Miracle-dz/UniFAR-FTUs huggingface dataset:
PolyBench/Python: benchmarking Python environments with polyhedral optimizations

Python has become one of the most used and taught languages nowadays. Its expressiveness, cross-compatibility and ease of use have made it popular in areas as diverse as finance, bioinformatics or machine learning. However, Python programs are often significantly slower to execute than an equivalent native C implementation, especially for computation-intensive numerical kernels. This work presents PolyBench/Python, implementing the 30 kernels in PolyBench/C, one of the standard benchmark suites for polyhedral optimization, in Python. In addition to the benchmark kernels, a functional wrapper including mechanisms for performance measurement, testing, and execution configuration has been developed. The framework includes support for different ways to translate C-array codes into Python, offering insight into the tradeoffs of Python lists and NumPy arrays. The benchmark performance is thoroughly evaluated on different Python interpreters, and compared against its PolyBench/C counterpart to highlight the profitability (or lack thereof) of using Python for regular numerical codes.
Development of the routine duration in artistic gymnastics from 1997 to 2019

ABSTRACT In this study, the development of routine duration (RD) in artistic gymnastics was investigated. Because of fundamental rule changes in 2006, the difference between the periods 1997–2005 and 2006–2019 and between the Olympic cycles (OC) over the entire period was examined. Therefore, 1387 routines were evaluated using video recordings. The results were: I) RD increased from 1997–2005 to 2006–2019 on pommel horse (36.0 to 44.0 s; p = 0.00), still rings (SR) (42.0 to 53.0 s; p = 0.00), parallel bars (PB) (35.0 to 50.0 s; p = 0.00), high bar (37.0 to 50.0 s; p = 0.00), uneven bars (UB) (32.5 to 36.0 s; p = 0.00), balance beam (83.0 to 85.0 s; p = 0.08) and floor female (87.0 to 89.0 s; p = 0.00), whereas floor male (67.0 vs. 67.0 s; p = 0.96) shows no differences; II) RD increase on SR from OC 2008 to OC 2012 (p = 0.00), at PB from OC 2012 to OC 2016 (p = 0.00), and reduced from OC 2012 to OC 2016 (p = 0.00) at UB. The increase of RD must be considered by coaches in order to prepare their athletes specifically for competitions.
Causality between Actual and Expected Inflation in Central and Eastern Europe: Evidence Using a Heterogeneous Panel Analysis

ABSTRACT This study applies a panel Granger non-causality test to explore the causal relationships between actual and expected inflation in Czechia, Hungary, Latvia, Lithuania, Poland, and Romania. The empirical results for these Central and Eastern European (CEE) countries show significantly positive causalities running from actual to expected inflation. However, the effect of actual inflation on inflation expectation weakens in Hungary and Romania following a financial crisis, and causality is no longer significant for Czechia, Latvia, Lithuania, and Poland. Domestic policies remain important for the management of actual and expected inflation, regardless of the monetary policy regime adopted.
Empirical Regularities in the Growth of Government

Abstract Meltzer and Richard (1983) test a model developed earlier (1981) of the size of government using a Stone-Geary utility function and annual data for the United States. They find that the ratio of government spending for redistribution to aggregate income, and the share of aggregate income redistributed in cash, rise and fall with the ratio of mean to median income and the level of (median) income. Redistribution in kind--the provision of education, health care, fire protection, and other services--also rises and falls with the ratio of mean to median income, but it appears to be independent of the level of income. In this paper a model is tested which is more comprehensive than that developed by Meltzer and Richard in the sense that it incorporates exogenous factors such as the fraction of the population that is under 18 years of age and that which is 65 years of age and over, the total population itself, the degree of homogeneity in the population, and most importantly, the use of per capita income in place of the level of median income to test “Wagner's (1958) law”. Time-series data for the United States and for Canada as well as cross-section data for the United States and for OECD countries are used. The replication of the tests of Meltzer and Richard's model using more recent data for the United States and for Canada indicates that while it may be theoretically sound the data do not seem to be consistent with their rational theory of the size of government. Since the coefficient estimates of the variables normally used in the public finance literature are volatile in terms of sign and magnitude, their interpretation is difficult and thus this study confirms the necessity of the development of a sound theory of the size and growth of government as a prerequisite for the robustness of regression results.
The Effect of Eight Weeks of Sling-Based Training with Rotational Core Exercises on Ball Velocity in Female Team Handball Players

Abstract The purpose of this study was to investigate whether sling-based training focused on rotational exercises would improve shooting performance in outfield handball players during the competitive season, and whether changes in performance were related to altered levels of core strength and rotational velocity. Twenty-five female outfield handball players (mean age 19.5 ± 2.0 years, height 1.72 ± 0.06 m, body mass 71.5 ± 8.6 kg, training experience 10.3 ± 2.4 years), performed 7 m shots, with and without a run-up, and jump shots. Maximal ball velocity, peak rotational velocity of the trunk with different loads and 1RM in a core strength test were measured before and after an 8-week training intervention. Players were divided into a sling-based and a plyometric/sprint training (control) group that trained three times per week for 8 weeks. The main findings were that sling-based training increased ball velocity by on average 3.2% across three techniques tested, while shooting performance decreased by 3% in the control group. However, both training groups demonstrated increased peak rotational velocity with different loads, but not the calculated 1RM core strength after the training period. It was concluded that sling-based training with rotational core exercises could improve maximal ball velocity in female handball players during a competitive season by around 3%. However, this increased ball velocity may have been caused by increased angular velocity in the core, rather than absolute maximal core strength. It is suggested that sling-based training has impacted timing variables of the different involved segments, or possibly power transfer between segments, which may explain the enhancement in ball velocity.
The Relationship Between the Perceived Movement Quality and the Kinematic Pattern of Complex Skills in Gymnastics

Abstract The study aimed to investigate the relationship between the perceived movement quality of a gymnastics skill and its kinematic pattern, as well as the influence of expertise. Thirty participants with different levels of gymnastics expertise (n = 10 visual experts, n = 10 motor experts and n = 10 novices) were recruited for the study. They were instructed to compare the movement quality of eleven video sequences, showing different handstand - back handspring performances. To extract the kinematics, the performances were digitized. By means of an ongoing cluster analysis, the kinematic pattern as well as the pattern of the perceived movement quality of the skills were determined for each experimental group. The results of the cluster analysis of the different experimental groups were analyzed and compared. Expertise differences were found regarding the pattern of the perceived movement quality. There was a significant correlation between the dendrograms of the visual experts and the motor experts (p = .021), as well as between the dendrograms of the visual experts and the novices (p = .011). There was no significant correlation between the dendrograms of the motor experts and the novices (p = .173). The pattern of the perceived movement quality was not correlated with the holistic kinematic pattern of judged skills (p > .143). These results suggest perceptual and cognitive differences of the participants due to their different previous visual and motor experience.
A New Foot-Mounted Inertial Measurement System in Soccer: Reliability and Comparison to Global Positioning Systems for Velocity Measurements During Team Sport Actions

Abstract The aims of this study were to i) compare a foot-mounted inertial system (PlayerMaker™) to three commercially available Global Positioning Systems (GPS) for measurement of velocity-based metrics during team sport movements and ii) evaluate the inter-unit reliability of the PlayerMaker™. Twelve soccer players completed a soccer simulation, whilst wearing a PlayerMaker™ and three GPS (GPS#1, #2 and #3). A sub-sample (n = 7) also wore two PlayerMaker™ systems concurrently. The PlayerMaker™ measured higher (p < 0.05) total distance (518 ± 15 m) compared to GPS#1 (488 ± 15 m), GPS#2 (486 ± 15 m), and GPS#3 (501 ± 14 m). This was explained by greater (p < 0.05) distances in the 1.5-3.5 m/s zone (356 ± 24 m vs. 326 ± 26 m vs. 324 ± 18 m vs. 335 ± 24 m) and the 3.51-5.5 m/s zone (64 ± 18 m vs. 35 ± 5 vs. 43 ± 8 m vs. 41 ± 8 m) between the PlayerMaker™, GPS#1, GPS#2 and GPS#3, respectively. The PlayerMaker™ recorded higher (p < 0.05) distances while changing speed. There were no systematic differences (p > 0.05) between the two PlayerMaker™ systems. The PlayerMaker™ is reliable and records higher velocity and distances compared to GPS.
Effects of Plyometric Vs. Combined Plyometric Training on Vertical Jump Biomechanics in Female Basketball Players

Abstract The purpose of this study was to assess and compare the effects of plyometric training and combined training programs on vertical jump kinematics and kinetics of female basketball players. Thirty-six female basketball players were included in the study and further divided into three groups: plyometric training, n = 11; combined training n =13; and a control group, n =12. Combined training comprised full squat exercise with low resistance (50-65% 1RM) and low volume (3-6 repetitions/set) combined with repeated jumps. Plyometric training included drop jumps and repeated jumps. Both training methods showed a moderate increase in jump performance, although combined training achieved substantially higher values than plyometric training alone. After plyometric training, the vertical velocity and displacement of the center of mass of the countermovement jump increased, while force variables decreased. Combined training increased power, vertical velocity and displacement of the center of mass, but force variables remained unchanged. Both training methods improved jump height, velocity and displacement of the center of mass. Combined training maintained force measures while plyometric training decreased them. These results indicate that combined training might provide better outcomes on jump performance than plyometric training alone. It also appears important to measure biomechanical variables to appropriately interpret the effects of different training methods.
On the semiclassical calculation of molecular absorption and fluorescence spectra

A semiclassical expansion is developed for the direct calculation of molecular electronic (absorption and fluorescence) spectra without having to calculate the molecular vibrational eigenstates. The expansion is based on expressing the necessary dipole correlation functions (which do not have a straightforward classical analog) in terms of a hierarchy of other intramolecular correlation functions which do have a simple semiclassical expansion. To lowest order in h/ the spectra may be calculated by running classical trajectories on a zero‐order Hamiltonian Hc. The present semiclassical expansion is not unique and depends on our choice of Hc. This arises since the spectra are not analytic functions of h/. Applications are made to the absorption and to the fluorescence spectra of polyatomic molecules (single‐ and two‐photon processes). The present method may be easily generalized to other multiphoton processes.
Synthesis and Characterization of Thermoset Biodegradable Elastomers Based on Star-Poly(ε-caprolactone-co-d,l-lactide)

Biodegradable elastomers represent a useful class of biomaterials. In this paper, we synthesize thermoset elastomers by utilizing the living nature of ring-opening polymerization of a star copolymer of d,l-lactide and e-caprolactone initiated with glycerol and catalyzed by stannous 2-ethylhexanoate. The star copolymers were synthesized of varying molecular weight and monomer composition and cross-linked by compression molding using a dilactone, bis(e-caprolactone-4-yl)propane dissolved in e-caprolactone monomer. The elastomers were then characterized by differential scanning calorimetry and uniaxial tensile testing and their physical properties related to the nature of the star copolymer prepolymers. The results demonstrate a means of predictably altering the elastomer physical properties by adjusting the star copolymer prepolymer initial molecular weight and monomer ratio.
Biomimetic Control Scheme for Musculoskeletal Humanoids Based on Motor Directional Tuning in the Brain

In this research, we have taken a biomimetic approach to the control of musculoskeletal humanoids. A controller was designed based on the motor directional tuning phenomenon seen in the motor cortex of primates. Despite the simple implementation of the control scheme, complex coordinated movements such as reaching for target objects with its upper body was achieved, and is demonstrated in the accompanying video. The controller does not require an internal model, and instead constantly observes its body in relation to the external world to update motor commands. We claim that such an embodied approach to the control of musculoskeletal robots will be able to effectively take advantage of their complex bodies to achieve motion.
Classifier Invariant Approach to Learn from Positive-Unlabeled Data

Learning from positive ($P$) and unlabeled ($U$) data has a rich history as it finds use in multiple applications. In this paper, we provide a novel framework to tackle this problem in a model agnostic fashion. We say model agnostic since, our solution involves identifying and weighting positive as well as negative examples in an unsupervised manner which could then be passed as input to any standard classification algorithm. Moreover, based on our framework we provide approximation guarantees for our algorithm in terms of how well the identified positive examples from $U$ along with their weights match the distribution of $P$. Such a principled approach has been missing for other methods that belong to the model agnostic category, not to mention that the current state-of-the-art are model dependent strategies that involve modifying the training algorithm. For Kernel Support Vector Machines, trained on a (non-negative) weighted dataset that as such is the output of our method, we derive generalization bounds. Given the advantages of having model agnostic methods (viz. use with (almost) any classifier, one time running cost), we show that our algorithm which possesses these benefits, is competitive with the best methods based on experiments on three real datasets. In fact, in a couple of cases we observe that our approach has better test performance than even standard supervised learning which has access to all positive as well as negative labels.
Whole-Game Motion Capturing of Team Sports: System Architecture and Integrated Calibration

This paper discusses the application of video motion capturing technology (VMocap) to a competitive team sports game. The setting introduces a specific set of constraints: large scale markerless motion capturing, big recording volume, transmitting and processing gigabytes of data, operation without interfering with players or distracting spectators and staff, etc. In this paper, we present how we tackled and successfully solved all of these constraints. That enabled us to analyze the sportsmen without any intrusions, while giving their peak performance, hence opening a new field for Mocap application. International volleyball game was recorded in full length with the described system. During the course of the event, we compressed 54TB of raw image data real-time, capturing 6 hours of high framerate video per camera, without disturbing any of the game operations. Using the data, we were able to reconstruct the motion, muscle activity and behavior of the athletes present on the court.
Stability/Instability Study and Control of Autonomous Dynamical Systems: Divergence Method

A novel method of instability and stability study of equilibrium points of autonomous dynamical systems using a flow and divergence of the vector field is proposed. A relation between the Lyapunov, Gauss (Ostrogradsky) and Chetaev theorems with the divergence ones is established. The generalizations of Bendixon and Bendixon-Dulac theorems about a lack of periodic solutions in arbitrary order systems are considered. The state feedback control law design based on new divergence conditions is proposed. Examples illustrate the efficiency of the proposed method and comparisons with some existing ones.
SMA Actuated Low-Weight Bio-Inspired Claws for Grasping and Perching Using Flapping Wing Aerial Systems

Taking inspiration from nature, the work presented in this paper aims to develop bio-inspired claws to be used for grasping and perching in flapping-wing aerial systems. These claws can be 3D printed out of two different materials and will be capable of adapt to any shape. Also, they will be soft for avoiding undesired damages on the objects when performing manipulation. These claws will be actuated by shape memory alloys (SMA) springs to get rid of the weight of traditional servos. The design of all the components will be explained in this work. Also, the challenges of being able to control SMA using only a LiPo battery on an aerial vehicle will be exposed. The solutions applied and electronics used will be also described. Lastly, experiments made both in test bench as on flight will be summarized.
A Multi-Contact Motion Planning and Control Strategy for Physical Interaction Tasks Using a Humanoid Robot

This paper presents a framework providing a full pipeline to execute a complex physical interaction behaviour of a humanoid bipedal robot, both from a theoretical and a practical standpoint. Building from a multi-contact control architecture that combines contact planning and reactive force distribution capabilities, the main contribution of this work consists in the integration of a sample-based motion planning layer conceived for transitioning movements where obstacle and self-collisions avoidance is involved. To plan these motions we use Rapidly Exploring Random Tree (RRT) projected on the contacts manifold and validated through the Centroidal Statics (CS) model, to ensure static balance on non-coplanar surfaces. Finally, we successfully validate the presented planning and control architecture on the humanoid robot COMAN+ performing a wall-plank task.
Jumping Motion Generation for Humanoid Robot Using Arm Swing Effectively and Changing in Foot Contact Status *

Human jumping involves not only lower limbs but also whole-body coordination. During jumping, the effect of sinking the center of mass for recoil and arm swing are significant, and they can cause changes in the jump height. However, upper body movements during jumping movements of humanoid robots have not been studied adequately. When jumping involves only the lower limbs, the burden on the lower limbs increases and it is difficult to jump as high as humans do. Also, if the sole is in contact with the ground during jumping movements, we cannot make good use of the ankle joint. Humans raise their heels during jumping movements, but there are few cases where humanoid robots achieve these movements. Therefore, we thought that jumping with recoil motion by the sinking, arm swing, and changing in foot contact status could result in a higher jump height higher than that possible with only lower limb movements. Hence, in this study, we generated jumping motion using sinking, arm swing and changing foot posture. First, a center of mass trajectory was generated by planning the entire jumping motion, and at the same time, the angular momentum was determined for stability. Next, the joint trajectory was calculated using these two parameters. At that time, arm trajectory and foot posture were specified in the null space. This generated a jumping motion considering arm swing. During simulations, this method provided a jump height almost four times the jump height that obtained without arm swing.
A Blockchain-based Key Management Protocol for Secure Device-to-Device Communication in the Internet of Things

The Internet of Things (IoT) is an emerging technology that aims to extend connectivity to all everyday devices. One of the main challenges that are slowing down its development is how to secure the Device-to-Device communication. Among all the security issues, the Key Management (KM) is one of the most challenging. The difficulty lies in the fact that most of the IoT devices suffer from a lack of resources. Although different protocols were proposed, most of them do not consider the dynamic nature of the IoT. Other solutions rely on a centralized entity to distribute the new keys upon a change in the network. However, this entity becomes a single point of failure and the main target of attacks. We propose a novel blockchain-based decentralized KM protocol. In addition to being resilient, scalable and dynamic, our solution uses the blockchain technology to securely distribute the KM on several entities.
Enhancing Classification Performance between Different GNSS Interferences using Neural Networks Trained by TAC-PSO Algorithm

Civil Global Navigation Satellite System (GNSS) receivers are susceptible to various interferences. In recent years, there have been many efforts to counteract these interferences. In this paper, we proposed an extension to the socalled Maximum-Likelihood Power-Distortion (PD-ML) detector, a GNSS authentication technique. Our proposed method differs from the PD-ML detector only in the classification stage and focuses on the classification problem. For the purpose of classification, we have used Artificial Neural Networks (ANNs), which are trained with the Particle Swarm Optimization (PSO) algorithm with Time-varying Acceleration Coefficients (TAC)-PSO, an alternative form of the PSO algorithm, best known for efficiently finding the global optima. Our results from simulation environment showed better classification ability in distinguishing between different interferences and interference-free signals in two classes. We achieved 43% accuracy, especially for multi-path afflicted signals, which is far superior to classification accuracies of previous classification methods. Our proposed classification method comes with more computation complexity in the classification stage.
Cross-Layer Hardware/Software Assessment of the Open-Source NVDLA Configurable Deep Learning Accelerator

The Nvidia Deep Learning Accelerator (NVDLA) is a free and open architecture that aims at promoting a standard way of designing deep neural network (DNN) inference engines. The analogy between open-source software and hardware points to FPGAs as ideal implementation platforms for open hardware accelerators. However, the instantiation flexibility enabled by reconfigurable logic should be correlated to the capacity of cost-effective devices. This paper explores the resource utilization-performance trade-offs spanned by the main precompiled NVDLA accelerator configurations on top of the mainstream Zynq UltraScale+ MPSoC. For the sake of comprehensive end-to-end performance characterization, the inference rate of the software stack is matched to that of the accelerator hardware, thus identifying current bottlenecks and promising optimization directions.