New global minimum conformers for the Pt 19 and Pt 20 clusters: low symmetric species featuring different active sites.

CONTEXT: The study of platinum (Pt) clusters and nanoparticles is essential due to their extensive range of potential technological applications, particularly in catalysis. The electronic properties that yield optimal catalytic performance at the nanoscale are significantly influenced by the size and structure of Pt clusters. This research aimed to identify the lowest-energy conformers for Pt 18 , Pt 19 , and Pt 20 species using Density Functional Theory (DFT). We discovered new low-symmetry conformers for Pt 19 and Pt 20 , which are 3.0 and 1.0 kcal/mol more stable, respectively, than previously reported structures. Our study highlights the importance of using density functional approximations that incorporate moderate levels of exact Hartree-Fock exchange, alongside basis sets of at least quadruple-zeta quality. The resulting structures are asymmetric with varying active sites, as evidenced by sigma hole analysis on the electrostatic potential surface. This suggests a potential correlation between electronic structure and catalytic properties, warranting further investigation. METHODS: An equivariant graph neural network interatomic potential (NequIP) within the Atomic Simulation Environment suite (ASE) was used to provide initial geometries of the aggregates under study. DFT calculations were performed with the ORCA 5 package, using functional approximations that included Generalized Gradient Approximation (PBE), meta-GGA (TPSS, M06-L), hybrid (PBE0, PBEh), meta-GGA hybrid (TPSSh), and range-separated hybrid ( ω B97x) functionals. Def2-TZVP and Def2-QZVP as well as members of the cc-pwCVXZ-PP family to check basis set convergence were used. QTAIM calculations were performed using the AIMAll suite. Structures were visualized with the AVOGADRO code.

Does Aromaticity Play a Role in Electronic and Structural Properties of YBn (n=2-14) Clusters?

Nanoclusters exhibit electronic, optical, and magnetic properties that differ significantly from those of extended and molecular systems with comparable stoichiometries. In this work, we examined the structural, energetic, and electronic characteristics of yttrium-doped boron clusters (YBn,  n =2-14) with robust wavefunction analysis tools. Special emphasis is placed on the elucidation of the potential aromatic character exhibited by the resultant molecules and how it can affect their chemical bonding and stability. Our results revealed that the YBn stability is governed by the maximization of the ionic Y-B interactions. This is evidenced from the lowest-energy conformations, which manifest as half-sandwich structures wherein the majority of boron atoms are bonded to yttrium. The stabilization of such chemical contacts comes at the expense of a notorious depletion of the Y local electron density, crystallizing in a considerable ionic character, close to Y2+ + Bn2-. Such a  charge transfer is coupled to the enhancement of the electron delocalization within the YBn lattice, resulting in quite remarkable local and global aromatic characters. Altogether, this study shows how the toolkit of real space chemical bonding descriptors can offer valuable insights into the structural and electronic properties,  of YBn clusters, contributing to a better understanding of their behavior.

Explainable chemical artificial intelligence from accurate machine learning of real-space chemical descriptors.

Machine-learned computational chemistry has led to a paradoxical situation in which molecular properties can be accurately predicted, but they are difficult to interpret. Explainable AI (XAI) tools can be used to analyze complex models, but they are highly dependent on the AI technique and the origin of the reference data. Alternatively, interpretable real-space tools can be employed directly, but they are often expensive to compute. To address this dilemma between explainability and accuracy, we developed SchNet4AIM, a SchNet-based architecture capable of dealing with local one-body (atomic) and two-body (interatomic) descriptors. The performance of SchNet4AIM is tested by predicting a wide collection of real-space quantities ranging from atomic charges and delocalization indices to pairwise interaction energies. The accuracy and speed of SchNet4AIM breaks the bottleneck that has prevented the use of real-space chemical descriptors in complex systems. We show that the group delocalization indices, arising from our physically rigorous atomistic predictions, provide reliable indicators of supramolecular binding events, thus contributing to the development of Explainable Chemical Artificial Intelligence (XCAI) models.

Research note: Virtual historical archive of the Faculty of Psychology, University of Buenos Aires, Argentina.

This article describes the organization, operation, and contents of the Virtual Historical Archive of the Faculty of Psychology, University of Buenos Aires, Argentina. The organization of this archive started in 2008, as part of the activities planned by the Chair II of History of Psychology, and gained the support of the Faculty of Psychology. From its beginnings to the present, several documentary sources and materials related to the history of psychology in Argentina have been incorporated. It currently contains six thematic sections and three special collections, and it is expected that in the future it will be extended to other thematic areas. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

An Unsupervised Machine Learning Approach for the Automatic Construction of Local Chemical Descriptors.

Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry Functions (ACSFs) offer an intuitive featurization approach by means of a tedious and labor-intensive selection of tunable parameters. In this work, we implement an unsupervised ML strategy relying on a Gaussian Mixture Model (GMM) to automatically optimize the ACSF parameters. GMMs effortlessly decompose the vastness of the chemical and conformational spaces into well-defined radial and angular clusters, which are then used to build tailor-made ACSFs. The unsupervised exploration of the space has demonstrated general applicability across a diverse range of systems, spanning from various unimolecular landscapes to heterogeneous databases. The impact of the sampling technique and temperature on space exploration is also addressed, highlighting the particularly advantageous role of high-temperature Molecular Dynamics (MD) simulations. The reliability of the resulting features is assessed through the estimation of the atomic charges of a prototypical capped amino acid and a heterogeneous collection of CHON molecules. The automatically constructed ACSFs serve as high-quality descriptors, consistently yielding typical prediction errors below 0.010 electrons bound for the reported atomic charges. Altering the spatial distribution of the functions with respect to the cluster highlights the critical role of symmetry rupture in achieving significantly improved features. More specifically, using two separate functions to describe the lower and upper tails of the cluster results in the best performing models with errors as low as 0.006 electrons. Finally, the effectiveness of finely tuned features was checked across different architectures, unveiling the superior performance of Gaussian Process (GP) models over Feed Forward Neural Networks (FFNNs), particularly in low-data regimes, with nearly a 2-fold increase in prediction quality. Altogether, this approach paves the way toward an easier construction of local chemical descriptors, while providing valuable insights into how radial and angular spaces should be mapped. Finally, this work opens the possibility of encoding many-body information beyond angular terms into upcoming ML features.

Radical revelations: the pnictogen effect in linear acetylenes.

Acetylenes are essential building blocks in modern chemistry due to their remarkable modularity. The introduction of heteroatoms, such as pnictogens (X), is one of the simplest approaches to altering the C≡C bond. However, the chemistry of the resultant dipnictogenoacetylenes (DXAs) is strongly dependent on the nature of X. In this work, rigorous theoretical chemistry tools are employed to shed light on the origin of these differences, providing a detailed evaluation of the impact of X on the geometrical and electronic features of DXAs. Special emphasis is made on the study of the carbene character of the systems through the analysis of the interconversion mechanism between the linear and zigzag isomers. Our results show that second-period atoms behave drastically differently to the remaining X: down the group, a zwitterionic resonance form emerges at the expense of decreasing the carbenoid role, eventually resulting in an electrostatically driven ring closure. Furthermore, our findings pave the way to potentially unveiling novel routes for the promotion of free-radical chemistry.

Pandemic Grief and Suicidal Ideation in Latin American Countries: A Network Analysis.

This study aimed to characterize the network structure of pandemic grief symptoms and suicidal ideation in 2174 people from eight Latin American countries. Pandemic grief and suicidal ideation were measured using the Pandemic Grief Scale and a single item, respectively. Network analysis provides an in-depth characterization of symptom-symptom interactions within mental disorders. The results indicated that, "desire to die," "apathy" and "absence of sense of life" are the most central symptoms in a pandemic grief symptom network; therefore, these symptoms could be focal elements for preventive and treatment efforts. Suicidal ideation, the wish to die, and the absence of meaning in life had the strongest relationship. In general, the network structure did not differ among the participating countries. It identifies specific symptoms within the network that may increase the likelihood of their co-occurrence and is useful at the therapeutic level.

Intention to receive the monkeypox vaccine and its psychological and sociodemographic predictors: a cross-sectional survey in the general population of Peru.

OBJECTIVE: The objective of this study was to identify predictors of intention to be vaccinated against Monkeypox (Mpox) in a sample of Peruvian citizens.  METHODS: A set of sociodemographic and psychological predictors were used, such as sex, sexual orientation, educational level, previous diagnosis of COVID-19, marital status, complete vaccination against COVID-19, employment status, living with vulnerable people, presence of chronic disease, area of residence, perceived usefulness of COVID-19 vaccines, fear of Mpox, conspiracy beliefs about Mpox, among others. A total of 472 Peruvian adults participated, selected by non-probabilistic snowball convenience sampling. A sociodemographic survey, the Mpox Fear Scale, was used. Conspiracy Beliefs about Mpox was assessed using three questions created specifically for this study. For inferential purposes, simple ordinal regressions ("crude models") were performed between each factor and the outcome.  RESULTS: Regarding their intention to be vaccinated against Mpox, more than 60% expressed clear approval. Being non-heterosexual, having greater emotional fear of Mpox, and perceiving some potential for this disease to become the next pandemic were related to greater intention to vaccinate. On the other hand, being older, having low perceived usefulness of COVID-19 vaccines, and having higher conspiracy beliefs about Mpox were associated with lower intention to vaccinate.  CONCLUSION: The study provides initial information for future research seeking to better analyze Mpox vaccination intention. In addition, cross-sectional data are provided that can be used to develop public health policies that target subgroups with low prevalence of intention to vaccinate against Mpox.

Cross-cultural invariance of the Spanish version of the COVID-19 Assessment Scorecard to measure the perception of government actions against COVID-19 in Latin America.

OBJECTIVES: The present study aimed to evaluate the measurement invariance of a general measure of the perception of governmental responses to COVID-|19 (COVID-SCORE-10) in the general population of 13 Latin American countries. METHODS: A total of 5780 individuals from 13 Latin American and Caribbean countries selected by non-probabilistic snowball sampling participated. A confirmatory factor analysis was performed and the alignment method was used to evaluate invariance. Additionally, a graded response model was used for the assessment of item characteristics. RESULTS: The results indicate that there is approximate measurement invariance of the COVID-SCORE-10 among the participating countries. Furthermore, IRT results suggest that the COVID-SCORE-10 measures with good psychometric ability a broad spectrum of the construct assessed, especially around average levels. Comparison of COVID-SCORE-10 scores indicated that participants from Cuba, Uruguay and El Salvador had the most positive perceptions of government actions to address the pandemic. Thus, the underlying construct of perception of government actions was equivalent in all countries. CONCLUSION: The results show the importance of initially establishing the fundamental measurement properties and MI before inferring the cross-cultural universality of the construct to be measured.

Work, telework, and mental health during COVID-19. / Trabajo, teletrabajo y salud mental en el contexto COVID-19.

This review addresses the impact of the COVID-19 pandemic on workers' mental health, in particular, teleworking conditions. Our analysis is based on documents from several international organizations and specialized scientific publications. The retrieved information reveals that the pandemic has had a significant effect on the mental health of frontline workers and employees who had to migrate to a virtual environment without prior warning. However, a positive aspect is reflected in the development of several remote mental health care devices implemented to protect vulnerable population, frontline workers, and the general population. Finally, this paper underscores the importance of developing public policies for protecting workers' mental health.

Este trabajo abordar una reflexión sobre el impacto de la pandemia COVID19 sobre la salud mental de los trabajadores, y en particular, sobre las condiciones del teletrabajo. Para ello se recupera y analiza diferentes documentos de organismos internacionales y diferentes publicaciones científicas especializadas. De la información recuperada se señala que la pandemia no sólo ha tenido importantes efectos sobre la salud mental de los trabajadores de primera línea, sino también, sobre los trabajadores que debieron migrar repentinamente hacia los entornos virtuales, sin demasiada organización previa. No obstante, un aspecto positivo se refleja en la organización de diferentes dispositivos de atención de la salud mental remota, implementados para la atención de poblaciones vulnerables, trabajadores de primera línea y población general. Se concluye enfatizando la importancia del desarrollo de políticas públicas para la atención específica de la salud mental de los trabajadores.

Assessment of Obsessive Thoughts About COVID-19 in 7 Latin American Countries: Structure and Measurement Invariance of the Obsession With COVID-19 Scale.

The present study aimed to evaluate the measurement invariance of the Obsession with COVID-19 Scale (OCS) among seven Latin American countries: Bolivia, Brazil, Cuba, El Salvador, Guatemala, Paraguay, and Uruguay. Although the OCS has been used in several countries and languages, there is a need for approaches that better integrate the cross-cultural equivalence of the scale. A total of 3185 people participated in the study. The results indicated the presence of a unidimensional structure and good reliability indices for the OCS in each country. The alignment method indicated that the OCS is an invariant measure of COVID-19 obsession among the populations of seven Latin American countries. The findings based on IRT analysis indicated that all OCS items had adequate discrimination and difficulty parameters. The findings contribute to the understanding of the internal structure of the scale in different countries at the same time, something that has been pending evaluation.

Trabajo, teletrabajo y salud mental en el contexto COVID-19 / Work, telework, and mental health during COVID-19

Resumen Este trabajo abordar una reflexión sobre el impacto de la pandemia COVID19 sobre la salud mental de los trabajadores, y en particular, sobre las condiciones del teletrabajo. Para ello se recupera y analiza diferentes documentos de organismos internacionales y diferentes publicaciones científicas especializadas. De la información recuperada se señala que la pandemia no sólo ha tenido importantes efectos sobre la salud mental de los trabajadores de primera línea, sino también, sobre los trabajadores que debieron migrar repentinamente hacia los entornos virtuales, sin demasiada organización previa. No obstante, un aspecto positivo se refleja en la organización de diferentes dispositivos de atención de la salud mental remota, implementados para la atención de poblaciones vulnerables, trabajadores de primera línea y población general. Se concluye enfatizando la importancia del desarrollo de políticas públicas para la atención específica de la salud mental de los trabajadores.

Abstract This review addresses the impact of the COVID-19 pandemic on workers' mental health, in particular, teleworking conditions. Our analysis is based on documents from several international organizations and specialized scientific publications. The retrieved information reveals that the pandemic has had a significant effect on the mental health of frontline workers and employees who had to migrate to a virtual environment without prior warning. However, a positive aspect is reflected in the development of several remote mental health care devices implemented to protect vulnerable population, frontline workers, and the general population. Finally, this paper underscores the importance of developing public policies for protecting workers' mental health.

Relationship Between Fear of COVID-19, Conspiracy Beliefs About Vaccines and Intention to Vaccinate Against COVID-19: A Cross-National Indirect Effect Model in 13 Latin American Countries.

The present study explored the predictive capacity of fear of COVID-19 on the intention to be vaccinated against COVID-19 and the influence in this relationship of conspiracy beliefs as a possible mediating psychological variable, in 13 Latin American countries. A total of 5779 people recruited through non-probabilistic convenience sampling participated. To collect information, we used the Fear of COVID-19 Scale, Vaccine conspiracy beliefs Scale-COVID-19 and a single item of intention to vaccinate. A full a priori Structural Equation Model was used; whereas, cross-country invariance was performed from increasingly restricted structural models. The results indicated that, fear of COVID-19 positively predicts intention to vaccinate and the presence of conspiracy beliefs about COVID-19 vaccines. The latter negatively predicted intention to vaccinate against COVID-19. Besides, conspiracy beliefs about COVID-19 vaccines had an indirect effect on the relationship between fear of COVID-19 and intention to vaccinate against COVID-19 in the 13 countries assessed. Finally, the cross-national similarities of the mediational model among the 13 participating countries are strongly supported. The study is the first to test a cross-national mediational model across variables in a large number of Latin American countries. However, further studies with other countries in other regions of the world are needed.

Wave function analyses of scandium-doped aluminium clusters, AlnSc (n = 1-24), and their CO2 fixation abilities.

Nanoclusters represent a connection between (i) solid state systems and (ii) species in the atomic and molecular domains. Additionally, nanoclusters can also have very interesting electronic, optical and magnetic properties. For example, some aluminium clusters behave as superatoms and the doping of these clusters might strengthen their adsorption capabilities. Thus, we address herein the structural, energetic and electronic characterisation of scandium-doped aluminium clusters (AlnSc (n = 1-24)) by means of density functional theory calculations and quantum chemical topology wave function analyses. We studied the effect of Sc-doping on the structure and charge distribution by considering pure Al clusters as well. The quantum theory of atoms in molecules (QTAIM) reveals that interior Al atoms have large negative atomic charges (≈2a.u.) and hence the atoms surrounding them are considerably electron deficient. The Interacting Quantum Atoms (IQA) energy partition allowed us to establish the nature of the interaction between the Al13 superatom and the Al12Sc cluster with Al to form the complexes Al14 and Al13Sc, respectively. We also used the IQA approach to examine (i) the influence of Sc on the geometry of the AlnSc complexes along with (ii) the cooperative effects in the binding of AlnSc and Aln+1 clusters. We also exploited the QTAIM and IQA approaches to study the interaction of the electrophilic surface of the examined systems with CO2. Overall, we observe that the investigated Sc-doped Al complexes with a marked stability towards disproportionation reactions exhibit strong adsorption energies with CO2. Concomitantly, the carbon dioxide molecule is considerably distorted and destabilised, conditions which might prepare it for further chemical reactions. Altogether, this paper gives valuable insights on the tuning of the properties of metallic clusters for their design and exploitation in custom-made materials.

Developing a User-Friendly Code for the Fast Estimation of Well-Behaved Real-Space Partial Charges.

The Quantum Theory of Atoms in Molecules (QTAIM) provides an intuitive, yet physically sound, strategy to determine the partial charges of any chemical system relying on the topology induced by the electron density ρ(r) . In a previous work [J. Chem. Phys. 2022, 156, 014112], we introduced a machine learning (ML) model for the computation of QTAIM charges of C, H, O, and N atoms at a fraction of the conventional computational cost. Unfortunately, the independent nature of the atomistic predictions implies that the raw atomic charges may not necessarily reconstruct the exact molecular charge, limiting the applicability of the latter in the chemistry realm. Trying to solve such an inconvenience, we introduce NNAIMGUI, a user-friendly code which combines the inferring abilities of ML with an equilibration strategy to afford adequately behaved partial charges. The performance of this approach is put to the test in a variety of scenarios including interpolation and extrapolation regimes (e.g chemical reactions) as well as large systems. The results of this work prove that the equilibrated charges retain the chemically accurate behavior reproduced by the ML models. Furthermore, NNAIMGUI is a fully flexible architecture allowing users to train and use tailor-made models targeted at any atomic property of choice. In this way, the GUI-interfaced code, equipped with visualization utilities, makes the computation of real-space atomic properties much more appealing and intuitive, paving the way toward the extension of QTAIM related descriptors beyond the theoretical chemistry community.

The impact of long Covid on people's capacity to work.

This commentary addresses the post-COVID-19 syndrome and its implications for workers' health. Post-COVID-19 syndrome consists of a set of physiological and psychological symptoms resulting from SARS-CoV-2 (COVID-19) infection, which occur continuously for several weeks or months. Therefore, it is an affectation that has multiple consequences for the recovery of people's health, and compromises the ability to perform daily activities, including work, whether in person or remotely. Although several studies have been published so far, and several long-term consequences on people's health have been demonstrated, most have not adequately delved into the implications for the health of workers, their families, and the socioeconomic cost for governments. The aim of this paper is to highlight this public health issue and to encourage more specialized research.

Calculation of the ELF in the excited state with single-determinant methods.

Since its first definition, back in 1990, the electron localization function (ELF) has settled as one of the most commonly employed techniques to characterize the nature of the chemical bond in real space. Although most of the work using the ELF has focused on the study of ground-state chemical reactivity, a growing interest has blossomed to apply these techniques to the nearly unexplored realm of excited states and photochemistry. Since accurate excited electronic states usually require to account appropriately for electron correlation, the standard single-determinant ELF formulation cannot be blindly applied to them, and it is necessary to turn to correlated ELF descriptions based on the two-particle density matrix (2-PDM). The latter requires costly wavefunction approaches, unaffordable for most of the systems of current photochemical interest. Here, we compare the exact, 2-PDM-based ELF results with those of approximate 2-PDM reconstructions taken from reduced density matrix functional theory. Our approach is put to the test in a wide variety of representative scenarios, such as those provided by the lowest-lying excited electronic states of simple diatomic and polyatomic molecules. Altogether, our results suggest that even approximate 2-PDMs are able to accurately reproduce, on a general basis, the topological and statistical features of the ELF scalar field, paving the way toward the application of cost-effective methodologies, such as time-dependent-Hartree-Fock or time-dependent density functional theory, in the accurate description of the chemical bonding in excited states of photochemical relevance.

Impact of COVID-19 on quality of life in Peruvian older adults: construct validity, reliability and invariance of the COV19-Impact on Quality of Life (COV19-QoL) measurement.

The aim of the present study was to translate into Spanish and evaluate the psychometric evidence of the Impact on Quality of Life (COV19-QoL) applied to a sample of Peruvian older adults (N = 298; 58.1% women, 41.9% men, mean age 65.34 years [SD = 11.33]). The study used techniques from the Classical Test Theory (CTT) and Item Response Theory (IRT). The findings confirmed the single factor structure of the COV19-QoL, high internal consistency reliability, measurement invariance by gender, and all items demonstrated adequate discrimination and difficulty indices. In this sense, the items allow adequate discrimination between low, medium and high levels of the impact of the COVID-19 pandemic on quality of life. In addition, a greater perceived impact of the pandemic on quality of life is necessary to answer the higher response options of the COV19-QoL. In conclusion, the COV19-QoL is a valid measurement scale of the impact of the COVID-19 pandemic on the quality of life of Peruvian older adults.

Relationship Between Fear of Monkeypox and Intention to be Vaccinated Against Monkeypox in a Peruvian Sample. The Mediating Role of Conspiracy Beliefs About Monkeypox.

The present study evaluated the predictive capacity of fear of Monkeypox (MPX) on the intention to be vaccinated against MPX and the influence of conspiracy beliefs as a mediating variable in this relationship in 516 Peruvian sample with an average age of 27.10 years participated. Monkeypox Fear Scale, MPX Conspiracy Beliefs Scale and a single item of intention to be vaccinated against MPX were used. Statistical analyses have included estimation of descriptive statistics for all variables in the model tested and Structural Equation Modeling to predict intention to be vaccinated against monkeypox. It has been found that fear has a positive impact on conspiracy beliefs about MPX and intention to be vaccinated against MPX. Finally, conspiracy beliefs are negatively related to intention to be vaccinated. As for indirect effects, both are statistically significant. The model explains 11.4% of the variance in beliefs and 19.1% in intention to be vaccinated. It is concluded that fear of MPX played an important role, both directly and indirectly, in the intention to be vaccinated against MPX, having conspiratorial beliefs about MPX as a mediating variable. The results have important implications for public health practices aimed at combating doubts about MPX vaccination.