical diffusivity is examined using a wide range of mixing coefficients. For sufficiently large vertical diffusivity the model shows a pronounced hysteresis behavior, so that two equilibrium states of the thermohaline circulation are found: one mode with intense deep-water formation in the North Atlantic (‘‘on’’ mode) and one mode with strongly reduced convective activity (‘‘off’’ mode). By decreasing the diffusivity, the two branches of the hysteresis merge. In addition, the effect of numerical diffusion is analyzed by applying different advection schemes. A positive feedback between overturning strength and the numerical diffusivity of upstream advection is found, resulting in a reduced stability of the ‘‘on’’ mode. Comparing the results with those from zonally averaged models exhibits substantial differences regarding the stability properties of the thermohaline circulation. Freshwater transports by horizontal gyres have an important effect on the overturning circulation in the OGCM.
Imbalanced Learning with Kernels

Imbalanced learning, or learning from imbalanced data, is a challenging problem in both academy and industry. Nowadays, the streaming imbalanced data become popular and trigger the volume, velocity, and variety issues of learning from these data. To tackle these issues, online learning algorithms are proposed to learn a linear classifier via maximizing the AUC score. However, the developed linear classifiers ignore the learning power of kernels. In this paper, we therefore propose online imbalanced learning with kernels (OILK) to exploit the non-linearity and heterogeneity embedded in the imbalanced data. Different from previously proposed work, we optimize the AUC score to learn a non-linear representation via the kernel trick. To relieve the computational and storing cost, we also investigate different buffer update policies, including first-in-first-out (FIFO) and reservoir sampling (RS), to maintain a fixed budgeted buffer on the number of support vectors. We demonstrate the properties of our proposed OILK through detailed experiments.
Auditory Neuroscience: Making Sense of Sound

Every time we listen -- to speech, to music, to footsteps approaching or retreating -- our auditory perception is the result of a long chain of diverse and intricate processes that unfold within the source of the sound itself, in the air, in our ears, and, most of all, in our brains. Hearing is an "everyday miracle" that, despite its staggering complexity, seems effortless. This book offers an integrated account of hearing in terms of the neural processes that take place in different parts of the auditory system. Because hearing results from the interplay of so many physical, biological, and psychological processes, the book pulls together the different aspects of hearing -- including acoustics, the mathematics of signal processing, the physiology of the ear and central auditory pathways, psychoacoustics, speech, and music -- into a coherent whole.
Kinetics, Hydrodynamics and Stochastodynamics of Cellular Structure Coarsening

For the first time the phenomenon of cellular structure coarsening are consistently analyzed from the positions of kinetic, hydrodynamic and stochastodynamic theories of nonequilibrium statistical systems. Thereby micro-, meso- and macroscopic levels of approach are distinguished. At the microscopic level the cellular structure is describe by a probability distribution function in a phase space of cell coordinates and of cell sizes. A kinetic equation for the function is written and a development to a hydrodynamic equation of a mesoscopic cell medium is realized. It has the form of a diffusion–reaction equation with a negative "diffusion" coefficient and with a cell interface density playing the role of concentration. Its analysis reveals a new effect of macroscopic patterning in the cell medium: existence of space-correlated stochastic fluctuations of the cell interface density.
Social Cues Support Learning about Objects from Statistics in Infancy

In laboratory experiments, infants can learn patterns of features that co-occur (e.g., Fiser & Aslin, 2002). This finding leaves two questions unanswered: What do infants do with the knowledge acquired from such statistical learning, and which patterns do infants attend to in the noisy and cluttered world outside of the laboratory? Here, we show that 9-month-old infants form expectations about co-occurring features remaining fused, an essential skill for object individuation and recognition (e.g., Goldstone, 2000; Schyns & Rodet, 1997). We also show that though social cues may temporarily detract attention away from learning events, they appear to stimulate infants to display learning better in complex situations than when infants learn on their own without attention cues. These findings suggest that infants can use feature co-occurrence to learn about objects and that social cues shape such foundational learning in a noisy environment during infancy.
Accurate timekeeping is controlled by a cycling activator in Arabidopsis

Transcriptional feedback loops are key to circadian clock function in many organisms. Current models of the Arabidopsis circadian network consist of several coupled feedback loops composed almost exclusively of transcriptional repressors. Indeed, a central regulatory mechanism is the repression of evening-phased clock genes via the binding of morning-phased Myb-like repressors to evening element (EE) promoter motifs. We now demonstrate that a related Myb-like protein, REVEILLE8 (RVE8), is a direct transcriptional activator of EE-containing clock and output genes. Loss of RVE8 and its close homologs causes a delay and reduction in levels of evening-phased clock gene transcripts and significant lengthening of clock pace. Our data suggest a substantially revised model of the circadian oscillator, with a clock-regulated activator essential both for clock progression and control of clock outputs. Further, our work suggests that the plant clock consists of a highly interconnected, complex regulatory network rather than of coupled morning and evening feedback loops. DOI: http://dx.doi. org/10.7554/eLife.00473. 001
Biochemia Medica introduces new section: Pre-analytical mysteries

Among the many things which journal editors need to focus on in order for a journal to become an internationally recognized, is to identify its niche, i.e. define topics which would make the journal recognizable (1). Over the years we have tried hard to establish our individuality via careful selection of topics covered by our journal. Quality management of the pre- and post- analytical phase has become our major focus and papers falling in that field have long been among the most downloaded and most cited papers published in Biochemia Medica. Besides dealing with quality in laboratory medicine, we have also been dedicated to educate our authors and readers by publishing simple and educational lessons covering various research integrity issues and different topics in biostatistics. The feedback that we are receiving from our audience tells us that the path we chose was right. To further nurture our educational goals and combine it with a commitment to raise awareness about some of the most challenging issues in the pre- and post-analytical phase of laboratory work, this issue introduces a new section in Biochemia Medica entitled: Pre-analytical mysteries. The aim of this section is to provide a platform to disseminate some common pre- analytical problems and how to deal with them in the form of short case reports. We therefore invite laboratory professionals to share their pre-analytical challenges encountered in their everyday work with the rest of laboratory community by submitting them in the form of pre- analytical case reports to Biochemia Medica. Cases do not necessarily need to be novel but should be aimed at educating laboratory professionals to better understand the various challenges in our work and learn how to better deal with these issues. To keep the format standardized and ensure its true educational component, the authors are kindly requested to use the proposed template.
Drivers' decision-making when attempting to cross an intersection results from choice between affordances

In theory, a safe approach to an intersection implies that drivers can simultaneously manage two scenarios: they either choose to cross or to give way to an oncoming vehicle. In this article we formalize the critical time for safe crossing (CTcross) and the critical time for safe stopping (CTstop) to represent crossing and stopping possibilities, respectively. We describe these critical times in terms of affordances and empirically test their respective contribution to the driver's decision-making process. Using a driving simulator, three groups of participants drove cars with identical acceleration capabilities and different braking capabilities. They were asked to try to cross an intersection where there was an oncoming vehicle, if they deemed the maneuver to be safe. If not, they could decide to stop or, as a last resort, make an emergency exit. The intersections were identical among groups. Results showed that although the crossing possibilities (CTcross) were the same for all groups, there were between-group differences in crossing frequency. This suggests that stopping possibilities (CTstop) play a role in the driver's decision-making process, in addition to the crossing possibilities. These results can be accounted for by a behavioral model of decision making, and provide support for the hypothesis of choice between affordances.
Interference Analysis of Asynchronous OFDM/FBMC Based Cognitive Radio Transceivers

In this paper, we investigate the impact of the asynchronismon the performance of a Cognitive Radio (CR) network, using the underlay paradigm. We are also comparing this effectdepending on which modulation technique we are using. Weprovide a new the theoretical aspect of interference analysis in thecontext of orthogonal frequency division multiplexing (OFDM) and the Filter Bank Multicarrier (FBMC) techniques in a CR network. In different communication systems, the asynchronism canbe harmful on the system's performance, and consequently cancause an asynchronous interference. Related works are evaluatingthe performance analytically either in terms of power allocationor spectrum sensing, and if the interference evaluation is done, itis not in the context of a CR network. In our work, we performa theoretical analysis of the interference in terms of Bit ErrorRate (BER) and Signal to Noise Ratio (SNR). Furthermore, we arealso leading with a comparison between the two cases (OFDM orFBMC). Simulation results, compared to the theoretical approachconfirm the validity of our analysis.
A novel ReRAM-based processing-in-memory architecture for graph computing

Graph algorithms such as breadth-first search (BFS) have been gaining ever-increasing importance in the era of Big Data. However, the memory bandwidth remains the key performance bottleneck for graph processing. To address this problem, we utilize processing-in-memory (PIM), combined with non-volatile metal-oxide resistive random access memory (ReRAM), to improve the performance of both computation and I/O. The idea is to integrate the computation logic into the memory in which the data accesses are located. We propose and implement a new ReRAM-based processing-in-memory architecture called RPBFS, in which graphs can be processed and persistently stored. We also design an efficient graph traversal scheme. Benefited from low data movement overhead and bank-level parallel computation, RPBFS shows a significant performance improvement compared with both the CPU-based and GPU-based BFS implementations. On a suite of real world graphs, our architecture yields up to 33.8× speedup.
Chaperone proteins as single component reagents to assess antibody nonspecificity

ABSTRACT Early stage assays that evaluate monoclonal antibody drug-like properties serve as valuable tools for selection of lead candidates. One liability for clinical development, off-target reactivity, is often assessed by binding to a mixture or panel of noncognate proteins. While robust, these mixes are often ill-defined, and can suffer from issues such as lot-to-lot variability. In this study, we discovered in immunoprecipitation experiments that certain chaperones are present in one of these mixtures;we then explored the use of recombinant chaperone proteins as well-characterized agents to predict antibody nonspecificity. Antibody binding to the heat shock proteins HSP70, HSP90, or trigger factor all served as predictors of cross-interaction propensity, with HSP90 providing the greatest ability to predict antibody clearance rates in mouse. Individual chaperone binding correlates surprisingly closely with binding to complex cell extracts, with the exception of a few “false negatives” (assuming a complex cell extract as the “true” value). As defined reagents, these chaperone reagents present advantages for high throughput assays of nonspecificity.
Magnesium and Ketamine Gargle and Postoperative Sore Throat

Background: Postoperative sore throat is one of the most common complications after endotracheal intubation. Both Ketamine and magnesium can block N-methyl-D-aspartic acid (NMDA) receptors and provide central and local analgesia. Objectives: To compare the effect of magnesium sulfate and ketamine gargle on the incidence and severity of postoperative sore throat. Patients and Methods: A total of 100 patients candidate for emergency acute appendicitis surgery were enrolled in the study. Patients in ketamine group received ketamine gargle (0.5 mg/kg) and magnesium group received magnesium sulfate gargle (20 mg/kg up to 30 mL dextrose water 20%) 15 minutes before the operation. Patient complaint of postoperative sore throat, and its severity measured by visual analogue scale (VAS) were recorded at baseline in recovery room, and then 2, 4, and 24 hours after operation. Results: There were no significant differences between age, sex, and body mass index (BMI) between two groups of patients. Hemodynamics of patients, including blood pressure, respiratory rate, oxygen saturation %, and conscious state were not significantly different (P > 0.05). Number of patients with sore throat were significantly lower in magnesium group compared to ketamine group at 2 (P = 0.032), 4 (P = 0.02), and 24 hours (P = 0.01) after the operation. Sore throat pain score (VAS) was significantly lower in magnesium group compared to ketamine group at 2 (P = 0.019), 4 (P = 0.028), and 24 hours (P = 0.014) after the operation. Conclusions: Magnesium at low dose decreases sore throat and pain severity more effectively compared to ketamine gargle.
Agent UML : A formalism for specifying multiagent interaction

In the past, research on agent-oriented software engineering had been widely lacking touch with the world of industrial software development. Recently, a cooperation has been established between the Foundation of Intelligent Physical Agents (FIPA) and the Object Management Group (OMG) aiming to increase acceptance of agent technology in industry by relating to de facto standards (object-oriented software development) and supporting the development environment throughout the full system lifecycle. As a first result of this cooperation, we proposed AGENT UML [Bauer, 1999; Odell 2000], an extension of the Unified Modeling language (UML), a de facto standard for object-oriented analysis and design. In this paper, we describe the heart of AGENT UML, i.e., mechanisms to model protocols for multiagent interaction. Particular UML extensions described in this paper include protocol diagrams, agent roles, multithreaded lifelines, extended UML message semantics, nested and interleaved protocols, and protocol templates.
On the extraction of dead-time controllers and estimators from delay-free parametrizations

A novel approach to control design for dead-time (DT) systems is proposed. The underlying idea is to treat the DT element not as a part of the generalized plant, but rather as a (causality) constraint imposed upon the controller (estimator). This enables one to use well-understood parametrizations of all delay-free controllers in the DT design. In particular, DT con- trollers can be extracted from such delay-free parametrizations. In this paper, the extraction procedures are developed in both and settings. It is shown that the proposed approach yields simple solution procedures and new transparent and intuitively appealing structures for the resulting controllers and estimators.
Deformation Quantization and Irrational Numbers

Diophantine approximation is the problem of approximating a real number by rational numbers. We propose a version of this in which the numerators are approximately related to the denominators by a Laurent polynomial. Our definition is motivated by the problem of constructing strict deformation quantizations of symplectic manifolds. We show that this type of approximation exists for any real number and also investigate what happens if the number is rational or a quadratic irrational.
Device signal strength self-calibration using histograms

Traditionally, positioning with WLAN Received Signal Strength (RSS) fingerprints involves the laborious task of collecting a radiomap with a reference mobile device. Best accuracy can be guaranteed only in case the user carries the same device, while positioning with different devices requires a calibration step to make the new devices' RSS values compatible with the existing radiomap. We propose a novel device self-calibration method that uses histograms of RSS values. First, we use the existing radiomap to create the RSS histogram of the reference device. Subsequently, when the user enters a building and starts positioning, the observed RSS values are recorded simultaneously in the background to create and update the histogram of the user device. We use these RSS histograms to fit a linear mapping between the user and reference device. Our calibration method is running concurrently with positioning and does not require any user intervention. Experimental results with five smartphones in a real indoor environment indicate that soon after positioning is initiated the device is self-calibrated, thus improving the accuracy to be comparable with the case of using a radiomap created with the same device.
Exploiting rational basis functions in iterative learning control

Iterative learning control approaches often suffer from poor extrapolability with respect to exogenous signals, including setpoint variations. The aim of this paper is to introduce rational basis functions in ILC. Such rational basis function have the potential to both increase performance and enhance extrapolability. The key caveat that is associated with these rational basis function lies in a significantly more complex optimization problem when compared to using polynomial basis functions. In this paper, a novel iterative optimization procedure is proposed that enables the use of rational basis functions in ILC. A simulation example confirms (1) the advantages of rational basis functions compared to pre-existing results, and (2) the efficacy of the proposed iterative algorithm.