Miracle-dz/UniFAR-FTUs huggingface dataset:
Ternary Bradley-Terry model-based decoding for multi-class classification

A multi-class classifier based on the Bradley-Terry model predicts the multi-class label of an input by combining the outputs from multiple binary classifiers, where the combination should be a priori designed as a code word matrix. According to this framework, the code word matrix was originally designed to consist of +1 and -1, and has later been extended to allow zero components. This extension has seemed to effectively work, but in fact, contains a problem. In this article, we propose a Boosting algorithm, which deals with three categories by allowing a dasiadonpsilat carepsila category, and present a modified decoding method called dasiaternarypsila Bradley-Terry model. In addition, we propose a fast decoding scheme which resolves the heavy computation of the conventional Bradley-Terry model-based decoding.
Competitive Ability of Native Grasses and Non-Native (Old World Bluestems; Bothriochloa Spp.) Grasses

Old World Bluestems (OWB), introduced from Europe and Asia in the 1920s, recently have begun to raise concerns in the Great Plains. Despite determination in the late 1950s that OWS were weedy and negatively impacted biological diversity, they were widely introduced throughout the Great Plains for agricultural purposes. Anecdotal evidence suggests that OWB exhibit invasive characteristics that promote competitive exclusion of other species. The objective of my study was to quantify the competitive abilities of two OWB species [Caucasian bluestem; Bothriochloa bladhii (Retz.) S.T. Blake [= Bothriochloa caucasia (Trin.) C.E. Hubb. ], and yellow bluestem; Bothriochloa ischaemum (L.) Keng] with three native grass species [big bluestem (Andropogon gerardii Vitman), little bluestem (Schizachyrium scoparium (Michx.) Nash), and sideoats grama (Bouteloua curtipendulua (Michx.) Torr. )]. A greenhouse target-neighbor study was conducted to assess both interspecific and intraspecific competition. A total of 480 pots (4.4 liter) filled with composited soil was used with all pair-wise combinations of species (six replications). Plant growth parameters including height and tiller number were measured weekly. Biomass was measured at the end of 16 weeks by separately harvesting, drying at 60°C, and weighing (g) above-ground (vegetative and reproductive) and below-ground plant structures. Both of the OWB significantly inhibited at least one growth parameter of the three native grass species, while most of the native species did not inhibit growth of either OWB species. Growth of yellow bluestem was enhanced when grown in association with little bluestem. Based upon the results of my study of OWB competitive superiority and previous research, many of tile characteristics possessed by owe are found to be in common with known invasive species. Hence, I propose that OWB are an invasive, non-native group or grasses, which could invade and threaten the native grasslands of the Central and Southern Great Plains.
A potential vorticity view of synoptic development

A physical discussion of vorticity and its change by stretching and tilting is presented. The discussion naturally leads on to the conservation of quasi‐geostrophic potential vorticity, q, and the flow associated with anomalies in q. The extension to full potential vorticity (PV) and the associated conservation and inversion properties is made. The use for illustrating and understanding synoptic developments of maps of PV on isentropic surfaces and potential temperature (θ) on PV surfaces is shown by considering two recent examples in the North Atlantic–Europe regions. The first is a summer situation and the second is the major blocking in January 1996. Concluding comments about the role of diabatic processes and other possible uses of these diagnostics are made. Copyright © 1997 Royal Meteorological Society
Cover Crop Effectiveness Varies in Cover Crop-Based Rotational Tillage Organic Soybean Systems Depending on Species and Environment

Organic farming relies heavily on tillage for weed management, however, intensive soil disturbance can have detrimental impacts on soil quality. Cover crop-based rotational tillage (CCBRT), a practice that reduces the need for tillage and cultivation through the creation of cover crop mulches, has emerged as an alternative weed management practice in organic cropping systems. In this study, CCBRT systems using cereal rye and triticale grain species are evaluated with organic soybean directly seeded into a rolled cover crop. Cover crop biomass, weed biomass, and soybean yields were evaluated to assess the effects of cereal rye and winter triticale cover crops on weed suppression and yields. From 2016 to 2018, trials were conducted at six locations in Wisconsin, USA, and Southern France. While cover crop biomass did not differ among the cereal grain species tested, the use of cereal rye as the cover crop resulted in higher soybean yields (2.7 t ha−1 vs. 2.2 t ha−1) and greater weed suppression, both at soybean emergence (231 vs. 577 kg ha−1 of weed biomass) and just prior to soybean harvest (1178 vs. 1545 kg ha−1). On four out of six sites, cover crop biomass was lower than the reported optimal (<8000 kg ha−1) needed to suppress weeds throughout soybean season. Environmental conditions, in tandem with agronomic decisions (e.g., seeding dates, cultivar, planters, etc.), influenced the ability of the cover crop to suppress weeds regardless of the species used. In a changing climate, future research should focus on establishing flexible decision support tools based on multi-tactic cover crop management to ensure more consistent results with respect to cover crop growth, weed suppression, and crop yields.
Document filtering boosted by unlabeled data

This paper describes three learning methods for document filtering that use unlabeled data. The proposed methods are based on a committee of the classifiers which are trained on a small set of labeled data and then augmented by a large number of unlabeled data. By taking advantage of unlabeled data, the effective number of labeled data needed is significantly reduced and the filtering accuracy is increased. The use of unlabeled data is important because obtaining labeled data is difficult and time-consuming, while unlabeled data are abundant. For all proposed methods, the experimental results show that the accuracy is improved up to 9.2% with only two-thirds as many labeled data as the method which does not use unlabeled data.
A Comparison of Adaboost and Learn++ Distribution Update Rule

In the AdaBoost formulation from learning new data, if instances of previously unseen instances are introduced. Actually AdaBoost do nothing. AdaBoost should work for incremental learning, but it was made more efficient by modifying the distribution update rule to make the update based on the ensemble decision, not just the previous classifier. The ability of a classifier to take on new information and classes by evolving the classifier without it having to be fully retrained is known as incremental learning. Incremental learning has been successfully applied to many classification problems, where the data is changing and is not all available at once.
Toward a gold standard for benchmarking gene set enrichment analysis

Abstract Motivation Although gene set enrichment analysis has become an integral part of high-throughput gene expression data analysis, the assessment of enrichment methods remains rudimentary and ad hoc. In the absence of suitable gold standards, evaluations are commonly restricted to selected datasets and biological reasoning on the relevance of resulting enriched gene sets. Results We develop an extensible framework for reproducible benchmarking of enrichment methods based on defined criteria for applicability, gene set prioritization and detection of relevant processes. This framework incorporates a curated compendium of 75 expression datasets investigating 42 human diseases. The compendium features microarray and RNA-seq measurements, and each dataset is associated with a precompiled GO/KEGG relevance ranking for the corresponding disease under investigation. We perform a comprehensive assessment of 10 major enrichment methods, identifying significant differences in runtime and applicability to RNA-seq data, fraction of enriched gene sets depending on the null hypothesis tested and recovery of the predefined relevance rankings. We make practical recommendations on how methods originally developed for microarray data can efficiently be applied to RNA-seq data, how to interpret results depending on the type of gene set test conducted and which methods are best suited to effectively prioritize gene sets with high phenotype relevance. Availability http://bioconductor.org/packages/GSEABenchmarkeR Contact ludwig.geistlinger@sph.cuny. edu
Manifestation of a nonclassical Berry phase of an electromagnetic field in atomic Ramsey interference

The Berry phase acquired by an electromagnetic field undergoing an adiabatic and cyclic evolution in phase space is a purely quantum-mechanical effect of the field. However, this phase is usually accompanied by a dynamical contribution and cannot be manifested in any light-beam interference experiment because it is independent of the field state. We here show that such a phase can be produced using an atom coupled to a quantized field and driven by a slowly changing classical field, and it is manifested in atomic Ramsey interference oscillations. We also show how this effect may be applied to one-step implementation of multiqubit geometric phase gates, which is impossible by previous geometric methods. The effects of dissipation and fluctuations in the parameters of the pump field on the Berry phase and visibility of the Ramsey interference fringes are analyzed.
A blueprint of seed desiccation sensitivity in the genome of Castanospermum australe

Most angiosperms produce seeds that are desiccated on dispersal with the ability to retain viability in storage facilities for prolonged periods. However, some species produce desiccation sensitive seeds which rapidly lose viability in storage, precluding ex situ conservation. Current consensus is that desiccation sensitive seeds either lack or do not express mechanisms necessary for the acquisition of desiccation tolerance. We sequenced the genome of Castanospermum australe, a legume species producing desiccation sensitive seeds, and characterized its seed developmental physiology and - transcriptomes. C. australe has a low rate of evolution, likely due to its perennial life-cycle and long generation times. The genome is syntenic with itself, with several orthologs of genes from desiccation tolerant legume seeds, from gamma whole-genome duplication events being retained. Changes in gene expression during development of C. australe seeds, as compared to desiccation tolerant Medicago truncatula seeds, suggest they remain metabolically active, prepared for immediate germination. Our data indicates that the phenotype of C. australe seeds arose through few changes in specific signalling pathways, precluding or bypassing activation of mechanisms necessary for acquisition of desiccation tolerance. Such changes have been perpetuated as the habitat in which dispersal occurs is favourable for prompt germination.
Prognostic and predictive factors for lung cancer

Lung cancer is the most common cancer worldwide. In 2008, the number of incident cases was estimated to be around 1.6 million (13% of all incident cancers). Mortality is high with 1.4 million of deaths the same year (18% of all deaths from cancer) (www.globocan.iarc.fr). Overall, survival rate at 5 years is <20% but heterogeneity is important and the search for prognostic factors has led to the publication of an impressive number of papers. However, due to the design and often retrospective nature of prognostic factors studies, few of these factors can really be used in routine care to guide management and to determine prognosis. More recently, with the development of so-called targeted therapies, more and more attention has been paid to the identification of predictive factors that might be better tools to guide therapy. In the present paper, we will review how prognostic and predictive factors are different and how they can be identified. We will also present some well-known and important factors although we will not attempt at all to make an exhaustive report. This is virtually impossible; in 2002, Brundage et al . [1], in a systematic overview of prognostic factors for non-small cell lung cancer, identified 887 articles published during a decade and more than 150 possible prognostic factors for non-small cell lung cancer. A prognostic factor is generally defined as a factor, measured before treatment, that has an impact on a patient′s outcome “independently” of received treatment or of the general class of treatment. Populations of patients used for prognostic factors identification may be very broad (from resected stage I patients to stage IV patients scheduled to receive chemotherapy) or more specific such as patients treated with radical radiotherapy or stage III patients. Outcome is most often defined as overall survival but …
genomalicious: serving up a smorgasbord of R functions for performing and teaching population genomic analyses

Turning SNP data into biologically meaningful results requires considerable computational acrobatics, including importing, exporting, and manipulating data among different analytical packages and programming environments, and finding ways to visualise results for data exploration and presentation. I present GENOMALICIOUS, an R package designed to provide a selection of functions for population genomicists to simply, intuitively, and flexibly, guide SNP data through their analytical pipelines, within and outside R. At the core of the GENOMALICIOUS is workflow is getting genomic data into a data.table object. This provides a useful way of storing large amounts of data in an intuitive format that can be easily manipulated using methods unique to this object class. Researchers using pooled allele frequencies, or individually sequenced genotypes, are sure to find functions that accommodate their tastes in GENOMALICIOUS. Moreover, the simplicity and accessibility of pipelines in GENOMALICIOUS may serve as a useful tool for teaching basic population genetics and population genomics in an R environment. The source code and a series of tutorials for this package are freely available on GitHub.
Pharmacokinetics and Pharmacodynamics of Morroniside: A Review

Morroniside belongs to a group of iridoid glycosides and is the primary active component of Cornus officinalis Sieb. et Zucc. This species is a rich source of iridoid glycosides and has been used as a traditional Chinese medicinal herbs for centuries. In this review, we discuss the pharmacokinetics and pharmacodynamics of morroniside. Morroniside is quickly absorbed and metabolized and is widely distributed throughout the body. It also exerts various pharmacological effects. Numerous pharmacological studies have indicated that morroniside plays a role in protecting the nervous system, treating osteoarthritis, inhibiting platelet aggregation, preventing diabetic angiopathies and renal damage, and reducing bone resorption, among others. Future research need to be conducted in support of the development of morroniside as a potential drug.
Evolution of satellite plasmids can stabilize the maintenance of newly acquired accessory genes in bacteria

Plasmids play a principal role in the spread of antibiotic resistance and other traits by horizontal gene transfer in bacteria. However, newly acquired plasmids generally impose a fitness burden on a cell, and they are lost from a population rapidly if there is not selection to maintain a unique function encoded on the plasmid. Mutations that ameliorate this fitness cost can sometimes eventually stabilize a plasmid in a new host, but they typically do so by inactivating some of its novel accessory genes. In this study, we identified an additional evolutionary pathway that can prolong the maintenance of newly acquired genes encoded on a plasmid. We discovered that propagation of an RSF1010-based IncQ plasmid in Escherichia coli often generated ‘satellite plasmids’ with spontaneous deletions of accessory genes and genes required for plasmid replication. These smaller plasmid variants are nonautonomous genetic parasites. Their presence in a cell drives down the copy number of full-length plasmids, which reduces the burden from the accessory genes without eliminating them entirely. The evolution of satellite plasmids may be favored relative to other plasmid fates because they give a more immediate fitness advantage to a cell’s progeny and because the organization of IncQ plasmids makes them particularly prone to certain deletions during replication. Satellite plasmids also evolved in Snodgrassella alvi colonizing the honey bee gut, suggesting that this mechanism may broadly contribute to the importance of IncQ plasmids as agents of bacterial gene transfer in nature. Significance Statement Plasmids are multicopy DNA elements found in bacteria that replicate independently of a cell’s chromosome. The spread of plasmids carrying antibiotic-resistance genes to new bacterial pathogens is a challenge for treating life-threatening infections. Often plasmids or their accessory genes encoding unique functions are lost soon after transfer into a new cell because they impose a fitness burden. We report that a family of transmissible plasmids can rapidly evolve ‘satellite plasmids’ that replicate as genetic parasites of the original plasmid. Satellite plasmid formation reduces the burden from the newly acquired genes, which may enable them to survive intact for longer after transfer into a new cell and thereby contribute to the spread of antibiotic resistance and other traits within bacterial populations.
Inferring the collective dynamics of neuronal populations from single-trial spike trains using mechanistic models

Multi-neuronal spike-train data recorded in vivo often exhibit rich dynamics as well as considerable variability across cells and repetitions of identical experimental conditions (trials). Efforts to characterize and predict the population dynamics and the contributions of individual neurons require model-based tools. Abstract statistical models allow for principled parameter estimation and model selection, but possess only limited interpretive power because they typically do not incorporate prior biophysical constraints. Here we present a statistically principled approach based on a population of doubly-stochastic integrate-and-fire neurons, taking into account basic biophysics. This model class comprises an idealized description for the dynamics of the neuronal membrane voltage in response to fast independent and slower shared input fluctuations. To efficiently estimate the model parameters and compare different model variants we compute the likelihood of observed single-trail spike trains by leveraging analytical methods for spiking neuron models combined with inference techniques for hidden Markov models. This allows us to reconstruct the shared input variations, classify their dynamics, obtain precise spike rate estimates, and quantify how individual neurons couple to the low-dimensional overall population dynamics, all from a single trial. Extensive evaluations based on simulated data show that our method correctly identifies the dynamics of the shared input process and accurately estimates the model parameters. Validations on ground truth recordings of neurons in vitro demonstrate that our approach successfully reconstructs the dynamics of hidden inputs and yields improved fits compared to a typical phenomenological model. Finally, we apply the method to a neuronal population recorded in vivo, for which we assess the contributions of individual neurons to the overall spiking dynamics. Altogether, our work provides statistical inference tools for a class of reasonably constrained, mechanistic models and demonstrates the benefits of this approach to analyze measured spike train data.
VLSI design of a robotic controller for a dual axis manipulator element

The overall architecture of the dual-axis manipulator element and its importance as a fundamental building block of an advanced telerobotic system are described. The design, implementation, and testing of a custom VLSI chip that provides multiaxis sensor interfacing and signal conditioning are discussed. The current chip design includes: two quadrature phase optical decoders with a 16-bit resolution, three pulse-width-modulated waveform generators with 11-bit precision, and a digital input/output microprocessor interface. Each of these components have been laid out with VLSI CAD (computer-aided design) tools and have been extensively computer simulated. A 64-pin prototype chip has been fabricated in 3- mu m SCMOS technology with an expected clock rate of 10 MHz for the pulse-width modulated waveform generators and 8 MHz for the optical decoders. The custom chip replaces over 125 standard SSI/MSI CMOS and TTL services and achieves a bit resolution far greater than what is currently available with off-the-shelf components. <<ETX>>
The Fluid Membrane determines Mechanics of Red Blood Cell Extracellular Vesicles and is Softened in Hereditary Spherocytosis

Extracellular vesicles (EVs) are widely studied regarding their role in cell-to-cell communication and disease, as well as for applications as biomarker or drug delivery vehicle. EVs contain both membrane and intraluminal proteins, affecting their structural properties and thereby likely their functioning. Here, we use atomic force microscopy for the mechanical characterization of red blood cell (RBC) EVs from healthy individuals as well as from a patient with hereditary spherocytosis (HS) due to ankyrin deficiency. We show that the EVs are packed with proteins, yet their response to indentation is similar to that of a fluid lipid vesicle lacking proteins. The bending modulus of RBC EVs of healthy donors is ~15 kbT, agreeing well with the bending modulus of the RBC membrane. Surprisingly, whereas RBCs become more rigid in HS, the excreted vesicles of a patient with this blood disorder have a significantly (~50%) lower bending modulus than donor EVs. These results shed new light on the mechanism and effects of EV budding and may underlie the reported increase in vesiculation and stiffening of RBCs in hereditary spherocytosis patients.