Miracle-dz/UniFAR-FTUs huggingface dataset:
Sage: Parallel Semi-Asymmetric Graph Algorithms for NVRAMs

Non-volatile main memory (NVRAM) technologies provide an attractive set of features for large-scale graph analytics, including byte-addressability, low idle power, and improved memory-density. NVRAM systems today have an order of magnitude more NVRAM than traditional memory (DRAM). NVRAM systems could therefore potentially allow very large graph problems to be solved on a single machine, at a modest cost. However, a significant challenge in achieving high performance is in accounting for the fact that NVRAM writes can be much more expensive than NVRAM reads. In this paper, we propose an approach to parallel graph analytics using the Parallel Semi-Asymmetric Model (PSAM), in which the graph is stored as a read-only data structure (in NVRAM), and the amount of mutable memory is kept proportional to the number of vertices. Similar to the popular semi-external and semi-streaming models for graph analytics, the PSAM approach assumes that the vertices of the graph fit in a fast read-write memory (DRAM), but the edges do not. In NVRAM systems, our approach eliminates writes to the NVRAM, among other benefits. To experimentally study this new setting, we develop Sage, a parallel semi-asymmetric graph engine with which we implement provably-efficient (and often work-optimal) PSAM algorithms for over a dozen fundamental graph problems. We experimentally study Sage using a 48-core machine on the largest publicly-available real-world graph (the Hyperlink Web graph with over 3.5 billion vertices and 128 billion edges) equipped with Optane DC Persistent Memory, and show that Sage outperforms the fastest prior systems designed for NVRAM. Importantly, we also show that Sage nearly matches the fastest prior systems running solely in DRAM, by effectively hiding the costs of repeatedly accessing NVRAM versus DRAM.
Bayesian Surface Warping Approach for Rectifying Geological Boundaries Using Displacement Likelihood and Evidence from Geochemical Assays

This article presents a Bayesian framework for manipulating mesh surfaces with the aim of improving the positional integrity of the geological boundaries that they seek to represent. The assumption is that these surfaces, created initially using sparse data, capture the global trend and provide a reasonable approximation of the stratigraphic, mineralization, and other types of boundaries for mining exploration, but they are locally inaccurate at scales typically required for grade estimation. The proposed methodology makes local spatial corrections automatically to maximize the agreement between the modeled surfaces and observed samples. Where possible, vertices on a mesh surface are moved to provide a clear delineation, for instance, between ore and waste material across the boundary based on spatial and compositional analysis using assay measurements collected from densely spaced, geo-registered blast holes. The maximum a posteriori (MAP) solution ultimately considers the chemistry observation likelihood in a given domain. Furthermore, it is guided by an a priori spatial structure that embeds geological domain knowledge and determines the likelihood of a displacement estimate. The results demonstrate that increasing surface fidelity can significantly improve grade estimation performance based on large-scale model validation.
Augmenting reality: On the shared history of perceptual illusion and video projection mapping

Perceptual illusions based on the spatial correspondence between objects and displayed images have been pursued by artists and scientists since the 15th century, mastering optics to create crucial techniques as the linear perspective and devices as the Magic Lantern. Contemporary video projection mapping inherits and further extends this drive to produce perceptual illusions in space by incorporating the required real time capabilities for dynamically superposing the imaginary onto physical objects under fluid real world conditions. A critical milestone has been reached in the creation of the technical possibilities for all encompassing, untethered synthetic reality experiences available to the plain senses, where every surface may act as a screen and the relation to everyday objects is open to alterations.
Analyzing COVID-19 on Online Social Media: Trends, Sentiments and Emotions

At the time of writing, the ongoing pandemic of coronavirus disease (COVID-19) has caused severe impacts on society, economy and people's daily lives. People constantly express their opinions on various aspects of the pandemic on social media, making user-generated content an important source for understanding public emotions and concerns. In this paper, we perform a comprehensive analysis on the affective trajectories of the American people and the Chinese people based on Twitter and Weibo posts between January 20th, 2020 and May 11th 2020. Specifically, by identifying people's sentiments, emotions (i.e., anger, disgust, fear, happiness, sadness, surprise) and the emotional triggers (e.g., what a user is angry/sad about) we are able to depict the dynamics of public affect in the time of COVID-19. By contrasting two very different countries, China and the Unites States, we reveal sharp differences in people's views on COVID-19 in different cultures. Our study provides a computational approach to unveiling public emotions and concerns on the pandemic in real-time, which would potentially help policy-makers better understand people's need and thus make optimal policy.
Seamlessly Integrating Loops That Matter into Model Development and Analysis

Understanding why models behave the way they do is critical to learning from them, and to conveying the insights they offer to a broad audience. The Loops that Matter methodology automatically shows which loops are dominating behavior at each point in time and generates simplified causal loop diagrams from a user adjustable set of important loops. This paper describes the challenges of implementing these tools into a fully functioning model development environment along with the solutions developed. The promise of the tools has, if anything, been amplified by the results of this implementation, and we give several examples of using the tools. For pedagogical models Loops that Matter can ease communication while speeding and deepening learning. For complex models the tools allow the extraction of realistic explanations of behavior in the form of animated simplified causal loop diagrams. For models with discrete and discontinuous elements, the bigger feedback picture is still easily discoverable. While there will doubtless be refinements and enhancement to the delivered tools, they represent a large step forward in our ability to understand models from conceptualization through delivery.
Learning From Context-Agnostic Synthetic Data

We present a new approach for synthesizing training data given only a single example of each class. Rather than learn over a large but fixed dataset of examples, we generate our entire training set using only the synthetic examples provided. The goal is to learn a classifier that generalizes to a non-synthetic domain without pretraining or fine-tuning on any real world data. We evaluate our approach by training neural networks for two standard benchmarks for real-world image classification: on the GTSRB traffic sign recognition benchmark, we achieve 96% test accuracy using only one clean example of each sign on a blank background; on the MNIST handwritten digit benchmark, we achieve 90% test accuracy using a single example of each digit taken from a computer font. Both these results are competitive with state-of-the-art results from the few-shot learning and domain transfer literature, while using significantly less data.
Harbsafe-162. A Domain-Specific Data Set for the Intrinsic Evaluation of Semantic Representations for Terminological Data

The article presents Harbsafe-162, a domain-specific data set for evaluating distributional semantic models. It originates from a cooperation by Technische Universitat Braunschweig and the German Commission for Electrical, Electronic & Information Technologies of DIN and VDE, the Harbsafe project. One objective of the project is to apply distributional semantic models to terminological entries, that is, complex lexical data comprising of at least one or several terms, term phrases and a definition. This application is needed to solve a more complex problem: the harmonization of terminologies of standards and standards bodies (i.e. resolution of doublettes and inconsistencies). Due to a lack of evaluation data sets for terminological entries, the creation of Harbsafe-162 was a necessary step towards harmonization assistance. Harbsafe-162 covers data from nine electrotechnical standards in the domain of functional safety, IT security, and dependability. An intrinsic evaluation method in the form of a similarity rating task has been applied in which two linguists and three domain experts from standardization participated. The data set is used to evaluate a specific implementation of an established sentence embedding model. This implementation proves to be satisfactory for the domain-specific data so that further implementations for harmonization assistance may be brought forward by the project. Considering recent criticism on intrinsic evaluation methods, the article concludes with an evaluation of Harbsafe-162 and joins a more general discussion about the nature of similarity rating tasks. Harbsafe-162 has been made available for the community.
A rank-3 network representation for single-affiliation systems

Single-affiliation systems are observed across nature and society. Examples include collaboration, organisational affiliations, and trade-blocs. The study of such systems is commonly approached through network analysis. Multilayer networks extend the representation of network analysis to include more information through increased dimensionality. Thus, they are able to more accurately represent the systems they are modelling. However, multilayer networks are often represented by rank-4 adjacency tensors, resulting in a N2M2 solution space. Single-affiliation systems are unable to occupy the full extent of this space leading to sparse data where it is difficult to attain statistical confidence through subsequent analysis. To overcome these limitations, this paper presents a rank-3 tensor representation for single-affiliation systems. The representations is able to maintain full information of single-affiliation networks in directionless networks, maintain near full information in directed networks, reduce the solution space it resides in (N2M) leading to statistically significant findings, and maintain the analytical capability of multilayer approaches. This is shown through a comparison of the rank-3 and rank-4 representations which is performed on two datasets: the University of Bath departmental journal co-authorship 2000-2017 and an Erdos-Renyi network with random single-affiliation. The results demonstrate that the structure of the network is maintained through both representations, while the rank-3 representation provides greater statistical confidence in node-based measures, and can readily show inter- and intra-affiliation dynamics.
Characterization of the Prolactin Receptor 3(PRLR3) and Retinol-Binding Protein 4(RBP4) Genes in the Birth Weight and Early Growth of Berkshire Pigs

To investigate the influences of candidate genes on the birth weight and the early stages of life, genotyping of the prolactin receptor 3 (PRLR3) and retinol-binding protein 4 (RBP4) genes was performed in 156 and 141 Berkshire pigs, respectively. The frequency of both PRLR3 alleles A and a was 0.50. The frequencies of the RBP4 alleles B and b were 0.42 and 0.58, respectively. Neither locus was in Hardy-Weinberg equilibrium. No significant associations of the PRLR3 alleles with birth or weaning weights and of the RBP4 alleles with birth weight were observed. The proportions of the phenotype variances due to the genotypes of PRLR3 in the feeder weights was 4.0% and those of RBP4 in the weaning and feeder weights were 11.9 and 3.3%, respectively (P < 0.05). The dominance effect of PRLR3 and RBP4 on feeder weights was 2.40 and 1.86 kg, respectively (P < 0.01). The additive and dominance effects of RBP4 on weaning weights were 0.332 and 0.682 kg, respectively (P < 0.01). Even if no significant epistasis of PRLR3 and RBP4 was detected, a considerable trend of consistent positive epistasis estimates of AA/BB and Aa/Bb was observed for all traits. The results of this study may have a considerable impact on early-stage growth by both loci, and a selection strategy should be designed separately for each marker in Berkshire pigs. (Key words : Prolactin receptor, Retinol-binding protein, Candidate genes)
Female and male Texas cichlids (Herichthys cyanoguttatum) do not fight by the same rules

Selection usually acts differently on males and females during intrasexual competition for resources and/or mates. Nevertheless, agonistic behavior has been examined both theoretically and empirically mostly in males. Our research questions whether males and females follow the same rules of engagement in intrasexual contests as predicted by the sequential assessment model (SAM). The SAM predicts negative correlations between contest intensity and duration and the magnitude of asymmetry in resource holding power (RHP) between the contestants, such that the most escalated contests are those between similarly endowed individuals. We staged male and female intrasexual contests with varying degrees of body size asymmetry under a round robin design using the monogamous Texas cichlid fish (Herichthys cyanoguttatum) as a study case. We used Mantel's matrix analysis to compare how the behavioral content, duration, structure, and outcome of male and female contests were affected by the relative body size of the contestants. In the case of males, relative size in each contest predicted outcome, duration, and frequency of conventional and escalated behaviors according to prevailing theory. Female contest structure and outcome, however, were not predicted by the relative size of contestants. We discuss our results in terms of other asymmetries that might be important in structuring female contests, and we propose potential approaches to study female--female aggression. Copyright 2004.
Cultural Psychology

Cultural psychology draws upon major psychological topics, theories, and principles to illustrate the importance of culture in psychological inquiry. It explores how culture broadly connects to psychological processing across diverse cultural communities and settings, highlighting its application to everyday life events and situations, and presenting culture as a complex medium in which individuals acquire skills, values, and abilities. One central theme is the view of culture as a mental and physical construct that individuals live, experience, share, perform, and learn; a second core theme is how culture shapes growth and development. Culture-specific and cross-cultural examples reveal connections between culture and psychological phenomena. The text is multidisciplinary and presents different perspectives on how culture shapes human phenomena. It provides an introduction to this field; covers the history of cultural psychology, cultural evolution, and cultural ecology; explains methods; and examines language and nonverbal communication, and cognition and perception. Topics investigating social behavior include the self, identity, and personality; social relationships, social attitudes, and intergroup contact in a global world; and social influence, aggression, violence, and war. Topics addressing growth and development include human development and its processes, transitions, and rituals across the life span; and socializing agents, socialization practices, and child activities. Additional topics explore emotion and motivation, mental health and psychopathology, and future directions for cultural psychology. Chapters contain teaching and learning tools, including case studies, multidisciplinary contributions, thought-provoking questions, class and experiential activities, a chapter summary, and additional print and media resources.
FOREST FIRE SUSCEPTIBILITY MODELLING USING REMOTE SENSING DATA, GIS AND AHP ANALYSIS (CASE STUDY: SOUHAN, ALGERIA)

The ecosystem loses significant areas of forests each year because of forest fires, in Algeria, many of those fires are registered, especially during the summer period, this situation has become a national concern, because of the great losses of these vegetal covers every year. The municipality of Souhane is greatly affected by forest fires. The purpose of this study is to make a susceptibility map for the risks of fires in the municipality of Souhane, this by combining GIS and AHP analysis. several studies have already proved the effectiveness of this method. Six factors were selected; We calculated their weights using the AHP method. The results indicated that 51% of this municipality total area are included in the areas of high and very high susceptibility. The fires that occurred in the year 2019 confirmed the relevance of those results, in addition, the combustion index (NBR) calculation has shown that the areas affected by forest fires are those that are once again, located in the areas of high and very high susceptibility. Thus, those are interesting results and this study can help the fire department to improve its forest fire prevention techniques for the municipality of Souhane.
Rooting and acclimatization of micropropagated cuttings of Pinus pinaster and Pinus sylvestris are enhanced by the ectomycorrhizal fungus Hebeloma cylindrosporum

The effect of different strains of the ectomycorrhizal fungus Hebeloma cylindrosporum on rooting in vitro and acclimatization of micropropagated cuttings of Pinus pinaster and Pinus sylvestris was studied. Two clones of P. pinaster and one of P. sylvestris were unable to root in the absence of auxin, but were induced to root on a medium devoid of auxin by all the fungal strains. Wild-type and indoleacetic acid (IAA)-overproducing mutant strains of the fungus stimulated rooting of clones showing a good reactivity to auxin to the same extent. In contrast, with a clone of P. sylvestris that showed low reactivity to auxin, IAA-overproduction by the fungus was advantageous for the induction of rooting of cuttings. Adventitious roots formed in the presence of a fungal strain were completely surrounded by a loosely packed network of hyphae which formed mycorrhizas as soon as roots grew outside the agar medium. During acclimatization, fungal inoculation improved the survival of rooted cuttings. At the end of acclimatization, fungal mycelia could be easily detected in the culture substrate of cuttings inoculated with dikaryotic strains and most of the pines' short roots were mycorrhizal. Monokaryotic mycelia, which have a lower growth rate and a lower infectivity, displayed poor ability to colonize the substrate and to form mycorrhizas. Two months after the end of acclimatization, fungal inoculation frequently depressed the growth of acclimatized cuttings of the clone J of P. pinaster. No depressive effect was observed with clone 78 and growth stimulation could even be observed with the infective dikaryon D1 which formed numerous mycorrhizas. From these studies, it was concluded that ectomycorrhizal fungi could be a suitable tool for improving rooting in vitro and survival at acclimatization of micropropagated conifer cuttings.
THE ROLE OF NUTRITIONAL FACTORS IN FOOD SELECTION AND PREFERENCE AS RELATED TO LARVAL NUTRITION OF AN INSECT, PSEUDOSARCOPHAGA AFFINIS (DIPTERA, SARCOPHAGIDAE), ON SYNTHETIC DIETS

Abstract Larvae of Pseudosarcophaga affinis auct. nec Fallén readily discriminated between synthetic diets satisfactory for growth and those that had nutritionally important faults. The faults were lack of an essential amino acid, unsatisfactory ratios of essential and nonessential amino acids, and unsatisfactory proportions of the best amino acid mixture relative to glucose levels. Some of these were made to resemble the proportions of amino acids and glucose found by other workers in tissues of aphid-resistant and -susceptible varieties of peas. All the experiments showed that the diets chosen by larvae were those on which they grew and developed best. That larvae can relate the chemical composition of the selected foodstuff with their nutritional requirements may cast some light on varietal resistance of plants or other foodstuff to insects.
THE RECENT UPDATE OF DEOXYARBUTIN: A SKIN DEPIGMENTATION AGENT WITH TYROSINASE INHIBITION TARGETING

Melanin is produced through the process of melanogenesis, which serves to protect the skin from the damaging effects of UV radiation. Abnormal accumulation of melanin will aesthetically disturb even interfere with health. One of the clinical manifestations of abnormal accumulation of melanin is the incidence of melasma. Some of the tyrosinase enzyme inhibitor agents most widely used as Hydroquinone, Kojic acid and Arbutin do not give satisfactory results and cause serious side effects. Hydroquinone is known to cause ochronosis exogenous and cytotoxic. Kojic acid is known to cause allergies and mutagenic, while arbutinisis is known to have cytotoxic properties lower than hydroquinone, but less satisfactory depigmentation activity. There was a compound that has been synthesized by removing the hydroxy group of arbutin, known as deoxyarbutin (4-[Tetrahydro-2H-Pyrans-2-yl) oxy] phenol). Deoxyarbutin (dA) shows Ki 10-fold is lower than hydroquinone and 350-fold is lower than arbutin. IC50dA is 17.5+0.5 µmol/l, while the IC50 hydroquinone is 73.7+9.1 µmol/l. In terms of security, dA indicates that cell viability is 95% higher than hydroquinone. However, dA is thermolabile and photolabile. Several studies have shown satisfactory results to improve the stability of dA, that these compounds are considerable potential for further development as a depigmentation agent. The aim of this review is to describe how the potency of dA as a tyrosinase inhibitor interferes melanogenesis process through the latest depigmentation agent, its safety, efficacy and stability.
Student Response - Based Learning: A Strategy for Improving Student Participation in Learning

In the context of 21st century learning, to achieve meaningful learning processes, one of the important elements is interaction. Student response based learning can be used to actively involve students in the learning process. The study focused on stages of the learning process based on student responses and student responses to the learning. Formulation of the research problem is following: (1) how are the stages of the learning process based on student responses to increasing student participation in learning ? ; (2) how is the student response to student response based learning? The research objectives are: (1) increasing the active participation of students in learning through conditioning the learning environment; and (2) describing the steps of the student response-based learning process. The research conducted is a research development. Conclusion of the results of the study: first, the stages of the student response-based learning process (learning model syntax) are (a) uploading teaching materials; (b) Question & Individual Vote; (c) Peer Discussion; (d) Second Vote; (e) Wholeclass Discussion. These learning steps can increase student participation in learning. Second, students generally give positive responses to student response based learning. A positive response is given to the factor of the variable (a) explanation; (b) facilitation; (c) value; (d) positivity; (e) distraction; and (f) participation. Article history: Received: 28 October 2019 Received in revised form: 13 December 2019 Accepted: 21 January 2020 Available online: 29 February 2020