Miracle-dz/UniFAR-FTUs huggingface dataset:
Herramientas digitales en el proceso de aprendizaje semipresencial en la Educación Dental Peruana durante la Pandemia COVID-19.

La pandemia del COVID-19 ha generado un vacío pedagógico en la educación dental, que por la naturaleza clínica, práctica y laboratorial de las asignaturas obligó a los docentes a incorporar recursos didácticos digitales novedosos en los que se simulan entornos de aprendizaje que ayudan a fomentar el desarrollo de habilidades y conocimientos en busca de la mejora continua. No obstante, los estudiantes se han visto también en la necesidad de recurrir a plataformas virtuales que le permitan una mayor adaptación a este complejo sistema híbrido de aprendizaje semipresencial. Los hallazgos de la presente revisión, es producto de un estudio exploratorio que tuvo como propósito identificar las principales Tecnologías de la Información y Comunicación y organizarlas según herramientas de interpretación, modelado dinámico, comunicación, colaboración y organización. De esta manera proporcionamos a la comunidad académica una visión del impacto de ellas sobre el proceso de aprendizaje y autoaprendizaje, sus experiencias de uso y la percepción de los beneficios y limitaciones de estas nuevas tecnologías en un contexto actual en estudiantes de Odontología. En la primera parte abordamos el estado de arte sobre los componentes pedagógicos de las TIC, el papel que desempeñan en la educación superior, las características y los estándares que deben cumplir para que se constituyan en herramientas cognitivas aliadas de la educación formal, de manera que permitan la interacción y la gestión del conocimiento de los estudiantes. Seguidamente compartimos los resultados de una encuesta abierta de los estudiantes de pregrado de una Facultad de Odontología Peruana que se realizó como una fase preliminar diagnóstica que se constituyó el punto de partida para la validación de instrumentos de un trabajo de investigación sobre experiencias del uso de las TIC como herramientas digitales y cognitivas de enseñanza y aprendizaje en la educación dental en línea que cuenta con la autorización del Comité de Ética en Investigación de la Facultad de Medicina de la Universidad Nacional Mayor de San Marcos N° 0209; Las respuestas obtenidas muestran los recursos al servicio de su educación formal y científica relacionadas con habilidades propias de usuarios denominados “nativos digitales” motivándolos a ser los protagonistas de su aprendizaje y desarrollo de competencias para un adecuado desempeño profesional.
One-loop corrections to AdS5 × S5 superstring partition function via Pohlmeyer reduction

We discuss semiclassical expansions around a class of classical string configurations lying in AdS3 × S1 using the Pohlmeyer-reduced form of the AdS5 × S5 superstring theory. The Pohlmeyer reduction of the AdS5 × S5 superstring theory is a gauged Wess–Zumino–Witten model with an integrable potential and two-dimensional fermionic fields. It was recently conjectured that the quantum string partition function is equal to the quantum reduced theory partition function. Continuing the previous paper (Hoare et al 2009 J. Phys. A: Math. Theor. 42 375204), where arbitrary solutions in AdS2 × S2 and homogeneous solutions were considered, we provide an explicit demonstration of this conjecture at the one-loop level for several string solutions in AdS3 × S1 embedded into AdS5 × S5. Quadratic fluctuations derived in the reduced theory for inhomogeneous strings are equivalent to respective fluctuations found from the Nambu action in the original string theory. We also show the equivalence of fluctuation frequencies for homogeneous strings with both the orbital momentum and the winding on a big circle of S5.
Searching for chameleon-like scalar fields with the ammonia method , II. Mapping of cold molecular cores in NH3 and HC3N lines

Context. In our previous work we found a statistically significant offset ΔV ≈ 27 m s −1 between the radial velocities of the HC3N J = 2− 1a nd NH 3 (J,K) = (1, 1) transitions observed in molecular cores from the Milky Way. This may indicate that the electron-toproton mass ratio, μ ≡ me/mp, increases by ∼3 × 10 −8 when measured under interstellar conditions with matter densities of more than 10 orders of magnitude lower than with laboratory (terrestrial) environments. Aims. We map four molecular cores L1498, L1512, L1517, and L1400K selected from our previous sample to estimate systematic effects in ΔV due to possible velocity gradients or other sources across the cloud and to check the reproducibility of the velocity offsets on the year-to-year time base. Methods. We use the ammonia method, which involves observations of inversion lines of NH3 complemented by rotational lines of other molecular species and allows us to test changes in μ caused by a higher sensitivity of the inversion frequencies to the μ-variation than with the rotational frequencies. Results. We find that in two cores L1498 and L1512 the NH3 (1, 1) and HC3N (2–1) transitions closely trace the same material and show an offset of ΔV ≡ Vlsr(HC3N) – Vlsr(NH3) = 26.9 ± 1.2stat ± 3.0sys ms −1 throughout the entire clouds. The offsets measured in L1517B and L1400K are 46.9 ± 3.3stat ± 3.0sys ms −1 and 8.5 ± 3.4stat ± 3.0sys ms −1 , respectively, and are, probably, subject to Doppler shifts due to spatial segregation of HC3 Nv ersus NH 3. We also determine frequency shifts caused by external electric and magnetic fields and by the cosmic black body radiation-induced Stark effect and find that they are less than 1 m s −1 . Conclusions. The measured velocity offset in L1498 and L1512, when interpreted in terms of Δμ/μ ≡ (μobs − μlab)/μlab ,g ivesΔμ/μ = (26 ± 1stat ± 3sys) × 10 −9 . Although this estimate is based on a limited number of sources and molecular pairs used in the ammonia method, it demonstrates a high accuracy with which the fundamental physics can be tested by means of radio observations. The non-zero signal in Δμ/μ should be further examined as larger and more accurate data sets become available.
Understanding the role of initial soil moisture and precipitation magnitude in flood forecast using a hydrometeorological modelling system

We adapted the WRF‐Hydro modelling system to Hurricane Florence (2018) and performed a series of diagnostic experiments to assess the influence of initial soil moisture and precipitation magnitude on flood simulation over the Cape Fear River basin in the United States. Model results suggest that: (1) The modulation effect of initial soil moisture on the flood peak is non‐linear and weakens as precipitation magnitude increases. There is a threshold value of the soil saturation, below and above which the sensitivity of flood peak to the soil moisture differentiates substantially; (2) For model spin‐up, streamflow needs longer time to reach the ‘practical’ equilibrium (10%) than the soil moisture and latent heat flux. The model uncertainty from spin‐up can propagate through the hydrometeorological modelling chain and get amplified into the flood peak; (3) For ensemble flood modelling with a hydrometeorological system, modelling uncertainty is dominated by the precipitation forecast. Spin‐up induced uncertainty can be minimized once the model reaches the ‘practical’ equilibrium.
An Experimentally Tuned Compact Electrical Model for Laser Fault Injection Simulation

This work reports LFI experiments carried out on custom CMOS 65 nm digital test gates, aiming at tuning the parameters of a compact electrical model. Like in previous works, we observed a difference in behavior in the induced faults when using nanosecond and picosecond range laser pulse duration. However, our experimental results showed that the laser-sensitive areas were restricted to the PMOS transistors for ns laser pulses, contrary to what was previously stated in the literature. For ps pulse duration, these works outline the sensitivity of both the NMOS and PMOS of an SRAM cell following the theoretical model of LFI. These experiments help to calibrate the parameters of a compact electrical model, allowing the simulation of LFI attacks (using SPICE-like CAD tools). This compact model is built upon previous works, with simplifications to facilitate its use. Once tuned, simulations using the proposed compact model exhibit a good correlation with the experimental results.
Thin accretion discs around millisecond X-ray pulsars

Millisecond X-ray pulsars have weak magnetic dipole moments of ∼10 16 Tm 3 compared to ordinary X-ray pulsars with dipole moments of 10 20 Tm 3 . For this reason a surrounding accretion disc can extend closer to the millisecond X-ray pulsars, and thus reach a higher temperature, at which the opacity is dominated by electron scattering and radiation pressure is strong. We compute the self-similar structure of such a geometrically thin axisymmetric accretion disc with an internal dynamo. Such models produce significantly stronger torques on the neutron star than models without dynamos, and can explain the strong spin variations in some millisecond X-ray pulsars.
Coexisting Passive RIS and Active Relay-Assisted NOMA Systems

A novel coexisting passive reconfigurable intelligent surface (RIS) and active decode-and-forward (DF) relay assisted non-orthogonal multiple access (NOMA) transmission framework is proposed. In particular, two communication protocols are conceived, namely Hybrid NOMA (H-NOMA) and Full NOMA (F-NOMA). Based on the proposed two protocols, both the sum rate maximization and max-min rate fairness problems are formulated for jointly optimizing the power allocation at the access point and relay as well as the passive beamforming design at the RIS. To tackle the non-convex problems, an alternating optimization (AO) based algorithm is first developed, where the transmit power and the RIS phase-shift are alternatingly optimized by leveraging the two-dimensional search and rank-relaxed difference-of-convex (DC) programming, respectively. Then, a two-layer penalty based joint optimization (JO) algorithm is developed to jointly optimize the resource allocation coefficients within each iteration. Finally, numerical results demonstrate that: i) the proposed coexisting RIS and relay assisted transmission framework is capable of achieving a significant user performance improvement than conventional schemes without RIS or relay; ii) compared with the AO algorithm, the JO algorithm requires less execution time at the cost of a slight performance loss; and iii) the H-NOMA and F-NOMA protocols are generally preferable for ensuring user rate fairness and enhancing user sum rate, respectively.
Modelling the formation and evolution of star cluster populations in galaxy simulations

The formation and evolution of star cluster populations are related to the galactic environment. Cluster formation is governed by processes acting on galactic scales, and star cluster disruption is driven by the tidal field. In this paper, we present a self-consistent model for the formation and evolution of star cluster populations, for which we combine an N-body/smoothed particle hydrodynamics galaxy evolution code with semi-analytical models for star cluster evolution. The model includes star formation, feedback, stellar evolution and star cluster disruption by two-body relaxation and tidal shocks. The model is validated by a comparison to N-body simulations of dissolving star clusters. We apply the model by simulating a suite of nine isolated disc galaxies and 24 galaxy mergers. The evolutionary histories of individual clusters in these simulations are discussed to illustrate how the environment of clusters changes in time and space. It is found that the variability of the disruption rate with time and space affects the properties of star cluster populations. In isolated disc galaxies, the mean age of the clusters increases with galactocentric radius. The combined effect of clusters escaping their dense formation sites (‘cluster migration’) and the preferential disruption of clusters residing in dense environments (‘natural selection’) implies that the mean disruption rate of the population decreases with cluster age. This affects the slope of the cluster age distribution, which becomes a function of the star formation rate density (star formation rate per unit volume). The evolutionary histories of clusters in a galaxy merger vary widely and determine which clusters survive the merger. Clusters that escape into the stellar halo experience low disruption rates, while clusters orbiting near the starburst region of a merger are disrupted on short time-scales due to the high gas density. This impacts the age distributions and the locations of the surviving clusters at all times during a merger. The paper includes a discussion of potential improvements for the model and a brief exploration of possible applications. We conclude that accounting for the interplay between the formation, disruption and orbital histories of clusters enables a more sophisticated interpretation of observed properties of cluster populations, thereby extending the role of cluster populations as tracers of galaxy evolution.
Stochastic distributed learning with gradient quantization and double-variance reduction

ABSTRACT We consider distributed optimization over several devices, each sending incremental model updates to a central server. This setting is considered, for instance, in federated learning. Various schemes have been designed to compress the model updates in order to reduce the overall communication cost. However, existing methods suffer from a significant slowdown due to additional variance coming from the compression operator and as a result, only converge sublinearly. What is needed is a variance reduction technique for taming the variance introduced by compression. We propose the first methods that achieve linear convergence for arbitrary compression operators. For strongly convex functions with condition number κ, distributed among n machines with a finite-sum structure, each worker having less than m components, we also (i) give analysis for the weakly convex and the non-convex cases and (ii) verify in experiments that our novel variance reduced schemes are more efficient than the baselines. Moreover, we show theoretically that as the number of devices increases, higher compression levels are possible without this affecting the overall number of communications in comparison with methods that do not perform any compression. This leads to a significant reduction in communication cost. Our general analysis allows to pick the most suitable compression for each problem, finding the right balance between additional variance and communication savings. Finally, we also (iii) give analysis for arbitrary quantized updates.
Computation of prime cubes of a complex boolean function based on BDDs - continuation on probability of time unfolded prime cubes

With decreasing feature size and increasing complexity of integrated circuits, effective tools for verification and testing are in high demand. When testing large and complex state machines, effective tools for calculating probabilities of future states are often needed. The PState program calculates these with an adapted form of Binary Desicion Diagrams. This project is part of an effort to extend this to search for functions to reach these states by extracting prime cube covers of these BDDs. This report documents my work with the PState program, the adaptation of the cube extraction algorithm, and attempting to unfold the computation over several cycles of a state machine, the problems encountered, and outlines possible ways to solve these challenges.
CAN Signal Extinction-based DoS Attack on In-Vehicle Network

As automobiles become more electrified, more and more Electronic Control Units (ECU) are installed in vehicles. ECUs communicate with each other through dedicated protocols such as a controller area network (CAN), but these protocols do not have their own security measures. Many cyberattacks have exploited this weakness, but an intrusion detection system (IDS) is emerging as an effective countermeasure. In this study, we introduce a new attack method that existing IDS cannot detect. CAN signal extinction-based DoS attack (CEDA) is a new attack method that uses a voltage drop to erase the CAN signal. When the target ECU transmits a signal, adding a resister that lowers the differential voltage to an undefined gray zone causes the other ECU to ignore the signal being sent from the target ECU. In cybersecurity, denial of service (DoS) is defined as restricting an authorized entity from accessing a resource or delaying a time-critical system. This attack is a kind of a DoS attack since the adversary can make the target ECU bus-off through a CEDA. CEDA could be a serious problem as it has not been detected by any known IDS to date. In this study, we use laboratory and vehicle tests to detail the attack methods and introduce appropriate security measures.
Observations and Impacts of Long‐Range Transported Wildfire Smoke on Air Quality Across New York State During July 2021

Wildfires are a significant source of PM2.5 that adversely affect local and regional air quality. However, tracking wildfire smoke and their impacts are difficult. This study explores how a ground‐based Doppler lidar network can improve monitoring of long‐range transported wildfire smoke. As a case study, this paper reviews the transported wildfire smoke and its impact on air quality across New York State (NYS) during two events: 18–21 and 25–27 July 2021. Observations of wildfire smoke and enhancement of PM2.5 across NYS during those events were consistent across ground‐based sensors, satellites, back trajectory analyses, and model forecasts. However, for some of the days, the model over/under‐forecasted smoke plumes. Overall, this study highlights the value of the NYS Mesonet Profiler Network to monitor wildfire smoke with high spatiotemporal resolution. Such a relatively dense network can be a valuable observational tool for evaluating PM2.5, and aiding satellite measurements and air quality forecasting models.
Sejong Open Cluster Survey. I. NGC 2353

UBV I CCD photometry of NGC 2353 is performed as a part of the \Sejong Open cluster Survey" (SOS). Using photometric membership criteria we selelct probable members of the cluster. We derive the reddening and distance to the cluster, i.e., E(B i V ) = 0:10 § 0:02 mag and 1:17 § 0:04 kpc, respectively. We flnd that the projected distribution of the probable members on the sky is elliptical in shape rather than circular. The age of the cluster is estimated to be log(age)=8.1 § 0.1 in years, older than what was found in previous studies. The minimum value of binary fraction is estimated to be about 48 § 5 percent from a Gaussian function flt to the distribution of the distance moduli of the photometric members. Finally, we also obtain the luminosity function and the initial mass function (IMF) of the probable cluster members. The slope of the IMF is i = i1:3 § 0:2.
The Historical Role of Energy in UK Inflation and Productivity and Implications for Price Inflation in 2022

We model UK price and wage inflation, productivity and unemployment over a century and a half of data, selecting dynamics, relevant variables, non-linearities and location and trend shifts using indicator saturation estimation. The four congruent econometric equations highlight complex interacting empirical relations. The production function reveals a major role for energy inputs additional to capital and labour, and although the price inflation equation shows a small direct impact of energy prices, the substantial rise in oil and gas prices seen by mid-2022 contribute half of the increase in price inflation. We find empirical evidence for non-linear adjustments of real wages to inflation: a wage-price spiral kicks in when inflation exceeds about 6–8% p.a. We also find an additional non-linear reaction to unemployment, consistent with involuntary unemployment. A reduction in energy availability simultaneously reduces output and exacerbates inflation.
Period Mappings and Period Domains

Part I. Basic Theory of the Period Map: 1. Introductory examples 2. Cohomology of compact Kahler manifolds 3. Holomorphic invariants and cohomology 4. Cohomology of manifolds varying in a family 5. Period maps looked at infinitesimally Part II. The Period Map: Algebraic Methods: 6. Spectral sequences 7. Koszul complexes and some applications 8. Further applications: Torelli theorems for hypersurfaces 9. Normal functions and their applications 10. Applications to algebraic cycles: Nori's theorem Part III: Differential Geometric Methods: 11. Further differential geometric tools 12. Structure of period domains 13. Curvature estimates and applications 14. Harmonic maps and Hodge theory Appendix A. Projective varieties and complex manifolds Appendix B. Homology and cohomology Appendix C. Vector bundles and Chern classes.
Recent advances in understanding the role of eosinophils

Our understanding of eosinophil biology, development, and regulation has dramatically increased in the past decade, leading to new paradigms for the role of eosinophils in human health and disease and, perhaps more importantly, providing insights toward novel treatment strategies in the fight against eosinophil-mediated inflammation. In this review, we discuss recent advances regarding the role of eosinophils in host-viral defense, eosinophil heterogeneity, and eosinophil-targeted therapies.
Parton Distributions in the Higgs Boson era

Parton distributions are an essential ingredient of the LHC program. PDFs are relevant for precision Standard Model measurements, for Higgs boson characterization as well as for New Physics searches. In this contribution I review recent progress in the determination of the parton distributions of the proton during the last year. Important developments include the impact of new LHC measurements to pin down poorly known PDFs, studies of theoretical uncertainties, higher order calculations for processes relevant for PDF determinations, PDF benchmarking exercises with LHC data, as well as methodological and statistical improvements in the global analysis framework. I conclude with some speculative considerations about future directions in PDF determinations from the theory point of view.
Solving moral dilemmas with AI: how it helps us address the social implications of the Covid-19 crisis and enhance human responsibility to tackle meta-dilemmas

ABSTRACT When combined with an appropriate level of human judgement, machine learning applications were crucial resources insupporting decision-making in the context of the Covid-19 crisis, resulting in more efficient and better-informed responses to ethicalissues. This paper focusses on four social dimensions (bioethical, political, psychological, and economic) from which the decisionstaken in the context of the Covid-19 crisis derived major ethical implications. On the one hand, I argue against the possibility ofaddressing these issues from a purely algorithmic approach, elaborating on two types of limitations for automated systems toaddress ethical issues. This leads me to discuss how different ethical situations call for different performance metrics with regards tothe ‘contextual explicability and performance issue’, as well as to enunciate a gold principle: ‘legitimacy trumps accuracy’. On the otherhand, I present practical examples of machine learning applications which enhance, instead of dilute, human moral agency in betteraddressing these issues. I also suggest a ‘moral perimeter’ framework to ensure the responsibility of algorithms-assisted decisionmakersfor critical decisions. The unique potential of AI to ‘solve’ moral dilemmas by intervening on their conditions of possibility thenprompts me to discuss a new type of moral situation: AI-generated meta-dilemmas.