Miracle-dz/UniFAR-FTUs huggingface dataset:
CDS Proxy Construction via Machine Learning Techniques—Part II: Parametrization, Correlation, Benchmarking

This is the second of two articles by the authors on the construction of credit default swap (CDS) proxy rates. In the first article, the authors proposed a machine learning (ML)-based proxy-rate construction technique that uses classification to construct so-called proxy names whose liquidly quoted CDS rates can be used as CDS proxy rates. The authors then compared the performances of ML classifiers from the eight most popular classifier families as a function of carefully selected sets of feature variables. In this second article, the authors take a closer look at the performances of the individual classifiers as a function of their different parametrizations, which they refer to as an intra-classifier performance study. The authors also examine the effects of feature variable correlations on classifier performance and perform a benchmarking exercise by comparing the ML-based CDS-proxy technique with two currently used proxy-rate construction methods: curve mapping and cross-sectional regression.
58-OR: The Novel Dual GIP and GLP-1 Receptor Agonist Tirzepatide Transiently Delays Gastric Emptying Similarly to a Selective Long-Acting GLP-1 Receptor Agonist

A long-acting GLP-1 receptor agonist (RA) transiently delays gastric emptying (GE). We investigated the GE effect of a novel dual GIP and GLP-1 RA, tirzepatide (TZP), compared to that of a selective GLP-1 RA in nonclinical and clinical studies. No effect on GE was seen with GIP RA alone in mice. Combination of GIP RA with GLP-1 RA or a dual agonist, TZP, did not delay GE more than GLP-1 RA alone. The effect of TZP on GE was evaluated in a Phase 1 study, comprising 4 week multiple ascending dose (MAD; N=35) QW in healthy subjects and 4-week proof of concept (PoC) (N=53) in patients with T2DM. In MAD, TZP was administered QW at fixed doses of 0.5, 1.5, 4.5 mg, and a titration dose of 5-5-8-10 mg. A selective GLP-1 RA, dulaglutide (dula), 1.5 mg QW was also included. In PoC, TZP was administered QW at fixed doses of 0.5 mg and 5 mg, and at titration doses of 5-5-10-10 mg and 5-5-10-15 mg. Acetaminophen (APAP) was administered on Day -1 (prior to TZP or dula), at 24 hours after the first (Day 2) and fourth (Day 23) doses to coincide with peak TZP or dula exposure. Impact of TZP on GE was evaluated using APAP Cmax, AUC, and tmax, compared to placebo (PL). Baseline adjusted Cmax of APAP (ratio to Day -1) was used to compare the GE effect of TZP with that of dula. APAP Cmax decreased by approximately 50% and tmax was delayed by an hour after the first TZP dose (doses >1.5 mg), suggesting a delay in GE while AUC was not notably altered. Evaluation of APAP PK after the first and fourth doses of the fixed dose regimen of TZP showed that impact of TZP on GE was maximized after first dose (Day 2 vs. PL), and showed complete tachyphylaxis after repeated dosing (Day 23 vs. PL). Similarly, in the titration cohort, impact of TZP on GE was significant after the first dose. However, incomplete tachyphylaxis was observed after 4 weeks of TZP administration due to the titration regimen. Impact of the fixed doses of TZP on GE was comparable to that of a selective GLP 1 RA (dula). Disclosure S. Urva: None. M.A. Nauck: Advisory Panel; Self; AstraZeneca, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S. Research Support; Self; AstraZeneca, Eli Lilly and Company, GlaxoSmithKline plc. , Merck Sharp & Dohme Corp., Novo Nordisk A/S. Speaker9s Bureau; Self; AstraZeneca, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sun Pharma. T. Coskun: Employee; Self; Eli Lilly and Company. X. Cui: Employee; Self; Eli Lilly and Company. A. Haupt: Employee; Self; Lilly Diabetes. Stock/Shareholder; Self; Lilly Diabetes. C. Benson: Employee; Self; Eli Lilly and Company. C. Loghin: Employee; Self; Eli Lilly and Company.
EFFECTS OF FISCAL DECENTRALIZATION ON POVERTY REDUCTION IN KENYA

The Kenya government has instituted fiscal decentralization over the years to promote social economic development, reduce poverty and income inequality and ensure balanced regional development. Despite these efforts, poverty levels have remained high in Kenya. The literature on the relationship between fiscal decentralization and poverty has been rather inconclusive about the effects of fiscal decentralization on poverty. The main objective of this paper was to analyse the effects of fiscal decentralization on poverty in Kenya. Using cross-county panel data from 2002 – 2014 and published data from government agencies, UNDP reports and World Bank reports, the paper estimated various empirical models to analyse the effects intergovernmental transfers, sub-national own-source revenue and county expenditure on poverty in Kenya. The study established that the effect of fiscal decentralization on poverty depends on the nature of decentralization and the extent of fiscal decentralization as well as the county specifics. The paper therefore, recommends the need for for county governments to have adequate own-source revenue to finance their expenditure as opposed to relying on intergovernmental transfers from national government.
Video Processing Techniques for the Contactless Investigation of Large Oscillations

The experimental acquisition of large vibrations presents various technical difficulties. Especially in the case of geometric nonlinearities, dealing with very flexible, very light structures causes minimal variations in mass or stiffness to affect severely the dynamical response. Thus, sensors’ added masses change the behaviour of the structure with respect to the unloaded condition. Moreover, the most common tools regularly employed for acquisition in vibration analysis - that is to say, laser vibrometers and accelerometers - are often designed with small amplitudes in mind. Their recordings are known to lack accuracy when the investigated structure undergoes large or very large motions, due to geometrical reasons. Image-based measurement techniques offer a valid solution to this problem. Here, an ensemble of three video processing techniques are benchmarked against each other and tested as viable options for the non-contact dynamic characterisation of slender beam-like structures. The methods have been applied to the case study of an aluminium spar for a highly-flexible airwing prototype and compared to the measurements recorded by a laser velocimeter and several Raspberry PI Inertial Measurement Units (IMUs), which also proved to be minimally invasive.
Motivation factors and barriers to the continuous use of blended learning approach using Moodle: students' perceptions and individual differences

ABSTRACT Practitioners of blended learning encounter challenges on how to cater students individual needs and to increase their motivational involvement with the system. Therefore, this study aims to identify and evaluate the motivation factors and barriers that influence students' decisions to continue using blended learning based on Moodle platform. The study proposes a research model to gain a better understanding of students' behavioural attitudes, motivations, and barriers to the continuous use of blended learning. In addition, a multi-group analysis was conducted to examine individual differences between students from three different universities in Palestine. The findings provide a comprehensive understanding of students' behaviours and the investigated factors of the proposed model were truly significant in forming students' perceptions and reflecting their decisions to continue using such learning approach. Features of blended learning system were found to be the most significant motivational antecedents in relation to influencing students' perceptions and involvements in the learning environment, while perceived behavioural control and subjective norms were found to be the primary factors driving students' continuous use. Finally, the findings shed light on the impact of individual differences on students' perceptions and usage behaviours and suggest that these differences could be leveraged to provide adaptive usage decisions.
Practice trends and the outcome of neuromodulation therapies in epilepsy: A single‐center study

Neuromodulation therapies (VNS, RNS, and DBS) can improve seizure control in persons with epilepsy. However, there is a significant service gap in integrating these therapies in clinical care. Our epilepsy center has established an epilepsy neuromodulation clinic to improve access to patients, communication with referring physicians, track outcome and train future providers in programming neuromodulation devices. We report the (a) treatment outcome of the available neuromodulation therapies (ie, reduction in seizure frequency over 6‐12 months follow‐up); and (b) demonstrate the benefit of the specialized clinic (rapid titration, continuity of care, superior access for patient and vendors). In this single‐center, retrospective study, forty‐three adults (VNS = 27; RNS = 16) with drug‐resistant epilepsy were followed in the clinic during the 19 months study period. About 44‐69% of patients reported > 60% decrease in seizure. All patients were scheduled in the clinic within 2‐4 weeks, and stimulations were optimized rapidly. About 40% of patients participated in research while 28% were referred for additional diagnostic studies. Nineteen students and fellows were trained in programming neurostimulator. Epilepsy neuromodulation clinic can serve as an optimal solution for patients as well as providers due to rapid access, better continuity of care, higher recruitment for research studies, and training health professionals.
Multifamily Groups in the Treatment of Severe Psychiatric Disorders

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Mapping orthographic and phonological neighborhood density effects in visual word recognition in two distinct orthographies

Mapping Orthographic and Phonological Neighborhood Density Effects in Visual Word Recognition in Two Distinct Orthographies. (May 2007) Hsin-Chin Chen, B.S., National Taiwan University; M.S., National Taiwan University Chair of Advisory Committee: Dr. Jyotsna Vaid A central issue in word recognition is how readers retrieve and select the right representation among others in the mental lexicon. Recently, it has been claimed that recognition of individual words is influenced by the degree to which the words possess unique vs. shared letters or sounds relative to other words, that is, whether the words have few or several neighbors. Research on so-called neighborhood density effects advances understanding of the organization and operation of the mental lexicon. Orthographic neighborhood effects have been claimed to be facilit ative, but recent studies of visual word recognition have led to a revised understanding of the nature of the orthographic neighborhood density effect. Through a reexamination of orthographic and phonological neighborhood density effects, the specific objective of the present research is to understand how orthographic and phonological representations interact across two different writing systems, i.e., English (an alphabetic orthography) and Chinese (a morphosyllabic orthography). The phenomena were studied using a joint behavioral (lexical decision) and neural imaging approach (near infrared spectroscopy, or NIRS).
Syntax-based language models for statistical machine translation

The goal of machine translation is to develop algorithms that produce human-quality translations of natural language sentences. The evaluation of machine translation quality is split broadly into two aspects: adequacy and fluency. Adequacy measures how faithfully the meaning of the original sentence is preserved, whereas fluency measures whether this meaning is expressed in valid sentences in the target language. While both of these criteria are difficult to meet; fluency is a much more difficult goal. Generally, this likely has something to do with the asymmetrical nature of producing and understanding sentences; although humans are quite robust at inferring the meaning of text even in the presence of lots of noise and error, the rules that govern grammatical utterances are exacting, subtle; and elusive. To produce understandable text, we can rely on this robust processing hardware, but to produce grammatical text, we have to understand how it, works. This dissertation attempts to improve the fluency of machine translation output by explicitly incorporating models of the target language structure into machine translation systems. It is organized into three parts. First, we propose a framework for decoding that decouples the structures of the sentences of the source and target languages, and evaluate it with existing grammatical models as language models for machine translation. Next, we apply lessons from that task to the learning of grammars more suitable to the demands of the machine translation. We then incorporate these grammars, called Tree Substitution Grammars, into our decoding framework.
An Adaptive Archive-Based Evolutionary Framework for Many-Task Optimization

Multi-task optimization is an emerging research topic in computational intelligence community. In this paper, we propose a novel evolutionary framework, many-task evolutionary algorithm (MaTEA), for many-task optimization. In the proposed MaTEA, an adaptive selection mechanism is proposed to select suitable “assisted” task for a given task by considering the similarity between tasks and the accumulated rewards of knowledge transfer during the evolution. Besides, a knowledge transfer schema via crossover is adopted to exchange information among tasks to improve the search efficiency. In addition, to facilitate measuring similarity between tasks and transferring knowledge among tasks that arrive at different time instances, multiple archives are integrated with the proposed MaTEA. Experiments on both single-objective and multi-objective optimization problems have demonstrated that the proposed MaTEA can outperform the state-of-the-art multi-task evolutionary algorithms, in terms of search efficiency and solution accuracy. Besides, the proposed MaTEA is also capable of solving dynamic many-task optimization where tasks arrive at different time instances.
FDD Cooperative Channel Estimation and Feedback for 3D Massive MIMO System

In this paper, a downlink cooperative channel estimation scheme is proposed for the three-dimensional massive multiple inputs multiple outputs (3D-mMIMO) system operating in the frequency division duplexing (FDD) mode. In the proposed cooperative scheme, users have to cooperate with each other via device-to-device (D2D) communication protocol to jointly exploit the sparsity structure property of the channel. Motivated by the sparsity property of the mMIMO channel in the angle-time domain, a parametric feedback scheme is proposed, where the feedback overhead is decreased by sending a limited version of the estimated coefficients rather than all the coefficients back to the BS. Then, a compressive sensing (CS) algorithm is proposed, which we named weighted fast iterative shrinkage thresholding (WFISTA). In the WFISTA, we first introduce new weights and threshold function to the original FISTA to enhance its sparsity-undersampling trade-off in the single measurement vector (SMV) case, then we extend the proposed WFISTA to the case of multiple measurement vector (MMV) problem by adopting ReMBo (reduce MMV and boost) strategy. The proposed WFISTA has the ability to estimate the mMIMO system’s channel coefficients by exploiting the joint sparsity structure through cooperation among users’ equipment (UEs). Complexity analysis and the probability of decreasing the feedback overhead are provided for the proposed cooperative estimation scheme. The simulation results verify the efficiency of the proposed cooperative algorithm scheme compared to several joint channel estimations.
Price Equilibriums, and Rationality of Price Equilibriums within Stock Markets

This study models price equilibriums that feasibly could obtain within stock markets. In all, the model generates five feasible price equilibriums. Given the equilibrium most attractive to issuers is characterized by presence of rational valuation bubbles, formal predictions show stock prices are prone to development of rational valuation bubbles. In presence of arrival of new innovations within stock markets prior to exhaustion of innovativeness of `previously new' innovations, rational valuation bubbles are maintained ad infinitum. If arrival rates for new innovations lag exhaustion rates for previously new innovations, stock markets experience market correction events. As reasonably could be expected, the formal model provides evidence for feasibility of irrational valuation bubbles within stock markets. Consistent with expectations, where they occur, irrational bubbles are larger in magnitude than corresponding rational bubbles. In this respect, formal predictions show evolution of return processes can be efficient, yet be generated by less than fully rational or irrational game theoretic actions undertaken by issuers or investors at some origin point in time. The study generates two test statistics for rationality of price equilibriums within stock markets, test statistics which, consistent with normative characterization of such statistics, embed jointness of stock prices and returns.
Coverage and capacity analysis for the multi-layer CDMA macro/indoor-picocells

This paper presents an analysis of coverage and capacity for the multi-layer CDMA cellular system. The multilayer CDMA system, that shares a common frequency band, consists of macrocells for outdoor users and picocells for indoor users. Though macrocells and picocells interfere with each other, the capacity of the whole system can be increased. We have analyzed the effect of mutual interference upon cell coverage, soft handover areas, and capacities. The parameters involved in the engineering of the system are discussed. The study results show that we can control the service coverage of indoor picocells with the system parameters set properly. It is also shown that the capacity of the whole system can be enhanced smoothly by deploying the indoor picocells within existing macrocells.
Does size matter? Comparing the party politics of climate change in Australia and Norway

ABSTRACT The implications of state size for the party politics of climate change are examined, and in particular its effect in facilitating or impeding cross-party consensus on the issue. This issue is explored through an in-depth, qualitative comparison of Australia and Norway, which are shown to be comparable in important respects yet differ in terms of their size and climate politics. Original primary data is presented from 44 interviews with policymakers and policy-shapers in both countries, which shows that, to the limited extent that state size moderates the parties’ behaviour, it is the countries’ geographical – not economic – size that matters. Institutional factors are found to play a more significant role, however, and the corporatist features of state-business cooperation, strong ENGOs and compensatory welfare arrangements are highlighted as particularly important.
Regional Economic Convergence and Spatial Spillovers in Turkey

Using sigma and beta convergence methods, this study tests economic convergence in Turkish NUTS-2 regions between 2004-2011. The findings of sigma convergence show that, in accordance with the literature, the interregional income gap decreases during economic recession periods and increases during economic expansion periods. The beta convergence results obtained by the cross-sectional and panel estimations indicate the existence of absolute convergence. In addition, spatial data analysis and beta convergence analysis provide strong evidence for the existence of spatial autocorrelation in regional income distribution and show that the spatial dimension should be taken into account in convergence analyses.
Computer Programs for Hierarchical Polythetic Classification ("Similarity Analyses")

It is demonstrated that hierarchical classifications have computational advantages over cluster analyses. Flexible programs are outlined providing two sorting strategies and four alternative similarity-coefficients. Preliminary results suggest that for qualitative data one of the strategies and two of the coefficients are superior to the remainder of the system; the further refinements desirable for a large-scale production program are discussed.
Attitudes towards plagiarism in academia

This contribution probes into the attitudes towards plagiarism in academia as it details the results of a questionnaire study within the larger framework of a joint Bulgarian-German research project on plagiarism in academia. The questionnaire focused on investigating the scope of the notion of plagiarism as Bulgarian academics understand it and second, looking into the availability of a system of support to prevent transgressors and/or sanctions for transgressing academics across Bulgarian universities. The results of the questionnaire suggest that while there appears to be a consensus among Bulgarian academics about the different facets that make up the notion of plagiarism, the reported attitudes towards plagiarism practices vary greatly, reflecting a non-uniform perception of what constitutes an offense. It also shows a deep dissatisfaction with existing anti-plagiarism regulatory systems in Bulgarian scientific institutions. Note: This study was financed by the Alexander von Humboldt Foundation, Germany, as part of a larger project entitled: “Text Plagiarism in the Social Sciences vis-à-vis Ethical Aspects and Common Practices” and realized within the framework of the Research Group Linkage Programme of the foundation in the period of 01.01. 2017 – 30.06. 2018. Ref. 3.4 – 1062413 – BGR – IP.
Factors Influencing Landowners’ Decisions for Income-Generating Activities on Private Coastal Wetland in Louisiana

The coastal zone of Louisiana contains more than 3 million wetland acres and has the highest acreage of salt marsh of any state. However, Louisiana accounts for 80 percent of the nation’s coastal land loss. The loss of Louisiana’s coastal wetlands results in changes in economic and ecological benefits on local communities. The purpose of the study is to investigate the factors that motivate private coastal landowners to participate in income-generating activities and the level of income derived from their coastal wetland parcels and to gauge their opinion of potential policy instruments for coastal wetlands stewardship. A double-hurdle model was applied to econometrically identify the determinants on the participation and level of participation in income-generating activities using data collected from a sample of coastal wetland owners. The results based on the estimated parameters and marginal effects revealed that decisions to participate and the level of participation are related to physical characteristics of the wetland and socioeconomic characteristics of the landowner. For example, the type of wetland is the primary factor influencing the decision to participate and the level of participation. In addition, understanding the landowner’s attitude toward wetland restoration program provides the opportunity for policymakers to better evaluate current and potential policies for coastal management in Louisiana.