Miracle-dz/UniFAR-FTUs huggingface dataset:
Industrial Ergonomics Risk Analysis Based on 3D-Human Pose Estimation

Ergonomics is important for smooth and sustainable industrial operation. In the manufacturing industry, due to poor workstation design, workers frequently and repeatedly experience uncomfortable postures and actions (reaching above their shoulders, bending at awkward angles, bending backwards, flexing their elbows/wrists, etc.). Incorrect working postures often lead to specialized injuries, which reduce productivity and increase development costs. Therefore, examining workers’ ergonomic postures becomes the basis for recognizing, correcting, and preventing bad postures in the workplace. This paper proposes a new framework to carry out risk analysis of workers’ ergonomic postures through 3D human pose estimation from video/image sequences of their actions. The top-down network calculates human body joints when bending, and those angles are compared with the ground truth body bending data collected manually by expert observation. Here, we introduce the body angle reliability decision (BARD) method to calculate the most reliable body-bending angles to ensure safe working angles for workers that conform to ergonomic requirements in the manufacturing industry. We found a significant result with high accuracy in the score for ergonomics we used for this experiment. For good postures with high reliability, we have OWAS score 94%, REBA score 93%, and RULA score 93% accuracy. Similarly, for occluded postures we have OWAS score 83%, REBA score 82%, and RULA score 82%, compared with expert’s occluded scores. For future study, our research can be a reference for ergonomics score analysis with 3D pose estimation of workers’ postures.
Quantifying tensions between CMB and distance data sets in models with free curvature or lensing amplitude

Recent measurements of the cosmic microwave background (CMB) by the Planck Collaboration have produced arguably the most powerful observational evidence in support of the standard model of cosmology, i.e. the spatially flat Lambda CDM paradigm. In this work, we perform model selection tests to examine whether the base CMB temperature and large scale polarization anisotropy data from Planck 2015 (P15;Planck Collaboration XIII) prefer any of eight commonly used one-parameter model extensions with respect to flat Lambda CDM. We find a clear preference for models with free curvature, Omega(K), or free amplitude of the CMB lensing potential, A(L). We also further develop statistical tools to measure tension between data sets. We use a Gaussianization scheme to compute tensions directly from the posterior samples using an entropy-based method, the surprise, as well as a calibrated evidence ratio presented here for the first time. We then proceed to investigate the consistency between the base P15 CMB data and six other CMB and distance data sets. In flat Lambda CDM we find a 4.8 sigma tension between the base P15 CMB data and a distance ladder measurement, whereas the former are consistent with the other data sets. In the curved Lambda CDM model we find significant tensions in most of the cases, arising from the well-known low power of the low-l multipoles of the CMB data. In the flat Lambda CDM+A(L) model, however, all data sets are consistent with the base P15 CMB observations except for the CMB lensing measurement, which remains in significant tension. This tension is driven by the increased power of the CMB lensing potential derived from the base P15 CMB constraints in both models, pointing at either potentially unresolved systematic effects or the need for new physics beyond the standard flat Lambda CDM model.
Complex dynamics of cellular automata emerging in chaotic rules

We show novel techniques of analysing complex dynamics of cellular automata (CA) with chaotic behaviour. CA are well known computational substrates for studying emergent collective behaviour, complexity, randomness and interaction between order and disorder. A number of attempts have been made to classify CA functions on their spatio-temporal dynamics and to predict behaviour of any given function. Examples include mechanical computation, $\lambda$ and $Z$-parameters, mean field theory, differential equations and number conserving features. We propose to classify CA based on their behaviour when they act in a historical mode, i.e. as CA with memory. We demonstrate that cell-state transition rules enriched with memory quickly transform a chaotic system converging to a complex global behaviour from almost any initial condition. Thus just in few steps we can select chaotic rules without exhaustive computational experiments or recurring to additional parameters. We provide analysis of well-known chaotic functions in one-dimensional CA, and decompose dynamics of the automata using majority memory.
Exploring Stroke Patients’ Needs after Discharge from Rehabilitation Centres: Meta-Ethnography

Healthcare providers must consider stroke survivors needs in order to enable a good quality of life after stroke. This review aimed to investigate the perceived needs of the stroke survivors across various domains of care following their discharge from hospital. A meta-ethnographic review of qualitative studies that reported needs of stroke patients after discharge from rehabilitation services was conducted. Main searches were conducted on the following electronic databases: Ovid Medline (1946 to 2021), CINAHL plus (EBSCO), AMED (EBSCO), PsycINFO (1967 to 2021), the Cochrane Library, and PubMed in June 2022. Main outcomes were related to stroke survivors’ views, experiences, and preferences on physical, psychological, social, rehabilitation needs, and other identified needs. Twenty-seven studies were included in the final analysis. The findings show that existing rehabilitation provision for stroke survivors does not address the long-term needs of stroke survivors. Two main issues were revealed concerning the unmet needs of stroke survivors: (1) a lack of information availability and suitability and (2) inadequacy of care and services. It is crucial to further investigate the needs of patients in Asian countries and the Middle East as there is very limited understanding of patients’ needs in the community in these regions.
The Looping Rate and Sandpile Density of Planar Graphs

Abstract We give a simple formula for the looping rate of a loop-erased random walk on a finite planar graph. The looping rate is closely related to the expected amount of sand in a recurrent sandpile on the graph. The looping rate formula is well suited to taking limits where the graph tends to an infinite lattice, and we use it to give an elementary derivation of the (previously computed) looping rate and sandpile densities of the square, triangular, and honeycomb lattices, and compute (for the first time) the looping rate and sandpile densities of many other lattices, such as the kagomé lattice, the dice lattice, the truncated hexagonal lattice (for which the values are all rational), and the square-octagon lattice (for which it is transcendental).
Comparative analysis of features of online numerical methods used for parameter estimation of PMSM

As permanent magnet synchronous motors (PMSM) have high power density, efficiency, good dynamic performance, and small size they are becoming popular in electric vehicle (EV) applications. Control performance and the efficiency of the system get affected due to electrical, mechanical parameters. Parameters value gets affected by voltage source inverter (VSI) non-linearities, temperature and magnetic saturation effects. If exact parameters for particular torque speed requirement are found, the efficiency of system increases. There are various offline and online methods for finding parameters. Offline methods are easy to implement but requires extra setup and estimate parameters in steady state. Because the effects of transient conditions are taken into account during identification, online methods for obtaining real-time data under running conditions are becoming more popular. An overview about online numerical methods to estimate electrical parameters of PMSM is given. It discusses difference between various methods in terms of computational cost, convergence speed, noise and identification error. Choosing of method will be easy using this work. For inductance estimation, the extended Kalman filter (EKF) algorithm has an identification error of 0.24% under temperature effect and -0.3% under VSI non-linearities effect. The identification error for Rs and ψf using the recursive least square (RLS) method is 0.5% and 0.02%, respectively, when temperature is considered. EKF and RLS algorithms are proposed.
Using Post-Emergence Herbicides in Combination with the Sowing Date to Suppress Sinapis arvensis and Silybum marianum in Durum Wheat

Wild mustard (Sinapis arvensis L.) and milk thistle (Silybum marianum (L.) Gaertn. ) are two competitive broad-leaved weeds commonly found in cereals in Europe, while several weed species have developed resistance to the main herbicides that are applied on these crops. Thus, the implementation of integrated weed management (IWM) programs is of great importance. Field experiments were conducted based on a split-plot design with two factors (sowing date and herbicides). Our results showed that the density of wild mustard and milk thistle was higher in the early sowing compared to the late sowing, while the total weed density was up to 75% higher in early sowing. Moreover, the herbicides florasulam + 2.4-D and bromoxynil + 2.4-D exhibited high efficacy (>98%) against milk thistle and wild mustard, while tribenuron-methyl and florasulam + clopyralid provided greater efficacy in the late sowing compared to the early sowing. Among the four herbicides, the lowest dry biomass and grain yield of wheat were observed in tribenuron-methyl and florasulam + clopyralid, while in the weed-infested treatment, the highest values of both parameters were recorded in late sowing. Finally, the results showed that the sowing date is a cultural weed control method that should be implemented in IWM programs, since it can affect both weed density and herbicide efficacy.
Suppression of small baryonic structures due to a primordial magnetic field

We investigate the impact of the existence of a primordial magnetic field on the filter mass, characterizing the minimum baryonic mass that can form in dark matter (DM) haloes. For masses below the filter mass, the baryon content of DM haloes are severely depressed. The filter mass is the mass when the baryon to DM mass ratio in a halo is equal to half the baryon to DM ratio of the Universe. The filter mass has previously been used in semi-analytic calculations of galaxy formation, without taking into account the possible existence of a primordial magnetic field. We examine here its effect on the filter mass. For homogeneous comoving primordial magnetic fields of B 0 ∼ 1 or 2 nG and a re-ionization epoch that starts at a redshift z s = 11 and is completed at z r = 8, the filter mass is increased at redshift 8, for example, by factors of 4.1 and 19.8, respectively. The dependence of the filter mass on the parameters describing the re-ionization epoch is investigated. Our results are particularly important for the formation of low-mass galaxies in the presence of a homogeneous primordial magnetic field. For example, for B 0 ∼ 1 nG and a re-ionization epoch of z s ∼ 11 and z r ∼ 7, our results indicate that galaxies of total mass M ∼ 5 x 10 8 M ⊙ need to form at redshifts z F ≳ 2.0, and galaxies of total mass M ∼ 10 8 M ⊙ at redshifts z F ≳ 7.7.
Ultracompact dwarfs around NGC 3258 in the Antlia cluster

Fil: Caso, Juan Pablo. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - La Plata. Instituto de Astrofisica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronomicas y Geofisicas. Instituto de Astrofisica La Plata; Argentina
Analyzing the Potential of Feature Groups for Misinformation Detection in WhatsApp

The new mass media (e.g., social networks, and instant messaging applications) have drastically changed how users generate, propagate, and consume information. Given this scenario, an emerging problem is the abuse of these platforms for the propagation of disinformation that, consequently, affects the credibility of the news ecosystem in these environments. The dissemination of misinformation on these platforms has become a worldwide phenomenon, and scalable strategies to contain or mitigate the problem are scarce. Thus, using automated approaches to detect disinformation on digital media can help journalists and fact-check teams identify content that needs to be verified. In this context, in this work, we investigate the potential of feature groups for automatic misinformation detection shared on digital platforms. Our results reveal that using a set of features from some groups, can be useful to build models with satisfactory performance, which can make the application of the model viable in a practical scenario.
Full-sky Gravitational Lensing Simulation for Large-area Galaxy Surveys and Cosmic Microwave Background Experiments

We present 108 full-sky gravitational lensing simulation data sets generated by performing multiple-lens plane ray-tracing through high-resolution cosmological N-body simulations. The data sets include full-sky convergence and shear maps from redshifts z = 0.05 to 5.3 at intervals of 150 h − 1 Mpc comoving radial distance (corresponding to a redshift interval of Δ z ≃ 0.05 at the nearby universe), enabling the construction of a mock shear catalog for an arbitrary source distribution up to z = 5.3. The dark matter halos are identified from the same N-body simulations with enough mass resolution to resolve the host halos of the Sloan Digital Sky Survey (SDSS) CMASS and luminous red galaxies (LRGs). Angular positions and redshifts of the halos are provided by a ray-tracing calculation, enabling the creation of a mock halo catalog to be used for galaxy–galaxy and cluster–galaxy lensing. The simulation also yields maps of gravitational lensing deflections for a source redshift at the last scattering surface, and we provide 108 realizations of lensed cosmic microwave background (CMB) maps in which the post-Born corrections caused by multiple light scattering are included. We present basic statistics of the simulation data, including the angular power spectra of cosmic shear, CMB temperature and polarization anisotropies, galaxy–galaxy lensing signals for halos, and their covariances. The angular power spectra of the cosmic shear and CMB anisotropies agree with theoretical predictions within 5% up to ℓ = 3000 (or at an angular scale θ > 0.5 arcmin). The simulation data sets are generated primarily for the ongoing Subaru Hyper Suprime-Cam survey, but are freely available for download at http://cosmo.phys.hirosaki-u.ac. jp/takahasi/allsky_raytracing/.
Dysregulated Hemostasis and Immunothrombosis in Cerebral Cavernous Malformations

Cerebral cavernous malformation (CCM) is a neurovascular disease that affects 0.5% of the general population. For a long time, CCM research focused on genetic mutations, endothelial junctions and proliferation, but recently, transcriptome and proteome studies have revealed that the hemostatic system and neuroinflammation play a crucial role in the development and severity of cavernomas, with some of these publications coming from our group. The aim of this review is to give an overview of the latest molecular insights into the interaction between CCM-deficient endothelial cells with blood components and the neurovascular unit. Specifically, we underscore how endothelial dysfunction can result in dysregulated hemostasis, bleeding, hypoxia and neurological symptoms. We conducted a thorough review of the literature and found a field that is increasingly poised to regard CCM as a hemostatic disease, which may have implications for therapy.
The Analgesic Museum

This manuscript uses the perspectives and insights that emerged from the Analgesic Museum conference held virtually on March 11, 2022 as a mechanism for considering the role museums and artists can play in the public health effort to reduce the burden of persistent pain. One hundred and fifty-seven individuals from 22 countries registered for the Analgesic Museum conference. The event explored the intersection of art and pain management practices with presentations centered on three domains of interest: exhibition development, arts experiences and practices, and research and creative scholarship.
On the nature of flux variations of trapped particles associated with sudden commencement and sudden impulse at synchronous orbit

Les variations de flux des particules energetiques observees par GMS/GEOS en 1978 se divisent en deux types: en «escalier» et en «pic». Elles sont reliees aux parametres des particules piegees. On met en avant deux mecanismes expliquant le phenomene: l'acceleration betatron et un niveau eleve de flux de particules avant les SSC et SI
La idoneidad del profesorado de educación secundaria obligatoria en España. Una percepción autoinformada

La idoneidad profesional docente es un constructo complejo que no solo se manifiesta en un conjunto variado de efectos, sino también en la evolución de su intensidad con el tiempo. En este contexto, la formación inicial, la formación permanente y las capacidades docentes reconocidas por los propios profesores constituyen aspectos clave para la definición de las políticas o para su corrección. Por otra parte, el diagnóstico diferencial, en función del nivel socioeconómico y cultural de los centros, es recomendable para ajustar las políticas compensatorias centradas en el factor profesorado. El estudio proporciona un diagnóstico empírico de todos estos elementos, a nivel nacional y territorial, mostrando los siguientes resultados: (1) la falta de formación inicial del profesorado en la materia que imparte arroja cifras moderadas que, particularmente en el caso de la Tecnología y de las Matemáticas, pueden considerarse preocupantes, en especial en algunos territorios; (2) la existencia de necesidades reconocidas de formación en aspectos clave de la enseñanza que afectan a entre la cuarta y la tercera parte de los profesores encuestados y que es superior en los centros desaventajados; (3) solo la mitad del profesorado que imparte ESO se considera suficientemente competente para cumplir con el conjunto de requerimientos.
An extension of König's theorem to graphs with no odd-K4

We prove the following mitr-max relations. Let G be an undirected graph, without isolated nodes, not containing an odd-K4 (a homeomorph of K4 (the 4-clique) in which the triangles of K4 have become odd cycles). Then the maximum cardinality of a stable set in G Ss equal to the mini-m~un ri~st uf a collectton uF edKeA and odd circults ln C, coverinR the nodes of G. Here the cost of an edge is 1 and the cost of a circuit of length 2kt1 equal to k. Moreover, the minimum cardínality of a node-cover for G is equal to the maximum profit of a collection mutually node disjoint edges and odd circuits in G. Here the rpofit of an edge is 1 and the r ~ ofit of a circuit of length 2kf1 is equal to ktl. Also weighted versions of these min-max relations hold. The result extends Kánig's well-known min-max relations for stable sets and node-covers in bipartíte graphs. Moreover it extends results of Chv~atal, Boulala, Fonlupt, and Uhry. A weaker, fractional, version of these min-max relations follows from earlier results obtained by Schrijver and the author.
Prediction of Flight Delays at Beijing Capital International Airport Based on Ensemble Methods

Predicting flight delays plays a critical role in reducing financial losses and increasing passenger satisfaction. Due to their ability to combine multiple algorithms, ensemble methods have demonstrated strong predictive performance in many research fields. In this paper, ensemble methods are adopted to predict flight delays. First, based on the current studies, two novel explanatory variables, named arrival/departure pressure and cruise pressure, are proposed as factors affecting flight delays. Second, we introduce the ensemble methods and select representative algorithms for the prediction problem. In addition to the ensemble methods, classical algorithms are also used to predict flight delays. Finally, the actual operational data of Beijing Capital International Airport were utilized to conduct a case study. The results show that the stacking method has better prediction performance than other baseline methods. The mean absolute error (MAE) of the stacking method was about 12.58 min on the test dataset. Furthermore, we tested the effect of the two explanatory variables proposed in this paper, and the results show that the MAE was reduced by about 20% by using the stacking method.
Sommerfeld-enhanced annihilation in dark matter substructure: Consequences for constraints on cosmic-ray excesses

In models of dark matter (DM) with Sommerfeld-enhanced annihilation, where the annihilation rate scales as the inverse velocity, N-body simulations of DM structure formation suggest that the local annihilation signal may be dominated by small, dense, cold subhalos. This contrasts with the usual assumption of a signal originating from the smooth DM halo, with much higher velocity dispersion. Accounting for local substructure modifies the parameter space for which Sommerfeld-enhanced annihilating DM can explain the PAMELA and Fermi excesses. Limits from the inner galaxy and the cosmic microwave background are weakened, without introducing new tension with substructure-dependent limits, such as from dwarf galaxies or isotropic gamma-ray studies. With substructure, previously excluded parameter regions with mediators of mass ~1-200 MeV are now easily allowed. For O(MeV) mediators, subhalos in a specific range of host halo masses may be evaporated, further suppressing diffuse signals without affecting substructure in the Milky Way.
Algorithms for Toeplitz Matrices with Applications to Image Deblurring

In this thesis, we present the O(n log 2 n) superfast linear least squares Schur algorithm (sflsschur). The algorithm we will describe illustrates a fast way of solving linear equations or linear least squares problems with low displacement rank. This program is based on the O(n 2) Schur algorithm speeded up via FFT. The algorithm solves a ill-conditioned Toeplitz-like system using Tikhonov regularization. The regularized system is Toeplitz-like of displacement rank 4. We show the effect of choice of the regularization parameter on the quality of the image reconstruction.