Miracle-dz/UniFAR-FTUs huggingface dataset:
Process-based Assignment-Setting Change for Support of Overcoming Bottlenecks in Learning by Problem-Posing in Arithmetic Word Problems

Problem-posing is well known as an effective activity to learn problem-solving methods. Monsakun is an interactive problem-posing learning environment to facilitate arithmetic word problems learning for one operation of addition and subtraction. The characteristic of Monsakun is problem-posing as sentence-integration that lets learners make a problem of three sentences. Monsakun provides learners with five or six sentences including dummies, which are designed through careful considerations by an expert teacher as a meaningful distraction to the learners in order to learn the structure of arithmetic word problems. The results of the practical use of Monsakun in elementary schools show that many learners have difficulties in arranging the proper answer at the high level of assignments. The analysis of the problem-posing process of such learners found that their misconception of arithmetic word problems causes impasses in their thinking and mislead them to use dummies. This study proposes a method of changing assignments as a support for overcoming bottlenecks of thinking. In Monsakun, the bottlenecks are often detected as a frequently repeated use of a specific dummy. If such dummy can be detected, it is the key factor to support learners to overcome their difficulty. This paper discusses how to detect the bottlenecks and to realize such support in learning by problem-posing.
1 Related Work 1 . 1 Current Transferability Metrics

For successful transfer and meta-learning, it’s critical to have a method for choosing relevant source and target tasks. Existing metrics require empirically evaluating transferability by quantifying time required to achieve benchmark performance on the target task. We would like a metric that can quantify potential for success after transfer, without empirically performing said transfer. In this work, we (1) describe relevant related work, highlighting lack of effective metrics for quantifying transfer in reinforcement learning, (2) introduce AEDist, a modification on the RBMDist transferability metric, (3) introduce a way to train and evaluate the metric, (4) introduce ways to incorporate the metric with ModelAgnostic Meta-Learning (MAML) by: guiding the learning of the metric using existing empirical metrics in MAML, guiding the learning of the MAML metalearner using AEDist, and mutually training the AEDist metric and the MAML meta-model, (5) evaluate all above models, (6) pose relevant research questions for directions of future work in expanding upon the AEDist transferability metric, and (7) create the first MuJoCo tensegrity environment, capable of locomotion with model-free learning, and (8) motivate research into transferability of tensegrity locomotion policies across environments with varying degrees of terrain incline. Our main takeaways are that (1) low AEDist is in fact predictive of tasks to which we can successfully transfer, in terms of immediate performance, asymptotic performance, and in terms of total return, and (2) incorporation of AEDist into the MAML meta-objective is not conducive to better MAML few-shot learning (neither MAML-return guided AEDist, nor AEDist-guided training of the MAML meta-learner, nor mutual guidance by both AEDist and empirical metrics). Our main contributions are as follows: • We introduce a “task-transferability” metric and evaluate its effectiveness as a stand-alone, and in combination with Model-Agnostic Meta-Learning. • We provide insight into transferability of Tensegrity locomotion policies across terrains of varying inclines, and motivate further work both in the “tasktransferability” metric, and its use in the domain of Tensegrity robotics.
Phenotypic Characterization and Evaluation of European Cherry Collections: A Survey to Determine the Most Commonly used Descriptors

Standardization of descriptors and protocols is a precondition when aiming to harmonize characterization data records from different plant collections. Improved information on the accessions maintained at the European collections has been a priority target of the Prunus Working Group (WG) of the European Cooperative Programme for Genetic Resources network (ECPGR) since its establishment in 1983. Recently, in order to prioritize in the characterization of the Prunus spp. accessions, the Prunus WG began selecting a subset of descriptors (First Priority Descriptors, FPD) considered most informative, from the crop-specific descriptors published by International organizations such as Bioversity International (formerly IPGRI) [1] and UPOV (International Union for the Protection of New Varieties of Plants) [16]. In 2013, a survey was carried out among the cherry collection holders, in the framework of the COST Action FA1104 'Sustainable production of high-quality cherries for the European market', to ascertain which descriptors, categories and scales were most in use for the evaluation and characterization of cherry cultivars in Europe [2]. Sixteen descriptors were routinely used by at least two-thirds of respondents (15 descriptors for sweet and 14 for sour/duke cherry), and deemed most effective in describing cherry accessions, based on the answers provided by 22 sweet cherry and 13 sour/duke cherry curators. This list of most used descriptors, relating to the phenology of blooming and harvesting, tree habit and vigor, fruit size, morphology and internal quality, are now under consideration by the Prunus WG for inclusion in the FPD list recommended for the characterization of the ECPGR cherry resources.
Distributed Multi-Robot Formation Splitting and Merging in Dynamic Environments

This paper presents a distributed method for splitting and merging of multi-robot formations in dynamic environments with static and moving obstacles. Splitting and merging actions rely on distributed consensus and can be performed to avoid obstacles. Our method accounts for the limited communication range and visibility radius of the robots and relies on the communication of obstacle-free convex regions and the computation of an intersection graph. In addition, our method is able to detect and recover from (permanent and temporary) communication and motion faults. Finally, we demonstrate the applicability and scalability of the proposed method in simulations with up to sixteen quadrotors and real-world experiments with a team of four quadrotors.
Specification, analysis and prototyping of mobile code systems

In the past few years dynamic and recon�gurable systems have evolved and new strategy and paradigms for the development of applications have been devised. In this thesis we study mobile code based systems focusing on the importance of formalization and investigation of the potential of code mobility. Mobile code paradigms have been used in di�erent systems, however, as most of these are Java based, the potential of code mobility are some-how lost behind the Java language capabilities, and design choices related to mobility have been conditioned by implementation choices. In this thesis we reason on code mobility systems at the design level in order to investigate novel powerful approaches. This thesis is composed of di�erent parts. We �rst introduce a coordination based language and a model checker to reason on formalization of mobile code based systems with automatic analysis. Properties of mobile agents, of their interaction and behavior may be formally expressed and veri�ed against the system speci�cation. Then, in order to express code mobility potential and to formalize the basic constructs for code migration, we describe a formal language for the speci�cation of very �ne-grained mobility. Every line of code, and every variable declaration can be mobile, giving a very high exibility in the range of application. A prototype of this model implemented in Java is also presented to validate the implementability of the model. Finally, we show a possible incarnation of the �ne-grained mobility approach based on XML. The approach allows XML documents to be updated cutting, extending, or replacing parts of the tree structure of the document. We exploit this idea to incrementally update remote code. The approach can be used in di�erent domains; we describe possible applications in graphic user interface management, document consistency checking and management of application on thin clients like personal digital assistants (PDAs).
Antioxidant activity of thymol : protective role in AAPH-induced hemolysis in diabetic erythrocytes

In the aerobic environment, reactive oxygen species are the most lethal by-products of metabolism that mediate many diseases including cancer, diabetes, immune deficiency diseases and ageing. Present study is aimed to assess the antioxidant activity of Thymol and its implication in diabetes in vitro. Thymol was evaluated by ferric reducing antioxidant power (FRAP) assay and measurement of its total reducing power, total phenolic content and 1,1-diphenyl 2-picrylhydrazyl (DPPH) scavenging activity. Furthermore, the extract in vitro was also checked if it protects red blood cells (RBCs) from 2,2-azo-bis(2amidinopropane) dihydrochloride (AAPH)-induced hemolysis in the samples of diabetic patients and healthy subjects. Thymol demonstrated good ferric reducing ability and high reducing power that can be attributed to its higher amount of phenolic contents. Moreover, it scavenges upto a great extent. Thymol was able to inhibit RBC hemolysis by 86.69±2.34% and 72.04±2.1% in normal and diabetic patients respectively. Our findings reveal that thymol possess antioxidant properties and could serve as a free radical scavenger, and this justifies its uses in folkloric medicines.
Diagnostic Performance of the Rutgers Alcohol Problem Index ( RAPI ) in Detecting DSM-5 Alcohol Use Disorders among College Students

Background and objectives: The DSM-5 Alcohol Use Disorder criteria (AUD) have been modified to reflect a single diagnosis, which may alter how AUDs are detected within our screening measures. The Rutgers Alcohol Problem Index (RAPI) is one of the most widely used screening measures of alcohol problems in college students. The present study sought to evaluate the diagnostic performance of the RAPI in detecting DSM-5 AUDs in college students. Methods: Participants (n = 396; 52% male) were past year drinkers in college either full or part-time. They were asked to fill out a one-hour anonymous packet of questionnaires. Results: The RAPI performed slightly better in the detection of DSM-5 AUDs (AUROC = 0.828; SE = 0.20) in comparison to any DSMIV AUD (0.791; SE = 0.022; 95% CI, 0.748 0.835). The performance of the RAPI was lower when detecting frequency (AUROC = 0.719; SE = 0.025) or quantity of alcohol use (AUROC = 0.758; SE = 0.024) in comparison to detecting DSM-5 AUDs. Gender differences emerged in the identification of optimal RAPI cut-off scores. Findings indicate that an overall RAPI score of 4 be used for female college students and an overall score of 6 be used for male college students in the detection of DSM-5 AUDs. Discussion and conclusions: This is the first study to evaluate the performance of the RAPI in identifying DSM-5 AUDs in college students. Study findings indicate that the RAPI provides reasonably good discrimination in classifying DSM-5 AUDs in college students.
Security Analysis of Networked Systems in the Presence of Impulsive Attacks

In this paper we study the effect of impulsive attacks, also known as initial condition attacks, on networked systems and propose a new security index to be able to analyze the impact of such attacks. In addition, we pose, and subsequently solve, optimization problems for selecting inputs or outputs that point to attacks with maximum impact and least detectability.
A study on attributes of interaction of a social network service on the web

Despite the fact that there has been an increase in the research on a social network service, we still lack well-defined practical knowledge of how to design interaction of the service. This paper is an attempt to develop an understanding of the interaction of the social network service as its own distinctive entity, emerging between individuals and a user interface of the social website. In order to grasp interaction of the social network service, we defined four basic factors of interaction, namely time, space, information, and relationship. After that, we extracted a variety of attributes from the combination of them, and classified the key attributes. In addition, we performed a case study on how the attributes are applied to various social websites such as Facebook, Cyworld, and etc. These attributes will provide a conceptual tool to help designers to make a decision about how to design interaction of the social network service which potential users may experience in a desired way.
Identification analysis of DSGE models with DYNARE

In this paper we describe the Identification package developed at JRC for the DYNARE environment. The package implements methodologies and collects developed algorithms to assess identification of DSGE models in the entire prior space of model deep parameters, by combining ‘classical’ local identification methodologies and global tools for model analysis, like global sensitivity analysis. ∗This work is funded by FP7, Project MONFISPOL, Grant no. 225149. 1
Credit card fraud detection using neural network and geolocation

The most acknowledged payment mode is credit card for both disconnected and online mediums in today's day and age. It facilitates cashless shopping everywhere in the world. It is the most widespread and reasonable approach with regards to web based shopping, paying bills, what's more, performing other related errands. Thus danger of fraud exchanges utilizing credit card has likewise been expanding. In the Current Fraud Detection framework, false exchange is recognized after the transaction is completed. As opposed to the current system, the proposed system presents a methodology which facilitates the detection of fraudulent exchanges while they are being processed, this is achieved by means of Behaviour and Locational Analysis(Neural Logic) which considers a cardholder's way of managing money and spending pattern. A deviation from such a pattern will then lead to the system classifying it as suspicious transaction and will then be handled accordingly.
Determinants and Consequences of Bureaucrat Effectiveness: Evidence from the Indian Administrative Service∗

Do bureaucrats matter? This paper studies high ranking bureaucrats in India to examine what determines their effectiveness and whether effectiveness affects state-level outcomes. Combining rich administrative data from the Indian Administrative Service (IAS) with a unique stakeholder survey on the effectiveness of IAS officers, we (i) document correlates of individual bureaucrat effectiveness, (ii) identify the extent to which rigid seniority-based promotion and exit rules affect effectiveness, and (iii) quantify the impact of this rigidity on state-level performance. Our empirical strategy exploits variation in cohort sizes and age at entry induced by the rule-based assignment of IAS officers across states as a source of differential promotion incentives. JEL classification: H11, D73, J38, M1, O20 ∗This project represents a colloboration between the Lal Bahadur Shastri National Academy of Administration (LBSNAA), the University of Chicago and London School of Economics. We are grateful to Padamvir Singh, the former Director of LBSNAA for his help with getting this project started. The paper has benefited from seminar/conference presentations at Berkeley, Bocconi, CEPR Public Economics Conference, IGC Political Economy Conference, LBSNAA, LSE, NBER India Conference, Stanford and Stockholm University. †Marianne Bertrand [University of Chicago Booth School of Business: Marianne.Bertrand@chicagobooth.edu]; Robin Burgess [London School of Economics (LSE) and the International Growth Centre (IGC): r.burgess@lse.ac. uk]; Arunish Chawla [Indian Administrative Service (IAS)]; Guo Xu [London School of Economics (LSE): g.xu2@lse.ac. uk]
A Hybrid Clustering Algorithm ( KM-GSA ) Based on Anomaly Intrusion Detection Method

Detection effectiveness of an IDS is characterized by high detection accuracy, high detection rate and low false positive rate. Many existing Anomaly-based Intrusion Detection Systems (AIDS) are ineffective and fail to distinguish between normal and abnormal data. This affects the detection accuracy and generates a high false alarm rate. Various clustering techniques have been used for Intrusion Detection for identifying anomalous events. The most important advantage of the clustering method is the ability to find unknown attacks that have not been previously detected. In this paper, a hybrid clustering algorithm based on the combination of the k-Means and Gravitational Search Algorithms (KM-GSA) is designed. In the KM-GSA, the GSA is used to solve the clustering problem by refining the clusters formed by the KM algorithm. The KDD 99 data set consisting of five traffic classes was used as the training and testing dataset. The result of the KM-GSA was compared against the results of the KM algorithm and GSA. Keywords— Network Intrusion Detection, Gravitational Search Algorithm (GSA), K-Means (KM)
Low-delay frequency scaling based on fractional delay filters

Introduction The two traditional approaches for frequency scale modification — phase vocoder and pitch-synchronizedoverlap-add (PSOLA) followed by a resampler — have both limitations when used in real-time applications [1]. Phase vocoders [2] offer high quality, but have a certain delay due to long FFT sizes required. PSOLA methods with resampling [3] can have low delay, but cannot handle polyphone sounds (e.g. music or multiple speakers). We have combined the methodology found in frequency warping [4] with OLA techniques [5], achieving low processing delays of about 10 ms, very good perceptual quality for speech signals and a wide range for continuously tunable frequency factor, e.g. 1% alternation, as well as 100% (transpose about one octave).
Order Book Liquidity on Primary Markets post MiFID II

This study assesses the impact of the new financial regulation (MiFID II) on the liquidity of stocks on a selection of major primary, European lit markets. An analysis of the limit order book (lob) liquidity is presented, including a review of bid-ask spreads, near-touch volumes, and the lob liquidity distributions across different tick levels. The shallow and deep costs of executing orders of different sizes by crossing the spread and sweeping the book are also evaluated. Detailed outcomes are presented for the STOXX 600, STOXX 50, FTSE 100, DAX 30, and CAC 40 as a function of the tick size changes that became effective as part of MiFID II and are compared between Q4 2017 and January 2018. Across the above European indices, as well as a number of sector-specific indices, for stocks with decreased tick sizes spreads narrowed (e.g. STOXX 600: −27%), liquidity at touch decreased (STOXX 600: −57%), the order book volume distribution shifted towards the bid and ask tick levels, while simultaneously broadening. As a consequence, deep and shallow costs of crossing the spread and potentially traversing through multiple levels of the lob declined marginally. The inverse trend – but often more pronounced regarding spread widening and trading costs – is observed for increased ticks. Stocks with unaltered tick schedules have seen no consistent effects on spreads or their lob-volume distribution on the primary, lit venues, although often experiencing a small decline in near touch liquidity. To obtain meaningful, high-level results, index-weighted aggregates of the above liquidity metrics are also computed. Despite the fact that overall outcomes generally point towards slightly higher costs of trading (e.g. an increase of over +6% for the STOXX 600), on an index basis, aggregate results are predominantly governed by the ratio and weights of the underlying constituents with reduced, unchanged, and enlarged ticks. Consequently, the impact on the trading costs of algorithmic strategies is mostly dictated by universe selection as well the passiveor aggressiveness of the adopted trading style.
Towards a dynamic theory of global production networks

25 May 2014 Abstract Global production networks (GPN) are organizational platforms through which actors in different regional and national economies compete and cooperate for a greater share of value creation, transformation, and capture through geographically dispersed economic activity. Existing conceptual frameworks on global value chains (GVC) and what we term GPN 1.0 tend to under-theorize the origins and dynamics of these organizational platforms and to overemphasize their governance typologies (e.g. modular, relational, and captive modes in GVC theory) or analytical categories (e.g. power and embeddedness in GPN 1.0). Building upon this expanding literature, our paper aims to contribute towards the reframing of existing GPN-GVC debates and the development of a more dynamic theory of global production networks that can better explain the emergence of different firm-specific activities, strategic network effects, and territorial outcomes in the global economy. It is part of a wider initiative – GPN 2.0 in short – that seeks to offer novel theoretical insights into why and how the organization and coordination of global production networks varies significantly within and across different industries, sectors, and economies. Taking an actor-centred focus towards theory development, we tackle a significant gap in existing work by systematically conceptualizing the causal drivers of global production networks in terms of their competitive dynamics (optimizing cost-capability ratios, market imperatives, and financial discipline) and risk environments. These capitalist dynamics are theorized as critical independent variables that shape the four main strategies adopted by economic actors in (re)configuring their global production networks and, ultimately, the developmental outcomes in different industries, regions, and countries.
Joint Precoder and Decoder Design for SU-MIMO System with Individual Transmit Power Constraint and Improper Constellation

This paper considers the issue of designing joint optimum precoder and decoder for single-user multiple-input multiple-output system. Most of the previous works on joint precoder and decoder designs are based on the total transmit power constraint (TTPC) with proper modulation techniques. On the other hand, in practice, individual transmit power constraint (ITPC) is more realistic as the power at each antenna at the transmitter is restricted independently by the linearity of the power amplifier. In this paper, a minimum total mean squared error (TMSE) design is formulated as a nonconvex optimization problem under equal power allocation (EPA) and the power constraint that jointly meets both EPA and TTPC (i.e ITPC). The closed-form optimum linear precoder and decoder for singleuser multiple-input multiple-output (SU-MIMO) systems with an improper modulation are determined by solving this nonconvex optimization problem. It considers both the perfect and imperfect channel state information (CSI) is available at both the transmitter and receiver. The simulation results show the performance improvement of the proposed work over conventional work in terms of bit error rate (BER). Keywords—Channel state information (CSI), mean-square error (MSE), multiple-input multiple-output (MIMO), linear precoding, spatial multiplexing, improper modulations.