(1) Background: This text emphasizes concerns regarding the safety of Spanish police officers at-tributed to inadequate training, employing biomechanics for the analysis and mitigation of risks during Use of Force training. The elevated global prevalence of musculoskeletal disorders under-scores the imperative for effective occupational health measures. The study concentrates on evalu-ating injury risks in novice police officers during Use of Force training. (2) Research method: The movements of police officers were captured using a Rokoko Smartsuit Pro equipped with 19 sen-sors. The Biomechanics of Bodies software processed the data, providing REBA and Marras risk scores. Statistical tests were conducted, and Operational Tactical Procedures (OTP) were inte-grated into police training. A diverse group of officers participated, categorized by training level and equipped with the Rokoko Smartsuit. (3) Results: The study evaluates police force training us-ing REBA and Marras methods. REBA scores indicate a moderate to high injury risk, suggesting effective technique design. ANOVA reveals no significant differences between training levels. Marras analysis, characterized by non-normal distribution, unveils varied risk perceptions among groups via the Kruskal-Wallis test. (4) Conclusions: The analysis of both the REBA and Marras methods implies the effectiveness of the OTP technique in reducing injury risks across dif-ferent training levels. The ANOVA test indicates no significant differences in REBA Maximum Scores between the groups. However, the Kruskal-Wallis test for Marras Probability of high-risk values suggests distinctions in medians between training levels. The combined analysis visually illustrates variations in membership regions between expert, intermediate, and novice groups.

Abstract: Mass spectrometry research laboratories reported multiple probes for ambient ionization in the last years. Combining them with a mechanical moving stage enables automated sampling and imaging applications. We developed a robotic platform, which is based on RepRap 3D-printer components, and therefore easy to reproduce and to adopt for custom prototypes. The minimal step width of the Open LabBot is 12.5 μm, and the sampling dimensions (x, y, z) are 18 × 15 × 20 cm. Adjustable rails in an aluminium frame construction facilitate the mounting of additional parts such as sensors, probes, or optical components. The Open LabBot uses industry-standard G-code for its control. The simple syntax facilitates the programming of the movement. We developed two programs: 1) LABI-Imaging, for direct control via a USB connection and the synchronization with MS data acquisition. 2) RmsiGUI, which integrates all steps of mass spectrometry imaging: The creation of G-code for robot control, the assembly of imzML files from raw data and the analysis of imzML files. We proved the functionality of the system by the automated sampling and classification of essential oils with a PlasmaChip probe. Further, we performed an ambient ionization mass spectrometry imaging (AIMSI) experiment of a lime slice with laser desorption low-temperature plasma (LD-LTP) ionization, demonstrating the integration of the complete workflow in RmsiGUI. The design of the Open LabBot and the software are released under open licenses to promote their use and adoption in the instrument developers’ community.

The life and work of Ignacio Ellacuría, S.J. is of radical vision, and revolutionary change. His dynamic life and works accompanied El Salvador and the Universidad Centroamericana through perhaps the most tumultuous years of the country’s history, yet there has been limited work done to examine his contributions. This paper shows how Ellacuría viewed the role of a Christian intellectual, and a Christian university within his philosophical and theological framework. I argue that Ignacio Ellacuría held, similarly to his soteriological views, that the intellectual must also be willing to sacrifice all for the sake of his/her work in a pattern of discipleship/martyrdom prefigured by his exemplars Christ and Socrates. It was this dedication to praxis and theory that western theology and philosophy had respectfully lost since their foundations which he sought to restore to a central role. In conclusion, the Christian intellectual and institution, according to Ellacuría, must use its voice and life in service of the people even to the point of martyrdom; he would argue, the implicit reason for Christian martyrdom and the crucifixion of Christ himself.

From June 18 to 19, 2013, the Ésera river in the Pyrenees, Northern Spain, caused widespread damage due to flooding as a result of torrential rains and sustained snowmelt. We estimate the contribution of snow melt to total discharge applying a snow energy balance to the catchment. Precipitation is derived from sparse local measurements and the WRF-ARW model over three nested domains, down to a grid cell size of 2 km. Temperature profiles, precipitation and precipitation gradient are well simulated, although with a possible displacement regarding the observations. Snowpack melting was correctly reproduced and verified in three instrumented sites, and according to satellite images. We found that the hydrological simulations agree well with measured discharge. Snowmelt represented 33% of total runoff during the main flood event and 23% at peak flow. The snow energy balance model indicates that most of the energy for snow melt during the day of maximum precipitation came from turbulent fluxes. This approach forecast correctly peak flow and discharge during normal conditions at least 24h in advance and could give an early warning of the extreme event 2.5 days before.

Predictive numerical models in the study of ground-borne vibrations generated by railway sys-tems have traditionally relied on the segmented approach of subsystems. In this approach, loads are individually applied, and the cumulative effect of rolling stock is obtained through superposi-tion. While this method serves to mitigate computational costs, it may not fully capture the com-plex interactions involved in ground-borne vibrations. Recent advancements in computational and software tools have enabled the development of more sophisticated vibrational pollution models. These advanced models encompass the entire dynamic system, from the rolling stock to the terrain, allowing for continuous simulations with a defined time step. Furthermore, the incorporation of computational contact tools between various ele-ments not only ensures temporal accuracy but also extends the analysis to the frequency domain. This paper explores the evolution of predictive numerical models in the context of ground-borne vibrations generated by trains on ballasted tracks. It highlights the shift from segmented models to continuous simulations, demonstrating the progressive advancement towards more comprehen-sive and accurate representations of railway-induced and generated vibrations in the track sur-roundings as an additional way of evaluate sustainability of infrastructures. In particular, this development of a numerical model from its inception aimed to expand upon ex-isting emission - prediction models by enriching the data with frequency-domain information. This approach has been driven by the aspiration to bridge the gap between numerical predictions and measured signals, striving for a higher level of accuracy in our obtained results. This model can predict the impact of a high-speed rail (HSR) vehicle passing on its own track. It possesses sufficient information in both the time and frequency domains to precisely characterize vibrations. This initiative marks a pivotal advancement, enabling us to more effectively capture the intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain, there's a heightened ca-pability to accurately characterize vibrations.

The emotional dimension in education has become increasingly important in recent decades. Enhancing the emotional dimension of prospective teachers in science subjects is higher education stuff responsibility. The implementation of active methodologies could modify the traditional student-teacher roles that are encouraged by the educational policies implemented in the Bologna Process. The principal aim of this work is to describe a Project Based Learning methodology and to introduce it as potential resource for the emotional and cognitive improvement of 19 prospective primary teachers enrolled in a scientific subject. This is a qualitative study with a transversal sustainability approach in the context of a research line focused on Higher Education for Sustainable Development. A questionnaire was designed and filled by the students at two different times, before and after implementation of the activity. The initial feedback from students was surprisingly enthusiastic by the fact that they were working with rockets, despite of this is not a common emotion in the science field. The results show the emotional improvement of prospective teachers after the implementation. It is concluded that a correct science education is necessary during the training of teachers taking into account their emotional dimension and the social repercussion due to the future transmission.

The COVID-19 pandemic and associated lockdown measures have been associated with substantial disruptions to health care services, including screening for human immunodeficiency virus (HIV) and management of people living with HIV (PLWH). Methods: Data from 3265 patients were examined in a retrospective cohort study. We compared outpatient follow-up for PLWH, the number of new patients, treatment adherence, hospitalizations, and deaths during the “pandemic period” (March 2020 to February 2021) to the “pre-pandemic period” (the equivalent timeframe in 2019) and the “post-pandemic period” (March to September 2021). Results: During the pandemic period, the number of new patients seen at the HIV clinic (116), as well as the requested viral load tests (2414), decreased significantly compared to the pre-pandemic (204 and 2831, respectively) and post-pandemic periods (146 and 2640, respectively)(p<0.01 for all the comparisons). However, across the three study periods, the number of drug refills (1385, 1330, 1411, respectively), the number of patients with undetectable viral loads (85%, 90%, 93%, respectively), and the number of hospital admissions among PLWH remained constant. Conclusions: Despite the COVID-19 pandemic impact, our findings show stability in the retention of clinical care, adherence to treatment, and viral suppression of PLWH, with no significant impact on hospitalization rates and all-cause mortality.

This paper introduces the novel concept of Time-Traveling Turing Machines (TTTMs) — Turing Machines with the ability to read symbols that have been explicitly sent from their future computational state. We delve into their properties and behavior, particularly emphasizing the importance of maintaining a self-consistent computational timeline. We present theorems demonstrating the universality of these machines and the challenges in achieving faster computations than traditional Turing Machines.

Abstract: Background: The periodization of physical exercise to optimize the objectives is common in competitive sports, however physical exercise programs for the older adults do not usu-ally present periodization in their programming, they are limited to carrying out similar sessions throughout the program. Methods:137 people over 60 years old performed a physical exercise program, 71 people participated in a multicomponent non-periodized program as the Control Group (CG) and 66 people participated in a program periodized in blocks as the Experimental Group (EG). The block periodization program was oriented to the development of strength, and was carried out in 86 sessions three times per week during a period of 8 months. Anthropometric assessments were made using: weight, height, BMI and electrical bioimpedance; and functional evaluations through standardized tests: SPPB, TUG, handgrip and two-minute stair test. Results: After the intervention, the EG presents significant improvements in the TUG, in the weight and in the BMI. On the other hand, the CG presents significant improvements in fat weight, in BMI and in the 2-minute stair test. The SPPB did not present changes after the intervention. Conclusion: The periodization of physical exercise for older adults does not have a significant impact on the functional capacity in this population group.

The COVID-19 pandemic has left no one indifferent: all around the globe, people have felt the massive impact of a virus that has stopped the world in its tracks. Many countries have been forced to impose strict lockdowns, causing devastating damage to the overall economy and welfare state, but also leaving an unprecedented emotional footprint on almost everyone. In this paper, we aim to quantify, by building our own method how, this pandemic has affected people emotionally by detecting the shifts in the emotional profile of representative users in selected countries. Our method processes the social media stream adapting the Pleasure-Arousal-Dominance (PAD) approach to measure emotional states on the Russell Circumplex plane, allowing for not only an overall emotional shift quantification but also a detailed analysis at mood level. By focusing on certain emotions and searching behavior, we establish a relationship between the pandemic and the emotional response. Although the method can be applied to any location with a significant and varied amount of geo-localized social media streams, the scope of this paper covers the most representative cities in Europe.

The acoustic environment in learning spaces significantly influences learning effectiveness and occupant well-being. Recent studies have shown that a series of architectural factors within physical learning environments can impact students' educational experiences. This research delves into the relationship between architectural characteristics and the perceived acoustic environment among 467 primary students in 19 learning spaces across 9 schools in Chile. The survey comprises a student questionnaire, a checklist evaluating space characteristics, and acoustic measurements of indoor noise levels during occupied conditions. Examined topics include Indoor Environmental Quality (IEQ) comfort perception, noise annoyance, hearing ability, and acoustic preference. Architectural characteristics considered encompass flexible and acoustic space design parameters. The results indicated that noise discomfort was a common issue, especially in traditional learning spaces without acoustic treatment. The type of learning space (traditional or flexible settings) has a greater impact on acoustic perception particularly concerning noise discomfort and acoustic preference. However, poorly acoustic spaces lacking absorbing materials or exhibiting lower spatial density (m2 per student) contribute to increased indoor noise levels affecting noise annoyance caused by children's talking inside. The study emphasizes the importance of considering both architectural design and acoustic conditioning for optimizing the acoustic experience in educational spaces.

Consumers are attracted by the increasing number of available SVOD platforms, but subscribing to all of them would be too expensive. To reduce costs, consumers could combine the use of proprietary subscriptions, non-proprietary subscriptions, and illegal streaming sites. In turn, platforms could enforce access control, a decision that could produce the desired reduction in non-proprietary subscriptions but also an undesired reduction in proprietary subscriptions. The effects of this decision and the determinants of SVOD content demand remain largely unexplored. We propose a baseline model where the SVOD content demand is driven by variety seeking, household financial situation, ethical evaluation, and social norms, as well as a change model where the subscription variation is driven by users’ trait reactance and perceived fairness of the decision. We conducted a survey on the current ways of SVOD content consumption and the responses to a hypothetical access control enforcement, with four randomized versions of the authentication mode. Results confirmed many of the proposed determinants and showed a noteworthy reduction in proprietary subscriptions due to the control enforcement but no effect due to the authentication modes. All these findings may help improve future models on SVOD content consumption and better address the difficult challenge of converting unauthorized users into authorized ones.

Tomography based on cosmic muon absorption is a rising technique because of its versatility and its consolidation as geophysics tool over the past decade. It allows to address major societal issues such as long-term stability of natural and man-made large infrastructures or sustainable underwater management. Traditionally, muon trackers consist of hodoscopes or multilayer detectors. For applications with challenging available volumes or wide field of view required, a thin time projection chamber (TPC) associated with a Micromegas readout plane can provide a good tradeoff between compactness and performance. This paper details the design of such a TPC aiming at maximizing primary signal and minimizing track reconstruction artifacts. The results of the measurements performed during a case study addressing the aforementioned applications are discussed. The current works lines and perspectives of the project are also presented.

Pore Forming Toxins (PFTs), formed mainly by virulence factors of bacteria, belongs to Pore Forming Protein (PFP) family. Secreted as soluble monomers, they bind specific targets in membranes where their oligomerization and insertion place. Lysenin, a member of the PFTs, forms and oligomer after sphingomyelin binding, the so-called prepore, which become inserted forming a pore after a conformational change triggered by a pH decrease. In crowded conditions, oligomers tends to stay in prepore form because the prepore-to-pore transition is sterically blocked. In this study, we investigate the effect of calcium ions in those crowded conditions, finding that calcium act as a trigger for lysenin insertion. We localize the residues responsible for calcium sensitivity in a small α-helix. Our results are not only one of the few complete structural descriptions of prepore-to-pore transitions but the very first that involves a calcium triggering mechanism. The presence of glutamic or aspartic acids in the insertion domains could be an indication that calcium may be a general trigger for PFTs and more generally PFP.

This essay studies Afro-Asian sociocultural interactions in cultural production by or about Asian Latin Americans, with an emphasis on Cuba and Brazil. Among the recurrent characters are the black slave, the china mulata, or the black ally who expresses sympathy or even marries the Asian character. This reflects a common history of bondage shared by black slaves, Chinese coolies, and Japanese indentured workers, as well as a common history of marronage. These conflicts and alliances between Asians and blacks contest the official discourse of mestizaje (Spanish-indigenous dichotomies in Mexico and Andean countries, for example, or black and white binaries in Brazil and the Caribbean), which, under the guise of incorporating the Other, favored whiteness, all the while attempting to silence, ignore, or ultimately erase their worldviews and cultures.

Pimobendan is an inotropic and vasodilator drug with no sympathomimetic effects. This study aimed to evaluate the haemodynamic effects of pimobendan during anaesthesia in healthy senior dogs. A prospective, randomised, triple-blinded, placebo-controlled clinical study was conducted. Thirty-three dogs (median [range]: 9 [7, 12] years) were anaesthetised for surgical procedures. Dogs were randomly allocated into two groups: eighteen dogs received pimobendan 0.15 mg kg-1 IV (PIMOBENDAN) and 15, saline solutions 0.2 ml kg-1 IV (PLACEBO). Data were recorded before, 1 minute, 10 minutes and 20 minutes after injection. Velocity-time integral (VTI), peak-velocity (PV) and mean-acceleration (MA) were measured using an oesophageal Doppler monitor (ODM). Heart rate and mean arterial pressure were also registered. Data were analysed using a two-way ANOVA for trimmed means. Statistical differences were considered if p &lt; 0.05. Twenty minutes after injection, VTI (13.0 cm [10.4, 22.3]), PV (95.0 [83.0, 160] m sec-1), and MA (12.6 [9.40, 17.0] m sec-2) were higher in PIMOBENDAN when compared to PLACEBO (VTI: 10.5 [6.50, 17.4] cm, PV: 80.0 [62.0, 103] m sec-1 and MA: 10.2 [7.00, 16.0] m sec-2). No differences were observed in the rest of the variables. Using pimobendan during anaesthesia increases VTI, PV and MA measured by an ODM.

With the developments of smart technologies, the use of rare earth elements (REEs) knows a widespread use, thus, their importance as valuable and strategic metals boosted to levels never known before. Due to their scarcity in Earth crust, the recovery of these elements from secondary resources also knows further developments. Traditional pyrometallurgical and hydrometallurgical processing, though of wide use, in the recovery of these REEs, have some environmental drawbacks, thus, the development of new recovery approaches are under developments. Here, Solvometallurgy appeared as a friendly environmental technology, and ionic liquids and deep eutectic solvents re-sulted as a first-row chemicals to be used in the different unit operations used in solvometallurgical processing: leaching, liquid-liquid extraction, ion exchange (adsorption), precipitation and elec-trolysis. This manuscript reviewed the most recent literature concerning the use of ionic liquids and deep eutectic solvents in the recovery of REEs from various sources.

Sentinel-2 provides the opportunity to map the snow cover at unprecedented spatial and temporal resolution at global scale. Here we calibrate and evaluate a simple empirical function to estimate the fractional snow cover (FSC) in open terrain using the normalized difference snow index (NDSI) from 20 m resolution Sentinel-2 images. The NDSI is computed from flat surface reflectances after masking cloud and snow-free areas. The NDSI-FSC function is calibrated using Pléiades very high resolution images and evaluated using independent datasets including SPOT 6/7 satellite images, time lapse camera photographs, terrestrial lidar scans and crowd-sourced in situ measurements. The calibration results show that the FSC can be represented with a sigmoid-shaped function 0.5×tanh(a×NDSI+b)+0.5 where a = 2.65 and b = -1.42 yielding a root mean square error of 25%. Similar RMSE are obtained with different evaluation datasets with a high topographic variability. With this function, we estimate that the confidence interval on the FSC retrievals is 38% at the 95% confidence level.

Endocrine therapy (ET) has established itself as an efficacious treatment for estrogen receptor-positive (ER+) breast cancers, with a reduction in recurrence rates and increased survival rates. The pre-surgical approach with chemotherapy (NCT) has become a common form of management for large, locally advanced or high-risk tumors. However, a good response to NCT is not usually expected in ER+ tumors. Good results with primary ET, mainly in elderly women, have encouraged studies in other stages of life, and nowadays neoadjuvant endocrine treatment (NET) has become a useful approach to many ER+ breast cancers. The aim of this review is to provide an update on the current state of art regarding the present and the future role of NET.

The use of probiotics in reproductive-related dysbiosis is an area of continuous progress due to the growing interest from clinicians and patients suffering recurrent reproductive microbiota disorders. An imbalance in the natural colonization sites related to reproductive health: vaginal, cervicovaginal, endometrial and also pregnancy-related altered microbiota could play decisive role in reproductive outcomes. Oral and vaginal administrations are in continuous discussion regarding the clinical effect pursued, but probiotics as oral supplement therapy is the route administration better studied. To complement and summarise with qualitative and quantitative information of vaginal probiotics clinical studies, the main objective of this work was to retrieve the standardised protocols commonly used and their microbiota modulation capacities. The studies selected were related to treat bacterial vaginosis (BV) as the most commonly disorder, few studies on vulvovaginal candidiasis (VVC) and also administration to stabilise microbiota before in vitro fertilisation (IVF). Probiotic doses administered were similar to oral probiotics protocols, ranging from ≥ 107 CFU/day to 2.5 x 1010 CFU/day, and variable regarding posology duration from 1 day to 12 weeks, being 1 week commonly applied. Moderate modulation was achieved regarding the relative abundance decrease of abnormal microbiota, coinciding with parallel increase in Lactobacillus species.

This work is a review of the current situation of type 1a diabetes mellitus in childhood. With a quick read, the reader will discover the current and immediate future challenges.

Natural deep eutectic solvents (NADES) have been shown as selective and environmentally friendly solvents for the extraction of bioactive compounds. However, studies on the solubility of low molecular weight carbohydrates (LMWC) in NADES are scarce. In this work, new solubility data of LMWC in NADES are provided and a new approach based on the use of these solvents for the efficient fractionation of bioactive carbohydrates was explored for the first time. Several mono- and disaccharides and three NADES based on choline chloride (ChCl) and different donors [2-ethylene glycol (EtG), glycerol (Gly) and ethanedioic acid dihydrate (Eth)] were considered. While degradation of carbohydrates, mainly ketoses, was detected with ChCl:Eth due to its acidic nature, ChCl:EtG and ChCl:Gly were found to be useful alternatives for selectively separating bioactive ketoses and their corresponding aldoses (e.g. lactulose/lactose and tagatose/galactose) present in equimolar binary mixtures. In addition, the usefulness of ChCl:EtG for the selective enrichment of lactulose to be used as food ingredient or nutraceutical was proven (from a 25% in the reaction mixture to a 56% in the purified sample). NADES could be used for the selective fractionation of value-added carbohydrates from interfering sugars for several applications including food science, engineering or pharmaceuticals.

As a model for economic and ecological systems, replicator dynamics represents a basic form of agent competition for finite resources. Here, we investigate the effects of stochastic resetting in this kind of processes. Random reset events abruptly lead individual resources to a small value from which dynamics must start anew. Numerical results show that resource distribution over the population of competing agents develops highly nonuniform profiles, exhibiting clustering and fluctuations with anomalous dependence on the population size. This non-standard statistical behavior jeopardizes an analytical treatment based on mean-field assumptions. We propose alternative simplified analytical approaches which provide a stylized description of entropy evolution for the clustered distribution of resources and explain the unusually slow decrease of fluctuations.

Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease that affects the nervous system. Peripheral blood leukocyte telomere length (LTL) and mitochondrial DNA copy number (mtDNA-CN) are potential biomarkers of disability and neurological damage. The present work evaluated LTL and mtDNA-CN in 75 relapsing-remittent MS (RRMS) patients 50 of whom had an Expanded Disability Status Scale (EDSS) 0 to 3 (mild-moderate disability), and 25 had an EDSS of 3.5 to 7 (severe disability). Absolute LTL and absolute mtDNA-CN were measured via real-time polymerase chain reaction (qPCR). The LTL and mtDNA-CN were significantly lower in RRMS severe disability than in RRMS mild-moderate disability (3.924 ± 0.124 vs 2.854 ± 0.092, p<00001; 75.14 ± 1.77 vs 68.06 ± 1.608, p<0.00001, respectively). The LTL and mtDNA-CN showed a linear correlation in RRMS with mild-moderate disability (r=0.2986, p=0.0351). In addition, in a binary logistic regression model the LTL can predict severe disability (AUC=0.697, p=0.0031, cutoff ≤ 3.0875 Kb, sensitivity= 73.1%, specificity=62.5%), the prediction is improved by including age to the model (AUC=0.765, <0.0001, sensitivity=78.26%, specificity=81.25%). Aging is closely linked to the development of disability in RRMS and can be evaluated through LTL and mtDNA-CN absolute quantification.

⦁ Introduction: The challenging context, resulting from a post-pandemic scenario, wars, and various natural disasters, does not allow for the ideal assurance of efficiency in the Agri-food supply chain. ⦁ Research significance Currently, Agri-food supply chains and Reverse logistics show critical characteristics such as centralization, limited flexibility, distrust, bureaucratization, Border and Documentary Compliance and there are problems about efficiency, security, and safety Agri-Food. using the Supply Chain Operations Reference (SCOR) framework, with the purpose of achieving Sustainable Development Goals, promoting transparency, traceability, and non-linearization of the agri-food supply chain. ⦁ Methodology The methodology is combined, the first part uses Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) identifying 72 articles with the principal contribution in the literature. The second part combines the application of Supply Chain Operations References (SCOR) and the Blockchain Technology aiming to decentralize the linear Agri-food Supply Chain and Reverse logistics. ⦁ Results/findings The results revealed a transformation of the traditional Agri-food Supply Chain, transitioning from linear management to a circular one. Additionally, after application it is possible to know a new way to manage the Reverse Logistic with more decentralization, flexibility, traceability, and reducing the unnecessary activities, which include Border and Documentary Compliance. The originality of this research is the novel combination of SCOR Model and Blockchain showing a priority about the key activities that add value and come close to the Sustainable practices. ⦁ Conclusion / Implications Based on the results is possible to conclude that the synergy between Blockchain and SCOR Model enables a new way to manage the Agri-food supply chain, improving efficiency and reducing activities without value. Also, it is possible to ensure that the practices of Reverse Logistics are improved based on terms of cost and time, and the reduction of the exposition on the Defective Product Risk. ⦁ Social Implications This paper could enhance confidence in all operations of the Agri-food supply chain as there are numerous issues regarding the security and safety of food. Additionally, it will aid in diminishing unnecessary activities and inefficient resource consumption practices, thereby accomplishing objectives 2 "zero hunger", 9 "Industry, Innovation, and Infrastructure", and 12 "Responsible consumption and production", along with their respective indicators. ⦁ Practical implications Regarding the practical implications, this research could contribute to analyses of the application of technology Blockchain in different sectors and identify the possible limitations when the main objective is to apply it on a big scale.

A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) has been designed. It is applied to a shape memory alloy (SMA) actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according data collected online during the first seconds of~therapy sessions. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the position reference pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm has been tested in simulations and with healthy people for control of an elbow exoskeleton in flexion–extension movements. The results indicate that sEMG signals from elbow muscles in combination with pressure sensors that measure arm–exoskeleton interaction can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according a patient's intention.

Social media has become the most influential battleground for political and societal debate. The reach, the speed, and the fact that everybody can participate make this medium very popular but also highly manipulative, subject to biases and extremely precious to control. Misinformation spreads in an unforeseeable way. Sometimes it just follows usual non-malicious social interaction patterns, but often a targeted and designed-for-purpose manner. In this paper, we propose a novel method to identify the most effective opportunities to moderate the social media debate at a large scale using the properties of social signed graphs, such as structural balance. After building the topic universe for a particular political debate in a given time frame, we extract the most active and influential users and mine their position regarding the topic based on their interactions with other users. The result is a signed graph where each edge represents either support or challenge between a pair of users in the context of the topic. This graph can be modelled as an Ising model, with the goal of minimizing its energy state by using the advantages of Adiabatic Quantum Computing. Applying this principle, we use a Quantum Annealing implementation to solve the problem of finding the edges violating the structural balance of this graph, which in classic computing is known to be an NP-hard problem. We then provide a non-intrusive moderation technique for those violations to mitigate or increase the structural imbalance, depending on the desired strategy. The methodology is shown in the context of the COVID-19 skeptics’ debate in Twitter and implemented using a D-Wave 2000Q-6 quantum annealer.

Plant-based alternative medicine is normally grounded on empiric cultural perception, as the main objective, these practices intent to either maintain good health or to provide a route to turn-the-tide on a specific disease or ailment. Amongst the thousands of plants that have been used and studied, Neem (Azadirachta indica) seems to have a very interesting tale to tell, since its properties to ward-off certain diseases have overtime, and in a rigorous way, been proven. The preceding concise review is a collection of some of the most relevant studies today, not only focusing on the health benefits obtained by its use, but digging into the molecular mechanisms of how the properties come about. In particular, we take a look over antioxidant properties and how these mediate and mitigate important molecules such as IL-6 and TNF-, leading the way in reducing systematic damage by oxidative stress. Further, we relate this oxidative reduction to other systemic diseases such as cancer and diabetes, as these are currently becoming the most rampant killers. As of yet not all is known about the different ways of extracting or the total composition of an extract, as these may be from different parts of the plant. Therefore, we also allude to an important cautionary view where toxicological effects and conflicting outcomes arise. Overall, presented results show a great potential for the different extracts of Neem as their antioxidant activity can be taken advantage off, and potentially used in modern medicine.

In this paper, we introduce a model for the automatic generation of literary sentences in French. It is based on algorithms that we have previously used to generate sentences in Spanish and Portuguese, and on a new corpus consisting of literary texts in French that we have constructed, called [FR]. Our automatic text generation algorithm combines language models, shallow parsing and deep learning, artificial neural networks. We have also proposed and implemented a manual evaluation protocol to assess the quality of the artificial sentences generated by our algorithm, by testing if they fulfill four simple criteria. We have obtained encouraging results from the evaluators for most of the desired features of our artificially generated sentences.

Study of micro-RNA regulatory networks (known as miRNA’s or miR’s), during development and in known pathologies have been the basis of study over the past decades. Herein, we recapitulate these findings in order to highlight the best underlying mechanisms found to date. We also seek to elucidate how miRNA dysregulation can be associated with many cardiovascular diseases. Furthermore, we discuss miR regulation mechanism during in early development in vivo and invitro. Since many of the miR’s are precursors to transcriptional regulation, we relate back to their molecular control as we can then look together at the fundamental disease they might be exacerbating by this dysregulation.

The Mexican Soil Mesh (MSMx) web service emerges as a pivotal tool for researchers, farmers, and policymakers in the efficient management of extensive soil databases. Built on a responsive and intelligent web design, MSMx synchronizes seamlessly with the SQL language, allowing users to selectively download variables tailored to their studies at the desired spatial scale. The programmatic structure enhances query speed, optimizes development times, and incorporates satellite programming modules for effective handling of the vast soil dataset. This paper high-lights the key features, benefits, and applications of MSMx, emphasizing its role in facilitating data-driven decision-making processes and promoting sustainable soil management practices on the continental shelf of Mexico.

Discriminatory attitudes towards people living with HIV/AIDS are prevalent. A Joint United Nations Program on HIV/AIDS report (2019) indicated that more than 50% of the people surveyed in one of the studies spanning 26 countries expressed unfavorable attitudes towards HIV-positive people. The objective of this study was to assess the attitudes of senior Education Studies students at a university in Spain towards people with HIV/AIDS so as to propose specific educational interventions. The study employed a quantitative methodological approach; a questionnaire with a 14-item attitude score served as the analytical instrument. The study sample comprised 613 students from the School of Education at the University of Huelva, Spain. The results showed that more than 50% of the School’s senior students had discriminatory attitudes towards HIV-positive people, some of whom were fellow classmates. This study proposes several formative approaches to reducing the stigma suffered by HIV-positive people, while also improving senior students’ skills and capabilities in the field of health promotion.

This paper applies a new artificial intelligence architecture, the Temporal Fusion Transformer (TFT), for the joint GDP forecasting of 25 OECD countries at different time horizons. This new attention-based architecture offers significant advantages over other deep learning methods. First, results are interpretable since the impact of each explanatory variable on each forecast can be calculated. Second, it allows to visualize persistent temporal patterns and to identify significant events and different regimes. Third, it provides quantile regressions and permits to train the model on multiple time series from different distributions. Results suggest that TFTs outperform regression models, especially in periods of turbulence such as the COVID-19 shock. Interesting economic interpretations are obtained depending on whether the country is domestic demand-led or export-led growth. In essence, TFT is revealed as a new tool that artificial intelligence provides to economists and policy makers, with enormous prospects for the future.

Conducting an accurate hydrological water balance at the regional and country-wide scales is paramount to assessing available water resources and adequately allocating them. One of the main components of these balances is the anthropogenic recharge of groundwater either intentionally, through managed aquifer recharge (MAR), or unintentionally, where infiltration from dams and dykes can play a significant role. In Spain, proper management of water resources is critical due to the arid to semiarid conditions prevalent in most of the territory and the relevance of water resources for maintaining a robust agricultural sector. Spanish Previous work has estimated country-wide recharge from MAR at 150-280 Mm3/year. Recently, water authorities have pointed out that, according to hydrological water balances, the total volume from "unintentional recharge" from water courses may exceed 500 Mm3/year. The present research aims to present a new inventory of transverse structures in Spain and use it to estimate country-wide unintentional recharge. The inventory, compiled by the Spanish Ministry for the Ecological Transition and the Demographic Challenge, has more than 26,000 structures and includes construction characteristics, which allow for estimating the wet perimeter and the infiltration area. Structural data from the inventory was crossed through map algebra with thematic layers, such as lithology, permeability, the digital elevation model, the average groundwater levels, etc., in a GIS environment to arrive at the objective. Different analytical formulas to compute infiltration from small dams and dykes were also employed. The resulting volume of unintentional recharge from transverse structures in Spain is about 800 Mm3/year. This quantity can help close the hydrological balance at the national and river basin levels. Furthermore, this figure provides an order of magnitude for anthropogenic recharge at a national scale, which is difficult to obtain.

Nowadays, inherently safer designs are considered as key priorities to prevent or mitigate serious incidents with devastating consequences. The need for process safety assessment during early design phases has motivated the development of several contributions related to computer-aided assessment methodologies in order to measure the inherent safety of chemical processes. In this work, the large-scale production of chitosan from shrimp wastes was evaluated from process safety point of view using the numerical descriptive inherent safety technique (NuDIST).To this end, simulation of the chitosan production was performed using Aspen Plus ® to obtain extended mass and energy balances. The assessment of all the chemicals involved within the process was carried out for the following safety parameters: explosivity (EXP), flammability (FL) and toxicity (TOX). The safety assessment of the process included the parameters of temperature (T), pressure (P) and heat of reaction (HR). The maximum chemical safety score was estimated in 171.01 with ethanol as main contributor to the parameter of explosivity and flammability. The score associated with operating data was calculated in 209.30 and heat of reaction reported to be the most affecting parameter. The NuDIST score was estimated in 380.30. This NuDIST value revealed the low hazards associated with the handling of substances such as shrimp wastes, chitosan and water, as well as the non-extreme temperature and pressure conditions. In general, the large-scale production of chitosan from shrimp shells showed to be an inherently safe alternative of waste valorization.

A significant part of the literature on innovative practice in medicine relates to seizing opportunities and curbing harms for patients in desperate situations. Unfortunately, the term innovation has multiple meanings and a rich rhetorical flourish that adds confusion and misunderstanding to an already difficult debate. This paper aims to enhance the current definition of innovative practice for medicine. First, we replace the term innovation with the more literal of new non-validated practice. To identify this meaning, we analyse the traditional research ethics’ distinction between research, validated practice, and innovation in the Belmont Report. Second, we propose the following explicit definition of new non-validated practice: the first or recent use of diagnostic, therapeutic or preventive interventions that introduce a significant change, with an insufficient level of evidence of safety or efficacy for regular healthcare, and with the main aim to benefit individual patients. This definition is a promising conceptual tool to inform empirical research, ethicists, and the harmonization of its regulation and legislation (e.g. right-to-try laws).

The paper discusses the experience of implementing an efficient economic management system at the University of Vigo in Spain. This system, which focuses on managing secondments, aims to minimize bureaucracy and standardize economic procedures for various staff groups. By adopting a qualitative methodology and utilizing content analysis, the study compares the University of Vigo's fully digital administrative procedure with other universities in the CRUE network. The results show significant time and cost savings due to this implementation. The improved traceability and information for users support the administrative change, and the positive environmental impacts highlight the commitment to a more sustainable approach. The paper's originality lies in demonstrating how this approach enhances efficiency, reduces costs, and improves sustainability within a Spanish public administration setting.

The development of biofuels and biodiesel industry specifically, has resulted in the generation of large amounts of glycerol as a surplus. The conversion of glycerol, into chemicals with indus-trial interest, through anaerobic fermentation using E. coli as a biocatalyst is an attractive alter-native to improve economic performance in the biodiesel industry, for example through the bi-otransformation of residual glycerol into ethanol. For 2019, the size of the global ethanol market was valued at $ 89.1 billion US dollar. Biodiesel can be produced from several materials like rapeseed, palm, soya, corn, palm kernel, frying oil or olive-pomace oil (OPO). The last, can be extracted from alperujo, byproduct of olive oil process. However, olive-pomace oil converting into biodiesel is not enough established to achieve a global olive-oil/biodiesel derived process with minimized waste generation. Traditionally biodiesel production process produces an equivalent of 10% by mass of glycerol as a waste or by-product. This work explores the conver-sion of residual glycerol into chemicals like ethanol and hydrogen with a focus on projecting raw material potential availability from OPO, contributing to the promotion of the use of biofu-els and biodegradable compounds.

Deep Learning (DL) has made significant advances in computer vision with the advent of Vision Transformers (ViT). Unlike Convolutional Neural Networks (CNNs), ViTs use self-attention to extract both local and global features from image data, and then use residual connections to feed these features directly into a fully networked multilayer perceptron head. In hospitals, hematologists prepare peripheral blood smears (PBSs) and read them under a medical microscope to detect abnormalities in blood counts such as leukemia. However, this task is time-consuming and prone to human error. This study investigates the transfer learning process of Google ViT and ImageNet CNNs to automate the reading of PBSs. The study used two online PBS datasets, PBC and BCCD, and transferred them into balanced datasets to investigate the influence of data amount and noise immunity on both neural networks. The PBC results show that Google ViT is an excellent DL neural solution for data scarcity. The BCCD results show that Google ViT is superior to ImageNet CNNs in dealing with unclean, noisy image data because it is able to extract both global and local features and use residual connections, despite the additional time and computational overhead.

This paper aims to establish a current relationship between pharmaceutical sciences and the development of perfumes and fragrances, which bring significant economic benefits and whose added value is among other professionals, the one made by professionals in Pharmacy. For this purpose, historical data are used as a starting point and galenic, chemical and botanical aspects are discussed in a transversal way. In this sense, it must be taken into account that in the case of Spanish pharmacy, it is closely linked to the knowledge and use of plants. Sources such as Web of Science (WOS) and databases such as Scopus, monographs and various web pages (where scientific-technical documents appear) have been used. The results and discussion are based on the selection of the 50 plant species most commonly used in high quality fragrances. Therefore, this publication should be considered as an approach to this subject based on an analysis of a representative sample of data. Some characteristics of perfumes (classification according to the concentration of essential oils and combination of plant extracts) are presented beforehand. They also briefly compile the traditional and modern ways in the treatment of these extracts. The main focus of this work is the botanical and chemical analysis of these described plants, pointing out their common name, correct botanical name, geographical place of origin, used part of the plant and main molecules. The 50 botanical species belong to 27 families of angiosperms and are represented in a large part of the phylogenetic tree of botanical systematics. The most significant families are aromatic: Rutaceae (16.7%), Lamiaceae (16.7%) and Apiaceae (6.5%). The most represented genus is Citrus (with seven species or hybrids). However, it should be noted that natural extracts of good quality natural fragrances may be supplemented with chemically synthesized molecules. Of the 50 botanical species selected, 84% of the extracts have their origin in Tropical Asia, the Middle East and the Mediterranean region. This figure generally coincides with the percentage of medicinal plants (or their extracts) admitted by the European Pharmacopoeia. All parts of a plant (depending on which one it is) can be a source of molecules for the elaboration of these products. The most commonly used parts to obtain extracts are flowers (34%) and leaves (30%), a biological circumstance that is explained in this work. On the opposite side are the resins (10%), rhizomes and roots (8%). In this work, 110 molecules have been found that are part of the essences of perfumes and fragrances, the most frequent are: linalool, limonene, 1,8-cineole, eugenol and derivatives, geraniol, vanillin and derivatives, β-cariophyllene, p-cmene and farnesene and derivatives (3.64%). However, in order to elaborate a quality perfume, many other molecules must be taken into account, according to the creative experience of the perfumer, which is subject to confidentiality and chemical analysis according to current legislation, which would avoid fraud, allergy and dermatitis problems.

The transformation of the state of polarization of a light beam by its linear interaction with a material medium can be modeled through the Stokes-Mueller formalism. The Mueller matrix associated with a given interaction depends on many aspects of the measurement configuration. In particular, different Mueller matrices can be measured for a fixed material sample depending on the spectral profile of the light probe. For a given light probe and a given sample with inhomogeneous spatial behavior, the polarimetric descriptors of the point-to-point Mueller matrices can be mapped leading to respective polarimetric images. The procedure can be repeated sequentially by using light probes with different central frequencies. In addition, the point-to-point Mueller matrices consecutively measured can be combined synthetically through convex sums leading to respective new Mueller matrices, in general with increased polarimetric randomness, thus exhibiting specific values for the associated polarimetric descriptors, including the indices of polarimetric purity, and generating new polarimetric images which are different from those obtained from the original Mueller matrices. In this work, the fundamentals for such synthetic generation of additional polarimetric images are described, providing a new tool that enhances the exploitation of Mueller polarimetry.

Parallel decompositions have proved to be powerful tools for the analysis and interpretation of the physical information provided by Mueller matrices experimentally obtained. In this work, the procedure for the so-called arbitrary decomposition of Mueller matrices is validated through its application to a set of representative experimentally determined Mueller matrices. The covariance and passivity criteria required for the physical realizability of the Mueller matrices involved in the parallel decompositions are integrated in the procedure, which ensures the physical consistency of the results presented.

The importance of rare earth elements as the basis in the development of new technologies or the improvement of the used ones, made of a necessity its recovery, besides that from raw materials, from waste materials. In this recovery, Hydrometallurgy and its derivative Solvometallurgy, play a key role due to its operational characteristics, which are emphasized with the use of ionic liquids. The manuscript reviewed the most recent advances (2023 and 2024 years) about the use of ionic liquids in the unit operations (leaching and separation technologies) aimed to the recovery of these valuable and strategic metals. Moreover, a comprehensive review about the use of these chemicals in the development of advanced materials containing some of these rare earth elements is presented.

The paper proposes, through an experimental method, a conceptualisation of theoretical-methodological and practical guidelines for the project on the system of collective open spaces, residual areas, abandoned areas that characterise the contemporary city, both in the urban contexts of the historical city, and in the more marginal areas of the modern suburbs. This methodology was experimented on an historical neighbourhood in Rome (San Lorenzo discrict) starting from the results of some researches conducted in collaboration between Sapienza University of Rome and the Escuela de Architettura, Universidad San Jorge and some design experiments conducted by Gràvalosdimonte design studio. This methodology and experimentation combines the theme of the inter-scalarity of the project (territorial, urban and local scale) with the themes of the flexibility and proximity of functions with respect to local instances and contingencies caused by the pandemic situation and by the sustainability perspectives, with particular reference to the need for urban health, the dialectic between public and private space in the perspective of the notion of common good, the bottom-up project for the construction of proximity spaces and plurality in the decision-making process.

The New World (NW) mammarenavirus group includes several zoonotic highly pathogenic viruses, such as Junin (JUNV) or Machupo (MACV). Contrary to Old World mammarenavirus, these viruses are not able to completely suppress the innate immune response, and trigger a robust interferon (IFN)-I response via retinoic acid-inducible gene I (RIG-I). Nevertheless, pathogenic NW mammarenaviruses trigger a weaker IFN response than their non-pathogenic relatives do. RIG-I activation leads to upregulation of a plethora of IFN-stimulated genes (ISGs), which exert a characteristic antiviral effect either as lone effectors, or resulting from the combination with other ISGs or cellular factors. The dsRNA sensor-protein kinase receptor (PKR) is an ISG that plays a pivotal role in the control of the mammarenavirus infection. In addition to its well-known protein synthesis inhibition, PKR further modulates the overall IFN-I response against different viruses, including mammarenaviruses. For this study, we employed Tacaribe virus (TCRV), the closest relative of the human pathogenic JUNV. Our findings indicate that PKR does not only increase IFN-I expression against TCRV infection, but also affects the kinetic expression and the extent of induction of Mx1 and ISG15 at both levels, mRNA and protein expression. Moreover, TCRV fails to prevent the effect of PKR on viral protein translation and its viral titer is inhibited when PKR is pre-stimulated via IFN-I. Here, we provide first evidence of the specific immunomodulatory role of PKR over selected ISGs, altering the dynamic of the innate immune response course against TCRV. IMPORTANCE: The mechanisms for innate immune evasion are key for emergence and adaptation of human pathogenic arenaviruses, and highly pathogenic mammarenaviruses such as JUNV or MACV trigger a weaker IFN response than non-pathogenic mammarenaviruses. Within the innate immune response context, PKR plays an important role in sensing and restricting the infection of TCRV virus. Although the mechanism of PKR for protein synthesis inhibition is well described, its immunomodulatory role is less understood. In this study, we found that TCRV protein expression and viral propagation are inhibited from early times after infection, and when externally activated, PKR inhibits TCRV viral progeny production. Our present findings further characterize the innate immune response in absence of PKR, unveiling the role of PKR in defining the ISG profile after viral infection.

The assessment of photovoltaic devices, which convert light energy into electricity, becomes significantly relevant due to the aspiration to reduce pollution on a global scale. In this context, the pursuit of optimizing the efficiency in converting light energy into electrical energy involves exhaustive studies and structural analyses of solar cells, all directed toward achieving this goal. This study introduces a research proposal aimed at analyzing the losses associated with series resistance (Rs). The analysis takes into account each component comprising this resistance, pro-posing a network of resistances that precisely models each of these elements. The aforementioned research focused on simple-structured crystalline silicon cells. During this investigation, the junction depth (xj) of n-p materials was varied with the aim of achieving efficiencies in the range of 12%. However, in the pursuit of this desired efficiency, a significant impact on series resistance was observed when analyzing the I-V curves of the cells obtained in each manufacturing process.

The aim of this work is to explain the behaviour of the multiresistance percentage of Pseudomona aeruginosa in some countries of Europe through a multivariate statistical analysis and machine learning validation, using data from the European Antimicrobial Resistance Surveillance System, the World Health Organization and the World Bank. First, we will use a descriptive analysis and a principal components analysis. Then, we use a k-means clustering to determine the countries and regions that are most affected by the antibiotic resistance. Second, we expand the database by adding some socioeconomic, governance and antibiotic-consumption variables. We then run a data panel regression analysis to determine some functions that relates the multiresistance percentage with those new variables. Finally, we use machine learning techniques to validate a pooling panel data case, using XGBoost and random forest algorithms. The results of the data panel analysis indicate that the most important variables for the multiresistance percentage are corruption control and the rule of law. Similar results are found with the machine learning validation analysis, where the human development index is an additional important variable for the multiresistance percentage.

The spatial and temporal changes in social vulnerability to natural hazards in Mexico are analyzed. To this end, using census data from 2000, 2010, and 2020 and a statistical method, different indices were computed, and with a GIS-based approach, patterns of social vulnerability are examined. In addition, a risk assessment test for severe weather (thunderstorms, hailstorms, and tornadoes) is made out. The results show different common social vulnerability driving factors in the three analyzed years, with root causes that have not been addressed since the beginning of the century. Likewise, a wider gap between Mexico's most and least vulnerable populations is identified. The changes in spatial patterns respond to different historical situations, such as migration, urbanization, and increased population. Also, poverty, ethnicity, and marginalization factors located in very particular regions in Mexico have remained relatively the same in the last few years. These situations have strongly influenced the spatial-temporal distribution of vulnerability in the country. The role of social vulnerability in the disaster risk to extreme events such as thunderstorms, hailstorms, and tornadoes in Mexico is fundamental to understanding changes in disaster distribution at the national level, and it is the first step to generating improvements in integrated risk management.

Though nowadays germanium do not reach the range of popularity than other metals, i.e. rare earth elements, its utility in target industries makes of it also a strategic metal. Though germanium can be find in a series of raw materials, the principal source for its recovery is from secondary wastes of the zinc industry, and also, the recycle of germanium-bearing waste materials is becoming of interest. In this recovery, Hydrometallurgy is performing a key role to the successful achievement of this goal. The present work reviews the most recent applications (2023 and 2024 years) of hydrometallurgical operations on the recovery of germanium from different solid and liquid sources.

The contribution of academics and researchers to the discussion around sustainable rural development planning and its impact on rural communities has grown exponentially in recent years. Understanding trends in sustainable rural development research requires considering the different factors involved and affecting people from a holistic approach. This review examines, through bibliometric studies, the scientific knowledge generated on sustainable rural development planning in the last 50 years, analyzing 6,895 articles published in journals between 1970 and 2020. The results reveal the existence of three clusters and an important growth is observed to respond to the continuous needs in relation to sustainable rural development. This research shows the evolution of a new approach for the planning of sustainable rural development projects in postmodernity: Working with People (WWP). This WWP model, as a conceptual framework from social learning has been validated as a novel proposal in numerous contexts. The bibliometric analysis shows an evolution "From Putting the Last first" to "Working with People in Rural Development" research and the contributions of influential teachers such as Chambers and Cernea. These bibliometric analyses demonstrate the correct approach of WWP model, and open new fields of research in the planning of sustainable rural development projects.

Inside Central Nervous System (CNS) appears neurons and glia cells. There are more glial cells than neurons and have more functions than neurons. Glia name represents different kind of cells, ones from neural origin (astrocytes, radial glia, and oligodendroglia), and others from blood monocytes (microglia). During ontogeny, neurons appear first (rat fetal 15th) and after astrocytes (rat fetal 21th) indicating a bigger importance function in the CNS. Also, during the phylogeny, reptiles have less astrocytes compared to neurons and in humans, astrocytes are double in number than neurons. This data, perhaps means that astrocytes are more special cells and work in memory and learning? Astrocytes have an important role in different mechanisms protecting CNS across the production of antioxidant and anti-inflammatory proteins, cleaning extracellular medium and helping neurons to communicate with each other correctly. Inflammatory mediators production are important to prevent changes in normal physiology. But, excessive or continue production leads to many diseases, such as Alzheimer's disease (AD), Sclerosis Lateral Amyotrophic (ELA), Multiple sclerosis (MS), and neurodevelopment diseases, like Bipolar disorder, Schizophrenia, and Autism's symptomatology. Different drugs and thecniques can reverse oxidative stress and/or inflammatory excess. This review is intended to serve as an approximation to the field.

A novel hypothesis concerning language evolution is advanced. It posits that languages have evolved as a means of binding individuals to a group, as well as for defining those groups. This means that language evolution has to be considered on the level of groups and not only on the level of individuals. This hypothesis helps to explain the huge diversity of human languages, as well as their complexity. Perhaps more importantly, it explains why adults lose the ability to learn languages with the ease that children possess.

This work focuses on analyzing acoustic emission (AE) signals as a means to predict failure in structures. Two main approaches are considered: (i) long-range correlation analysis using both the Hurst (H) and the Detrended Fluctuation Analysis (DFA) exponents, and (ii) natural time domain (NT) analysis. These methodologies are applied to the data collected from two application examples: a glass fiber reinforced polymeric plate and a spaghetti bridge model, where both structures were subjected to increasing loads until collapse. A traditional (AE) signal analysis is also performed to reference the study of the other methods. Results indicate that the proposed methods yield a reliable indication of failure in the studied structures.

Recent advances in artificial intelligence combined with behavioral sciences have led to the development of cutting-edge tools for recognizing human emotions based on text, video, audio, and physiological data. However, these data sources are expensive, intrusive, and regulated, unlike plants which have been shown to be sensitive to human steps and sounds. A methodology is proposed to use plants as human emotion detectors. Electrical signals from plants are tracked and labeled based on video data. Labeled data are then used for classification. MLP, biLSTM, MFCC-CNN, MFCC-ResNet, and additionally, Random Forests, 1-Dimensional CNN, and biLSTM without windowing models are set using a grid search algorithm with cross-validation. Finally, best-parameterized models are trained and used with the test set for classification. The performance of this methodology is measured with a case study with 54 participants, who were watching an emotionally charged video, as ground truth their facial emotions were simultaneously measured using face emotion analysis. The Random Forest model shows the best performance, particularly in recognizing high-arousal emotions, achieving an overall weighted accuracy of 55.2% and demonstrating high weighted recall in emotions such as fear 61.0% and happiness 60.4%. The MFCC-ResNet model offers decently balanced results, with Accuracy(MFCC-ResNet)=0.318 and Recall (MFCC-ResNet)=0.324. With the MFCC-ResNet model fear and anger are recognized with 75% and 50% recall respectively. Thus, using plants as an emotion recognition tool seems worth investigating, addressing both cost and privacy concerns.

The study also found that older age was a protective factor in prospective studies. The consistency of results across different study designs and sensitivity analyses further supported the robustness of the findings. It is important to note that the existing literature on revictimization in women facing intimate partner violence is limited and exhibits significant heterogeneity in terms of methodology and conceptual frameworks.

Education is one of the most important tools available to policymakers and non-governmental bodies to promote a change in the behavior of society and to address the climate crisis, in line with the 4^th and 13^th Sustainable Development Goals of the United Nations 2030 Agenda. Project-based learning (PBL) addresses real and global challenges and allows the academic and professional formation of students. As part of the reflection stage of the educational action research method using the Business Canvas Model (BMC), pedagogic deficiencies were identified in the PBL and a didactic proposal was elaborated to emulate the interaction of students with the ecosystems of society. A prototype for improving the management of organic manures as soil amendments was initially developed, to provide the students with a quick start on the first steps of the proposed project. In the 10 sessions designed for the PBL (Make it happen!), the students elaborate a more sophisticated artifact in response to the demands of potential clients, as per the outcomes of the primary market research (5^th session). Active teaching methods and tools, such as a modified template of the BMC with the Rumsfeld’s matrix, aid the metacognition of students and their competences development. In a double session of the PBL, the primary market research is organized with key stakeholders of the agroindustry to enquire about the feasibility of the implementation of the technological solution and the logistics at farm level. Finally, the evaluation relies on the suitability of the upgraded prototype to respond customers’ demands.

Firms are increasingly organized around the client. At the same time, there is customer pressure on green and sustainable organizations. The purpose of this paper is to map the current state of the research in the domain of customer-centric organizations from a sustainable perspective. We conducted a bibliometric analysis from published documents between 1990 and 2020. Key findings indicate that research on customer centricity and sustainability has increased in recent years and that the topic is structured into 3 clusters: (1) Sustainability; (2) Customer-Centric Perspective, and Sustainable Development; and (3) Customer Experience and Sales. Moreover, new concepts and technologies have been introduced during the last three years. The implementation of a bibliometric methodology and the focus given to the definition, the relationships, and the evolution of the three main clusters within the topic are the characteristics that differentiate our study from other publications or reviews in the field of research. This paper is beneficial for practitioners who aim to deploy the customer centricity approach in their firms from a sustainable perspective.

(1) E-governance is defined as the application of electronic means in the interaction between government and citizens and government and business, as well as in internal government operations to simplify and improve democratic, governmental, and business aspects of governance. Thus, e-governance is built from a paradigmatic dimension such as e-democracy (relationship between government and citizens) and an operational one such as e-government. The objective was to design and validate an instrument to measure e-governance based on three factors: a) e-administration, b) e-services, and c) e-democracy; (2) Methods: Based on the level of importance given to each factor (sample of 2042 Latin American citizens), as well as the relationships between them, an analysis of the importance of each factor is carried out; (3) Results: After the confirmatory analysis, the definitive instrument with which e-governance can be measured by other researchers and future research is obtained, considering the three selection factors, namely: e-administration, e-services and e-democracy; (4) Conclusions: This research contributes to political science through the design and validation of an instrument consisting of 39 items that can be used to measure e-governance according to the dimensions proposed by the United Nations Educational, Scientific and Cultural Organization.

There is consensus over the fact that urban green areas contribute to the quality of life of their inhabitants. So, efficient city management must assess whether the population has access to green areas and their quality in relation to vegetation, facilities or furnishings, for example. Therefore, the objective set is to establish the environmental justice of urban parks in Tarragona (Spain) by developing a Park Quality Index (PQI) and the sociodemographic characteristics (level of studies, Human Development Index [HDI], home sale and rental prices) of the population living within 300 metres of a park. To prepare this, a GIS-integrated Multi-Criteria Evaluation (MCE) has been produced. The results show that the green areas have low accessibility and availability and that most parks obtain an average-low PQI, with the best- valued aspect being the vegetation and the worst the facilities. As for the degree of environmental justice, a casual relationship emerges between the PQI and the indicators used. The average value of the home sale prices is the one that shows the greatest correlation. These results can be used together with participatory procedures as a basis for identifying places with greater inequality, and for selecting the more effective actions that enable increasing environmental justice with respect to green areas.

White and three types of black garlic (13, 32 and 45 days of fermentation, named 0C1, 1C2 and 2C1 respectively) were selected in order to check possible differences in their nutraceutic potential. For this purpose, garlic were physico-chemically characterised, and both in vivo and in vitro assays were carried out. Black garlic showed higher polyphenol content and antioxidant capacity than white garlic. The biological studies have shown that only white garlic was not safe showing toxicity effect. Furthermore, none garlic exert protective effects against H₂O₂, except the 0C1 black garlic. Moreover, garlic was non-genotoxic with the exception of the highest concentration of white garlic. On the other hand, 0C1 was the most antigenotoxic substance. The in vivo longevity assays yielded significant extension of lifespan results in some concentrations of white and 0C1and 1C2 black garlic. The in vitro experiments showed that all studied garlic induced a decrease in leukaemia cells growth. However, none type of garlic was able to induce proapoptotic internucleosomal DNA fragmentation. Taking into account the physicochemical and biological data, black garlic could be considered as a potential functional food and used in preventive treatment of age-related diseases. In addition, our findings could be relevant for the black garlic processing agrifood companies as the economical and timing costs are significantly reduced to 13 days aging.

Taking four of the United Nations Development Goals as reference, this overview describes the need to see from a systemic perspective, the food certifications programs along the food chain in Mexico as today food certifications are voluntary. Using secondary data, the main objectives were: a) there is a fall short in food safety policies and those federal agencies responsible for food safety, to guarantee safe food along the whole domestic food chain, especially in that for low income players; b) the amount of the Mexican Federal Budget Expenses devoted to safety food issues is really low, considering the health, well- being, and food security consequences; and c) due the structural heterogeneity of the Mexican food market, there is a lack of coordination in food regulations along all agents of the food supply chain, bringing to alternate informal markets that put at risk peoples´ health, increasing poverty and inequalities. According to this exercise, only 0.7- 8.7% of producers, 12.5% of supermarkets as well as 42.8% of restaurants would have some type of certifications. Public policies must attend this issue in order to improve food safety and security for the whole population, reducing inequalities, poverty and ensuring them a healthy live.

(1) Background: Mindfulness-based interventions (MBIs) have shown interesting preliminary ef-fects over self-regulation processes in early adolescence. However, interventions usually integrate various types of practices with no clarity about the specific effect of each of them over attentional, emotional, and behavioral regulation. The objective of this research was to evaluate the effect of two MBIs, one focused on classic attentional practices and another one focused on the recognition and expression of emotions, over attentional, emotional, and behavioral self-regulation in early adolescents. (2) Method: An experimental method was carried out. A sample of 70 children be-tween 8 and 12 years old were randomized and assigned to three experimental conditions: 1) MBI with a focus on attentional practices, 2) MBI with a focus on recognition and expression of emotions, 3) control group, waiting list. The programs lasted 8 weeks, with a weekly 1-hour online synchronic session, plus home practices. Children were evaluated before starting the in-tervention and at the end of the 8-week program. The assessed variables were: 1) Mindfulness; 2) Emotional Regulation; 3) Attentional Regulation and 4) Behavioral regulation. (3) Results: Chil-dren that participated in both programs, increased their mindfulness and emotional and be-havioral regulation scores. Only children who participated in the program with a focus on at-tention showed significant changes in their ability to self-regulate attention. (4) Conclusions: online MBIs, with attention to external and internal stimuli practices, can be a good strategy to strengthen self-regulation skills of attention, emotions, and behavior in early adolescence.

A three-dimensional vector field model is proposed, whose dimensions are the Hansen Solubility Parameters: dispersion parameter (δD), polarity parameter (δP), and hydrogen bonding parameter (δH). The vector space that defines the field has the peculiarity of having the dispersion vector with a magnitude of 2, as its base vector, while polarity and hydrogen bonding vectors have a magnitude of 1. A substance is characterised as a position vector, and the interaction between two substances is determined by calculating the vector difference of both, known as the interaction vector. Interaction among substances may involve solubility, swelling, cracking, surface tension, interface tension, and any physical phenomena where intermolecular energies of dispersion, polarity or hydrogen bonding come into play. This paper studies free surface energy (surface and interfacial tension). It has been found that free surface energy is directly proportional to the square of the magnitude of the interaction vector. The proportionality constant, τ, is expressed in length units, has a value of 0.025 nm, and does not depend on the chemical nature of the substance or state of matter (solid, liquid or gas). Constant value τ appears universal and aligns with the thickness of interfaces, thereby supporting Guggenheim's hypothesis. This hypothesis asserts that interfaces possess actual thickness and are not merely mathematical surfaces, as originally postulated by Gibbs. Moreover, it also has been found that interface thickness, τ, is approximately equal to half of the Bohr radius, a0, which is defined by universal constants. Because the solubility parameters of thousands of substances are known and can be easily determined from molecular structure, a good approximation of the surface and interfacial tension of any given substance can now be calculated. It has also been found that contact angles of sessile droplets in three-phased systems can be calculated from the interaction vectors of the implicated substances.

Aging is associated with an increasing dysfunction of key brain homeostasis mechanisms and represents the main risk factor across most neurodegenerative disorders. However, the degree of dysregulation and the affectation of specific pathways set apart normal aging from neurodegenerative disorders. In particular, the neuronal metabolism of catecholaminergic neurotransmitters appears to be a specifically sensitive pathway that is affected in different neurodegenerations. In humans, catecholaminergic neurons are characterized by an age-related accumulation of neuromelanin (NM), rendering the soma of the neurons black. This intracellular NM appears to serve as a very efficient quencher for toxic molecules. However, when a neuron degenerates, NM is released together with its load (many undegraded cellular components, transition metals, lipids, antibiotics) contributing to initiate and worsen an eventual immune response, exacerbating the oxidative stress, ultimately leading to the neurodegenerative process. This review focuses on the analysis of the role of NM in normal aging and catecholaminergic metabolism due to its capability as a pro-oxidant and other harmful molecules, versus its involvement in oxidative stress and aberrant immune response, which it is highly dependent on NM saturation state and its extracellular release.

The development of plant-based meat analogues has become a significant challenge for the food industry in recent years due to the increasing demand for sustainable and healthier proteins in the context of a global protein transition. Plant-based meat analogues imitate the visual, textural, and chemical properties of traditional meat products and are required to closely resemble meat to appeal to consumers. In addition, consumers demand natural, clean-label, and nutritional and healthy products. To address these challenges, the food industry must develop highly healthy, nutritious, and E-number-free meat analogue products. Understanding the functionality of each ingredient and its role in the food matrix is crucial to being a key player in the innovation of the meat analogues market. This review provides updated information on the primary ingredients utilized for the development of plant-based burger meat alternatives and their functionality. The key components of meat analogue burgers are outlined, including plant proteins, binding agents, fats and oils, flavorings, colorings, preservatives, fortificants, and clean-label considerations.

Technological development has profoundly marked the evolution of the economy. The constant changes brought about by scientific and technological advances have been decisive in the transition from an analogue to a digital world. In this context, the impact of the fourth industrial revolution (or Industry 4.0.) manifests itself in many ways. Environmental impact is one of these. The energy sector has been evolving and changing just like the economy and society. Therefore, a study of this sector, and of the other related elements, is of interest to better understand the 4.0 concept. The promotion of sustainability at both political and social levels has led to changes in different areas, such as the productive vision, the use of green energies or the implementation of green taxes. Energy as a key factor in Industry 4.0. involves studying it both quantitatively and qualitatively. This is to under-stand the lights and shadows that the concept currently presents. Therefore, this work aims to bring the reality of the energy sector closer to reality, both in its positive and negative aspects, considering the main factors of incidence, in order to show the strengths and weaknesses that can be deduced.

The consequences of climate change and anthropogenic stressors, such as habitat loss and overexploitation, are threatening the subsistence of species and communities across the planet. Therefore, it is crucial to analyze the impact of environmental perturbations on the diversity, structure and function of ecosystems. In this work, in silico simulations of biodiversity loss were carried out on the marine food web of Caleta Potter (25 de Mayo Island, Antarctica) where global warming has caused critical changes in the abundance and distribution of benthic and pelagic communities during the last 30 years. We performed species removal considering their degree and trophic level and including four different thresholds on the occurrence of secondary extinctions. We examined the impact of extinctions on connectance, modularity and stability of the food web. We found different responses of these properties depending on the extinction criteria used, e.g., large increase in modularity and rapid decrease in stability when most-connected and relatively high-trophic level species were removed. Additionally, we studied the complexity-stability relationship of the food web founding two regimes: 1) high sensitivity to small perturbations suggesting that Potter Cove would be locally unstable, and 2) high persistence to long-range perturbations suggesting global stability of this ecosystem.

In this paper, the power quality of interconnected microgrids is managed using a Model Predictive Control (MPC) methodology which manipulates the power converters of the microgrids in order to achieve the requirements. The control algorithm is developed for the microgrids working modes: grid-connected, islanded and interconnected. The results and simulations are also applied to the transition between the different working modes. In order to show the potential of the control algorithm, a comparison study is carried out with classical Proportional-Integral Pulse Width Modulation (PI-PWM) based controllers. The proposed control algorithm not only improves the transient response in comparison with classical methods but also shows an optimal behavior in all the working modes, minimizing the harmonics content in current and voltage even with the presence of non-balanced and non-harmonic-free three-phase voltage and current systems

MATERIAL AND METHOD: This is an observational analytical cohort study carried out on a total of 160 patients, divided into 4 groups: healthy, with myopia, with primary open-angle glaucoma (POAG), and with POAG and myopia together. The study variables were Bruch's membrane opening area (BMO), the thickness of the RNFL and the RGC layer using the Glaucoma Premium program of the OCT Spectralis of Heidelberg. RESULTS: Regarding the analysis between age and the thickness of the RNFL, significant results were found in the healthy and glaucoma groups with myopia, for the rest of the groups, although there are no significant results, the correlation is negative, the older the younger is the thickness. Regarding intraocular pressure (IOP), significant results have been found in the nasal sector in the glaucoma group. In the glaucoma with myopia group, statistically significant results have been obtained when analyzing the thickness of the RNFL with refraction. In the analysis between the thickness of the RNFL and the RGC layer, significant results were obtained in the myopia and glaucoma groups; in the group of glaucoma with myopia, it occurs in the superior temporal sector. CONCLUSION: In the case of myopic patients with glaucoma, damage at the functional, both the thickness of the RNFL, the RCG and the BMO-MRW are greater than other groups. All these alterations can be evaluated and monitored with the OCT Spectralis thanks to the programs it includes, making this instrument one of the best for an early diagnosis of glaucoma and the damage produced in myopic patients.

The recovery and valorization of waste are some of the key aspects of sustainable production. The crustacean exoskeletons can be potentially used to obtain value-added products such as chitosan. A comprehensive analysis including both safety and sustainability aspects of chitosan production from shrimp shells is presented in this study. The inherent safety analysis and sustainability evaluation was performed using the Inherent Safety Index (ISI) methodology and the Sustainable Weighted Return on Investment Metric (SWROIM), respectively. The process was designed for a processing capacity of 57,000 t/y according to shrimp production in Colombia. The economic (%ROI), environmental (PEI output), energy (exergy efficiency), and safety (ITI) technical parameters were included in the sustainability evaluation. The three first were obtained from the previous analysis performed by the authors. The total inherent safety index was estimated at 25 indicating that the process is inherently unsafe. The main process risks were given by the dangerous substance, reactivity, and inventory subindices. The overall sustainability evaluation showed a SWROIM of 36.23% indicating that the case study showed higher weighted performance compared to the return on investment (ROI) metric of 18.08%.

In this work, an embroidered textile moisture sensor is presented. The sensor is based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidery conductor yarn composed by 99% pure silver plated nylon yarn 140/17 dtex. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 25% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity. Moreover, the reproducibility of the sensor performance subject to the manufacturing process variability and washing process is also evaluated. The results show that the manufacturing variability introduce a moisture measurement error up to 4%. The washing process impact on the sensor behavior after applying the first washing cycle implies a sensitivity reduction higher than 14%. Despite these effect, the textile sensor keeps its functionality and can be reused in standard conditions. Therefore, these properties point out the usefulness of the proposed sensor to develop wearable applications on health and fitness scope including the user needs to have a life cycle longer than one-time use

Let $a, b$ and $n > 1$ be three positive integers such that $a$ and $\sum_{j=0}^{n-1} b^j$ are relatively prime. In this paper, we prove that the toric ideal $I$ associated to the submonoid of $\mathbb{N}$ generated by $\{\sum_{j=0}^{n-1} b^j\} \cup \{\sum_{j=0}^{n-1} b^j + a\, \sum_{j=0}^{i-2} b^j \mid i = 2, \ldots, n\}$ is determinantal. Moreover, we prove that for $n > 3$, the ideal $I$ has a unique minimal system of generators if and only if $a < b-1$.

This document presents the design and manufacture of a reflectarray (RA) antenna for the Ku-band, based on a fully-metallic 3D architecture. The reflectarray unit cell is formed by a square-shaped waveguide section ended in a short circuit, that is the reflectarray back ground plane. Each cell has the ability of configuring the phase of its own reflected field by means of resonators perforated on the walls of the cell waveguide section. The resonator-based waveguide cell introduces the 3D character to the design. The geometry of the resonators and its size variation introduces the phase behaviour of each cell, conforming the radiation pattern of the reflectarray. This design explores the potential of phase value truncation (6 states and 2 states), and demonstrates that proper pattern results can be obtained with this phase truncation.

The cancer stem cell hypothesis suggests that neoplastic cells with stem characteristics hierarchically regulate tumor generation and its high cellular heterogeneity. These cells have been detected in all cancer types, and specific signaling pathways give the regulation of self-renewal and differentiation. In prostate cancer, androgen receptor signaling has been extensively studied, and in non-stem cells, it promotes cell proliferation and tumor progression, but in the cancer stem cell population, it negatively regulates processes such as self-renewal. However, in other types of cancer, such as breast and glioblastoma, the androgen receptor seems to favor the maintenance of cancer stem cells, suggesting that androgen signaling has different effects depending on the tumor context. This review discusses the role of androgen receptor in maintaining cancer stem cells by regulating proliferation, self-renewal, and differentiation, as well as the possible signaling pathways involved in these processes.

Huge amounts of wastes are generated during shrimp processing, representing approximately 65% of the initial shrimp weight, which can become an environmental problem when accumulated. Residues such as shrimp shells can be processed to obtain value-added products such as chitin, chitosan, astaxanthin, and a nitrogenous extract under the biorefinery concept. In this work, the economic evaluation and the techno-economic sensibility analysis for a mass integrated biorefinery based on shrimp were developed to determine the economic feasibility of the project and to identify the critical techno-economic variables that affect the profitability of the process. The results showed that a biorefinery for the annual processing of 4,113.09 tons of fresh shrimp in Colombia is profitable, with a return on investment percentage (%ROI) equal to 65.88% and a net present value (NPV) of 10.40 MM USD. The process supports decreases of up to 28% in capacity of production and increases of 12% and 11% in the cost of raw materials and variable operating costs without incurring losses, respectively. However, the decrease over 500 USD/t in the shrimp meat selling price is not supported, thus it is mainly recommended to increase the selling price of this product.

The manuscript delves into the intricacies of food production chains, offering a comprehensive breakdown of their components. Moreover, it sheds light on the initiatives orchestrated by government agencies to endorse sustainable practices and fortify areas of opportunity for producer organizations. While the context paints a broad picture, we contend that, to the best of our knowledge, there exists no comparable publication that succinctly encapsulates the role of government in bolstering food production chains. The document unfolds with a detailed exploration of the interaction mechanisms among the various components of the chain. Subsequently, it introduces a set of twelve elements meticulously outlining the multifaceted role of the government. Each element undergoes thorough scrutiny, fostering a nuanced understanding of the intricate relationship between the food production chain and the government's pivotal role in enhancing stability and efficiency. In conclusion, the manuscript not only lays bare the structural elements of food production chains but also presents a unique and in-depth analysis of the government's role, encapsulated within the framework of twelve essential elements.

We report the production of metal oxide (TiFe₂O₄, ZnFe₂O₄) nanoparticles by pulsed laser ablation technique in liquid environment. We used nano second Nd: YAG laser systems working at 532 nm and 1064 nm of wavelength, the energy of the laser beam was kept constant at 80 mJ. Absorbance spectra, surface plasmon resonance, optical band-gap and nanoparticle morphology were investigated using ultraviolet-visible (UV-Vis) spectroscopy, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). Changing the wavelength of the laser for growth, nanoparticles shown shift between the absorbance and surface plasmon resonance peaks in their UV-Vis spectra, this implies that the optical properties of the colloid nanoparticles depends on laser parameters, this was confirmed with the variation of the band gap energy. Furthermore, red shift for the absorbance peak was observed for samples as-growth at 532 nm around the 150 nm as function of time preparation. Whereas, for the samples as-growth at 1064 nm there is no shift in the absorbance spectra, this can be due to agglomeration and formation of larger particles. The characterization results shown appropriate plasmonic photo-catalysts properties of the particles, hence the photo activation of the nanoparticles was examined on antibacterial effect using colonies of Staphylococcus Aureus and Escherichia coli.

Abstract: Introduction: Covid-19 lockdown has caused important changes in children's routines, especially in terms of nutrition, physical activity, screen time, social activity, and school time. Regarding these changes, recent studies show that Covid-19 lockdown was associated with higher levels of anxiety and depression in children. The objective of this study was to assess changes in sleep quality in Spanish children during lockdown decreed by the Spanish government between March and June 2020. Methodology: We compared the BEAR score of 478 participants in the SENDO project at the periods before, during and after lockdown. We used hierarchical models with two levels of clustering to account for the intra-cluster correlation between siblings. Interaction of time with and a set of a priori selected variables was assessed by introducing the interaction term into the model and calculating the likelihood ratio test. Results: Mean scores in the BEAR questionnaire referred to the periods before, during, and after lockdown were 0.52 (sd 1.25), 1.43 (sd 1.99) and 1.07 (sd 1.55), respectively, showing a worsening of sleep quality as a result of confinement. Parental level of education was found to be an effect modifier (p for interaction=0.004). Children whose parents had higher education (university graduates or higher) showed a smaller worsening than those without. Conclusion: We found that the mean score in the BEAR questionnaire significantly worsened during lockdown and significantly improved after it. However, it did not reach the initial level. The mean score in the BEAR questionnaire referred to the period after lockdown was significantly higher than before.

In the Brazilian Amazon, rural settlements are increasingly isolated by large-scale production farms, jeopardizing their sustainability and the good living of family farmers. Works were carried out in settlements to measure sustainability. However, the majority does not consider the participation and the collectively of those involved. In this way, we propose to evaluate, in a collective and participatory way, the sustainability and good living of the SDP São Paulo Rural Settlement, of the northern Amazon of Mato Grosso. We used the didactic-pedagogical method Circle of Sustainability, developed from five points: 1st - circle of investigation of generating themes; 2nd - circle of the history of the subject world; 3rd - circle of diagnosis of rural settlements; 4th - circle of exchange of knowledge; and 5th - circle of sustainable perceptions and narratives. The historical, socioeconomic and cultural characterization of the settlement allowed us to understand how sustainability and good living are being built in the settlement history process. Sustainability and good living are dialectical processes, are under construction, in movement.

This study investigates the impact of real-time emotional feedback on the quality of teamwork conducted over videoconferencing. We developed a framework that provides real-time feedback through a virtual mirror based on facial and voice emotion recognition. In an experiment with 28 teams (84 participants), teams collaborated over Zoom to set up a virtual Mars station using custom simulation software. Participants were divided into 14 experimental teams which were shown the virtual mirror, and 14 control teams without it. Team performance was measured by the improvement in the Mars simulation output quality. Our analysis using correlation, multilevel regression, and machine learning revealed that fewer interruptions but an increasing number over time correlated with higher performance. Higher vocal arousal and happiness also enhanced performance. We confirmed that female presence in teams boosts performance. SHAP values indicated that high variability in happiness, head movement, and positive facial valence—an “emotional rollercoaster”—positively predicted team performance. The experimental group outperformed the control group, suggesting that virtual mirroring improves virtual teamwork and that interrupting each other more, while speaking less, leads to better results.

The removal of harmful arsenic(V) from aqueous solutions using Cyanex 923 (solvation extractant) was investigated under various experimental variables: equilibration time, acidity of the aqueous phase, temperature, extractant and arsenic concentrations, and O/A ratio. Cyanex 923 extracted As(V) (and sulphuric acid) from acidic solutions, thus, its use to remove the metal from slightly acid or neutral solutions it is not possible. Extraction of arsenic is exothermic, and responded to the formation of H3AsO4·nL species in the organic phase (L represented the extractant and the stoichiometric factor n: 1 or 2, depends on the acidity of the aqueous phase). Extraction isotherms are derived from experimental results. Both arsenic and sulphuric acid loaded onto the organic phase can be stripped with water, and stripping isotherms are also derived from the experimental results. The selectivity of the system against the presence of other metals (Cu(II), Ni(II), Bi(III), Sb(III)) are investigated, and also it is investigated the ability of Cyanex 923 to extract As(V) and sulphuric acid against the use of other P=O based solvation reagents, such dibutyl butylphosphonate (DBBP) and tri-butyl phosphate (TBP).

In this paper, we redefine the boundaries of blood cell classification, expanding from 5 to 11 distinct blood cell types using the challenging 11-class PBC dataset. This shift enables a deeper understanding of blood cell diversity, overcoming previous limitations in medical image analysis. Our approach combines state-of-the-art deep learning techniques, including pre-trained ConvNets, ViTb16 models, and custom CNN architectures. We employ transfer learning, fine-tuning, and ensemble strategies, such as CBAM and Averaging ensembles, to achieve unprecedented accuracy and interpretability. Our fully fine-tuned EfficientNetV2 B0 model sets a new standard, with a macro-average precision, recall, and F1-score of 91%, 90%, and 90%, respectively, and an average accuracy of 93%. This breakthrough underscores the transformative potential of 11-class blood cell classification for more precise medical diagnoses. Moreover, our groundbreaking "Naturalize" augmentation technique produces remarkable results. The 2K-PBC dataset generated with "Naturalize" boasts a macro-average precision, recall, and F1-score of 97%, along with an average accuracy of 96% when leveraging the fully fine-tuned EfficientNetV2 B0 model. This innovation not only elevates classification performance but also addresses data scarcity and bias in medical deep learning. Our research marks a paradigm shift in blood cell classification, enabling more nuanced and insightful medical analyses. The "Naturalize" technique’s impact extends beyond blood cell classification, emphasizing the vital role of diverse and comprehensive datasets in advancing healthcare applications through deep learning.

Landscapes evolve due to climatic conditions, tectonic activity, geological features, biological activity, and sedimentary dynamics. These processes link geological processes at depth to surface features. Consequently, the study of landscapes can reveal essential information about the geochemical footprint of ore deposits at depth. Advances in satellite imaging and computing power have enabled the creation of large geospatial datasets, the sheer size of which necessitates automated processing. We describe a methodology to enable the automated mapping of landscape pattern domains using machine learning (ML) algorithms. From a freely available Digital Elevation Model, derived data, and sample landclass boundaries provided by domain experts, our algorithm produces a dense map of the model region in Western Australia. Both random forest and support vector machine classification achieve about 98\% classification accuracy with reasonable runtime of 48 minutes on a single core. We discuss computational resources and study the effect of grid resolution. Larger tiles result in a more contiguous map, while smaller tiles result in a more detailed, and at some point, noisy map. Diversity and distribution of landscapes mapped in this study support previous results. In addition, our results are consistent with the geological trends and main basement features in the region.

This paper presents an alternative process to fabricate flexible bandpass filters by using embroidered yarn conductor on electronic-textile. The novelty of the proposed miniaturized filter is its complete integration on the outfit, with benefits in terms of compressibility, stretch ability and high geometrical accuracy, opening the way to develop textile filters in sport and medicine wearable applications. The proposed design consists of a fully embroidered microstrip topology with a length equal to quarter wavelength (λ/4) to develop a bandpass filter frequency response. A drastic reduction in size of the filter was achieved by taking advantage of a simplified architecture based on meandered-line stepped impedance resonator. The e-textile microstrip filter has been designed, simulated, fabricated and measured, with experimental validation at a 7.58 GHz frequency. The insertion loss obtained by simulation of the filter is substantially small. The return loss is greater than 20 dB for bands. To explore the relations between physical parameters and filter performance characteristics, theoretical equivalent circuit model of the filter constituent components were studied. The effect of bending of the e-textile filter is also studied. The results show that by changing the radius of bending up to 40 mm, the resonance frequency is shifted up 4.25 MHz/mm.

RO membrane fouling is one of the main challenges that membrane manufactures, the scientific community and industry professionals have to deal with. The consequences of this inevitable phenomenon have a negative effect on the performance of the desalination system. Predicting fouling in RO systems is key to evaluating the long-term operating conditions and costs. Much research has been done on fouling indices, methods, techniques and prediction models to estimate the influence of fouling on the performance of RO systems. This paper offers a critical review evaluating the state of industry knowledge in the development of fouling indices and models in membrane systems for desalination in terms of use and applicability. Despite major efforts in this field, there are gaps in terms of effective methods and models for the estimation of fouling in full-scale RO desalination plants. In existing models applied to full-scale RO desalination plants, neither the spacer geometry of membranes nor the efficiency and frequency of chemical cleanings - which play an important role in the performance of this process - are considered.

Background: The incidence of prostate cancer (PC) has been risen annually. Despite the diagnosis is made mainly with non-metastatic PC, mortality is explained by the metastatic disease (mPC). Without a doubt there is an intermediate scenario in which patients have no mPC but will have initiated a metastatic cascade through an epithelial-mesenchymal transition. There is indeed a need for more and better tools to predict what patients will progress in the future to non-localized clinical disease or already have micrometastatic disease, and therefore, will clinically progress after primary treatment. Biomarkers for predicting mPC are still under development; there are few studies and not much evidence of their usefulness. Summary: This review is focused on tissue-based genomic biomarkers (TBGB) for predicting metastatic disease. We developed four main research questions that will attempt to answer according to the current evidence. Why is important to predict metastatic disease? Which tests are available to predict metastatic disease? What impact should there be on clinical guidelines and clinical practice in predicting metastatic disease? What are current prostate cancer treatments? Key Messages: Knowing useful predict tools could help determine which patients may need multimodal or adjuvant treatment even with a localized disease, and in consequence, what patients do not need more than a single modality of treatment. The importance of predicting metastasis is fundamental, given that once metastasis is diagnosed, the quality of life (QoL) and survival drop dramatically.

Wood is poised to become a material of choice for future construction. When appropriately managed, it is a renewable material with unique mechanical properties. Beyond its inherent sustainability, the use of wood has a crucial role in addressing climate change concerns due a significantly lower energy consumption and emissions during manufacturing and transportation, while simultaneously acting as a carbon sink. Thus, there has been a growing demand for hardwoods for structural applications, including Castanea sativa Mill., the focal point of this investigation. Albeit in a limited capacity, Eurocode 5-2 offers friction coefficients for softwoods, but it falls short for hardwoods which it is a gap to bridge with this research. These coefficients play a critical role in numerical simulations involving friction, enabling the optimization of joints and, by extension, the overall structural integrity. Test samples were evaluated at 18% moisture content, which is typical of Service Class 2, for various orientations of timber-to-timber and timber-to-steel friction. Considering previous friction coefficients at 12% moisture content, the linear variation was evaluated at an intermediate value of 15%. The results provide an experimental database for numerical simulations and highlight the influence of moisture content on the coefficients, which increase linearly along moisture percentages.

Land degradation and climate change are among the main threats to the sustainability of ecosystems worldwide. Therefore, the restoration of degraded landscapes is essential to maintain the functionality of ecosystems, especially those with greater social, economic and environmental vulnerability. Nevertheless, policy-makers are frequently challenged by deciding on where to prioritize restoration actions, which usually includes to deal with multiple and complex needs under an always short budget. If these decisions are not taken based on proper data and processes, restoration implementation can easily fail. To help decision-makers taking informed decisions on where to implement restoration activities, we have developed a semiautomatic geospatial platform to prioritize areas for restoration activities based on ecological, social and economic variables. This platform takes advantage of the potential to integrate R coding, Google Earth Engine cloud computing and GIS visualization services to generate an interactive geospatial decision-maker tool for restoration. Here, we present a prototype version called "RePlant alpha" which was tested with data from the Central Zone of Chile. This exercise proved that integrating R and GEE was feasible, and that the analysis, with at least six indicators and for a specific region was also feasible to implement even from a personal computer. Therefore, the use of a virtual machine in the cloud with a large number of indicators over large areas is both possible and practical.

Piggery wastewater (PWW) is characterized by its high concentrations of organic matter and ammonium, and by their odour nuisance. Traditionally, PWW has been treated in open anaerobic lagoons, anaerobic digesters and activated sludge systems, which exhibit high greenhouse gas emissions, a limited nutrients removal and a high energy consumption, respectively. Photosyn-thetic microorganisms can support a sustainable PWW treatment in engineered photobioreactors at low operating costs and with an efficient recovery of carbon, nitrogen and phosphorous. These microorganisms are capable of absorbing solar irradiation through the photosynthesis process to obtain energy, which is used for their growth and associated carbon and nutrients assimilation. Purple phototrophic bacteria (PPB) represent the photosynthetic microorganisms with the most versatile metabolism in nature, while microalgae are the most studied photosynthetic microor-ganisms in recent years. This review describes the fundamentals, symmetry and asymmetry of PWW treatment using photosynthetic microorganisms such as PPB and microalgae. The main photobioreactor configurations along with the potential of PPB and microalgae biomass valori-zation strategies are also discussed.

In this work, two embroidered textile moisture sensors are characterized with three different conductive yarns. The sensors are based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidered conductor yarn. The performance comparison of 3 different type of conductive yarns has been addressed. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 30% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity and the used conductor yarns. This dependence points out the optimum conductive yarn to be used to develop wearable applications for moisture measurement.

As consequence of COVID-19, millions of households suffered mobility restrictions and changes in their lifestyle during several months. The aim of this study was to evaluate the effects of COVID-19 home confinement in food habits, lifestyle and emotional balance of the Spanish population. This cross-sectional study used data collected via an anonymous online questionnaire during the last month before lockdown finished in Spain in a total of 675 participants. 38.8% of the respondents experienced weight gain while 31.1% lost weight during confinement. The increase in body weight was positively correlated with the age (Rs = 0.14, p &lt;0.05) and BMI (Rs = 0.20, p &lt;0.05). We also identified that 39.7% reported poorer quality sleep, it was positively correlated with BMI (Rs = -0.18, p &lt;0.05) and with age (Rs = -0.21, p &lt;0.05). 44.7% of the participants had not performed physical exercise during confinement with differences by sex (p &lt;0.05), by age (p &lt;0.05), by BMI (p &lt;0.05) and sleep quality (p &lt;0.05). According to emotional-eater questionnaire, 21.8% and 11% were classified as emotional eater and very emotional eater, respectively. We emphasize the importance of adopting a healthy lifestyle, as the COVID-19 pandemic nowadays is ongoing.

Cuba is struggling with a growing environmental problem: the uncontrolled spread of the allochthonous weed species marabou (Dichrostachys cinerea) throughout the country. Over the last 70 years, marabou has become a formidable invasive species that poses a threat to Cuban biodiversity and agricultural productivity. In this paper, we present a free and affordable method for regularly mapping the spatial distribution of the marabou based on the Google Earth Engine platform and ecological surveys. To test its accuracy, we develop an 18-year analysis (2000–2018) of marabou dynamics using the Valle de los Ingenios, a Cuban UNESCO World Heritage Site, as an experimental model. Our spatial analysis reveals clear patterns of marabou distribution and highlights areas of concentrated growth. Temporal trends illustrate the dynamic nature of the species, identifying periods of expansion and decline. In addition, our system is able to detect specific, large-scale human interventions against the marabou plague in the area. The results highlight the urgent need for remedial strategies to maintain the fragile balance in the region.

This paper describes the design and implementation of an ultrasonic non-contact air-coupled technique (UNCACT) using antisymmetric Lamb waves (ALW) for NDT assessment in novel composite sandwich plates of the car body shell. This technique is complemented with a C-Scan image implementation using this kind of guided waves. The finite element method using Comsol 6.1 is developed for the interpretation of the several wave modes presented in the experiments, including the ALW mode. The phase velocity method (PVM) is applied for the verification of the ALW mode in the portion of the RF signal necessary in the C-Scan image.

This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport, and arrival to the packing) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization of the process based on Hidden Markov Models and uses the Viterbi algorithm to perform inference and estimate the most likely state trajectory. The obtained state trajectory estimate is then used to compute a potential damage indicator in real-time. The proposed methodology does not require information about the weight of the basket to identify each of the different stages, which makes it effective and more efficient than other alternatives available in the industry.

Gluten is a complex mixture of storage proteins in cereals like wheat, barley and rye. Prolamins are the main components of gluten. Their high content in proline and glutamine makes them water-insoluble and difficult to digest in the gastrointestinal tract. Partial digestion generates peptide sequences which trigger immune responses in celiac and gluten-sensitive patients. Gluten detection in food is challenging because of the diversity, in various food matrices, of protein proportions and their immunogenicity. Attempts to develop standard reference materials have been unsuccessful. We present here a summary of recent studies reporting the detection of dominant Gluten Immunogenic Peptides (GIP) sharing epitopes presented in the α-gliadin 33-mer, the most important celiac disease-immunogenic sequence within gluten. GIP were not only detectable and quantifiable in very different kind of difficult to analyze food, but also in stool and urine of celiac patients on a supposedly gluten-free diet (GFD), providing the first simple and objective means to assess adherence to the GFD. Methods to specifically and sensitively detect the most active GIP in food and biological fluids are rational candidates may use similar analytical standard references for determination of the immunopathological risk of gluten exposure in gluten-related diseases.

In this paper, we prove some random fixed point theorems for generalized random $\alpha-\psi-$contractive mappings in a Polish space and, as some applications, we show the existence of random solutions of second order random differential equation.

A substantial body of phenomenological and theoretical work over the last few years strengthens the possibility that the vacuum energy density (VED) of the universe is dynamical, and in particular that it adopts the `running vacuum model' (RVM) form, in which the VED evolves mildly as $\delta \rho_{\rm vac}(H)\sim \nu_{\rm eff} m_{\rm Pl}^2{\cal O}\left(H^2\right)$, where $H$ is the Hubble rate and $\nu_{\rm eff}$ is a (small) free parameter. This dynamical scenario is grounded on recent studies of quantum field theory (QFT) in curved spacetime and also on string theory. It turns out that what we call the `cosmological constant', $\Lambda$, is no longer a rigid parameter but the nearly sustained value of $8\pi G(H)\rho_{\rm vac}(H)$ around (any) given epoch $H(t)$, where $G(H)$ is the gravitational coupling, which can also be very mildly running (logarithmically). Of particular interest is the possibility suggested in past works that such a running may help to cure the cosmological tensions afflicting the $\Lambda$CDM. In the current study, we reanalyze it in full and we find it becomes further buttressed. Using the modern cosmological data, namely a compilation of the latest SNIa+BAO+$H(z)$+LSS+CMB observations, we probe to which extent the RVM provides a quality fit better than the concordance $\Lambda$CDM model, paying particular emphasis on its impact on the $\sigma_8$ and $H_0$ tensions. We utilize the Einstein-Boltzmann system solver \texttt{CLASS} and the Monte Carlo sampler \texttt{MontePython} for the statistical analysis, as well as the statistical DIC criterion to compare the running vacuum against the rigid vacuum ($\nu_{\rm eff} = 0$). On fundamental grounds, $\nu_{\rm eff}$ receives contributions from all the quantized matter fields in FLRW spacetime. We show that with a tiny amount of vacuum dynamics ($|\nu_{\rm eff}|\ll 1$) the global fit can improve significantly with respect to the $\CC$CDM and the mentioned tensions may subside to inconspicuous levels.

Associating the most influential parameters with the product distribution is of uttermost importance in complex catalytic processes such as fluid catalytic cracking (FCC). These correlations can lead to the information-driven catalyst screening, kinetic modeling and reactor design. In this work, a dataset of 104 uncorrelated experiments, with 64 variables, has been obtained in an FCC simulator using 6 types of feedstock (vacuum gasoil, polyethylene pyrolysis waxes, scrap tire pyrolysis oil, dissolved polyethylene and blends of the previous), 36 possible sets of conditions (varying contact time, temperature and catalyst/oil ratio) and 3 industrial catalysts. Principal component analysis (PCA) has been applied over the dataset, showing that the main components are associated with feed composition (27.41% variance); operational conditions (19.09%) and catalyst properties (12.72%). The variables of each component have been correlated with the indexes and yields of the products: conversion, octane number, aromatics, olefins (propylene) or coke, among others.

Background: Diabetes mellitus (DM) and periodontitis are two chronic diseases that are interconnected. The coexistence of these conditions leads to increased severity of periodontitis and challenges in controlling blood glucose levels in diabetic patients. Objectives: The aim of this study was to evaluate both the influence of periodontal disease and its treatment in patients with DM in terms of a reduction in glycosylated hemoglobin levels at 3 and 6 months after treatment. Methods: A sequential, nonprobabilistic, controlled, prospective and longitudinal case−control study was carried out at the University Dental Clinic of the Morales Meseguer Hospital in Murcia, Spain. Thirty diabetic patients were divided into two groups: patients with periodontitis (test group) and patients without periodontitis (control group). The periodontal and endocrine-metabolic variables were measured at baseline and at 3 and 6 months after periodontal treatment for both groups. Results: Statistically significant differences were found at 3 and 6 months after periodontal treatment with respect to HbA1c levels in the group of periodontal patients. However, these differences were not observed in the control group. Conclusion: The presence of periodontal disease increased HbA1c levels in patients with DM. Nonsurgical periodontal treatment significantly decreased the degree of periodontal inflammation and the HbA1c level at 3 and 6 months after treatment.

The construction industry is responsible for 40 to 45% of primary energy consumption in Europe alone. Therefore, it is essential to find new materials with a lower environmental impact in order to attain sustainable housing. This study aims to determine and compare the environmental impact of two clay samples forming a basis for the manufacture of traditional brick, a standard material in building construction; traditional red clay brick and a brick based on clay mixed with a biological ingredient. The samples of fired clay were manufactured at the laboratory scale, the results being valid exclusively as indicators for the extrapolation of the analysis to other studies. The results of the environmental impact of these formulations have been examined through an evaluation of life-cycle analysis (LCA), observing that the incorporation of biological pore forming agents led to a decrease of around 15 to 20% of all impact categories studied. Thus, the suitability of using biological-based additives in clay bricks was confirmed both for their constructive characteristics (lighter material) and increased energy efficiency (better thermal insulation) considering the environmental point of view.