Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognizing Paraphrases and Textual Entailment Using Inversion Transduction Grammars

We present first results using paraphrase as well as textual entailment data to test the language universal constraint posited by Wu's (1995, 1997) Inversion Transduction Grammar (ITG) hypothesis. In machine translation and alignment, the ITG Hypothesis provides a strong inductive bias, and has been shown empirically across numerous language pairs and corpora to yield both efficiency and accuracy gains for various language acquisition tasks. Monolingual paraphrase and textual entailment recognition datasets, however, potentially facilitate closer tests of certain aspects of the hypothesis than bilingual parallel corpora, which simultaneously exhibit many irrelevant dimensions of cross-lingual variation. We investigate this using simple generic Bracketing ITGs containing no language-specific linguistic knowledge. Experimental results on the MSR Paraphrase Corpus show that, even in the absence of any thesaurus to accommodate lexical variation between the paraphrases, an uninterpolated average precision of at least 76% is obtainable from the Bracketing ITG's structure matching bias alone. This is consistent with experimental results on the Pascal Recognising Textual Entailment Challenge Corpus, which show surpisingly strong results for a number of the task subsets.
Mitochondrial Uptake of Thiamin Pyrophosphate: Physiological and Cell Biological Aspects

Mammalian cells obtain vitamin B1 (thiamin) from their surrounding environment and convert it to thiamin pyrophosphate (TPP) in the cytoplasm. Most of TPP is then transported into the mitochondria via a carrier-mediated process that involves the mitochondrial thiamin pyrophosphate transporter (MTPPT). Knowledge about the physiological parameters of the MTPP-mediated uptake process, MTPPT targeting and the impact of clinical mutations in MTPPT in patients with Amish lethal microcephaly and neuropathy and bilateral striatal necrosis are not fully elucidated, and thus, were addressed in this study using custom-made 3H-TPP as a substrate and mitochondria isolated from mouse liver and human-derived liver HepG2 cells. Results showed 3H-TPP uptake by mouse liver mitochondria to be pH-independent, saturable (Km = 6.79±0.53 µM), and specific for TPP. MTPPT protein was expressed in mouse liver and HepG2 cells, and confocal images showed a human (h)MTPPT-GFP construct to be targeted to mitochondria of HepG2 cells. A serial truncation analysis revealed that all three modules of hMTPPT protein cooperated (although at different levels of efficiency) in mitochondrial targeting rather than acting autonomously as independent targeting module. Finally, the hMTPPT clinical mutants (G125S and G177A) showed proper mitochondrial targeting but displayed significant inhibition in 3H-TPP uptake and a decrease in level of expression of the MTPPT protein. These findings advance our knowledge of the physiology and cell biology of the mitochondrial TPP uptake process. The results also show that clinical mutations in the hMTPPT system impair its functionality via affecting its level of expression with no effect on its targeting to mitochondria.
Keystroke-level analysis to estimate time to process pages in online learning environments

ABSTRACT It is challenging for students to plan their work sessions in online environments, as it is very difficult to make estimates on how much material there is to cover. In order to simplify this estimation, we have extended the Keystroke-level analysis model with individual reading speed of text, figures, and questions. This was used to estimate how long students might take to work through pages in an online learning environment. The estimates from the model were compared to data collected from 902 volunteer students. Despite the huge differences in reported reading speeds between students, the presented model performs reasonably well and could be used to give learners feedback on how long it takes to work through pages in online learning environments. This feedback could be used to support students’ motivation and effort regulation as they work through online course components. Although the model performs reasonably well, we propose giving feedback in the form of intervals to indicate the uncertainty of the estimates.
The Association between Glomerular Filtration Rate Estimated Using Different Equations and Mortality in the Japanese Community-Based Population: The Yamagata (Takahata) Study

Background To evaluate renal function, the indices of estimated glomerular filtration rate (eGFR) obtained using several equations, including the Japanese versions of the serum creatinine-based MDRD equation (eGFRcreat), Chronic Kidney Disease Epidemiology Collaboration equation (eGFR-EPI), and serum cystatin C-based equation (eGFRcys), are utilized. This study prospectively examined the association between these eGFR values and all-cause mortality during a 12-year observational period in a community-based population. Methods and Results The subjects of this study were 1312 participants undergoing a health checkup, aged ≥40 years. In the total population, the mean eGFR values (mL·min−1·1.73 m−2) were 81.5 for eGFRcreat, 78.1 for eGFR-EPI, and 76.6 for eGFRcys. There were 141 deaths during the observation period, and the area under the receiver operating characteristic curve for predicting mortality was 0.59 for eGFRcreat, 0.67 for eGFR-EPI, and 0.70 for eGFRcys (all P < 0.01). In the Cox proportional analysis adjusted for age and sex, eGFRcys, but not eGFRcreat and eGFR-EPI, showed a significant association with all-cause mortality (per 15 mL·min−1·1.73 m−2 decrease: hazard ratio 1.40, 95% confidence interval 1.18–1.67). Conclusions This study revealed that eGFRcys showed lower values than eGFRcreat and eGFR-EPI and was significantly associated with all-cause mortality in the Japanese community-based population.
The versatility of the Bristow absorption tester – a review

Abstract This paper reviews the use of the Bristow Absorption Tester (known also as the Bristow wheel) in the characterization of fiber-based substrates. The Bristow wheel is a laboratory-scale instrument that has been designed for studying substrate wettability and dynamic liquid absorption properties in short time intervals, which are important in many converting and printing processes of paper and paperboard. The tester also gives information about substrate roughness. The Bristow wheel has shown great usefulness in predicting print quality especially in inkjet applications, in which a good correlation between print quality (letter area) and ink penetration rate has been found by several researchers. The apparatus is particularly useful in dynamic wetting studies, but it has also been successfully used in numerous other research purposes such as the determination of the degree of sizing, evaluation of material glueability, and various coatability studies. Modifications of both the testing principle and the tester structure have also been reported. These include e. g. equipping the apparatus with a corona unit that makes it possible to mimic a printing process on a relevant time-scale. This review summarizes the reported applications of Bristow wheel with a special focus on tester performance and versatility.
A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality.
Adaptive Aggregation Routing to Reduce Delay for Multi-Layer Wireless Sensor Networks

The quality of service (QoS) regarding delay, lifetime and reliability is the key to the application of wireless sensor networks (WSNs). Data aggregation is a method to effectively reduce the data transmission volume and improve the lifetime of a network. In the previous study, a common strategy required that data wait in the queue. When the length of the queue is greater than or equal to the predetermined aggregation threshold (Nt) or the waiting time is equal to the aggregation timer (Tt), data are forwarded at the expense of an increase in the delay. The primary contributions of the proposed Adaptive Aggregation Routing (AAR) scheme are the following: (a) the senders select the forwarding node dynamically according to the length of the data queue, which effectively reduces the delay. In the AAR scheme, the senders send data to the nodes with a long data queue. The advantages are that first, the nodes with a long data queue need a small amount of data to perform aggregation; therefore, the transmitted data can be fully utilized to make these nodes aggregate. Second, this scheme balances the aggregating and data sending load; thus, the lifetime increases. (b) An improved AAR scheme is proposed to improve the QoS. The aggregation deadline (Tt) and the aggregation threshold (Nt) are dynamically changed in the network. In WSNs, nodes far from the sink have residual energy because these nodes transmit less data than the other nodes. In the improved AAR scheme, the nodes far from the sink have a small value of Tt and Nt to reduce delay, and the nodes near the sink are set to a large value of Tt and Nt to reduce energy consumption. Thus, the end to end delay is reduced, a longer lifetime is achieved, and the residual energy is fully used. Simulation results demonstrate that compared with the previous scheme, the performance of the AAR scheme is improved. This scheme reduces the delay by 14.91%, improves the lifetime by 30.91%, and increases energy efficiency by 76.40%.
Review on the Development of New Technology of Biological Nitrogen Removal from Sewage

With the improvement of water treatment technology, the biological nitrogen removal of sewage has also made a great progress. Research economic and efficient denitrification technology has become the hot issues of domestic and foreign scholars. During the long-term operation of wastewater treatment, the differences in physiological and biochemical characteristics of traditional denitrification technologies make various functional microflora interact with each other in the same system, which restricts the efficiency and stability of the process. Therefore, some new treatment technologies emerge. This review introduces the new technology and its development direction of biological nitrogen removal in recent years from two aspects: New technology of the original technology improvement and combination and new technology based on the principle of development, engineering examples in the wastewater treatment industry are enumerated.
G-HBase: A High Performance Geographical Database Based on HBase

With the recent explosion of geographic data generated by smartphones, sensors, and satellites, a data storage that can handle the massive volume of data and support high-computational spatial queries is becoming essential. Although key-value stores efficiently handle large-scale data, they are not equipped with effective functions for supporting geographic data. To solve this problem, in this paper, we present G-HBase, a high-performance geographical database based on HBase, a standard keyvalue store. To index geographic data, we first use Geohash as the rowkey in HBase. Then, we present a novel partitioning method, namely binary Geohash rectangle partitioning, to support spatial queries. Our extensive experiments on real datasets have demonstrated an improved performance with k nearest neighbors and range query in G-HBase when compared with SpatialHadoop, a state-of-the-art framework with native support for spatial data. We also observed that performance of spatial join in G-HBase is on par with SpatialHadoop and outperforms SJMR algorithm in HBase. key words: HBase, high performance, spatial index, GeoHash, BGR Partitioning
Modeling and Simultaneously Removing Bias via Adversarial Neural Networks

In real world systems, the predictions of deployed Machine Learned models affect the training data available to build subsequent models. This introduces a bias in the training data that needs to be addressed. Existing solutions to this problem attempt to resolve the problem by either casting this in the reinforcement learning framework or by quantifying the bias and re-weighting the loss functions. In this work, we develop a novel Adversarial Neural Network (ANN) model, an alternative approach which creates a representation of the data that is invariant to the bias. We take the Paid Search auction as our working example and ad display position features as the confounding features for this setting. We show the success of this approach empirically on both synthetic data as well as real world paid search auction data from a major search engine.
Proposing a Definition and a Framework of Organisational Sustainability : A Review of Efforts and a Survey of Approaches to Change

Organisations (civil society, companies, and public-sector organisations (PSOs)) have been instrumental in driving sustainability. In the last five years, there has been an increasing interest in organisational sustainability, where the importance of sustainability’s dimensions depends on an organisation’s nature and purpose. A large body of literature on organisational sustainability has focused on companies, followed by education institutions, in particular higher education. Limited, yet increasing, attention has been directed to PSOs and other civil society organisations. Although there have been some attempts to define a sustainable organisation, there is still a need to define and establish the principles of how organisations can address and contribute to sustainability. The sustainability efforts in the different types of organisations were reviewed and then analysed in this paper by using hermeneutics. This was complemented with a survey on sustainability changes. The survey was sent to a database of 1574 contacts from different organisations. In addition, 106 anonymous links were sent out. From the total list of emails, 118 full responses were obtained, with 39 from civil society (37 from higher education and 2 NGOs), 66 corporations, and 13 PSOs. This research distils the key system elements of the efforts in each of the organisations in order to synthesise and propose a definition and a conceptual framework of organisational sustainability. These can help organisations understand where their efforts are and how they could better embed sustainability into their systems, thus contributing to the well-being of societies and the environment for this generation and future ones.
Prospects and challenges of virtual machine migration in HPC

The continuous growth of supercomputers is accompanied by increased complexity of the intra‐node level and the interconnection topology. Consequently, the whole software stack ranging from the system software to the applications has to evolve, eg, by means of fault tolerance and support for the rising intra‐node parallelism. Migration techniques are one means to address these challenges. On the one hand, they facilitate the maintenance process by enabling the evacuation of individual nodes during runtime, ie, the implementation of fault avoidance. On the other hand, they enable dynamic load balancing for an improvement of the system's efficiency. However, these prospects come along with certain challenges. On the process level, migration mechanisms have to resolve so‐called residual dependencies to the source node, eg, the communication hardware. On the job level, migrations affect the communication topology, which should be addressed by the communication stack, ie, the optimal communication path between a pair of processes might change after a migration. In this article, we explore migration mechanisms for HPC and discuss their prospects as well as the challenges. Furthermore, we present solutions enabling their efficient usage in this domain. Finally, we evaluate our prototype co‐scheduler leveraging migration for workload optimization.
Semantically Enriched Models for Modal Sense Classification

Modal verbs have different interpretations depending on their context. Previous approaches to modal sense classification achieve relatively high performance using shallow lexical and syntactic features. In this work we uncover the difficulty of particular modal sense distinctions by eliminating both distributional bias and sparsity of existing small-scale annotated corpora used in prior work. We build a semantically enriched model for modal sense classification by novelly applying features that relate to lexical, proposition-level, and discourse-level semantic factors. Besides improved classification performance, especially for difficult sense distinctions, closer examination of interpretable feature sets allows us to obtain a better understanding of relevant semantic and contextual factors in modal sense classification.
Exceptional Heterogeneity in Viral Evolutionary Dynamics Characterises Chronic Hepatitis C Virus Infection

The treatment of HCV infection has seen significant progress, particularly since the approval of new direct-acting antiviral drugs. However these clinical achievements have been made despite an incomplete understanding of HCV replication and within-host evolution, especially compared with HIV-1. Here, we undertake a comprehensive analysis of HCV within-host evolution during chronic infection by investigating over 4000 viral sequences sampled longitudinally from 15 HCV-infected patients. We compare our HCV results to those from a well-studied HIV-1 cohort, revealing key differences in the evolutionary behaviour of these two chronic-infecting pathogens. Notably, we find an exceptional level of heterogeneity in the molecular evolution of HCV, both within and among infected individuals. Furthermore, these patterns are associated with the long-term maintenance of viral lineages within patients, which fluctuate in relative frequency in peripheral blood. Together, our findings demonstrate that HCV replication behavior is complex and likely comprises multiple viral subpopulations with distinct evolutionary dynamics. The presence of a structured viral population can explain apparent paradoxes in chronic HCV infection, such as rapid fluctuations in viral diversity and the reappearance of viral strains years after their initial detection.
Optimal Macroprudential-Fiscal Policy and Financial Stability The Effects on Private Debt Deleveraging in Advanced and Emerging Economies

What is the optimal interaction between macroprudential and fiscal policy to foster financial stability? This thesis evaluates whether policy interaction can impact private debt growth. First, a model is built with borrowing constraints that illustrate the links between private and public debt dynamics. The derived hypothesis and theoretical predictions indicate that a tighter macroprudential stance is reinforced by prudential fiscal policies, conditional on the initial level of public debt and scope for countercyclical fiscal policies. Second, the hypothesis is tested by using a dynamic panel data model for a sample of 49 advanced and emerging economies over the period 2000-2013. Whilst the interaction term alone yields insignificant results, interesting inferences can be drawn of the findings within the context of existing literature. The suggestion is that there may exist two opposing effects associated with the interaction between macroprudential and fiscal policy on private debt. Moreover the outcome of this interaction is contingent upon the levels of public debt and private indebtedness.
An approach to modelling DC-DC converter circuits using graph theoretic concepts

An approach to modelling DC-DC converter circuits based on graph theoretic concepts is discussed in this paper. the DC-DC converter circuits are treated as networks containing switches, with the magnitudes of their associated eigenvalues much smaller than the switching frequency. the procedure for modelling this class of networks essentially involves separating the original network into two N-port networks, one containing those branches responsible for all phenomena peculiar to the switching action and the other containing the remaining branches of the network. the two N-port networks thus formed lead to a systematic and convenient way of developing low-frequency circuit models for DC-DC converter circuits.
Combining Specialized Entailment Engines Bernardo Magnini

In this paper we propose a general method for the combination of specialized textual entailment engines. Each engine is supposed to address a specific language phenomenon, which is considered relevant for drawing semantic inferences. The model is based on the idea that the distance between the Text and the Hypothesis can be conveniently decomposed into a combination of distances estimated by single and disjoint engines over distinct linguistic phenomena. We provide both the formal definition of the model and preliminary empirical evidences supporting the underlying intuition.
A comparative study of search and optimization algorithms for the automatic control of physically realistic 2-D animated figures

In the Spacetime Constraints paradigm of animation, the animator speci(cid:12)es what a character should do, and the details of the motion are generated automatically by the computer. Ngo and Marks [11, 12] recently proposed a technique of automatic motion synthesis that uses a massively parallel genetic algorithm to search a space of motion controllers that generate physically realistic motions for 2D articulated (cid:12)gures. In this paper, we describe an empirical study of evolutionary computation algorithms and standard function optimization algorithms that were implemented in lieu of the massively parallel GA in order to (cid:12)nd a substantially more e(cid:14)cient search algorithm that would be viable on serial workstations. We discovered that simple search algorithms based on the evolutionary programming paradigm were most e(cid:14)cient in searching the space of motion controllers. 1