Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of an antifungal insect defensin on the proteome of the phytopathogenic fungus Botrytis cinerea.

ETD151, an analogue of the antifungal insect defensin heliomicin, is an antifungal peptide active against yeasts and filamentous fungi. In order to decipher the mechanisms underlying its molecular action on the phytopathogenic fungus Botrytis cinerea, a necrotrophic pathogen responsible for gray mold disease, we investigated the changes in three-day old mycelia upon treatment with different concentrations of ETD151. Optical and fluorescent microscopies were used prior to establishing the peptide/protein profiles through two mass spectrometry approaches: MALDI profiling, to generate molecular mass fingerprints as peptide signatures, and a gel-free bottom-up proteomics approach. Our results show that a concentration of ETD151 above the half-maximal inhibitory concentration can alter the integrity of the mycelial structure of B. cinerea. Furthermore, reproducible modifications of the peptide/protein composition were demonstrated in the presence of ETD151 within a 1,500 - 16,000 mass (m/z) range. After the robustness of LC-ESI-MS/MS analysis on B. cinerea mycelial extracts was confirmed, our analyses highlighted 340 significantly modulated proteins upon treatment with ETD151 within a 4.8 - 466 kDa mass range. Finally, data mapping on KEGG pathways revealed the molecular impact of ETD151 on at least six pathways, namely spliceosome, ribosome, protein processing in endoplasmic reticulum, endocytosis, MAPK signaling pathway and oxidative phosphorylation.
The scincid lizard genus Sigaloseps (Reptilia: Scincidae) from New Caledonia in the southwest Pacific: description of a new species and review of the biology, distribution, and morphology of Sigaloseps deplanchei (Bavay)

Sigaloseps is a genus of two species of scincid lizards endemic to the southern ultramafic region of New Caledonia in the southwest Pacific. The morphology, distribution, and habits of the moderately widespread species Sigaloseps deplanchei are reviewed. The other species in the genus represents a new taxon known only from two high altitude sites above 1,000 m asl. The conservation status of both species is assessed. Sigaloseps deplanchei is not regarded as threatened. The new species, Sigaloseps ruficauda, by virtue of its restricted distribution and habitat preference, is likely to be adversely affected by habitat modification, and is regarded as vulnerable.
Acclimatization of Cucumber (Cucumis sativus L.) Grafted Cuttings by Warming the Hypocotyl of the Rootstock in a Cold Chamber

Cuttings of cucumber (Cucumis sativus L.) grafted onto squash (Cucurbita moschata Duch.) rootstock using a hole-insertion graft were warmed at the hypocotyl of the rootstock in a cold chamber for acclimatization: they were soaked in water held at 31°C from the basal cut-end to the graft union at an air temperature of 12°C for 2 days. Warmed cuttings were planted and grown in an acclimatization chamber for 5 days. Control cuttings were planted immediately after grafting and grown in the chamber for 7 days. The fresh weight of the control scions decreased 2 days after grafting as a result of reduced water content, but that of warmed scions did not decrease. The fresh and dry weight of the warmed scions was 2.2 and 1.6 times that of the control, respectively, at 7 days after grafting. The graft development of warmed and control cuttings, evaluated based on the tensile strength, improved to a similar degree. The leaf conductance and chlorophyll fluorescence ratio (Fv/Fm) of the warmed scions, both of which indicate the degree of water stress, improved compared to those of the control at 7 days. These results demonstrate that the warming treatment does not adversely affect graft development but does reduce water stress at low air temperature during early acclimatization, and therefore improves early growth.
Ranking Marginal Influencers in a Target-labeled Network

Using social networks for spreading marketing information is a commonly used strategy to help in quick adoption of innovations, retention of customers and for improving brand awareness. In many settings, the set of entities in the network who must be the targets of such an information spread are already known, either implicitly or explicitly. It would still be beneficial to route the information to them through a carefully chosen set of influencers in the network. We term networks where we have such vertices labeled as targeted recipients as targeted networks. For instance, in an online marketing channel of a fashion product, where vertices are tagged with 'fashion' as their preferred choice of online shopping, forms a targeted network. In such targeted networks, how to select a small subset of vertices that maximizes the influence over target nodes while simultaneously minimizing the non-target nodes which get the information (e.g., to reduce their spam, or in some cases, due to costs)? We term this as the problem of maximizing the marginal influence over target networks and propose an iterative algorithm to solve this problem. We present the results of our experiment with large information networks, derived from English Wikipedia graph, which show that the proposed algorithm effectively identifies influential nodes that help reach pages identified through queries/topics. Qualitative analysis of our results shows that we can generate a semantically meaningful ranking of query-specific influential nodes.
Automated Detection of Sewer Pipe Defects Based on Cost-Sensitive Convolutional Neural Network

Regular inspection and repair of drainage pipes is an important part of urban construction. Currently, many classification methods have been used for defect diagnosis using images inside pipelines. However, most of these classification models train the classifier with the goal of maximizing accuracy without considering the unequal error classification cost in defect diagnosis. In this study, the authors analyze the characteristics of sewer pipeline defect detection and design an automated detection framework based on the cost-sensitive deep convolutional neural network (CNN). The method makes the CNN network cost sensitive by introducing learning theories at the structural and loss levels of the network. To minimize misclassification costs, the authors propose a new auxiliary loss function Cost-Mean Loss, which allows the model to obtain the original parameters of the network to maximize the accuracy and improve the performance of the model by minimizing total misclassification costs in the learning process. Theoretical analysis shows that the new auxiliary loss function can be applied to the classification task to optimize the expected value of misclassification costs. The inspection images collected from multiple drainage pipes were used to train and test the network. Results show that after the cost-sensitive strategy was added, the defect detection rate decreased from 2.1% to 0.45%. Moreover, the model with Cost-Mean Loss has better performance than the original model.
Absolute continuity of measures and preservation of Randomness

We continue to explore the relationship between notions of effective measure theory and properties of algorithmically random elements, as started in [1]. We prove a tight quantitative equivalence between effective versions of absolute continuity and preservation of randomness. We then relate these to the computability of the Radon-Nikodym derivative, as an element of L. In doing this we show how algorithmic randomness enables direct and short proofs when concerned with Lcomputability.
Spatial analysis linking landscape features and genetic population structure in cougars ($Puma concolor$) in the northern Rocky Mountains

Landscape genetics is a field of research that seeks to understand the drivers of the observed spatial distribution of genetic variation in a species of plant or animal using methods from population genetics, landscape ecology, geography, and spatial statistics. One of the important research areas in landscape genetics is to identify landscape barriers to genetic flow. Barriers can limit interaction of organisms and hence lead to genetic structure (i.e. frequency of genotypes) in a population that becomes increasingly spatially structured over time. Here, we investigate model-based spatial methods to assess the relationship between landscape and genotype distributions of cougars (Puma concolor) in Western North America. Previous research has assessed genetic differentiation in cougars in North America using a non-spatial Bayesian clustering model and found evidence of genetic population structure in cougars, with suggestive but indistinct spatial boundaries between subpopulations. To determine if including spatial information on samples in a classification model would refine the observed spatial signal within the genetic population structure, we applied Bayesian classification models to microsatellite loci data with associated spatial locations. The spatial model revealed two clearly differentiated cougar subpopulations, in contrast to the two overlapping subpopulations suggested by methods not accounting for space. We also explored through geographic information systems and generalized linear models whether resulting genetic population structure boundaries aligned with landscape features. The spatial correspondence of genetic subpopulations and a major river and road is suggestive of possible landscape barriers to cougar movement. This study demonstrates that the use of explicit spatial information and Bayesian classification models adds novel insight when investigating genetic population structure in a species.
Does glucocorticoid exposure explain the association between metabolic dysfunction and tendinopathy?

Background While metabolic health is acknowledged to affect connective tissue structure and function, the mechanisms are unclear. Glucocorticoids are present in almost every cell type throughout the body and control key physiological processes such as energy homeostasis, stress response, inflammatory and immune processes, and cardiovascular function. Glucocorticoid excess manifests as visceral adiposity, dyslipidemia, insulin resistance, and type 2 diabetes. As these metabolic states are also associated with tendinopathy and tendon rupture, it may be that glucocorticoids excess is the link between metabolic health and tendinopathy. Objective To synthesise current knowledge linking glucocorticoid exposure to tendon structure and function. Methods Narrative literature review. Results We provide an overview of endogenous glucocorticoid production, regulation, and signalling. Next we review the impact that oral glucocorticoid has on risk of tendon rupture and the effect that injected glucocorticoid has on resolution of symptoms. Then we highlight the clinical and mechanistic overlap between tendinopathy and glucocorticoid excess in the areas of visceral adiposity, dyslipidemia, insulin resistance and type 2 diabetes. In these areas, we highlight the role of glucocorticoids and how these hormones might underpin the connection between metabolic health and tendon dysfunction. Conclusions There are several plausible pathways through which glucocorticoids might mediate the connection between metabolic health and tendinopathy.
Varia Children ’ s Strategies in Approximate Quantification

Fifth and seventh graders were asked to provide a quick and rough estimate of the number of items in collections of 11—79 items. We collected verbal strategy reports and performance on each item. Results showed that: (a) participants used six different estimation strategies, (b) overall, fifth and seventh graders used the same set of strategies but varied in how often they used each strategy, (c) fifth graders’ strategy repertoire was smaller than seventh graders’, and (d) strategy selection varied as a function of children’s age, and of numerosities and configurations of items. These findings show that different processes are available for approximate quantification in both fifth and seventh graders, and document age-related differences in children’s approximate quantification. Des enfants de 10 et 12 ans ont été testés sur une tâche de quantification approximative, consistant à donner le nombre approximatif de points contenus dans des grilles de 10x10. Nous avons collecté plusieurs indicateurs comportementaux des performances : les protocoles verbaux, les latences et la précision des réponses. Les résultats ont montré que : (a) les enfants utilisaient six stratégies différentes d’estimation, (b) globalement, les enfants des deux groupes d’âge disposaient du même répertoire stratégique mais se distinguaient sur la fréquence d’utilisation de chacune de ces stratégies, (c) les enfants de 10 ans utilisaient, en moyenne, moins de stratégies que les enfants de 12 ans, et (d) la sélection stratégique variait en fonction de l’âge des enfants et des caractéristiques des configurations (disposition spatiale des items et Children’s Strategies in Approximate Quantification Current psychology letters, Vol. 26, Issue 1, 2010 | 2010 16
Structure and dynamics of multicellular assemblies measured by coherent light scattering

Determining the structure and the internal dynamics of tissues is essential to understand their functional organization. Microscopy allows for monitoring positions and trajectories of every single cell. Those data are useful to extract statistical observables, such as intercellular distance, tissue symmetry and anisotropy, and cell motility. However, this procedure requires a large and supervised computational effort. In addition, due to the large cross-section of cells, the light scattering limits the use of microscopy to relatively thin samples. As an alternative approach, we propose to take advantage of light scattering and to analyze the dynamical diffraction pattern produced by a living tissue illuminated with coherent light. In this article, we illustrate with a few examples that supra-cellular structures produce an exploitable diffraction signal. From the diffraction signal, we deduce the mean distance between cells, the anisotropy of the supra-cellular organization and, from its fluctuations, the mean speed of moving cells. This easy to implement technique considerably reduces analysis time, allowing real time monitoring.
How can social robots spark collaboration and engagement among people with intellectual disability?

Social robots have been successfully used in previous research to develop social behaviours among participants with Autism Spectrum Disorder (ASD). Technology has often been found to be a contributing factor to heightened engagement in learning activities, including for people with intellectual disability. This research proposes to build on these two opportunities by exploring the potential of social robots to elicit social interaction, cooperation and engagement among groups of adults with intellectual disability. The study presented here involved observation, semi structured interviews and video analysis of six participants with intellectual disability interacting with a social robot in a series of five weekly workshops. The robot used for this study was Cozmo ©, a small AI toy robot with a vehicular appearance and movement, and animated eyes that it uses to display human emotions. Participants played games with Cozmo and took turns in controlling its movements in small groups. Through an inductive thematic analysis we identified themes of collaboration, competition, positive affect and attitudes of participants as well as the factors that affected their engagement with Cozmo. We detail characteristic behaviours within each theme. The study found that interacting with Cozmo resulted in positive affect, high engagement and collaboration. The aspects of Cozmo that had the most positive impact were the ability to play games with it and its humanlike relatable behaviour.
Measures of care fragmentation: Mathematical insights from population genetics.

OBJECTIVE To identify novel properties of health care fragmentation measures, drawing on insights from mathematically equivalent measures of genetic diversity. STUDY DESIGN We describe mathematical relationships between two measures: (a) Breslau's Usual Provider of Care (UPC), the proportion of care with the most frequently visited provider, analogous to the "frequency of the most frequent allele" at a genetic locus; and (b) Bice-Boxerman's Continuity of Care Index (COCI), a measure of care dispersion across multiple providers, analogous to "Nei's estimator of homozygosity" in genetics. PRINCIPAL FINDINGS Just as the frequency of the most frequent allele places a tight constraint on homozygosity, the proportion of care with the most frequently visited provider (UPC) places lower and upper bounds on dispersion of care (COCI), and vice versa. This property presents the possibility of a normalized COCI given UPC (NCGU) measure, which reflects a bounded range of care dispersion dependent on the number of visits with the most frequently visited provider. Mathematical aspects of UPC and COCI also suggest thresholds for the minimal number of patient visits to use when studying fragmentation. CONCLUSIONS Applying knowledge from population genetics elucidated relationships between care fragmentation measures and produced novel insights for care fragmentation studies.
A Revisionist Model of Suburbanization and Sprawl

This article proposes a process-based conceptual model that explains sprawl in the United States since the 1970s. In contrast to traditional explanations that look to “natural,” or ecological, processes, our explanation of sprawl focuses on the local regulatory environment and the ways in which residents and homebuilders respond to it. We look at the way in which growth controls—given fragmentation—produce “spillovers” and whether spillovers have been a principal force (process) fueling suburbanization and exurbanization in recent decades. Although the role of spillovers has received some attention recently, few scholars have launched comprehensive analyses of its impact on the contemporary urban landscape. Our spillovers-based explanation of sprawl will likely hold for metropolitan regions in which growth management/control has been imposed in the absence of statewide or regionwide coordination.
Working papers in transport , tourism , information technology and microdata analysis Predicting entry of Swedish wholesale firms into local markets

Applying microeconomic theory, we develop a forecasting model for firm entry into local markets and test this model using data from the Swedish wholesale industry. The empirical analysis is based on directly estimating the profit function of wholesale firms. As in previous entry studies, profits are assumed to depend on firmand location-specific factors, and the profit equation is estimated using panel data econometric techniques. Using the residuals from the profit equation estimations, we identify local markets in Sweden where firm profits are abnormally high given the level of all independent variables included in the profit function. From microeconomic theory, we then know that these local markets should have higher net entry than other markets, all else being equal, and we investigate this in a second step, also using a panel data econometric model. The results of estimating the net-entry equation indicate that four of five estimated models have more net entry in high-return municipalities, but the estimated parameter is only statistically significant at conventional levels in one of our estimated models.
Question Answering on SQuAD

This is version 1 of the 2019 Default Final Project handout. It was released on Thursday February 7 to help students write their project proposals. We will release a final version of this document (version 2), including leaderboard submission instructions, no later than Thursday February 21. In the meantime, this document may undergo minor updates (check timestamp to ensure you have the latest version).
Does organic school food service provide more healthy eating environments than their non organic counterparts

Organic food strategies are increasingly developing within European school food services at the same time as these services are being involved in measures aiming at promoting healthy eating at school and counteracting obesity. Schools have an important role to play in teaching children fundamental life skills, including good food habits according to a number of authoritative policy papers from Council of Europe, the WHO and the EU platform. Although there are great national differences, European school food culture seems to be in a transitional state in which both healthy eating as well as sustainable consumption strategies are contributing to shaping the future school food culture. It is therefore imperative to study how these changes in agendas influences each other and to study the associations between healthy eating and organic supply strategies at school. This has been the point of departure for Working Package 5 (WP5): Nutrition and Health. The WP5 study has included Denmark, Norway, Germany, Finland and Italy. The WP has been asking questions about the possible spin offs and ramification on nutrition and health that the emerging public organic food strategies might have had. The WP is a part of the project “innovative Public Organic food Procurement for Youth” (iPOPY) and the WP5 has been carried out by Aalborg University Denmark. The research presented here has been conducted in Germany, Finland, and Italy.
Sites and sources of sympathoexcitation in obese male rats: role of brain insulin.

In males, obesity increases sympathetic nerve activity (SNA), but the mechanisms are unclear. Here, we investigate insulin, via an action in the arcuate nucleus (ArcN), and downstream neuropathways, including melanocortin receptor 3/4 (MC3/4R) in the hypothalamic paraventricular nucleus (PVN) and dorsal medial hypothalamus (DMH). We studied conscious and α-chloralose-anesthetized SD rats fed a high fat diet, in which obesity prone (OP) rats accrue excess fat, whereas obesity resistant (OR) rats maintain fat content like rats eating a standard control (CON) diet. Nonspecific blockade of the ArcN with muscimol, and specific blockade of ArcN insulin receptors (InsR), decreased lumbar SNA (LSNA), heart rate (HR), and mean arterial pressure (MAP) in OP rats, but not OR/CON, rats, indicating that insulin supports LSNA in obese males. In conscious rats, intracerebroventricular insulin infusion increased MAP only in OP rats, and also improved HR baroreflex function from subnormal to supranormal. The brain sensitization to insulin may elucidate how insulin can drive central SNA pathways, when transport of insulin across the blood-brain barrier may be impaired. Blockade of PVN, but not DMH, MC3/4R with SHU9119 decreased LSNA, HR, and, MAP in OP, but not OR/CON, rats. Interestingly, PVN nanoinjection of the MC3/4R agonist, MTII, increased LSNA only in OP rats, similarly to PVN MTII-induced increases in LSNA in CON rats after blockade of sympathoinhibitory Neuropeptide Y Y1 receptors. ArcN InsR expression was not increased in OP rats. Collectively, these data indicate that obesity increases SNA in part via increased InsR signaling and downstream PVN MC3/4R.