Miracle-dz/UniFAR-FTUs huggingface dataset:
Peer Groups and Academic Achievement: Panel Evidence from Administrative Data

We examine the impact of classroom and grade level peer achievement on individual elementary students’ rate of achievement gain in math and reading using a detailed panel data-set from San Diego Unified School District. We find that controls for unobserved student heterogeneity through addition of student fixed effects to be important, as are controls for potential simultaneity and regression to the mean. The preferred specifications suggest positive and significant effects of peer achievement. Tests for independent effects of peer achievement at the classroom and grade level suggest that the former are more important but for reading gains both types of peer achievement are significant. We also find some evidence for asymmetry in peer effects.
Methyl Salicylate Esterases in Plant Immunity

Salicylic acid (SA) is an important signal in various plant processes. It is well known and widely studied for its role in plant disease resistance. Several proteins, which physically interact with SA has been identified and characterized for their possible role in disease resistance signaling. These plant proteins bind to SA with varying affinity and they differ considerably in their structure and activity. The protein, which binds to SA with highest affinity amongst all the characterized SA-binding proteins, is SABP2. It is a 29-kDa protein and has esterase like enzymatic activity. It is able to use plant synthesized methyl salicylate as a substrate and convert it into SA, which triggers disease resistance in plants. Silencing of SABP2 makes plants more susceptible to pathogens and their capacity to induce SAR is severely compromised. The esterase activity of SABP2 is required to process the phloem mobile signal, MeSA in distal uninoculated tissues to induce resistance. The binding of SA to SABP2 is important for activation of SAR in distal tissues. _____________________________________________________________________________________________________________
Defining a Meaningful Baseline for News Recommender Systems

Evaluation protocols for news recommender systems typically involve comparing the performance of methods to a baseline. The difference in performance ought to tell us what benefit we can expect from using a more sophisticated method. Ultimately, there is a trade-off between performance and effort in implementing and maintaining a system. This work explores what baselines have been used, what criteria baselines must fulfil, and evaluates a variety of baselines in a news recommender evaluation setting with multiple publishers. We find that circular buffers and trend-based predictions score highly, need little effort to implement, and require no additional data. Besides, we observe variations among publishers, suggesting that not all baselines are equally competitive in different circumstances.
Environmental variability in the monsoonewesterlies transition zone during the last 1200 years: lake sediment analyses from central Mongolia and supraeregional synthesis

A high resolution multieproxy (pollen, grain size, total organic carbon) record from a small mountain lake (Lake Khuisiin; 46.6 N, 101.8 E; 2270 m a.s.l.) in the southeeastern Khangai Mountains of central Mongolia has been used to explore changes in vegetation and climate over the last 1200 years. The pollen data indicates that the vegetation changed from dry steppe dominated by Poaceae and Artemisia (ca AD 760e950), to Larix forest steppe (ca AD 950e1170), LarixeBetula forest steppe (ca AD 1170e1380), meadow dominated by Cyperaceae and Poaceae (ca AD 1380e1830), and LarixeBetula forest steppe (after w AD 1830). The cold-wet period between AD 1380 and 1830 may relate to the Little Ice Age. Environmental changes were generally subtle and climate change seems to have been the major driver of variations in vegetation until at least the early part of the 20th century, suggesting that either the level of human activity was generally low, or the relationship between human activity and vegetation did not alter substantially between AD 760 and 1830. A review of centennialescale moisture records from China and Mongolia revealed that most areas experienced major changes at ca AD 1500 and AD 1900. However, the moisture availability since AD 1500 varied between sites, with no clear regional pattern or relationship to presenteday conditions. Both the reconstructions and the moisture levels simulation on a millennium scale performed in the MPI Earth System Model indicate that the monsoonewesterlies transition area shows a greater climate variability than those areas influenced by the westerlies, or by the summer monsoon only. 2013 Elsevier Ltd. All rights reserved.
Listening to the inner soundscape: A pedagogical tool for opening minds to sound-based music

This paper describes the context and methodology for research into developing heightened listening as a pedagogical and compositional tool. It builds on my previous research into whether heightened listening (which is defined as a close concentration on sound that allows for external associations with the source) can be effective as an access tool for electroacoustic music. The paper describes the results of my previous project and outlines how my current research aims to build on this to help facilitate a greater interest in sound-based music, for school children, through creative practice. In the current research writing exercises are being used to help participants listen to their ‘inner soundscapes’ (Tzedaki, 2011). They are then required to create their own narratives and, when composing their pieces, use sounds that will support that narrative. In working this way, participants can begin to make the step to listen as composers by internalizing their initial listening, rather than just as listeners, an approach advocated by the composer Michelle Nagai (Nagai, 2011). It is hoped that through this process a deeper interest in sound-based music will be cultivated. Listening to the inner soundscape: A pedagogical tool for opening minds to sound-based
Trends in Commuting Time of European Workers: A Cross-Country Analysis

This paper examines the time spent commuting to/from work by workers in fifteen European countries, during the last three decades, with the aim of analyzing recent trends in commuting and the factors affecting commuting behavior in those countries. Using data from several waves of the European Working Conditions Survey, results show a significant gender gap in commuting time in Austria, Belgium, France, Germany, Italy, Ireland, Luxembourg, the Netherlands, and the UK, with male workers devoting more time to commuting than their female counterparts. We further explore the factors related to commuting time, documenting a level of heterogeneity in commuting behavior as certain determinants of commuting time differ across countries. By analyzing the evolution of commuting time in Europe in recent decades, and the factors associated with commuting time, our analysis may serve to guide future planning programs.
EMBRIO – a 3D Software for Learning Embryology

This paper presents an embryology teaching system called EMBRIO, developed to improve the learning of embryology based on learning objects. In this sense, the changes observed in the development of the conceptus, which would otherwise be hardly understood from two-dimensional figures as printed in textbooks, may be more easily visualized upon complete comprehension, using three-dimensional models. The learning objects present in EMBRIO were developed based on the analysis of hundreds of twodimensional images of the conceptus, obtained from different sources. The result was the creation of a system containing tens of three-dimensional images of the conceptus, at distinct development stages. The aim is to increase the students’ understanding of embryology, improving chances of producing correct diagnoses by health professionals in the future concerning inborn malformations. This correct diagnosis may also, in many cases, mean a better quality of life for the subject carrying a malformation.
Structuring Information through Gesture and Intonation

Face-to-face communication is multimodal. In unscripted spoken discourse we can observe the interaction of several “semiotic layers”, modalities of information such as syntax, discourse structure, gesture, and intonation. We explore the role of gesture and intonation in structuring and aligning information in spoken discourse through a study of the co-occurrence of pitch accents and gestural apices. Metaphorical spatialization through gesture also plays a role in conveying the contextual relationships between the speaker, the government and other external forces in a naturally-occurring political speech setting.
A Comparative Study of Genetic Algorithm and Particle Swarm Optimization

Among different search and optimization techniques, the development of Evolutionary Algorithms (EA) has gained large attention in the field of research and EA acts as an effective method for solving various optimization problems. Genetic Algorithm (GA) is an adaptive metaheuristic optimization algorithm which is mainly based on the theory of Natural Selection and Genetics. GA can be mainly used in various areas such as Neural Networks, Image Processing, Vehicle routing problems and so on. The drawback of the GA is, it is of high cost. Particle Swarm Optimization (PSO) which is also a kind of metaheuristic optimization algorithm based on the social behavior of organisms which possess swarming characteristics. PSO and the GA are very closely associated population based search methods where both advances from a set of points to another set of points in an iteration providing perceptible improvements from the antecedent values using some probabilistic and deterministic conditions. The main objective of this paper is to study and compare the efficiency and effectiveness of the two evolutionary algorithms.
Baseline Susceptibility of Culiseta longiareolata (Diptera: Culicidae) to Different Imagicides, in Eastern Azerbaijan, Iran

Background: Culiseta longiareolata is an important vector for many human diseases such as brucellosis, avian influenza and West Nile encephalitis. It is likely an intermediate host of avian Plasmodium that can transmit Malta fever. The aim of this study was to determine the susceptibility level of Cs. longiareolata to different classes of imagicides which are recommended by World Health Organization . Methods: Larval stages of the Cs. longiareolata were collected from their natural habitats in Marand County at East Azerbaijan Province, northwestern of Iran in 2017. Adult susceptibility test were carried out with using impregnated papers to insecticides including DDT 4%, Cyfluthrin 0.15%, Deltamethrin 0.05%, Propoxur 0.1% and Fenitrothion 1% by standard test kits. Results: Results showed that Cs. longiareolata adult is more susceptible to pyrethroid and carbamate insecticides. Among tested insecticides, Cyfluthrin was the most toxic against Cs. longiareolata with LT50 value of 11.53 minutes and Fenitrothion had the least toxic effect (LT50: 63.39 min). Conclusions: This study provided a guideline for monitoring and evaluation of insecticide susceptibility tests against Cs. longiareolata mosquitoes for further decision making.
Regional cerebral blood flow during auditory recall in 47 subjects exposed to assaultive and non-assaultive trauma and developing or not Post Traumatic Stress Disorder

■ Abstract Objective Psychological trauma leads to posttraumatic stress disorder (PTSD) in susceptible subjects. The aim of this study was to investigate the differences in regional cerebral blood flow (rCBF) between two groups of subjects exposed to different types of traumatic stressor either developing or not developing PTSD. Method Twenty subjects developing (S) and 27 not developing (NS) PTSD after being exposed to either earlier person-under-the-train accident (NA) or being assaulted in the underground environment (A) were included in the study. 99mTc-HMPAO SPECT was performed and the uptake in 29 regions of the brain (VOIs), bilaterally, was assessed. rCBF distribution was compared, using analysis of variance (ANOVA), between groups (S/NS) and type (A/NA) during a situation involving an auditory evoked re-experiencing of the traumatic event. Discriminant analysis was applied to test the concordance between clinical diagnosis and SPECT findings. Results In the general analyses significant differences were found between groups and types and there was a significant hemisphere type interaction. S showed higher CBF than NS and so did A as compared to NA, particularly in the right hemisphere. Discriminant analysis correctly classified 66 % of cases (p < 0001) in testing S/NS and 72 % (p < 0001) in testing NA/A. Conclusions Under recall of their traumatic experience we found higher relative CBF distribution values in S as compared to NS. CBF was higher in the right hemisphere and particularly in assaulted subjects. These findings underscore the role upon trauma recall of both the right hemisphere and the nature of the stressing event.
Recent Advances in Non-Pharmacological Behaviour Management Techniques in Children – An Overview

A proper communication combined with a caring attitude develops sound rapport with any paediatric patient. Non-pharmacological behaviour management techniques enable paediatric dentists to successfully alleviate behavioural problems by matching their selection of techniques to that of the child’s style of interaction. On the other hand, few aggressive techniques applied in childhood have been implicated as being prominent factors in the behaviour of developed adult patients with dental phobias. The aim of instilling positive reinforcement is achieved by conventional methods but disruptiveness increase with increase in treatment time. Hence, to overcome this disadvantage newer non-threatening techniques were handled by the paediatric dentists, which provide long time reinforcement in younger children. This review will focus on enumerating the recent advances in non-pharmacological behaviour management techniques in children.
Forecast of Potential Areas of Urban Expansion in the Laguna de Bay Basin and Its Implications to Water Supply Security

*Corresponding Author: kgotangco@ateneo.edu The Laguna de Bay Basin is a highly important economic and environmental resource with a variety of land and water uses. This study investigates the status and trends of the land cover change of the Laguna de Bay Basin, focusing on urban expansion. Using the Land Transformation Model (LTM), drivers of conversion of agricultural and natural land cover to built-up land were determined based on the land cover change between 2003 and 2015. Drivers identified include distance to rivers, distance to roads, distance to Laguna Lake, distance to existing built-up, slope, population density, soil type, temperature, and rainfall. A forecast of urban expansion assuming “business-as-usual” conditions to year 2050 shows the expansion of built-up areas southward of the National Capital Region towards the areas of Cavite, Batangas, and Laguna, and eastward to Rizal. This poses a risk to the water bodies near these areas. Potential implications on water quality and quantity, as components of overall water supply security, are discussed. A framework for future research integrating land use and land cover change (LULCC) and water supply security is proposed. The study recommends the continued implementation of integrated watershed management and the development of more transboundary management policies. Philippine Journal of Science 148 (4): 715-724, December 2019 ISSN 0031 7683 Date Received: 4 Jun 2019
SLURRY SAWING OF MULTICRYSTALLINE SILICON WITH LOW-VISCOSITY CARRIER LIQUID

The wafering of crystalline silicon is industrially realized by wire sawing with loose abrasive particles dispersed in a carrier medium (slurry process) or by fixed diamond particles embedded on the wire (diamond wire sawing DWS). DWS demonstrates cost advantages by the usage of a cheap cooling fluid, which consists of water with about 2% of additives. In the slurry process, SiC particles are used as abrasive typically dispersed in polyethylene glycol (PEG200) as carrier liquid. A cost reduction of this process by saving electrical energy can be achieved by the usage of a lower-viscosity carrier liquid. In this contribution, PEG200 is substituted by the lowerviscosity organic substance propylene carbonate. In four consecutive sawing processes on multicrystalline silicon bricks, the cutting performance of this liquid was tested. The results are compared with the standard sawing process using PEG200. It was found that the average power of the wire saw main drive can be reduced by about 60%.
Sol: Fast Distributed Computation Over Slow Networks

The popularity of big data and AI has led to many optimizations at different layers of distributed computation stacks. Despite – or perhaps, because of – its role as the narrow waist of such software stacks, the design of the execution engine, which is in charge of executing every single task of a job, has mostly remained unchanged. As a result, the execution engines available today are ones primarily designed for low latency and high bandwidth datacenter networks. When either or both of the network assumptions do not hold, CPUs are signiﬁcantly underutilized. In this paper, we take a ﬁrst-principles approach toward developing an execution engine that can adapt to diverse network conditions. Sol, our federated execution engine architecture , ﬂips the status quo in two respects. First, to mitigate the impact of high latency, Sol proactively assigns tasks, but does so judiciously to be resilient to uncertainties. Second, to improve the overall resource utilization, Sol decouples communication from computation internally instead of commit-ting resources to both aspects of a task simultaneously. Our evaluations on EC2 show that, compared to Apache Spark in resource-constrained networks, Sol improves SQL and machine learning jobs by 16.4 × and 4.2 × on average.
Advanced Assistive Technologies for Elderly People: A Psychological Perspective on Seniors’ Needs and Preferences (part A)

This paper provides an overview of the literature concerning Seniors’ psychological perspective in exploiting assistive robots and the embodied conversational agents. The main theoretical models devoted to assess user’s technology acceptance are briefly reviewed along with a description of the main factors empirically found to be positively/negatively associated with Seniors’ acceptance level. Special attention is reserved to barriers generated by Seniors’ representations of social assistive technologies, such as, a stigma or threat to their autonomy, infantilization, privacy interferences, fear of dehumanization and isolation.
Misallocation and Intersectoral Linkages ∗ — Link to the most recent version —

We analytically characterize the aggregate productivity loss from distortions in the presence of sectoral production linkages. We find that accounting for low input substitutability reduces the productivity loss and the impact of intermediate-input suppliers. Moreover, with elasticities below one (i.e. below Cobb-Douglas), sectoral linkages do not systematically amplify the productivity loss. We quantify these effects in the context of the distortions caused by market power, using industrylevel data for 35 countries. With our benchmark calibration, the median aggregate productivity loss from industry-level markups is 1.2%; assuming Cobb-Douglas elasticities would lead to overestimating the productivity loss by a factor of 1.8. ∗We thank Simon Anderson, Susanto Basu, Vasco Carvalho, Kerem Cosar, Pete Klenow, Guy Laroque, Julien Martin, Ellen McGrattan, Mathieu Parenti, Jorge Miranda Pinto, Toshihiko Mukoyama, B. Ravikumar, Pierre Sarte, Venky Venkateswaran, Enghin Atalay; participants at various seminars and conferences. Sophie Osotimehin thanks the Opportunity and Inclusive Growth Institute of the Minneapolis Fed for their support and hospitality. We thank Jaeki Jang, Ilhan Guner, and Diego LegalCañisá for excellent research assistance; and Susan Langenkamp and James Holt for editorial assistance.
Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems

Likelihood-free (a.k.a. simulation-based) inference problems are inverse problems with expensive, or intractable, forward models. ODE inverse problems are commonly treated as likelihood-free, as their forward map has to be numerically approximated by an ODE solver. This, however, is not a fundamental constraint but just a lack of functionality in classic ODE solvers, which do not return a likelihood but a point estimate. To address this shortcoming, we employ Gaussian ODE filtering (a probabilistic numerical method for ODEs) to construct a local Gaussian approximation to the likelihood. This approximation yields tractable estimators for the gradient and Hessian of the (log-)likelihood. Insertion of these estimators into existing gradient-based optimization and sampling methods engenders new solvers for ODE inverse problems. We demonstrate that these methods outperform standard likelihood-free approaches on three benchmark-systems.
Leveraging Cross Feedback of User and Item Embeddings for Variational Autoencoder based Collaborative Filtering

Matrix factorization (MF) has been widely applied to collaborative filtering in recommendation systems. Its Bayesian variants can derive posterior distributions of user and item embeddings, and are more robust to sparse ratings. However, the Bayesian methods are restricted by their update rules for the posterior parameters due to the conjugacy of the priors and the likelihood. Neural networks can potentially address this issue by capturing complex mappings between the posterior parameters and the data. In this paper, we propose a variational auto-encoder based Bayesian MF framework. It leverages not only the data but also the information from the embeddings to approximate their joint posterior distribution. The approximation is an iterative procedure with cross feedback of user and item embeddings to the others' encoders. More specifically, user embeddings sampled in the previous iteration, alongside their ratings, are fed back into the item-side encoders to compute the posterior parameters for the item embeddings in the current iteration, and vice versa. The decoder network then reconstructs the data using the MF with the currently re-sampled user and item embeddings. We show the effectiveness of our framework in terms of reconstruction errors across five real-world datasets. We also perform ablation studies to illustrate the importance of the cross feedback component of our framework in lowering the reconstruction errors and accelerating the convergence.
Guider l'attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue

The task of predicting dialog acts (DA) based on conversational dialog is a key component in the development of conversational agents. Accurately predicting DAs requires a precise modeling of both the conversation and the global tag dependencies. We leverage seq2seq approaches widely adopted in Neural Machine Translation (NMT) to improve the modelling of tag sequentiality. Seq2seq models are known to learn complex global dependencies while currently proposed approaches using linear conditional random fields (CRF) only model local tag dependencies. In this work, we introduce a seq2seq model tailored for DA classification using: a hierarchical encoder, a novel guided attention mechanism and beam search applied to both training and inference. Compared to the state of the art our model does not require handcrafted features and is trained end-to-end. Furthermore, the proposed approach achieves an unmatched accuracy score of 85% on SwDA, and state-of-the-art accuracy score of 91.6% on MRDA.