Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization and complete genome sequence of Privateer, a highly prolate Proteus mirabilis podophage

The Gram-negative bacterium Proteus mirabilis causes a large proportion of catheter-associated urinary tract infections, which are among the world’s most common nosocomial infections. Here, we characterize P. mirabilis bacteriophage Privateer, a prolate podophage of the C3 morphotype isolated from Texas wastewater treatment plant activated sludge. Basic characterization assays demonstrated Privateer has a latent period of ~40 min and average burst size around 140. In the 90.7 kb Privateer genome, 43 functions were assigned for the 144 predicted protein-coding genes. Genes encoding DNA replication proteins, DNA modification proteins, four tRNAs, lysis proteins, and structural proteins were identified. Cesium-gradient purified Privateer particles analyzed via LC-MS/MS verified the presence of several predicted structural proteins, including a longer, minor capsid protein apparently produced by translational frameshift. Comparative analysis demonstrated Privateer shares 83% nucleotide similarity with Cronobacter phage vB_CsaP_009, but low nucleotide similarity with other known phages. Predicted structural proteins in Privateer appear to have evolutionary relationships with other prolate podophages, in particular the Kuraviruses
Arousal modulates the motor interference effect stimulated by pictures of threatening animals

Previous research related to the motor interference effect from dangerous objects indicated that delayed responses to dangerous objects were associated with more positive parietal P3 amplitudes, suggesting that great attentional resources were allocated to evaluate the level of danger (i.e., negative valence). However, arousal covaried with valence in this research. Together with previous studies in which the P3 amplitude was found to be increased along with a higher arousal level in the parietal lobe, we raised the issue that more positive parietal P3 amplitudes might also be affected by a high arousal level. To clarify whether valence or arousal impacted the motor interference effect, this study used a motor priming paradigm mixed with a Go/NoGo task and manipulated the valence (negative, neutral and positive) and arousal (medium and high) of target stimuli. Analysis of the behavioral results identified a significant motor interference effect (longer reaction times (RTs) in the negative valence condition than in the neutral valence condition) at the medium arousal level and an increased effect size (increment of RT difference) at the high arousal level. The results indicated that negative valence stimuli may interfere with the prime elicited motor preparation more strongly at the high arousal level than at the medium arousal level. The ERP results identified larger centroparietal P3 amplitudes for the negative valence condition than for the neutral valence condition at a high arousal level. However, the inverse result, i.e., lower centroparietal P3 amplitudes for the negative valence condition than for the neutral valence condition, was observed at a medium arousal level. The ERP results further indicated that the effect size of the behavioral motor interference effect increased because subjects are more sensitive to the negative valence stimuli at the high arousal level than at the medium arousal level. Furthermore, the motor interference effect is related to the negative valence rather than emotionality of the target stimuli because different result patterns emerged between the positive and negative valence conditions. Detailed processes underlying the interaction between valence and arousal effects are discussed.
Molecular identification and larval morphology of spionid polychaetes (Annelida, Spionidae) from northeastern Japan

Abstract Planktonic larvae of spionid polychaetes are among the most common and abundant group in coastal meroplankton worldwide. The present study reports the morphology of spionid larvae collected mainly from coastal waters of northeastern Japan that were identified by the comparison of adult and larval 18S and 16S rRNA gene sequences. The molecular analysis effectively discriminated the species. Adult sequences of 48 species from 14 genera (Aonides Claparède, 1864; Boccardia Carazzi, 1893; Boccardiella Blake & Kudenov, 1978; Dipolydora Verrill, 1881; Laonice Malmgren, 1867; Malacoceros Quatrefages, 1843; Paraprionospio Caullery, 1914; Polydora Bosc, 1802; Prionospio Malmgren, 1867; Pseudopolydora Czerniavsky, 1881; Rhynchospio Hartman, 1936; Scolelepis Blainville, 1828; Spio Fabricius, 1785; Spiophanes Grube, 1860) and larval sequences of 41 species from 14 genera (Aonides; Boccardia; Boccardiella; Dipolydora; Laonice; Paraprionospio; Poecilochaetus Claparède in Ehlers, 1875; Polydora; Prionospio; Pseudopolydora; Rhynchospio; Scolelepis; Spio; Spiophanes) of spionid polychaetes were obtained; sequences of 27 of these species matched between adults and larvae. Morphology of the larvae was generally species‐specific, and larvae from the same genus mostly shared morphological features, with some exceptions. Color and number of eyes, overall body shape, and type and arrangement of pigmentation are the most obvious differences between genera or species. The morphological information on spionid larvae provided in this study contributes to species or genus level larval identification of this taxon in the studied area. Identification keys to genera and species of planktonic spionid larvae in northeastern Japan are provided. The preliminary results of the molecular phylogeny of the family Spionidae using 18S and 16S rRNA gene regions are also provided.
The potential for income improvement and biodiversity conservation via specialty coffee in Ethiopia

The specialty coffee sector represents opportunities for coffee farmers and other actors due to increased value within the supply chain, driven by elevated consumer purchase prices. We investigated these relationships up to the export stage, as well as the potential for specialty coffee to improve stakeholder participation in biodiversity conservation. Household data was collected from a sample of 272 coffee farmers belonging to five primary cooperatives, in the heavily forested area of Yayu, in the Illubabor administrative zone of Oromia regional state in south-western Ethiopia, for the 2017/2018 harvest season. Qualitative and quantitative data, gathered between 2015 and 2019, from focus group discussions, was used to supplement the survey and to explain the empirical findings. We show that the income from coffee (and thus household income) can be increased, in some cases substantially, via participation in the specialty coffee market. The unit price for coffee was much higher than standard market prices and those including certification premiums. Whilst quality is a key factor for specialty coffee, income increases via the specialty market are caveat bound. In particular, there is a critical requirement for efficient and effective cooperative management, and we provide suggestions for improvements. In the long-term, more focus is needed to increase the financial and human capacities of Ethiopian coffee cooperatives, to make them more effective partners in the specialty coffee value chain. The high conversion rates from harvested to clean exportable specialty coffee (8:1, or higher) is identified as a major constraint on profitability. We show that specialty coffee can bring about positive environmental benefits. Elevating coffee prices and farm profitability to bring household income levels to around or above the global poverty line may ensure the continuation of forest coffee production, and thus the retention of forest. The increases in income via specialty coffee production, reported in the study, were achieved without increasing land use or the application of environmentally costly inputs. Moreover, analysis of satellite data shows that a large proportion of the coffee farms surveyed retain a level of forest cover and quality approaching primary (undisturbed) forest, and that the coffee production area at Yayu has not experienced any significant deforestation (since 2000). We recommend that coffee premiums linked to environmental benefit should demonstrate clearly defined and appropriate metrics, as we have demonstrated here for forest (canopy) quality and coverage (area).
The Effect of Subsequent Pregnancy on Prognosis in Young Breast Cancer Patients (≤35 Years Old) According to Hormone Receptor Status

Purpose We aimed to examine the effect of pregnancy on prognosis in young breast cancer (YBC) patients with hormone receptor (HR) positive after surgery and the safety of interrupting endocrine therapy (ET). Methods A retrospective cohort study was performed in patients who became pregnant after BC surgery under the age of 35 and were matched (1:4) to nonpregnant patients from 2006 to 2014. The primary endpoints were disease-free survival (DFS) and overall survival (OS) in HR-positive BC patients, and the secondary endpoints were DFS and OS in HR-negative BC patients and the whole population. Subgroup analyses included the DFS of patients who became pregnant within 5 years after surgery and DFS according to the ET interval time (≤ 30 months v > 30 months) in the pregnant group. Results A total of 1323 YBC patients were collected in our study, which included 68 pregnant patients and 264 matched nonpregnant patients. There were no statistically significant differences in DFS and OS among HR-positive patients (P=0.657, P=0.250, respectively) and the whole population (P=0.058, P=0.152, respectively). A BC pregnancy interval ≤ 5 years showed a better DFS (P=0.042), and an ET interval ≤ 30 months had a worse DFS (P = 0.01). Conclusion This study did not observe a worse prognosis in patients with HR-positive disease who became pregnant after BC surgery, and an ET interval less than 30 months in pregnant patients led to a worse outcome. Patients were able to become pregnant within 5 years after surgery.
Real-world management of hyperphosphataemia with sucroferric oxyhydroxide: the VELREAL multicentre study

Abstract Background The efficacy and safety of sucroferric oxyhydroxide (SO) have been reported in clinical trials. However, real-life data are scarce. This study presents data on the use, efficacy and safety of SO in real clinical practice. Methods We performed a retrospective multicentre study, without any influence on the prescription decisions, that included 220 patients from 11 Spanish centres. Demographic, treatment, analytical and nutritional parameters and adherence, side effects and dropout rates were collected during 6 months. Results SO was initiated due to inadequate control of serum phosphate (P) in 70% of participants and in 24.5% to reduce the number of tablets. Monotherapy with SO increased from 44% to 74.1%, with a reduction in the average daily number of sachets/tablets from six to two. Serum P decreased by 20% (4.6 ± 1.2 versus 5.8 ± 1.3 mg/dL; P < 0.001), with a significant reduction in intact parathyroid hormone levels (P < 0.01). The percentage of patients with adequate serum P control at threshold levels of 5 and 4.5 mg/dL increased by 45.4% and 35.9%, respectively. Serum ferritin was not modified, while the transferrin saturation index increased significantly (P = 0.04). Serum albumin and normalized protein catabolic rate, when normalized by serum P, increased, averaging 37% and 39%, respectively (P < 0.001). Adherent patients increased from 28.2% to 52.7%. Adverse effects were reported by 14.1% of participants, with abandonment of treatment in 9.5%. Conclusions The use of SO in real-life results in better control of serum P, a reduction in the number of tablets and an improvement in therapeutic adherence. In addition, it may be beneficial with regards to secondary hyperparathyroidism and nutritional status.
Growth Trajectories of HIV Exposed and HIV Unexposed Infants. A Prospective Study in Gweru, Zimbabwe

Background: With the increasing HIV seroprevalence among women of childbearing age in sub-Saharan Africa, limited data on growth outcomes of HIV exposed infants under current policies of universal maternal antiretroviral therapy exist. Methods: The longitudinal growth patterns of 114 HIV exposed and unexposed infants were assessed and compared. The prevalence and factors associated with malnutrition were established. Infants under prevention of mother to child transmission care were recruited at 6 weeks post-delivery as were their HIV unexposed counterparts. Weight and length measurements were recorded at birth, 6 and 16 weeks postpartum. Results: HIV vertical transmission rate was 8.8%. HIV exposed infants had significantly lower mean birth weights compared to HIV unexposed infants (2.9 ± 0.3; 3.2 ± 0.5; P < .001) respectively. Mean weight/length-for-age z-scores for HIV exposed, uninfected (HEU) infants were significantly below those of the HIV unexposed infants during follow up. By 6 weeks of age, 28.5% of HEU infants were malnourished while no malnutrition was evident in HIV unexposed infants. A gestational age <37 weeks (OR: 3.83; 95% CI: 1.03-14.30; P = .045) and HIV exposure (OR: 1.62; 95% CI: 0.17-15.73; P = .017) substantially increased the risk of stunting. Conclusion: Growth deficits were witnessed in HIV exposed infants compared to HIV unexposed infants. There is need for early nutritional monitoring and support among HIV exposed infants.
Fertilizer Use and Wheat Yield in Central and Eastern European Countries from 1986 to 2005 and Its Implication for Developing Sustainable Fertilizer Management Practices

Economic and political challenges impact agricultural practices, production efficiency, and crop yields. We hypothesize that increased conversion efficiency of fertilizer to crop yield resulted from changes in fertilizer management in Central and Eastern European countries. Efficient nutrient management depends on fertilizer applied, management practices, and weather, which impact uptake, utilization efficiency, and crop yield. Trends in fertilizer consumption and wheat yields from 1986 to 2005 were studied for five countries. There were significant differences in yield gap, defined as the difference between potential and actual yields. Partial factor productivity of applied nitrogen fertilizer (N) is calculated from real and modified indices. A predictive metric is introduced based on the quantity of unworked, or nonproductive, N (Nuw). Sustainable cropping practices reduce Nuw and yield gap. Improved knowledge of crop responses to balanced plant nutrition at the country level contribute to improved agricultural and environmental policies and enhance production sustainability.
Quantum channel marginal problem

Given a set of local dynamics, are they compatible with a global dynamics? We systematically formulate these questions as quantum channel marginal problems. These problems are strongly connected to the generalization of the no-signaling conditions to quantized inputs and outputs and can be understood as a general toolkit to study notions of quantum incompatibility. In fact, they include as special cases channel broadcasting, channel extendibility, measurement compatibility, and state marginal problems. After defining the notion of compatibility between global and local dynamics, we provide a solution to the channel marginal problem that takes the form of a semidefinite program. Using this formulation, we construct channel incompatibility witnesses, discuss their operational interpretation in terms of an advantage for a state-discrimination task, prove a gap between classical and quantum dynamical marginal problems and show that the latter is irreducible to state marginal problems.
On Efficient Training, Controllability and Compositional Generalization of Insertion-based Language Generators

Auto-regressive language models with the left-to-right generation order have been a predominant paradigm for language generation. Recently, out-of-order text generation beyond the traditional left-to-right paradigm has attracted extensive attention, with a notable variation of insertion-based generation, where a model is used to gradually extend the context into a complete sentence purely with insertion operations. However, since insertion operations disturb the position information of each token, it is often believed that each step of the insertion-based likelihood estimation requires a bi-directional re-encoding of the whole generated sequence. This computational overhead prohibits the model from scaling up to generate long, diverse texts such as stories, news articles, and reports. To address this issue, we propose InsNet, an insertion-based sequence model that can be trained as efﬁciently as traditional transformer decoders while maintaining the same performance as that with a bi-directional context encoder. We evaluate InsNet on story generation and CleVR-CoGENT captioning, showing the advantages of InsNet in several dimensions, including computational costs, generation quality, the ability to perfectly incorporate lexical controls, and better compositional generalization.
Lottery Ticket Implies Accuracy Degradation, Is It a Desirable Phenomenon?

In deep model compression, the recent ﬁnding “Lottery Ticket Hypothesis” (LTH) (Frankle & Carbin, 2018) pointed out that there could exist a winning ticket (i.e., a properly pruned sub-network together with original weight initialization) that can achieve competitive performance than the original dense network. However, it is not easy to observe such winning property in many scenarios, where for example, a relatively large learning rate is used even if it beneﬁts training the original dense model. In this work, we investigate the underlying condition and rationale behind the winning property, and ﬁnd that the underlying reason is largely attributed to the correlation between initialized weights and ﬁnal-trained weights when the learning rate is not sufﬁciently large. Thus, the existence of winning property is correlated with an insufﬁcient DNN pretraining, and is unlikely to occur for a well-trained DNN. To overcome this limitation, we propose the “pruning & ﬁne-tuning” method that consistently outperforms lottery ticket sparse training under the same pruning algorithm and the same total training epochs. Extensive experiments over multiple deep models (VGG, ResNet, MobileNet-v2) on different datasets have been conducted to justify our proposals.
Solvation of the Nonionic Surfactant in Organic and Mixed Solvents

Hypothesis: By combining the experimental small- and wide-angle x-ray scattering (SWAXS) method with molecular dynamics simulations and the theoretical "complemented-system approach" it is possible to obtain detailed information about the intra- and inter-molecular structure and dynamics of the solvation and hydration of the surfactant in organic and mixed solvents, e.g., of the nonionic surfactant Brij 35 in alcohols and aqueous alcohol-rich ternary systems. This first application of the complemented-system approach to the surfactant system will promote the use of this powerful methodology that is based on experimental and calculated SWAXS data in studies of colloidal systems. By applying high-performance computing systems, such an approach is readily available for studies in the colloidal domain. Experiments: SWAXS experiments and MD simulations were performed for binary Brij 35/alcohol and ternary Brij 35/water/alcohol systems with ethanol, n-butanol and n-hexanol as the organic solvent component at 25 °C. Findings: We confirmed the presence of solvated Brij 35 monomers in the studied organic media, revealed their preferential hydration and discussed their structural and dynamic features at the intra- and inter-molecular levels. Anisotropic effective surfactant molecular conformations were found. The influence of the hydrophobicity of the organic solvent on the hydration phenomena of surfactant molecules was explained.
Thinking Deeply with Recurrence: Generalizing from Easy to Hard Sequential Reasoning Problems

Deep neural networks are powerful machines for visual pattern recognition, but reasoning tasks that are easy for humans may still be difﬁcult for neural models. Humans can extrapolate simple reasoning strategies to solve difﬁcult problems using long sequences of abstract manipulations, i.e., harder problems are solved by thinking for longer. In contrast, the sequential computing bud-get of feed-forward networks is limited by their depth, and networks trained on simple problems have no way of extending their reasoning capabilities without retraining. In this work, we observe that recurrent networks have the uncanny ability to closely emulate the behavior of non-recurrent deep models, often doing so with far fewer parameters, on both image classiﬁcation and maze solving tasks. We also explore whether recurrent networks can make the generalization leap from simple problems to hard problems simply by increasing the number of recurrent iterations used at test time. To this end, we show that recurrent networks that are trained to solve simple mazes with few recurrent steps can indeed solve much more complex problems simply by performing additional recurrences during inference.
High-order differentiable autoencoder for nonlinear model reduction

This paper provides a new avenue for exploiting deep neural networks to improve physics-based simulation. Specifically, we integrate the classic Lagrangian mechanics with a deep autoencoder to accelerate elastic simulation of deformable solids. Due to the inertia effect, the dynamic equilibrium cannot be established without evaluating the second-order derivatives of the deep autoencoder network. This is beyond the capability of off-the-shelf automatic differentiation packages and algorithms, which mainly focus on the gradient evaluation. Solving the nonlinear force equilibrium is even more challenging if the standard Newton's method is to be used. This is because we need to compute a third-order derivative of the network to obtain the variational Hessian. We attack those difficulties by exploiting complex-step finite difference, coupled with reverse automatic differentiation. This strategy allows us to enjoy the convenience and accuracy of complex-step finite difference and in the meantime, to deploy complex-value perturbations as collectively as possible to save excessive network passes. With a GPU-based implementation, we are able to wield deep autoencoders (e.g., 10+ layers) with a relatively high-dimension latent space in real-time. Along this pipeline, we also design a sampling network and a weighting network to enable weight-varying Cubature integration in order to incorporate nonlinearity in the model reduction. We believe this work will inspire and benefit future research efforts in nonlinearly reduced physical simulation problems.