Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunological Mechanisms Explaining the Role of Vaccines, IgE, Mast Cells, Histamine, Elevating Ferritin, IL-6, D-dimer, VEGF Levels in COVID-19 and Dengue, Potential Treatments Such as Mast Cell Stabilizers, Antihistamines: Predictions and Confirmations

A novel coronavirus, SARS-CoV-2 was identified in Wuhan, China. The disease caused by the virus can range in severity from asymptomatic to acute respiratory distress syndrome (ARDS) and death. Primary dengue infection results in IgE mediated sensitization against dengue virus proteins. These IgE bind to receptors on mast cells. Upon subsequent exposure to the antigen recognized by the IgE, mast cell degranulation occurs releasing mediators such as histamine. Therefore secondary dengue infection results in urticaria, increased vascular permeability, hypotension, dengue hemorrhagic fever and dengue shock syndrome. A case of “slow rolling anaphylaxis”. Vaccines contain proteins derived from coronavirus infected animals as well as other proteins with high homology to SARS-CoV-2. So one could develop IgE mediated sensitization to SARS-CoV-2-like proteins. Therefore, receipt of such vaccines acts like a dengue “primary infection”. It results in IgE mediated sensitization. Subsequent SARS-CoV-2 infection becomes a “secondary dengue infection” that has a severe course due to IgE mediated mast cell degranulation and the immune cascade that follows. There are many common observations between COVID-19 and dengue. Elevated levels of ferritin, interleukin-6, vascular endothelial growth factor, D-dimer, coagulopathy, urticaria and ARDS are reported in both diseases. Numerous teams have now confirmed this mechanism that was predicted in Jan 2020, upon analyzing the 2019-nCoV proteome. There are many indicators that mast cell degranulation and histamine release have a major role in COVID-19, dengue and influenza severity. Mast cell stabilizers, antihistamines and anti-parasite treatments may address different aspects of this cascade and thus reduce disease severity.
Applications of Memory-Based learning to spoken dialogue system development

This thesis introduces a new Spoken Dialogue System (SDS) development tool called the Generalising Memory-Based Learner (GMBL). The principle components and techniques, namely Hierarchical Hidden Markov Models (HHMM) and Memory-Based Learning (MBL), are described. We will argue that GMBL is an elegant, fast and intuitive way of constructing SDSs capable of answering questions and responding to commands that control connected equipment. Expediting the building of SDSs is the primary focus. It is argued that GMBL is elegant by virtue of the regular, modular nature of the HHMMs used extensively throughout its architecture. These HHMM modules are straightforward to visualise and are easily comprehensible to developers, thus making development intuitive and simple. The ease of SDS construction was evaluated by having a developer construct a train timetable application using GMBL, from a specification in a previous experiment. GMBL was clearly faster than a hand-coded application but was comparable though slightly slower than the reference system. With further development, this hierarchical memory-based paradigm shows promise for practical dialogue system development. The usability of a GMBL-developed SDS was empirically evaluated by having participants use two interfaces to a simulation of an automated house. The GMBL-developed speech interface was compared with a conventional handheld remote control style interface. This experiment found that user satisfaction of the GMBL-developed speech interface compared well with the remote control interface and in general users successfully completed more tasks more quickly using the GMBL-developed interface. The technical contributions of this thesis include demonstrations of novel applications for HHMMs in Spoken Dialogue Systems, novel ways of constructing HHMM topologies, and new modifications to HHMM that increase their power of representation when applied to adjacency pairs (question-answering) and instruction-action pairs. In conclusion GMBL does demonstrate the promise of hierarchical memory-based learning architectures for dialogue modelling, although there were difficulties with minimising developer effort, not all of which were resolved satisfactorily. This work further highlights the under-reporting of development effort in dialogue modelling literature and argues that the developer, rather than the user, should be the crucial stakeholder in natural language system development.
Astyanax henseli, a new name for Tetragonopterus aeneus Hensel, 1870 from southern Brazil (Teleostei: Characiformes)

Tetragonopoterus aeneus Hensel (1870) is removed from synonymy with Astyanax fasciatus (Cuvier, 1819), revalidated and redescribed as A. henseli to avoid homonymy. Astyanax henseli differs from A. fasciatus stricto sensu and other Astyanax species by the presence of two to four maxillary teeth, two vertically-elongated humeral spots, dentary tooth cusps positioned close to one another, and the slender form of the dentary teeth.
Predictive Learning Analytics "At Scale": Towards Guidelines to Successful Implementation in Higher Education Based on the Case of the Open University UK.

Predictive Learning Analytics (PLA) aim to improve learning by identifying students at risk of failing their studies. Yet, little is known about how best to integrate and scaffold PLA initiatives into higher education institutions. Towards this end, it becomes essential to capture and analyze the perceptions of relevant educational stakeholders (i.e., managers, teachers, students) about PLA. This paper presents an “at scale” implementation of PLA at a distance learning higher education institution and details, in particular, the perspectives of 20 educational managers involved in the implementation. It concludes with a set of recommendations about how best to adopt and apply large-scale PLA initiatives in higher education.
Predicting global abundance of a threatened species from its occurrence: implications for conservation planning

Aim Global abundance is an important characteristic of a species that is correlated with geographical distribution and body size. Despite its importance these estimates are not available since reliable field estimates are either expensive or difficult to obtain. Based on the relationship between a species’ local abundance and distribution, some authors propose that abundance can be obtained through spatial distribution data from maps plotted at different scales. This has never been tested over the entire geographical range of a species. Thus, the aim of this study was to estimate global abundance of the Neotropical primate Brachyteles hypoxanthus (northern muriqui) and compare the results with available field estimates.
Benzoic Acid and Derivatives

The article contains sections titled: 1. Introduction 2. Physical Properties 3. Chemical Properties 4. Production 5. Quality Specifications 6. Storage, Transportation and Legal Aspects 7. Uses and Economic Aspects 8. Derivatives of Benzoic Acid 8.1. Salts of Benzoic Acid 8.2. Esters of Benzoic Acid 8.3. Benzoyl Chloride 8.4. Benzonitrile 8.5. Alkyl and Acyl Analogues 8.6. Chlorobenzoic Acids 8.7. Aminobenzoic Acids 8.8. Nitrobenzoic Acids 8.9. 3-Sulfobenzoic Acid 8.10. Hexahydrobenzoic Acid 9. Toxicology
GENETIC DIVERSITY IN F1 DESCENDENTS OF Cereus peruvianus Mill. (Cactaceae) SOMACLONES REGENERATED IN SOUTH REGION OF BRAZIL (DIVERSIDAD GENÉTICA EN DESCENDENCIA F1 DE SOMACLONES DE Cereus peruvianus Mill. (Cactaceae) REGENERADO EN LA REGIÓN SUR DE BRASIL)

SUMMARY Polymorphism in the Cereus peruvianus somaclones (S) and the relationships among their F1 descendents (R1 plants) were detected and examined by RAPD markers. Sixteen primers yielded repetitive patterns for all scored bands in four somaclones (S3, S9, S48 and S71 plants) and in 14 R1 plants of S3, 11 R1 plants of S9, 8 R1 plants of S48 and 14 R1 plants of S71. The 16 primers generated 222 reproducible fragments of which 65 were polymorphic in R0 plants and 103, 100, 80 and 108 were polymorphic in R1 plants of S3, S9, S48 and S71, respectively. Total number of polymorphic bands for the R1 plants from four somaclones was 124. Polymorphism in R1 plants (55.9%) was higher than the polymorphism detected in R0 plants (29,8%). Polymorphism between somaclones may result from genetic variability in vitro induced since S3, S9, S48 and S71 somaclones were independently regenerated from different callus tissues, and the polymorphism between R1 plants may result from the genetic constitution of the male and female parent of the F1 descendents, since R1 plants were obtained from seeds of somaclones collected from open-pollinated S3, S9, S48 and S71 plants. Dendrogram generated by Jaccard coefficient showed that there was no grouping of R1 plants according to parental somaclone and that the similarity in R1 plants ranged from 72.5% to 90.5%. This fact supports our hypothesis that in vitro induced variability may be used for broadening the genetic base of C. peruvianus species.
The leaf economics spectrum and the prediction of photosynthetic light–response curves

Summary 1. In this paper we determine whether interspecific variation in entire photosynthetic light–response curves correlates with the leaf traits of the ‘leaf economics spectrum’ (LES) and the degree to which such traits can predict interspecific variation in light–response curves. This question is important because light–response curves are included in many ecosystem models of plant productivity and gas exchange but such models do not take into account interspecific variation in such response curves. 2. We answer this question using original observations from 260 leaves from 130 plants of 65 different species of herbaceous (25) and woody (40) angiosperms. Herbs were grown in growth chambers and gas exchange measurements were taken in the laboratory. Leaf traits and gas exchange measurements for the woody plants were taken in the field. Leaf traits measured were leaf mass per area (LMA), leaf nitrogen concentration (N) and leaf chlorophyll concentration (Chl). We fitted the Mitscherlich and Michaelis–Menten equations of the light–response curve separately for each leaf. This gave (for the Mitscherlich equation) the light compensation point (ϕ), the quantum yield at the light compensation point (q(ϕ)), and maximum net photosynthesis (Amax) and (for the Michaelis–Menten equation), the maximum gross photosynthesis (Gmax), the half saturation coefficient (k) and the dark respiration rate (Rd). 3. Amax and q(ϕ) were highly correlated with the measured leaf traits but ϕ was not. All three parameters of the Michaelis–Menten equations were correlated with the leaf traits. Allometric equations predicting the parameters of the Mitscherlich and Michaelis–Menten equations by N and LMA are presented. Replacing the leaf-specific parameters by these general allometric equations based on leaf N and LMA gave good predictions of net photosynthetic rates over the entire range of irradiance (r = 0·79–0·98) but with a downward bias for the herbs when the most general allometric equations are used. 4. These results further extend the generality of the LES and may allow available information from large leaf trait data bases to be incorporated into ecosystem models of plant growth and gas exchange.
Ecological biogeography

In this article, I first review recent developments in biogeography, after which I discuss some attempts at synthesis. The main body of the article, however, is devoted to the conception of ranges in terms of physiological responses to environmental variation. Because of this variation, such deterministic responses have to be described in stochastic terms in the case of local processes. Moreover, because of the same variation, species ranges will change location, size, and shape all the time, whereas internally their numerical structure shows up their dynamic nature. Ranges, therefore, are to be conceived as processes rather than as patterns, as they have been for long in the past.
Water use and yield of bioenergy poplar in future climates: modelling the interactive effects of elevated atmospheric CO2 and climate on productivity and water use

Vegetation exerts large control on global biogeochemical cycles through the processes of photosynthesis and transpiration that exchange CO2 and water between the land and the atmosphere. Increasing atmospheric CO2 concentrations exert direct effects on vegetation through enhanced photosynthesis and reduced stomatal conductance, and indirect effects through changes in climatic variables that drive these processes. How these direct and indirect CO2 impacts interact with each other to affect plant productivity and water use has not been explicitly analysed and remains unclear, yet is important to fully understand the response of the global carbon cycle to future climate change. Here, we use a set of factorial modelling experiments to quantify the direct and indirect impacts of atmospheric CO2 and their interaction on yield and water use in bioenergy short rotation coppice poplar, in addition to quantifying the impact of other environmental drivers such as soil type. We use the JULES land‐surface model forced with a ten‐member ensemble of projected climate change for 2100 with atmospheric CO2 concentrations representative of the A1B emissions scenario. We show that the simulated response of plant productivity to future climate change was nonadditive in JULES, however this nonadditivity was not apparent for plant transpiration. The responses of both growth and transpiration under all experimental scenarios were highly variable between sites, highlighting the complexity of interactions between direct physiological CO2 effects and indirect climate effects. As a result, no general pattern explaining the response of bioenergy poplar water use and yield to future climate change could be discerned across sites. This study suggests attempts to infer future climate change impacts on the land biosphere from studies that force with either the direct or indirect CO2 effects in isolation from each other may lead to incorrect conclusions in terms of both the direction and magnitude of plant response to future climate change.
Using Process Data to Evaluate Scientific Inquiry Practice in Technology-Enhanced Assessment

This paper investigates differences in students having various scores when designing controlled experiments in two types of scientific inquiry tasks (a fair test and an exhaustive test). We measure temporal features of preparation time and execution time, which reflect respectively the process of question understanding and answer planning and that of executing the control-of-variables strategy in answer formulation. We also measure mean execution time per answering event to reflect the efficiency of answering events. Results show that: in the fair test, the full score students showed less execution time than the lowest score ones; in the exhaustive test, the full score students showed more execution time than the lowest score ones; but in both tests, the high-performing students had less mean execution time than the low-performing ones. These results reveal that despite test differences, students who appropriately apply the control-of-variables strategy in these tests are more goal-directed and efficient in planning and executing response strategies than those who fail to do so. This study provides process-based features and large-scale evidence of scientific inquiry practice in in educational assessment.
Unlocking Inverse Problems Using Deep Learning: Breaking Symmetries in Phase Retrieval

In many physical systems, inputs related by intrinsic system symmetries generate the same output. So when inverting such systems, an input is mapped to multiple symmetry-related outputs. This causes fundamental difﬁculties for tackling these inverse problems by the emerging end-to-end deep learning approach. Taking phase retrieval as an illustrative example, we show that careful symmetry breaking on the training data can help get rid of the difﬁculties and signiﬁcantly improve learning performance in real data experiments. We also extract and highlight the underlying mathematical principle of the proposed solution, which is directly applicable to other inverse problems
Use of Morphology and CO1 Barcoding to Test the Validity of Tetraopes huetheri Skillman (Coleoptera: Cerambycidae)

Tetraopes huetheri Skillman, 2007 was recently described from far western South Dakota and adjacent Wyoming. It was initially diagnosed by the combination of small size, prominent pronotal tubercles, an elevated umbone, appendiculate tarsal claws, and lack of elytral chevron. The small size was thought related to the host plant, whorled milkweed (Asclepias verticillata L.; Asclepiadaceae), which has a very slender stem. The discovery of T. huetheri in a well-studied genus from the northern Great Plains generated considerable interest, especially since the main institutional collections in South Dakota, Wyoming, and adjacent Montana did not hold any specimens of the new find. Therefore, when three of us (FEE, MAI, PJJ) were in the area of the type locality 18–23 July 2011, we made a special effort to collect specimens to obtain representatives for morphological comparison and DNA extraction. Specimens that matched the description were taken on swamp milkweed (Asclepias incarnata L.) and common milkweed (Asclepias syriaca L.) at the type locality. A search of A. verticillata did not yield any specimens. During this time period, similar specimens were collected at a few sites in southeastern Montana, and upon comparison with material in the Montana Entomology Collection at Montana State University, comparable specimens were found to have been taken as far west as Madison Co., Montana. However, upon close examination, both the fresh and museum specimens disagreed with the original description of T. huetheri in the form of the tarsal claws. Skillman’s (2007) description used appendiculate tarsal claws as a diagnostic character, but the new specimens all had bifid tarsal claws (Linsley and Chemsak 1984, Fig. 2). This character is the first in Chemsak and Noguera’s (2004) key to species of Tetraopes Dalman and is critical to placement of the species. However, in every other way, the new material matched the detailed description of T. huetheri, but superficially they also seemed to be small specimens of the widespread Tetraopes annulatus LeConte.
USE OF LECTINS TO CHARACTERISE GENETIC VARIABILITY AND GEOGRAPHIC DIFFERENTIATION IN NATURAL POPULATIONS OF Thunnus alalunga (Bonn. 1788)

SUMMARY New tools from cell and molecular biology can be used to implement the knowledge of fish biology and fisheries. In this sense, we suggest that the use of lectins can be an understandable procedure to study population structure of fishes. Lectins are proteins or glycoproteins of nonimmune origin that agglutinate cells and/or precipitate complex carbohydrates. Several lectins behave like blood group antibodies and can be used as specific gene markers. We characterise blood groups of Thunnus alalunga worldwide populations under a population genetics point of view using lectins. Fishes from several populations of Mediterranean Sea, Atlantic, Pacific and Indian Oceans were captured and 5 mL blood was obtained from each fish. Each fish was treated with 8 FITC-labelled lectins. The binding activity of the lectins was detected using a fluorescence assay. Several statistical procedures of populations genetics were employed to analyse genetic variability, geographic differentiation, and genetic distance showing that: i) there is genetic variability within Thunnus alalunga populations, ii) we detect highly significant heterogeneity among populations, and considerable geographic differentiation, iii) Mediterranean population is quite distant of North Atlantic population, iv) North and South Atlantic populations are extremely distant, v) Pacific population is the most distant from the others , vi) Gulf of Guinea and South Atlantic populations are distant, vii) Gulf of Guinea and North Atlantic are proximate, viii) Indian and South Atlantic populations are also proximate. RESUME
Learning Spectral Regularizations for Linear Inverse Problems

One of the main challenges in linear inverse problems is that a majority of such problems are ill-posed in the sense that the solution does not depend on the data continuously. To analyze this effect and reestablish a continuous dependence, classical theory in Hilbert spaces largely relies on the analysis and manipulation of the singular values of the linear operator and its pseudoinverse with the goal of, on the one hand, keeping the singular values of the reconstruction operator bounded, and, on the other hand, approximating the pseudoinverse sufﬁciently well for a given noise level. While classical regularization methods manipulate the singular values via explicitly deﬁned functions, this paper considers learning such parameter choice rules in such a way, that one obtains higher quality reconstruction results while still remaining in a setting of provably convergent spectral regularization methods. We discuss different ways of parametrizing our spectral regularization methods via neural networks, interpret existing feed forward networks in the setting of spectral regularization which can become provably convergent via an additional projection, and ﬁnally demonstrate their superiority in 1d numerical examples.
A new centrality measure for identifying influential nodes in social networks

The identification of central nodes has been a key problem in the field of social network analysis. In fact, it is a measure that accounts the popularity or the visibility of an actor within a network. In order to capture this concept, various measures, either sample or more elaborate, has been developed. Nevertheless, many of “traditional” measures are not designed to be applicable to huge data. This paper sets out a new node centrality index suitable for large social network. It uses the amount of the neighbors of a node and connections between them to characterize a “pivot” node in the graph. We presented experimental results on real data sets which show the efficiency of our proposal.
Enterprise maturity models: a systematic literature review

ABSTRACT Maturity models (MM) have been used by different enterprise segments. However, while many MM have been developed, few have been validated because of the lack of studies that demonstrate how to classify model levels. This study investigates the literature that presents assessment models for classifying maturity levels as well as the development of the research area. A systematic literature review was carried out, finding 409 relevant papers and a list of the few methods for classifying the maturity level. This review enabled us to update the state of the art on MM and identify gaps that may prompt future research.
THE EFFECT OF DAM PARITY ON PROGENY GROWTH PERFORMANCE, PASSIVE IMMUNITY, AND GASTROINTESTINAL MICROBIOTA

Previous research has shown that parity (P) 4 progeny have greater weaning weights and decreased microbial diversity. The objective of this experiment was to evaluate litter performance, passive immunity, and fecal microbiota among P1 (n = 56) and P3 (n = 49) dams and their progeny. Blood samples were collected from P1 and P3 dams on d 90 and 114 of gestation and d 0 of lactation and from their progeny (n = 4 pigs/litter) on d 0, 7, and 14 of lactation. Colostrum/milk samples were collected from dams on d 0, 7, and 14 of lactation. Fecal samples were collected from dams (d 7) and their progeny (n = 4 pigs/litter; d 0, 7, and 14 of lactation). Serum and milk samples were analyzed for immunoglobulin (Ig; G and A) concentrations via ELISA. Microbial fingerprinting of fecal samples from dams and progeny were performed via DGGE. No differences were observed between parities in total born, live born, mummies, deaths, or total weaned. A greater number of stillborns (P 0.50). Litter performance and transfer of passive immunity are affected by dam parity.