Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationships Between Landscape Structure and Breeding Birds in the Oregon Coast Range

Human-caused fragmentation of forests is increasing, yet the consequences of these landscape changes to vertebrate communities are poorly understood. Although bird community response to forest fragmentation caused by agricultural or urban development has been well studied, we have little understanding of these dynamics in landscapes undergoing intensive forest management, where late-seral forest stands are separated by younger forest stands of varying ages and are part of a spatially and temporally dynamic forest landscape. We investigated the relationship between landscape structure and breeding bird abundance in the central Oregon Coast Range. We sampled vegetation and birds in 30 landscapes (250-300 ha) distributed equally among three basins. Landscapes represented a range in structure based on the proportion of the landscape in a late-seral forest condition and the spatial configuration of that forest condition within the landscape. We computed a variety of landscape metrics from digital vegetation cover maps for each landscape. Using analysis of variance and regression procedures, we quantified the independent effects of habitat area and configuration on 15 bird species associated with late-seral forest. Species varied dramatically in the strength and nature of the relationship between abundance and several gradients in habitat area and configuration at the landscape scale. Landscape structure (composition and configuration) typically explained <50% of the variation in each species' abundance among the landscapes. Species' abundances were generally greater in the more heterogenous landscapes; that is, they were associated with the more fragmented distribution of habitat. Only Winter Wrens showed evidence of association with the least fragmented landscapes. These results must be interpreted within the scope and limitations of our study. In particular, the scale of our analysis was constrained by the lower and upper limits of resolution in our landscapes, as set by minimum patch size and landscape extent, respectively. Thus, our results do not preclude much stronger and different relationships at finer and/or coarser scales. In addition, our community-centered habitat classification scheme and artificially discrete representation of patch boundaries may not have captured the functionally meaningful heterogeneity for each species. Finally, our analysis was limited to relatively common and widespread diurnal breeding bird species. Species sensitive to habitat fragmentation at the scale of our analysis may have been rare already and therefore not subject to the parametrical statistical approach that we employed.
ESA/STAT/AC. 202/S5.3 International Seminar on Early Warning and Business Cycle Indicators 14 to 16 December 2009 Scheveningen, The Netherlands The Euro-area recession and nowcasting GDP growth using statistical models

This paper assesses the performance of nowcasts for Euro-area quarterly GDP growth, constructed ahead of Eurostat’s Flash estimate which is at 45 days, over a period which includes the recent recession. The exercise uses real-time data and allows for the staggered release of monthly information on indicator variables throughout the quarter. The results indicate that the recent recession, due to the global financial crisis of 2007-8, led to a dramatic deterioration in the performance of nowcasts at 0 and 15 days, but a clear improvement relative to autoregressive benchmarks. The utility of constructing nowcasts using indicator variables increased over the recessionary period. But the performance of the different statistical nowcasting models varies considerably according to which statistical model is used. The relative performance of different nowcasting models and different indicator variables switched suddenly in the recession with “soft” data from qualitative surveys becoming more important relative to “hard” data on industrial production, even when the “hard” data are known. Despite the fact that prior to the recession it paid to wait for release of two months of within quarter industrial production data, over the recessionary period one would have been better off ignoring this statistical evidence and constructing nowcasts zero-weighting the industrial production data and focusing on the qualitative surveys alone. But our results suggest that now the recession appears to over the utility of indicator-based nowcasts, whether used in a regression or factor-based model, will diminish and the autoregressive benchmark will once again become a competitive, albeit perhaps not the best, nowcasting model. They also suggest that, as before the recession, waiting for two months of industrial production data will improve accuracy. 1 Address for correspondence: James Mitchell, National Institute of Economic and Social Research, 2 Dean Trench Street, Smith Square, London SW1P 3HE, U.K. Email: j.mitchell@niesr.ac. uk.
COVID-19: disease pathways and gene expression changes predict methylprednisolone can improve outcome in severe cases

Abstract Motivation COVID-19 has several distinct clinical phases: a viral replication phase, an inflammatory phase, and in some patients, a hyper-inflammatory phase. High mortality is associated with patients developing cytokine storm syndrome. Treatment of hyper-inflammation in these patients using existing, approved therapies with proven safety profiles could address the immediate need to reduce mortality. Results We analyzed the changes in the gene expression, pathways and putative mechanisms induced by SARS-CoV2 in NHBE, and A549 cells, as well as COVID-19 lung vs. their respective controls. We used these changes to identify FDA approved drugs that could be repurposed to help COVID-19 patients with severe symptoms related to hyper-inflammation. We identified methylprednisolone (MP) as a potential leading therapy. The results were then confirmed in five independent validation data sets including Vero E6 cells, lung and intestinal organoids, as well as additional patient lung sample vs. their respective controls. Finally, the efficacy of MP was validated in an independent clinical study. Thirty-day all-cause mortality occurred at a significantly lower rate in the MP-treated group compared to control group (29.6% vs. 16.6%, p = 0.027). Clinical results confirmed the in silico prediction that MP could improve outcomes in severe cases of COVID-19. A low number needed to treat (NNT = 5) suggests MP may be more efficacious than dexamethasone or hydrocortisone. Availability iPathwayGuide is available at https://ipathwayguide.advaitabio. com/ Supplementary information Supplementary data are available at Bioinformatics online.
Effects of density and spatial heterogeneity on foraging behaviour and fitness correlates of Armadillidium vulgare (Isopoda Oniscidea)

The encounter rate of focal individuals of Armadillidium vulgare in experimental arenas increased with increasing density of other isopods. This increase was only significantly more than would be predicted from a random encounter model when the additional animals were of a different species, Porcellio scaber. Increasing density of both species resulted in focal individuals spending a higher proportion of time walking while in high quality food patches, and a smaller proportion of their time feeding on the high quality food. This was only significant when the high quality food was most heterogeneously distributed and was more significant following encounters with P. scaber than with other A. vulgare. At higher densities focal individuals alternated turns less while searching in the low quality food matrix Relative growth rates and survivorship were both higher at higher population densities (278 m–2) than in the low density treatments of 28 m–2. We suggest that at low densities, which are below those observed for three field populations over twenty years, the advantages of having additional individuals with which to aggregate while sheltering may outweigh the costs of increased interference competition during foraging. The effects of spatial heterogeneity of food resources on interference competition between species differing in aggressiveness are discussed. The possible advantages of aggregating with another species, that has different morphological, physiological and behavioural adaptations to the terrestrial environment, while sheltering are examined in relation to the Allee effect of the positive fitness consequences of increasing population densities from very low levels.
Bayesian Subspace HMM for the Zerospeech 2020 Challenge

In this paper we describe our submission to the Zerospeech 2020 challenge, where the participants are required to discover latent representations from unannotated speech, and to use those representations to perform speech synthesis, with synthesis quality used as a proxy metric for the unit quality. In our system, we use the Bayesian Subspace Hidden Markov Model (SHMM) for unit discovery. The SHMM models each unit as an HMM whose parameters are constrained to lie in a low dimensional subspace of the total parameter space which is trained to model phonetic variability. Our system compares favorably with the baseline on the human-evaluated character error rate while maintaining significantly lower unit bitrate.
Potato glycoalkaloids: chemistry, analysis, safety, and plant physiology

Abstract Potatoes, members of the Solanaceae plant family, serve as a major, inexpensive food source for both energy (starch) and good-quality protein, with worldwide production of about 350 million tons per year. U.S. per capita consumption of potatoes is about 61 kg/year. Potatoes also produce potentially toxic glycoalkaloids, both during growth and after harvest. Glycoalkaloids appear to be more toxic to man than to other animals. The toxicity may be due to anticholinesterase activity of the glycoalkaloids on the central nervous system and to disruptions of cell membranes affecting the digestive system and other organs. The possible contribution of glycoalkaloids to the multifactorial aspects of teratogenicity is inconclusive. Possible safe levels are controversial; guidelines limiting glycoalkaloid content of potato cultivars are currently being debated. This review presents an integrated, critical assessment of the multifaceted aspects of the role glycoalkaloids play in nutrition and food safety; che.
Large Margin Mechanism and Pseudo Query Set on Cross-Domain Few-Shot Learning

In recent years, few-shot learning problems have received a lot of attention. While methods in most previous works were trained and tested on datasets in one single domain, cross-domain few-shot learning is a brand-new branch of few-shot learning problems, where models handle datasets in different domains between training and testing phases. In this paper, to solve the problem that the model is pre-trained (meta-trained) on a single dataset while fine-tuned on datasets in four different domains, including common objects, satellite images, and medical images, we propose a novel large margin fine-tuning method (LMM-PQS), which generates pseudo query images from support images and fine-tunes the feature extraction modules with a large margin mechanism inspired by methods in face recognition. According to the experiment results, LMM-PQS surpasses the baseline models by a significant margin and demonstrates that our approach is robust and can easily adapt pre-trained models to new domains with few data.
On the Power of Unambiguity in Büchi Complementation

In this work, we exploit the power of unambiguity for the complementation problem of Buchi automata by utilizing reduced run directed acyclic graphs (DAGs) over infinite words, in which each vertex has at most one predecessor. Given a Buchi automaton with n states and a finite degree of ambiguity, we show that the number of states in the complementary Buchi automaton constructed by the classical Rank-based and Slice-based complementation constructions can be improved, respectively, to $2^{\mathcal{O}(n)}$ from $2^{\mathcal{O}( n \log n)}$ and to $\mathcal{O}(4^n)$ from $\mathcal{O}( (3n)^n)$, based on reduced run DAGs. To the best of our knowledge, the improved complexity is exponentially better than best known result of $\mathcal{O}(5^n)$ in [21] for complementing Buchi automata with a finite degree of ambiguity.
Global solutions for a family of GSQG front equations

We prove the global existence of solutions with small and smooth initial data of a nonlinear dispersive equation for the motion of generalized surface quasi-geostrophic (GSQG) fronts in a parameter regime $1<\alpha<2$, where $\alpha=1$ corresponds to the SQG equation and $\alpha=2$ corresponds to the incompressible Euler equations. This result completes previous global well-posedness results for $0<\alpha \le 1$. We also use contour dynamics to derive the GSQG front equations for $1<\alpha<2$.
On Intrinsic Dataset Properties for Adversarial Machine Learning

Deep neural networks (DNNs) have played a key role in a wide range of machine learning applications. However, DNN classifiers are vulnerable to human-imperceptible adversarial perturbations, which can cause them to misclassify inputs with high confidence. Thus, creating robust DNNs which can defend against malicious examples is critical in applications where security plays a major role. In this paper, we study the effect of intrinsic dataset properties on the performance of adversarial attack and defense methods, testing on five popular image classification datasets - MNIST, Fashion-MNIST, CIFAR10/CIFAR100, and ImageNet. We find that input size and image contrast play key roles in attack and defense success. Our discoveries highlight that dataset design and data preprocessing steps are important to boost the adversarial robustness of DNNs. To our best knowledge, this is the first comprehensive work that studies the effect of intrinsic dataset properties on adversarial machine learning.
Morphological and Physiological Characters of Aloe vera Subjected to Saline Water Irrigation

Aloe vera is grown in arid climates where salinity can limit plant growth and development. A study was conducted to examine the morphological and physiological characters under salt stress. Plants were cultivated in pots and irrigated with freshwater (EC 450 μs cm−1) or saline lake water (EC 3, 6, 9, 12, 15, 18, or 21 dS m−1). Results indicated that salinity influenced the plant growth and morphological traits and the biomass. Glucose, xylose, and mannose concentrations in leaf gel increased with increasing salinity up to 9 dS m−1 and decreased with higher saline concentrations. Aloin concentration increased with salt stress up to 15 dS m−1 that decreased at higher salinity concentrations.
Grain Growth in Newly Discovered Young Eruptive Stars

FU Orionis–type stars are young stellar objects showing large outbursts due to highly enhanced accretion from the circumstellar disk onto the protostar. FU Orionis–type object (FUor) outbursts happen in a wide variety of sources from the very embedded ones to those with almost no sign of extended emission beyond the disk. The subsequent eruptions might gradually clear up the obscuring envelope material and drive the protostar on its way to become a disk-only T Tauri star. We used the Very Large Telescope (VLT)/VLT spectrometer and imager for the mid-infrared (VISIR) to obtain the first spectra that cover the 8–13 μm mid-infrared wavelength range in low resolution of five recently discovered FUors. Four objects from our sample show the 10 μm silicate feature in emission. We study the shape and strength of the silicate feature in these objects and find that they mostly contain large amorphous grains, suggesting that large grains are typically not settled to the midplane in FUor disks. This is a general characteristic of FUors, as opposed to regular T Tauri–type stars whose disks display anything from pristine small grains to significant grain growth. We classify our targets by determining whether the silicate feature is in emission or in absorption, and confront them with the evolutionary scenarios on the dispersal of the envelopes around young stars. In our sample, all Class II objects exhibit silicate emission, while for Class I objects, the appearance of the feature in emission or absorption depends on the viewing angle with respect to the outflow cavity. This highlights the importance of geometric effects when interpreting the silicate feature.
Large 2-colored cliques in 3-edge-colorings of the complete graph with forbidden patterns

Erd\H{o}s and Szekeres's quantitative version of Ramsey's theorem asserts that any complete graph on n vertices that is edge-colored with two colors has a monochromatic clique on at least 1/2log(n) vertices. The famous Erd\H{o}s-Hajnal conjecture asserts that forbidding fixed color patterns ensures larger monochromatic cliques. Specifically, it claims that for any fixed integer k and any clique K on k vertices edge-colored with two colors, there is a positive constant a such that in any complete n-vertex graph edge-colored with two colors that does not contain a copy of K, there is a monochromatic clique on at least n^a vertices. We consider edge-colorings with three colors. For a family H of triangles, each colored with colors from {r, b, y}, Forb(n,H) denotes a family of edge-colorings of the complete n-vertex graph using colors from {r, b, y} and containing none of the colorings from H. Let h_2(n, H) be the maximum q such that any coloring from Forb(n, H) has a clique on at least q vertices using at most two colors. We provide bounds on h_2(n, H) for all families H consisting of at most three triangles. For most of them, our bounds are asymptotically tight. This extends a result of Fox, Grinshpun, and Pach, who determined h_2(n, H) for H consisting of a rainbow triangle, and confirms the multicolor Erd\H{o}s-Hajnal conjecture for these sets of patterns.
An Information-Theoretic Approach for Path Planning in Agents with Computational Constraints

In this paper, we develop a framework for path-planning on abstractions that are not provided to the system a-priori but instead emerge as a function of the agent's available computational resources. We show how a path-planning problem in an environment can be systematically approximated by solving a sequence of easier to solve problems on abstractions of the original space. The properties of the problem are analyzed, and supporting theoretical results presented and discussed. A numerical example is presented to show the utility of the approach and to corroborate the theoretical findings. We conclude by providing a discussion of the results and their interpretation relating to anytime algorithms and bounded rationality.
Single-Deletion Single-Substitution Correcting Codes

Correcting insertions/deletions as well as substitution errors simultaneously plays an important role in DNA-based storage systems as well as in classical communications. This paper deals with the fundamental task of constructing codes that can correct a single insertion or deletion along with a single substitution. A non-asymptotic upper bound on the size of singledeletion single-substitution correcting codes is derived, showing that the redundancy of such a code of length n has to be at least 2 log n. The bound is presented both for binary and non-binary codes while an extension to single deletion and multiple substitutions is presented for binary codes. An explicit construction of single-deletion single-substitution correcting codes with at most 6 log n + 8 redundancy bits is derived. Note that the best known construction for this problem has to use 3-deletion correcting codes whose best known redundancy is roughly 24 log n.
The Effect of Moderation on Online Mental Health Conversations

Many people struggling with mental health issues are unable to access adequate care due to high costs and a shortage of mental health professionals, leading to a global mental health crisis. Online mental health communities can help mitigate this crisis by offering a scalable, easily accessible alternative to in-person sessions with therapists or support groups. However, people seeking emotional or psychological support online may be especially vulnerable to the kinds of antisocial behavior that sometimes occur in online discussions. Moderation can improve online discourse quality, but we lack an understanding of its effects on online mental health conversations.In this work, we leveraged a natural experiment, occurring across 200,000 messages from 7,000 online mental health conversations, to evaluate the effects of moderation on online mental health discussions. We found that participation in group mental health discussions led to improvements in psychological perspective, and that these improvements were larger in moderated conversations. The presence of a moderator increased user engagement, encouraged users to discuss negative emotions more candidly, and dramatically reduced bad behavior among chat participants. Moderation also encouraged stronger linguistic coordination, which is indicative of trust building. In addition, moderators who remained active in conversations were especially successful in keeping conversations on topic. Our findings suggest that moderation can serve as a valuable tool to improve the efficacy and safety of online mental health conversations. Based on these findings, we discuss implications and trade-offs involved in designing effective online spaces for mental health support.
LIPID CLASS DISTRIBUTION OF HIGHLY UNSATURATED LONG CHAIN FATTY ACIDS IN MARINE DINOFLAGELLATES

The very long chain highly unsaturated C28 fatty acids, octacosaheptaenoic [28:7(n‐6)] and octacosaoctaenoic acid [28:8(n‐3)], were found to be associated with phospholipids, obtained by fractionation of total lipid extracts into distinct lipid classes, in 4 and 6, respectively, of 16 examined dinoflagellates. An interfraction comparison of fatty acids associated with phospholipids and glycolipids has also shown that the phospholipid fractions contained the majority (over 75% in 12 of 16 strains) of docosahexaenoic acid [22:6(n‐3)] and traces of tetracosanoic acid (24:0). By contrast, the highly unsaturated C18 fatty acids octadecatetraenoic [18:4(n‐3)] and octadecapentaenoic acid [18:5(n‐3)] were primarily recovered from a chloroplast‐associated glycolipid fraction comprised of monogalactosyldiacylglycerol, digalactosyldiacylglycerol, and sulfoquinovosyldiacylglycerol. In 12 of 16 strains, an interfraction comparison showed that over 90% of 18:5(n‐3) was found to be associated with glycolipids. These findings indicate that the C28 fatty acids are located and probably synthesized in the cytoplasm or in an organelle other than the chloroplast, possibly with 22:6(n‐3) and 24:0 as precursors, whereas the C18 fatty acids 18:4(n‐3) and 18:5(n‐3) are glycolipid constituents apparently synthesized within the chloroplast. The function(s) of these C28 fatty acids as components of phospholipids in cellular membranes is currently unknown.
Investigations on Phoneme-Based End-To-End Speech Recognition

Common end-to-end models like CTC or encoder-decoder-attention models use characters or subword units like BPE as the output labels. We do systematic comparisons between grapheme-based and phoneme-based output labels. These can be single phonemes without context (~40 labels), or multiple phonemes together in one output label, such that we get phoneme-based subwords. For this purpose, we introduce phoneme-based BPE labels. In further experiments, we extend the phoneme set by auxiliary units to be able to discriminate homophones (different words with same pronunciation). This enables a very simple and efficient decoding algorithm. We perform the experiments on Switchboard 300h and we can show that our phoneme-based models are competitive to the grapheme-based models.