Jaume I University

The Glycerol Electrooxidation Reaction (GEOR) is a promising alternative to oxygen evolution in electrochemical processes like hydrogen production and CO2 reduction. Although GEOR has attracted increasing attention, its oxidation kinetics in alkaline media are not well understood. In this study, electrochemical characterization and kinetic analysis were conducted using nickel foil as the electrocatalyst. Four galvanostatic conditions (1, 3, 5, and 10 mA cm⁻²) were evaluated to study product distribution. Increasing the current density from 3 to 5 mA cm⁻² led to a fivefold decrease in formate production, indicating a shift in GEOR selectivity within the Oxygen Evolution Reaction (OER) region. At 10 mA cm⁻², formate remained as major product, followed by glycolate and glycerate, while tartronate and oxalate production were significantly inhibited, reducing the total Faradaic Efficiency (FE) by half relative to 5 mA cm⁻². Rate constants showed increased kinetics for glycerate, glycolate, oxalate, and tartronate as current increased, surpassing formate production at 5 mA cm⁻². Spectroelectrochemical measurements revealed the reaction order for GEOR (αGEOR ~1) and OER (αOER ~3), showing that GEOR proceeds via a more efficient oxidative pathway, requiring interaction with just one NiOOH species, while OER involves three highly oxidized Ni‐species.

This dataset presents human foot joints kinematics and kinetics data during walking, classified by static foot posture, filling a gap in existing lower limb databases that lack data on foot joints beyond the ankle or on static posture data, despite its link to foot and lower limb pathologies. Kinematics were recorded using a three-dimensional mocap system, and kinetics through a pressure platform, employing a multi-segment foot model including the ankle, midtarsal and first metatarsophalangeal joint. The dataset contains 350 recordings of right foot joint angles and moments and contact pressures from 70 healthy subjects with varying static posture (highly pronated, highly supinated and normal). Data were collected at 100 Hz, filtered and resampled to 100 frames throughout the stance phase. Descriptive data are also provided: age, weight, height, BMI and foot anthropometric data and foot posture index. Plots, tables and ANOVAs are included for validation. Presented in .xlsx and .mat formats, this database can assist professionals in corrective footwear design, insole customization, surgical planning, and evaluating interventions on foot dynamics.

In this work, 2D PEA2SnI4 (PEA: 2‐phenylethanaminium) perovskite thin films, formed with the reducing agent NaBH4 to control the Sn⁺⁴ defects are investigated. Optical characterization of the films reveals idoneous properties for the development of photon sources, particularly an extraordinarily high absorption coefficient at the exciton resonance > 10 µm⁻¹, the ability to enhance the light‐matter interaction due to the high refractive index. These linear optical properties are complemented with impressive nonlinear optical characteristics, involving a giant nonlinear absorption β = 7–10 cm MW⁻¹ and a remarkably high nonlinear refractive coefficient, n2 = 1.5–4 cm² GW⁻¹. The integration of PEA2SnI4 films into rigid and flexible waveguides further enhances the generation of waveguided photoluminescence (PL), which is also obtained under the two‐photon absorption mechanism. The efficient generation of PL is validated by the reabsorption effect, resulting in the propagation of recycled photons over distances longer than 3 mm with an increased effective lifetime from 3 to 8.5 ns. These findings pave the way for the development of novel photonic functionalities based on these innovative low‐dimensional semiconductors.

Background Extended reality (XR), encompassing technologies such as virtual reality, augmented reality, and mixed reality, has rapidly gained prominence in health care. However, existing XR research often lacks rigor, proper controls, and standardization. Objective To address this and to enhance the transparency and quality of reporting in early-phase clinical evaluations of XR applications, we present the “Reporting for the early-phase clinical evaluation of applications using extended reality” (RATE-XR) guideline. Methods We conducted a 2-round modified Delphi process involving experts from diverse stakeholder categories, and the RATE-XR is therefore the result of a consensus-based, multistakeholder effort. Results The guideline comprises 17 XR-specific (composed of 18 subitems) and 14 generic reporting items, each with a complementary Explanation & Elaboration section. Conclusions The items encompass critical aspects of XR research, from clinical utility and safety to human factors and ethics. By offering a comprehensive checklist for reporting, the RATE-XR guideline facilitates robust assessment and replication of early-stage clinical XR studies. It underscores the need for transparency, patient-centeredness, and balanced evaluation of the applications of XR in health care. By providing an actionable checklist of minimal reporting items, this guideline will facilitate the responsible development and integration of XR technologies into health care and related fields.

The behaviour of the generalized Hilbert operator associated with a positive finite Borel measure $\mu$ μ on [0, 1) is investigated when it acts on weighted Banach spaces of holomorphic functions on the unit disc defined by sup-norms and on Korenblum type growth Banach spaces. It is studied when the operator is well defined, bounded and compact. To this aim, we study when it can be represented as an integral operator. We observe important differences with the behaviour of the Cesàro-type operator acting on these spaces, getting that boundedness and compactness are equivalent concepts for some standard weights. For the space of bounded holomorphic functions on the disc and for the Wiener algebra, we get also this equivalence, which is characterized in turn by the summability of the moments of the measure $\mu$ μ . In the latter case, it is also equivalent to nuclearity. Nuclearity of the generalized Hilbert operator acting on related spaces, such as the classical Hardy space, is also analyzed.

This study investigates the conceptual metaphors employed to characterize Artificial Intelligence (AI) within online public discourse. By using a cognitive semantic approach, this investigation aims to uncover how metaphors shape social perceptions of AI, revealing the cognitive mechanisms involved in making sense of this rapidly evolving technology. An adapted version of the Metaphor Identification Procedure (MIP) has been combined with semantic frames to analyze the metaphorical mappings between the source and target frames, offering a more precise examination of the metaphors' conceptual structure. The analysis reveals a spectrum of metaphors portraying AI both as a beneficial partner and a potential threat, reflecting diverse attitudes and concerns about its integration into society. By focusing on the frame level, this study provides a fine-grained understanding of how different aspects of AI are construed through familiar conceptual frames. The findings contribute to the field of Cognitive Semantics and offer valuable insights for AI developers, educators, and communicators, emphasizing the importance of metaphors in framing society’s understanding of emerging technologies.

The impact of cognitive biases on decision-making in the digital world remains under-explored despite its well-documented effects in physical contexts. This paper addresses this gap by investigating the attractiveness halo effect using AI-based beauty filters. We conduct a large-scale online user study involving 2748 participants who rated facial images from a diverse set of 462 distinct individuals in two conditions: original and attractive after applying a beauty filter. Our study reveals that the same individuals receive statistically significantly higher ratings of attractiveness and other traits, such as intelligence and trustworthiness, in the attractive condition. We also study the impact of age, gender and ethnicity and identify a weakening of the halo effect in the beautified condition, resolving conflicting findings from the literature and suggesting that filters could mitigate this cognitive bias. Finally, our findings raise ethical concerns regarding the use of beauty filters.

Deep learning (DL) generates new computational tasks that are different from those encountered in classical scientific applications. In particular, DL training and inference require general matrix multiplications (gemm) with matrix operands that are far from large and square as in other scientific fields. In addition, DL models gain arithmetic/storage complexity, and as a result, reduced precision via quantization is now mainstream for inferring DL models in edge devices. Automatic code generation addresses these new types of gemm by (1) improving portability between different hardware with only one base code; (2) supporting mixed and reduced precision; and (3) enabling auto-tuning methods that, given a base operation, perform a (costly) optimization search for the best schedule. In this paper, we rely on Apache TVM to generate an experience-guided gemm that provides performance competitive with the TVM auto-scheduler, while reducing tuning time by a factor of 48×.

This article presents a case study of a 31‐year‐old woman with a dual diagnosis of Borderline Personality Disorder (BPD) and Eating Disorder Not Otherwise Specified (EDNOS). Paula received a 12‐month Dialectical Behavior Therapy (DBT) outpatient treatment. DBT is considered a transdiagnostic treatment approach to address emotion dysregulation, which shifts the therapy focus traditionally placed only on behavioral change toward including also validation and acceptance and dialectical strategies. DBT addresses eating symptomatology as a dysfunctional form of emotional regulation and has shown promising results regarding its efficacy for the treatment of BPD and EDNOS comorbidity. Given the growing evidence, a standard DBT treatment plan was developed for this case. Specifically, pretreatment and phase 1 of the DBT program are described. During pretreatment and phase 1, individual therapy aims to improve and maintain client's motivation to change and engage in treatment, as well as to establish and prioritize treatment goals. As for group therapy, the main goal of the skills training in DBT is to enhance individual's capability by increasing skillful behavior (mindfulness, emotion regulation, distress tolerance, and interpersonal effectiveness skills). Paula received 24 weekly skills training sessions over a year. The results after a 12‐month standard DBT treatment showed that Paula no longer met criteria for BPD, she had a significant decrease in difficulties in emotional regulation and impulsiveness and in EDNOS symptomatology. This case study may enhance learning about how to apply a transdiagnostic treatment to address BPD and EDNOS together in clinical practice.

In this study, we introduce an innovative methodology for anomaly detection of curves, applicable to both multivariate and multi-argument functions. This approach distinguishes itself from prior methods by its capability to identify outliers within clustered functional data sets. We achieve this by extending the recent AA + kNN technique, originally designed for multivariate analysis, to functional data contexts. Our method demonstrates superior performance through a comprehensive comparative analysis against twelve state-of-the-art techniques, encompassing simulated scenarios with either a single functional cluster or multiple clusters. Additionally, we substantiate the effectiveness of our approach through its application in three distinct computer vision tasks and a signal processing problem. To facilitate transparency and replication of our results, we provide access to both the code and the datasets used in this research.

Early postnatal development is a critical period for the configuration of neural networks that support social and affective-like behaviors. In this sense, children raised in stressful environments are at high risk to develop maladaptive behaviors immediately or later in life, including anti-social and aggressive behaviors. However, the neurobiological bases of such phenomena remain poorly understood. Here we showed that, at long-term, maternal separation with early weaning (MSEW) decreased the density of somatostatin-expressing (SST+) neurons in the basolateral amygdala (BLA) of females and males, while their activity was only reduced in the medial amygdala (MeA) of males. Interestingly, only MSEW males exhibited long-term behavioral effects, including reduced sociability and social novelty preference in the 3-chamber test (3CH), decreased social interest in the resident-intruder test (RI), and increased aggressivity in both the RI and the tube dominance test (TT). To test whether the manipulation of MeASST+ neurons was sufficient to reverse these negative behavioral outcomes, we expressed the chemogenetic excitatory receptor hM3Dq in MSEW adult males. We found that the activation of MeASST+ neurons ameliorated social interest in the RI test and reduced aggression traits in the TT and RI assays. Altogether, our results highlight a role for MeASST+ neurons in the regulation of aggressivity and social interest and point to the loss of activity of these neurons as a plausible etiological mechanism linking early life stress to these maladaptive behaviors in later life.

A new activity‐based probe (ABP) of cysteine proteases (FGA139) has been designed and synthesized. The design of the ABP has been done based upon the chemical structure of an irreversible inhibitor of cysteine proteases by attaching a bodipy fluorophore at the N‐terminus of the peptide backbone. The synthetic route of the probe has a metathesis and a “click” reaction as key steps. Although some studies have been reported about the role played by cysteine proteases in neurodegenerative diseases, there are not definitive conclusions. The obtained ABP has been employed as a chemical tool to profile activities of cysteine proteases cathepsins B, L, and calpain in neurodegenerative cell models through confocal imaging. Colocalization of the probe to specific antibodies of the proteases and competitive experiments with non‐fluorescent inhibitors confirm the specificity of the ABP. From a theranostic perspective, our findings strongly suggest that FGA139 exhibits a protective role in various cell lines against oxidative stress or pro‐inflammatory toxicity and it effectively attenuates macrophage activation triggered by LPS.

Tomato is a major global crop. However, its production is limited by Botrytis cinerea. Due to the toxicity of postharvest pesticide application, alternative control methods such as priming are being investigated. Plants were treated with β‐aminobutyric acid (BABA) at two developmental stages and resistance against B. cinerea was tested in fruit tissue and in progenies. DNA methylation and RNA sequencing were conducted to characterise the (epi)genetic changes associated with long‐lasting resistance. Grafting experiments were done to assess the systemic nature of this signal, which was further characterised by small RNA (sRNA) sequencing of scions. Only BABA‐treated seedlings displayed induced resistance (IR). DNA methylation analysis revealed seedling‐specific changes, which occurred in the context of lower basal methylation. BABA‐IR was found to be transmissible from primed rootstock to grafted unprimed scions. In these scions, we identified a subset of mobile 24 nt sRNAs associated with genes showing primed expression during infection in fruit. Our results demonstrate the functional association of a systemic signal with long‐lasting IR and priming. Through integrated omics approaches, we have identified markers of long‐lasting priming in tomato fruit which could also serve as targets for durable resistance in other crops.

Background/objective: In addition to obesity, adiposity and abdominal obesity (AO) are parameters included in the cardiovascular–kidney–metabolic (CKM) syndrome. However, their prevalence and association with the other CKM factors have been less studied. Our study aimed to determine the prevalence rates of AO, high waist-to-height ratio (WtHR), and excess adiposity (EA), and to compare their associations with CKM factors. Methods: A cross-sectional observational study was conducted with a random population-based sample of 6,588 study subjects between 18 and 102 years of age. Crude and sex- and age-adjusted prevalence rates of AO, high-WtHR, and EA were calculated, and their associations with CKM variables were assessed by bivariate and multivariate analyses. Results: The adjusted prevalence rates for AO, high-WtHR, and EA were 39.6% (33.6% in men; 44.9% in women), 30.6% (31.1% in men; 30.6% in women), and 65.6% (65.6% in men; 65.3% in women), respectively, and they increased with age. The main independent factors associated with AO, high-WtHR, and EA were hypertension, diabetes, prediabetes, low HDL-C, hypercholesterolaemia, hypertriglyceridemia, physical inactivity, hyperuricemia, and chronic kidney disease. Conclusions: Two-thirds of the adult population have EA, one-third have AO, and one-third have high-WtHR. These findings support that the other factors of CKM syndrome, in addition to hyperuricemia and physical inactivity, show an independent association with these adiposity-related variables.

The development of eco‐friendly indoor photovoltaics (IPVs) for Internet‐of‐Things (IoT) devices is booming. Emerging IPVs, especially those based on lead halide perovskites (LHPs), outperform the industry standard of amorphous hydrogenated silicon (a‐Si:H). However, the toxic lead in LHPs drives the search for safer alternatives. Perovskite‐inspired materials (PIMs) containing bismuth (Bi) and antimony (Sb) have shown promise, achieving indoor power conversion efficiencies (PCE) approaching 10% despite early research stages. This is promising due to their eco‐friendlier light‐harvesting layers compared to LHPs. Yet, the environmental footprint of pnictogen‐based PIM over their lifecycle remains unassessed. This study conducts a life‐cycle assessment (LCA) of the best‐performing Sb‐ and Bi‐PIMs, considering PCE, raw material availability, energy consumption, and waste generation. It is find that PCE plays a decisive role in identifying the PIM for IPVs with minimized environmental impact, namely a Bi‐Sb alloy. Extended LCA simulations for industrial‐scale processing show that the most promising Bi‐PIM has a reduced environmental burden compared to a‐Si:H. It is also explore challenges and solutions for enhancing Bi‐and Sb‐PIMs’ sustainability. Overall, this study provides the first evidence of the potential of pnictogen‐based PIMs as a sustainable IPV technology, addressing whether lead‐free PIMs are truly eco‐friendly, thus contributing toward battery‐less IoT applications.

Background The lack of training for professionals on how to manage suicide risk is an important barrier to effective intervention. Dialectical Behavior Therapy Intensive Training™ (DBT-IT) includes specific training for suicide and has shown promising results to enhance implementation of DBT. To our knowledge, no published studies have evaluated the effect of DBT-IT on therapists’ attitudes towards treating suicide risk and among Spanish-speaking mental health professionals. The main aim of this study was to evaluate the effect of DBT-IT on therapists’ attitudes regarding treating suicide risk and its relationship with the implementation of DBT before and after receiving DBT-IT. Methods A total of 242 mental health workers (76.4% women, mean age 35.38, SD = 9.17; 77.7% from Latin America; 22.3% from Spain) who had received a DBT-IT participated in the study. Self-efficacy (Efficacy in Assessing and Managing Suicide Risk Scale) and concerns (Concerns about Treating Suicidal Clients Scale) in treating suicide, perceived burnout (Copenhagen Burnout Inventory), confidence in applying DBT (Behavioral Anticipation and Confidence Questionnaire), barriers to implementation (Barriers to Implementation Inventory), implementation of DBT and reach were measured via online survey at parts 1 (pre-training) and 2 (post-training, after 9 months of implementation) of the DBT-IT. Results Differences between pre-training and post-training (n = 61) indicated statistically significant improvements in self-efficacy, concerns about the lack of training and competence in treating suicide, and confidence in applying DBT. Statistically significant increases in the rates of DBT treatment modes implementation (except for individual therapy) and mindfulness practice, as well as the number of team members and consultation team hours, were also found. Findings also indicated statistically significant positive correlations between burnout and concerns about treating suicidal clients, as well as with structural and administrative implementation barriers, and between self-efficacy in managing suicide, confidence in applying DBT and implementation of DBT treatment modes. Participants with more implementation barriers reported lower rates of consultation team meetings and phone coaching implementation.