Ranolazine (Rn) is a drug used to treat persistent chronic coronary ischemia. It has also been shown to have therapeutic benefits on the central nervous system and an anti-diabetic effect by lowering blood glucose levels and however, no effects of Rn on cellular sensitivity to insulin (Ins) have been demonstrated yet. The present study aimed to investigate the permissive effects of Rn on the actions of Ins in astrocytes in primary culture. Ins at 10-8 M, Rn (10-6 M) and Ins+Rn (10-8 M and 10−6 M respectively) were added to astrocytes during 24 h. In comparison to control cells, Rn and/or Ins caused modifications in cell viability and proliferation. p-AKT, p-ERK, p-eNOS, Mn-SOD, COX-2, and the anti-inflammatory protein COX-2 were all upregulated by ins. On the contrary, no significant changes were found in the protein expression of Cu/Zn-SOD, NF-κB and IκB. The presence of Rn produced an increase in p-ERK protein and a significant decrease in COX-2 protein expression. Furthermore, Rn significantly increased the effects of Ins on the expression of p-AKT, p-eNOS, p-ERK, Mn-SOD, and PPAR-γ. On the other hand, Rn+Ins produced a significant decrease in COX-2 expression. In conclusion, Rn facilitated the effects of insulin on the p-AKT, p-eNOS, p-ERK, Mn-SOD and PPAR-γ, signaling pathways, as well as on the anti-inflammatory and antioxidant effects of the hormone.

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.

Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an 'Urban Laboratory' as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project 'El Campo de Cebada' in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities.

Antimony (Sb) has gained significance as a critical raw material (CRM) within the European Union (EU) due to its strategic importance in various industrial sectors, particularly in the textile industry for flame retardants and as a component of Sb-based semiconductor materials. Moreover, Sb is emerging as a potential alternative for anodes used in lithium-ion batteries, a key element in the Energy transition. This study focused on exploring the feasibility of identifying and quantifying Sb mineralizations through the spectral signature of soils using reflectance spectroscopy, a non-invasive remote sensing technique, and by employing deep learning algorithms such as Convolutional Neural Networks (CNNs). Common signal preprocessing techniques were applied to the spectral data, and the soils were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Despite achieving high R-squared values, the study faces a significant challenge of generalization of the model to new data. Despite the limitations, this study provides valuable insights into potential strategies for future research in this field.

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.

The effect of the addition of maleated polyethylene (MAPE) to compounds of natural rubber (NR) and Teline monspessulana flour (TMF) previously mercerized was investigated. Two factors were analyzed: A. concentration of MAPE with five levels 2; 4; 6; 8; 10 phr (parts per hundred rubber), B. concentration of TMF with two levels 25 and 40 phr. The effect of MAPE on compatibility between NR and HTM was evaluated by tensile testing the compounds. The mixing was performed in a laboratory scale mill. The test tubes were obtained by cutting or die-cutting crosslinked peroxide sheets, these were obtained during the compression molding process. Analysis indicate that the MAPE coupling agent improved the compatibility between HTM and NR, this effect was evidenced by the values of tensile strength and elongation at break. However, the gel content determination indicates that the addition of 10 phr of MAPE crosslinking decreases due to competition with coupling reaction MAPE - HTM.

Neck circumference (NC), neck circumference to height ratio (NHtR) and neck circumference to weight ratio (NWtR) appear to be good candidates for the non-invasive management of non-alcoholic fatty liver disease (NAFLD). This study aimed to evaluate the ability of routine variables to assess and manage NAFLD in participants with obesity and NAFLD included in a 2-year nutritional intervention program. Anthropometric measurements, biochemical variables and imaging techniques were performed at different study time-points (baseline, 6, 12 and 24 months). The nutritional intervention significantly improved all anthropometric measurements as well as the glucose profile and the hepatic enzymes. NC and neck ratios combined with ALT levels and HOMA-IR showed good prediction ability for the hepatic fat content and hepatic steatosis at all the study time-points in a ROC analysis. The prediction ability of the combination panels improved when the weight loss variable was also considered. NC and neck ratios are easy anthropometric measurements that in combination with routine biochemical variables (ALT and HOMA-IR) showed good prediction ability of NAFLD. More research studies are necessary to validate the utility of these simple and easy variables as surrogate markers of NAFLD since their application could improve the prevention and management of this prevalent disease.

The blood count is crucial for assessing bone marrow's cell production and differentiation during infections, gauging disease severity, and monitoring therapeutic responses. The profile of blood count in chronic form of paracoccidioidomycosis (PCM) has been insufficiently explored. To better understand the changes in hematological cells in different stages of the PCM chronic form, we evaluated the blood count, including immature blood cells in automated equipment, before and during the treatment follow-up of 62 chronic PCM patients. Predominantly male (96.8%) with an average age of 54.3 (SD 6.9) years, participants exhibited pre-treatment conditions such as anemia (45.2%), monocytosis (38.7%), and leukocytosis (17.7%) which became less frequent after clinical cure. Anemia was more prevalent in severe cases. Notably, hemoglobin and reticulocyte hemoglobin content increased, while leukocytes, monocytes, neutrophils, immature granulocytes, and platelets decreased. Chronic PCM induced manageable hematological abnormalities, mainly in the red blood series. Monocytosis, indicating monocytes' role in PCM's immune response, was frequent. Post-treatment, especially after achieving clinical cure, significant improvements were observed in various hematological indices, including immature granulocytes and reticulocyte hemoglobin content, underscoring the impact of infection on these parameters.

Today, maritime transport is responsible for moving approximately 80 percent of the volume of world trade, which has favored Colombia, which, due to its geographical position, has managed to become one of the most competitive and dynamic economies in the world. South America. For this reason, this investigation is carried out in a port of their country, with the aim of identifying and analyzing restrictions or critical points that may cause delays in the unloading of goods, these would also cause delays in the loading of vehicles. To do this, it began with a diagnosis of the current situation through interviews with the operational personnel of the port, then a simulated model was designed in the ARENA software, in which it was observed that the weighing activities are where the queues were formed, this will cause a delay in the download. As possible solutions, it is recommended to senior management that a proper verification of the operation of the weighing equipment be carried out in order to unload goods more quickly. In addition, a replacement weighing equipment must be purchased. With this change, it would be possible to reduce inefficiencies or cost overruns caused by download delays, which are reducing the fluidity of the goods and the competitiveness of the organization

Environmental degradation leads to a totally unsustainable food system. In addition to this is-sue, the consumption of foods that improve people's health and well-being is recommend-ed. These guidelines create new challenges and the demand for alternatives to meet these needs in the short term. One of the alternatives is undoubtedly the use of by-products of winemaking, namely in the form of grape pomace flour (GPF), which is obtained in a totally sustainable way, requires no further water consumption or agricultural land, and is an ingredient that boasts all the characteristics that meet the circular economy and has colossal potential in promoting nutrition and healthy eating. To verify the benefits of using the Touriga Nacional and Arinto (Vitis vinifera L.) flour varieties, analytical determinations were made to identify and quantify different components, such as nitrogen and extractable phosphorus, ash, moisture, proteins, fats, dietary fibers, total sugars, and phenolic content. GPF could become a valuable ingredient due to its nutritional quality and high content in various polyphenols namely flavonoids and pyranoanthocyanins.

This research was carried out with the objective of analyzing the principles of social and solidarity economy in the community funds of the rural sector of Pichincha, Ecuador. Small organizations promote microcredits for local, social and economic development, representing an alternative to those managed by traditional banks. The research was descriptive, non-experimental field research. The population analyzed consisted of 220 community funds, and the size of the representative sample was 49 community organizations that practice solidarity finance. The data were collected through online questionnaires using a Likert scale, and the validity of this approach was judged by experts; the reliability of the instrument obtained was 0.95 using the Cronbach’s alpha method. The results highlight that in these organizations, the following traits prevail: associativity, self-management and organization. However, autonomy and solidarity have a negative valuation, which shows that strategies must be rethought to achieve the empowerment of the financial service. This will allow them to be sustainable and to expand with more benefits that promulgate financial activity and promote structures in rural community networks that promote local development and strengthen deficient principles as a basis for generating a greater benefit to the partners.

Colombia is noteworthy as a biodiversity hotspot, featuring an extraordinary number of en-demic orchids, birds, and butterflies. This exploratory study examines the perceptions of desti-nation image considering the cognitive and affective image in predicting behavioral intentions of ecotourists through symmetric data analysis. Using Partial Least Squares (PLS), the author(s) analyzed 64 survey responses collected of rural areas, including a new 15 statement scale spe-cialized on birdwatching. The findings support the reliability of the model, symmetric analysis presents the higher influence of emotions and affections in increasing intentions of recommen-dation, considering birdwatching as based on personal relationships. Additionally, the cognitive image for the birders despite representing destination attributes or sets of destination resources of a mental picture does not have the same impact on behavioral intentions. Therefore, manag-ers should develop positioning strategies based on the generation of emotions, because bird-watching tourists seek to have more emotional experiences.

This work deals with a systematic review of literature data concerning the theme of the integrated approach to occupational health and safety management, with particular reference to the programming of assistance plans, which guide the company's organizational choices also by aiming at the principles of the Total Worker Health. In the current regulatory framework on this issue, the UNI ISO 45001: 2018 standard assumes particular relevance, which defines the dynamic approach to occupational health and safety management systems, paying particular attention to external contextual factors that may influence corporate organizational decisions. The adoption of these systems is not mandatory, but allows companies to fulfill their duties in terms of health and safety at work, through an organizational approach aimed at awareness, involvement and participation of all subjects of the company prevention system, overcoming the phase of the mere technological and prescriptive approach, towards a holistic vision of prevention, which places the person at the center of preventive actions. In this context, the role of institutional networks and socio-economic partnerships assumes particular importance, in the activation of territorial assistance interventions to support companies for the improvement of risk management levels. To this end, the importance of verifying the effectiveness of assistance interventions emerges from the scientific debate, through the use of indicators such as quantitative ones for measuring the performance of all phases of the intervention with particular attention to the effects in terms of improved solutions developed.

Bacterial infections and resistance to antibiotic drugs represent the highest challenges to public health. The search for new and promising compounds with anti-bacterial activity is a very urgent matter. In order to promote the development of platforms enabling to the discovery of compounds with anti-bacterial activity, Fourier Transformed Mid-Infrared (FT-MIR) spectroscopy associated with the machine learning algorithms were used to predict the impact of compounds extracted from Cynara cardunculus against Escherichia coli cells. According to the plant tissue (seeds, dry and fresh leaves, and flowers) and the solvents (ethanol, methanol, acetone, ethyl acetate, and water), compounds with different compositions concerning, phenol content, antioxidant, and antimicrobial activity were obtained. Principal component analysis of spectra, allowed to discriminate compounds that inhibit the E. coli growth, according to the conventional assay. The supervised classification models enabled the prediction of the compound's impact on the E. coli growth, with the accuracy for the test data: Partial least squares-discriminant analysis of 94%; Support vector machines of 89%; k-Nearest neighbor of 72%; and a Backpropagation network of 100%. According to the promising results, the integration of FT-MIR spectroscopy with machine learning presents a high potential to promote the discovery of new compounds with antibacterial activity, thereby streamlining the drug exploratory process.

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.

Land Surface Temperature (LST) is routinely retrieved from remote sensing instruments using semi-empirical relationships between top of atmosphere (TOA) radiances and LST, using ancillary data such as total column water vapor or emissivity. These algorithms are calibrated using a set of forward radiative transfer simulations that return the TOA radiances given the LST and the thermodynamic profiles. The simulations are done in order to cover a wide range of surface and atmospheric conditions and viewing geometries. This work analyses calibration strategies, considering some of the most critical factors that need to be taken into account when building a calibration dataset, covering the full dynamic range of relevant variables. A sensitivity analysis of split-windows and single channel algorithms revealed that selecting a set of atmospheric profiles that spans the full range of surface temperatures and total column water vapor combinations that are physically possible seems beneficial for the quality of the regression model. However, the calibration is extremely sensitive to the low-level structure of the atmosphere indicating that the presence of atmospheric boundary layer features such as temperature inversions or strong vertical gradients of thermodynamic properties may affect LST retrievals in a non-trivial way. This article describes the criteria established in the EUMETSAT Land Surface Analysis – Satellite Application Facility to calibrate its LST algorithms applied both for current and forthcoming sensors.

The Galvanic Skin Response (GSR, also widely known as electrodermal activity EDA) is one of the signals related to this emotional reaction. Given the sparsity of studies related to and the variety of devices, we experimented at the Human Health Activity Laboratory with 17 healthy subjects. The goal is to know the variability of detection changes in the electrodermal activity among a test group with heterogeneous respondents in response to valence and arousal stimuli, correlating GSR biosignals measured from different body sites. We experiment with the right and left wrist, left fingers, the right foot's inner side using Shimmer3GSR, and Empatica E4 sensors. Results indicate as the most promising homogeneous GSR measure place the left fingers and right foot. Results suggest that due to a significantly strong correlation among the inner side of the right foot and left fingers and moderate correlations with the right and left wrist, the foot is a good place to measure EDA. This paper also contributes knowledge about some wearable sensor technologies available in the market. Shimmer3GSR sensor may be better reliable to homogenous detecting electrodermal activity changes, as these have fewer anomalies among the respondents. However, we found some anomalies in signals from the Empatica E4 sensor, which we discuss in this work.

Gold nanoparticles (AuNPs) exhibit improved optical and spectral properties compared to bulk materials, making them suitable for detection of DNA, RNA, antigens, and antibodies. Here, we describe a simple, selective, and rapid non-cross linking detection assay, using approx. 35 nm spherical Au nanoprobes, for a common mutation occurring in exon 19 of the epidermal growth factor receptor (EGFR), associated with non-small cell lung cancer cells. AuNPs were synthesized based on the seed-mediated growth method and functionalized with a specific 16 bp thiolated oligonucleotide using a pH-assisted method. Both AuNPs and Au nanoprobes proved to be highly stable and monodisperse by ultraviolet-visible spectrophotometry, dynamic light scattering (DLS) and electrophoretic light scattering (ELS). Our results indicate a detection limit of 1.5 µg mL−1 using a 0.15 nmol dm−3 Au nanoprobe concentration. In conclusion, this work is an effective possibility for a straight-forward, fast, and inexpensive alternative for the detection of DNA sequences related to lung cancer, leading to a potential platform for an early diagnosis of lung cancer patients.

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.

The complex interplay between dietary factors, inflammation, and macrophage polarization is pivotal in the pathogenesis and progression of chronic liver diseases (CLDs). Omega-3 fatty acids (FAs) have been attracted attention due to their potential to modulate inflammation and exert protective effects in various pathological conditions. This review explores the emerging role of omega-3 FAs and their specialized pro-resolving mediators (SPMs) in the context of macrophage polarization, with a focus on chronic liver diseases. Omega-3, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have promising effects in mitigating inflammation and enhancing the resolution of inflammatory responses. They influence the M1/M2 macrophage phenotype balance, promoting a shift towards the M2 anti-inflammatory phenotype. SPMs, such as resolvins (Rvs), protectins (PDs), and maresins (MaRs), have emerged as potent regulators of inflammation and macrophage polarization. They show anti-inflammatory and pro-resolving properties. These mediators modulate the expression of cytokines, facilitate the phagocytosis of apoptotic cells, and promote tissue repair. MaR1, in particular, has demonstrated significant hepatoprotective effects by promoting M2 macrophage polarization, reducing oxidative stress, and inhibiting key inflammatory pathways such as NF-κB. In the context of CLD, such as nonalcoholic fatty liver disease (NAFLD) and cirrhosis, omega-3 and their SPMs have shown promise in attenuating liver injury, promoting tissue regeneration, and modulating macrophage phenotypes. However, the mechanisms underlying their effects and their interactions with other cell types within the liver microenvironment require further investigation. Understanding the intricate relationship among SPM and macrophage polarization holds unlimited potential for the development of novel therapeutic strategies for chronic liver diseases.

Metal-organic frameworks (MOFs) have been subject of extensive scientific investigation in the last three decades and, currently, are one of the type of compounds most studied to be potentially applied in a wide range of distinct catalytic processes. Pristine MOF compounds provide several intriguing benefits for catalytic applications, including high interior surface areas and densities of active sites, allowing high catalytic reaction rates per volume, post-synthesis modified with com-plementary catalytic groups, enabling multiple functional groups to catalyze the reaction. Most of large-scale catalytic applications, including those in fuel processing, gas emission reduction and chemical synthesis, nevertheless the pristine MOFs often reveal limited stabilities and opportuni-ties for regeneration at high temperatures. As a result, the real applications of MOFs in these tech-nologies are likely to be constrained, and their controlled thermal modification aiming the prepa-ration of MOF-derivative compounds has been applied to induce crystalline structural changes and increase their structural stability, enhancing its potential applicability in more severe catalytic processes. Recent advances concerning the use of this strategy to boost the catalytic potential of the MOF-derivative compounds are outlined in this short-review article.

This study analyses the changes in land use in the Sado estuary (West-Central Portugal) based on a multitemporal analysis of cartographic data from the 19th century and remote sensing land use maps from the 21st century, updated by field work. A GIS plotting of land-use evolution is summarized in a quantitative table. The comparison shows the changes in land use, with increasing occupation by human economic activities, including extensive agriculture and forestry, as well as localized urbanization and industrialization. The main elements of the landscape impacted by anthropogenic uses were: i) hydrography - river dams affected the flow dynamics and sedimentary processes in the estuary; ii) vegetation – increasing agriculture and forestry reduced the areas of native vegetation, nowadays mostly occupied by vineyards, pine forests and cork oaks. iii) wetlands - tidal and alluvial plains are being occupied by rice cultivation, aquaculture, industries, and ports; iv) coastal dunes – new developments are occupying large areas of Holocene coastal dunes; v) natural environment – mining and dredging affected some habitats and biodiversity. This analysis is intended to help the territorial organization of present and future economic activities, as well as to reduce environmental and social problems, promoting long-term sustainability of this rapidly evolving region.

The use of active video games or exergames has been booming recently, as they are motivating and promote exercise and healthy lifestyle habits for their users, and these immersive virtual reality (IVR) exercise programs could be compared to traditional physical exercise programs. A starting point for this would be to explore the physiological responses that can be generated by its use. Therefore, the main objective of this study was to evaluate the response across certain physiological parameters (heart rate, blood pressure and stress) after an IVR exergame exposure in a sample of healthy adults, and secondarily to explore its feasibility and usefulness as a tool to facilitate physical exercise. 37 healthy adults (22-54 years, 54.1% women) participated in the study. They carried out one exergaming session with the HTC Vive ProTM hardware. The primary outcome was evaluated using the concentration of cortisol, heart rate and blood pressure. Secondary outcomes were evaluated with safety using the Simulator Sickness Questionnaire (SSQ); usability evaluated with the System Usability Scale (SUS); personal experiences evaluated with Game Experience Questionnaire (GEQ) and perceived exertion through the Borg perceived effort scale. All participants completed the IVR session without significant adverse effects, and all physiological parameters analysed increased significantly in relation to pre-intervention levels. Perceived exertion corresponded to a moderate to intense exercise (6.30±0.50/10 on the modified Borg scale). All the sample considered the experience as good or very good and would recommend it. These findings support that our IVR session can be compared to a moderate to intense physical activity, as it involved similar perceived exertion with significant increases in heart rate, blood pressure and salivary cortisol levels.

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 < 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.

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.

Artificial insemination (AI) is considered as the most efficient feasible tool to improve the dairy cows’ profitability and productivity. In bovines, AI helps to promote genetic improvement and can positively impact the rural economy. The achievement of education in rural populations was one of the Millennium Development Goals (MDGs), made by the United Nations. During the last World Summit on Sustainable Development (WSSD), it was concluded that most of the world’s poor, illiterate and undernourished population lives in rural areas; therefore, access to education is considered one of the greatest challenges for governments in countries with developing economies. To determine the effects of a theoretical-practical training program related to rural management and leadership, AI, and bovine genetic improvement, on the perception and level of knowledge in a rural Colombian population that has been affected by the armed conflict. Phase 1. Included the practical and theoretical training of undergraduate animal sciences students in three dimensions rural management; leadership (D-ML), AI in bovines (D-AI), and genetic improvement (D-GI) after training students were evaluated and selected according to their skills, characteristics, solidarity skills, and their social sensitivity was identified. Phase 2. Included the socioeconomic characterization and training of rural residents by students and field experts in three dimensions D-ML, D-AI, and D-GI. After training we evaluated the perception and level of knowledge before and after training in 63 rural residents using an evaluative instrument. The data before and after (post-test) of the theoretical-practical training, were analyzed to obtain a statistical significance. The perception of knowledge in rural residents was low for general knowledge (2.48±0.76, p ˂ 0.05), D-ML (2.89±1.18, p ˂ 0.05) and D-AI and D-GI (2.17±0.83, p ˂ 0.05). On the other hand, before the theorical-practical training the level of general knowledge was 45.9%, however, after the training increased at 77.6% (p<0.01), while the level of knowledge for the D-AI was increased from 38.5 % to 80.6 % (p ˂ 0.05) after training. Regarding the level of knowledge for the D-GI pre-training was 50.8 and increased to 73.0% (p<0.01) then after. Finally, the level of knowledge for the D-ML was increased (p<0.01) from 54.8 before training to 75% after training. Altogether, the rural extension programs contribute to the closing of knowledge gaps in relation to the use of reproductive biotechnologies and bovine management in rural areas affected by armed conflict.

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.

⦁ 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.

This review presents an updated overview of research concerning Leishmania protein structures, primarily sourced from the Protein Data Bank (PDB), that play a role in the metabolic pathways of the Leishmania parasite. Furthermore, we assess the current progress in the identification and development of bioactive chemical agents aimed at addressing this substantially overlooked tropical disease. We have analyzed experimental data obtained from in vitro, in vivo and in silico sources. This data has been categorized into four main areas: a) vector taxonomy and geographic distribution; b) parasite taxonomy and geographic distribution; c) enzymatic functions of proteins engaged in parasite/host interactions throughout various developmental stages (such as oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases, and cytokines); and d) established and experimental treatments employing bioactive chemical compounds. Our objective is to establish a foundational point of reference for research efforts concentrating on the elucidation of interaction mechanisms and the processes of ligand-protein activation/inactivation, specifically linked to Leishmania infections. Consequently, we emphasize enzymes recognized for their involvement in the biochemical pathways incited during Leishmania infection episodes. This review encapsulates the current understanding, offering insights to inform and direct future explorations aimed at targeting proteins and pathways to enhance the management of Leishmania-related diseases.

Cranio-maxillofacial structure is a region of particular interest in the field of regenerative medicine due to both its anatomical complexity and the numerous abnormalities affecting this area. However, this anatomical complexity is what makes possible the coexistence of different microbial ecosystems in the oral cavity and the maxillofacial region, contributing to the increased risk of bacterial infections. In this regard, different materials have been used for their application in this field. These materials can be obtained from natural and renewable feedstocks or by synthetic routes with desired mechanical properties, biocompatibility and antimicrobial activity. Hence, in this review, we have focused on bio-based polymers, which by their own nature, by chemical modifications of their structure, or by their combination with other elements, provide a useful antibacterial activity as well as the suitable conditions for cranio-maxillofacial tissue regeneration. This approach has not been reviewed previously, and we have specifically arranged the content of this article according to the resulting material and its corresponding application, reviewing guided bone regeneration membranes; bone cements; and devices and scaffolds for both soft and hard maxillofacial tissue regeneration, including hybrid scaffolds, dental implants, hydrogels and composites.

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.

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.

Background: Depending on the phase of the menstrual cycle the athlete is in, some kinetic, physiological and fatigue variables will show differences. The aim of this study is to analyze whether there are changes in these variables over the course of the menstrual cycle. Methods: Eight regular female runners and triathletes performed a maximal treadmill test, as well as a submaximal test (6’ stages at 50%, 60% and 80% of maximal aerobic speed) in each of the phases of the menstrual cycle: bleeding phase (day 2.4 ± 0.7), follicular phase (day 10.4 ± 2.2) and luteal phase (day 21.8 ± 2.1). Running dynamics were measured (using RunScribe) at the end of each test, as were lactate concentration, heart rate and fatigue (evaluated on a scale of 0 to 5). Results: Higher shock (G) values were recorded in the bleeding phase and higher vertical spring stiffness (kN/m) in the follicular phase. The phase of the menstrual cycle had a significant effect on average and peak heart rate, which was significantly higher in the follicular phase. Conclusions: Higher vertical spring stiffness was observed in the follicular phase, as well as higher peak and average heart rate.

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).

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.

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 presence of heavy metals in cocoa crops is currently a serious problem for farmers and producers in various regions of Peru. Exports of cocoa and its derivatives to European markets are threatened by possible indications of contamination of heavy metals such as Cadmium (Cd) in cocoa beans for export, some at levels higher than those allowed by food regulations established by European Community, which are oriented to consumer protection. The possible sources of cadmium contamination in cocoa crops can be due to natural activities, such as volcanic activities, erosion processes and sedimentation in rocks that contain minerals with a high content of heavy metals (Greenockite, Burnsite, Hawleite, among others), and by anthropogenic activities such as: mining of associated deposits, agriculture (use of fertilizers), smelting of minerals and burning of fossil fuels. Currently, there is no information about contents of heavy metals in areas located in The Campo Verde-Honoria-Tournavista corridor (Ucayali Region and Huanuco Region), due to this, in this work we make a study of this region. A methodology will be used to take cocoa samples from the seed and soil in these areas, and then through chemical analysis, determine the concentrations of heavy metals, using an atomic absorption spectrophotometer. As a consequence of this study, we determined and concluded that the concentrations of cadmium obtained in soils are slightly higher than European standards allowed. Therefore, with this information we prepare a geochemical cadmium map in soils for the study area, which will help cocoa producers to identify areas that exceed the allowed cadmium values, in order to comply with standards that European Community demands in relation of concentration levels of heavy metals (Cadmium) in chocolate. In this way, we can carry out in the future a mitigation plan for areas with cadmium problems, which allows to reduce their content in order to export the product without any problem. .

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.

ZnO films with Ti atoms incorporated (TZO) in a wide range (0-18 at. %) have been grown by reactive co-sputtering on silicon and glass substrates. The influence of the titanium incorporation in the ZnO matrix on the structural and optical characteristics of the samples has been determined by Rutherford backscattering spectroscopy (RBS), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD). The results indicate that the samples with low Ti content (< 4 at. %) exhibit the wurtzite-like structure, with the Ti+4 ions substitutionally incorporated into the ZnO structure, forming Ti-doped ZnO films. In particular, very low concentration of Ti (<0.9 at. %) leads to a significant increase of the crystallinity of the TZO samples. Higher Ti contents give rise to a progressive amorphization of the wurtzite-like structure so samples with high Ti content (≥18at. %), displays an amorphous structure indicating the XPS analysis a predominance of Ti-O-Zn mixed oxides. The energy gap, obtained from absorption spectrophotometry, increases from 3.2 eV for pure ZnO films to 3.6 eV for those with the highest Ti content. Ti incorporation in the ZnO samples below 0.9 at. % rises both, the blue (380 nm) and green (550 nm) bands of the photoluminescence (PL) emission, thereby indicating a significant improvement of PL efficiency of the samples.

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 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.

Background: The aim of our study was to analyze the effect of socioeconomic inequalities, both at the individual and area of residence levels, on the probability of COVID-19 confirmed infection, and its variations across three pandemic waves. Methods: Retrospective cohort study. We included data from all individuals tested by COVID-19 during the three waves of the pandemic, from March to December 2020 (357,989 individuals). We studied the effect of inequalities on the risk of having a COVID-19 confirmed diagnosis after being tested using multilevel analyses with two levels of aggregation: individuals and basic healthcare area (BHA) of residence (deprivation level and type of zone). Results: Patient profile changed through the pandemic, with a predominance of low-paid employees living in deprived BHA. Workers with low salaries, unemployed and people on minimum integration income or who no longer receive the unemployment allowance, had a higher probability of COVID-19 infection than workers with salaries ≥€18,000 per year. Inequalities were higher in women and in the second wave. The deprivation level of BHA of residence influenced the risk of COVID-19 infection, especially in the second wave. Conclusions: There are inequalities in the risk of COVID-19 confirmed infection, both at individual and area level. It is necessary to develop individual and area coordinated measures in the control, diagnosis and treatment of the epidemic, in order to avoid an increase in the already existing inequalities.

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.

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.

Immune response stimulation may be an adjuvant to antimicrobial treatment. Here, we evaluated the impact of immune response modification by lysophosphatidylcholine (LPC) combined with imipenem or ceftazidime in murine models of peritoneal sepsis (PS) and pneumonia by Pseudomonas aeruginosa. Imipenem and ceftazidime-susceptible strain (Pa39), and imipenem and ceftazidime-resistant strain (Pa238) were used. Ceftazidime pharmacokinetic and pharmacodynamic parameters were determined. Therapeutic efficacy, and TNF-α and IL-10 levels were determined in murine models of PS and pneumonia by Pa39 and Pa238 treated with LPC, imipenem or ceftazidime, alone or in combination. In PS model, LPC+ceftazidime reduced spleen and lungs Pa238 concentrations (-3.45 and -3.56 log10 CFU/g; P<0.05) than ceftazidime monotherapy, while LPC+imipenem maintained the imipenem efficacy (-1.66 and -1.45 log10 CFU/g; P>0.05). In pneumonia model, LPC+ceftazidime or LPC+imipenem reduced lungs Pa238 concentrations (-2.37 log10 CFU/g, P=0.1, or -1.35 log10 CFU/g, P=0.75). For Pa39 no statistically significant difference has been observed in PS and pneumonia models between combined therapy and monotherapy. Moreover, LPC+imipenem and LPC+ceftazidime decreased and increased significantly TNF-α and IL-10 levels, respectively, in comparison with untreated controls and monotherapies. These results demonstrate the impact of immune response modification by LPC plus antibiotics on the prognosis of infections by ceftazidime-resistant P. aeruginosa.

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.

Identifying a panel of markers detecting kidney injury before the glomerular filtration rate (GFR) reduction is the challenge to improve the diagnosis and the management of acute kidney injury (AKI) in septic patients. This study evaluated the roles of tissue inhibitor metal proteinase, insulin growth factor binding protein (TIMP2*IGFBP7), and mid-regional pro-adrenomedullin (MR-proADM) in AKI patients. Patients and Methods: This study was prospectively conducted in the Intensive Care Unit (ICU) enrolling 230 patients who underwent cardiac surgery. Biomarkers were evaluated before and after 4 hours of the cardiac surgery. Results: Whereas urine and creatinine alterations appeared at 23.2 (12.7 – 36.5) hours, after cardiac surgery, urinary TIMP2*IGBP7 levels were higher at 4 hours in AKI patients (1.1±0.4 mg/l vs 0.08±0.02 mg/l; p < 0.001). Its concentration >2 mg/l increases the AKI risk within the following 24 hours, clearly identifying the population at high risk of renal replacement therapy (RRT). In patients with sepsis, MR-proADM levels were 2.3 nmol/l (0.7–7.8 nmol/l), with the highest values observed in septic shock [5.6 nmol/l (3.2–18 nmol/l)] and a better diagnostic profile than procalcitonin and C-reactive protein to identify septic patients. MR-proADM values >5.1 nmol/l and urine TIMP2*IGBP7 levels > 2 mg/l showed a significantly faster progression to RRT, with a mean follow-up time of 1.1 days. Conclusions: TIMP2*IGBP7 and MR-proADM precociously diagnose AKI in septic patients after cardiac surgery, giving prognostic information for RRT requirement.

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.

(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.

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.

Plant species are precursors of a wide variety of secondary metabolites that, besides having useful activity for themselves, can also be used by humans for their consumption and economic benefit. Pepper (Capsicum annuum L.) fruit is not only a common food and spice source, but it also stands out for containing high amounts of antioxidants (such as vitamins C and A), polyphenols and capsaicinoids. Particular attention has been paid to capsaicin, whose anti-inflammatory, antiproliferative and analgesic activities, have been proven. Due to the potential interest in pepper metabolites for human use, in this project, we carried out an investigation to identify new bioactive compounds of this crop is carried out. To achieve this, we developed a metabolomic approach, using an HPLC (high-performance liquid chromatography) separative technique coupled to metabolite identification by high resolution mass spectrometry (HRMS). After chromatographic analysis and data processing against metabolic databases, 12 differential bioactive compounds were identified in sweet pepper fruits, including quercetin and its derivatives, L-tryptophan, phytosphingosin, FAD, gingerglycolipid A, tetrahydropentoxylin, blumenol C glucoside, colnelenic acid and capsoside A. The abundance of these metabolites varied depending on the ripening stage of the fruits, either immature green or ripe red. We also studied the variation of these 12 metabolites upon treatment with exogenous nitric oxide (NO), a free radical gas involved in a good number of physiological processes in higher plants such as germination, growth, flowering, senescence, and fruit ripening, among others. Overall, it was found that the content of the analysed metabolites was modulated by the ripening stage and by the presence of NO. The metabolic pattern followed by quercetin and its derivatives, as a consequence of the ripening stage and NO treatment, was also corroborated by transcriptomic analysis of genes involved in the synthesis of these compounds. This opens new research windows on the pepper fruit’s bioactive compounds with nutraceutical potentiality, where biotechnological strategies can be applied for optimizing the level of these beneficial compounds.

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.

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.

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.

Annually, the oak forests of the Zagros Mountain chains, in western Iran and northeastern Iraq, face recurring challenges posed by forest fires, particularly in the Kurdo-Zagrosian forests situated in western Iran and northeastern Iraq. Assessing fire susceptibility relies significantly on vegetation condition. Integrating in situ data, Remote Sensing (RS) data, alongside the integration of Geographical Information Systems (GIS), presents a cost-effective and precise approach to capturing environmental conditions before, during, and after fire events, minimizing the need for extensive fieldwork. This study refines and applies the Zagros Grass Index (ZGI), a local vegetation index tailored to discern between grass-covered surfaces from tree canopies in Zagros forests, identifying the grass masses as the most flammable fuel type. Utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) product as input, from 2013 to 2022, the ZGI aims to mitigate the influence of tree canopies, isolating NDVI values solely attributable to grass cover. By incorporating phenological characteristics of forest trees and grass species, the ZGI outperforms NDVI in mapping grass-covered areas that are crucial for fire susceptibility assessment in the study region. Results demonstrate a strong overlap between ZGI-based maps and recorded fire occurrences, validating the efficacy of the index in fire susceptibility estimation.

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.

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.

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.

The most common form of mixed dementia (MixD) is constituted by abnormal protein deposits associated with Alzheimer´s disease (AD) that coexist with vascular disease. Although olfactory dysfunction is considered a clinical sign of AD-related de-mentias, little is known about the impact of this sensorial impairment in MixD at molecular level. To address this gap in knowledge, we have assessed olfactory bulb (OB) proteome-wide expression in MixD subjects (n=6) respect to neurologically intact controls (n=7). Around 9% of the quantified proteins were differentially expressed, pinpointing aberrant proteostasis involved in synaptic transmission, nucleoside monophosphate and carbohydrate metabolisms and neuron projection regeneration. In addition, net-work-driven proteomics revealed a modulation in cell-survival related pathways such as ERK, AKT and PDK1-PKC axis. Part of the differential OB protein set was not specific of MixD, being also deregulated across different tauopathies, synucleinopathies and tardopathies. However, the comparative functional analysis of OB proteome data between MixD and pure AD pathologies deciphered commonalities and differences between both related phenotypes. Finally, olfactory proteomics allowed to propose serum Prolow-density lipoprotein receptor-related protein 1 (LRP1) as a candidate marker to differentiate AD from MixD phe-notypes.

Previously, using the conjugate frame-based reconciliation approach, we defined a method to correct errors produced in pairs of non-orthogonal quantum states that are transmitted through a quantum key distribution (QKD) link. The security of the frame-based reconciliation was discussed in order to deal with Photon Number Division (PNS) attack and Intercept and Forward (IR) attack, among others. However, until the time of publication we did not have the distillation software to test our method. In this article, following the conjugate frame distillation method, we present the implementation of the post-processing system that demonstrates that it is capable of correcting errors in the presence of error rates close to unity. The system shows that when the number of double-sensing events at Bob's station is as low as 100, the number of secret bits stays above 4500 bits in about 12 seconds, giving a secret rate of 375 bits per second while that the channel error rate reaches 90\%.

The education system has become even more complex following the global pandemic, which saw face-to-face teaching transition to virtual teaching. To cope with this abrupt transition, it is essential that teachers had a sufficient level of digital teaching competence. This article aims to increase awareness of teachers' self-perception of their digital teaching competences in the educational field. Specifically, this study explores Spanish secondary school teachers’ knowledge and use of different ICT tools by evaluating their competence based on different areas proposed by The National Institute of Technology and Professional Development (Instituto Nacional de Tecnologías Educativas y de Formación del Profesorado, INTEF), Madrid, Spain. From the results of the questionnaires, we have determined that teachers consider themselves to have an upper intermediate level of digital teaching competence, although there are still shortcomings that need to be addressed in order to improve this level of competence, and its true integration in the teaching–learning process.

This paper, the second in a series of two, describes the experimental results for removing arsenic from the dust collected in the electrostatic precipitators of a fluidized bed roasting oven (RP dust). The RP dust produced is discharged as a toxic waste, although its copper content is close to 20% by weight. This work aims to process the RP dust; until obtained a material with a low concentration of arsenic, which could be recirculated in smelting operations and recover the valuable metals. Based on the successful experience obtained in the first document with FS dust, this work proposes to use the reduction-sulphidation-volatilization processes to carry out the volatilization of arsenic from RP dust. A set of experiments was realized in the roasting different ratios of the mixture of copper concentrate / RP dust, sulfur / RP dust varying temperature and roasting time; to reach an arsenic concentration <0.5% by weight. The RP dust was characterized using different techniques, that confirmed more than 20% by weight of copper and describing its structure as a small particle agglomerate (<5 µm), with a complex sulfoxide morphology. The main results indicated: that for a 75/25 mixture of the copper concentrate / PR dust under 700 ° C, 15 minutes roasting time with air atmosphere, the arsenic volatilization was 96% by weight. Meanwhile, for a 5/95 mixture of sulfur / RP dust, at 650 ° C, the volatilization of arsenic was 67% by weight.

This paper (the first of a series of two) seeks to describe the experimental results of removing arsenic from dust collected in electrostatic precipitators of copper into the pyro-metallurgy gas cleaning systems. The first work corresponds to the treatment of dust contained in gas off generated in the copper Flash Smelting Furnace process (FS dust), while the second focuses on the treatment of dust generated from a Fluidized Bed Roasting Furnace (RP dust). The dust is complex sulphur-oxide-metals with concentrations of copper above 10 wt % and relatively high concentrations of silver. Due to the dust has an arsenic’s concentration above 5 wt %, makes it difficult to recover valuable metals through hydro-metallurgical processes or by direct recirculation of the dust into a smelting furnace. Thus, the development of pyrometallurgical processes aimed to reduce the concentration of arsenic in dust is the main purpose of this study, particularly the production of a material suitable for recirculation in smelting operations. The works conducted provide a detailed characterization of the dust, including Quantitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN), Scanning electron microscope-Energy Dispersive X-ray analysis (SEM/EDS), X-ray diffraction (XR-D), elemental chemical analysis using Atomic Adsorption (A. A.) and X-Ray Fluorescence (X-RF). By considering that arsenic volatilization requires a process of reduction-sulphidation-volatilization, the works explore the roasting of mixtures of copper concentrate/dust, sulphur/dust and pyrrhotite/dust. The degree of volatilization was determined by elemental chemical analysis of arsenic in the mixture after and before the roasting process. The results indicated the effect of parameters such as temperature, gas flow, gas composition and the ratio of mixtures (concentrate, sulphur or pyrrhotite)/dust on the volatilization of arsenic. The findings indicate that the concentration of arsenic in the FS dust can be reduced to a relatively low level (<0.5 wt %), allowing to the material to be recirculated into smelting processes.

Electricity distribution network operators face several operational constraints in the provision of safe and reliable power given that investments for network area reinforcement must be commensurate with improvements in network reliability. This paper provides an integrated approach for assessing the impact of different operational constraints on distribution network reliability by incorporating component lifetime models, time-varying component failure rates as well as the monetary cost of customer interruptions in an all-inclusive probabilistic methodology that applies a time-sequential Monte Carlo simulation. A test distribution network based on the Roy Billinton test system is modelled to investigate the system performance when overloading limits are exceeded as well as when preventive maintenance is performed. Standard reliability indices measuring the frequency and duration of interruptions, and the energy not supplied are complemented with a novel monetary reliability index. The comprehensive assessment includes not only average indices but also their probability distributions to adequately describe the risk of customer interruptions. Results demonstrate the effectiveness of this holistic approach as the impacts of operational decisions are assessed from both reliability and monetary perspectives. This informs network planning decisions through optimum investments and consideration of customer outage costs.

The spatial segregation is a characteristic of Latin American cities, resulting in distinct dynamics of social inclusion and exclusion at both spatial and identity levels. Then, specific green spaces may convert into appreciated and contested territories, where various actors negotiate their uses and regulations. Considering a case-study in a green icon of the metropolitan city of Santiago de Chile, the main objective of the present study was to describe and comprehend the uses and meanings of the Quebrada Macul park among different social groups over the past two decades. We employed qualitative methods including six in-depth interviews with key informants (social and ecological leaders, historical neighbors, and park workers), five participant observations in the park, and statistical analysis of visitors. Results reveal that (1) the transition of being a popularly used hill to a metropolitan park rises tensions between public and private statuses of place; (2) conflicts emerge regarding who uses the space and how, reflecting power dynamics among different social groups; (3) the park, beyond being a public space, holds significant identity value for its historical residents, both for those who fought for its recovery and those who have lived closely, so processes of forgetfulness might be resentful. We conclude on enduring meanings of the park associated with the struggle for the place among different groups, highlighting the role of memory for the social integration of groups among natural spaces.

Background: our purpose is to assess the effectiveness and safety of sacubitril/valsartan (SV) in “real-world” patients with heart failure and reduced ejection fraction (HFrEF), including a broader spectrum of patients than those in clinical trials and evaluating variables not previously described in the literature. Methods: real-world study in HFrEF patients (N:204), both in and out-patients, who started SV between October 2017 and December 2018. We performed a prospective analysis with a 12-month follow-up. The study outcomes were effectiveness and safety, measured by individual parameters and combined endpoints, comparing the pre and post practice periods. Results: at the end of follow-up, an improvement of left ventricle ejection fraction (LVEF): 29.8% vs 33.7; p<0.0001, a decrease in NT-proBNP levels (3928 pg/mL vs 2902 pg/mL; p=0.012), number of hospital admissions (141 vs 35; p<0.0001) and percentage of patients with implantable cardioverter defibrillator (ICD) indication (79.9% vs 49.5%; p<0.0001) were observed. Of our population, 81.3% met a combined efficacy endpoint (defined by increase of LVEF, reduction of hospital admission or improvement in functional class). No differences were observed in parameters regarding safety. Conclusions: Sacubitril/valsartan has brought about a revolution in the therapeutic management of HFrEF patients and its use may raise questions about what is considered "optimal medical therapy" prior to implantation of cardiac devices.

This paper presents a study of different types of parametric signals with application to underwater acoustic communications. In all the signals, the carrier frequency is 200 kHz, which corresponds to the resonance frequency of the transducer under study and different modulations are presented and compared. In this sense, we study modulations with parametric sine sweeps (4 to 40 kHz) that represent binary codes (zeros and ones), getting closer to the application in acoustic communications. The different properties of the transmitting signals in terms of bit rate, directivity, efficiency and power needed are discussed as well.

The use of covers to protect blueberry orchards from adverse weather events has increased due to the variability in climate patterns, but the effects of rain cover and netting materials on yield and fruit quality have not been studied yet. This research evaluated the simultaneous effect of LDPE plastic cover, woven cover and netting materials on environmental components (UV light, PAR, NIR and growing degree days, GDD), plant performance (light interception, leaf area index, LAI, yield and flower development), and fruit quality traits (firmness, total soluble solids and acidity) in two blueberry cultivars. On average, UV transmission under netting was 11% and 43% higher compared to that under woven and LDPE plastic covers, while NIR was 8 -13% higher with both types of rain covers, with an increase in fruit air temperature and GDD. Yield was 27% higher under woven cover with respect to netting, but fruit firmness values under netting were 12% higher than those of LDPE plastic cover. Light interception, LAI and flower development explained 64% (p=0.0052) of the yield variation due to the cover material effect. The obtained results suggest that the type of cover differentially affects yield and fruit quality in blueberries due to the specific light and temperature conditions generated under these materials.

The aim of this work is to evaluate the impact of proposed modifications to conventional capturing and discharging effluents devices in Subsurface Flow Wetland (SSFW) systems. Main modifications proposed consist on extending the influence of the capture and discharge device in such a way that the SSFW width and height are fully covered. Additionally an SSFW prototype was built as pilot including the proposed modifications and the impact of the innovative device is measured based on the efficiency of the Chemical Oxygen Demand (COD) removal as compared to a traditionally built SSFW. The results show that for the innovative device, the COD removal was 10% higher than for the conventional device.

The solvent extraction of gold(III) by undiluted 2-ethylhexanol or dissolved in toluene from HCl solution has been investigated. The numerical analysis of gold distribution data suggests the formation of HAuCl4·L and HAuCl4·2L (L= 2-ethylhexanol) species in the organic phase with formation constants K11= 38 and K12= 309, respectively. The results derived from gold(III) distribution have been implemented in a solid-supported liquid membrane system. The influence of several variables on gold transport was considered: feed and receiving phases stirring speeds, HCl and gold concentrations in the feed phase and carrier concentration in the membrane phase as well as the presence of base metals (Fe,Cu,Ni) and PGMs in the feed phase. Also, diffusional resistances to mass transfer are estimated. Gold is recovered as zero valent nanoparticles.

This paper provides an overview of flexible and wearable respiration sensors with emphasis on their significance in healthcare applications. The paper classifies these sensors based on their operating frequency distinguishing between high-frequency sensors which operate above 10 MHz and low-frequency sensors. The operating principles of breathing sensors as well as the materials and fabrication techniques employed in their design are addressed. The research highlights the need for robust and flexible materials to enable the development of reliable and comfortable sensors. Finally, the paper presents potential research directions and proposes research challenges in the field of flexible and wearable respiration sensors. Thus, identifying emerging trends and gaps in knowledge, it encourages further advancements and innovation in the rapidly evolving domain of flexible and wearable sensors.

The objective of this work is to evaluate the impact of the innovative modifications made to the conventional effluent capture and discharge devices used in subsurface flow wetlands (SSFW). The main modifications developed consist on extending the influence of the capture and discharge device in such a way that the SSFW width and height are fully covered. This improved innovative device was applied and evaluated in two subsurface flow wetlands, one on a pilot scale and one on a real scale. To evaluate the impact of the innovative device with respect to conventional one in the operational functioning of subsurface flow wetlands, the elimination of chemical oxygen demand was measured and compared. The results show that for the innovative device, the COD removal was 10% higher than for the conventional device, confirming the validity and effectiveness of the modifications implemented in the effluent capture and discharge devices used in SSFW.

Chromatin is dynamically remodeled to adapt to all DNA-related processes, including DNA damage responses (DDR). This adaptation requires DNA and histone epigenetic modifications, which are mediated by several types of enzymes; among them are lysine methyltransferases (KMTs). Methods: KMT inhibitors, chaetocin and tazemetostat (TZM), were used to study their role in the DDR induced by ionizing radiation or doxorubicin in two human sarcoma cells lines. The effect of these KMT inhibitors was tested by the analysis of chromatin epigenetic modifications, H4K16ac and H4K20me2. DDR was monitored by the formation of γH2AX, MDC1, NBS1 and 53BP1 foci, and the induction of apoptosis. Results: Chaetocin and tazemetostat treatments caused a significant increase of H4K16 acetylation, associated with chromatin relaxation; and increased DNA damage, detected by the labeling of free DNA-ends. These inhibitors significantly reduced H4K20 dimethylation levels in response to DNA damage and impaired the recruitment of 53BP1, but not of MDC1 and NBS1, at DNA damaged sites. This modification of epigenetic marks prevents DNA repair by the NHEJ pathway and leads to cell death. Conclusion: KMT inhibitors can function as sensitizers to DNA damage-based therapies and be used in novel synthetic lethality strategies for sarcoma treatment.

Neuroendocrine prostate cancer (NEPC) is a highly aggressive subtype of prostate cancer (PC) that commonly emerges through a transdifferentiation process from prostate adenocarcinoma and evades conventional therapies. Extensive molecular research has revealed factors that drive lineage plasticity, uncovering novel therapeutic targets to be explored. A diverse array of targeting agents is currently under evaluation in pre-clinical and clinical studies with promising results in suppressing or reversing the neuroendocrine phenotype and inhibiting tumor growth and metastasis. This new knowledge has the potential to contribute to development of novel therapeutic approaches that may enhance clinical management and prognosis of this lethal disease.

Breakthrough curves for the adsorption of H2S using a metal-oxides mixture were predicted using the Bohart-Adams model of fixed bed adsorption. This mixture (ZnMn2O4+ZnO+Mn2O3) came from the processing of an urban waste as spent alkaline batteries were. The H2S adsorption experiments were carried out in a fixed-bed column at 20º C, and under various experimental conditions: gas flow rate, inlet H2S concentration and adsorbent dosage. Curves predicted by the model matched well with experimental data, providing data for the possible scale-up of the system. At the various experimental variables, the efficiency of the column, were also provided in the work. This investigation demonstrated the usefulness of a waste material, like spent alkaline batteries, to provide an adsorbent material to mitigate the problem of the presence of this harmful gas.

Superscaling in electron scattering from nuclei is re-examined paying special attention to the definition of the averaged single-nucleon responses. The validity of the extrapolation of nucleon responses in the Fermi gas has been examined, which previously lacked a theoretical foundation. To address this issue, we introduce new averaged responses with a momentum distribution smeared around the Fermi surface, allowing for momenta above the Fermi momentum. This approach solves the problem of negativity in the extrapolation away from the scaling region and, at the same time, validates its use in the scaling analysis. This work has important implications for the interpretation of scaling data and contributes to the development of a more complete understanding of the scaling approach.

This study evaluates various safety aspects of standardized impacts that cyclists may suffer while wearing a bicycle helmet, by combining a partially validated finite element model of the cranio-cervical region and a newly developed bicycle helmet model. Under EN 1078 standardized impact conditions, the results of simulated impact tests show that the helmet can absorb 40% to 50 % of the total impact energy at impact velocities above 4 m/s. Further, based on a relationship between Head Injury Criterion and the risk of injury from field data, the results of the simulations suggest that minor injuries may occur at impact velocities of 10 km/h, serious injuries at 15 km/h, and severe injuries at 20 km/h. Fatal injuries will likely occur at impact velocities of 30 km/h and higher.