Miracle-dz/UniFAR-FTUs huggingface dataset:
Variation and generality in encoding of syntactic anomaly information in sentence embeddings

While sentence anomalies have been applied periodically for testing in NLP, we have yet to establish a picture of the precise status of anomaly information in representations from NLP models. In this paper we aim to fill two primary gaps, focusing on the domain of syntactic anomalies. First, we explore fine-grained differences in anomaly encoding by designing probing tasks that vary the hierarchical level at which anomalies occur in a sentence. Second, we test not only models’ ability to detect a given anomaly, but also the generality of the detected anomaly signal, by examining transfer between distinct anomaly types. Results suggest that all models encode some information supporting anomaly detection, but detection performance varies between anomalies, and only representations from more re- cent transformer models show signs of generalized knowledge of anomalies. Follow-up analyses support the notion that these models pick up on a legitimate, general notion of sentence oddity, while coarser-grained word position information is likely also a contributor to the observed anomaly detection.
Reference-Free Word- and Sentence-Level Translation Evaluation with Token-Matching Metrics

Many modern machine translation evaluation metrics like BERTScore, BLEURT, COMET, MonoTransquest or XMoverScore are based on black-box language models. Hence, it is difficult to explain why these metrics return certain scores. This year’s Eval4NLP shared task tackles this challenge by searching for meth-ods that can extract feature importance scores that correlate well with human word-level error annotations. In this paper we show that unsupervised metrics that are based on token-matching can intrinsically provide such scores. The submitted system interprets the similarities of the contextualized word-embeddings that are used to compute (X)BERTScore as word-level importance scores. We make our code available 1 .
Low Resource Quadratic Forms for Knowledge Graph Embeddings

We address the problem of link prediction between entities and relations of knowledge graphs. State of the art techniques that address this problem, while increasingly accurate, are computationally intensive. In this paper we cast link prediction as a sparse convex program whose solution defines a quadratic form that is used as a ranking function. The structure of our convex program is such that standard support vector machine software packages, which are numerically robust and efficient, can solve it. We show that on benchmark data sets, our model’s performance is competitive with state of the art models, but training times can be reduced by a factor of 40 using only CPU-based (and not GPU-accelerated) computing resources. This approach may be suitable for applications where balancing the demands of graph completion performance against computational efficiency is a desirable trade-off.
FAST: A carefully sampled and cognitively motivated dataset for distributional semantic evaluation

What is the first word that comes to your mind when you hear giraffe, or damsel, or freedom? Such free associations contain a huge amount of information on the mental representations of the corresponding concepts, and are thus an extremely valuable testbed for the evaluation of semantic representations extracted from corpora. In this paper, we present FAST (Free ASsociation Tasks), a free association dataset for English rigorously sampled from two standard free association norms collections (the Edinburgh Associative Thesaurus and the University of South Florida Free Association Norms), discuss two evaluation tasks, and provide baseline results. In parallel, we discuss methodological considerations concerning the desiderata for a proper evaluation of semantic representations.
Who’s on First?: Probing the Learning and Representation Capabilities of Language Models on Deterministic Closed Domains

The capabilities of today’s natural language processing systems are typically evaluated using large datasets of curated questions and answers. While these are critical benchmarks of progress, they also suffer from weakness due to artificial distributions and incomplete knowledge. Artifacts arising from artificial distributions can overstate language model performance, while incomplete knowledge limits fine-grained analysis. In this work, we introduce a complementary benchmarking approach based on SimPlified Language Activity Traces (SPLAT). SPLATs are corpora of language encodings of activity in some closed domain (we study traces from chess and baseball games in this work). SPLAT datasets use naturally-arising distributions, allow the generation of question-answer pairs at scale, and afford complete knowledge in their closed domains. We show that language models of three different architectures can answer questions about world states using only verb-like encodings of activity. Our approach is extensible to new language models and additional question-answering tasks.
An Investigation into the Contribution of Locally Aggregated Descriptors to Figurative Language Identification

In natural language understanding, topics that touch upon figurative language and pragmatics are notably difficult. We probe a novel use of locally aggregated descriptors – specifically, an architecture called NeXtVLAD – motivated by its accomplishments in computer vision, achieve tremendous success in the FigLang2020 sarcasm detection task. The reported F1 score of 93.1% is 14% higher than the next best result. We specifically investigate the extent to which the novel architecture is responsible for this boost, and find that it does not provide statistically significant benefits. Deep learning approaches are expensive, and we hope our insights highlighting the lack of benefits from introducing a resource-intensive component will aid future research to distill the effective elements from long and complex pipelines, thereby providing a boost to the wider research community.
Investigating Negation in Pre-trained Vision-and-language Models

Pre-trained vision-and-language models have achieved impressive results on a variety of tasks, including ones that require complex reasoning beyond object recognition. However, little is known about how they achieve these results or what their limitations are. In this paper, we focus on a particular linguistic capability, namely the understanding of negation. We borrow techniques from the analysis of language models to investigate the ability of pre-trained vision-and-language models to handle negation. We find that these models severely underperform in the presence of negation.
A Novel Wikipedia based Dataset for Monolingual and Cross-Lingual Summarization

Cross-lingual summarization is a challenging task for which there are no cross-lingual scientific resources currently available. To overcome the lack of a high-quality resource, we present a new dataset for monolingual and cross-lingual summarization considering the English-German pair. We collect high-quality, real-world cross-lingual data from Spektrum der Wissenschaft, which publishes human-written German scientific summaries of English science articles on various subjects. The generated Spektrum dataset is small; therefore, we harvest a similar dataset from the Wikipedia Science Portal to complement it. The Wikipedia dataset consists of English and German articles, which can be used for monolingual and cross-lingual summarization. Furthermore, we present a quantitative analysis of the datasets and results of empirical experiments with several existing extractive and abstractive summarization models. The results suggest the viability and usefulness of the proposed dataset for monolingual and cross-lingual summarization.
Growth in Syria: losses from the war and potential recovery in the aftermath

ABSTRACT This paper addresses three questions: (1) what would have been the growth and income trajectory of Syria in the absence of war; (2) given the war, what explains the reduction in economic growth; and (3) what potential growth scenarios for Syria there could be in the aftermath of war. Conflict impact estimates point to negative GDP growth of −12% on average over 2011–2018, with output contracting to about one-third of the 2010 level. In post-conflict simulation scenarios, the growth drivers are affected by the assumed levels of reconstruction assistance, repatriation of refugees, and productivity improvements associated with three political settlement outcomes: a baseline (Sochi-plus) moderate scenario, an optimistic (robust political settlement) scenario, and a pessimistic (de facto balance of power) scenario. Respectively for these scenarios, GDP per capita average growth in the next two decades is projected to be 6.1%, 8.2%, or 3.1%, assuming a final and stable resolution of the conflict.
Effectiveness of a clinical pilates program in women with chronic low back pain: A randomized controlled trial

Ozden Baskan1, Ugur Cavlak2, Emre Baskan3 1Physical therapist, İstanbul Rumeli University School of Physical Therapy and Rehabilitation, Istanbul 2Physical therapist, Avrasya University School of Physical Therapy and Rehabilitation, Trabzon 3Physical therapist, Pamukkale University School of Physical Therapy and Rehabilitation, Denizli, Turkey Pilates for back pain Effectiveness of a clinical pilates program in women with chronic low back pain: A randomized controlled trial
An Empirical Research on the Factors Determining Economic Literacy Level

Economic literacy, which is explained as being able to interpret economic events and developments, and having a basic level of economic knowledge, becomes more and more important every day. In the globalizing world, it is seen that the economic decision-making processes of individuals who have consumer, producer and investor roles have diversified and become more complex. In this diverse and complex decision-making process, individuals' economic knowledge levels affect the decisions to be made. In this direction, the decisions taken by individuals become more important for both their own wealth and the economies of the country. Survey of individuals living in Turkey for over 385 people in the framework of the aforementioned considerations in this study to determine the level of economic literacy is made. When the answers given by the participants are evaluated, it is seen that the level of economic literacy is sufficient. When the effect of demographic factors on economic literacy is examined in the study, there is no statistically significant difference according to gender, age, marital status and income level, it is seen that the differentiation is significant according to education level and occupation groups. Within the framework of the findings obtained as a result of the study, it is considered that making economics education more widespread and providing access to information with the cooperation of universities and economic institutions will be beneficial in increasing the level of economic literacy.
Effects of Blackboard on the work-life balance of students and lecturers

In the modern world of increased work intensity, workload and resulting stress the concept of work-life balance has become an important topic for both academics and practitioners. Technology has been identified as an influential factor on the balance of these two domains. Since in the context of universities no research has been done in this field, this study aimed at getting insights into the usage of the technology of e-learning platforms, its implications and effects on the work-life balance of students and lecturers. The research object was the e-learning platform ‘Blackboard’ and research context the ‘University of Twente’. For this purpose, semi-structured interviews were conducted with twelve students and nine lecturers. On the basis of these, codes and sub-codes were found that described the usage and the relationship between the usage of Blackboard and the perceived work-life balance. The finding that was most noticeable is that for lecturers it was found no influence of Blackboard on their work-life balance, while for students both positive and negative influences of Blackboard on their work-life balance was found. The same was found for the influence on the private life, because for lecturers there was no influence perceived but for students both positive and negative impacts were detected. Reason for this might be that students use Blackboard passively as information receivers while lecturers use it actively as deliverers. Lecturers thus have more control over the system. The most important given recommendation is to introduce a policy where no announcements can be posted on Blackboard during evenings and weekends to enhance the work-life balance of students. The uniqueness of this study lies in its special focus on e-learning platforms and its assessment of the work-life balance of students. Due to its explorative and qualitative character, this study can serve as basis for different future studies.
Simulated lifecycle costs of ultracapacitors in battery electric vehicles

The pulse power characteristics of ultracapacitors appear well suited to electric vehicle applications, where they may supply the peak power more efficiently than the battery, and can prevent excessive over sizing of the battery pack due to peak power demands. Operation of ultracapacitors in battery electric vehicles (BEVs) is examined for possible improvements in system efficiency, vehicle driving range, battery pack lifetime, and potential reductions in system lifecycle cost. The lifecycle operation of these ultracapacitors is simulated using a custom-built, dynamic simulation code constructed in Matlab. Despite apparent gains in system efficiency and driving range, the lifecycle cost benefits as simulated appear to be marginal, and are heavily influenced by the incremental cost of power components. However, additional factors are identified which, in reality, will drive ultracapacitors towards viability in electric vehicle applications.
Business Model You: A One-Page Method For Reinventing Your Career

1 Canvas Learn to use the key tool for describing and analyzing organizational and personal business models. Chapter 1 Business Model Thinking: Adapting to a Changing World 19 Chapter 2 The Business Model Canvas 25 Chapter 3 The Personal Business Model Canvas 53 2 Reflect Revisit your life direction and consider how you want to align your personal and career aspirations. Chapter 4 Who Are You? 81 Chapter 5 Identify Your Career Purpose 133 3 Revise Adjust or reinvent your work life using the Canvas and discoveries from previous sections. Chapter 6 Get Ready to Reinvent Yourself 161 Chapter 7 Re-Draw Your Personal Business Model 175 4 Act Learn to make it all happen. Chapter 8 Calculate Your Business Value 209 Chapter 9 Test Your Model in the Market 223 Chapter 10 What's Next? 243 5 Extras Read more about the people and resources behind Business Model You. The Business Model You Community 252 Creator Bios 254 Notes 256
A SPH-based method to simulate local scouring

A method for the numerical prediction of scouring processes is proposed. The method is based on a Lagrangian description of the flow by Smoothed Particle Hydrodynamics, coupled with a description of the bed evolution based on the Exner equation and solved by a finite-difference predictor-corrector scheme. The numerical solutions are compared with measurements of bed evolution and water velocity, obtained in a case of local scour downstream of a protection apron caused by a planar jet flowing from a sluice gate. The results show that the predicted evolution of position and depth of the maximum scour agrees quite well with the experimental data.
Malaria Outbreak Facilitated by Increased Human Activities around Swamps: Kisoro District, Uganda, December 2017-March 2018

Background: Malaria elimination is increasingly becoming a global priority. On 19 December 2018, a district in southwestern Uganda known to have achieved pre-elimination levels of malaria (<30 cases per month) reported a sudden increase in cases to the Ministry of Health. We investigated to determine the magnitude and scope of the outbreak and identify exposures associated with transmission. Methods:We reviewed medical records in all health facilities in the affected Kanaba and Murora sub-counties to find cases. We calculated attack rates (AR) by age, sex, and village using the projected 2016 population. In a case-control study, we compared potential exposures between case-patients, selected randomly from the line-list, and neighborhood- and age-matched asymptomatic controls. We conducted an entomological and environmental assessment of randomly-selected households and potential breeding sites of the affected sub-counties. Results: We found 3,130 malaria cases (compared with 879 cases during the same period the previous year). Persons in the age groups 10-19 (AR=14/1,000) and 20-29 (AR=12/1,000) years were the most affected. Villages closest to the swamp had the highest attack rate. In the case-control study, 89% (129/145) of case-patients and 73% (106/145) of controls reported frequent late-night mosquito bites (ORCLR=3.9; 95%CI: 1.8-8.4); 70% (102/145) of case-patients and 59% (86/145) of controls had a household size >5 (ORCLR=1.8; 95%CI: 1.04-3.1); 78% (113/145) of case-patients and 86% (125/145) of controls usually slept under a bednet (ORCLR=0.56; 95%CI: 0.29-1.1). Anopheles gambiae sensu lato was identified in breeding places around Sereri and Mpundu swamps. In total, 64% (23/36) of female adult Anopheles captured in case-patients’ households by pyrethrum spray catches were fed, suggesting low bed-net usage the previous night in the surveyed households. Conclusion: This malaria outbreak was likely propagated by favorable breeding conditions, including recent heavy rainfall, and exacerbated by new human activities around two swamps. To achieve malaria elimination, low-endemic areas should be particularly aware of activities that can lead to resurgences in malaria, such as night-time exposures, lack of bed-net usage, and human activities focused around breeding sites. We recommended increased awareness about bed-net usage and use of larvicides in the residential area and swamps to break the breeding cycle.
Looking for the universal core of the RI stage

As it is well known, child Italian does not show a typical Root Infinitive (RI) stage (Guasti 1994), in contrast to German, Dutch, etc. Salustri and Hyams (2003) provided evidence from 3 monolingual Italian children and 1 bilingual German-Italian child that there exists an analogue of the RI stage in this language. We argued that the RI analogue in Italian is the imperative. In this paper, we present data from 4 additional null subject languages, Spanish, Catalan, Slovenian and Hungarian – in support of the Imperative Analogue Hypothesis (IAH). We also present relevant data from Icelandic and Dutch, both RI languages, which further support the IAH. Finally we will evaluate two competing theories of the IAH against these data.
IPPA: Individually Prioritised Problem Assessment

Individually Prioritised Problem Assessment (IPPA) is an instrument to assess the effectiveness of assistive technology provision. It is a generic instrument that can be used to assess the extent to which problems identified by an individual assistive technology user have been diminished. IPPA was developed because existing instruments in the field of Health Technology Assessment are not sufficient for assessing effectiveness of assistive technology. IPPA assesses effectiveness in relation to those activities that the individual respondent considers relevant. At the start of the service delivery process, the client is asked to identify and rate the activities that he or she has problems with in everyday life. The same activities are rated again, a few months after receiving a new assistive technology. IPPA has been used in several studies and has proven to be a usable and valid instrument. 1. Purpose Individually Prioritised Problem Assessment (IPPA) was conceived as an instrument to assess the effective- ness of assistive technology provision. It assesses the extent to which problems identified by an individual assistive technology user in his or her daily activities have been diminished as a result of the provision of assistive technology (5). IPPA is primarily meant to be used in outcome stud- ies. Results can be used to support policy decisions related to provision of assistive technology. IPPA can also be used to structure and evaluate an individual service delivery process. IPPA is a generic effectiveness measure. Basically, it can be used to assess the effectiveness of any kind of assistive technology provision. So far, IPPA has been applied in outcome studies to assess the effectiveness of provision of mobility aids (2,5), transportation ser- vices (2), hearing aids (5), communication devices (5), home adaptations (5), telephone relay services (1) and a robot manipulator (8). In Norway it has been used
Diagnosing the integrity of your performance measurement system

The aim of the research and development work being carried out on Integrated Performance Measurement Systems at the Centre for Strategic Manufacturing in the University of Strathclyde is to develop a Reference Model and an Audit Method for a robust and integrated performance measurement system. The Reference Model is being developed as a result of research into past and present academic work and industry best practices. This paper describes the development and structure of the reference model as well as discussing the principles embedded within the model. The paper concludes with a brief description of the audit method.
The Prevalence of Hearing Loss within Selected U.S. Army Branches

Abstract : The purpose of this investigation was to derive estimates of the prevalence of hearing loss within U.S. Army branches suspected to be high-risk with regard to hearing loss. Questionnaire data were obtained from high-risk personnel concerning their opinions of their hearing ability, hearing protective devices, and exposure to hazardous noises. Audiometric and questionnaire data were obtained from 3000 enlisted men representing three combat branches (i.e., infantry, armor, artillery) and five time-in-service categories. Subjects were selected at random, in proportion to population sizes, from ten Army posts. All of the data gathering was accomplished by the Audiology Officer(s) assigned to each post. The results suggest that the prevalence of hearing loss is approximately the same in the infantry, armor and artillery branches. In contrast, there are substantial differences in the prevalence of hearing loss according to length of time in service. Further, the problem of premature hearing loss among U.S. Army troops affects only the mid- to high-frequency range in the majority of soliders, with speech-reception thresholds and speech discrimination in quiet frequently remaining within normal limits even in advanced cases of noise-induced hearing loss. A comparison of reported profiles and profiles based upon the audiometric data suggests that many soldiers do not appear to carry the appropriate profile for hearing.