Miracle-dz/UniFAR-FTUs huggingface dataset:
Swimming mediated by ciliary beating: comparison with a squirmer model

The squirmer model of Lighthill and Blake has been widely used to analyse swimming ciliates. However, real ciliates are covered by hair-like organelles, called cilia; the differences between the squirmer model and real ciliates remain unclear. Here, we developed a ciliate model incorporating the distinct ciliary apparatus, and analysed motion using a boundary element–slender-body coupling method. This methodology allows us to accurately calculate hydrodynamic interactions between cilia and the cell body under free-swimming conditions. Results showed that an antiplectic metachronal wave was optimal in the swimming speed with various cell-body aspect ratios, which is consistent with former theoretical studies. Exploiting oblique wave propagation, we reproduced a helical trajectory, like Paramecium, although the cell body was spherical. We confirmed that the swimming velocity of model ciliates was well represented by the squirmer model. However, squirmer modelling outside the envelope failed to estimate the energy costs of swimming; over 90 % of energy was dissipated inside the ciliary envelope. The optimal swimming efficiency was given by the antiplectic wave; the value was 6.7 times larger than in-phase beating. Our findings provide a fundamental basis for modelling swimming micro-organisms.
Environmental Tracers Applied to Quantifying Causes of Salinity in Arid-Region Rivers : Preliminary Results from the Rio Grande , Southwestern USA

The upper Rio Grande extends ~1,200 km between its headwaters in southern Colorado (USA) and the USA/Mexico border region. Over this distance the total dissolved solids content of the water increases from ~40 mg L to over 2,000 mg L. This increase has previously been attributed to evapotranspirative concentration and to flushing by irrigation water of salts accumulated by pre-irrigation evapotranspiration. We employed environmental tracers, including δO, δH, Cl, and the Cl/Br ratio to help identify the causes of salinization. Both δO and δH are enriched with flow distance due to evaporation, but not sufficiently to explain most of the salinization as caused by evapotranspiration. The Cl/Br ratio increases from about 50 in the headwaters to over 1,000 at the distal end of the river basin, indicating influx of subsurface saline waters, which are commonly characterized by high Cl/Br ratios. The Cl concentration and the Cl/Br ratio increase in a step-wise fashion and are typically localized at the southern ends of the sedimentary basins comprising the Rio Grande Rift, suggesting that the salts are from discharge of deep ground water where it is forced to the surface by bedrock highs, rather than due to flushing by irrigation water.
Structured Representations for Coreference Resolution

Coreference resolution is the task of determining which expressions in a text are used to refer to the same entity. This task is one of the most fundamental problems of natural language understanding. Inherently, coreference resolution is a structured task, as the output consists of sets of coreferring expressions. This complex structure poses several challenges since it is not clear how to account for the structure in terms of error analysis and representation. In this thesis, we present a treatment of computational coreference resolution that accounts for the structure. Our treatment encompasses error analysis and the representation of approaches to coreference resolution. In particular, we propose two frameworks in this thesis. The first framework deals with error analysis. We gather requirements for an appropriate error analysis method and devise a framework that considers a structured graph-based representation of the reference annotation and the system output. Error extraction is performed by constructing linguistically motivated or data-driven spanning trees for the graph-based coreference representations. The second framework concerns the representation of approaches to coreference resolution. We show that approaches to coreference resolution can be understood as predictors of latent structures that are not annotated in the data. From these latent structures, the final output is derived during a post-processing step. We devise a machine learning framework for coreference resolution based on this insight. In this framework, we have a unified representation of approaches to coreference resolution. Individual approaches can be expressed as instantiations of a generic approach. We express many approaches from the literature as well as novel variants in our framework, ranging from simple pairwise classification approaches to complex entity-centric models. Using the uniform representation, we are able to analyze differences and similarities between the models transparently and in detail. Finally, we employ the error analysis framework to perform a qualitative analysis of differences in error profiles of the models on a benchmark dataset. We trace back differences in the error profiles to differences in the representation. Our analysis shows that a mention ranking model and a tree-based mention-entity model with left-to-right inference have the highest performance. We discuss reasons for the improved performance and analyze why more advanced approaches modeled in our framework cannot improve on these models. An implementation of the frameworks discussed in this thesis is publicly available.
Loughborough University Institutional Repository The effect of clinician-patient alliance and communication on treatment adherence in mental health care : a systematic review

Background: Nonadherence to mental health treatment incurs clinical and economic burdens. The clinician-patient alliance, negotiated through clinical interaction, presents a critical intervention point. Recent medical reviews of communication and adherence behaviour exclude studies with psychiatric samples. The following examines the impact of clinician-patient alliance and communication on adherence in mental health, identifying the specific mechanisms that mobilise patient engagement. Methods: In December 2010, a systematic search was conducted in Pubmed, PsychInfo, Web of Science, Cochrane Library, Embase and Cinahl and yielded 6672 titles. A secondary hand search was performed in relevant journals, grey literature and reference. Results: 23 studies met the inclusion criteria for the review. The methodological quality overall was moderate. 17 studies reported positive associations with adherence, only four of which employed intervention designs. 10 studies examined the association between clinician-patient alliance and adherence. Subjective ratings of clinical communication styles and messages were assessed in 12 studies. 1 study examined the association between objectively rated communication and adherence. Meta-analysis was not possible due to heterogeneity of methods. Findings were presented as a narrative synthesis. Conclusions: Clinician-patient alliance and communication are associated with more favourable patient adherence. Further research of observer rated communication would better facilitate the application of findings in clinical practice. Establishing agreement on the tasks of treatment, utilising collaborative styles of communication and discussion of treatment specifics may be important for clinicians in promoting cooperation with regimens. These findings align with those in health communication. However, the benefits of shared decision making for adherence in mental health are less conclusive than in general medicine.
Pathology and cancer in Africa

In high-income countries, it would be inconceivable to treat a tumour when its pathology is unknown. However, this can be the case among patients in sub-Saharan Africa. The absence of pathologists and the resultant delays in reporting contribute to patients being treated before the nature of the lesion is known. This is compounded by the frequent absence of auxiliary tests to better define tumour characteristics.
A promising Fruit Cherry laurel Prunus laurocerasus L and steps on breeding

Cherry laurel ( Prunus laurocerasus L.), is a fruit native to the regions bordering the Black Sea in Southwestern Asia and Southeastern Europe and widely spread out in the North part of Turkey. There are many cultivars which show different characteristics in Turkey and germplasm provides a rich parental material for crossing opportunities. The cherry laurel tree has pleasant fruits when fully ripe and also is a valuable fruit for industrial uses. Production of this fruit has increased over time and evaluation possibilities are varied. The detailed information about characteristics and nutritional value of cherry laurel was obtained from earlier studies and served for breeding of new cultivars. Studies on breeding of this species are focused on selection of superior types, resistance to disease, environmental adaptability, and molecular mapping of these types. This review aims to create a perspective to results of undergoing studies and discusses an overview of breeding opportunities of cherry laurel.
Improving Communication in Chip Multiprocessors Using Emerging Technologies and Machine Learning

Improving Communication in Chip Multiprocessors Using Emerging Technologies and Machine Learning Parisa Khadem Hamedani Doctor of Philosophy Graduate Department of Electrical and Computer Engineering University of Toronto 2017 Technology scaling along with power and thermal limitations ushers the industry to the many-core system era. Thread level parallelism and complex applications demand a communication architecture that can provide high bandwidth communication and facilitate efficient usage of the computational units. Therefore, the communication architecture plays a major role in the performance of applications and the energy expended on data movements. The communication framework can be viewed at: 1) the interconnect infrastructure (physical) level and, 2) the inter-thread communication (logical) level. This thesis offers three different approaches to address the communication issues in many-core systems at the physical and the logical levels. First, we propose a novel low-power all-optical Networks-on-Chip (NoC) with a deterministic wavelength routing algorithm. This routing algorithm is based on wavelength division multiplexing that allows us to reduce the number of wavelengths and optimize micro-ring resonators in optical switches. The key advantages of our optical network are simplicity and lower power consumption. Second, to improve performance of on-chip interconnect infrastructure, we employ three-dimensional (3D) integration technology. To tackle the temperature issues in 3D NoCs, we model the mapping problem as an Integer Linear Programing (ILP) problem and propose three static ILP-based thermal-aware mapping algorithms. We then investigate the thermal constraints and their effects on temperature and performance. Third, we propose a new scheme to dynamically predict the critical path of a multi-threaded application. We formulate the cache statistics and the barrier arrival times as a machine learning problem to predict critical threads. We propagate criticality of these critical threads to the other threads using lock contention information. This dissertation demonstrates how opportunities at the physical and logical levels can be used to improve the communication framework.
The Competitive Advantage and Strategic Configuration of Knowledge-Intensive , Small & Medium-Sized Multinationals : A Modified Resource-Based View

This study employs a modified resource-based approach to examine the competitive advantage enjoyed by knowledge-intensive, small and medium-sized multinationals (KI-SMMs). Compared to larger knowledge-intensive multinationals, KI-SMMs possess both superior and inferior core capabilities. The paper demonstrates how KI-SMMs compete globally by leveraging their relatively superior R&D capabilities and by choosing a strategic configuration that allows them to compete internationally despite their relatively inferior capabilities in marketing and production activities Our results show that KI-SMMs internalize R&D activities, which we view as core capabilities, externalize production activities, which are viewed here as non-core capabilities, and internalize marketing activities, for which they have an inferior capacity, but which are, arguably, core capabilities. KI-SMMs compensate for their inferior capabilities in marketing activities by focusing on customers with whom a low number of high value transactions can be maintained.
Do Employees Reciprocate to Intra-Firm Trainings ? An Analysis of Absenteeism and Turnover Rates

This paper studies the behavioral e¤ects of intra- rm trainings on absence behavior and turnover probability. We argue that participation in rm-sponsored trainings might lead to behavioral responses among employees. When rms pay for general trainings, employees may perceive this as a gift to which they can reciprocate by providing higher levels of e¤ort or commitment. Based on the personnel records of a large multinational rm we nd that, in contrast to human capital predictions, general trainings lead to a decrease in turnover rates. Furthermore, a short-term decrease in absenteeism indicates a temporary, reciprocal reaction by employees. Key Words: Training, Human Capital, Reciprocity, Turnover, Absenteeism JEL Classi cation: D64, J24, J31, M50, M53 We thank Bernd Irlenbusch, Matthias Kräkel, Dirk Sliwka and Thomas Zwick as well as conference and seminar participants in Cologne, Göttingen and Paderborn for helpful comments and suggestions. yBoth University of Cologne, Albertus-Magnus-Platz, 50923 Köln, Germany. zCorresponding author: Tel: +49 221 470-2584, e-mail: patrick.kampkoetter@unikoeln.de
Venture Capital and New Business Creation : International Evidence

Using a comprehensive database of European rms from 21 countries over the period 1998-2008, we nd that venture capital investment has a positive e ect on the rate of new business creation. This is especially true in R&D-intensive industries and in countries with lower taxes on capital gains and higher human capital. We address endogeneity by exploiting data on buyout fundraising, pension fund assets, and on laws that regulate risk capital investments by pension funds. Our results hold when we account for barriers to entry, general access to credit, protection of intellectual property, and labor regulations.
Optimal dynamic portfolio with mean-CVaR criterion Risks

Value-at-risk (VaR) and conditional value-at-risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of a Neyman–Pearson type binary solution. We add a constraint on expected return to investigate the mean-CVaR portfolio selection problem in a dynamic setting: the investor is faced with a Markowitz type of risk reward problem at the final horizon, where variance as a measure of risk is replaced by CVaR. Based on the complete market assumption, we give an analytical solution in general. The novelty of our solution is that it is no longer the Neyman–Pearson type, in which the final optimal portfolio takes only two values. Instead, in the case in which the portfolio value is required to be bounded from above, the optimal solution takes three values; while in the case in which there is no upper bound, the optimal investment portfolio does not exist, though a three-level portfolio still provides a sub-optimal solution.
Testing Stationarity of Consumption-Income Ratios Incorporating Nonlinearities and Asymmetries : Evidence from Emerging Economies

To account for the nonlinearities and asymmetries while studying the stochastic properties of consumptionincome ratios, Average Propensity to Consume (APC), for fourteen emerging economies, this study calls in the exponential smooth transition autoregressive (ESTAR) and asymmetric exponential smooth transition autoregressive (AESTAR)unit root testing procedures developed by Kapetanios, Shin, & Snell (2003) and Sollis (2009). Except for Chile, Morocco and Peru, consumption-income ratios turn out to be non-stationary processes for the selected time periods. Thus, the consumption behaviors in these countries appear to be congruent with the Absolute Income Hypothesis (AIH), Involuntary Savings and Marxian Under-compensating Theories. Accordingly, the policy implications have permanent effects on the consumption of households for all the countries except for Chile, Morocco and Peru. This warrants the use of fiscal policy for these countries.
Is there a trade-off between monetary independence and exchange rate stability in Central and Eastern European economies ?

The paper examines the relation between the exchange rate flexibility and monetary independence in Central and Eastern European (CEE) economies. According to the conventional open economy model one of the important advantages of the floating exchange rate regime is that a country can pursue an autonomous monetary policy. Recently the empirical validity of the trilemma has been questioned: H. Rey argued that the choice is between openness to financial flows and monetary independence, ‘irreconcilable duo’, no matter which exchange rate regime prevails. We derive a contagion model of monetary policy to examine whether the degree of ‘policy contagion’ is indeed unrelated to the exchange rate flexibility in CEE economies. Our main findings are that: (1) the spillover effect from the euro area monetary policy is strong for the Czech Republic, but rather weak for Hungary, Poland and Romania; (2) the trilemma monetary policy independence indices are rather crude and their informativeness is substantially limited; (3) the CEE countries, except for the Czech Republic, are likely to maintain their monetary independence in the face of future ECB’s exit from the zero-interest-rate policy.
Multi-Temporal Monsoon Crop Biomass Estimation Using Hyperspectral Imaging

Hyperspectral remote sensing is considered to be an effective tool in crop monitoring and estimation of biomass. Many of the previous approaches are from single year or single date measurements, even though the complete crop growth with multiple years would be required for an appropriate estimation of biomass. The aim of this study was to estimate the fresh matter biomass (FMB) by terrestrial hyperspectral imaging of the three crops (lablab, maize and finger millet) under different levels of nitrogen fertiliser and water supply. Further, the importance of the different spectral regions for the estimation of FMB was assessed. The study was conducted in two experimental layouts (rainfed (R) and irrigated (I)) at the University of Agricultural Sciences, Bengaluru, India. Spectral images and the FMB were collected over three years (2016–2018) during the growing season of the crops. Random forest regression method was applied to build FMB models. R² validation (R²val) and relative root mean square error prediction (rRMSEP) was used to evaluate the FMB models. The Generalised model (combination of R and I data) performed better for lablab (R²val = 0.53, rRMSEP = 13.9%), maize (R²val = 0.53, rRMSEP = 18.7%) and finger millet (R²val = 0.46, rRMSEP = 18%) than the separate FMB models for R and I. In the best derived model, the most important variables contributing to the estimation of biomass were in the wavelength ranges of 546–910 nm (lablab), 750–794 nm (maize) and 686–814 nm (finger millet). The deviation of predicted and measured FMB did not differ much among the different levels of N and water supply. However, there was a trend of overestimation at the initial stage and underestimation at the later stages of crop growth.
Career Concerns and Strategic Effort Allocation by Analysts

We examine how sell-side analysts allocate their effort among firms in their research portfolios and the consequences of their effort allocation decisions. We show that analysts play favorites among portfolio firms by strategically devoting more effort to firms that are relatively more important for their career concerns. Specifically, we find that within each analyst’s portfolio, firms ranked relatively higher based on market capitalization, trading volume, or institutional ownership receive more frequent, accurate, and informative earnings forecast revisions and stock recommendation changes that contain greater information content. As a result, these firms display less information asymmetry and exhibit higher stock market liquidity and lower costs of capital. Moreover, we find that analysts who engage in a greater extent of strategic effort allocation are more likely to experience favorable career outcomes.
A Statistical Analysis of Melody Curves in the Intonation of American English

Pitch and duration characteristics of the melodies of American English (intonation) have been investigated by many researchers and several factors were found to influence them. In this study, in addition to pitch and duration characteristics, pitch patterns of American English were investigated statistically by introducing a method of evaluating the Fo in the pitch shifts and that of normalizing the duration of melody curves. By the introduction of such methods, it became possible to use a simple statistical index (correlation coeflicient) to compare the similarity or dissimilarity of any pair of melody curves. The authors believe that the comparative study of the variability of melody curves is important for the understanding of the functions and the structures of intonation in English. Eight sets of ten sentences were recorded and analyzed. These were conversational sentences in American English. All were simple sentences including statements, wh questions and yes-no questions and varied from one to ten syllables in length. A sample of a sentence set is shown in Table ]. Forty-eight students of the Ohio State University served as speakers. They were assigned to eight sentence sets: six speakers in each set. All groups included the same number of male and female speakers. Speakers were requested to produce as many different intonations as they could think of in recording each of the ten sentences in the set assigned to them. They were also asked to provide a written description of the intended meaning. In recording the sentences a combination of a dynamic microphone (Shure Bros., Model 545) and a Magnecord 1022 was used. For reproduction and extraction of the Fo, a combination of a Magnecord, Transpitchmeter and a Mingograf was used. Fundamental frequencies were measured at every 40 msec. Statistical analyses of the data were made by using the computing facilities of the Instruction and Research Computer Center of the Ohio State University. Statistics such as the mean, standard deviation, duration, and rate of frequency change were computed from the Fo of each utterance. They were considered to correspond with listeners’ perception of pitch level, pitch range, length, and rate of