Miracle-dz/UniFAR-FTUs huggingface dataset:
Protection against Listeria monocytogenes by ODN Containing CpG Motifs in BALB/c and C57BL/6 Mice

Abstract Rad, M. , Ahmadi, M. , Farid Hosseini, R. , Ashkar, A.A. , Nejati, M. , Tabaraie, B. and Nourozian, D. 2006. Protection against Listeria monocytogenes by ODN containing CpG motifs in BALB/c and C57BL/6 mice. J. Appl. Anim. Res., 29: 145–147. Synthetic oligodeoxynucleotides containing CpG motifs have been shown to be effective immunoprotective agents in murine models for intracellular bacterial, viral and protozoan infections. In the present study, we demonstrated that CpG-ODN can induce protection against Listeria monocytogenes in BALB/c and C57BL/6 mice, the survival rate being higher in BALB/c mice. Further studies to determine the cause have been recommended.
A hierarchical field-level inference approach to reconstruction from sparse Lyman-α forest data

We address the problem of inferring the three-dimensional matter distribution from a sparse set of one-dimensional quasar absorption spectra of the Lyman-α forest. Using a Bayesian forward modelling approach, we focus on extending the dynamical model to a fully self-consistent hierarchical field-level prediction of redshift-space quasar absorption sightlines. Our field-level approach rests on a recently developed semiclassical analogue to Lagrangian perturbation theory (LPT), which improves over noise problems and interpolation requirements of LPT. It furthermore allows for a manifestly conservative mapping of the optical depth to redshift space. In addition, this new dynamical model naturally introduces a coarse-graining scale, which we exploited to accelerate the Markov chain Monte-Carlo (MCMC) sampler using simulated annealing. By gradually reducing the effective temperature of the forward model, we were able to allow it to first converge on large spatial scales before the sampler became sensitive to the increasingly larger space of smaller scales. We demonstrate the advantages, in terms of speed and noise properties, of this field-level approach over using LPT as a forward model, and, using mock data, we validated its performance to reconstruct three-dimensional primordial perturbations and matter distribution from sparse quasar sightlines.
Using PHAST to port Caffe library: First experiences and lessons learned

Performance has always been a hot topic in computing. However, the viable ways to achieve it have taken many forms in the different moments of computing history. Today, technological limits have pushed the adoption of increasingly parallel multi-core and many-core architectures and even the use of highly specific hardware (aka Domain-Specific Architectures, or DSAs) to solve very specific problems. In this new context, one major problem is how to develop software once, and be able to run it on multiple accelerator architectures, seamlessly. Ideally aiming at a single programming model that can automatically target the code to different kinds of parallel architectures, allowing specific tuning with minimal, if any, changes to the source-code in order to seek performance portability. A comprehensive solution to this is still lacking. In this work, we present the use of the PHAST Library, which allows users to code once, at a high level of abstraction and thus with high productivity, and automatically targeting different parallel devices by changing the compilation process. As a case study, we have worked on the porting of the well-known deep-learning Caffe framework. The framework has been split into different parts and some of them have been ported, obtaining a working straightforward implementation that can be run on both CPUs and GPUs. We conclude discussing the lessons learned during the porting process, and analyzing the obtained performance in the perspective of completing the porting and expanding it to future consequent works.
Mass mortality of the tropical seagrass Thalassia testudinum in Florida Bay (USA)

This report documents rapid and widespread mortality of the seagrass Thalassia testudinum Banks ex Konig (turtle grass) in Florida Bay at the southern tip of the Flonda peninsula (USA). More than 4000 ha of seagrass beds have been completely lost in recurring episodes of mortality since summer 1987 An additional 23 000 ha have been affected to a lesser degree. Loss of T. testudinurn, the dominant rnacrophyte species in thls highly productive system, may affect ecosystem function within the bay as well as estuarine-dependent sport and commercial fisheries. A pathogenic protist related to the causal agent of the eelgrass wasting disease may be involved in the mortality and may place 7. testudinunl populations outside Florida Bay at risk. Environmental factors and chronic hypoxia of below-ground T testudinum tissue may also contnbute to the die-off. Flonda Bay is a shallow, triangular lagoon a t the southern tip of peninsular Florida bordered on the north by the Florida mainland and on the southeast by the Florida Keys; its western margin is open to the Gulf of Mexico. Shallow carbonate mud banks divide the bay into basins, restrict circulation, and attenuate the Gulf's lunar tidal influence. Freshwater enters the bay in the northeast from Taylor Slough, a s overflow from the C-l l l Canal that is part of the South Florida Water Management District's canal system, and as sheet flow generated by local rainfall. Depending on the timing and amounts of local rainfall, water conditions in the
Slow Learning of Foraging Skills and Extended Parental Care in Cooperatively Breeding White-Winged Choughs

This is the first study to associate costs of extended juvenile development and the necessity of cooperative breeding. Juvenile choughs require unusually long periods to attain foraging independence. The transition is gradual, usually taking about 200 d after fledging. These results show a clear relationship between the amount of help a juvenile gets, the nature of its transition to foraging independence (TFI), and its prospects of surviving its first year. Despite high variance within broods, individuals with greater numbers of helpers in their group receive more food from begging and remain dependent for longer periods. Juveniles invariably lose weight over winter, but those that remain dependent on adults for food for longer periods both begin and emerge from winter with higher body weights. However, these individuals lack experience and are poorer foragers throughout winter. Three years of survival data show that juveniles with high numbers of adults to care for them have better prospects of surviving their first year. It is suggested that juveniles must optimize between acquiring sufficient food from begging and devoting sufficient time to learning to forage. Juveniles probably apply a learning rule to maximize fitness when faced with varying numbers of helpers and siblings. I show that a number of avian and mammalian cooperative breeders have unusual causes of delayed breeding. In these species, costs of parental care may constrain independent reproduction when the development of their young is exaggerated. Examples include unusually large litters or body size of young, or a difficult foraging niche causing extra burdens on developmental time budgets.
Effect of desiccation and salinity stress on seed germination and initial plant growth of Cucumis melo

Smellmelon, an annual invasive weed of soybean production fields in the north of Iran, reproduces and spreads predominately through seed production. This makes seed bank survival and successful germination essential steps in the invasive process. To evaluate the potential of Smellmelon to invade water-stressed environments, laboratory studies were conducted to investigate the effect of desiccation and salinity at different temperatures on seed germination and seedling growth of Cucumis melo. Seeds were incubated at 25, 30, 35 and 40 oC in the darkness in a solution (0, -0.2, -0.4, -0.6, -0.8, 1 and 1.2 MPa) of a salt (NaCl), and in a solution (0, -2, -4, -6, -8, -10, -12 bar) of PEG-6000 (Polyethylene glycol), in two separate experiments. The results showed that the highest percentage and rate of germination occurred at 35 oC in salt concentrations of 0, -0.2, -0.4 MPa and PEG concentrations of 0, -2, -4 bar. Increasing the concentration of salt (NaCl) and PEG limited germination, seedling growth and water uptake but increased the sodium content in the seedlings. No significant difference was observed among 0, -0.2 and -0.4 MPa of NaCl and among 0, -2 and -4 bar of PEG concentration at 35 oC. The negative effects of PEG were more than those of NaCl on germination percentage and germination rate. Increased stress levels lead to reduction of root and shoot length, and SVL of seedlings. Na+ content of seedling decreased with limited seedling growth of C. melo.
Stochastic Potential Games

Computing the Nash equilibrium (NE) for N-player non-zerosum stochastic games is a formidable challenge. Currently, algorithmic methods in stochastic game theory are unable to compute NE for stochastic games (SGs) for settings in all but extreme cases in which the players either play as a team or have diametrically opposed objectives in a two-player setting. This greatly impedes the application of the SG framework to numerous problems within economics and practical systems of interest. In this paper, we provide a method of computing Nash equilibria in nonzero-sum settings and for populations of players more than two. In particular, we identify a subset of SGs known as stochastic potential games (SPGs) for which the (Markov perfect) Nash equilibrium can be computed tractably and in polynomial time. Unlike SGs for which, in general, computing the NE is PSPACE-hard, we show that SGs with the potential property are P-Complete. We further demonstrate that for each SPG there is a dual Markov decision process whose solution coincides with the MP-NE of the SPG. We lastly provide algorithms that tractably compute the MP-NE for SGs with more than two players.
Median bias reduction in cumulative link models

Abstract This paper presents a novel estimation approach for cumulative link models, based on median bias reduction. The median bias reduced estimator is obtained as solution of an estimating equation based on an adjustment of the score. It allows to obtain higher-order median centering of maximum likelihood estimates without requiring their finiteness. The estimator is equivariant under componentwise monotone reparameterizations and the method is effective in preventing boundary estimates. Through simulation studies and an application, we compare the median bias reduced estimator with the two main competitors, the maximum likelihood and the mean bias reduced estimators. The method is seen to be highly successful in achieving median centering and shows remarkable properties under reparameterizations related to effect measure.
Patterns of Lipid Distribution and Utilisation in Insects

During the course of insect evolution lipids have assumed a significant role in facilitating several important morphogenetic and physiological strategies. Stored glycerides provide a convenient reservoir of metabolic energy for periods of prolonged energy demand, while cuticular lipids are of profound importance in enabling terrestrial insects to resist dessication. The present review identifies the lipid classes of fat body, haemolymph and cuticle, and summarises the contribution of lipids to insect development, migration, diapause, protection, reproduction and flight. The release, transport and uptake of lipid during flight isdiscussed.
GROWTH ANALYSIS OF THE SEEDLINGS OF BALSA, OCHROMA LAGOPUS

SUMMARY In a glasshouse near Oxford, under conditions similar to a large gap in lowland tropical rain forest, young seedlings of balsa, Ochroma lagopus Swartz, had an estimated unit leaf rate (net assimilation rate) of 33 g m−2 week−1 compared to 44 g m−1 week−1 for Helianthus annuus. The energy conversion efficiency was 05 and 0–6 % of incident radiation 300 to 3000 ran respectively. Unit leaf rates of woody plants have almost always been found to be lower than those of Helianthus, when both are grown side by side. The lowest rates relative to Helianthus are in Agathis, the only shade-tolerant genus yet examined.
Accelerating Neural Network Inference by Overflow Aware Quantization

The inherent heavy computation of deep neural networks prevents their widespread applications. A widely used method for accelerating model inference is quantization, by replacing the input operands of a network using fixed-point values. Then the majority of computation costs focus on the integer matrix multiplication accumulation. In fact, high-bit accumulator leads to partially wasted computation and low-bit one typically suffers from numerical overflow. To address this problem, we propose an overflow aware quantization method by designing trainable adaptive fixed-point representation, to optimize the number of bits for each input tensor while prohibiting numeric overflow during the computation. With the proposed method, we are able to fully utilize the computing power to minimize the quantization loss and obtain optimized inference performance. To verify the effectiveness of our method, we conduct image classification, object detection, and semantic segmentation tasks on ImageNet, Pascal VOC, and COCO datasets, respectively. Experimental results demonstrate that the proposed method can achieve comparable performance with state-of-the-art quantization methods while accelerating the inference process by about 2 times.
Semi-Supervised Source Localization with Deep Generative Modeling

We propose a semi-supervised localization approach based on deep generative modeling with variational autoencoders (VAE). Localization in reverberant environments remains a challenge, which machine learning (ML) has shown promise in addressing. Even with large data volumes, the number of labels available for supervised learning in reverberant environments is usually small. We address this issue by perform semi-supervised learning (SSL) with convolutional VAEs. The VAE is trained to generate the phase of relative transfer functions (RTFs), in parallel with a DOA classifier, on both labeled and unlabeled RTF samples. The VAE-SSL approach is compared with SRP-PHAT and fully-supervised CNNs. We find that VAE-SLL can outperform both SRP-PHAT and CNN in label-limited scenarios.
Waveform relaxation for low frequency coupled field/circuit differential-algebraic models of index 2

Motivated by the task to design quench protection systems for superconducting magnets in particle accelerators we address a coupled field/circuit simulation based on a magneto-quasistatic field modeling. We investigate how a waveform relaxation of Gaus-Seidel type performs for a coupled simulation when circuit solving packages are used that describe the circuit by the modified nodal analysis. We present sufficient convergence criteria for the coupled simulation of FEM discretised field models and circuit models formed by a differential-algebraic equation (DAE) system of index 2. In particular, we demonstrate by a simple benchmark system the drastic influence of the circuit topology on the convergence behavior of the coupled simulation.
Effects of Exogenous Spermidine on Antioxidant System Responses of Typha latifolia L. Under Cd2+ Stress

: The effects of foliar spraying with spermidine (Spd), ranging in concentration from 0.25 to 0.50 mmol/L, on the antioxidant system under Cd2+ stress (range 0.1–0.2 mmol/L Cd2+) in Typha latifolia L. grown hydroponically were investigated in order to offer a referenced evidence for an understanding of the mechanism by which polyamines (PAs) relieve the damage to plants by heavy metal and improve the phytoremediation efficiency of heavy metal-contaminated water. The results showed that Cd2+ stress induced oxidative injury, as evidenced by an increase in the generation of superoxide anion (O2-), as well as the hydrogen peroxide (H2O2) and malondialdehyde (MDA) contents in both leaves and caudices. With the exception of superoxide dismutase (SOD) activity in the leaves, an increase in the activities of catalase (CAT), guaiacol peroxidase (GPX), and glutathione reductase (GR) was observed in both leaves and caudices, SOD activity was increased in caudices, and ascorbate peroxidase (APX) activity was increased in leaves following Cd2+ treatment. The reduced glutathione (GSH) content in both leaves and caudices and the reductive ascorbate content in leaves was obviously increased, which were prompted by the application of exogenous Spd. Spraying with Spd increased the activity of GR and APX in both leaves and caudices, whereas the activity of SOD, CAT, and GPX was increased only in caudices following spraying with Spd. The generation of O2 -. and the H2O2 and MDA content in both leaves and caudices decreased after spraying with Spd. The decrease in MDA was more obvious following the application of 0.25 than 0.50 mmol/L Spd. It is supposed that exogenous Spd elevated the tolerance of T. latifolia under Cd2+ stress primarily by increasing GR activity and the GSH level. (Managing editor: Ping HE)
On the Convergence of Gradient Descent Training for Two-layer ReLU-networks in the Mean Field Regime

We describe a necessary and sufficient condition for the convergence to minimum Bayes risk when training two-layer ReLU-networks by gradient descent in the mean field regime with omni-directional initial parameter distribution. This article extends recent results of Chizat and Bach to ReLU-activated networks and to the situation in which there are no parameters which exactly achieve MBR. The condition does not depend on the initalization of parameters and concerns only the weak convergence of the realization of the neural network, not its parameter distribution.
A search for supernova-like optical counterparts to ASKAP-localised fast radio bursts

Fast radio bursts (FRBs) are millisecond-scale radio pulses, which originate in distant galaxies and are produced by unknown sources. The mystery remains partially because of the typical difficulty in localising FRBs to host galaxies. Accurate localisations delivered by the Commensal Real-time ASKAP Fast Transients (CRAFT) survey now provide an opportunity to study the host galaxies and potential transient counterparts of FRBs at a large range of wavelengths. In this work, we investigate whether the first three FRBs accurately localised by CRAFT have supernova-like transient counterparts. We obtained two sets of imaging epochs with the Very Large Telescope for three host galaxies, one soon after the burst detection and one several months later. After subtracting these images no optical counterparts were identified in the associated FRB host galaxies, so we instead place limits on the brightness of any potential optical transients. A Monte Carlo approach, in which supernova light curves were modelled and their base properties randomised, was used to estimate the probability of a supernova associated with each FRB going undetected. We conclude that Type Ia and IIn supernovae are unlikely to accompany every apparently non-repeating FRB.
Structural Control Analysis of System Dynamics Models

Structural control theory could be applied to study the control principles of social, economic and managerial systems. System Dynamics (SD) is the target field in social-economic sciences for endogenizing this theory, a subject that provides modeling solutions to real-world problems. SD models adopt diagrammatic representations, making it an ideal ground for transplanting structural control theory which utilizes similar graphic representations. This study sets up the theoretical ground for conducting structural control analysis (SCA) on SD models, summarized as a post-modeling workflow for SD practitioners, which serves as a specific application of the general structural control theory in social-economic sciences. Theoretical and practical establishments for SCA components are developed coordinately. Specifically, this study addresses the following questions: (1) How do SD models differ from physical control systems in graphic representations, and how do these differences affect the way of applying structural control theories to SD? (2) How could one identify control inputs in SD models, and how could different levels of system control in SD models be conceptualized? (3) What are the structural control properties for important SD components, and how could these properties and control principles help justify modeling heuristics in SD practice? (4) What are the procedures for conducting Structural Control Analysis (SCA) in SD models, and what are the implications of SCA results for model calibration and decision making? Overall, this study provides general insights for system control analysis of nonlinear dynamic simulation models, which may go beyond SD and extend to various disciplines in social-economic sciences.
Insertion-Based Modeling for End-to-End Automatic Speech Recognition

End-to-end (E2E) models have gained attention in the research field of automatic speech recognition (ASR). Many E2E models proposed so far assume left-to-right autoregressive generation of an output token sequence except for connectionist temporal classification (CTC) and its variants. However, left-to-right decoding cannot consider the future output context, and it is not always optimal for ASR. One of the non-left-to-right models is known as non-autoregressive Transformer (NAT) and has been intensively investigated in the area of neural machine translation (NMT) research. One NAT model, mask-predict, has been applied to ASR but the model needs some heuristics or additional component to estimate the length of the output token sequence. This paper proposes to apply another type of NAT called insertion-based models, that were originally proposed for NMT, to ASR tasks. Insertion-based models solve the above mask-predict issues and can generate an arbitrary generation order of an output sequence. In addition, we introduce a new formulation of joint training of the insertion-based models and CTC. This formulation reinforces CTC by making it dependent on insertion-based token generation in a non-autoregressive manner. We conducted experiments on three public benchmarks and achieved competitive performance to strong autoregressive Transformer with a similar decoding condition.
Establishing a New State-of-the-Art for French Named Entity Recognition

The French TreeBank developed at the University Paris 7 is the main source of morphosyntactic and syntactic annotations for French. However, it does not include explicit information related to named entities, which are among the most useful information for several natural language processing tasks and applications. Moreover, no large-scale French corpus with named entity annotations contain referential information, which complement the type and the span of each mention with an indication of the entity it refers to. We have manually annotated the French TreeBank with such information, after an automatic pre-annotation step. We sketch the underlying annotation guidelines and we provide a few figures about the resulting annotations.