Miracle-dz/UniFAR-FTUs huggingface dataset:
Concurrent Validation of OMNI Rate of Perceived Exertion Colour-Face Scale in Young Adults- NIEjr01

The OMNI Rate of Perceived Exertion Scales have been validated across different age groups, genders, ethnicities, but it can be revised for greater user inclusivity. Purpose : The aim of this study is to establish the concurrent validation of OMNI Rate of Perceived Exertion Colour-Face Scale on healthy male and female adults. Methodology : 20 subjects, 10 males and 10 females, participated in the investigation. The session involved a discontinuous submaximal graded exercise test. The submaximal treadmill test functions on a 4 minutes cycle at 1:1 work rest ratio. The treadmill started at 6km·h -1 and increased at of 0.5km·h -1 per work stage. During the work stage, oxygen uptake was obtained via the metabolic cart. Both heart rate and perceived exertion were recorded and at the last 15 seconds of each work stage. The test was terminated upon volitional exhaustion. Results : Significant positive linear regression was observed between heart rate (r = 0.78, p = 0.00) and oxygen uptake (r = 0.81, p = 0.00) with perceived exertion ratings OMNI Ratings of Perceived Exertion Colour-Face Scale. Conclusion: Concurrent validity is established for OMNI Rate of Perceived Exertion Colour-Face scale on healthy male and female adults.
Predicting the speed of ships on the Northern Sea Route using ice concentration isolines

The speed modes of movement for ships in continuous ice on the Northern Sea Route are poorly understood at present. The existing methods for predicting the speed of ships are based on its tactical and technical characteristics and aren’t suitable for the Arctic conditions because they give large errors, which leads to economic uncertainty for many shipowners. The most objective and operational information about the speed of movement of ships in ice are AIS data, space and radar images. The processing of these data was carried out using the methods of mathematical statistics and using geographic information systems. Large-capacity ships with high ice class Arc7 and their routes in the Kara Sea during the winter navigation period were selected as objects of research. The main research method is the construction of lines of equal values for the speeds of ships in different parts of ice fields and in clear water. For ice fields, according to radiometric monitoring data, ice concentration fields with a grid of 1 square kilometer were determined, land areas were automatically removed, the separation line of clean water and ice edges was also recorded every day. Zones with the highest ice concentration were identified, which were also indicated using level isolines. The combination of lines of equal parameters of speed and ice concentration made it possible to measure the magnitude of the change (decrease) in the speed in comparison with the passport for clear water. Since several real AIS tracks can be collected for the water area of the Kara Sea during the day, quite adequate and related information about the change in speed in the ice is obtained. This work is rather the creation of a methodology for choosing a strategy and numerical methods for predicting the speed of movement of groups of vessels in the ice of the NSR, if it becomes possible to obtain satellite images several times a day, it can be used in practice. The processed data showed good convergence for the same areas of ice fields. In the future, this technique can be used to find the most optimal routes along the Northern Sea Route.
Ofﬂine Reinforcement Learning with Munchausen Regularization

Most temporal differences based (TD-based) Reinforcement Learning (RL) meth-ods focus on replacing the true value of a transiting state by their current estimate of this value. Munchausen-RL (M-RL) proposes the idea of incorporating the current policy to be leveraged to bootstrap RL. It regularize policies that are: 1. Too far from the previous one. 2. Too far from uniform policy. The concept of 1. , penalizing two consecutive policies that are far from each other is also applicable to ofﬂine settings. In our work, we add the Munchausen term in the Q-update step to penalize policies that deviate from previous policy too far. Our results indicate that this method could be implemented in various ofﬂine Q-learning methods to help improve the performance. In addition, we evaluate another TD-based method, prioritized experience replay (PER), it prioritizes the mini-batch by its TD-error and weighted importance sampling. Our results show that Munchausen Ofﬂine RL outperforms the original methods that are without the regularization term. The results indicate that adding the extra regularization term indeed helps improve the performance of Q-learning methods even in ofﬂine settings.
The Effect Analysis of Predisposing, Enabling and Reinforcing Factors on Employees Infected with Covid-19 at RSU Dr. H. Koesnadi Bondowoso

:- The aims of study were to analyze effect of predisposing, enabling and reinforcing factors on employees who contracted COVID-19 at RSU dr. H. Koesnadi Bondowoso. This type of research used observational analytic with case control study design. The number of samples wete 216 respondents. Methods of data analysis used chi-square and logistic regression. The results showed that there were an effect between predisposing factors including comorbidities, education level, knowledge and attitudes towards employees who had contracted COVID-19. There was an efect between reinforcing factors including supervision by hospital leaders on employees who have contracted COVID-19. There is no effect between predisposing factors including age on employees who have contracted COVID-19. There is no effect between enabling factors including the availability of PPE, availability of hand washing/hygiene facilities, availability of health information for employees who have contracted COVID-19. There is no effect between reinforcing factors including the existence of regulations/laws on employees who have contracted COVID-19. There is an effect between predisposing factors (comorbid, education level, knowledge level, attitude) on employees who have contracted COVID-19. There is an effect between the reinforcing factor (supervision by the leadership) on employees who have contracted COVID-19. The most dominant variables influencing include attitude, supervision by hospital leadership, education level and comorbidities. There is no effect between reinforcing factors including the existence of regulations/laws on employees who have contracted COVID-19. There is an effect between predisposing factors (comorbid, education level, knowledge level, attitude) on employees who have contracted COVID-19. There is an effect between the reinforcing factor (supervision by the leadership) on employees who have contracted COVID-19. The most dominant variables influencing include attitude, supervision by hospital leadership, education level and comorbidities. There is no effect between reinforcing factors including the existence of regulations/laws on employees who have contracted COVID-19. There is an effect between predisposing factors (comorbid, education level, knowledge level, attitude) on employees who have contracted COVID-19. There is an effect between the reinforcing factor (supervision by the leadership) on employees who have contracted COVID-19. The most dominant variables hospital
Amplitude death in steadily forced chaotic systems

Steady forcing can induce the amplitude death in chaotic systems, which generally exists in coupled dynamic systems. Using the Lorenz system as a typical example, this paper investigates the dynamic behaviours of the chaotic system with steady forcing numerically, and finds that amplitude death can occur as the strength of the steady forcing goes beyond a critical constant.
A Learning-Based Dependency to Constituency Conversion Algorithm for the Turkish Language

This study aims to create the very first dependency-to-constituency conversion algorithm optimised for Turkish language. For this purpose, a state-of-the-art morphologic analyser and a feature-based machine learning model was used. In order to enhance the performance of the conversion algorithm, bootstrap aggregating meta-algorithm was integrated. While creating the conversation algorithm, typological properties of Turkish were carefully considered. A comprehensive and manually annotated UD-style dependency treebank was the input, and constituency trees were the output of the conversion algorithm. A team of linguists manually annotated a set of constituency trees. These manually annotated trees were used as the gold standard to assess the performance of the algorithm. The conversion process yielded more than 8000 constituency trees whose UD-style dependency trees are also available on GitHub. In addition to its contribution to Turkish treebank resources, this study also offers a viable and easy-to-implement conversion algorithm that can be used to generate new constituency treebanks and training data for NLP resources like constituency parsers.
Rosetta-LSF: an Aligned Corpus of French Sign Language and French for Text-to-Sign Translation

This article presents a new French Sign Language (LSF) corpus called “Rosetta-LSF”. It was created to support future studies on the automatic translation of written French into LSF, rendered through the animation of a virtual signer. An overview of the field highlights the importance of a quality representation of LSF. In order to obtain quality animations understandable by signers, it must surpass the simple “gloss transcription” of the LSF lexical units to use in the discourse. To achieve this, we designed a corpus composed of four types of aligned data, and evaluated its usability. These are: news headlines in French, translations of these headlines into LSF in the form of videos showing animations of a virtual signer, gloss annotations of the “traditional” type—although including additional information on the context in which each gestural unit is performed as well as their potential for adaptation to another context—and AZee representations of the videos, i.e. formal expressions capturing the necessary and sufficient linguistic information. This article describes this data, exhibiting an example from the corpus. It is available online for public research.
Tensor categorical foundations of algebraic geometry

Tannaka duality and its extensions by Lurie, Sch\"appi et al. reveal that many schemes as well as algebraic stacks may be identified with their tensor categories of quasi-coherent sheaves. In this thesis we study constructions of cocomplete tensor categories (resp. cocontinuous tensor functors) which usually correspond to constructions of schemes (resp. their morphisms) in the case of quasi-coherent sheaves. This means to globalize the usual local-global algebraic geometry. For this we first have to develop basic commutative algebra in an arbitrary cocomplete tensor category. We then discuss tensor categorical globalizations of affine morphisms, projective morphisms, immersions, classical projective embeddings (Segre, Pl\"ucker, Veronese), blow-ups, fiber products, classifying stacks and finally tangent bundles. It turns out that the universal properties of several moduli spaces or stacks translate to the corresponding tensor categories.
Eco Friendly Synthesis of Zinc Oxide Nanoparticles and Printing onto Electrically Conductive Substrate Using Electrostatic Spray Deposition

How to cite this article S Javadpour Eco Friendly Synthesis of Zinc Oxide Nanoparticles and Printing onto Electrically Conductive Substrate Using Electrostatic Spray Deposition. J The study presents the efficient synthesis of hexagonal wurtzite zinc oxide (ZnO) nanoparticles and a stable nano colloid by a one-pot thermolysis synthesis method. In this investigation, the average particle size for the synthesized ZnO was about 60 nm, condensed and adhesive zinc oxide thin films were productively sprayed onto fluorine doped tin oxide glass at room temperatures using a controllable electrostatic spray deposition method. This technique is useful method to deposit a facile, non-vacuum, and inexpensive layer. The synthesized nanoparticles were characterized by X-ray diffraction, dynamic light scattering, Fourier-transform infrared spectroscopy, and purity and surface morphology of thin film was confirmed by scanning electron microscope. Thermogravimetric analysis of the ZnO nanoparticles showed that weight loss continued until 450 ˚C. Results revealed optimized deposition conditions at the voltage of 26 kV, the flow rate of 3 μl/min, and nozzle to substrate distance of 8 cm. In the wavelength ranging between 300-900 nm, the optical absorbance and transmittance measurements were recorded and the UV–Visible spectrum of the ZnO thin film showed maximum absorbance at around 350 nm.
Challenging the Assumption of Structure-based embeddings in Few- and Zero-shot Knowledge Graph Completion

In this paper, we report experiments on Few- and Zero-shot Knowledge Graph completion, where the objective is to add missing relational links between entities into an existing Knowledge Graph with few or no previous examples of the relation in question. While previous work has used pre-trained embeddings based on the structure of the graph as input for a neural network, nobody has, to the best of our knowledge, addressed the task by only using textual descriptive data associated with the entities and relations, much since current standard benchmark data sets lack such information. We therefore enrich the benchmark data sets for these tasks by collecting textual description data to provide a new resource for future research to bridge the gap between structural and textual Knowledge Graph completion. Our results show that we can improve the results for Knowledge Graph completion for both Few- and Zero-shot scenarios with up to a two-fold increase of all metrics in the Zero-shot setting. From a more general perspective, our experiments demonstrate the value of using textual resources to enrich more formal representations of human knowledge and in the utility of transfer learning from textual data and text collections to enrich and maintain knowledge resources.
A singular perturbation approach to stabilization of the internal dynamics of multilink flexible robots

One of the main difficulties in controls design for multilink flexible arms is the instability of its internal dynamics. This paper presents a singular perturbation method to stabilize the internal dynamics and to achieve desired tracking performance. It is shown that by first applying partial feedback linearization and then inducing time-scale separation, a better time-scale separation can be obtained. The slow part of the control ensures tracking of the desired rigid trajectory and the fast part is then designed for stabilizing the internal dynamics. It is shown that the off-manifold error, the tracking error and its first and second-order derivatives are uniformly bounded by exponentially decaying terms plus a small constant term. It is also proved that the first-order derivative of the off-manifold error is uniformly bounded. One of the special features of the authors' approach is that the bounds for the tracking error, the off-manifold error, the initial off-manifold value, and the bound for stiffness which guarantees the convergence can be explicitly computed. The simulations show excellent path tracking and vibration rejection properties.
Track Association with Bayesian Probability Theory

Abstract : Data association and track association algorithms have been developed over the course of thirty years. Almost all technical papers that describe these association algorithms have begun the derivations by adopting log-likelihood ratios as the measure of association. At best, this starting point has obscured the assumptions necessary to use log-likelihood ratios. At worst, the log-likelihood ratios have been improperly defmed. This report provides the first known derivation of a track association algorithm from the first principles of Bayesian probability theory. By starting with first principles, all the assumptions that are necessary to derive an association algorithm are explicitly stated as the derivation proceeds. The correct form for the log-likelihood ratios is obtained later in the derivation and can be traced back to first principles. The pitfalls and deficiencies of poorly performing association algorithms are identified easily by comparing the algorithms with the full derivation. These deficiencies arise from such mistakes as the incorrect definition of the log-likelihood ratio, poor selection of the probability density functions, incorrect construction of the cost matrices, and the application of an algorithm to a system that violates the assumptions that were adopted during the algorithm construction. In addition, the firm grounding in Bayesian probability theory provides the means to easily extend the derivation to produce more complex association algorithms, such as feature-aided track association algorithms. The basic derivation provided in this report makes it clear that the ensemble of track association algorithms is much more extensive that most data fusion researchers would believe. These algorithms can be created by simply changing any of the derivation assumptions or the probability density functions.
Local a Priori Estimate on the General Scale Subdomains

The local a priori estimate for the finite element approximation is essential for underlying the local and parallel technique. It is well known that the constant coefficients in the inequality is independent of themesh size. But it is not so clear whether the constant depends on the scale of the local subdomains. The aim of this note is to derive a new local a priori estimate on the general scale domains. We also show that the dependence of the constant appearing in the local a priori estimate on the scale of the subdomains.
Self-regularity - a new paradigm for primal-dual interior-point algorithms

An apparatus and method for continuously detecting oxygen in a carrier gas stream. The apparatus employs a sensor film comprising a fluorescent material emitting from 3000 - 8000 A, dissolved in a carrier or solvent, the film being supported on a suitable substrate. Exciting radiation of about 2000 - 6500 A is applied to the film causing the fluorescent material to emit.
Land Mammals and the Great American Interchange

Xhe continents of South America, Africa, Antarctica, Australia, and India were once joined in a large land mass in the southern hemisphere called Gondwana. About 100 million years ago (mya) South America began to separate from Africa, moving in a primarily westward direction. There is no convincing geological evidence to indicate that South America had a continuous land connection with any other continent _ until about 3 mya, when the Bolivar Trough marine barrier disappeared and the Americas were united by the emergence of the Panamanian land bridge. The long-isolated continental biotas of North and South America were brought into contact, resulting in an intermingling that has come to be known as the Great American Interchange (Webb 1976; Fig. 1). The site of the former Bolivar Trough is thus the gateway for this event, de noting the historical boundary be tween two biotic provinces (Fig. 2). Although many different groups of plants and animals took part in the interchange, I will focus on land mammals, which are the most thoroughly studied of the participants. The Great American Interchange was first recog nized by Wallace (1876), but it has taken another hun dred years of intense paleontological study by Amegh ino, Matthew, Scott, Patterson, Simpson, Webb, and others to clarify patterns of dispersal (see, for example, Marshall 1981, 1985; Webb 1985; Webb and Marshall The emergence of the Panamanian land bridge three million years ago permitted the mingling of the long-separated faunas of North and South America 1982). It is only during the last decade, moreover, that greater precision in dating the sediments containing interchange taxa has provided a firm time frame for various aspects of the event. It is now possible to assess the interchange in detail, and to analyze the tempo and mode of dispersal and the rates of extinction and origina tion in successive faunas through time. As a result, the _ Great American Interchange repre sents the best-documented example in the fossil record of the intermin
Title: Continued Increases of Gross Primary Production in Urban Areas During 2000 –

Urbanization affects vegetation within city administrative boundary and nearby rural areas. Gross primary production (GPP) of vegetation in global urban areas is one of 21 important metrics for assessing the impacts of urbanization on terrestrial ecosystems. To 22 date, very limited data and information on the spatial-temporal dynamics of GPP in the 23 global urban areas are available. In this study, we reported the spatial distribution and 24 temporal dynamics of annual GPP during 2000 – 2016 from 8,182 gridcells (0.5 ° by 0.5 ° 25 latitude and longitude) that have various proportion of urban areas. Approximately 26 79.3% of these urban gridcells had increasing trends of annual GPP during 2000-2016. As 27 urban area proportion (%) within individual urban gridcells increased, the means of 28 annual GPP trends also increased. Our results suggested that for those urban gridcells, 29 the negative effect of urban expansion (often measured by impervious surfaces) on GPP 30 was to large degree compensated by increased vegetation within the gridcells, mostly 31 driven by urban management and local climate and environment. Our findings on the 32 continued increases of annual GPP in most of urban gridcells shed new insight on the importance of urban areas on terrestrial carbon cycle and the potential of urban management and local climate and environment on improving vegetation in urban areas.
EFFECT OF SIGNIFICANT CLIMATIC FACTORS ON AGRICULTURAL PRODUCTION AND INCOMES

Abstract Recent studies relating to the human use of the atmosphere have emphasized the need for investigations into the economics of weather and climate. They reveal that little attention has been given by meteorologists to the non-scientific gains of their profession. Of the many gains, those affecting the agricultural community are of primary importance. The technique of assessing the gains associated with monetary variations in agricultural production is examined through the use of an “agroclimatological model” for several agricultural products in New Zealand. The most significant partial correlations were examined, the subsequent analysis indicating the importance of climatic variations on various aspects of agricultural production, and their effects on agricultural incomes. The major finding of the analysis is the significance of climatic factors in their influence on butterfat production, a “significant” climatic variation such as a “wet” January, for example, being “worth” about $N.Z. 2 million to.