We develop a quantitative microscopic theory of decaying Turbulence by studying the dimensional reduction of the Navier-Stokes loop equation for the velocity circulation. We have found an infinite dimensional manifold of solutions of the Navier-Stokes loop equation\cite{M93, M23PR} for the Wilson loop in decaying Turbulence in arbitrary dimension $d >2$. This family of solutions corresponds to a fractal curve in complex space $\mathbb C^d$, described by an algebraic equation between consecutive positions plus a nonlinear periodicity condition. We derive the constrained SDE for the evolution of the fractal curve at a fixed moment of physical time as a function of an auxiliary stochastic time. We expect this stochastic process to cover our fixed manifold of the solutions of the decaying Turbulence. The energy density of the fluid decays as $\mathcal E_0/t$, where $\mathcal E_0$ is an initial dissipation rate. Presumably, we have found a new phase of extreme Turbulence yet to be observed in real or numerical experiments.

The presence of dark matter, though well established by indirect evidence is yet to be observed directly. Various dark matter detection experiments running for several years have yielded no positive results so far. In view of these negative results, we had earlier proposed alternate models by postulating a minimum gravitational field strength (minimum curvature) and also a minimum acceleration. These postulates led to the modified Newtonian dynamics and modified Newtonian gravity (MONG). The observed flat rotation curves of galaxies had also been accounted for through these postulates. Here we extend these postulates to galaxy clusters and model the dynamical velocity-distance curves for such large-scale structures. The velocity-distance curve of the Virgo cluster, plotted with this model is found to be in accordance with that observed.

The new observations, including the fastest star, the circular velocity curve of the Milky Way and the fast galaxy bar, should imply that the mass of the center of the Milky Way is almost 10¹¹ times the mass of the Sun.

At the beginning of 2020, with the onset of the pandemic, the traditional learning environment for learners drastically changed globally. Since then, most students/teachers have started and practiced distance and virtual learning/teaching. Thus, a technological breakthrough in virtual learning has followed. In connection with this, many countries worldwide have commenced allocating additional financing and funds for educational institutions' technological improvement and development. The long-term stay in distance learning has revealed and highlighted new problems students face: their knowledge level has decreased, they lack socialization skills, and they face psychological and physical health problems. Due to this negative impact on students, a need to research and evaluate how much the EU countries allocated to solve the distance learning-caused problems and what programs or models they prepared has emerged and encouraged further studies. The research has found that many countries increased their allocations very minimally, e.g., 0.0.1%, but some increased their available budgets to 32%. Notably, most countries did not separate distance learning exit funding from distance learning preparation funding. Based on the problems the countries saw, only a few states identified withdrawal from distance learning as a problem. Considering this, we set ourselves the goal to evaluate exit models from distance learning and allocated funding amounts. The following objectives were planned to achieve the goal: · to evaluate the global practice of exit from distance learning; · to determine the scope of funding for pandemic management; · to evaluate the amounts of funding allocated to manage pandemic-caused consequences and the GDP ratio. Research methods: mathematical-statistical analysis, empirical analysis, and analysis of scientific literature.

Bonchev and Trinajstic defined two distance based entropy measures to measure the molecular branching of molecular graphs in 1977 [Information theory, distance matrix, and molecular branching, J. Chem. Phys., 38 (1977), 4517–4533]. In this paper we use these entropy measures which are based on distance matrices of graphs. The first one is based on distribution of distances in distance matrix and the second one is based on distribution of distances in upper triangular submatrix. We obtain the two entropy measures of paths, stars, complete graphs, cycles and complete bipartite graphs. Finally we obtain the minimal trees with respect to these entropy measures with fixed diameter.

We propose two methods for obtaining estimations on the minimum distance and covering radius of orthogonal arrays. Both methods are based on knowledge about the (feasible) sets of distance distributions of orthogonal arrays with given length, cardinality, factors and strength. New bounds are presented either in analytic form and as products of an ongoing project for computation and investigation of the possible distance distributions of orthogonal arrays with parameters in doable ranges.

We investigate how formal institutional distance (FID) moderates the relationship between cul-tural distance (CD) and the financial performance of foreign subsidiaries firms. Following recent research, we estimate the asymmetric effects of CD by considering its size and direction towards host countries on the opposite poles of each cultural dimension` scale. We propose that a limited understanding of the formal institutions in the host country, as measured by the magnitude and direction of the FID, can have a positive moderating effect, increasing the impact of CD on finan-cial performance. This is mainly because foreign subsidiary firms may be more reliant on their ca-pacity to navigate the less formal (and more implicit) aspects of the host country's institutional environment, such as their ability to cope with the CD. We use foreign subsidiary data from the Orbis database including 22 developed and 22 developing home countries and over 1400 foreign subsidiaries during a period of 3 consecutive years operating in 10 of the largest economies (host countries) in Latin America including: Argentina, Brazil, Colombia, Chile, Ecuador, Mexico, Panama, Peru, Uruguay, and Venezuela. Findings confirm the asymmetric effects of CD, howev-er, by considering the direction of FID, our findings reveal that the higher the FID towards less developed host countries, the more significant the effects of CD on the financial performance. These findings contribute to the knowledge of how formal and informal institutional distances in-teract by showing that the greater the FID towards less developed host countries, to higher the impact of CD on the financial performance of foreign subsidiary firms.

We show how it is possible to define and study black holes of arbitrary shapes in the framework of Newtonian mechanics.

Student retention is one indicator of accountability in the implementation of educational programs. Achievement of student retention rates indicates the performance of the quality objectives of an institution or college. To get an accurate picture of the factors related to retention, we need to do modeling. The retention variable is the time response variable measured in semester units. One of the statistical analyzes that can be used to analyze response data in time is survival analysis. The selection of an accurate analytical method in modeling will produce valid conclusions and impact making policies that are right and on target. This paper presents alternative modeling of student retention in distance education using survival analysis. The method used is a literature review. This paper also briefly describes distance education, open and distance education, distance education students' characteristics, distance education student retention, and survival models for modeling student retention in distance education.

In this paper, we introduce deboost, a Python library devoted to weighted distance ensembling of predictions for regression and classification tasks. Its backbone resides on the scikit-learn library for default models and data preprocessing functions. It offers flexible choices of models for the ensemble as long as they contain the predict method, like the models available from scikit-learn. deboost is released under the MIT open-source license and can be downloaded from the Python Package Index (PyPI) at https://pypi.org/project/deboost. The source scripts are also available on a GitHub repository at https://github.com/weihao94/DEBoost.

The node position information is critical in the wireless sensor network (WSN). However, the existing positioning algorithms commonly have low positioning accuracy because of noise interferences in communication. To solve this problem, this paper presents an iterative positioning model based on distance correction to improve the positioning accuracy of the target node in WSN. First, the log-distance distribution model of received signal strength indication (RSSI) ranging is built and the noise impact factor is derived based on the model. Second, the initial position coordinates of the target node are obtained based on the triangle centroid localization algorithm, thereby calculating the distance deviation coefficient under the influence of noise. Then, the ratio of the distance measured by the log-normal distribution model to the median distance deviation coefficient is taken as the new distance between the anchor node and the target node. Based on the new distance, the triangular centroid positioning algorithm is used again to calculate the target node coordinates. Finally, the iterative positioning model is constructed, and the distance deviation coefficient is updated repeatedly to update the positioning result until the set number of iterations is reached. Experiment results show that the proposed iterative positioning model can improve positioning accuracy effectively.

Different values of the Hubble constant for extragalactic objects are not considered here. We give a number of examples of the extreme accordance of expansion rates of different fields of knowledge with the cosmological expansion rate. The coincidence of the expansion rates means that a common cause is almost inevitable. All these examples are gravitationally bound in themselves and in this case are subject to cosmological expansion. According to standard theory, this should not happen. We therefore question the common boundary of gravity and expansion for both theoretical and observational reasons and conclude that all gravitationally dominated objects participate in cosmological expansion or scale drift, contrary to general doctrine. The space expands with its contents while numerically maintaining distance, radius, rotation time and density. What is generally interpreted as an expansion is obviously a scale drift with a drift rate that corresponds to the size of the Hubble constant. The Earth is subject to expansion and scale drift. This results in numerically constant measured values. This drift apparently also applies to distant galaxies and other objects. The cosmological red shift is not interpreted here as a Doppler effect and numerical increase in distances, but in accordance with standard theory as an expansion or drift of the space-time scale. The expansion of the radii of galaxies makes the assumption of dark matter superfluous. The continents and our everyday environment are not subject to expansion or scale drift.

This paper proposed an explicit and simple representation of velocity fluctuation and the Reynolds stress tensor in terms of the mean velocity field. The proposed turbulence equations are closed. The proposed formulations reveal that the mean vorticity is the key source of producing turbulence. It is found that there are no velocity fluctuation and turbulence if there were no vorticity. As a natural consequence, the laminar- turbulence transition condition was obtained in a rational way.

Based on author's previous work [Sun, B. The Reynolds Navier-Stokes Turbulence Equations of Incompressible Flow Are Closed Rather Than Unclosed. Preprints 2018, 2018060461 (doi: 10.20944/preprints201806.0461.v1)], this paper proposed an explicit representation of velocity fluctuation and formulated the Reynolds stress tensor in terms of the mean velocity field. The proposed closed Reynolds Navier-Stokes turbulence formulations reveal that the mean vorticity is the key source of producing turbulence.

This study aims to identify benefits and barriers to distance education, particularly from the perspective of teachers in Saudi Arabia. As the applied data collection tool, a questionnaire was distributed to the general education teachers in three districts. The sample size of the study was 1076 teachers. The results revealed that despite several benefits gained from distance learning, there are also some barriers. Teachers found that the most important advantage in distance learning is the acquisition of technical skills during the online teaching processes, they learn more and use digital education platforms, they have sufficient time to prepare the scientific content, they were able to provide adequate technical solutions for their courses, and they have the opportunity to use multiple media to deliver their courses. With the introduction of distance learning, teachers have explored new ways to deliver course contents to students. It has fostered better ways to provide more interactive real-time and on-demand teaching and learning using modern technology, thus, helping teachers become familiar with the use of electronic resources. It seems that teachers invest in technical methods to enhance students’ performance. Also, teachers reported some obstacles that they face during remote teaching. Most of these problems are connection problems applied with devices and the internet, lack of students’ motivation to learn in distance, problems associated with urban learners.

Fault line detection timely and accurately when single-phase-to-earth fault occurs in resonant grounding system is still a focus of research. This paper presents a new approach for fault detection based on data fusion and it has non-artificial setting. Firstly, the fault criterion for interphase difference energy ratio and time-frequency correlation coefficient of each line is proposed. Subsequently, the paper establish a coordinate system with the interphase difference energy ratio as X axis and the time-frequency correlation coefficient as Y axis, and it uses the Euclidean distance algorithm to get the characteristic distance of each line by fusing two-dimensional information. Finally, comparing the sound distance and the fault distance of each line to discriminate the fault line. Electromagnetic Transients Program (EMTP) simulation results and adaptability analysis have confirmed the effectiveness and reliability of the proposed scheme.

We emphasize the point that, standard model of cosmology is basically a model of classical general relativity and it seems inevitable to have a revision with reference to quantum model of cosmology. Utmost important point to be noted is that, ‘Spin’ is a basic property of quantum mechanics and ‘rotation’ is a very common experience. In this context, we propose five assumptions in line with Planck mass as the baby universe. We appeal that, 1) Universe can be modeled as a time-reversed black hole (a white hole) with rotation and light speed expansion, and 2) ‘Light speed expanding cosmic space’ can be called as ‘Flat space’. With reference to light speed expansion, if one is willing to re-define cosmic red shift as [z/(1+z)], without considering Lambda cosmology model of matter density fractions, light travel distances can be reproduced with a marginal error of +8.6% at z =1.2, (i.e. traditional light travel distance is 8.6% higher than our estimate), 0% at z = 11.5 and -5.5% at z = 1200.( i.e. traditional light travel distance is 5.5% lower than our estimate). Advantages of our model are, 1) A quantum model of cosmology can be developed with unification of general theory of relativity and quantum mechanics. 2) Tension in estimating the current Hubble parameter can be eliminated via scaled Hawking’s black hole temperature formula with great confidence. 3) Galactic dark matter and visible matter can be studied in a unified manner. 4) Galactic light travel distances can be estimated very easily without matter density fractions. 5) Big Bang and Inflation like non-general relativistic concepts can be relinquished with further study.

Separation Distances are used throughout the world to protect people and assets from the potential hazardous effects from propellants, explosives, and pyrotechnics. The current separation distances for Hazard Division (HD) 1.3 substances and articles used in the United States, in some cases, may not adequately protect against the effects from heat flux and debris when those substances and articles are ignited in a confined structure. Multiple tests in such a confined scenario with HD 1.3 substances have shown that the heat flux and debris hazards could result in injury at distances beyond the current specified explosives safety separation distance (ESSD). Herein are recommended ESSD’s for confined as well as unconfined HD 1.3 articles and substances based on the analysis of hundreds of tests. Recommended ESSD’s include a smaller value for unconfined quantities less than 145 kilograms and ESSD’s that are consistent with NATO distances for confined substances and articles.

In 2020, students of Pakistan had to adapt to the online environment for the very first time. This study aims to analyze the perceptions of medical, dental, and allied health students about online education in Pakistan. A descriptive, cross-sectional study was done to assess the level of acceptance of undergraduate students. A pre-validated questionnaire regarding demographics, past-experience of e-learning, advantages disadvantages of e-learning, and general perception of students towards e-learning was distributed. Descriptive statistics were computed for demographics, Mann-Witney-U test was used to compare the differences of perceptions between pre-clinical year and clinical years students. Kruskal-Wallis test was applied to compare the results of three specialties of students. Chi-square was used to compare overall category-wise positive and negative responses of students. 1200 students participated in the study. The major advantage identified by all students was the ‘comfortable environment’ in which they studied online. The major disadvantage selected by preclinical year students was ‘anxiety due to social isolation’ and that chosen by clinical year students was ‘lack of patient interaction’. Overall, 72% of students had a negative perception of e-learning. Student-teacher training, student counselling sessions, and innovative techniques need to be introduced to enhance student engagement and reduce pandemic stress.

Online courses in horticulture increase the breadth of students who may be able to enroll. However, it is challenging to create hands-on learning experiences in online classes that are valuable for student learning. In an online introduction to horticulture class at the University of Maine, we created a hands-on project that is appropriate for students to work on independently at home. Students built an environmental monitoring system using a relatively inexpensive Raspberry Pi microcomputer and sensors for monitoring environmental factors that impact plant growth with a particular focus on monitoring temperature and humidity. They monitored the growing environment in their homes while growing house plants and used the information from their environmental monitoring system to determine whether their home environment was suitable for growing plants. Students were asked to use a pre-existing computer program in the Python language to monitor the environment. They also learned about how components of the code function and changed some simple parts of the code. A majority of students working on this project felt moderately confident, somewhat more confident, or very confident about their ability to use a Raspberry Pi microcomputer in the future. This project provides students with valuable hands-on experience in building environmental monitoring systems and provides them with a deeper understanding of the impact of the environment on plant growth.

Let G[F,Vk, Huv] be the graph with k pockets, where F is a simple graph of order n ≥ 1,Vk= {v1,v2,··· ,vk} is a subset of the vertex set of F and Hvis a simple graph of order m ≥ 2,v is a specified vertex of Hv. Also let G[F,Ek, Huv] be the graph with k edge pockets, where F is a simple graph of order n ≥ 2, Ek= {e1,e2,···ek} is a subset of the edge set of F and Huvis a simple graph of order m ≥ 3, uv is a specified edge of Huvsuch that Huv− u is isomorphic to Huv− v. In this paper, we derive closed-form formulas for resistance distance and Kirchhoff index of G[F,Vk, Hv] and G[F,Ek, Huv] in terms of the resistance distance and Kirchhoff index F, Hv and F, Huv, respectively.

A picture is a powerful and convenient medium for inducing the illusion that one perceives a real three-dimensional scene. The relative invariance of picture perception across viewing positions has aroused the interest of painters, photographers and visual scientists. Many studies have been devoted to perceptual invariance when pictures are viewed from oblique directions. Invariance across viewing distances has received less attention. This study presents a computational analysis of pictures of perspective scenes taken from different distances between camera and physical objects. Distances and directions of pictorial objects were computed as function of viewing distance to the picture and compared with distances and directions of the physical objects as function of camera position. The computations show that pictorial distance and direction are determined by angular size of the depicted objects. Pictorial distance and direction are independent of camera position, focal length of the lens, and picture size. Ratios of pictorial distances, directions and sizes are constant as function of viewing distance. The constant ratios are proposed as the reason for invariance of picture perception over a range of viewing distances. Reanalysis of distance judgments obtained from the literature shows that perspective space, previously proposed as the model for visual space, is also a good model for pictorial space. The geometry of pictorial space contradicts some conceptions about picture perception.

In this brief paper a quantum algorithm to calculate the Hamming distance of two binary strings of equal length (or messages in theory information) is presented. The algorithm calculates the Hamming weight of two binary strings in one query of an oracle. To calculate the hamming distance of these two strings we only have to calculate the Hamming weight of the xor operation of both strings. To test the algorithms the quantum computer prototype that IBM has given open access to on the cloud has been used to test the results.

The efficiency of the MOND theory of Mordehai Milgrom might be unrelated to distance, but instead connected to flatness of galaxies and the fact that the large scale distribution of matter is essentially two-dimensional. A combination of the pushing gravity paradigm with essential flatness of large luminous matter clusters leads to an approximate MOND theory which would allow to avoid the dark matter hypothesis.

Increasing rate of seepage velocity from several formation characteristics, such as permeability and porosity, in water aquifer environment greatly prompt pollution of water reservoirs within a short period of time. Considerably, migration rate of dissolved heavy metals from Solid Waste Dumpsites (SWD), such as municipal dumpsites and landfills, through heterogeneous aquifer environment, and finally into nearby water reservoirs are mainly influenced by variation of seepage velocity within the soil and water environment. This presents a dynamic system for water pollution that was studied using a formulated mathematical model to describe the transport process of dissolved heavy metals, mainly characterized by seepage velocities, within the water aquiferous environment. Permeability, porosity, fluid pressure and concentration of heavy metals in aquiferous environment were used as principal parameters that influence seepage velocity of the metals, in dissolved state, through the structural formation of water aquifers. The derived mathematical equations that constitute the model of this study were generated through Darcy’s law and the equation of continuity. The model was validated on structural river aquifer sediments, and it was solved using graphical method through matlab open-source software. The initial and boundary conditions were obtained by discretizing the geological setting of flow region so as to transform the gradient of the head, into the time domain.

This research work studies the characteristics of wear and wear resistance of composite powder coatings, deposited by high-velocity oxygen fuel, which contain composite mixtures Ni-Cr-B-Si having different chromium concentrations – 9.9%; 13.2%; 14%; 16% and 20% , at one and the same size of the particles and the same content of the remaining elements. The coating of 20% Cr does not contain B and Si. Out of each powder, composite coatings have been prepared without any preliminary thermal treatment of the substrate and with preliminary thermal treatment of the substrate up to 650оС. The coatings have been tested under identical conditions of dry friction over a surface of solid firmly attached abrasive particles using the tribological testing device „Pin-on-disk“. Results have been obtained and the dependences of the hardness, mass wear, intensity of the wearing process, absolute and relative wear resistance on the Cr concentration under identical conditions of friction. It has been found out that for all the coatings the preliminary thermal treatment of the substrate leads to a decrease in the wear intensity. Upon increasing Cr concentration the wear intensity diminishes and it reaches minimal values at 16% Cr. In the case of coatings having 20% Cr concentration, the wear intensity is increased, which is due to the absence of the components B and Si in the composite mixture, whereupon no inter-metallic structures are formed having high hardness and wear resistance. The obtained results have no analogues in the current literature and they have not been published by the authors.

The teaching of the lunge technique in fencing is critical in the developmental age. The relations of anthropometrics with kinematics of lunge was studied only in adult fencers, and no study exist in young considering the different level of experience. Our aims were to assess, in young fencers, which factors, between the anthropometric and the kinematics, were mostly connected with lunge performance (speed and excursion) in different genders and expertise levels. Fifteen young fencers participated in this study. Lunge kinematics, anthropometric characteristics and force expressed in vertical jump tests were collected. Maximal lunge velocity resulted mainly correlated with the posterior knee’s extension ((r=0.56, p=0.031). The lunge distance and mean hip velocity were mostly correlated with fencers’ height (r=0.85, p=0.000 and r=0.76, p=0.001) and FFM (r=0.8, p=0.000 and r=0.73, p=0.002). Experts and non-experts show significant differences in fat free mass, area of upper arm, and of thighs (Effect Size = 1,27 – 1,33, p= 0,021-0,035). From our results it emerges that, in this age range, the analysed aspects of lunge performance are mainly correlated with participant’s anthropometry. Moreover, it is already possible in this age span, to find technical differences linked to the experience.

We calculate the sound velocity and the damping rate of the collective excitations of a 2D fermionic superfluid in a non-perturbative manner. Specifically, we focus on the Anderson-Bogoliubov excitations in the BEC-BCS crossover regime, as these modes have a soundlike dispersion at low momenta. The calculation is performed within the path integral formalism and the Gaussian pair fluctuation approximation. From the action functional, we obtain the propagator of the collective excitations and determine their dispersion relation by locating the poles of this propagator. We find that there is only one kind of collective excitation, which is stable at $T=0$ and has a sound velocity of $v_{F}/\sqrt{2}$ for all binding energies, i.e. throughout the BEC-BCS crossover. As the temperature is raised, the sound velocity decreases and the damping rate shows a non-monotonous behavior: after an initial increase, close to the critical temperature $T_{C}$ the damping rate decreases again. In general, higher binding energies provide higher damping rates. Finally, we calculate the response functions and propose that they can be used as another way to determine the sound velocity.

Purposely slow velocity resistance exercise (i.e., 10 s concentric and eccentric phases) is a popular training method, but limits the loads that can be lifted (e.g., <50% 1 RM). This study compared the biomechanical properties of purposely slow velocity (SLOW) and traditional resistance exercise (TRAD) that uses maximal lifting velocities. Healthy resistance-trained men (n=5) performed two testing sessions (barbell squat and bench press) in random-order; a SLOW session (1 set x 10 repetitions at 28% 1 RM, 10 s concentric & eccentric), and a TRAD session (3 x 10 at 70% 1 RM, controlled eccentric and maximal concentric). A force plate and linear position transducer were used to collect kinetic and kinematic data for every repetition of both protocols (α = 0.05). For both exercises, both concentric and eccentric mean force (N) and power (W) for each repetition was greater for TRAD. When the entire training session (squat + bench press) was examined, SLOW exhibited greater time under tension, while TRAD produced greater work (J) and impulse (N·s). Contrary to suggestions in both the lay and scientific literature, purposely slow resistance exercise produced less force, power, and work than traditional velocity resistance exercise.

In this paper, we studied and analyzed the behavior of velocity profiles and the distribution of pressures in a pipe connected to an accessory. In this case, it was a 90º elbow fitting in which water flows as an incompressible flow. This study was developed numerically through the fluent program of ANSYS. It is of practical interest in engineering because it is based on results regarding the internal structure of a model of incompressible flows. In the same way, it provides a basis for the proper design and implementation of velocity profiles within an elbow.In the agricultural industry, suitable systems can be implemented for crop irrigation in this way with the results obtained to improve the design in the fluid distribution system.We used a feasible κ-ε turbulence model because this model causes less turbulence than the standard κ-ε model. A mesh independence study was developed, in which it was observed that combining different densities of meshes for the same geometry causes some variables, so a fine meshing was used to carry out the study so that the results are as close to reality as possible.

The objective of this study is to measure the crack propagation speed in three types of self-compacting concrete reinforced with steel fibers loaded under four different loading rates. Central-notched prismatic beams with two types of fibers (13 mm and 30 mm in length), three fiber volume ratios, 0.51%, 0.77% and 1.23%, were fabricated. Four strain gages were glued on one side of the specimen notch to measure the crack propagation velocity, a fifth one at the notch tip to estimate the strain rates upon the initiation of a cohesive crack and the stress-free crack. A servo-hydraulic testing machine and a drop-weight impact device were employed to conduct three-point bending tests at four loading-point displacement rates, the former to perform tests at 2.2 μm/s, 22 mm/s and the latter for those at 1.77 m/s, 2.66 m/s, respectively. With lower fiber contents, smooth mode-I cracks were formed, the crack speed reached the order of 1 mm/s and 20 m/s. However, crack velocities up to 1417 m/s were obtained for the concrete with high content of fibers under impact loading. This value is fairly close to the theoretically predicted terminal crack velocity of 1600–1700 m/s. Numerical simulations based on cohesive theories of fracture and preliminary results based on the technique of Digital Image Correlation are also presented to complement those obtained from the strain gages. In addition, the toughness indices are calculated under all four loading rates. Strain hardening (softening) behavior accounting from the initiation of the first crack is observed for all three types of concrete at low (high) loading rates. Significant enhancement in the energy absorption capacity is observed with increased fiber content.

With reference to Planck scale, increasing support for large scale cosmic anisotropy and preferred directions and by considering an increasing ratio of Hubble parameter to angular velocity, right from the beginning of Planck scale, we make an attempt to estimate ordinary matter density ratio, dark matter density ratio, mass, radius, temperature, age and expansion velocity (from and about the baby universe in all directions). We would like suggest that, from the beginning of Planck scale, 1) Dark matter can be considered as a kind of cosmic foam responsible for formation of galaxies. 2) Cosmic angular velocity decreases with square of the decreasing cosmic temperature. 3) Increasing ratio of Hubble parameter to angular velocity plays a crucial role in estimating increasing cosmic expansion velocity and decreasing density ratios of dark matter and ordinary matter. 4) There is no need to consider dark energy for understanding cosmic acceleration.

Distance Learning has become the new standard, especially after the pandemic and due to the technological advances, that are incorporated into the teaching procedure. At the same time, the augmented use of the internet has blurred the borders between distance and conventional learning. Students interact mainly through LMSs, leaving their digital traces that can be leveraged to improve the educational process. This work aims to propose a model that can capture the students' behaviors based on the clickstream data associated with the discussion forum and additionally to suggest interpretable patterns that will support education administrators and tutors in the decision-making process. To achieve our goal, we use Social Network Analysis (SNA) as networks represent complex interactions in a meaningful and easily interpretable way. Moreover, simple or complex network metrics are becoming available to provide valuable insights into the students’ social interaction. This study concludes that by leveraging the imprint of these actions in an LMS and using metrics of SNA, differences can be spotted in the communicational patterns that go beyond simple participation recording. Although HITS and PageRank algorithms were created with completely different targeting, it is shown that they can also reveal methodological features in students’ communicational approach.

An irreparable rotator cuff tear is a challenging condition to treat, and various treatment modalities are being introduced. Medialization in the partial repair method has the limitation of exposing the tuberosity, while tension-free biologic interpositioning tuberoplasty using acellular dermal matrix (ADM) has the limitation of exposing the humeral head. The authors believe that by combining these two techniques, it is possible to complement each other's limitations. Therefore, they propose a surgical method that combines medialization and biologic interpositioning tuberoplasty for addressing these constraints.

During the pandemic, educational digitization experienced a significant increase. In Mexico, social service is a crucial component of technical and professional training, a phase during which individuals apply the knowledge gained throughout their university education. The aim of this study is to standardize a digital model for the management of social service in the health care sector within health care units. This study employed an analytical, observational, retrospective, and longitudinal approach, involving two groups of trainees: Group A (n=133), utilizing a Non-Digital Model, and Group B (n=50), employing a Digital Model. In Stage I. the model design underwent validation through the Delphi method with a panel of three experts. The model was implemented on a Classroom® digital platform with the integration of the elements 1) a monthly rotation rubric 2) care services rubric 3) clinical cases or nursing process rubric, and 4) innovation project rubric. The validation of the model achieved 100% agreement (K=1). The variables measured for each group included the school of origin, career, unit of assignment, timely enrolment, and timely delivery of rubrics on the platform. The difference between the two groups was measured using Chi-Square. To measure the impact, the difference in the timeliness of the products was considered. From the University of Quintana Roo, the difference was 20.3 vs 34%. According to the Unit of Attachment the most frequent was HGR No. 17 with Group A at 22.5 vs 52%. According to the product the least delivered was Product 4, with 69% vs 81%. Timely enrollment was observed in Group A at 89% vs Group B at 80% p=0.001. Overall timely delivery in Group A was 81% vs Group B at 91% p=0.001 in the first 6 months post-implementation. Demonstrating that the implementation of the digital platform was effective, representing a significant advance in the adaptation of medical education to the circumstances imposed by the pandemic, highlighting the feasibility and effectiveness of digital teaching methods in the training of health professionals.

Critical distance concerns precise digital levelling, which has inaccurate results at a certain sighting distance. The influence of critical distance on a measured height difference has been confirmed by calibrating certain digital levels and their appropriate code devices on a vertical comparator under laboratory conditions. The paper describes the research based on experimental measurements done to find the influence of critical distance on height differences obtained by precise digital levels of Leica NA3003 and DNA03. The processing of the measurement results consisted of de-fining a random error on a station by using parameter estimation of an error model to specify a partial error on a station dependent on sighting distance and then the processing phase continues with the finding the relation between sighting distance and dispersion of height differences ac-quired by digital levelling under terrain conditions. The theoretical part involves the development of levelling accuracy theories that vary over time by view on random and systematic error propagation. The numerical and graphical solution of the experimental measurements involves ordering the height differences into sighting groups according to the sighting distances and the computed standard deviations, which represent a measure of height differences dispersion. The suspicious sighting groups are highlighted in the table and compared with theoretical data pro-vided by authors of calibrating the same digital levels

One of the greatest COVID-19 related challenges for children and their families was managing distance learning due to school closures. We also know from previous research that families with a child with a neurodevelopmental disorder such as ADHD or ASD were struggling more than others, but also experiences some positive effects. However, few qualitative studies have been conducted. The present study therefore aimed to investigate parental experiences of negative and positive effects of distance learning during the COVID-19 pandemic in a large sample of families with an adolescent with ADHD and/or ASD and a matched comparison group (n = 682). Data was collected through open-ended questions as part of a larger survey study. Five main themes, with different sub-themes were identified for both negative and positive effects: 1) Teaching, 2) Social, 3) Support, 4) Child factors, and 5) Home environment. In addiction, the main themes “Technical problems” were identified for negative effects. Families with a child with ADHD/ASD reported negative effects related to “Child factors” and “Support” more frequently than the controls, as well as negative effects related to some aspects of “Teaching” and “Technical problems”. Regarding positive effects, significant group differences were primarily found for the theme “Child factors”. These findings are discussed botn in terms of how to best prepare for possible future pandemics, but also how to best provide educational support for children with ADHD and/or ASD when schools are open.

Background: Distance to a health facility for inpatient care in developing countries has been a huge hindrance towards the achievement of the Sustainable Development Goal three. The United Nation encourages countries to research on access to inpatient care, so as to form health policies based on data. Methods: Data on four hundred and eighty-one participants of all ages from forty-seven counties in Kenya who sought inpatient care in Kenya in 2018 were analyzed. Distance to a health facility was captured as a continuous variable and was self-reported by the respondent. The response exhibited a discrete mass at zero and continuous characteristic, therefore a Tweedie distribution was adopted for modelling. Due to the correlation nature of clustered data, we embraced the Generalized Estimating Equations approach with an exchangeable correlation. Since no standard software was available to analyze this problem, we developed an R functions. We assessed the best model fit using the QICu and criteria, in which the lowest value for the former and the highest for the later are preferred.Findings: Differences in employment, ability to pay for the service and household size are associated with the distance covered to access government facilities. Interpretation: Poor people tend to have large households and are more likely to live in rural areas and slums, thus are forced to travel for long distance to access inpatient care. Compared to unemployed, the employed could have better socio-economic status and possibly live within reach of the inpatient health facilities, therefore travel less distances to access. Longer distances are associated with high payments, signifying some form of specialized treatment care due to the complexity of the medical cases, that are expensive to treat.

The angular diameter is the angle subtended by a generic object – an apple or a star – to the eye of an observer, and it describes how large the object appears from a given viewpoint. The angular diameter represents a powerful tool for distance calculations starting from a directly measurable information and it finds application in several contexts varying from cosmography to architecture. In this article, the author proposes a novel equation to calculate the apparent diameter of whatever object. This equation defines the relationship between the object’s apparent diameter with respect to the travelled distance starting from the initial distance R₀ at which the observed object is located. Based on the preliminary tests conducted, the model seems to faithfully portray this relation with respect to measured values, also at the astronomical scale, thus considering the Earth-Moon distance, where, the absolute error detected is about 0.56%. Tests highlight also a dependency between the results accuracy and the measurement conditions suggesting a high level of sensibility linked to the initial magnification effect produced by the retina or the artificial lens employed.

Allama Iqbal Open University (AIOU) is the largest distance learning institute of Pakistan and providing education to 1.4 million students. This is fairly a large setup across the country where students are geographically distributed. Currently the system works on a manual approach which is not efficient. Allocation of tutors and study centers to students plays a key role in distance learning for a better learning environment. Assigning tutors and study centers to distance learning students is a challenging task when there is huge geographical spread. The utilization of geospatial technologies in open and distance learning can fix allocation problems. This research analyzes the real data of twin cities Islamabad and Rawalpindi. The results show that the geospatial technologies can be used for efficient and proper resource utilization and allocation, which in turn can save the time and money. The overall idea fits into improved distance learning framework and related analytics.

The Centers for Disease Control and Prevention (CDC) indicates that individuals with prediabetes are significantly less likely to develop type 2 diabetes if they participate in a lifestyle change program that results in at least 5% weight loss and 150 minutes of physical activity per week. The CDC recognizes distance learning as an effective delivery mode for lifestyle change programs to prevent type 2 diabetes. The purpose of this study was to assess enrollment, engagement, and effectiveness of a type 2 diabetes prevention program (DPP) using synchronous distance technology. Eat Smart, Move More, Prevent Diabetes (ESMMPD) is an intensive 12-month DPP delivered using synchronous distance technology. Throughout 26 lessons, participants focused on healthy eating, physical activity, and mindfulness behaviors. Study findings showed a significant decrease in A1C (-0.24 p<.0001). Weight loss averaged 5.66% for those who completed the program. Based on the Wilcoxon signed-rank test, participants demonstrated statistically significant changes in self-reported confidence in their ability to perform all 18 health-promoting behaviors assessed (p<.0001). Participation in the program also resulted in the adoption of health promoting behaviors. A DPP using synchronous distance technology is an effective delivery mode to help participants adopt healthy behaviors, increase physical activity, and achieve the weight loss necessary to prevent or delay the onset of type 2 diabetes.

To investigate the structural behavior of simply supported concrete beams with steel and polypropylene fiber under low velocity impact loading. In all twenty-four beams (150X200X1800 mm) with simply supported boundary condition were modeled and analyzed using ABAQUS software. Steel and polypropylene fibers of aspect ratio of 60 and 231 respectively are used. The total volumes of fibers are maintained at 1% by volume of specimen. A 100 kg hammer with tip diameter 16 mm (hemispherical contact area = 201 mm2) with four different velocities (3.13 m/s, 4.42 m/s, 5.43 m/s and 6.11 m/s) were used in the analysis. It is observed that with the addition of hybrid fibers the deflection in beams was reduced. The beams with 1% PP and 0% steel fiber shows the maximum deflection values due to low modulus of elasticity. Beams with 0.9% steel and 0.1% polypropylene fibers was less affected in terms of deflection as compared to all other beams, it is due to presence of high tensile strength fibers.

Background - Technological developments induced lifestyle changes and increase population physical inactivity. This change in lifestyle can affect the male-female morphological and physical fitness differences. The aim of this study is to determine and to compare the effect of sex differences in percentage of body fat on speed and endurance running performance. Methods - 72 male and 64 female students aged 20 to 23 years participated in this study. After assessing their morphological characteristics, running performances during 30 m and 400 m, and maximum aerobic velocity (MAV) and maximal oxygen consumption (VO2max) during a 20 m shuttle running test have been estimated for each subject. Male students were re-tested after being overweighed down with a weight equivalent to the mean differences in body fat recorded between the two sexes in the form of a loaded worn vest. Results – Male presented a percentage of fat mass (17.2 ±2%) significantly (p <0.001) lower than that of women subject (25.0 ±2.5%). Running performances during 30 m and 400 m, MAV and VO2max were significantly (p<0.001) better in males. During the weighted condition, male performances during 30 m and 400 m, MAV and VO2max were attenuated by 6.89%, 14.16%, 6.48% and 10.07%, respectively but remain significantly better than those of female students. Conclusion - The persistence of sex differences after overweighting male students indicates that body fat could be responsible for ≈ 50 to 70% of the observed differences between sexes performances during short and long sprints, and 20 m shuttle running test.

Shear velocity logs are crucial in the oil and gas industry for assessing subsurface mechanical properties, including rock stiffness, shear strength, and seismic wave propagation, essential for optimizing hydrocarbon exploration and production strategies. However, obtaining shear velocity logs conventionally is expensive and time-consuming, especially when drilling additional wells solely for this purpose. With the recent boom in machine learning algorithms adoption across various scientific domains, it proved to be an extremely valuable tool for numerous applications in the oil and gas industry. It makes use of the readily available large datasets collected over decades and leverages this data to train powerful, data-driven models, reducing the reliance on empirical relationships that usually have poor generalization. This study follows this approach and presents the use and comparison of machine learning algorithms for predicting shear velocity logs from conventional and readily available logs in the Ahnet field, Algeria. Ultimately, this study aims to enhance reservoir assessment and optimize hydrocarbon recovery processes, potentially reducing exploration costs and improving oil and gas production decision-making in the region.

Impact force and maximum velocity are important indicators of kick efficiency in fighting activities. Therefore, this systematic review compared the front kick (FK) and roundhouse kick (RK), including maximal and impact force, maximum velocity, maximum angular velocity, and execution time, at different target types and experience levels. The Web of Science, SportDiscus, and PubMed were systematically searched from January 1982 to May 2022, according to PRISMA guidelines. The normalized kicking values were compared using one-way ANOVA. Eighteen articles, including FK with a pooled sample of 113 elite men, 109 sub-elite men, and 46 novices, and 25 articles, including RK with a sample of 238 elite men, 143 sub-elite men, and 27 novice men, fulfilled the inclusion criteria. The primary findings were that the impact forces of FK were higher than RK for the novice, sub-elite, and elite groups by 47% (p<0.01), 92% (p<0.01), and 120% (p<0.01), respectively. Moreover, the maximum foot velocity of RK was faster than FK for the sub-elite and elite groups by 44% (p<0.01) and 48% (p<0.01), respectively. The Elite group had 65% (p<0.01) higher knee extension angular velocity within RK than FK, and 138% (p<0.01) higher hip extension angular velocity within FK than RK.

Power series expansions are useful in approximation theory and mathematical physics. The manuscript presents several types of fractional Taylor expansions of sufficiently smooth functions. This is achieved by employing an incremental regularization procedure to the computation of the derivative. The series are constructed in an algorithmic way, which allows for its implementation in computer algebra systems.

Surface velocity is traditionally measured with in situ techniques such as velocity probes (in shallow rivers) or Acoustic Doppler Current Profilers (in deeper water). In the last years, researchers have developed remote sensing techniques, both optical (e.g., image-based velocimetry techniques) and microwave (e.g., Doppler radar). These techniques can be deployed from Unmanned Aerial Systems (UAS), which ensure fast and low-cost surveys also in remotely-accessible locations. We compare the results obtained with a UAS-borne Doppler radar and UAS-borne Particle Image Velocimetry (PIV) in different rivers, which presented different hydraulic–morphological conditions (width, slope, surface roughness and sediment material). The Doppler radar was a commercial 24 GHz instrument, developed for static deployment, adapted for UAS integration. PIV was applied with natural seeding (e.g., foam, debris) when possible, or with artificial seeding (woodchips) in the stream where the density of natural particles was insufficient. PIV reconstructed the velocity profile with high accuracy typically in the order of a few cm s⁻¹ and a coefficient of determination (R²) typically larger than 0.7 (in half of the cases larger than 0.85), when compared with acoustic Doppler current profiler (ADCP) or velocity probe, in all investigated rivers. However, UAS-borne Doppler radar measurements show low reliability because of UAS vibrations, large instrument sampling footprint, large required sampling time and difficult-to-interpret quality indicators suggesting that additional research is needed to measure surface velocity from UAS-borne Doppler radar.

By using directed dimensional analysis and data fitting, an explicit universal scaling law for the velocity of dominoes toppling motion is formulated. The scaling law shows that domino propagational velocity is linearly proportional to the 1/2 power of domino separation and thickness, and -1/2 power of domino height and gravitation. The study also proved that dominoes width and mass have no influence on the domino wave traveling velocity. The scaling law obtained in this Letter is very useful to the dominoes game and will help the domino player to place the dominoes for fast speed and have a quick estimation on the speed without doing complicated multi-bodies dynamical simulation.

This paper deals with a non-contact method to identify the aerodynamic propeller parameters of the Parrot AR.Drone quadrotor. The experimental set consists in a camera recording the vehicle flights, the audio signal is extracted and is used a spectrogram analysis to estimates the propeller velocity. First, the aerial vehicle takes off and starts a hovering maneuver. The experiment is repeated with different additional masses attached to its rigid body. If the weight over the UAV increases/decreases, then the propeller must rotates faster/slower to produce a higher/lower thrust, and consequently, the sound frequency increases/decreases. Finally, this proposition is validated experimentally, and the estimated velocity is used to identify the quadrotor thrust parameters.

We present a tutorial to realize a multidimensional fitting procedure capable of extracting all the relevant information contained in a sequence of charged particle images acquired as a function of time in femtosecond pump-probe experiments. The images are reproduced using a 3D fitting method, which provides the velocity (or center-of-mass kinetic energy) and angular distributions contained in the images and their time evolution. A detailed example of the method is shown through the analysis of the time-resolved predissociation dynamics of CH₃I on the B-band origin [Gitzinger et al., J. Chem. Phys. 133, 234313 (2010)]. We show that the multidimensional approach is essential for the analysis of complex images that contain several overlapping contributions where reduced dimensionality analyses cannot provide a reliable description of the features present in the image sequence. This methodology can be generalized to many types of multidimensional data analysis.

Quaternion algebra is used both for the description of the motion of material objects in 4D space-time and for the representation of the energy-momentum density tensor in the same quaternion basis, accurate to some arbitrary scalar fields. Quaternionic generating operators applied repeatedly to the energy-momentum density tensor lead to the gravitomagnetic equations that are parent equations for the series of physical equations ranging from the wave equations up to the quantum mechanical ones. Before finally deducing the gravitomagnetic equations, it is necessary to use the Lorentz gauge at a certain stage to cut off the arbitrary scalar fields. We declare that these superfluous scalar fields, inaccessible to direct observation, represent dark matter and dark energy. We show in what way the dark matter can provide a flat profile of the orbital speed of the galaxy's arm rotations.

With reference to Planck scale, Mach’s relation, increasing support for large scale cosmic anisotropy and preferred directions and by introducing two new parameters Gamma and Beta, right from the beginning of Planck scale, we make an attempt to estimate ordinary matter density ratio, dark matter density ratio, mass, radius, temperature, age and expansion velocity (from and about the baby universe in all directions). We would like suggest that, from the beginning of Planck scale, 1) Dark matter can be considered as a kind of cosmic foam responsible for formation of galaxies. 2) Cosmic angular velocity is directly proportional to squared cosmic temperature. 3) Ratio of critical temperature to actual temperature plays a heuristic role in understanding ordinary and dark matter density ratios. 4) Cosmic expansion velocity increases with decreasing total matter density ratio. 5) There is no need to consider dark energy for understanding cosmic acceleration.

Accurately predicting the distance an object will travel to its destination is very important in various sports. Acceleration sensors as a means of real-time monitoring are increasingly gaining increasing attention in sports. Due to the low energy output and power density of Triboelectric Nanogenerators (TENGs), recent efforts have focused on developing various acceleration sensors. However, these sensors suffer from significant drawbacks of large size, complexity, high power input requirements, and high cost. Here, we described a portable and cost-effective real-time refreshable strategy design comprising a series of individually addressable and controllable units based on TENGs embedded in a flexible substrate. This results in a highly sensitive, low-cost, and self-powered acceleration sensor. Putting, which accounts for nearly half of the strokes played, is obviously an important component of the golf game. The developed acceleration sensor has an accuracy controlled within 5 %. The initial velocity and acceleration of the forward movement of a rolling golf ball after it is hit by a putter can be displayed, and the stopping distance quickly calculated and predicted in about 7 seconds. This research demonstrates the application of the portable TENG-based acceleration sensor, while paving the way for designing portable, cost-effective, scalable, and harmless ubiquitous self-powered acceleration sensors.

Radial basis function (RBF) networks are often viewed as instable when used in multi-layered architectures and therefore are mostly used in a single-layered manner. Universal approximation theorems for single-layered RBF networks further render deeper architectures useless. However, deep neural networks have proven their effectiveness on many different tasks. We show that deeper RBF architectures with multiple radial basis function layers are achievable and able to learn. We introduce an initialization scheme for deep RBF networks based on k-means clustering and covariance estimation. We further show how to make use of convolutions to speed up the calculation of a Mahalanobis distance in a partially-connected fashion, similar to convolutional neural networks (CNNs). Finally, we evaluate our approach on image classification as well as speech emotion recognition tasks. Our results show that deep RBF networks perform similar to simple CNNs.

The purpose of the present study was to develop an experimental model for studying of the intra-articular knee movements depending on the work of the knee joint and applied muscle groups in isometric stretching conditions with different tens. The experimental procedure includes ultrasound examination of a knee joint after isometric stretching of healthy men (n=32). The changes in millimeters of the distances between the femur and tibia were measured with ultrasound sonographer at three stages. The first stage was performed on ten (n=10) healthy men at five different sitting and upright positions. In the second and third experimental model stages the lower limbs loading was on 22 participants. Our hypothesis which was confirmed, was that as a result of increasing extraloads on the participants back (2, 5, 10, 15, 17, 20 kg), a intra-articular decrease in the femur-tibia cartilage surface distance wiil be observed. The accuracy of the created experimental model was improved over its three stages from 30% to 9%. Quantitative model data can help to create a mathematical model for the mechanical effects during deformation of the knee joint bone cartilage, as well as to outlines the some future tasks: increasing loading weights; enlarge participant groups; comparison men and women; healthy and pathology comparison.

With increasing demand from unmanned driving and robotics, more attention has been paid to point cloud-based 3D object accurate detection technology. However, due to the sparseness and irregularity of the point cloud, the most critical problem is how to utilize the relevant features more efficiently. In this paper, we proposed a point-based object detection enhancement network to improve the detection accuracy in the 3D scenes understanding based on the distance features. Firstly, the distance features are extracted from the raw point sets and fused with the raw features about reflectivity of the point cloud to maximizing the use of information in point cloud. Secondly, we enhanced the distance features and raw features that we collectively refer to them as self-features of the key points in Set Abstraction (SA) layers with the self-attention mechanism, so that the foreground points can be better distinguished from the background points. Finally, we revised the group aggregation module in SA layers to enhance the feature aggregation effect of key points. We conducted experiments on the KITTI dataset and nuScenes dataset and the results show the enhancement method proposed in this paper has excellent performance.

Abstract: (1) Background: The Covid-19 pandemic has spread globally since January 2020 and is a threat to public health. This study aims to highlight the psychosocial impact on Greek nursing students and the challenges they received regarding the new sustainable educational reality, in the context of the sudden and exclusive application of distance education during the pandemic Covid-19; (2) Methods: Questionnaires were distributed through an online form (Lime Survey) to undergraduate nursing students enrolled in online courses. Data were collected between De-cember 2020 and January 2021 (3) Results: A total of 341 participants were included in the study. Some of the participants (9.1%) reported that being unemployed because of the Covid-19 affected their sustainability of life. Similarly, distance education had a negative impact on students' par-ticipation in social activities with their classmates (64.5%), while many of the participants were concerned that the sudden transition from face-to-face to distance education would have a negative impact on their future career (46.3%). Furthermore, the majority of students in this study seemed to disagree that distance education could be more effective than face-to-face education (72.1%); (4) Conclusions: It is undoubtedly proven that the effects of the Covid-19 pandemic have a great impact on the educational sector. These social and psychological changes endangered the viability of students in the Greek educational reality.

Background: Recent advances allow the usage of Augmented Reality (AR) for many medical procedures. We perform different AR-assisted knee surgery techniques using optical surgical navigation with ArUco-type artificial marker sensors. Our study aimed to evaluate the system’s accuracy using an in vitro protocol. We hypothesised that the system’s accuracy was equal to or less than 1mm and 1° for distance and angular measurements, respectively. Methods: Our research was an in-vitro laboratory with a 316 L steel model. We evaluated absolute reliability according to the Hopkins criteria with seven independent evaluators. Each observer measured the thirty palpation points and the trademarks to acquire direct angular measurements on three occasions separated by at least two weeks. Results: The accuracy of the system to assess distances had a mean error of 1.203mm and an un-certainty of 2.062, and for the angular values, a mean error of 0.778° and an uncertainty of 1.438. The intraclass correlation coefficient was for all intra-observer and inter-observer almost perfect or perfect. Conclusions: The mean error for the distance’s determination has been statistically larger than 1mm (1.203mm) but with a trivial effect size. The mean error assessing angular values was sta-tistically minor than 1°. Our results are similar to those published by other authors in accuracy analyses of AR systems.

So called Higuchi’s method of fractal dimension estimation is widely used and the term Higuchi’s fractal dimension even occurs in many publications. This paper deals with this method from mathematical point of view. Terms distance and dimension and its basic properties are explained and Higuchi’s dimension according the original source is defined. Definition of Higuchi’s dimension was comparated with mathematical definition of the distance and dimension. It is showed, that the definition of the Higuchi’s dimension does not satisfy axioms of distance and dimension. So called Higuchi’s method and Higuchi’s dimension are mathematically incorrect. Therefore, all results achieved by this method are scientifically unreliable.

Education setting evolved from historical open learning system to traditional classroom set-up to distance learning modality. Teaching-Learning practice is transformed with an evolution of teaching-learning materials. With technological advancement in progressive manner and it’s increasing use in academic setting, distance learning has been the on-demand and on-debate topic in current educational discourse. Comparatively fresh topic in Nepali academic setting, this paper intended to analyze the perception of Nepali students towards online modality in Nepali academic setting. This paper further analyzed the student’s preference towards distance learning in current Nepali academic setting. Research findings were analyzed based on data collected through literature review, interview with students and professor and quantitative data collection through use of google form. Study identified opportunities as revenue generation; continuation of academic career from any part of country; increase learning outcome among jobholders. Study identified challenges as unequal access and quality of internet facilities; affordability of laptops/computers; limited interaction; and frequent disturbances. Seeing the better prospects, study strongly supported the need of shift in academic shift from traditional setting to non-traditional setting in Nepali context to meet the global needs of competitive and quality education.

We propose a quantum version of the well known minimum distance classification model called "Nearest Mean Classifier" (NMC). In this regard, we presented our first results in two previous works. In [34] a quantum counterpart of the NMC for two-dimensional problems was introduced, named "Quantum Nearest Mean Classifier" (QNMC), together with a possible generalization to arbitrary dimensions. In [33] we studied the n-dimensional problem into detail and we showed a new encoding for arbitrary n-feature vectors into density operators. In the present paper, another promising encoding of n-dimensional patterns into density operators is considered, suggested by recent debates on quantum machine learning. Further, we observe a significant property concerning the non-invariance by feature rescaling of our quantum classifier. This fact, which represents a meaningful difference between the NMC and the respective quantum version, allows to introduce a free parameter whose variation provides, in some cases, better classification results for the QNMC. The experimental section is devoted to: i) compare the NMC and QNMC performance on different datasets; ii) study the effects of the non-invariance under uniform rescaling for the QNMC.

The k-means is one of the most popular and widely used clustering algorithm, however, it is limited to only numeric data. The k-prototypes algorithm is one of the famous algorithms for dealing with both numeric and categorical data. However, there have been no studies to accelerate k-prototypes algorithm. In this paper, we propose a new fast k-prototypes algorithm that gives the same answer as original k-prototypes. The proposed algorithm avoids distance computations using partial distance computation. Our k-prototypes algorithm finds minimum distance without distance computations of all attributes between an object and a cluster center, which allows it to reduce time complexity. A partial distance computation uses a fact that a value of the maximum difference between two categorical attributes is 1 during distance computations. If data objects have m categorical attributes, maximum difference of categorical attributes between an object and a cluster center is m. Our algorithm first computes distance with only numeric attributes. If a difference of the minimum distance and the second smallest with numeric attributes is higher than m, we can find minimum distance between an object and a cluster center without distance computations of categorical attributes. The experimental shows proposed k-prototypes algorithm improves computational performance than original k-prototypes algorithm in our dataset.

In this study, the friction factor of turbulent pipe flow for dried rice malt extract solutions is reduced experimentally to that of a Newtonian fluid. The friction factor is measured for four types of solutions at different culture times and concentrations. The results indicate that the experimental data points of the test solutions diverge from the maximum drag reduction asymptote at and above Re√f ≅ 200 and align parallel to those of Newtonian fluids. This drag reduction phenomenon differs from that of artificial high molecular polymer solutions. It is classified as a Type B drag reduction phenomenon of biopolymer solutions and fine solid particle suspensions. The order of drag reduction corresponds approximately to that of 5–50 ppm xanthan-gum solutions reported previously. Furthermore, the velocity profile in a turbulent pipe flow was predicted using a semi-theoretical equation, in which the friction factors were determined using the difference between the experimental results of the tested solutions and Newtonian fluids. The results indicate a more considerable thickening of the viscous sublayer in the turbulent pipe flow of the test solutions than that of Newtonian fluids.

Abstract: Rationale. Object tracking has significance in many applications ranging from control of unmanned vehicles to autonomous monitoring of specific situations and events, especially when providing safety for patients with certain adverse conditions such as epileptic seizures. Conventional tracking methods face many challenges, such as the need for dedicated attached devices or tags, influence by high image noise, complex object movements, and intensive com-putational requirements. We have developed earlier computationally efficient algorithms for global optical flow reconstruction of group velocities that provide means for convulsive seizure detection and have potential applications in fall and apnea detection. Here, we address the chal-lenge of using the same calculated group velocities for object tracking in parallel. Methods. We propose a novel optical flow-based method for object tracking. It utilizes real-time image se-quences from the camera and directly reconstructs global motion-group parameters of the con-tent. These parameters can steer a rectangular region of interest surrounding the moving object to follow the target. The method successfully applies to multi-spectral data, further improving its effectiveness. Results. Experimental results on simulated tests and complex real-world data demonstrate the method's capabilities. The proposed optical flow reconstruction can provide accurate, robust, and faster results compared to current state-of-the-art approaches.

High-resolution wave measurements at intermediate water depth are required to improve coastal impact modeling. Specifically, such data sets are desired to calibrate and validate models, and broaden the insight on the boundary conditions that force models. Here, we present a wave data set collected in the North Sea at three stations in intermediate water depth (6-14~m) during the 2021/2022 storm season as part of the RealDune/REFLEX experiments. Continuous measurements of synchronized surface elevation, velocity and pressure were recorded at 2-4~Hz by Acoustic Doppler Profilers and an Acoustic Doppler Velocimeter for a 5~month duration. Time series were quality-controlled, directional-frequency energy spectra were calculated, and common bulk parameters were derived. Measured wave conditions vary from calm to energetic with 0.1-5.0~m sea-swell wave height, 5-16~s mean wave period and W-NNW direction. Nine storms, i.e. wave height beyond 2.5~m for at least six hours, were recorded including the triple storms Dudley, Eunice and Franklin. This unique data set can be used to investigate wave transformation, wave nonlinearity and wave directionality for higher and lower frequencies (e.g. sea-swell and infragravity waves) to compare with theoretical and empirical descriptions. Furthermore, the data can serve to force, calibrate and validate models during storm conditions.

This study aimed to assess the enhancement of physical fitness and quality of life through an 8 weeks strength program training in male adolescents soccer players. A lower body muscle groups intervention was performed, with 17 players in the experimental group (EG) and 15 in the control group (CG). The EG carried out soccer training complemented by specific strength work. Pre and post- intervention assessments included body composition, jump height, speed with change of direction, maximum speed in 20 m, movement velocity in back-squat, perceived fatigue effort, academic performance and quality of life. A general linear repeated measures model analysis was used considering for each variable, the interaction between groups (CG, EG) and time (basal, final), to analyze the differences between and within groups. The results showed reduction of fat in the upper limbs and trunk EG, improvements in jump height, maximum speed of 20 m, changes of direction and quality of life increased (p<0.05) in the EG too. It was concluded that a strength program could improve some components of physical performance in male adolescents soccer players.

Antioxidants reduce arterial stiffness but the effects previously reported are weak. The present study evaluated the effects of 2 weeks of therapy with a combination of antioxidants (l-cysteine, thiamine, pyridoxine and ascorbic acid) compared to placebo on stiffness index (SI) a measure of arterial stiffness that is strongly correlated with central pulse wave velocity (PWV), using a Pulse Trace recorder in a diverse group of 78 volunteers. SI fell by 1.7 m/sec relative to placebo (95% confidence intervals 0.6 to 2.7 m/sec), a reduction of 19% (95% confidence intervals 9% to 31%). The Glass effect size was 1.4, indicating a very strong treatment effect which was substantially greater than found in previous studies of the effects of antioxidant therapy on arterial stiffness. The magnitude of reduction in SI was positively correlated with increasing age (r = 0.362 P = 0.02). The change in RI, a measure of compliance of small to medium size arteries, did not differ between the antioxidant and placebo groups The combination of antioxidants studied reduced PWV to a much greater extent than reported for other antioxidants. This combination may be of value in the treatment of cardiovascular disease.

The arranged paths of dominoes have many shapes. The scaling law for the propagation speed of domino toppling has been extensively investigated. However, in all previous investigations, the scaling law for the velocity of domino toppling motion in curved lines was not taken into account. In the present work, the finite-element analysis (FEA) program ABAQUS was used to study the velocity of domino toppling motion in curved lines. It is shown that the domino propagation speed has a rising trend with increasing domino spacing in a straight line. It is also found that domino propagation speed is linearly proportional to the square root of domino separation. This research proved that the scaling law for the speed of domino toppling motion given by Sun (2020) is true [B-H. Sun, 2020. Scaling law for the propagation speed of domino toppling. AIP Advances, 10(9),095124.]. Moreover, the shape of domino arrangement paths has no influence on the scaling law for the propagation speed of dominoes but can affect the coefficient of the scaling law for the velocity. Therefore, the amendatory function for the propagation speed of dominoes in curved lines was formulated by the FEA data. The fitted amendatory function, $\varphi_{revise}$, provides the simple method for a domino player to quickly estimate the propagation speed of dominoes in curved lines.

Full-waveform seismic data inversion has given rise to hope for the simultaneous and automated execution of tomography and imaging by solving a nonlinear least-squares optimization problem. As previously recognized, brute force minimization by classical methods is hopeless if the data lacks low temporal frequencies. The article developed a reliable numerical method for recovering smooth velocity using model space decomposition. We present realistic synthetic examples to test the presented algorithm.

The zero velocity update(ZUPT) algorithm is the core of a foot-mounted pedestrian navigation system. The zero velocity detection method is the premise and guarantee of the effective application of the ZUPT algorithm. To make ZUPT work properly, it is necessary to detect zero velocity intervals correctly. The detection accuracy of the existing zero velocity detection methods is easy to be affected by users and environment. A novel zero velocity detection method based on the plantar pressure is proposed in this paper, which has higher detection accuracy and better environmental adaptability. First, the paper analyzes the motion characteristics of foot during walking. Second, the inherent relationship between the plantar pressure and the gait change during walking is studied based on the pressure sensor. Then, the model of the zero velocity detection method using the plantar pressure is established. Finally, the indoor and outdoor multi-scene experiments show that this method not only has a high detection accuracy, but also has good adaptability to users and walking environment.

Ho Chi Minh City (HCMC), the most crowded city and economic hub of Viet Nam, has been experiencing land subsidence over the past decades. This effort aims to contribute the spatial distribution of subsidence in HCMC in its horizontal and vertical components using synthetic aperture radar interferometry (InSAR) time series. To this purpose, an advanced Persistent Scatterers and Distributed Scatterers (PSDS) InSAR technique was applied to two European Space Agency (ESA) Sentinel-1 datasets consisting of 96 ascending and 202 descending images, acquired from 2014 to 2020 over the HCMC area. A time series of 33 COSMO-SkyMed ascending images was also used for comparison. The combination of ascending and descending satellite passes is used to decompose the light of sight velocities into horizontal east-west and vertical components. Taking into account the presence of east-west horizontal motion, our findings indicate that the accuracy of the decomposed vertical velocity can be improved by up to 3 mm/year for Sentinel-1 data. The obtained results revealed that subsidence is most pronounced in the areas along the Sai Gon River, in the northwest-southeast axis, and in the southwest of the city, with a maximum value of 80 mm/yr, which is in accordance with the findings of the literature. The amplitude of east-west horizontal velocities is relatively small and large-scale eastward movement can be observed in the west of the city at a rate of 3-5 mm/yr. This confirmed that the displacement in Ho Chi Minh City area is mainly vertical downward. Together, these results reinforced the remarkable suitability of ESA's SAR Sentinel-1 for subsidence applications, even for non-European countries such as Vietnam and Southeast Asia.

Translational rockslides caused by toe excavation are one of the commonly seen geohazards in mountainous regions due to line traffic construction. Quantifying their failure extension length (FEL) and travel distance are of significant interest as well as huge challenges in landslide hazard assessment. In this paper, a simple criterion is proposed for predicting these two factors based on the principles of rigid body limit equilibrium and kinetic energy theorem. Further, the proposed criterion is validated against the field observations and numerical results with a practical case of the Xinjianan landslide, a medium-sized translational rockslide that occurred in 2013 in Nanchuan District, Chongqing. The findings indicate that a tiny discrepancy can be found in FEL between the field observations and the proposed criteria, while this discrepancy could be considerable in travel distance between different methods. However, the relative discrepancies all fall within 20%, deemed acceptable.

This study explores the dependence of drone acoustic detection systems performance on distance, using learning machines with different complexities, from simple linear discriminants, to deep neural networks, such as YAMNet, which exploits transfer learning. Other machine learning systems studied are the multilayer perceptron, support vector machines and random forest. These methods have been evaluated with a meticulously selected database that includes a wide variety of drone and interference sounds, previously processed by array signal processing and affected by ambient noise. Two strategies for training learning machines are considered. In the first one, they are trained with unattenuated signals, trying to preserve the information generated by the sound sources, but they are tested considering the attenuation with distance, achieving effective detection at distances up to 200 metres with some methods, especially linear discriminant. In all cases, the existence of interferences that hinder detection is considered. In the second strategy, the systems are trained and tested with attenuated signals as a function of distance. The effective detection range increases up to 300 metres for most methods and up to 500 metres for the YAMNet based detector. In addition, this second approach raises the possibility of developing specialised detectors for each distance range, thus significantly extending the effective detection range. These results underline the promising potential of acoustic detection of drones at various distances, encouraging further exploration in this research area.

Conceptual distance refers to the degree of proximity between two concepts within a conceptualization. It is closely linked with semantic similarity and relationship, but its computation relies entirely on the context of the given concepts. The DIS-C algorithm, which requires using search algorithms such as Breadth First Search, represents an advance in computing the semantic similarity/relation regardless of the type of knowledge structure and semantic relationships. The shortest path algorithm facilitates the determination of the semantic closeness between two indirectly connected concepts in an ontology by propagating local distances. This process is implemented for each concept pair to establish the most effective and efficient paths to connect these concepts. The algorithm identifies the shortest path between the concepts, allowing for the inference of the most relevant relationships between them. This approach contributes to developing a comprehensive understanding of the ontology and enhances the accuracy and precision of the semantic representation of the concepts. However, one of the critical issues is associated with the computational complexity due to the nature of the algorithm, which is errorn3. This paper studies alternatives to accelerate the DIS-C based on approximation and optimized algorithms, focusing on Dijkstra, pruned Dijkstra, and Sketched-based algorithms to compute conceptual distance. Based on the experiments, we discovered that the bottleneck can be avoided using the proposed 2-hop coverages, bringing DIS-C almost linearity.

This research uses the computing of conceptual distance to measure information content in Wikipedia categories. The proposed metric, generality, relates information content to conceptual distance by determining the ratio of information a concept provides to others compared to the information it receives. The DIS-C algorithm calculates generality values for each concept, considering each relationship's conceptual distance and distance weight. The findings of this study were compared to current methods in the field and found to be comparable to results obtained using the WordNet corpus. This method offers a new approach to measuring information content applied to any relationship or topology in conceptualization.

The need for continuous research to refine the models used in accident reconstruction appears with the development of new car models that satisfy consumer complaints. The paper analyzed a sub-sequence of car and pedestrian accidents, from the perspective of the distance traveled by them in the contact phase, with the aim of improving the information regarding the reconstruction of road accidents. The research included the analysis of some accidents with pedestrian dummies, as well as the simulation of the impact between different classes of vehicles and pedestrians in two different walking positions. Specialized software was used with complex multibody models of pedestrians, modifying the speed and deceleration parameters at the time of the collision. The research results highlight the differences between bilinear models used in accident reconstruction and the proposed study. They can also be used to determine the distance traveled by the vehicle in the first phase of the collision with pedestrians.

The process of Thermal spray is effective for creating a metal matrix composite (MMC) by embedding zirconium diboride reinforcement into a molybdenum matrix. This allows for the combination of beneficial properties in a new composite, as both materials have a high The materials Mo and ZrB2 possess different characteristics. For example, Mo has a melting point of 2622 ◦C while ZrB2 has a higher melting point of 3246 ◦C. Additionally, Mo has a high thermal conductivity of 139 W/m◦C compared to ZrB2's thermal conductivity of 24 W/m◦C. However, both materials have good thermal shock resistance, and Mo has a low coefficient of thermal expansion of 5.35 µm/m◦C while ZrB2 has a coefficient of thermal expansion of 5.8 × 10−6 K−1., as well as the ability to maintain strength at elevated temperatures and stability in extreme environments. The study focused on creating Mo/Zrb2 composites using a thermal spray coating technique, varying the parameters of spraying distance, number of passes, and gas pressure, and testing the resulting castings to evaluate their hardness and Young's Modulus. The primary objective of the research was to use the Taguchi technique for identifying the optimal parameters for generating the highest Young's Modulus and hardness for the castings. The Taguchi method integrates experimental and analytical principles to identify the most significant parameter affecting the response, which can significantly enhance overall performance. The study found that the optimal parameters were a spraying distance of 20 cm, gas pressure of 6 bar, and the number of passes of 18. The Taguchi method accurately predicted the parameters that produced the highest properties for the composite coatings, which demonstrated good surface formation without hot cracks and fewer pores, with well-formed metallurgical bonding between the coating and the substrate.

Distance learning has assumed a relevant role in the Educational scenario. The use of Virtual Learning Environments contributes to obtain a substantial amount of educational data. In this sense, the analyzed data generate knowledge used by institutions to assist managers and professors in strategic planning and teaching. The discovery of students’ behaviors enables a wide variety of intelligent services for assisting in the learning process. This article presents a literature review in order to identify the intelligent services applied in distance learning. The research covers the period from January 2010 to May 2021. The initial search found 1,316 articles, among which 51 were selected for further studies. Considering the selected articles, 33% (17/51) focus on learning systems, 35% (18/51) propose recommendation systems, 26% (13/51) approach predictive systems or models, and 6% (3/51) use assessment tools. This review allowed to observe that the principal services offered are recommendation systems and learning systems. In these services, the analysis of student profiles stands out to identify patterns of behavior, detect low performance and identify probabilities of dropouts from courses.

Accurate monthly runoff estimation is fundamental in water resources management, planning, and development, resulting in preventing and reducing water-related problems, such as flooding and drought. This article evaluates the performance of the monthly hydrological rainfall-runoff model, GR2M model, in Thailand's southern basins. The GR2M model requires only two parameters, and no prior research has been reported on its application in this region. The 37 runoff stations, which are distributively located in three sub-watersheds of Thailand's southern region, namely; Thale Sap Songkhla, Peninsular-East Coast, and Peninsular-West Coast, were selected as study cases. The available monthly hydrological data of runoff, rainfall, air temperature from the Royal Irrigation Department (RID) and the Thai Meteorological Department (TMD) were collected and analyzed. Thornthwaite method was utilized for the determination of evapotranspiration. The model's performance was conducted using three statistical indices: Nash-Sutcliffe Efficiency (NSE), Correlation Coefficient (r), and Overall Index (OPI). The model's calibration results for 37 runoff stations gave the average of NSE, r, and OPI of 0.637, 0.825, and 0.757, and those values for verification of 0.465, 0.750, and 0.639, respectively. It indicated a model's acceptable performance and could apply the GR2M model for determining monthly runoff variation in this region. The spatial distribution of X1 and X2 values was conducted by using IDW method. It was susceptible to the X1 value and X2 value of approximately more than 0.90 gave the higher model's performance.

In higher eukaryotes, enhancers determine the activation of developmental gene transcription in specific cell types and stages of embryogenesis. Enhancers transform the signals produced by various transcription factors within a given cell, activating the transcription of the targeted genes. Often, developmental genes can be associated with dozens of enhancers, some of which are located at large distances from the promoters that they regulate. Currently, the mechanisms that underly the specific distance interactions between enhancers and promoters remain unknown. This review describes the properties and activities of enhancers and discusses the mechanisms of distance interactions and potential proteins involved in this process.

The value of landscape, as part of collective heritage, can be acquired by GIS due to the multilayer approach of the spatial configuration. Proficiency in geospatial technologies in order to collect, process, analyze, interpret, visualize and communicate geographic information is being increased by undergraduate and graduate students, but in particular by those who are training to become geography teachers at secondary education. This training can be carried out through personalized learning and distance learning methodology. Personalized GIS education aims to integrate students and enhance their understanding of landscape. Some teaching experiences are shown whereby opportunities offered by WebGIS will be described, through quantitative tools and techniques that will allow this modality of learning and improve its effectiveness. Results of this research show that students, through geospatial technologies, learn landscape as a diversity of elements but also the complexity of physical and human factors involved. Several conclusions will be highlighted: i) the contribution of geospatial training to education for sustainable development; ii) spatial analysis as a mean of skills acquisition about measures for landscape conservation; iii) expanding and applying acquired knowledge to other geographic spaces and different landscapes.

Amidst escalating environmental concerns, short natural fiber thermoplastic (SNFT) biocomposites have emerged as sustainable materials for the eco-friendly production of mechanical components. However, their limited durability has prompted research into the experimental evaluation of the deterioration of the mechanical characteristics of SNFT biocomposites, particularly under the influence of ultraviolet rays. However, conducting tests to evaluate the mechanical properties can be time-consuming and expensive. In this study, an artificial neural network (ANN) model was employed to predict the mechanical properties (tensile strength) and the impact performance (resistance and absorbed energy) of polypropylene reinforced with 30 wt.% short flax or wood pine fibers (referred to as PP30-F or PP30-P, respectively). Eight parameters were collected from experimental studies. The ANN input parameters comprised nondestructive test results, including mass, hardness, roughness, and natural frequencies, while the output parameters were the tensile strength, the maximum impact load and absorbed energy. The model was developed using the ANN toolbox in MATLAB. The linear coefficient of correlation and mean squared error were selected as the metrics for evaluating the performance function and accuracy of the ANN model. They calculate the relationship and the average squared difference between the predicted and actual values. The data analysis conducted by the models demonstrated exceptional predictive capability, achieving an accuracy rate exceeding 96%, which was deemed satisfactory. For both the PP30-F and PP30-P biocomposites, the ANN predictions deviated from the experimental data by 3, 5, and 6% about the impact load, absorbed energy, and tensile strength, respectively.

This paper presents a robust method based on graph topology to find the topologically correct and consistent subset of inter-robot relative pose measurements for multi-robot map fusion. However, the absence of good prior gives a severe challenge to distinguish the inliers and outliers, and wrong loop closures can seriously corrupt the fused global map. Existing works mainly rely on the consistency of spatial dimension to select inter-robot measurements, which does not always hold. In this paper, we propose a fast inter-robot loop closure selection method that integrates the consistency and topology relationship of measurements, which both conform to the continuity characteristics of similar scenes and spatiotemporal consistency. The traditional high-dimensional consistency matrix is decomposed into the sub-matrix blocks corresponding to the overlapping trajectory area. Building on this logic, a clustering method involving topology correctness of inter-robot loop closures is introduced to split the entire measurement set into multiple clusters. We define the weight function to find the maximum cardinality subset with topologically correct and consistent, then convert the weight function to a maximum clique problem in the graph and solve it. We evaluate the performance of our method in a simulation and in a real-world experiment. Compared to state-of-the-art methods, the results show that our method can achieve competitive performance in accuracy while reducing computation time by 75%.

We have introduced a sign operator of energy, analogous to the operator helicity, but in the direction of what we call energy vector. However, this energy vector needs a time vector. To give physical senses to the components of such a time vector, we try to explain the time dilation in special relativity and try to relate the components of the time vector to the tunneling times when an electron crosses a potential barrier.

Engineering properties of bedrock materials at Badlands National Park were used to develop models for Park managers to assess slope erosion and stability for fossil resource protection. Six fully instrumented sites were used to document slope conditions. Bedrock consisted of Oligocene White River Group rocks. Bulk erosion rates correlated to grain size with silty-sandy materials producing higher mass erosion rates as a function of the silt-to-clay ratio and plastic index. Data indicated that as grain size decreased, plastic index increased leading to a decrease in erodibility. These parameters were used to construct a grain-size proxy, ψ, that was substituted for grain size, D, in Bagnold’s entrainment equation and provided significant improvement in calculation of critical entrainment velocities for fine-grained materials. Hydraulic analyses of slope and pediment surface processes indicated surface roughness was a controlling factor and materials washed from rough steep slopes were effectively transported across smooth low-angle pediments with slope-to-pediment angle ratios of nearly 6:1. Slope stability modeling of ten slopes produced high factors of safety for all slopes, even under saturated conditions and was attributable to clay cohesion. All results were used to construct models that predicted years until net slope erosion equaled 2.5 cm (1 inch). Using these results, Park managers were advised to visit erosion-prone sites on a 1 to 6 year schedule, based on site geology and slope aspect, to adequately protect critical fossil resources from destruction.

The present work is concerned with the study of the generalized Langevin equation and its link to the physical theories of statistical mechanics and scale relativity. It is demonstrated that the form of the coefficients of Langevin equation depend critically on the assumption of continuity of the reconstructed trajectory. This in turn demands for the fluctuations of the diffusion term to be discontinuous in time. This paper further investigates the connection between the scale-relativistic and stochastic mechanics approaches, respectively, with the study of the Burgers equation, which in this case appears as a stochastic geodesic equation. By further demanding time reversibility of the drift the Langevin equation can also describe equivalent quantum-mechanical systems in a path-wise manner. The resulting statistical description obeys the Fokker-Plank equation of the probability density of the differential system, which can be readily estimated from Monte Carlo simulations of the random paths. Based on the Fokker-Plank formalism a new derivation of the transient probability densities is presented. Finally, stochastic simulations are compared to the theoretical results.

This study investigates how Electronic Livestock Health Recording Systems (ELHRs) facilitates the detection of disease burden and make cluster analysis by applying data analytics tools and techniques. A sample size of 18333 livestock disease cases reported from 2007-2015 by the Ministry of Agriculture of the Federal Democratic of Ethiopia was used for data collection. The results showed that ELHRs are important as livestock disease data preservers, saving costs, and facilitating the extraction of up-to-date and complete information. Euclidean and Manhattan distance performed well at 98%, while cosine distance measurement metrics performed poorly. Finally, with the application of the selected clustering techniques, metrics, tools, and dataset, it has been attempted to successfully detect an optimal number of disease clusters and meet the objectives of the study.

Faba bean (Vicia faba L.) is a partially outcrossing species requiring an isolation distance to maintain genetic purity when more than one variety is grown in field conditions. This information is crucial for seed growers and faba bean breeders. A study was conducted at the University of Sydney’s Plant Breeding Institute, Narrabri over two years to examine the extent of natural outcrossing using a creamy white flower characteristic as a morphological marker, which is controlled by a single recessive gene. The white flowered genotype (IX225c) was grown in paired rows of 150 m length in four directions from a central 480 m2 plot of the normal flowered genotype PBA Warda. A beehive was placed in the central plot at flowering time and natural pollination was allowed. At maturity, seed samples were taken from the white flowered genotype at designated intervals along each axis and 100 seeds from each sample were grown in the glasshouse/birdcage to the 4-5 leaf stage and the proportion of plants displaying stipule spot pigmentation (normal flower colour and spotted stipule are linked) was used to determine the percentage of outcrossing. Maximum outcrossing of 2.28% occurred where both genotypes were grown side by side (0 m) and the degree of outcrossing decreased as the distance along each axis from the central plot increased. At 6 m distance the outcrossing was less than 1%, however on occasion it increased to 1% beyond a distance of 100 m, indicating the volatile and unpredictable nature of bee flights. Distance had the major effect on outcrossing, but direction and its interaction had no effect. The results suggest that to limit outcrossing to below 0.5%, a distance of more than 150 m between plots of different faba beans cultivars would be required. It also indicated that Australian faba bean genotypes are mostly self-fertile and a relatively narrow isolation distance will ensure self-fertilization in seed production and breeding programs.

Introduction: In the medical area, teaching is essential since it must offer the appropriate instruments to demonstrate that graduates have acquired the necessary skills. Objective: Evaluate the quality of research in residents of medical specialties after a standardized digital training program with rubrics. Methods: An observational, prospective research study in resident physicians of seven medical specialties first-year of an introductory program to methodology. It is integrated with the result variable through the quality of the final product and the quality variable will be measured with an ad hoc questionnaire validated by the Delphi method with a consistency level of 3-3. The data will be integrated into a base of the SPSS system and determined with the Chi-square test considering a minimum significance of 0.05. Results: 85 first-year medical residents (n=85) enrolled in the Research Seminar. The mean age was 31.34 years (± 3.96). About gender Male 38±31.13 Female 31.51±3.83. The global final grade was 80.61 (± 9.59) and the global sat-isfaction of the course was referred to as good by 62.2%. We observed a positive relationship between the scope of evaluation and the level of satisfaction. Conclusion: The research seminar implementation in a b-learning mode in response to the educational needs in medical residents for the field of health education showed a relationship between higher qualification, higher satisfaction, as well as determining that the comprehensive evaluation through the use of rubrics standardized allowed to delimit the deficiencies and strengths for timely feedback influencing the process of acquiring skills and the quality of the final product.

Here are given tight probabilistic inequalities that provide nearly best estimates for the Csiszar's f-divergence. These use the right and left psi -Hilfer fractional derivatives of the directing function f. Csiszar's f- divergence or the so called Csiszar's discrimination is used as a measure of dependence between two random variables which is a very essential aspect of stochastics, we apply our results there. The Csiszar's discrimination is the most important and general measure for the comparison between two probability measures. We give also other applications.

River valley bottoms have hydrological, geomorphological, and ecological importance and are buffers for protecting the river from upland nutrient loading coming from agriculture and other sources. They are relatively flat, low-lying areas of the terrain that are adjacent to the river and bound by increasing slopes at the transition to the uplands. These areas have under natural conditions, a groundwater table close to the soil surface. The objective of this paper is to present a stepwise GIS approach for the delineation of river valley bottom within drainage basins and use it to perform a national delineation. We developed a tool that applies a concept called cost distance accumulation with spatial data inputs consisting a river network and slope derived from a digital elevation model. We then used wetlands adjacent to rivers as a guide finding the river valley bottom boundary from the cost distance accumulation. We present results from our tool for the whole country of Denmark carrying out a validation within three selected areas. The results reveal that the tool visually performs well and delineates both confined and unconfined river valleys within the same drainage basin. We use the most common forms of wetlands (meadow and marsh) in Denmark's river valleys known as Groundwater Dependent Ecosystems (GDE) to validate our river valley bottom delineated areas. Our delineation picks about half to two-thirds of these GDE. However, we expected this since farmers have reclaimed Denmark's low-lying areas during the last 200 years before the first map of GDE was created. Our tool can be used as a management tool, since it can delineate an area that has been the focus of management actions to protect waterways from upland nutrient pollution.

As education becomes more and more important in creating improved societies, many people who do not have access to it are falling behind. To help them catch up, many people, especially those in rural areas and developing countries, are turning to different methods of self-learning, especially those that utilize cheap technology and use interactive methods to teach. Our empirical study tests the effectiveness of an e-learning system that utilizes newer, less tested forms of interactivity and could potentially be used in these areas as a self-learning system and compares it to non-interactive video and textbook self-learning in two different topics. The results of the experiment showed that the increased interactivity provided by the e-learning system achieved significantly better learning performance over both non-interactive video and textbook self-learning. It was also found that students who learned through non-interactive video performed significantly better than those who used textbooks for self-learning.

Starting from the analysis of the lack of positivity of the Cattaneo heat equation, the article addresses the thermodynamic relevance of the positivity constraint in irreversible thermodynamics, than is at least as important as the entropic constraints. The fulfillment of this condition in hyperbolic models leads to the parametrization of the concentration fields with respect to internal variables associated with the microscopic dynamics. Using Brownian motion theory as a landmarking example for deriving macroscopic transport equations from the equations of motion at the particle/molecular level, we discuss two typical problems involving hydrodynamic interactions at microscale: surface chemical reactions at a solid interface of a diffusing reactant, and mass-balance equations in a complex viscoelastic fluid, in which the physics of the interaction leads either to the overcome the parabolic diffusion model or to consider the parametrization of the concentration with respect to the degrees of freedom associated with the relaxation dynamics of the solvent fluid.

Numerical simulations of standard situations in the transition region from gas kinetics to fluid dynamics at small Mach numbers indicate a clear dependence of the simulation results on the underlying kinetic model (here: nonlinear and linearized Boltzmann collision operator vs. BGK relaxation model). We develop an improved mathematical framework (trace theory) to explain these differences. In particular we reveal certain deficiencies for the classical BKG system as well as for the standard Navier Stokes approach.

Mass transfer and phase transition have important effect on the velocity of bubble migration in deepwater wellbore, and accurate prediction of bubble migration velocity is crucial for calculating the safe shut-in period of deepwater oil and gas well. Therefore, the effect of bubble dissolution mass transfer and hydrate phase transition on bubble migration behavior in deepwater environment have attracted extensive attention from researchers in the fields of energy, marine chemistry, and marine engineering safety. In this work, a new model of bubble migration velocity in deepwater is developed, which considers the effect of hydrate phase transition and gas-water bidirectional cross-shell mass transfer during bubble migration. Based on the observation data of bubble migration in deepwater, the reliability of the model in predicting bubble migration velocity is verified. Then, the model is used to calculate and analyze the bubble migration velocity and bubble migration cycle under different initial bubble size, different annular fluid viscosity and density. The results show that the initial size of bubble and the viscosity of annulus fluid are the main factors affecting the migration velocity of bubble, but the density of annulus fluid has little effect on the migration velocity of hydrated bubble and clean bubble. In addition, the migration velocity of clean bubble gradually increases during the migration process from the bottom to the wellhead, while the migration velocity of hydrated bubble is divided into gradually decreasing stage and slowly increasing stage. The gas consumption and the thickening of hydrate shell in the gradually decreasing stage play a dominant role, and the increase of bubble volume caused by the decrease of pressure in the slowly increasing stage is the most important factor. The formation of hydrated bubble can significantly reduce the migration velocity of bubble and effectively prolong the safe shut-in period. This study provides a reference for quantitative description and characterization of complex bubble migration behavior with phase change and mass transfer in deepwater environment.

Wind loads have become one of the key influence factors for the running safety of vehicles and comfort of passengers. Investigation on the wind speed spectrum characteristics of a moving vehicle under turbulent crosswinds is of great influence. Expressions of the wind speed spectrum of a moving vehicle was obtained from the von Kármán spectrum based on Taylor’s frozen flow hypothesis. The influence factors, including the ratio of the vehicle speed to the wind speed and the wind yaw angle from 15° to 175°, were analyzed. The maximum value of the wind speed spectrum and the corresponding frequency were studied as well. The results show that the maximum values of the wind speed spectrum of the moving vehicle were larger than those of the static vehicle. The maximum value of the wind speed spectrum corresponding to the moving vehicle first increased and then decreased as the wind yaw angle increased. Some of the frequencies corresponding to the longitudinal wind speed spectrum values of the moving vehicles were smaller than those of the static vehicle. For moving vehicles, the frequency values corresponding to the maximum values of the longitudinal wind speed spectrum first increased and then decreased as the ratio of the vehicle speed to the wind speed and the wind yaw angle increased.

The effect of coal hydrophilic particles in water-glycerol drops on the maximum diameter of spreading along a hydrophobic solid surface is experimentally studied by analyzing the velocity of internal flows by Particle Image Velocimetry. The grinding fineness of coal particles was 45-80 μm and 120-140 μm, their concentration was 0.06 wt.% and 1 wt.%. The impact of particle-laden drops on a solid surface occurred at Weber numbers (We) from 30 to 120. It is revealed the interrelated influence of We and the concentration of coal particles on changes in the maximum absolute velocity of internal flows in a drop within the kinetic and spreading phases of the drop-wall impact. A physical model is formulated for internal convective flows in the longitudinal section of a drop parallel to the plane of the solid wall. The kinetic energy of translational motion of coal particles in a spreading drop compensates for the energy expended by the drop on sliding friction along the wall. At We=120, the inertia-driven spreading of the particle-laden drop is mainly determined by the dynamics of the deformable Taylor rim. An increase in We contributes to more noticeable differences in the convection velocities in spreading drops. When the drop spreading diameter rises at the maximum velocity of internal flows, a growth of the maximum spreading diameter occurs. The presence of coal particles causes a general tendency to reduce the drop spreading.

The aim of this study was to verify the effects of blood flow restriction on movement velocity and muscle activity during the back-squat exercise. Methods: Twenty-four university students participated in this study. In two randomized 72-hours apart sessions, participants performed a 4-set protocol consisting of 30-15-15-15 repetitions performed at 30% of their one-repetition maximum in the back-squat exercise. In both sessions, neuromuscular function was monitored by surface electromyography (EMG) and movement velocity (mean propulsive velocity [MPV], peak concentric velocity [Vmax] and the effort index [EI]). Blood flow restriction (BFR) was applied during exercise in one of the experimental sessions with 80% of full arterial occlusion pressure over lower limbs. Results: BFR condition showed higher (p&lt;0.05) EI, peak and rooted mean square normalized EMG in set 1 compared to set 2. Similar MPV and Vmax were observed at each set for both BFR and control conditions. No significant differences were observed between conditions at any set. Conclusions: BFR did not imply changes in neuromuscular performance during low-intensity resistance training, but it might induce greater intra-series velocity loss and less activation of the muscles involved.

The upper limb force-velocity relationship (FVR) is a crucial aspect of athletic performance, par-ticularly in para sports where upper limb movements play a leading role in activities such as wheelchair propulsion. Athletes’ mechanical capacities can be evaluated on the field or in lab conditions. However, no studies have indicated a relationship between ergometers and field FVR or performances. Understanding para-athletes’ upper limb FVR can provide important insights for developing effective training programs and improving athletic performance in wheelchair bas-ketball players. Twenty-three wheelchair basketball players (12 women and 11 men) from French national teams performed a battery of three tests consisting of a 20 m sprint (SP) with Inertial measurement units (IMU) on wheels, a horizontal upper limb push-offs on a frictionless sled with two Kistler force plates (HBP), and a crank ergometer sprints test (CES) derived from arm er-gometer sprints using Brachumera, Lode. For the SP test, the FVR was computed with an estimation of force from the acceleration, the rolling resistance, and an estimation of the air resistance. Correlations between each variable measured were computed via Pearson correlations in R, as-suming strong relationships for r=0.7-1.0, moderate when r=0.40-0.69, and weak relationship when r<0.1-0.39. Significant differences were assumed when p<0.05. Strong correlations were found between the results of three tests conducted. The correlation coefficient between maximal theo-retical force (F0) data ranged from 0.85 to 0.88 and that between maximal theoretical power (P0) data ranged from 0.87 to 0.94. However, for maximal theoretical velocity (V0) data, the correlations between the three tests were less important. The performance variables showed a strong corre-lation with power measured on the HBP test without load. There is a significant relationship between HBP, CES, and SP variables. There is a correlation between performances on the three tests in our population, especially for the power. However, the V0 value of HBP was not representative of any performances. This work can show multiple protocols to assess para-athletes’ performances and show that upper limb symmetry depends on the gesture of the task and personal sports’ wheelchairs.

Lyme disease is a growing public health problem in Québec. Its emergence over the last decade is caused by environmental and anthropological factors that favour the survival of Ixodes scapularis, the vector of Lyme disease transmission. The objective of this study was to estimate the speed and direction of Lyme disease emergence in Québec and to identify spatiotemporal risk patterns. A surface trend analysis was conducted to estimate the speed and direction of its emergence based upon the first detected case of Lyme disease in each municipality in Québec since 2004. A cluster analysis was also conducted to identify at-risk regions across space and time. These analyses were reproduced for the date of disease onset and date of notification for each case of Lyme disease. It was estimated that Lyme disease is spreading northward in Québec at a speed varying between 18 and 32 km/year according to the date of notification and the date of disease onset, respectively. A high rate of disease risk was found in seven clusters identified in the south-west of Québec in the sociosanitary regions of Montérégie and Estrie. The results obtained in this study improve our understanding of the spatiotemporal patterns of Lyme disease in Québec, which can be used for proactive, targeted interventions by public and clinical health authorities.