Miracle-dz/UniFAR-FTUs huggingface dataset:
Redundancy in Anaerobic Digestion Microbiomes during Disturbances by the Antibiotic Monensin

ABSTRACT The antibiotic monensin is fed to dairy cows to increase milk production efficiency. A fraction of this monensin is excreted into the cow manure. Previous studies have found that cow manure containing monensin can negatively impact the performance of anaerobic digesters, especially upon first introduction. Few studies have examined whether the anaerobic digester microbiome can adapt to monensin during the operating time. Here, we conducted a long-term time series study of four lab-scale anaerobic digesters fed with cow manure. We examined changes in both the microbiome composition and function of the anaerobic digesters when subjected to the dairy antibiotic monensin. In our digesters, monensin was not rapidly degraded under anaerobic conditions. The two anaerobic digesters that were subjected to manure from monensin feed-dosed cows exhibited relatively small changes in microbiome composition and function due to relatively low monensin concentrations. At higher concentrations of monensin, which we dosed directly to control manure (from dairy cows without monensin), we observed major changes in the microbiome composition and function of two anaerobic digesters. A rapid introduction of monensin to one of these anaerobic digesters led to the impairment of methane production. Conversely, more gradual additions of the same concentrations of monensin to the other anaerobic digester led to the adaptation of the anaerobic digester microbiomes to the relatively high monensin concentrations. A member of the candidate OP11 (Microgenomates) phylum arose in this anaerobic digester and appeared to be redundant with certain Bacteroidetes phylum members, which previously were dominating. IMPORTANCE Monensin is a common antibiotic given to dairy cows in the United States and is partly excreted with dairy manure. An improved understanding of how monensin affects the anaerobic digester microbiome composition and function is important to prevent process failure for farm-based anaerobic digesters. This time series study demonstrates how anaerobic digester microbiomes are inert to low monensin concentrations and can adapt to relatively high monensin concentrations by redundancy in an already existing population. Therefore, our work provides further insight into the importance of microbiome redundancy in maintaining the stability of anaerobic digesters.
Phase-based learning for micro-baseline depth estimation

Methods designed for traditional stereo matching problem are not suitable for micro-baseline stereo problem. In this paper, a novel phase-based learning framework is proposed dedicated to this problem. The inspiration comes from the relationship between phase in frequency domain and shifts in space domain. Steerable pyramid decomposition is used to compute the phase difference of micro-baseline stereo inputs, and learning based methods are adopted to determine disparity from phase difference patch. The proposed framework is a combination of domain transformation and machine learning, which exploits neighbor gradient information as well as data-driven benefits. Experimental results show that the combination effectively reduces the inherent error of phase-based methods, and our innovative framework outperforms traditional stereo matching methods.
Radiometric Calibration for Internet Photo Collections

Radiometrically calibrating the images from Internet photo collections brings photometric analysis from lab data to big image data in the wild, but conventional calibration methods cannot be directly applied to such image data. This paper presents a method to jointly perform radiometric calibration for a set of images in an Internet photo collection. By incorporating the consistency of scene reflectance for corresponding pixels in multiple images, the proposed method estimates radiometric response functions of all the images using a rank minimization framework. Our calibration aligns all response functions in an image set up to the same exponential ambiguity in a robust manner. Quantitative results using both synthetic and real data show the effectiveness of the proposed method.
IFT trains in different stages of assembly queue at the ciliary base for consecutive release into the cilium

Intraflagellar transport (IFT) trains, multimegadalton assemblies of IFT proteins and motors, traffic proteins in cilia. To study how trains assemble, we employed fluorescence protein-tagged IFT proteins in Chlamydomonas reinhardtii. IFT-A and motor proteins are recruited from the cell body to the basal body pool, assembled into trains, move through the cilium, and disperse back into the cell body. In contrast to this ‘open’ system, IFT-B proteins from retrograde trains reenter the pool and a portion is reused directly in anterograde trains indicating a ‘semi-open’ system. Similar IFT systems were also observed in Tetrahymena thermophila and IMCD3 cells. FRAP analysis indicated that IFT proteins and motors of a given train are sequentially recruited to the basal bodies. IFT dynein and tubulin cargoes are loaded briefly before the trains depart. We conclude that the pool contains IFT trains in multiple stages of assembly queuing for successive release into the cilium upon completion. DOI: http://dx.doi. org/10.7554/eLife.26609. 001
R&D Investments in the Presence of Knowledge Spillover and Debt Financing: Can Risk Shifting Cure Free Riding?

In an industry with knowledge spillover and debt financing, equilibrium investments in research and development (R&D) projects are subject to three economic forces. First, knowledge spillover among firms enables free dissemination of new technologies and produces investment synergies. Second, knowledge spillover also causes free riding: in equilibrium, firms underinvest in R&D expecting to benefit from investments by others. Third, debt financing creates incentive for risk shifting: equity holders overinvest in riskier R&D projects. We study how interactions among these forces affect a firm’s investment decisions and equilibrium industry outcomes using a three-stage game between two firms and the external debt market. We characterize subgame perfect, Pareto-dominant equilibria and show that for some parameter choices, free riding and risk shifting cancel each other in the decisions of individual firms, resulting in the first-best investments. Interestingly, for some cases, the equilibrium with first-best .
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors

We show that Entropy-SGD (Chaudhari et al., 2017), when viewed as a learning algorithm, optimizes a PAC-Bayes bound on the risk of a Gibbs (posterior) classifier, i.e., a randomized classifier obtained by a risk-sensitive perturbation of the weights of a learned classifier. Entropy-SGD works by optimizing the bound's prior, violating the hypothesis of the PAC-Bayes theorem that the prior is chosen independently of the data. Indeed, available implementations of Entropy-SGD rapidly obtain zero training error on random labels and the same holds of the Gibbs posterior. In order to obtain a valid generalization bound, we rely on a result showing that data-dependent priors obtained by stochastic gradient Langevin dynamics (SGLD) yield valid PAC-Bayes bounds provided the target distribution of SGLD is {\epsilon}-differentially private. We observe that test error on MNIST and CIFAR10 falls within the (empirically nonvacuous) risk bounds computed under the assumption that SGLD reaches stationarity. In particular, Entropy-SGLD can be configured to yield relatively tight generalization bounds and still fit real labels, although these same settings do not obtain state-of-the-art performance.
The association between the TP53 Arg72Pro polymorphism and colorectal cancer: An updated meta-analysis based on 32 studies

Several previous studies evaluated the association between the Arg72Pro (rs1042522) polymorphism in the TP53 tumor suppressor gene and colorectal cancer (CRC). However, the results are conflicting. This meta-analysis aimed to shed new light on the precise association between TP53 variants and CRC. We analyzed 32 published case-control studies involving 8,586 cases and 10,275 controls using crude odd ratios (ORs) with 95% confidence intervals (CIs). The meta-analysis was performed using a fixed-effect or random-effects model, as appropriate. We found that the TP53 Arg72Pro polymorphism was not significantly associated with CRC risk in the overall population. However, subgroup analysis based on ethnicity revealed an increased risk of CRC among Asians (CC vs. GC+GG: OR=1.22, 95% CI: 1.02-1.45), and similar results were found for rectal cancer (CC vs. GC+GG: OR=1.34, 95% CI: 1.120-1.62). These results suggest that the TP53 Arg72Pro polymorphism CC genotype may contribute to an increased risk of CRC, especially for rectal cancer and among Asians.
The estimation accuracy for ultrasonic Doppler velocity distribution of arterial blood flow based on coherent plane wave compounding

The velocity distribution of arterial blood flow is an important parameter to evaluate the physiological and pathological conditions of human body. In the ultrasonic detection, the traditional focus mode has low frame rate in linear scan, poor detected accuracy outside the focus points, difficulty of quick estimation in two-dimensional area and some other limitations, is restrainedly used in clinic. Plane wave doesn't make beam forming in emission, so the frame rate can reach 20 kHz. It can obtain the two-dimensional velocity distribution covered by the transducer at one emission and reception. And the detected region that is penetrated by coherent plane wave compound with different inclination angle is helpful to improve the estimated accuracy of blood flow velocity distribution (BFVD). However, the key factors, inclination angle interval and compound times, are lack of systematic investigation in terms of the estimated accuracy of BFVD. In present study, an intensive research on this issue based on Field II platform is made. Plane wave imaging mode, coherent plane wave compound, autocorrelation estimation and other methods are used to deal with pulse-echo radio frequency signals to calculate the BFVD. In the simulation experiment, transducer emits plane waves of different inclination angle, then, the velocity is estimated respectively from the signals combined coherently by 3, 5, 7 and 9 times. The results show that the normalized root mean square errors (NRMSE) are 0.24, 0.30, 0.35 and 0.36 when the inclination angle is set to ± 0.5°, ± 7°, ± 14° and ± 21° at the compound times of 3. The accuracy of the estimated results has an opposite trend with the increase of inclination angle interval. It also shows that the NRMSE are 0.24, 0.23, 0.22 and 0.22 when using 3, 5, 7 and 9 times to compound at a fixed angle interval of ± 0.5°. The accuracy of the estimation results is related slightly to the number of compound.
The physical dimensions of amyloid aggregates control their infective potential as prion particles

Transmissible amyloid particles called prions are associated with infectious prion diseases in mammals and inherited phenotypes in yeast. All amyloid aggregates can give rise to potentially infectious seeds that accelerate their growth. Why some amyloid seeds are highly infectious prion particles while others are less infectious or even inert, is currently not understood. To address this question, we analyzed the suprastructure and dimensions of synthetic amyloid fibrils assembled from the yeast (Saccharomyces cerevisiae) prion protein Sup35NM. We then quantified the ability of these particles to induce the [PSI+] prion phenotype in cells. Our results show a striking relationship between the length distribution of the amyloid fibrils and their ability to induce the heritable [PSI+] prion phenotype. Using a simple particle size threshold model to describe transfection activity, we explain how dimensions of amyloid fibrils are able to modulate their infectious potential as prions.
SAFE: Spectral Evolution Analysis Feature Extraction for Non-Stationary Time Series Prediction

This paper presents a practical approach for detecting non-stationarity in time series prediction. This method is called SAFE and works by monitoring the evolution of the spectral contents of time series through a distance function. This method is designed to work in combination with state-of-the-art machine learning methods in real time by informing the online predictors to perform necessary adaptation when a non-stationarity presents. We also propose an algorithm to proportionally include some past data in the adaption process to overcome the Catastrophic Forgetting problem. To validate our hypothesis and test the effectiveness of our approach, we present comprehensive experiments in different elements of the approach involving artificial and real-world datasets. The experiments show that the proposed method is able to significantly save computational resources in term of processor or GPU cycles while maintaining high prediction performances.
Clinical Evaluation Comparing the Efficacy of Aquacel® Ag Hydrofiber® Dressing Versus Petrolatum Gauze With Antibiotic Ointment in Partial-Thickness Burns in a Pediatric Burn Center

We conducted this Institutional Review Board-approved retrospective study to compare Aquacel® Ag Hydrofiber® dressing (Aquacel Ag) to a standard dressing for the treatment of partial thickness burns in children. We used the St. Christopher’s Hospital burn center registry to identify 20 pediatric patients who had sustained partial thickness burns over a 10-month period. Ten of these patients had been treated with Aquacel Ag Hydrofiber dressing and 10 were treated with conventional Xeroflo gauze with Bacitracin Zinc ointment, the institutional standard of care for nonoperative partial-thickness burn wounds. Inclusion criteria included anyone with partial-thickness burns below the age of 18 years and in excellent baseline health. Exclusion criteria included inhalation injury, presence of full-thickness burns necessitating surgical debridement, cellulitic, or infected wounds, and percentage total body surface area involvement greater than 40%. Outcomes measured for the Aquacel Ag versus the Xeroflo gauze with Bacitracin Zinc ointment group included hospital length of stay (2.4 vs. 9.6 days), total number of in-house dressing changes (2.7 vs. 17.1), pain on a 10-point scale associated with dressing changes (6.4 vs. 8.2), total number of intravenous narcotic administrations (2.3 vs. 14.4), nursing time adjusted for percentage total body surface area (1.9 vs. 3.5 min), time to wound reepithelialization (10.3 vs. 16.3 days), and patient primary caregiver satisfaction score using a 4-point scale—with four delineating maximum satisfaction (3.8 vs. 1.8). Aquacel Ag proved to be a safe and effective means of treating partial thickness burns with a significant reduction in nursing time and patient pain involved with dressing changes.
DOES THE DATA RESOLUTION/ORIGIN MATTER? SATELLITE, AIRBORNE AND UAV IMAGERY TO TACKLE PLANT INVASIONS

Abstract. Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.
Thinking Aloud with a Tutoring Robot to Enhance Learning

Thinking aloud, while requiring extra mental effort, is a metacognitive technique that helps students navigate through complex problem-solving tasks. Social robots, bearing embodied immediacy that fosters engaging and compliant interactions, are a unique platform to deliver problem-solving support such as thinking aloud to young learners. In this work, we explore the effects of a robot platform and the think-aloud strategy on learning outcomes in the context of a one-on-one tutoring interaction. Results from a 2x2 between-subjects study (n = 52) indicate that both the robot platform and use of the think-aloud strategy promoted learning gains for children. In particular, the robot platform effectively enhanced immediate learning gains, measured right after the tutoring session, while the think-aloud strategy improved persistent gains as measured approximately one week after the interaction. Moreover, our results show that a social robot strengthened students’ engagement and compliance with the think-aloud support while they performed cognitively demanding tasks. Our work indicates that robots can support metacognitive strategy use to effectively enhance learning and contributes to the growing body of research demonstrating the value of social robots in novel educational settings.
Probing dynamical gravity with the polarization of continuous gravitational waves

The direct detection of gravitational waves provides the opportunity to measure fundamental aspects of gravity which have never been directly probed before, including the polarization of gravitational waves. In the context of searches for continuous waves from known pulsars, we present novel methods to detect signals of any polarization content, measure the modes present and place upper limits on the amplitude of nontensorial components. This will allow us to obtain new model-independent, dynamical constraints on deviations from general relativity. We test this framework on multiple potential sources using simulated data from three advanced-era detectors at design sensitivity. We find that signals of any polarization will become detectable and distinguishable for characteristic strains h ≳ 3×10^(−27)√1 yr/T, for an observation time T. We also find that our ability to detect nontensorial components depends only on the power present in those modes, irrespective of the strength of the tensorial strain.
Differences in Copper Absorption and Accumulation between Copper-Exclusion and Copper-Enrichment Plants: A Comparison of Structure and Physiological Responses

Differences in copper (Cu) absorption and transport, physiological responses and structural characteristics between two types of Cu-resistant plants, Oenothera glazioviana (Cu-exclusion type) and Elsholtzia haichowensis (Cu-enrichment type), were investigated in the present study. The results indicated the following: (1) After 50 μM Cu treatment, the Cu ratio in the xylem vessels of E. haichowensis increased by 60%. A Cu adsorption experiment indicated that O. glazioviana exhibited greater resistance to Cu, and Cu absorption and the shoot/root ratio of Cu were significantly lower in O. glazioviana than in E. haichowensis. (2) An analysis of the endogenous abscisic acid (ABA) variance and exogenous ABA treatment demonstrated that the ABA levels of both plants did not differ; exogenous ABA treatment clearly reduced Cu accumulation in both plants. (3) The leaf stomatal density of O. glazioviana was significantly less than that of E. haichowensis. Guard cells in E. haichowensis plants were covered with a thick cuticle layer, the epidermal hair was more numerous and longer, and the number of xylem conduits in the root was small. (4) The transpiration rate and the stomatal conductance of O. glazioviana were both significantly lower than those of E. haichowensis, regardless of whether the plants were treated with Cu. Taken together, these results indicate that the differences in the structural characteristics between these two plant species, particularly in the characteristics related to plant transpiration, are important factors that govern whether plants acquire or exclude Cu.
Predictors of Pharmacotherapy Response in Generalized Anxiety Disorder: A Systematic Review

Background Pharmacotherapy for generalized anxiety disorder (GAD) may be effective in reducing symptoms in the majority of patients. The study of moderators and predictors of treatment response may help clinicians both to select appropriate interventions to maximize the probability of response and to inform the general prognosis. Methods A systematic literature search of electronic databases, selected authors, and reference lists was used to identify articles that reported trials of drug monotherapy in GAD. Data on predictors and moderators were extracted. Quality of evidence was determined by the presence of a priori hypotheses, number of variables investigated, adequate quality of the measurement, and use of interaction-effects testing. Results From the 98 articles meeting inclusion criteria, 24 reported a total of 22 factors associated with treatment response. The reported results were heterogeneous, ranging over sociodemographic, clinical, comorbidity, genetic, and functional-imaging studies. Major depressive symptoms were found to moderate treatment outcome in favor of antidepressants versus benzodiazepines. Neuroticism, previous treatment, genetic polymorphisms (including serotonin receptor gene 2A), and functional activation of the anterior cingulate cortex and amygdala were identified as potential predictors of treatment response. Conclusions Correlates of poor emotion regulation predicted poor treatment response, but subclinical depression was the only variable capable of informing treatment selection in this review. Future research should focus on further exploring the value of depression as a moderator and on a narrower list of potential genetic, brain-imaging, and temperament predictors of response to pharmacotherapy in GAD.