Miracle-dz/UniFAR-FTUs huggingface dataset:
The nexus prevalent in nonlinear finance and growth in the presence of macroeconomic instability in Turkey: Does the stock market really matter?

The link between stock market and economic development has become a significant volatile issue over the past few years. Our major contribution in the debate concerning the nexus between finance and growth is to bring to the fore the asymmetric effects of stock market development on economic growth under macroeconomic instability. Hence, towards this purpose, the stock market development index and the macroeconomic instability index, which are both constructed by incorporating the exchange rate and unemployment rate, are built based on principal component analysis. Utilizing the nonlinear autoregressive distributed lag model (NARDL) within the framework of a time series approach, we provide evidence that there is an asymmetric relationship between economic growth and the development of the stock market in Turkey.
Optimal control of multiscale systems using reduced-order models

We study optimal control of diffusions with slow and fast variables and address a question raised by practitioners: is it possible to first eliminate the fast variables before solving the optimal control problem and then use the optimal control computed from the reduced-order model to control the original, high-dimensional system? The strategy ``first reduce, then optimize''---rather than ``first optimize, then reduce''---is motivated by the fact that solving optimal control problems for high-dimensional multiscale systems is numerically challenging and often computationally prohibitive. We state sufficient and necessary conditions, under which the ``first reduce, then control'' strategy can be employed and discuss when it should be avoided. We further give numerical examples that illustrate the ``first reduce, then optmize'' approach and discuss possible pitfalls.
Changes in Some Soil Physico-Chemical Properties of Lithosols under Different Levels of Nitrogen and Cowdung Fertilizers in Mubi Area, North-Eastern of Nigeria,

The research work was conducted to evaluate the changes in some lithosols soil physico-chemical properties under different levels of nitrogen and cowdung fertilizers in Mubi area, North-eastern of Nigeria. The Treatments comprised of five rates of N (0, 30, 60, 90 and 120 kg ha- 1 ) and two levels of cowdung (0 and 5 ton ha- 1 ). These treatments were combined and arranged in an experiment laid out in Complete Randomized Design and replicated three times. Data were collected on some soil chemical properties and were subjected to analysis of variance. Correlation analysis was also carried out to assess relationship between measured parameters. The results showed that Differences in soil Available Phosphorus and Exchangeable Potassium concentration decreased in all the treatments except at 60 kg N ha- 1 by 30.23% for Exch. K while percent O.C, O.M, Ec and pH generally increased except for pH which slightly decreased at 60 kg N ha- 1 than at 120 kg N ha- 1 + 5 kg cowdung ha- 1 respectively. Significant positive correlation exists between leaf area and plant height with correlation value of r = 0.723 at (P 5%) and between pH with O.M content r = 0.442 at (P > 5%), while significantly negative correlation occurred between P content with leaf area r = -0.374 at (P > 5 %), and O.M with O.C content r = -0.612 at (P < 0.1%). It is therefore assessed that combined application of organic and inorganic fertilizers produced more effect on maize growth and retained nutrient availability in the soil than sole application of each nutrient sources or none. Thus, 120 kg N ha -1 + 5 kg cowdung ha -1 should be adopted for maintaining soil physic-chemical properties and optimum growth of maize in the area.
Exploring the Reliability and Validity of the Huntington’s Disease Quality of Life Battery for Carers (HDQoL-C) within A Polish Population

Huntington’s disease (HD) is a rare genetic neurodegenerative disorder that causes motor disorders, neuropsychiatric symptoms and a progressing deterioration of cognitive functions. Complex issues resulting from the hereditary nature of HD, the complexity of symptoms and the concealed onset of the disease have a great impact on the quality of life of family carers. The caregivers are called the “forgotten people” in HD, especially with relation to genetic counseling. This study aims to explore the reliability and validity of the Huntington’s Disease Quality of Life Battery for carers (HDQoL-C) within a Polish population. A total of 90 carers recruited from the Enroll-HD study in Polish research centers of the European Huntington’s Disease Network completed a polish translation of the HDQoL-C. Data were subjected to Principle Components Analysis (PCA) and reliability measures. The Polish version of the shortened versions of the HDQoL-C is similarly valid compared to the original English version and suitable for use within this population. The HDQoL-C has previously demonstrated a wide range of benefits for practitioners in capturing and understanding carer experience and these benefits can now be extended to Polish speaking populations.
Place Attachment, Image, and Support for Marijuana Tourism in Colorado

Colorado became the first state in the United States that passed the legalization of recreational (retail) marijuana with Amendment 64 in 2012. With this unprecedented tourism environment, it is imperative to understand different perspectives of stakeholders involved. In particular, residents’ view is important in that their attitude and behaviors plan and manage the design of marketing activities and sustainable development of the tourist place. Therefore, the purpose of the study is to examine the local residents’ image, attachment, and support of marijuana tourism as a result of the legalization of recreational marijuana in Colorado. Results of the study concluded that the highly attached residents held a positive image of their place, which in turn influence their support of marijuana tourism. Implications for industry professionals and state policy makers are presented.
Exponential convergence of a learning controller for robot manipulators

The proof for the exponential convergence of a class of learning and repetitive control algorithms for robot manipulators is given. The learning process involves the identification of the robot inverse dynamics function by having the robot execute a set of tasks repeatedly. Using the concepts of functional persistence of excitation and functional uniform complete observability, it is shown that, when a training task is selected for the robot which is persistently exciting, the learning controllers are globally exponentially stable. Repetitive controllers are always exponentially stable. >
A large hyaenodont from the Lutetian of Switzerland expands the body mass range of the European mammalian predators during the Eocene

We here present a new hyaenodont genus and species from the Lutetian locality of Egerkingen γ (Switzerland; MP13? ): Cartierodon egerkingensis gen. et sp. nov. The new taxon is represented by numerous dental elements, mostly isolated teeth. The molars show typical features of a hypercarnivorous predator such as the strong reduction of the crushing (talonid/protocone) and puncturing (metaconid) structures. The calculation of several dental indices indicates that this hyaenodont may have been a bone-cracking predator. The new taxon differs from all the hyaenodonts previously known in Europe during the Ypresian and Lutetian by its larger size, with an estimated mass of almost 29 kg (the size of the extant African wild dog, Lycaon pictus ). Other hyaenodonts known for this period do not exceed 20 kg. Previous authors proposed the hypothesis of an ecological limitation of the body mass, but the description of Cartierodon egerkingensis indicates instead that the European hyaenodonts continuously increased in size throughout the Eocene. We also performed a phylogenetic analysis in order to test the relationships of this new taxon: the new hyaenodont appears to be closely related to the Lutetian hyaenodont Prodissopsalis eocaenicus .
The impact of climatic factors on the relative chlorophyll content and yield of a maize hybrid in a long-term experiment

The impact of the climatic factors of crop year on the relative chlorophyll content of maize was examined for three years. The examinations were carried out on the Látókép Experiment Site of the University of Debrecen on calcareous chernozem soil in a small-plot, non-irrigated long-term field experiment with strip plot design. In addition to a non-fertilised (control) treatment, nitrogen (N) fertiliser doses were applied as base and top dressing. The 60 and 120 kg N ha-1 base dressing doses were followed by two top dressing doses at the V6 and V12 phenophases. Averaged over the different fertiliser treatments, SPAD readings increased in all three years as the growing season progressed. The highes SPAD value increase was observed in the average crop year (2017) at the V12 phenophase (11.8), which further increased at the R1 phenophas, by 3,7. No significant Spad value difference was observed between the average (2017) and the dry year (2018) at the V6 growth phase. However, in the wet crop year (2016), the V690 treatment provided the statistically highest relative chlorophyll content (46.8). At the V12 phenophase, the base dressing dose of 120 kg N ha-1+30 kg N ha-1 (V6150) showed to be successful in two years (2016 and 2018), while in 2017, the base dressing dose of A60 was successful. The impact of crop year on relative chlorophyll content can be clearly shown at the R1 growth stage. In all three years, the significantly highest relative chlorophyll content could be achieved at different nutrient levels: A60 in 2016, V6150 in 2017 and V690. In a wet year (2016), higher yield could be achieved as a result of the 60 kg N ha-1 base dressing and 30 kg N ha-1 at the V6 growth stage (V690) as top dressing in comparison with 2017 and 2018, when higher fertiliser dose (120 kg N ha-1 base dressing and 30 kg N ha-1top dressing at the V6 growth stage) was needed to achieve a significant yield surplus. Altogether, averaged over the different treatments, the highest yield (12.48 t ha-1) was observed in the wet year, when the relative chlorophyll content was also the highest (50.6).
An interprofessional approach to pressure ulcer prevention: a knowledge and attitudes evaluation

Background: Pressure ulcers (PUs) are a major burden to individuals, impacting their physical, mental and social wellbeing. While PU prevention is traditionally regarded as a nursing issue, an interprofessional approach has been promoted as best practice. However, little is known about current practice or the knowledge and attitudes of the wider interprofessional team (IPT). Purpose: Pre-designed questionnaires were used to explore knowledge and attitudes with healthcare staff in the community. Methods: Questionnaires were disseminated to all healthcare staff within a community healthcare Trust predominantly via an online tool. Data were analyzed using descriptive and inferential statistics. Results: The median values of all professional groups demonstrated satisfactory attitudes (>75%) and levels of knowledge (>60%) to PU prevention. However, there were differences within and between groups. Management staff demonstrated the most positive attitude to PU prevention (89%), followed by occupational therapists (OTs) and healthcare assistants (HCAs) (87%, IQR: 75%→89%). OTs demonstrated the highest scores for knowledge (69%, IQR: 62%→73%), while healthcare and rehabilitation assistants scored the lowest (58%, IQR: 58%-64%). Conclusion: This study has demonstrated that the majority of healthcare staff in a UK community setting have satisfactory levels of knowledge and attitudes in relation to PU prevention overall. Nevertheless, there were some differences between groups, albeit non-significant. There were also differences between sub-themes of the questionnaires, indicating a greater focus of pressure ulcer treatment over prevention. While PU prevention is widely regarded to be a nursing issue, these findings provide some indication of the potential for an interprofessional approach.
Assessment of knee pain from MRI scans using a convolutional Siamese network

ABSTRACT Objectives It remains difficult to characterize pain in knee joints with risk of osteoarthritis solely by radiographic findings. We sought to understand if advanced machine learning methods such as deep neural networks can be used to predict and identify the structural features that are associated with knee pain. Methods We constructed a convolutional Siamese network to associate MRI scans obtained on subjects from the Osteoarthritis Initiative (OAI) with frequent unilateral knee pain (n=1,529) comparing their knee with frequent pain to the contralateral knee without pain. The Siamese network architecture enabled pairwise learning of information from two-dimensional (2D) sagittal intermediate-weighted turbo spin echo slices obtained from similar locations on both knees. Class activation mapping (CAM) was utilized to create saliency maps, which highlighted the regions that were most associated with knee pain. The MRI scans and the CAMs of each subject were reviewed by a radiologist to identify the presence of abnormalities within the model-predicted regions of high association. Results Using 10-fold cross validation, our model achieved an area under curve (AUC) value of 0.808. When individuals whose knee WOMAC pain scores were not discordant were excluded, model performance increased to 0.853. The radiologist review revealed that about 86% of the cases that were predicted correctly had effusion-synovitis within the regions that were most associated with pain. Conclusions This study demonstrates a proof of principle that deep learning can be applied to assess knee pain from MRI scans.
Intermittent Motivational Interviewing and Transdiagnostic CBT for Anxiety: A Case Study

Recent meta-analytic findings have revealed that the addition of motivational interviewing (MI) to cognitive behavior therapy (CBT) for anxiety disorders improves treatment outcome. However, for the most part, previous research has limited MI as a prelude to CBT. This article explored the benefits and complications of a more integrated approach by adapting and examining an already established transdiagnostic CBT protocol to include intermittent MI strategies. The presented protocol is described and illustrated using a case study of a woman meeting criteria for four anxiety disorder diagnoses. This study presents session-by-session treatment accounts, as well as pre, post, and follow-up data. Results indicated clinically significant improvement, supporting the utility of intermittent MI strategies within CBT. Implementation recommendations and future research directions are discussed.
Multi-informant Assessment of Therapeutic Competence: Development and Initial Validation of a Set of Measurements

Assessment of therapeutic competence is required to be multi-informant and should therefore include the perspectives of therapists, clients and observers. There are several instruments assessing therapeutic competence from one of the requested perspectives. But heretofore there is no valid and reliable set of measurements that allows the assessment of therapeutic competence from the different perspectives based on the same theoretical basis, what is central for making comparisons possible. We developed a set of measurements assessing therapeutic competences from different perspectives: therapists’ global (GloRa-T) and session self-rating (SeRa-T), clients’ session rating (SeRa-C) and observer rating (CoRa-O). The psychometric properties of the measurements were investigated. The analysis suggested satisfactory psychometric properties of the presented measurements, some limitations are discussed. All measurements are promising instruments for multi-informant assessment of therapeutic competence. They assess the same components of therapeutic competence, so comparisons among the perspectives are possible.
RATING BASED LÉVY LIBOR MODEL

In this paper we consider modeling of credit risk within the Libor market models. We extend the classical definition of the defaultfree forward Libor rate to defaultable bonds with credit ratings and develop the rating based Libor market model. As driving processes for the dynamics of the default-free and the pre-default term structure of Libor rates time-inhomogeneous Lévy processes are used. Credit migration is modeled by a conditional Markov chain, whose properties are preserved under different forward Libor measures. Conditions for absence of arbitrage in the model are derived and valuation formulae for some common credit derivatives in this setup are presented.
DEVELOPMENT OF OPENFOAM SOLVERS FOR INCOMPRESSIBLE NAVIER–STOKES EQUATIONS BASED ON HIGH-ORDER RUNGE–KUTTA SCHEMES

Nowadays open-source CFD codes provide suitable environments for implementation and testing low-dissipative algorithms typically used for turbulence simulation. Moreover these codes produce a reliable tool to test high-fidelity numerics on unstructured grids, which are particularly appealing for industrial applications. Therefore in this work we have developed several solvers for incompressible Navier–Stokes equations (NSE) based on high-order explicit and implicit Runge–Kutta (RK) schemes for time-integration. Note that for NSE space discretization the numerical technology available within OpenFOAM (Open-source Field Operation And Manipulation) library was used. Specifically in this work we have considered explicit RK projected type schemes for index 2 DAE system and L-stable Singly Diagonally Implicit Runge–Kutta (SDIRK) techniques. In the latter case an iterated PISO-like procedure based on Rhie–Chow correction was used for handling pressure-velocity coupling within each RK stage. The accuracy of the considered algorithms was evaluated studying the Taylor–Green vortex. Moreover several benchmark solutions have been computed in order to assess the reliability, the accuracy and the robustness of the presented solvers.
International knowledge spillovers and productivity: A study of the manufacturing industry in Mexico

The aim of this paper is to examine the degree of impact of technological externalities, associated with international trade and foreign direct investment (FDI), on productivity, and the role of technological capabilities in the process of dissemination of knowledge. Tested empirically the contribution of the international flow of knowledge on Total Factor Productivity (TPF) of manufacturing in Mexico for the period 1999-2012, using a panel autoregressive distributive lag (ARDL) model. The main findings are: i) the presence of gains in productivity via international trade, however the magnitude of these coefficients is small; ii) technological externalities are more relevant in sectors with high technological capacity; iii) the FDI has a marginal and inconclusive on the performance of productivity contribution.
Technology for Enhancing the Learning and Teaching Experience in Higher Education

— The rapid development and growth of technology has changed the method of obtaining information for educators and learners. Technology has created a new world of collaboration and communication among people. Incorporating new technology into the teaching process can enhance learning outcomes. Billions of individuals across the world are now connected together, and are cooperating and contributing their knowledge and intelligence. Time is no longer wasted in waiting until the teacher is ready to share information as learners can go online and get it immediatelt. The objectives of this paper are to understand the reasons why changes in teaching and learning methods are necessary, to find ways of improving them, and to investigate the challenges that present themselves in the adoption of new ICT tools in higher education institutes. To achieve these objectives two primary research methods were used: questionnaires, which were distributed among students at higher educational institutes and multiple interviews with faculty members (teachers) from different colleges and universities, which were conducted to find out why teaching and learning methodology should change. The findings show that both learners and educators agree that educational technology plays a significant role in enhancing instructors’ teaching style and students’ overall learning experience; however, time constraints, privacy issues, and not being provided with enough up-to-date technology do create some challenges.
How Short Is Long Enough? Modeling Temporal Aspects of Human Mobility Behavior Using Mobile Phone Data

Time–location data collected from location-sensing technologies have the potential to advance our understanding of human mobility. Existing human activity studies tend to ignore a critical issue in data collection—the time period for which the activity data will be collected. Our study investigated this significant gap in the literature on temporal aspects of human mobility behavior—how many days constitute a period long enough to capture individuals’ highly organized activity episodes and how they vary among individuals with heterogeneous demographic and social-economic characteristics. To determine a minimum number of days to capture individuals’ highly organized activity episodes in activity space, we examined a distribution of Kullback–Leibler divergence indexes. To evaluate the differences in the minimal number of observation days per subgroup whose demographic and economic characteristics are heterogenous, we used a Bayesian profile regression model. Our study showed that the estimated minimum number of days required to capture routine activity patterns was 13.5 days with a standard deviation of 6.64. We found that participant’s age, employment status, size of household, and accessibility to downtown, food, and physical activity, as well as economic status of residential environment, are important factors that affect temporal aspects of mobility behavior. Key Words: Bayesian profile regression, human mobility, Kullback–Leibler divergence, mobile phone data, temporal regularity.
Weed Seed Population Dynamics During Six Years of Weed Management Systems in Crop Rotations on Irrigated Soil

The influence of two weed management systems was determined on weed seed and seedling populations and on yields of cantaloupe (Cucumis melo L. var. reticulatus Naudin ‘Perlita′), bell pepper (Capsicum annuum L. var. grossum ‘Grande Rio 66′), cotton (Gossypium hirsutum L. ‘CP 3374′), onion (Allium cepa L. ‘1015Y′), and cabbage (Brassica oleracea, var. capitata L. 'Sanibel′) sequentially grown in two 3-yr cycles. Palmer amaranth (Amaranthus palmeri S. Wats. # AMAPA) did not exist initially, but hurricane-introduced seed populations increased to 1.1 billion/ha as seed populations of common purslane (Portulaca oleracea L. # POROL) decreased from 786 million/ha to 124 million/ha in the 6-yr period, without weeding or herbicide. Use of herbicides and handweeding reduced Palmer amaranth seed populations 98%, but 18 million/ha still remained after 6 yr. The use of herbicides and Palmer amaranth interference decreased the seed populations of common purslane by 84%, but handweeding was inefficient. Yields of all but the first crop of cantalouple were almost totally eliminated by season-long interference of Palmer amaranth. Savings with the utilization of herbicides rather than handweeding ranged from $62/ha for cotton to $4703/ha for bell pepper.