Miracle-dz/UniFAR-FTUs huggingface dataset:
The constitutive relation for the granular flow of rough particles, and its application to the flow down an inclined plane

A perturbation expansion of the Boltzmann equation is used to derive constitutive relations for the granular flow of rough spheres in the limit where the energy dissipation in a collision is small compared to the energy of a particle. In the collision model, the post-collisional relative normal velocity at the point of contact is $-e_n$ times the pre-collisional normal velocity, and the post-collisional relative tangential velocity at the point of contact is $-e_t$ times the pre-collisional relative tangential velocity. A perturbation expansion is employed in the limit $(1 - e_n)\,{=}\,\varepsilon^2 \ll 1$, and $(1 - e_t^2) \propto \varepsilon^2 \ll 1$, so that $e_t$ is close to $\pm 1$. In the ‘rough’ particle model, the normal coefficient of restitution $e_n$ is close to 1, and the tangential coefficient of restitution $e_t$ is close to 1. In the ‘partially rough’ particle model, the normal coefficient of restitution $e_n$ is close to 1; and the tangential coefficient of restitution $e_t$ is close to $-1$ if the angle between the relative velocity vector and the line joining the centres of the particles is greater than the ‘roughness angle’ (chosen to be $(\upi/4)$ in the present calculation), and is close to 1 if the angle between the relative velocity vector and the line joining the centres is less than the roughness angle. The conserved variables in this case are mass and momentum; energy is not a conserved variable in the ‘adiabatic limit’ considered here, when the length scale is large compared to the ‘conduction length’. The results for the constitutive relations show that in the Navier–Stokes approximation, the form of the constitutive relation is identical to that for smooth particles, but the coefficient of shear viscosity for rough particles is 10%–50% higher than that for smooth particles. The coefficient of bulk viscosity, which is zero in the dilute limit for smooth particles, is found to be non-zero for rough and partially rough particles, owing to the transport of energy between the translational and rotational modes. In the Burnett approximation, there is an antisymmetric component in the stress tensor for rough and partially rough particles, which is not present for smooth particles. The constitutive relations are used to analyse the ‘core region’ of a steady granular flow down an inclined plane, where there is a local balance between the production of energy due to the mean shear and the dissipation due to inelastic collisions. It is found that realistic results, such as the decrease in density upon increase in the angle of inclination near close packing, are obtained for the rough and partially rough particle models when the Burnett coefficients are included in the stress tensor, but realistic results are not obtained using the constitutive relations for smooth particles. This shows that the flow dynamics is sensitive to the numerical values of the viscometric coefficients, and provides an indication of the minimal model required to capture the flow dynamics.
Experiences of lower limb prosthesis users in Kenya: a qualitative study to understand motivation to use and satisfaction with prosthetic outcomes

Abstract Purpose To explore the personal and system factors that motivate and enhance outcomes for patients accessing a prosthetic service and using a lower-limb prosthesis within a low resource setting. Materials and methods This study employed a qualitative approach to explore the motivations and satisfaction of individuals with lower limb loss engaging with a prosthetic service in Mombasa, Kenya. In-depth interviews were conducted over Microsoft Teams with 10 lower limb prosthesis users and thematic analysis was applied. Results Five key themes emerged: acceptance, self-determination, hope, clinician relationship and perception. These findings demonstrate the importance of hopeful thinking and a supportive community in overcoming physical and stigmatising challenges. The findings further highlight the value of the service provider relationship beyond just prescribing an assistive device. Conclusion These results have relevance in developing patient-centred services, assistive devices and personnel training that are responsive, motivating, and cognisant of the service user. This is of particular interest as assistive technology services are newly developed in low resource settings. IMPLICATIONS FOR REHABILITATION This research provides an understanding of lower-limb prosthesis users’ satisfaction of a device and motivation for engaging with a prosthetic service within a low resource setting. The relationship the rehabilitation professional has with the service user plays a significant role in facilitating motivation during rehabilitation. Rehabilitation professionals should consider how they can foster a network of support amongst service users when planning services in remote, rural locations. Rehabilitation professionals should be aware of how hopeful thinking can be facilitated during rehabilitation to support motivation. When reviewing the success of services, or designing new service models, the service users should be consulted on what they would deem as a successful outcome.
Evaluation of Peak Ground Velocity as a “Good” Intensity Measure for Near-Source Ground Motions

This paper investigates the “goodness” of peak ground velocity as a dependable intensity measure for the earthquake shaking of civil structures. The paper stresses the importance of distinguishing between acceleration pulses and velocity pulses, and identifies two classes of near-source ground motions: those where the peak ground velocity is the integral of a distinguishable acceleration pulse and those where the peak ground velocity is the result of a succession of high-frequency, one-sided acceleration spikes. It is shown that the shaking induced by the former class is in general much more violent than the shaking induced by the latter class of motions even when motions that belong to the former class may be generated by significantly smaller-magnitude earthquakes. Building on the dimensional analysis introduced in the companion papers this paper shows that both linear and nonlinear structural responses from a variety of records which exhibit distinguishable pulses scale better with the peak pulse accel.
The Effect of Target-Country Institutions on Cross-Border Merger and Acquisition Activity: A Quantitative Literature Survey

DOI: 10.2478/erfin-2022-0001 © 2022 The Author(s). Licensed under the Creative Commons Attribution 4.0 International License. ABSTRACT: In this paper, we synthesize and compare 2,961 estimates extracted from 90 papers on the effect of target-country institutions on crossborder merger and acquisition (CBMA) intensity and premia. The synthesis results show statistically significant effects of institutional quality, cultural similarity, corruption control, and political stability and effectiveness on CBMA activity, although the economic significance of these effects is modest. Study characteristics such as the choice of target and acquiring countries, estimation techniques, and sample selection strongly influence the effect estimates. Moreover, we examine the literature for the possible influence of publicationselection bias on the estimated effects and conclude that the presence of such bias calls into question whether the literature reports the true effects of institutions on CBMA activity. The results presented in our quantitative literature review suggest further research efforts to identify the true effect size.
S0033291722001696jra 1..11

Background. Cognitive training (CT) and aerobic exercise both show promising moderate impact on cognition and everyday functioning in schizophrenia. Aerobic exercise is hypothesized to increase brain-derived neurotrophic factor (BDNF) and thereby synaptic plasticity, leading to increased learning capacity. Systematic CT should take advantage of increased learning capacity and be more effective when combined with aerobic exercise. Methods. We examined the impact of a 6-month program of cognitive training & exercise (CT&E) compared to cognitive training alone (CT) in 47 first-episode schizophrenia outpatients. All participants were provided the same Posit Science computerized CT, 4 h/week, using BrainHQ and SocialVille programs. The CT&E group also participated in total body circuit training exercises to enhance aerobic conditioning. Clinic and home-based exercise were combined for a target of 150 min per week. Results. The MATRICS Consensus Cognitive Battery Overall Composite improved significantly more with CT&E than with CT alone ( p = 0.04), particularly in the first 3 months (6.5 v. 2.2 T-score points, p < 0.02). Work/school functioning improved substantially more with CT&E than with CT alone by 6 months ( p < 0.001). BDNF gain tended to predict the amount of cognitive gain but did not reach significance. The cognitive gain by 3 months predicted the amount of work/school functioning improvement at 6 months. The amount of exercise completed was strongly associated with the degree of cognitive and work/school functioning improvement. Conclusions. Aerobic exercise significantly enhances the impact of CT on cognition and functional outcome in first-episode schizophrenia, apparently driven by the amount of exercise completed.
Slow Compressible Flow past a Circular Cylinder

The low Reynolds number flow of a gas past an infinite heated circular cylinder is studied for the case of variable property flow when the temperature difference between the cylinder and free stream is small. The perturbation to the corresponding incompressible velocity field is calculated by the method of matched asymptotic expansions developed by Kaplun, and Proudman and Pearson. When the temperature difference between the cylinder and free stream is appreciable, a solution for the velocity field is found on the assumption that the viscosity and thermal conductivity of the gas are invariant. This solution possesses the interesting property that the zero‐order solution for the velocity field near the cylinder is a uniformly valid solution of the problem.
Effect of Chemotherapy on the Gut Microbiome of Breast Cancer Patients During the First Year of Treatment

Introduction: There is accumulating information of the effects of chemotherapy and weight changes on the gut microbiome of breast cancer patients. Methods: In this 1-year follow-up study, we investigated gut microbiome of 33 breast cancer patients who donated fecal samples at baseline and after completion of treatment. We compared alpha diversity and mean taxa abundance at baseline and absolute taxa abundance changes (final-baseline) by treatment (16 neoadjuvant [neoADJ], 13 adjuvant [ADJ], 4 no chemotherapy [noC]) and specific chemotherapy agent using Wilcoxon rank sum and negative binomial mixed model (NBMM) analysis. Results: All four gut alpha diversity measures changed in association with chemotherapy treatment; they increased in the neoADJ (+16.4% OTU p = 0.03; +51.6% Chao1 p = 0.03; +7.0% Shannon index p = 0.02; +11.0% PD whole tree p = 0.09) but not in the ADJ and noC group (ADJ+noC). The difference in Chao1 index change between groups was statistically significant (p neoADJ vs. ADJ+noC =0.04). Wilcoxon p values of 0.03–0.003 were observed for five taxa. In NBMM analysis, changes in taxa abundance differed (Bonferroni-adjusted p ≤ 0.0007) for two Bacteroidetes taxa ( g_Alistipes , f _S24-7 ) and two Firmicutes taxa (g_Catenibacterium, g_Eubacterium ). NBMM analysis results remained unchanged with adjustment for weight changes. Alpha diversity changes were also found by receipt of chemotherapy agents. Consistent increases in alpha diversity were observed among those treated with TCHP (OTU p = 0.009; Chao1 p = 0.02; Shannon p = 0.02; PD whole tree p = 0.05) but not AC, Taxol or Herceptin. Those treated with TCHP or Herceptin showed increases in Verrucomicrobia (g_Akkermansia) but decreases of Bacteroidetes(g _ Alistipes ); the differences in changes in taxa abundance were statistically significant. Conclusion: Results from this pilot longitudinal study support an effect of chemotherapy, particularly neoADJ on the gut microbiome of breast cancer patients even after adjustment for weight changes. Further investigations are needed to confirm these findings in larger studies and with longer follow-up and to assess the impact of these microbiome changes on patient outcome.
How Do Stock Indices Respond to Market Shocks? Examining Stock Market Contagion in European Countries with Minimum Spanning Trees

: This paper analyses the structural changes of the European stock markets by using a minimum spanning tree graph. The aim was to point out similarities and differences of the previous recessions, namely the Subprime crisis around 2008, the European sovereign debt crisis of the 2010s and the recent COVID-19 period. Focusing on the structural changes of the graph, we were looking for the emergence of shock-propagating hub. During each of the three examined recession periods, we could see a constant change in the stock market network, where stock market indices are connected mainly through one central index during turbulent times, while the connections became more diverse in calm periods.
Order does matter: recency effects in tourist satisfaction after multi-destination trips

ABSTRACT Whereas the drivers of tourist satisfaction with a destination have been largely studied, we know little about whether the serial order of the destination in multi-destination trips plays a role in explaining satisfaction. Based on a large longitudinal data set and using ordered probit models, we show that tourists are systematically highly satisfied with those destinations visited later within a multi-destination trip. This finding is conditional on a large set of controls and individual random effects. Interestingly, length of stay at each destination, age and travel party size are found to be significant mediators of the relationship between the serial order of the trip and satisfaction, partially counterbalancing recall bias. The results provide evidence of recency effects in tourist satisfaction recall and have important implications for the interpretation of tourist satisfaction studies.
Large-scale fluctuations in the interplanetary medium

Power spectra of measurements of the magnetic field strength in the heliosphere obtained by Voyager 1 between 1 AU and 9 AU have the form of a power law ƒ−a from periods of several hours to at least 6 days. The exponent was a = 2.0 ±0.05 for all of the spectra considered, which is the exponent for a series of steps and for Burgers' turbulence. Spectra of large-scale speed fluctuations also have the form ƒ−b from a period of a few hours to periods greater than 13 days in the region from 1 AU to 8.9 AU. The exponent b is generally somewhat larger than b = 2, implying some “persistence” of the speed fluctuations. The low-frequency cutoff (outer cutoff) of the power law increases from a period of 6.5 days at 1 AU to 26 days at (6.1–8.9) AU, which can be attributed to (1) the coalescence of interaction regions and (2) a transfer of energy from the spectrum of large-scale speed fluctuations. The outer cutoff of the spectrum of speed fluctuations increases from a period of 13 days at 1 AU to 26 days between a few AU and 8.9 AU. Both the magnetic field strength fluctuations and the speed fluctuations have fractal behavior, suggesting that they are self affine rather than dominated by a few large discontinuities.
Relativism and Monadic Truth

1. Overview: Simplicity, Possible Worlds Semantics and Relativism 2. Diagnostics for Shared Content: From 'Say' to 'Agree' 3. Operators, the Anaphoric 'That' and Temporally Neutral Propositions 4. Predicates of Personal Taste Bibliography
Lubricant reflow after laser heating in heat assisted magnetic recording

In heat assisted magnetic recording (HAMR) technology for hard disk drives, the media will be heated to about 500 °C during the writing process in order to reduce its magnetic coercivity and thus allow data writing with the magnetic head transducers. The traditional lubricants such as Z-dol and Z-tetraol may not be able to perform in such harsh heating conditions due to evaporation, decomposition and thermal depletion. However, some of the lubricant depletion can be recovered due to reflow after a period of time, which can help to reduce the chance of head disk interface failure. In this study, experiments of lubricant thermal depletion and reflow were performed using a HAMR test stage for a Z-tetraol type lubricant. Various lubricant depletion profiles were generated using different laser heating conditions. The lubricant reflow process after thermal depletion was monitored by use of an optical surface analyzer. In addition, a continuum based lubrication model was developed to simulate the lubricant refl.
Analysing the effect of different aggregation approaches on remotely sensed data

The effect of spatial aggregation varies depending on the aggregation logic. This study examined and compared the effect of both categorical and numerical aggregation. Categorical aggregation focused on the majority rule-based (MRB), random rule-based (RRB), and point-centred distance-weighted moving window (PDW). Both RRB and PDW have a stochastic component. Numerical aggregation focused on mean aggregation and central pixel resampling (CPR). The change in class proportions and landscape metrics with respect to a fine-resolution base image were assessed. RRB, PDW, and CPR preserved class proportion with decreasing spatial resolution. MRB increased the proportion of the dominant class and decreased all other class proportions, whereas mean aggregation increased the proportion of non-dominant class. All approaches led to a less clumped pattern for each class, except MRB, which made the dominant class more clumped. For all classes, RRB, PDW, and CPR led to a lower distortion in shape complexity than MRB and mean aggregation. RRB responded similarly for all realizations, but variability in PDW could be minimized by choosing a specific parameter value. The study showed that RRB, PDW, and CPR can be used in, for example, studies on ecological resource management where consistency of the class proportions at coarser resolutions is required, and that PDW is the best option. MRB can be used in regional-level as well as national-level agriculture or forest planning, where the delineation of the dominant class is required.
Assimilation of along‐track altimeter data in the tropical Pacific region of a global OGCM ensemble

Identical‐twin experiments are performed with an ocean general‐circulation model ensemble to investigate the potential for correction of subsurface ocean model states through assimilation of altimetric sea level observations with the Ensemble Kalman Filter (EnKF). The EnKF provides a convenient extension to existing ensemble prediction systems. Observations are simulated for the tropical Pacific by sampling a truth run at 10‐day intervals at the TOPEX/POSEIDON along‐track measurement points and adding realistic instrument and orbit errors. Ensemble spread is generated by perturbing the best‐guess forcing fields. The perturbations are based on a multivariate EOF decomposition of differences between two reanalysis products. The effectiveness of the assimilation is investigated by comparison of the forecasts and analyses with a control run and with the truth. Time series of subsurface state variables along the equator show that the analyses are closer to the truth than the control in all cases, indicating a significant potential for improved ENSO forecast initialization. A second assimilation run with an Ensemble Square‐Root Filter (ESRF) shows that the analyses are very similar to those from the EnKF. However, ensemble spread in the subsurface state variables is found to be a poor proxy for the true analysis error in this experiment, in particular in the case of the ESRF. While the sea level analyses remain close to the truth, persistent offsets are introduced in the subsurface state, suggesting a role for bias correction schemes in ensemble methods. Copyright © 2005 Royal Meteorological Society
Radio Resource Management for Cellular-Connected UAV: A Learning Approach

Integrating unmanned aerial vehicles (UAVs) into existing cellular networks encounters lots of challenges, among which one of the most striking concerns is how to achieve harmonious coexistence of aerial transceivers, inter alia, UAVs, and terrestrial user equipments (UEs). In this paper, a cellular-connected UAV network is focused, where multiple UAVs receive messages from base stations (BSs) in the down-link, while BSs are serving ground UEs in their cells. For effectively managing inter-cell interferences (ICIs) among UEs due to intense reuse of time-frequency resource block (RB) resource, a first $p$ -tier based RB coordination criterion is proposed and adopted. Then, to enhance wireless transmission quality for UAVs while protecting terrestrial UEs from being interfered by ground-to-air (G2A) transmissions, a radio resource management (RRM) problem of joint dynamic RB coordination and time-varying beamforming design minimizing UAV’s ergodic outage duration (EOD) is investigated. To cope with conventional optimization techniques’ inefficiency in solving the formulated RRM problem, a deep reinforcement learning (DRL)-aided solution is initiated, where deep double duelling Q network (D3QN) and twin delayed deep deterministic policy gradient (TD3) are invoked to deal with RB coordination in discrete action domain and beamforming design in continuous action regime, respectively. The hybrid D3QN-TD3 solution is trained via interacting with the considered outer and inner environments in an online centralized manner so that it can then help achieve the suboptimal EOD minimization performance during its offline decentralized exploitation. Simulation results have illustrated the effectiveness of the proposed hybrid D3QN-TD3 algorithm, compared to several representative baselines.
Performance Evaluation of Apache Spark MLlib Algorithms on an Intrusion Detection Dataset

The increase in the use of the Internet and web services and the advent of the fifth generation of cellular network technology (5G) along with ever-growing Internet of Things (IoT) data traffic will grow global internet usage. To ensure the security of future networks, machine learning-based intrusion detection and prevention systems (IDPS) must be implemented to detect new attacks, and big data parallel processing tools can be used to handle a huge collection of training data in these systems. In this paper Apache Spark, a general-purpose and fast cluster computing platform is used for processing and training a large volume of network traffic feature data. In this work, the most important features of the CSE-CIC-IDS2018 dataset are used for constructing machine learning models and then the most popular machine learning approaches, namely Logistic Regression, Support Vector Machine (SVM), three different Decision Tree Classifiers, and Naive Bayes algorithm are used to train the model using up to eight number of worker nodes. Our Spark cluster contains seven machines acting as worker nodes and one machine is configured as both a master and a worker. We use the CSE-CIC-IDS2018 dataset to evaluate the overall performance of these algorithms on Botnet attacks and distributed hyperparameter tuning is used to find the best single decision tree parameters. We have achieved up to 100% accuracy using selected features by the learning method in our experiments