Natural carotenoids are secondary metabolites that exhibit antioxidant, anti-inflammatory and anti-cancer properties. These types of compounds are in high demand by pharmaceutical, cosmetic, textile and food industries, leading to the search for new natural sources of carotenoids. In recent years, the production of carotenoids from bacteria has become of great interest for industrial applications. In addition to carotenoids with C40-skeletons, some bacteria have the ability to synthesize characteristic carotenoids with C30-skeletons. In this regard, a great variety of methodologies for the extraction and identification of bacterial carotenoids has been reported and this is the first review that condenses much of this information. To understand the diversity of these carotenoids, we present their biosynthetic origin in order to focus on the methodologies employed in their extraction and characterization. Special emphasis has been made on high-performance liquid chromatography-mass spectrometry (HPLC-MS) for the analysis and identification of bacterial carotenoids. We end up this review showing their potential commercial use of bacterial carotenoids. This review is proposed as a guide for the identification of these metabolites, which are frequently reported in new bacteria strains.

Andean blueberries are wild berries grown and consumed in Ecuador which contain high values of bioactive compounds, mainly anthocyanins, with powerful antioxidant activity. The aim of this study was to evaluate the profile and contents of (poly)phenols and carotenoids in Andean blueberry by HPLC-DAD-MSn and determine a wide range of its biological activities. The antioxidant capacity of this fruit was evaluated in vitro by three different methods and in vivo using the zebrafish animal model, also the toxicity effect was determined by the zebrafish embryogenesis test. Besides, the antimicrobial activity and the capacity of Andean blueberry to produce hemagglutination in blood cells were evaluated. Finally, the bioaccessibility of (poly)phenols and related antioxidant capacity were determined in the different phases of an in vitro digestion. The global results indicated no toxicity of Andean blueberry, weakly bacteriostatic activity, and high contents of anthocyanins and antioxidant capacity, which were partially bioaccesible in vitro (~ 50 % at the final intestinal step), contributing to the knowledge of its health benefits for consumers and its potential use in the food and pharmaceutical industry as functional ingredient.

Chronic lymphocytic leukemia (CLL) is a hematologic malignancy characterized by progressive accumulation of a rare population of CD5+ B lymphocytes in peripheral blood, bone marrow and lymphoid tissues. CLL exhibits remarkable clinical heterogeneity, with some patients presenting with indolent disease and others progressing rapidly to aggressive CLL. The significant heterogeneity of CLL underscores the importance of identifying novel prognostic markers. Recently, the RAS-related gene RRAS2 has emerged as both a driver oncogene and a potential marker for CLL progression, with higher RRAS2 expression associated with poorer disease prognosis. Although missense somatic mutations in the coding sequence of RRAS2 have not been described in CLL, this study reports the frequent detection of three somatic mutations in the 3' untranslated region (3'UTR) affecting positions +26, +53, and +180 downstream of the stop codon in the mRNA. An inverse relationship was observed between these three somatic mutations and RRAS2 mRNA expression, which correlated with lower blood lymphocytosis and better prognosis. These findings highlight the importance of RRAS2 overexpression in CLL development and prognosis and point to somatic mutations in its 3'UTR as novel mechanistic clues. Our results may contribute to the development of targeted therapeutic strategies and improved risk stratification for CLL patients.

Machines for direct digital inkjet printing on cylindrical containers are a new technology out on the market. Their commercialization in the industrial sector has been affected by their high precision. This leads to the use of mechanisms with narrow manufacturing tolerances and to the search for topologies that have the least accumulated error without affecting quality. Machines with topologies to work on flat substrates have printing and productivity problems working on cylindrical substrates. This research paper presents the qualitative design of a direct digital inkjet printer working over cylindrical substrates comparing five mechanical topologies; three topologies with radial distribution and two topologies with parallel distribution. The aim of these topologies is to find the precision, quality and efficiency of the printer taking into account the restrictions present in its construction. Each topology has separate constitutive mechanisms, it is analyzed the tolerance ranges between the print head and the substrate whose cumulative error maximizes the inkjet print resolution to determine precision. From five Topologies, number 1, 2 and 5 meet the requirements. the topology 2 meets the requirements but it is not able to be developed due to current technological limitations.

The Region of Arica and Parinacota is characterized as an agricultural region located in Atacama Desert at the extreme north of Chile. Its agriculture has allow developing the economy of pre- and post-Hispanic communities, which have been settled since colonial times at different locations in the region. This article is focused on how Aymara communities of Lluta Valley and Precordillera of Arica and Parinacota Region have been included as part of Chilean population, particularly, from social and economic point of view. Furthermore, a characterization of agronomic aspects of the main towns of this zone, and commercialization of agricultural and livestock is included. It must be considered that the evolution of this region would have an important impact in the safeguard on endemic flora and fauna so that it is imperative to protect the genetic heritage of local species and to promote new technologies which allow the production of commercial products from Arica and Parinacota Region.

ChatGPT has significantly increased in popularity in recent months because of its capacity to generate novel content and provide genuine responses to questions. Nevertheless, like all technologies, it is crucial to assess its limitations and features prior to implementing it into an educational setting. A major obstacle associated with ChatGPT is its tendency to produce consistent yet occasionally unreliable and inaccurate responses. Our study provides students with training in this area, and its objective was to analyse the opinion of those same university students studying education-related degrees regarding the efficacy of the usefulness of ChatGPT for their learning. We used a mixed methodology and two instruments for data collection: questionnaires and discussion groups. The sample comprised 150 university students pursuing degrees in Teaching and Social Education. The results show that the majority of students are familiar with the technology, but have not had any formal training at university. They use this tool to complete academic assignments outside the classroom, and they emphasise the need for training in it. Furthermore, following the training, the students highlight an increase in motivation and a positive impact on the development of generic skills such as information analysis, synthesis and management, problem-solving and learning how to learn. Ultimately, this study provides an opportunity to consider the implementation of educational training of this tool at university level in order to ensure its appropriate use.

Deep learning machines are computational models composed of multiple processing layers of adaptive weights to learn representations of data with multiple levels of abstraction. Their structure is mainly reflecting the intuitive plausibility of decomposing a problem into multiple levels of computation and representation since it is believed that higher layers of representation allow a system to learn complex functions. Surprisingly, after decades of research, from learning and design perspectives these models are still deployed in a heuristic manner. In this paper, deep learning feed-forward machines are modeled from a statistical mechanics point of view as disordered physical systems where its macroscopic behavior is determined in terms of the interactions defined between the basic constituent of these models, namely, the artificial neuron. They are viewed as the equilibrium states of a theoretical body that is subject to the law of increase of the entropy. The study of the changes in energy of the body when passing from one equilibrium state to another is used to understand the structure and role of the phase space of the system, the stability of the equilibrium states, and the resulting degree of disorder. It is shown that the topology of these models is strongly linked to their stability and resulting level of disorder. Furthermore, the proposed theoretical characterization permit to assess the thermodynamic efficiency with which information can be processed by these models, and to provide a practical methodology to quantitatively estimate and compare their expected learning and generalization capabilities. These theoretical results provides new insights to the theory of deep learning and their implications are shown to be consistent through a set of benchmarks designed to experimentally assess their validity.

Entropion is a condition characterized by the total or partial inversion of the eyelid margin, resulting in contact between the outer skin and the corneal or conjunctival surface, and sometimes both. This condition can affect various animals, including horses, pigs, goats, sheep, rabbits, felines, and particularly canines. It typically manifests in the lower lid's lateral portion but can affect any part of the lid. This contact between eyelashes or facial hair and the cornea or conjunctiva leads to severe irritation, causing self-inflicted trauma, as evidenced by clinical signs of pain, irritation, ulcerations, and vision loss. Entropion can be classified as primary (congenital or developmental) or secondary (spastic and scarring). Diagnosis relies on clinical signs, the animal's history, and its breed. It's essential to assess the degree of entropion in the dog without applying topical anesthesia. This study conducts a literature review on surgical techniques for correcting various types of entropion in canines.

In this work, we report the fabrication of the new heterojunction of two 2D hybrid layered semiconductors, ZnO(stearic acid)/V₂O₅(hexadecylamine), and its behavior in the degradation of aqueous methylene blue under visible light irradiation. The optimal photocatalyst efficiency, reached at a ZnO(stearic acid)/ V₂O₅(hexadecylamine) ratio of 1:0.25, results to be about six times higher than that of pristine zinc oxide. Reusability test shows that after three photocatalysis cycles no significant changes in neither the dye degradation efficiency loss nor photocatalyst structure occur. Visible light photocatalytic performance observed indicates there is synergetic effect between both 2D nanocomposites used in the heterojunction. The visible light absorption enhancement promoted by the narrower bandgap V₂O₅ based components; an increased photo generated charge separation favored by extensive interface area; and abundance of hydrophobic sites for dye adsorption appear as probable causes of the improved photocatalytic efficiency in this hybrid semiconductors heterojunction. Estimated band-edge positions for both conduction and valence band of semiconductors together with experiments using specific radical scavengers allow a plausible photodegradation mechanism.

Hydrological modeling allows us to make a comprehensive assessment of the interaction between dynamics of the hydrological cycle, climate conditions, and land use. These modeling results are relevant in water resources management field. We use TopModel (TOPography based hydrological MODEL for the hydrological modeling of an area of 17 000 km² in the Middle Magdalena Valley (MMV), a tropical basin located in Colombia. This study is located in the intertropical convergence zone (ITCZ) which is characterized by special meteorological conditions and fast water fluxes over the year. This area has been subjected to significant land use changes, as a result of intense economic activities, e.g., agriculture, hydropower energy and oil & gas production (Avellaneda, 2003). The proposed model is based on a record of 12 years of: i.) daily precipitation data from observed gauges, ii.) daily evapotranspiration data from temperature data and iii.) daily streamflow data as observed data. A calibration process was performed using data from 2000 to 2008, and a validation was performed with data from 2009 to 2012. The Nash-Sutcliffe coefficient was used as an objective function to assess the quality of these processes (values of this metric are between 0.74 and 0.73 respectively, for model calibration and validation). The results show us an adequate performance of the model in areas of the tropical region and allow us to analyze the relationship between water storage capacity in the soils of the area with subsurface runoff. This conclusion is consistent with the characteristics of the region. The calibrated model provides an idea about the hydrological functioning of the basin and estimates an approximation of the groundwater recharge in the region. The estimation of the recharge is important to quantify the interaction of surface water and groundwater, especially during the dry season, due to its importance in the analysis of scenarios with climate variability.

This study delves into the foundational aspects of electrocardiographic (ECG) lead systems, specifically focusing on Einthoven’s Triangle and Wilson’s Central Terminal. We introduce the innovative concept of a Precordial Central Terminal, a strategic arrangement of thoracic electrodes that establishes two Einthoven’s triangles within the horizontal plane, in accordance with physical-mathematical principles. Furthermore, we meticulously scrutinize Goldberger’s contributions to the field of ECG, particularly augmented leads, which shed light on the development of our theory. Additionally, we propose the implementation of a novel standardized electrocardiograph, characterized by its use of exclusively “precordial” electrodes, yet capable of providing a comprehensive three-dimensional perspective of cardiac electrical activity. By amalgamating theoretical underpinnings with empirical experimentation, our study lays the groundwork for future investigations, including the experimental validation of our innovative Precordial Terminal. This validation holds the promise of yielding substantial advancements in the realm of clinical electrocardiography.

Wildfires have always been a part of the history of Mediterranean forests. However, forest regeneration after a wildfire is not certain. It depends on many factors, some of which may be influenced by land management activities. Failure of regeneration will cause a regime shift in the ecosystem, reducing the provision of ecosystem services and ultimately leading to desertification. How can we increase Mediterranean forests’ resilience to fire? To answer this question, we did a literature review, investigating chains of processes that allow forests to regenerate (which we label “regeneration mechanisms”), and assessed the impact of selected management practices documented in the WOCAT database on the regeneration mechanisms. We identified three distinct regeneration mechanisms that enable Mediterranean forests to recover, as well as the time frame before and after a fire in which they are at work, and factors that can hinder or support resilience. The three regeneration mechanisms enabling a forest to regenerate after a fire consist of regeneration (1) from a seed bank; (2) from resprouting individuals; and (3) from unburned plants that escaped the fire. Management practices were grouped into four categories: (1) fuel breaks, (2) fuel management, (3) afforestation, and (4) mulching. We assessed how and under what conditions land management modifies the ecosystem’s resilience. The results show that land management influences resilience by interacting with resilience mechanisms before and after the fire, and not just by modifying the fire regime. Our analysis demonstrates a need for adaptive – i.e. context- and time-specific – management strategies.

Circular Economy (CE) is a growing topic among scholars, industry and government aiming at decoupling economic growth and development from the consumption of finite resources. CE incorporates different meanings, from reduce, reuse and recycle activities to environmental degradation or resource scarcity, and supported by specific indicators to attain sustainable development. However, so far, there has been no agreement to measure how effective an industry/product is in making the transition from linear to circular approaches, particularly those affected the society. This research work aims to perform a systematic literature review (n=60) to analyze and discuss how social aspects have been considered and integrated in the CE research so far. Moreover, this review provides and overview of the literature on social impact within CE, that resulted in three main outputs: a knowledge map of the CE, an analysis of social aspects within CE, and the theories/frameworks used to evaluate social impact of CE. Finally, this study brings to light how CE implementation can affect society and highlights the importance of social dimension in the domains of CE and policy-making community, which could help moving CE towards a sustainable development.

Smoked cigarette butts (SCB) can be used as precursors to obtain activated carbon (AC) due to their high carbon content related to the presence of cellulose acetate and components that are retained in the tobacco combustion process. In this way, it was analyzed how the process of pyrolysis or formation of char from this residue occurs, for this a study of the kinetics of formation of char is carried out by thermogravimetry, using three heating speeds 5, 10 and 15 °C/min. Based on the data obtained, mathematical models such as Kissenger - Akahira - Sunose (KAS), Starink (STK) and Ozawa - Flynn - Wall (OFW) were used in order to identify thermodynamic parameters through the energy of activation. The char obtained was subjected to an activation treatment with KOH in order to increase the surface area and pore volume, obtaining values of 433 m2/g of BET area and 0.25 cm3/g of micropore volume. Finally, the adsorbent was applied in the removal of Cr (VI) obtaining a Qmax capacity determined by the Langmuir model of 55.8 mg/g.

The Chagas disease (CD) is an endemic infectious disease in a large part of Latin America. This disease is characterized by the fact of being caused by the parasite Trypanosoma cruzi. Some symptoms of this disease are cardiopathies and gastrointestinal problems. Therefore, the commonly used treatment consists of nitro drugs such as benznidazole and nifurtimox, which target the nitroreductase enzyme that docks to the coenzyme flavin mononucleotide (FMN) and an oxidation-reduction reaction is generated. From this reaction, the nitro chemical function of benznidazole and nifurtimox is reduced to amine. This amine in turn interacts with the parasite´s DNA. In vitro tests experimentally help in the study of the parasite resistance to the drug benznidazole. This fact could explain how nonsynonymous mutations in the nitroreductase (NTR) enzyme do not allow the anchorage of the FMN coenzyme and as a consequence the parasite susceptibility to benznidazole decreases as the drug cannot be reduced. The structural relations from the hybrid Quantum Mechanics-Molecular Mechanics (QM/MM) allow to detect the small changes generated in the system, considering a charge distribution associated with the structure, angle changes, interaction distances, potential surface calculations between the wildtype enzyme and the mutation found.

With the current increase in the demand from animal and agricultural products, management of agrowaste has become critical to avoid greenhouse gas emissions. The present article investigates the applicability of ammonium bicarbonate synthesis via flash distillation to valorize and stabilize several types of anaerobic digestate produced from individual fermentations of amino acids. Prior to the development of the model in Aspen Plus v12, the description of the system aqua-ammonia-carbon dioxide provided by the electrolyte non-random two-liquid property method was validated with empirical data available in the literature. The content of CO₂ in the digestate was found to be responsible of the OH alkalinity (0.4 equivalents of acid/kg digestate), while the partial and total alkalinities (0.8 eq/kg digestate) were essentially derived from the content of NH₃. The most suitable conditions for the flash distillation were 95 ⁰C and 1 bar with the condensation occurring at 25 ⁰C. However, in order to attain the precipitation of NH₄HCO₃ in the distillate, it was necessary to consider digestates with a moisture content of 50 wt.%, since the minimum levels of inorganic nitrogen and inorganic carbon were not attained otherwise. Even under these conditions, few amino acids (i.e. arginine, glycine, and histidine) were able to provide an anaerobic digestate, upon fermentation, that would be suitable for NH₄HCO₃ stabilization. Despite alanine digestate and glutamine digestate presented sufficient concentrations of inorganic nitrogen and inorganic carbon, the NH₄HCO₃-stabilization was not feasible due to the limited volatilization of NH₃. The process of stabilization with a capacity of a tonne of digestate per hour was improved by adding hydrochloric acid or sodium hydroxide at rates 44 kg/h, leading to production of 34 kg NH₄HCO₃/h. The economic viability of this process needs to be investigated considering not only the market value of the isolated inorganic fertilizer but the carbon credits saved, resulting from handling a more stabilized organic manure. Furthermore, given the role of the volatile elements of the biogas as endogenous stripping agents, it is recommended to use a fresh and saturated digestate as feed for the flash distillation.

We have much to learn from historic buildings. The fact that they are still standing is obvious, but unfortunately often not appreciated. In this paper the results obtained from a series of parametric analyses, where the influence that geometric and mechanical parameters have in the structural response of existing cob walls within an Irish context, are presented. A design of experiments using central composite designs was implemented along with analysis of variance following two computational approaches, namely, finite element method and kinematic limit analysis. As results, a series of response surfaces and parametric equations with which it is possible to compute safety factors and collapse multipliers (within the range of values studied) are provided. Based on the results obtained, it could be concluded that traditional cob walls in Ireland are very robust. Relatively high acceleration values, unlikely to happen in a low seismic hazard region such as Ireland, would be needed to start the collapse mechanisms studied or cause yielding in typical vernacular cob walls. Furthermore, the equations generated with the refined regression models, can be used by practitioners as a first approach to estimate the safety levels of existing cob buildings with similar characteristics.

Participatory landscape conservation is an innovative approach that weaves theory and practice to bridge the gap between theoretical models and practical applications. Intertropical regions as the case of Mexico face challenges to conciliate regional governability, social justice, and nature conservation. The State of Michoacan is one of these regions where the challenges exacerbate since nature conservation is last due to its ongoing territorial disputes. We implemented the participatory landscape conservation approach by creating a complementary form of protected areas with ongoing conflicts, drought conditions, and extreme poverty. We conducted participatory mapping and land cover/use analyses as main methodological tools to reach consensus among stakeholders. We integrated, macro, micro and social scales to provide sound arguments to integrate local, scholar and policy makers perceptions. The outcomes of the participatory mapping analyses were assessed. The present papers provide evidence of the positive outcome of using a Participatory Landscape Conservation to establish a Biosphere Reserve, safeguarding one of the most biologically diverse and delicate ecosystems consisting of seasonally dry tropical forests within a rather disputed region. We discussed the relevance of our findings and compared them to ongoing regional and global trends in the light of other forms of establishing protected areas.

A common fault in turbomachinery is rotor--casing rub. Shaft vibration, measured with proximity probes, is the most powerful indicator of rotor-stator rub. However, in machines such as aeroderivative turbines, with increasing industrial relevance in power generation, constructive reasons prevent the use of those sensors, being only acceleration signals at selected casing locations available. This implies several shortcomings in the characterization of the machinery condition, associated with a lower information content about the machine dynamics. In this work we evaluate the performance of the Continuous Wavelet Transform to isolate the accelerometer signal features that characterize rotor-casing rub in an aeroderivative turbine. The evaluation is carried out on a novel rotor model of a rotor flexible casing system. Due to damped transients and other short-lived features that rub induces in the signals, the Continuous Wavelet Transform proves being more effective than both Fourier and Cepstrum Analysis. This creates the chance for enabling early fault diagnosis of rub before it may cause machine shutdown or damage.

Forty-five male Dorper crossbred lambs (40.17 ± 0.35 kg BW) were used in order to investigate the effects of the duration of calcium propionate (CaPr) supplementation in lambs finished with zilpaterol hydrochloride (ZH) on the productive performance, carcass characteristics, and meat quality. Lambs were individually housed and fed a finishing-diet for 42 d before being slaughtered. Lambs received the following treatments: 1) No additives (CTL), 2) ZH supplementation for 28 d (with 3 d ZH withdrawal before slaughter) at a dosage of at 7.2 mg/kg diet (ZH), for treatments 3, 4, and 5, lambs received ZH and 10g CaPr/lamb/d throughout the entire phase (42 d), or during the last 28 or 14 d before slaughter. Compared to CTL, ZH lambs exhibited a similar average daily gain (ADG) but had lower dry matter intake (DMI), leading to increased feed efficiency. Supplementing with ZH alone did not affect carcass traits, visceral mass, whole cuts, or meat quality. Lambs that received both CaPr and ZH exhibited quadratic increases (p < 0.05) in final BW (FBW), ADG, and dressing percentage (D%). These increases were optimal at an estimated inclusion durations of 26 d for FBW, 30 for ADG, and 39 d for D%. The ADG:DMI ratio and the longissimus muscle area (LMA) both exhibited quadratic increases (p < 0.05). The optimal duration of CaPr supplementation for ADG:DMI ratio was found to be 28 d, while for LMA, it was 14 d. As the period of CaPr supplementation increased, there was a linear increase (p <0.05) in hot carcass weight, leg circumference, and whole cuts of breast IMPS209 and shoulder IMPS207. Cook loss percent increased quadratically (p < 0.05), being higher when CaPr was included for an estimated duration of 26 d. As the duration of CaPr supplementation increased, the purge loss percentage (PLR) also increased linearly (p < 0.05). In conclusion, including CaPr in the diet for a duration of 28 d in lambs improved the response to ZH supplementation on the productive performance, carcass weight and some whole cuts. However, it can also have a negative effect on PRL%.

Less than half of e-waste plastics is sorted worldwide and this rate is likely to decline as major processing countries have banned importation of e-waste plastics. This forces the development of decentralized processing facilities, also known as microfactories. The present work investigates the recyclability of different grades of acrylonitrile-butadiene-styrene (ABS) copolymer, polycarbonate, and polypropylene, which were found to be very abundant in a recycling site in the UK. The determination of the matrix relied on the resin identification code imprinted in the e-waste plastic and subsequent FTIR analysis. The melt-blend extrusion technology enabled the valorization of the wasted thermoplastics as 3D filament without significant degradation of the polymers. The recycled materials maintained the tensile strength around 2.5 MPa in agreement with the specifications offered by virgin polymers. Further characterization was done by means of laser microscope, thermogravimetric analysis, and XRF to determine the commercial viability of the recycled filament. A modified solvent-based method was developed with acetone to remove the brominated flame retardants: 25g/100mL, 30 minutes of contact time, and 4 extraction steps. The FTIR results show that the degradation of the rubbery dispersed phase corresponding to the butadiene can be accumulated in the less soluble fraction of the waste ABS.

Cloud platforms are widely employed in today's educational context to enhance collaborative learning and the overall quality of the teaching-learning process. In 2016, Nextcloud was im-plemented in the Faculty of Chemical Engineering at the Technological University of Havana "José Antonio Echeverría" (CUJAE), Cuba. Subsequently, an evaluative phase was conducted to ensure the continuous development of the platform. The objective was to assess the use and ac-ceptance of the Nextcloud platform from the perspective of students and professors in the Fac-ulty. An exploratory, non-experimental, and cross-sectional study was conducted. Data was col-lected through observation and a survey. Matomo Analytics tool was employed for observation, revealing low visitation numbers. The survey was based on the Unified Theory of Acceptance and Use of Technology model. Better results were obtained in positive acceptances compared to negative ones, both for professors and students. It is concluded that the evaluation of the Next-cloud platform is infrequently used by users; however, there were higher positive acceptances than negatives from the perspectives of both students and professors.

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. Over history, NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. On the other hand, computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element for the CADD. This work reviews the progress toward developing compound databases of natural origin, particularly databases developed in Latin America, and their practical applications in the drug discovery area. We also survey the computational methods, emphasizing chemoinformatic approaches to profile natural product databases.

The strong couplings among ecological, economic, social and technological processes explains the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemics. Among complexification’s essential features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This in turn means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy and information, and a given time horizon, aiming at enhancing the co-evolutionary power of the Biosphere and its human subsystems. Giving the high-stakes, the need for effective, efficient, diverse solutions, their local-global, present-future effects, and their unforeseen short, medium and long-term impacts, achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents, harnessing the strong functional coupling between human, artificial and nonhuman biological intelligence in a no-zero-sum game to achieve sustainability.

The wave energy converter (WEC) technology constantly develops new designs and models. To encourage its development within the energy sector, research is required to improve current designs and create durable and effective devices. However, it is also crucial to investigate the suitability of a WEC to a site-specific sea condition as this can impact its optimal power absorption and constructability. This study evaluates and compares the efficiency of a heaving buoy with varied geometries in one of the most energetic places along the Mexican coast. A statistical analysis of the wave climate on the coast of Ensenada during the last 42 years is performed to define the conditions to which the device is subjected. The location of the WEC in shallow waters is chosen using a computational model which solves the modified mild slope equation in its elliptic shape. The heaving buoy floater is studied using three distinct geometries: a semi-sphere, a cylinder, and a proposed rounded semi-rectangle. The hydrodynamic response of the three geometries is then analysed in the frequency and time domain using ANSYS AQWA. The hydrodynamic study involves the assessment of the floating body dynamics, exerted forces, the power absorbed as well as the suitability of the proposed power take-off (PTO) system. Findings reveal that the proposed geometry absorbs the most energy, with an annual power of 135.11 MW, and that the transmission PTO design is appropriate for this type of technology.

One mechanism by which fructose could exert deleterious effect in metabolism and inflammation is via its potency vis-à-vis de Maillard reaction. We employed simulated stomach and duodenum digestion of ovalbumin to test the hypothesis that indeed AGEs are formed by fructose during simulated digestion of an ubiquitous food protein with intrinsic allergenic potential and under model physiological conditions. Methods: OVA was subjected to simulated gastric and intestinal digestion using standard models, in presence of fructose or glucose (0-100 mM). Peptide fractions were analyzed by fluorescence spectroscopy and intensity at Excitation: λ370 nm, Emission: λ 440nm. Results: AGE adducts form between fructose and OVA which can be found in peptide fractions (< 5 kDa) at times (30 min) and concentration ranges (10 mM) plausibly found in the intestines, whereas no reaction occurs with glucose. The reaction is inhibited by chlorogenic acid at concentrations compatible with those found in the gut. The reaction is inhibited by AG, a specific antiglycation agent. Conclusion: Our proof of principle study shows that fructose-AGE formation on an ubiquitous allergenic protein indeed occurs in one hour and thereby may pave the way for the study of yet another mechanism by which the excess fructose in our Western diets is contributing to disease: intestinal AGE formation, absorption and RAGE engagement.

Rural women constitute one of the most marginalized and vulnerable groups in the world. Despite playing a critical role in sustainable development and food security, they face systemic inequalities and structural constraints that limit their access to resources, services and opportunities. The purpose of this research is to identify advances and setbacks in the formulation of 17 SDG indicators for rural women. Systematic Review Registered in PROSPERO: CRD42023420583. Sixteen articles were included. Three indicators were identified: entrepreneurship, empowerment and gender equality. Due to its relevance in rural areas where women have an active role in family income through cooperatives, associations and companies to improve quality of life and that of their community, however, aspects of discrimination are still evident in gender and inequality in participation in economic spheres and decision making.

Grafting polyethylene glycol (PEG) on polymers surface is widely used to improve biocompatibility by reducing protein and cell adhesion. Although PEG is considered to be bioinert, its incorporation to biomaterials has shown to improve cell viability depending on the amount and molecular weight (MW) used. This phenomenon was studied here by grafting PEG of three MW onto polyurethane (PU) substrata at three molar concentrations to assess their effect on PU surface properties and on the viability of osteoblasts and fibroblasts. PEG formed a covering on the substrata which increased the hydrophilicity and surface energy of PUs. Among the results it was observed that osteoblast viability increased for all MW and grafting densities of PEG employed compared with unmodified PU. However, fibroblast viability only increased at certain combinations of MW and grafting densities of PEG, suggesting an optimal level of these parameters. PEG grafting also promoted a more spread cell morphology than that exhibited by unmodified PU; nevertheless, cells became apoptotic-like as PEG MW and grafting density were increased. These effects on cells could be due to PEG affecting culture medium pH, which became more alkaline at higher MW and concentrations of PEG. Results support the hypothesis that surface energy of PU substrates can be tuned by controlling the MW and grafting density of PEG, but these parameters should be optimized to promote cell viability without inducing apoptotic-like behavior.

Hyperspectral images are an important tool to assess ecosystem biodiversity both on terrestrial and benthic habitats. To obtain more precise analysis of biodiversity indicators that agree with indicators obtained using field data, analysis of spectral diversity calculated from images have to be validated with field based diversity estimates. The plant species richness is one of the most important indicators of biodiversity. This indicator can be measured in hyperspectral images considering the Spectral Variation Hypothesis (SVH) which states that the spectral heterogeneity is related to spatial heterogeneity and thus to species richness. The goal of this research is to capture spectral heterogeneity from hyperspectral images for a terrestrial neo tropical forest site using Vector Quantization (VQ) method and then use the result for prediction of plant species richness. The results are compared with that of Hierarchical Agglomerative Clustering (HAC). The validation of the process index is done calculating the Pearson correlation coefficient between the Shannon entropy from actual field data and the Shannon entropy computed in the images. Terrestrial dry forest and marine coastal hyperspectral images with different resolutions have been used for spectral diversity feature validation.

The importance of diet and the gut-brain axis for brain health and cognitive function is increasingly acknowledged. Dietary interventions are tested for their potential to prevent and/or treat brain disorders. Intermittent fasting (IF), the abstinence or strong limitation of calories for 12 to 48 hours, alternated with periods of regular food intake, has shown promising results on neurobiological health in animal models. In this review article, we discuss the potential benefits of IF on cognitive function and the possible effects on the prevention and progress of brain-related disorders in animals and humans. We do so by summarizing the effects of IF which - through metabolic, cellular and circadian mechanisms - lead to anatomical and functional changes in the brain. Our review shows that there is no clear evidence of a positive short-term effect of IF on cognition in healthy subjects. Clinical studies show benefits of IF for epilepsy, Alzheimer’s disease and multiple sclerosis on disease symptoms and progress. Findings from animal studies show mechanisms by which Parkinson’s disease, ischaemic stroke, autism spectrum disorder and mood- and anxiety disorders could benefit from IF. Future research should disentangle whether positive effects of IF hold true regardless of age or the presence of obesity. Also, variations in fasting patterns, total caloric intake and intake of specific nutrients may be relevant components of IF success. Longitudinal studies and Randomized Clinical Trials (RCTs) will provide a window into the long-term effects of IF on the development and progress of brain-related diseases.

In this work, we investigated for the first time the complexation of sepiapterin (SP), the natural precursor of the natural essential cofactor tetrahydrobiopterin, that displays mild water-solubility and short biological half-life, with the hydrophobic triacetyl-β-cyclodextrin (TAβCD) to improve its encapsulation within methoxy-poly(ethylene-glycol)-poly(epsilon-caprolactone) (mPEG-PCL) nanoparticles. First, TAβCD-SP complexes were produced by spray-drying of TAβCD/SP binary solutions by utilizing the Nano Spray Dryer B-90 HP. Then, dry powders were characterized by differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR) and transmission and scanning electron microscopy (SEM and TEM, respectively) and compared to the complex components and physical mixtures (PMs). Next, SP was encapsulated within methoxy-poly(ethylene-glycol)-poly(epsilon-caprolactone) (mPEG-PCL) nanoparticles by nanoprecipitation of a SP/TAβCD complex/mPEG-PCL solution. In addition to complex nanoencapsulation, we assessed encapsulation of pure SP by nanoprecipitation with an intermediate step, which comprised the co-drying of SP, TAβCD and mPEG-PCL copolymer solution in organic solvent; this step aimed to promote the formation of molecular interactions between SP, TAβCD and the PCL blocks in the copolymer. SP-loaded mPEG-PCL nanoparticles were characterized by dynamic light scattering (DLS) and SEM. Nanoparticles with size of 74-75 nm and small polydispersity index (PDI <0.1) were obtained when SP-TAβCD equimolar spray-dried complex was used for nanoencapsulation, and SEM analysis indicated the absence of free SP crystals. Moreover, the encapsulation efficiency (%EE) and drug loading (DL) were 85% and 2.6%, respectively, as opposed to those achieved with pure SP encapsulation (14% and 0.6%, respectively). Overall, our results confirm that spray-drying of SP/TAβCD solutions at the appropriate molar ratio leads to the hydrophobization of the relatively hydrophilic SP molecule, enabling its encapsulation within mPEG-PCL nanoparticles.

Floods are one of the most wide-spread, frequent, and devastating natural disasters that continue to increase in frequency and intensity. Remote sensing, specifically synthetic aperture radar (SAR), has been widely used to detect surface water inundation to provide retrospective and near-real time (NRT) information due to its high-spatial resolution, self-illumination, and low atmospheric attenuation. However, the efficacy of flood inundation mapping with SAR is susceptible to reflections and scattering from a variety of factors including dense vegetation and urban areas. In this study, the topographic dataset height above nearest drainage (HAND) was investigated as a potential supplement to Sentinel-1A C-Band SAR along with supervised machine learning to improve the detection of inundation in heterogeneous areas. Three machine learning classifiers were trained on two sets of features SAR only (VV & VH) and VV, VH & HAND to map inundated areas. Three study sites along the Neuse River in North Carolina, USA during the record flood of Hurricane Matthew in October 2016 were selected. The binary classification analysis (inundated as positive vs. non-inundated as negative) revealed significant improvements when incorporating HAND in several metrics including classification accuracy (ACC) (+37.1%), true positive rate (TPR) (+51.2%), and negative predictive value (NPV) (+23.7%), A marginal improvement of +1.4% was seen for positive predictive value (PPV), but true negative rate (TNR) fell -15.1%. By incorporating HAND, a significant number of areas with high SAR backscatter but low HAND values were detected as inundated which increased true positives. This in turn also increased the false positives detected but to a lesser extent as evident in the metrics. This study demonstrates that HAND could be considered a valuable feature to enhance SAR flood inundation mapping especially in areas with heterogeneous land covers with dense vegetation that interfere with SAR.

Inside hippocampal circuits, neuroplasticity events that individual cells may undergo during synaptic transmissions occur in the form of Long Term Potentiation (LTP) and Long Term Depression (LTD). The high density of NMDA receptors expressed on the surface of the dendritic CA1 spines confers to hippocampal CA3-CA1 synapses, the ability to easily undergo NMDA-mediated LTP and LTD, that is essential for some forms of explicit learning in mammals. Providing a comprehensive kinetic model that can be used for running computer simulations of the synaptic transmission process is currently a major challenge. Here, we propose a compartmentalized kinetic model for CA3-CA1 synaptic transmission. Our major goal was to tune our model in order to predict the functional impact caused by disease associated variants of NMDA receptors related to severe cognitive impairment. Indeed, for variants Glu413Gly and Cys461Phe, our model predicts negative shifts in the glutamate affinity and changes in the kinetic behavior, consistent with experimental data. These results pinpoint to the predictive power of this multiscale viewpoint, which aims to integrate the quantitative kinetic description of large interaction networks typical of system biology approaches with a focus on the quality of few, key, molecular interactions typical of structural biology ones.

In addition to their importance in statistical thermodynamics, probabilistic entropy measurements are crucial for understanding and analyzing complex systems, with diverse applications in time series and one-dimensional profiles. However, extending these methods to two- and three-dimensional data still requires further development. In this study, we present a new method to classify spatiotemporal processes based on entropy measurements. To test and validate the method, we selected four classes of similar processes related to the evolution of random patterns: dynamic colored noises ((i)~white and (ii)~red); (iii)~weak turbulence from reaction-diffusion; (iv)~hydrodynamic fully developed turbulence, and (v)~plasma turbulence from MHD. Considering seven possible ways to measure entropy from a matrix, we present the method as a parameter space composed of the two best separating measures of the five selected classes. The results highlight better combined performance of Shannon Permutation Entropy ($S^p_H$) and a new approach based on Tsallis Spectral Permutation Entropy ($S^s_q$). Notably, our observations reveal the segregation of reaction terms in this $S^p_H \times S^s_q$ space, a result that identifies specific sectors for each class of dynamic process, and can be used to train machine learning models for automatic classification of complex spatiotemporal patterns.

With confirmed COVID-19 cases surpassing the 8.5 million mark around the globe, there is an imperative need to deepen the efforts from the international scientific community to gain comprehensive understanding of SARS-CoV-2. Although the main clinical manifestations are associated with respiratory or intestinal symptoms, reports of specific and non-specific neurological signs and symptoms, both at presentation or during the course of the acute phase, are increasing. Approximately 25-40% of the patients present neurological symptoms. The etiology of these neurological manifestations remains obscure, and probably involves several direct pathways, not excluding the direct entry of the virus to the Central Nervous System (CNS) through the olfactory epithelium, circumventricular organs, or disrupted blood-brain barrier (BBB). Furthermore, neuroinflammation might occur in response to the strong systemic cytokine storm described for COVID-19, or due to dysregulation of the CNS angiotensin system. Descriptions of neurological manifestations in patients in the previous coronavirus (CoV) outbreaks have been numerous for the SARS-CoV and lesser for MERS-CoV. Strong evidence from patients and experimental models suggests that some human variants of CoV have the ability to reach the CNS and that neurons, astrocytes and/or microglia can be target cells for CoV. A growing body of evidence shows that astrocytes and microglia have a major role in neuroinflammation, responding to local CNS inflammation and/or to dysbalanced peripheral inflammation. This is another potential mechanism for SARS-CoV-2 damage to the CNS. In this work we will summarize the known neurological manifestations of SARS-CoV-2, SARS-CoV and MERS-CoV, explore the potential role for astrocytes and microglia in the infection and neuroinflammation, and compare them with the previously described human and animal CoV that showed neurotropism. We also propose possible underlying mechanisms by focusing on our knowledge of glia, neurons, and their dynamic intricate communication with the immune system.

This paper investigates calendar anomalies, volatility patterns, and the best forecasting model for predicting volatility in the cryptocurrency market, focusing on ten prominent cryptocurrencies: Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Spanning from January 2016 to December 2023, the study utilizes sophisticated statistical models such as GARCH (p,q), EGARCH (p,q), and GJR-GARCH (p,q) to analyze precise changes in market dynamics and the impact of day-of-week fluctuations on cryptocurrency returns. Empirical evidence reveals significant findings regarding the persistence of volatility, positive and negative news effects on volatility, and day-of-week effects on cryptocurrency returns. Post-COVID-19, Sunday emerges as the least volatile day for cryptocurrencies, while Thursdays and Tuesdays exhibit greater volatility. Binance, Ethereum, Dogecoin, and Tether show anomalies where returns on Tuesday and Thursday significantly differed from those on other days of the week. Many other currencies, like the USD coin, Cardano, and Ripple, show anomalies only in the pre-COVID-19 period. The findings highlight the best forecast model for volatility for each top cryptocurrency, offering practical implications for investors, traders, regulators, and policymakers. These insights emphasize the importance of understanding and addressing calendar anomalies in the cryptocurrency market for informed decision-making, trading strategies, regulatory frameworks, and market stability.

This review article explores the transformative impact of Artificial Intelligence (AI) on glaucoma care, focusing on advancements in diagnosis, monitoring, and treatment algorithms. AI technologies have revolutionized the field of ophthalmology by enhancing the accuracy and efficiency of diagnosing glaucoma. Furthermore, AI-powered monitoring systems enable continuous and personalized patient care, facilitating early detection of disease progression. Integrating AI algorithms in treatment protocols promises individualized and optimized therapeutic strategies for better management of glaucoma. This comprehensive review elucidates AI applications' current state and future directions in transforming glaucoma care, emphasizing the potential benefits of improving patient outcomes.

This paper presents a new methodology to evaluate the performance of an electric vehicle hybrid power system consisting of a fuel cell and a supercapacitor. The study compares the results with those obtained for a battery-electric vehicle. The methodology extends to three driving modes, ECO, NORMAL, and SPORT, corresponding to conservative, moderate, and aggressive acceleration, and three driving conditions, low, medium, and high energy demand. We develop a simulation process to evaluate the energy consumption and the energy rate of a specific electric vehicle used as a prototype for the study. The methodology applies to a driving route that includes acceleration, deceleration, braking, and constant speed segments reproducing standard driving conditions in urban journeys. The proposed method considers combined driving modes, ECO, NORMAL, and SPORT, in each acceleration process, with variable fractions, 0% to 100%, for each mode. This methodology optimizes the simulation results as it fits the current driving way in urban environments. The simulation results show an average reduction in energy consumption of 37% and 27.1% in vehicle weight, contributing to lower energy use. The study concludes that using a hybrid power system, fuel cell/supercapacitor, instead of a battery in electric vehicles is beneficial, especially in journeys with frequent acceleration processes.

It is well known that the Continuous Galerkin Finite Element (CGFE) method is globally consistent with respect to the first law of thermodynamics. This means that, for any mesh, all obtained discrete solutions will conserve total energy. One might expect, that the method is, also, globally consistent with respect to the second law of thermodynamics. In this paper, we formally study if such conjecture is true. The heat conduction equation is used as the physical model for this analysis. In the present study it is proved that the conjecture is false: at least, for standard piecewise linear (1D and 2D) elements, the CGFE method is not always globally consistent with respect to the second law of thermodynamics. In other words, some obtained discrete solutions can violate the global postulate of the second law, which asserts that total entropy can never decrease.

Polyolefin fibre reinforced concrete (PFRC) has become an attractive alternative to steel for the reinforcement of concrete elements mainly due to its chemical stability and the residual strengths that can be reached with lower weights. The use of polyolefin fibres can meet the requirements in the standards, although the main constitutive relations are based on the experience with steel fibres. Therefore, the structural contributions of the fibres should be assessed by inverse analysis. In this study, the fibre dosage has been fixed at 6kg/m³ and both self-compacting concrete and conventional concrete have been used to compare the influence of the positioning of the fibres. An idealized homogeneous distribution of the fibres with such fibres crossing from side to side of the specimen has been added to self-compacting concrete. The experimental results of three-point bending tests on notched specimens have been reproduced by using the cohesive crack approach. Hence, the constitutive relations were found. The significance of this research relies on the verification of the formulations found to build the constitutive relations. Moreover, with these results it is possible to establish the higher threshold of the performance of PFRC and the difficulties of limiting the first unloading branch typical of fracture tests of PFRC.

Intranasal (i.n.) administration became an alternative strategy to bypass the blood-brain barrier and improve drug bioavailability in the brain. The main goal of this work was to preliminarily study the biodistribution of mixed amphiphilic mucoadhesive nanoparticles made of chitosan-g-poly(methyl methacrylate) and poly(vinyl alcohol)-g-poly(methyl methacrylate) and ionotropically crosslinked with sodium tripolyphosphate in the brain after intravenous (i.v.) and i.n. administration to Hsd:ICR mice. After i.v. administration, the highest nanoparticle accumulation was detected in the liver, among other peripheral organs. After i.n. administration of a 10-times smaller nanoparticle dose, the accumulation of the nanoparticles in off-target organs was much lower than after i.v. injection. In particular, the accumulation of the nanoparticles in the liver was 20 times lower than by i.v. When brains were analyzed separately, intravenously administered nanoparticles accumulated mainly in the “top” brain, reaching a maximum after 1h. Conversely, in i.n. administration, nanoparticles were detected in the “bottom” brain and the head (maximum reached after 2 h) owing to their retention in the nasal mucosa and could serve as a reservoir from which the drug is released and transported to the brain over time. Overall results indicate that i.n. nanoparticles reach similar brain bioavailability, though with a 10-fold smaller dose, and accumulate in off-target organs to a more limited extent and only after redistribution through the systemic circulation. At the same time, both administration routes seem to lead to differential accumulation in brain regions and thus, they could be beneficial in the treatment of different medical conditions.

We analyze the transformation of a very broad class of metrics that can be put in terms of static coordinates. Starting from a general ansatz, we obtain a relation for the parameters in which one can impose further symmetries, or restrictions. One of the simplest restrictions leads to FLRW cases, while transforming from the initial static to other static-type coordinates can lead to near horizon coordinates, Wheeler-Regge, isotropic coordinates, among others. As less restrictive cases, we show an indirect route for obtaining Kruskal-Szekeres within this approach, as well as Lema\^{\i}tre coordinates. We use Schwarzschild spacetime as prototype for testing the procedure in individual cases. However, application to other spacetimes, such as de-Sitter, Reissner-Nordstr\"{o}m or Schwarzschild de Sitter, can be readily generalized.

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

Greenhouses are instrumental in the advancement of regions globally. The geometric arrangement of these structures plays a pivotal role in governing sunlight distribution, facilitating ventilation, and managing condensation. The roof's shape significantly affects energy efficiency and the accumulation of condensation water, which, when dripping onto crops, can induce diseases and diminish production. This study introduces a Matlab program designed for defining and analyzing greenhouse roof geometry, adaptable to both single-span and multi-span structures. Various roof shapes are examined, determining angles along their length to facilitate condensation droplet runoff. Furthermore, the greenhouse's energy efficiency is evaluated by analyzing diverse roof models, accounting for surface area and internal air volume. The results aim to aid in selecting the optimal greenhouse type based on climate and latitude. This study offers a valuable decision-making tool for the planning and design of agricultural structures, providing insights to enhance overall sustainability and performance in diverse environmental contexts.

Ocular drug delivery is one of the most challenging administration routes due to the very low drug bioavailability. In this work, we produce and characterize mucoadhesive mixed polymeric micelles (PMs) made of chitosan and poly(vinyl alcohol) backbones graft-hydrophobized with short poly(methyl methacrylate) blocks and use them to encapsulate cannabidiol (CBD), an anti-inflammatory cannabinoid. CBD-loaded mixed PMs are physically stabilized by ionotropic crosslinking of the CS domains with sodium tripolyphoshate and spray-drying. These mixed PMs display CBD loading capacity of 20% w/w and sizes of 100-200 nm, and spherical morphology (cryogenic-transmission electron microscopy). The good compatibility of the unloaded and CBD-loaded PMs is assessed in a human corneal epithelial cell line. Then, we confirm the permeability of CBD-free PMs and nanoencapsulated CBD in cornea cell monolayers under liquid-liquid and air-liquid conditions. Overall, our results highlight the potential of these polymeric nanocarriers for ocular drug delivery.

In December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the province of Wuhan, China. Since then, it has spread worldwide with new mutations being reported. We performed genomic analysis to identify the changes in genetic diversity of SARS-CoV-2 between December 2019 and November 2020, and through molecular surveillance, we monitored the mutations that could be involved in viral fitness. We analyzed 2,213 complete genomes from 6 geographical regions worldwide, which were downloaded from GenBank and GISAID databases. Although SARS-CoV-2 presented low genetic diversity, there has been an increase over time, with the presence of several hotspot mutations throughout its genome. We identified 7 frequent mutations that resulted in non-synonymous substitutions (dN). Two of them, C14408T>P323L and A23403G>D614G, located in the nsp12 and Spike protein, respectively, emerged early in the pandemic and showed a considerable increase in frequency over time. Two other mutations, A1163T>I120F in nsp2 and G22992A>S477N in the Spike protein emerged recently and have spread in Oceania and Europe. Continuous molecular surveillance of SARS-CoV-2 will be necessary to detect and describe the transmission dynamics of new variants of the virus with clinical relevance. This information is important to improve programs to control the virus.

There is a need to develop tools for mastitis management in goats and to measure the effects of milking machines on teats. Infrared thermography (IRT), as shown in cows, was a good candidate for early detection of mastitis and focusing on milking equipment and settings implicated in potential problems. The aim of this study was to test IRT to detect udder inflammation and the effects of mechanical milking on teats in relation to inflammation status, udder balance and teat shape in Alpine goats. IRT spectra were compared before and after milking in 551 goats from three commercial herds compared to their individual SCC (somatic cell count). We found no regression or trend between logSCC and IRT measurement or response to milking, even in highly inflamed goat udders. The effect of milking was significant (P

The use of Learning Management Systems (LMS) has had a rapid growth over the last decades. Great efforts have been recently made to assess the level of performance of the students online due to the COVID-19 pandemic. Faculty members with limited experience in the use of LMS such as Moodle, Edmodo, MOOC, Blackboard and Google Classroom can have some problems creat-ing online tests. In this work, a new plugin for Moodle is presented: FastTest PlugIn. This plugin is based on a Microsoft® Excel spreadsheet and it can be used to export questions to Moodle. Us-ers of FastTest PlugIn can create question pools in an easy and intuitive way. A literature review about plugins used to import/export questions in Moodle is carried out. Then, the characteristics of FastTest PlugIn are presented. At the end, the characteristics of the main plugins found in the literature are discussed and compared with the ones of FastTest PlugIn.

RNAi technology is a versatile, effective, safe, and eco-friendly alternative for crop protection. There is plenty of evidence of its use through host-induced gene silencing (HIGS) and spray-induced gene silencing (SIGS) techniques to control viruses, bacteria, fungi, insects, and nematodes. For SIGS, its most significant challenge is achieving stability and avoiding premature degradation of RNAi in the environment or during its absorption by the target organism. One alternative is encapsulation in liposomes, virus-like particles, polyplex nanoparticles, and bioclay, which can be obtained through the recombinant production of RNAi in vectors, transgenesis, and micro/nanoencapsulation. The materials must be safe, biodegradable, and stable in multiple chemical environments, favoring the controlled release of RNAi. Most of the current research on encapsulated RNAi focuses primarily on oral delivery to control insects by silencing essential genes. The regulation of RNAi technology focuses on risk assessment using different approaches; however, this technology has positive economic, environmental, and human health implications for its use in agriculture. The emergence of alternatives combining RNAi gene silencing with the induction of resistance in crops by elicitation and metabolic control is expected, as well as multiple silencing and biotechnological optimization of its large-scale production.

A new approach to the measurement with elastic lidar of depolarization produced by atmospheric aerosols is presented. The system uses two different telescopes: one for depolarization measurements and another for total-power measurements. The system architecture and principle of operation are described. The first experimental results are also presented, corresponding to a collection of atmospheric conditions over the city of Barcelona.

this article presents the results of implementing existing software tools in the accounting field. The teaching processes regarding the use of Learning and Knowledge Technologies (TAC) in the university environment, and very specifically, in what has to do with the pedagogical integration of the same in the curriculum is deficient and disjointed with the current technological development. Thus, in the different curricula of professional programs of Public Accounting and related, the courses related to computer automation processes are oriented only towards the management of computer science and accounting software and the great diversity of existing applications that would undoubtedly directly benefit the student to know the potential of these in their future accounting practice is not taken into account. Strengthen the various skills of a Public Accountant in training through Learning and Knowledge Technologies (TAC), under the hypothesis of developing skills in the accounting field through TACs. The research was developed using a quantitative approach, an empirical-analytical method, with a type of descriptive research under an experimental design based on G1 x O1 and G2–O2, three phases were defined. In the first phase, the characterization of the existing software tools in the accounting field was carried out. In the second phase, their relevance was determined. In the third phase, performance was evaluated and then classified in a repository. The data obtained were analyzed with parametric analysis techniques through which it was found that the difference in quantitative results in the academic process between the experimental and control groups was statistically significant, which concluded the success of the experimental treatment. The use of CT scans in the classroom by the experimental group resulted in an improvement in their academic performance compared to the control group, strengthening their self-learning processes and facilitating the development of cognitive functions and skills necessary in the exercise of their accounting profession. This research supports and strengthens the work skills developed in the classroom for public accounting students. The tools TAC is developed from the request made by the radiometry laboratory as a first phase and a second phase is necessary for validation with experts.

The energy sector plays an important role in Mexico’s development trajectory. Mexico makes an interesting case study, because it shows how difficult it is to reduce fossil energy dependence despite geographic and climatic conditions that favour renewable energy deployment and use. Resolving path dependencies and the related carbon lock-in are key to Mexico’s sustainable energy transition. This case study aims to identify and discuss how carbon lock-in affects Mexico’s sustainable energy transition. Mexico’s carbon lock-in involves oil and oil-run power plants that are costly to build but relatively inexpensive to operate. This case study identifies potential entry points for transitioning towards sustainable energy in Mexico – resources that can promote the use of clean energy despite carbon lock-in. For example, focusing on electrification – particularly of the carbon-intensive sectors – can help Mexico transit towards sustainable energy despite institutional constraints. Complementing this case study is a teaching guide with recommendations for using Mexico’s energy transition in courses on sustainability. It introduces a “learning activation framework” to identify emerging opportunities that can advance sustainable energy transitions in different cases of carbon lock-in. Finally, the framework also gives students a chance to help dismantle or cope with carbon lock-ins.

Antioxidants are molecules that neutralize free radicals. In general, the reaction mechanisms of antioxidants are well known. The main reaction mechanisms of antioxidants are electron transfer (ET), proton transfer (PT), H atom transfer (HAT) and radical adduction (RAF). The study of these mechanisms is helpful to understand how antioxidants control high free radical levels on the cell. There are many studies focused on determine the main mechanism of an antioxidant to neutralize a wide spectrum of radicals, mainly reactive oxygen species (ROS) type radicals. Most of these antioxidants are polyphenols type compounds. Some esters, amides and metal-antioxidants have shown antioxidant activity. There are few experimental and theoretical studies about the antioxidant reaction mechanism of the aforementioned compounds. In this work, we shown the reaction mechanism proposed of an amide and its metal-antioxidant counterpart. We show how the presence of the metal increase the electron transfer on polar media and the H transfer in non-polar media. Even though, esters and amides are non-polar compound, the scavenger activity is good for the metal-antioxidant compound in no-polar media

Agroecology, defined as the ecological science of food production is also as practical approach to design food production systems based on local concerted solutions that aim to promote synergy among the diversity of human and non human food systems elements. These two facets makes agroecology a good candidate for participatory research. Information technology should help using this information for the production of structured scientific knowledge. In this respect, there is a need for information technology that is adaptive to encompass the diversity of within and between systems and that provide benefit to farmers that feed it with data. We present MiCampoApp, a webapp that aims to join participatory research and certification in agroecology, with two roles, the farmer and the administrator. The idea to join participatory research for decision support with certification for market differentiation in single system is that much of the certification data harbors information for scientific research, and this incentivize data collection for the interest of the farmer and the community. The administrator create a model for data collection in order to solve a research question of interest for a communities or to produce traceability information to feed participatory guarantee system in a community. The farmer collects information using simple icons and produces traceability pages for research or certification purposes.

Severe COVID-19 is associated with viraemia and multiple organ disease. Similar clinicopathological features have been previously seen in SARS and MERS. Clinically, the severity of SARS, MERS and COVID-19 has been associated with the presence of SARS-CoV, MERS-CoV or SARS-CoV2 viraemia in affected patients. In vitro work has looked at the pattern of viral entry and release from polarised epithelial cells infected by coronaviruses. This work has demonstrated a correlation between the severity of a coronavirus infection and the ability of the virus to reach and infect the basal surface of host cells. It has been postulated that this ability helps the virus invade the bloodstream of the host, resulting in a systemic infection with multiple organ involvement. Here we propose that basal surface release and entry of COVID-19 into and out of cells at epithelial-endothelial interface plays a key pathogenic role in severe COVID-19 disease.

Severe Covid-19 disease is associated with endothelial infection, viraemia, and multi-organ dysfunction. The process through which SARS-CoV2 causes severe disease is yet to be determined. Here, we propose that in severe Covid-19 infection, SARS-CoV2 reaches the host bloodstream by infecting endothelial cells through their basal surface. This occurs, independently of ACE2, through CD147, a putative SARS-CoV2 receptor. The pathway proposed here encourages research on the mechanisms mediating endothelial cell infection in Covid-19.

Plant male sterility refers to the failure in the production of fertile pollen. It occurs spontaneously in natural populations and may be caused by genes encoded in the nuclear (genic male sterility; GMS) or mitochondrial (cytoplasmic male sterility; CMS) genomes. This feature has great agronomic value for the production of hybrid seeds and has been widely used in crops, such as corn, rice, wheat, citrus, and several species of the family Solanaceae. Mitochondrial genes determining CMS have been uncovered in a wide range of plant species. The modes of action of CMS have been classified in terms of the effect they produce in the cell, which ultimately leads to a failure in the production of pollen. Male fertility can be restored by nuclear-encoded genes, termed restorer-of-fertility (Rf) factors. CMS from wild plants has been transferred to species of agronomic interest through somatic hybridization. Somatic hybrids have also been produced to generate CMS de novo upon recombination of the mitochondrial genomes of two parental plants or by separating the CMS cytoplasm from the nuclear Rf alleles

Considering the concerns for emissions reduction in the maritime sector, the present paper evaluates, through modeling and simulation, the oxy-fuel combustion in a two-stroke ship engine (2SE) and the best production system configuration to obtain the required oxygen (O2). An initial model of a ship engine is calibrated with the engine manufacturer’s data, and then adapted to work with O2 as the oxidant to eliminate nitrogen oxides (NOx) emissions and with exhaust gas recirculation (EGR) to control the in-cylinder combustion temperature. Mixed Ionic-Electronic Conducting (MIEC) membranes produce the necessary O2 from the ambient air, which is heated up and pressurized by a heat exchanger and turbocharging coupled system to provide the air conditions required for the proper operation of the MIEC. Several layouts of this system are evaluated for the full load engine operating point to find the optimum O2 production system configuration. Results reveal that the engine operating under oxy-fuel combustion conditions avoids NOx emissions at the expense of higher brake specific fuel consumption (BSFC) to obtain the original brake torque, and also expels a stream composed exclusively of CO2 and H2O, what facilitates the separation of CO2 from exhaust gases.

Osteosarcoma is the most common subtype of primary bone cancers, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its molecular etiology has still not been determined with precision. Therefore, we applied a consensus strategy with the use of several bioinformatics tools to prioritize genes involved in its pathogenesis. Subsequently, we assessed the physical interactions of the previously selected genes and applied a communality analysis to this protein-protein interaction network. The consensus strategy prioritized a total list of 553 genes. Our enrichment analysis validates several studies that describe the signaling pathways PI3K/AKT and MAPK/ERK as pathogenic. The gene ontology described TP53 as a principal signal transducer that chiefly mediates processes associated with cell cycle and DNA damage response It is interesting to note that the communality analysis clusters several members involved in metastasis events such as MMP2 and MMP9 and genes associated with DNA repair complexes, like ATM, ATR, CHEK1, and RAD51. In this study, we could identify well-known pathogenic genes for osteosarcoma and prioritized genes that need to be further explored.

This article presents a review of resources for batteries with a specific focus on sustainability aspects related to raw materials, electrode and electrolyte chemistries suitable for the automobile industry. We emphasize the importance of prioritizing sustainability in battery technology evolution, which is expected to shift towards earth-abundant materials. One notable advancement in this direction is the utilization of glass solid-state electrolytes, known for their high ionic conductivity, low electronic conductivity, and high dielectric constant. However, our review suggests that further research should explore synthesis methods to modify anisotropic properties, enhancing the performance of solid-state electrolytes, particularly in facilitating the flow of ions.

Electromyographic (EMG) signals provide information about a person's muscle activity. For hand movements, in particular, the execution of each gesture involves the activation of different combinations of the forearm muscles, which generate distinct electrical patterns. Conversely, the analysis of these muscle activation patterns, represented by EMG signals, allows recognizing which gesture is being performed. In this study, we aimed to implement an automatic identification system of hand or wrist gestures based on supervised Machine Learning (ML) techniques. We trained different computational models and determined which of these showed the best capacity to identify six hand or wrist gestures and generalize between different subjects. We used an open access database containing recordings of EMG signals from 36 subjects. Among the results obtained, we highlight the performance of the Random Forest model, with an accuracy of 95.39%, and the performance of a convolutional neural network with an accuracy of 94.77%.

Colombia has one of the largest numbers of internally displaced populations in the world and recently entered a period of post-conflict. These socio-political processes and trends have increased the migration of people towards cities and accordingly are affecting the distribution and occurrence of tropical diseases in its urban and peri-urban areas. Studies have suggested that many human phenomena such as urbanization scale according to the size of human populations regardless of cultural context. But other studies show that health epidemics such as malarial and human immunodeficiency virus infections, follow a scale-free distribution in terms of population size and density. We explore these relationships and dynamics in a tropical context using statistical analyses and available geospatial data to identify the scale dynamics between urbanization processes and disease transmission in Colombia. We found that rural populations and certain disease dynamics were described by power-laws that are frequently mentioned in urbanization studies. However, we found that malaria presented higher intensity of infection in human settlements of less than 50,000 individuals, particularly for ethnic indigenous populations. Results indicate that epidemics and urbanization dynamics do indeed follow scales in Colombia; findings that differ from previous epidemiological studies such as those for malarial infection. Additionally, we identified trends showing that malarial infections become endemic in peri-urban areas. Targeting such peri-urban locations and certain demographic groups are key for managing public health issues in the urbanizing tropics.

‘Arrayana’ mandarin fruits have a short postharvest life and are sensitive to chilling injury (CI) during cold storage. Brassinosteroids (BR) have been used as a sustainable technology to alleviate CI in fruits and improve postharvest quality. This study evaluated the effect of applying the 24-epibrasinolide analogue (EBR), at doses of 5 mg L-1; DI-31 analogue, at 5 and 10 mg L-1; and control, on the main physical and biochemical characteristics of 'Arrayana' mandarin stored at 4°C for 40 days and, subsequently, 7 days at room temperature (shelf life). The application of EBR and DI-31 analogues reduced the appearance of CI in the exocarp of 'Arrayana' mandarin fruits by reducing electrolyte leakage, maintaining membrane integrity, and increasing antioxidant activity and phenol content at the end of cold storage and shelf life. This was especially pronounced with 5 mg L-1 of EBR. Similarly, the BR maintained the postharvest quality of mandarins by reducing weight loss, respiratory intensity and chlorophyll degradation; increasing β-carotene; and maintaining titratable acidity, and soluble solids. Our research reports for the first time CI tolerance in Arrayana mandarin using natural (EBR) and spirostanic (DI-31), analogues and illustrates the tolerance functionality of the DI-31 analog on CI in fruit postharvest.

The sympathetic restoration and conservation of built cultural heritage play a significant role in the management and preparedness for future climate scenarios by facilitating adaptive reuse, enhancing cultural resilience, preserving traditional knowledge, and boosting tourism. The importance of restoring damaged heritage sites after an earthquake drew international attention to Nepal after the 2015 Gorka Earthquake. UNESCO established an office in Kathmandu to promote the restoration of tangible and intangible heritage in the area. This included developing structural analyses of buildings with historical and cultural value that due to their nature cannot be intervened with the same methodology as modern buildings. In this paper, the case study of the earthquake-damaged Gopinath temple, is discussed. First, an initial visual inspection phase and the following diagnosis of the structure are discussed. Then, the results from a series of static and dynamic structural analyses performed to determine the safety level of the structure, together with a sensitivity analysis, are presented. A sympathetic intervention proposal capable of increasing the temple safety level and based on the addition of timber plates, has resulted in substantial improvements of the lateral behavior of the structure. The proposed intervention is deemed sustainable and able to increase the resilience of the temple in the face of future hazards.

This paper investigates portfolio optimization methodologies and short-term investment strate-gies in the context of the cryptocurrency market, focusing on ten major cryptocurrencies from January 2020 to November 2023. We employ high frequency data and utilize the Kurtosis Mini-mization methodology, alongside other optimization strategies, to construct and evaluate port-folios under different rebalancing frequencies. The empirical analysis reveals that cryptocurren-cies exhibit significant volatility, skewness, and kurtosis, necessitating sophisticated portfolio management techniques. We find that the Kurtosis Minimization methodology consistently outperforms other optimization strategies, delivering optimal returns to investors, particularly in shorter-term investment horizons. We demonstrate the diversification benefits of integrating cryptocurrencies into multi-asset portfolios and emphasize the importance of regular portfolio rebalancing in the volatile cryptocurrency market. Our findings offer insights for portfolio man-agers and investors seeking to optimize their investment outcomes in the cryptocurrency market, highlighting the importance of risk management, diversification, and dynamic portfolio man-agement strategies.

Electrical rotating machines like Induction Motors (IMs) are widely used in several industrial applications since their robust elements, provide high efficiency and give versatility in industrial applications. Nevertheless, the occurrence of faults in IMs is inherent to their operating conditions, hence, Inter-turn short-circuit (ITSC) is one of the most common failures that affect IMs and its appearance is due to electrical stresses leads to the degradation of the stator winding insulation. In this regard, this work proposes a diagnosis methodology for the assessment and detection of incipient ITSC in IMs, the proposed method is based on the processing of vibration, stator currents and magnetic stray-flux signals. Certainly, the novelty and contribution include the characterization of different physical magnitudes by estimating a set of statistical time domain features, as well as, their fusion and reduction through the Linear discriminant Analysis technique within a feature-level fusion approach. Furthermore, the fusion and reduction of information from different physical magnitudes leads to perform the automatic fault detection and identification by a simple Neural-Network (NN) structure. The proposed method is evaluated under a complete set of experimental data and the obtained results demonstrate that the fusion of information from different sources (physical magnitudes) allows to improve the accuracy during the detection of ITSC in IMs , the results make this proposal feasible to be incorporated as a part of condition-based maintenance programs in the industry.

Topology optimization has become a very popular design tool when an optimum design with a concrete objective and subjected to several restrictions is searched. However, the resultant shape of the optimization process isn’t usually easy to manufacture with a typical manufacturing method as machining, being necessary an interpretation and validation of the result; besides, some parameters can be chosen, and the final shape is directly dependent on them. In this paper, a sensitivity analysis of the main parameters involved in 3D topology optimization, the penalization and the filter radius, is carried out for the concrete case of the density-based method, analyzing how manufacturable the results are for 3 axis machining. Also, a new filter and method is proposed for obtaining highly manufacturable and low interpretable parts. The main aim of the study is to help designers to choose the more appropriate parameters and showing what they must have into account for obtaining the desired optimized shapes. Note that the density-based topology optimization method has been chosen due to its popularity in commercial packages, so the conclusions may have direct applications in designers’ work. Finally, the results of the study are verified through different cases for checking the validity of the conclusions.

This paper seeks to optimize the mechanical and durability properties of ultra-high performance concrete (UHPC). To meet this objective, concrete specimens were manufactured by using 1,100 kg/m3 of binder, water/binder ratio 0.20, silica sand and last generation of superplasticizer. Silica fume, metakaolin and two types of nano silica were used for improving the performances of the concrete. Additional mixtures included 13mm long OL steel fibers. Compressive strength, electrical resistivity, mercury intrusion porosimetry tests and differential and thermogravimetric thermal analysis were carried out. The binary combination of nano silica and metakaolin, and the ternary combination of nano silica with metakaolin and silica fume, led to the best performances of the UHPC, both mechanical and durable performances.

Methotrexate is an antimetabolic agent with proliferative and immunosuppressive activity. It has been demonstrated to be an effective treatment for acute lymphoblastic leukemia (ALL) in children. However, there is evidence of an association between methotrexate and toxicity risks, which influences the personalization of treatment, particularly in the case of childhood ALL. This article presents the development and implementation of an algorithm based on artificial neural networks to detect methotrexate toxicity in pediatric patients with acute lymphoblastic leukemia. The algorithm utilizes historical clinical and laboratory data, with an effectiveness of 99% in the tests performed with the patients dataset. The use of neural networks in medicine is often linked to disease diagnosis systems. However, neural networks are not only capable of recognizing examples, but also hold very important information. For this reason, one of the main areas of application of neural networks is the interpretation of medical data. In this article we diagnose with the application of neural networks in medicine with a concrete example: Detecting Methotrexate in Pediatric Patient in its early stages.

Size effect on plain concrete specimens is well known and can be correctly captured when performing numerical simulations by using a well characterised softening function, but in the case of fibre reinforced concrete this is not directly applicable, since an only diagram cannot capture the material behaviour on elements with different size due to dependence of the orientation factor of the fibres with the size of the specimen. In previous works, the use of a trilinear softening diagram proved to be very convenient for reproducing fracture of polyolefin fibre reinforced concrete elements, but only if it is previously adapted for each specimen size. In this work, a predictive methodology is used to reproduce fracture of polyolefin fibre reinforced concrete specimens of different sizes under three-point bending. Fracture is reproduced by means of a well known embedded cohesive model, with a trilinear softening function that is defined specifically for each specimen size. The fundamental points of these softening functions are defined a priori by using empirical expressions proposed in past works, based on an extensive experimental background. Therefore, the numerical results are obtained in a predictive manner, and then compared with a previous experimental campaign, showing that this approach properly captures the size effect, although some values of the fundamental points in the trilinear diagram could be defined more accurately.

Van Wyk Grumbach syndrome refers to the development of peripheral precocious puberty, long-standing hypothyroidism, and gonadal masses; when not diagnosed, an unnecessary gonadectomy may be done; Here we present a case of a 10-year-old girl with Down syndrome, short stature, and vitiligo presented with vaginal bleeding, and a pelvic mass, in whom bilateral gonadectomy was performed. Most cases of Van Wyk Grumbach syndrome present in women, and classic hypothyroidism symptoms always precede the diagnosis; 11% of patients have Down Syndrome, sometimes tumor markers get elevated, and some develop severe symptoms (myopathy, short stature, mental delay, ascites, pericardial effusion, Cullen sign, pituitary hyperplasia, and severe anemia), that respond to levothyroxine treatment; Conclusions: Children with peripheral precocious puberty and gonadal masses, must be studied for hypothyroidism before any radical decision is made. Keywords: Puberty, Precocious; Ovarian Cysts, gonadectomy, Van Wyk Grumbach Syndrome

Protein malnutrition is present in developing countries but also in developed ones, due by the actual eating habits with insufficient protein intake, in addition to this it is estimated by the Food and Agricultural Organization of the United Nations an increase of world population of 9.1 billion people in less those 30 years, posing the challenge of nourish the mankind. There are different strategies to afford this challenge, one of the most promising ones is to approach novel protein sources like plants, microorganisms, and insects from dry lands.

Biological gels (bio-gels) are hydrated polymer networks that serve diverse biological functions, which often lead to intentional or unintentional exposure to particulate matter. In this work, we derive a microscopically motivated framework that enables the investigation of penetration mechanisms into bio-gels. We distinguish between two types of mechanisms: spontaneous (unforced) penetration and forced penetration. Using experimental data available in literature, we exploit the proposed model to characterize and compare between the micro-structures of respiratory, intestinal, and cervicovaginal mucus and two types of biofilms. Next, we investigate the forced penetration process of spherical and ellipsoidal particles into a locally quadrilateral network. The proposed framework can be used to improve and complement the analysis of experimental findings in vitro, ex vivo, and in vivo. Additionally, the insights from this work pave the way towards enhanced designs of nano-medicines and allow to assess risk factors related to the nano-pollutants exposure.

This article presents a method that uses a semi-automatic algorithm for the detection and analysis of microcracks in steel test specimens using binarized image analysis. It obtains the length along the crack path in contrast to previous methods that have obtained linear length, thereby achieving a closer approximation to its actual value. Additionally, this method automatically calculates the COD and COA parameters with measurement deviations in micrometres, thus providing greater precision than previous methods proposed to date.

The use of the commercial simulator Aspen Plus® could bring an amelioration in the accuracy of the predictions of the chemical species composition in the output streams of the anaerobic digestion process, due to availability of a broad library of thermodynamic and phenomena transport properties in this commercial package. In the present investigation, the process simulation model for anaerobic digestion, which was originally developed by Rajendran et al. [1], has been modified by including a stoichiometric-equilibria reactor to calculate the extent of the ionization of the molecules present in the anaerobic digestate. The refined model offers a more accurate prediction of the composition of the biogas because it delves on the chemical equilibrium of the gaseous stream and the anaerobic digestate. Additionally, the refined model allows to assess the possibility of upgrading the gaseous stream to biomethane degree via manufacturing of ammonium bicarbonate. This processing pathway relies on the stabilization of the anaerobic digestate by means of biomass ash-based treatment. First of all, the titration of the manure digestate with the hydrochloric acid showed that a dose of 3.18 mEq/g would be required to attain the targeted pH of zero-point charge, upon addition of the sewage sludge ash in a ratio to the manure digestate of 0.6 ± 0.2 %. Secondly, the profiles of ammonia, carbon dioxide, and methane found in the biogas agree with both the pH of the treated digestate and the processes described in for the simultaneously upgrading the biogas and the production of ammonium bicarbonate. The refined Aspen Plus® model presented in this article needs to be further developed to ensure the standards are attained in all output streams of stabilized anaerobic digestate, biomethane, and isolated added-value chemical fertilizers.

G-protein coupled estrogen receptor (GPER) was described to exerts several cardioprotective effects. However, the exact mechanism involved in cardiac protection remains unclear. The aim of this study is to investigate the role of GPER activation on excitation-contraction coupling (ECC), and the possibility that such effect participates in cardioprotection. Cardiac myocytes of male Wistar rats were isolated with digestive buffer and loaded with Fura-2-AM for measurement of intracellular calcium transients (CaT). Sarcomere shortening (SS) and L-type calcium current (ICaL) were also registered. Confocal technique was used to measure nitric oxide (NO) production in cells loaded with DAF-FM-diacetate. Cardiac myocytes exposed to E2 (10 nM), or G-1 (1 µM) for fifteen minutes decreased CaT, SS and ICaL. These effects were prevented using G-36 (antagonist of GPER, 1 µM), L-Name (NO synthase inhibitor, 100 nM), or wortmannin (phosphoinositide-3-kinase inhibitor, 100 nM). Moreover, G1 increased NO production, and this effect was abolished in the presence of wortmannin. We concluded that the selective activation of GPER with E2 or G1 in isolated cardiac myocytes of male rats induced a negative inotropic effect due to the reduction of ICaL and the decrease in CaT. Finally, the pathway that we proposed to be implicated in these effects is PI3K-NOS-NO.

Machine learning (ML) has a large capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A set of 22 SD-OCT images belonging to a random set of corneal pathologies was compared to 71 healthy corneas (control group). A binary classification method was applied; three approaches of ML were used. Once all images were analyzed, representative areas from every digital image were also processed and analyzed for a statistical feature comparison between healthy and pathologic corneas. The best performance was obtained from transfer learning - support vector machine (TL-SVM) (AUROC = 0.94, SPE 88%, SEN 100%) and transfer learning – random forest (TL- RF) method (AUROC = 0.92, SPE 84%, SEN 100%), followed by convolutional neural network (CNN) (AUROC = 0.84, SPE 77%, SEN 91%) and random forest (AUROC = 0.77, SPE 60%, SEN 95%). The highest diagnostic accuracy in classifying corneal images was achieved with the TL-SVM and the TL-RF models. In image classification, CNN was a strong predictor. This pilot experimental study developed a systematic mechanized system to discern pathologic from healthy corneas.

Electroencephalography (EEG) enabled earbuds represent a promising frontier in evaluating brain activity beyond traditional laboratory settings. However, these devices need more comprehensive characterization before widespread health related usage. A toolbox was developed to facilitate and expand the assessment of ear-EEG devices. The first component of this toolbox is a desktop application (“EaR-P Lab”) that integrates EEG validation paradigms. This application is designed to be used with EEG amplifiers compatible with the Lab Streaming Layer (LSL) protocol. The second element of the toolbox introduces an adaptation of the phantom testing concept, to the domain of ear-EEG by using 3D ear scans of the tested individuals, allowing controlled assessment of ear-EEG devices. The EEG paradigms were validated for scalp acquisitions and applied on ear-EEG measurements, under wet ear electrode conditions. The ear-EEG phantom was successful in measuring useful metrics in EEG system characterization, highlighting performance differences within the electrodes on the tested earpieces. This knowledge was factored in to select an optimal electrode reference which resulted in increased response power on the auditory steady-state response (ASSR). Through this work, an ear-EEG evaluation toolkit is made available with the intention to enable future and systematic assessment of novel ear-EEG devices from the hardware to the neural signals.

This paper aims to provide the smart grid research community with an open and accessible general mathematical framework to develop and implement optimal flexibility mechanisms in large-scale network applications. The motivation of this paper is twofold. On the one hand, flexibility mechanisms are currently a hot topic of research, which is aimed to mitigate variation and uncertainty of electricity demand and supply in decentralised grids with a high aggregated share of renewables. On the other hand, a large part of such related research is performed by heuristic methods, which are generally inefficient (such methods do not guarantee optimality) and difficult to extrapolate for different use cases. Alternatively, this paper presents an MPC-based (Model Predictive Control) framework explicitly including a generic flexibility mechanism which is easy to particularise to specific strategies such as Demand Response, Flexible Production and Energy Efficiency Services. The proposed framework is benchmarked with other non-optimal control configurations to better show the advantages it provides. The work of this paper is completed by the implementation of a generic use case which aims to further clarify the use of the framework and thus, to ease its adoption by other researchers in their specific flexibility mechanisms applications.

We construct admissible circulant Laplacian matrix functions as generators for strictly increasing random walks on the integer line. These Laplacian matrix functions refer to a certain class of Bernstein functions. The approach has connections with biased walks on digraphs. Within this framework, we introduce a space-time generalization of the Poisson process as a strictly increasing walk with discrete Mittag-Leffler jumps subordinated to a (continuous-time) fractional Poisson process. We call this process ‘space-time Mittag-Leffler process’. We derive explicit formulae for the state probabilities which solve a Cauchy problem with a Kolmogorov-Feller (forward) difference-differential equation of general fractional type. We analyze a “well-scaled” diffusion limit and obtain a Cauchy problem with a space-time convolution equation involving Mittag-Leffler densities. We deduce in this limit the ‘state density kernel’ solving this Cauchy problem. It turns out that the diffusion limit exhibits connections to Prabhakar general fractional calculus. We also analyze in this way a generalization of the space-time fractional Mittag-Leffler process. The approach of construction of good Laplacian generator functions has a large potential in applications of space-time generalizations of the Poisson process and in the field of continuous-time random walks on digraphs.

This paper investigates the use of deep learning techniques to perform energy demand forecasting. Specifically, the authors have adapted a deep neural network originally thought for image classification and composed of a convolutional neural network (CNN) followed by a multilayered fully connected artificial neural network (ANN). The convolutional part of the network was fed with a grid of temperature forecasting data distributed in the area of interest in order to extract a featured temperature. The subsequent ANN is then fed with this calculated temperature along with other data related to the timing of the forecast. The proposed structure was first trained and then used in a real setting aimed to provide the French energy demand forecast using ARPEGE forecasting weather data. The results show that the performance of this approach is in the line of the performance provided by the reference RTE subscription-based service, which opens the possibility to obtain high accuracy forecasting using widely accessible deep learning techniques through open-source machine learning platforms.

Fibre reinforced cementitious materials (FRC) have become an attractive alternative for structural applications. Among such FRC, steel and polyolefin fibre reinforced concrete and glass fibre reinforced concrete are the most used ones. However, in order to exploit the properties of such materials structural designers need constitutive relations that reproduce FRC fracture behaviour accurately. This contribution analyses the suitability of multilinear softening functions combined with a cohesive crack approach for reproducing the fracture behaviour of the FRC previously mentioned. The implementation performed accurately simulates the fracture behaviour while being versatile, robust and efficient from a numerical point of view.

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.

While Twitter has been touted to provide up-to-date information about hazard events, the reliability of tweets is still a concern. Our previous publication extracted relevant tweets containing information about the 2013 Colorado flood event and its impacts. Using the relevant tweets, this research further examined the reliability (accuracy and trueness) of the tweets by examining the text and image content and comparing them to other publicly available data sources. Both manual identification of text information and automated (Google Cloud Vision API) extraction of images were implemented to balance accurate information verification and efficient processing time. The results showed that both the text and images contained useful information about damaged/flooded roads/street networks. This information will help emergency response coordination efforts and informed allocation of resources when enough tweets contain geocoordinates or locations/venue names. This research will help identify reliable crowdsourced risk information to enable near-real time emergency response through better use of crowdsourced risk communication platforms.

In this article, we delve into the intricate behavior of electronic mechanisms underlying NMR magnetic shieldings, σ, in molecules containing heavy atoms such as cadmium, platinum, and mercury. Specifically, we explore PtXn^{−2} (X = F, Cl, Br, I; n = 4, 6) and XCl2 Te2 Y2 H6 (X = Cd, Hg; Y = N, P) molecular systems. It is known that the leading electronic mechanisms responsible for the relativistic effects on σ are well characterized by the linear response with elimination of small components model (LRESC). In this study, we present results obtained from the innovative LRESC-Loc model, which offers the same outcomes as the LRESC model but employs localized molecular orbitals (LMOs) instead of canonical MOs. These LMOs provide a chemist’s representation of atomic core, lone pairs, and bonds. The whole set of electronic mechanisms responsible of the relativistic effects can be expressed in terms of both non-ligand-dependent and ligand-dependent contributions. We elucidate the electronic origins of trends and behaviors exhibited by these di- verse mechanisms in the aforementioned molecular systems. In PtX4^{−2} molecules, the predominant relativistic mechanism is the well-established one-body spin-orbit (σ^SO(1) ) mechanism, while the paramagnetic mass-velocity (σ^Mv ) and Darwin (σ^Dw ) contributing mechanisms also demand con- sideration. However, in PtX6−2 molecules, the σ Mv+ Dw contribution surpasses that of the SO(1) mechanism, thus influencing the overall ligand-dependent contributions. As for complexes con- taining Cd and Hg, the ligand-dependent contributions exhibit similar magnitudes when nitrogen is substituted with phosphorus. The only discrepancy arises from the σ^SO(1) contribution, which changes sign between the two molecules due to the contribution of bond orbitals between the metal and tellurium atoms.

Weight loss solutions are on the rise, and there is growing interest in natural alternatives to the pharmaceuticals in the market, which are not devoid of relevant side effects. To this end, the objective of the current study is to assess the effects of a botanical-based blend comprised of lemon verbena and hibiscus extracts in weight management, body fat, appetite, lipid, and glucose profiles, in an overweight population, for 90 days. As a result, the volunteers presented significant weight loss in absence of diet, which coincided with decreased body fat. Body fat was assessed by anthropometry, electrical bioimpedance and DEXA scan. Cholesterol levels were also significantly decreased. Satiety assessment revealed that the product contributed to increased feeling of fullness and satisfaction after a meal, compared to the placebo group, which could contribute to the weight loss observed. Blood glucose and blood pressure levels remained unchanged, which was expected as the volunteers were normoglycemic and their blood pressure was in the healthy range. In conclusion, daily supplementation of a botanical-based blend contributes to weight loss in overweight individuals, in absence of diet, while not affecting other parameters that are in the healthy range. This product could be a candidate alternative or add-on to other weight loss products, as part of a healthy lifestyle.

The need to develop novel lightweight materials and their manufacturing processes is sets out to meet the new aerospace, automotive and construction requirements. Within this context, this research work is proposed to develop a novel thermoplastic composite material with high mechanical properties. These composites will be based on thermoplastic matrixes made from polyamide and 35% short glass fiber filled-polyamide reinforced with different types of fabrics. As reinforcement, glass fiber fabrics will be used as the base. They will be treated with different processes, both chemical and physical, to promote adherence to the matrix. Textile overmoulding technology was selected for manufacturing these composites. This technology was primarily developed to manufacture aesthetic lined components and has achieved a great implantation. Once these new composites are manufactured, they will be submitted to different tests to evaluate their behavior regarding adhesion, impact strength and stiffness. It is expected an improvement on stiffness and impact absorption.

This paper presents a statistical approach to identify the underlying roughness characteristics in synthetic aperture radar (SAR) intensity data. The physical modeling of this kind of data allows the use of the Gamma distribution in the presence of fully-developed speckle, i.e., when there are infinitely many independent backscatterers per resolution cell, and none dominates the return. Such areas are often called ``homogeneous'' or ``textureless'' regions. The GI0 distribution is also a widely accepted law for heterogeneous and extremely heterogeneous regions, i.e., areas where the fully-developed speckle hypotheses do not hold. We propose three test statistics to distinguish between homogeneous and inhomogeneous regions, i.e., between gamma and GI0 distributed data, both with a known number of looks. The first test statistic uses a bootstrapped non-parametric estimator of Shannon entropy, providing a robust assessment in uncertain distributional assumptions. The second test uses the classical coefficient of variation (CV). The third test uses an alternative form of estimating the CV based on the ratio of the mean absolute deviation from the median to the median. We apply our test statistic to create maps of \(p\)-values for the homogeneity hypothesis. Finally, we show that our proposal, the entropy-based test, outperforms existing methods, such as the classical CV and its alternative variant, in identifying heterogeneity when applied to both simulated and actual data.

This review article seeks to systematically identify appropriate ways to measure managerial skills. The systematic literature review was conducted according to the criteria in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guide, and the eligibility criteria were declared through the PICOS tool (population, interventions, comparators, outcomes and study); a tool based on 6,803 records identified bibliometrically in the Web of Science database. The literature review stages determined a reduced set of articles that presented valid and reliable measurement scales covering some determinant constructs on managerial skills for employability such as fundamental, emotional, managerial, leadership, decision-making, communication and teamwork skills.

Sustainability has been playing a major role on the world stage. As with everything in the be-ginning, it was aligned to purely environmental contexts, but with the passing of the years and the new way of producing, marketing, and consuming, this concept has encompassed other as-pects which are the way of producing products and services. In this article, to obtain information on the implementation of sustainable innovation, a search equation was formulated in the SCOPUS database, contemplating the period from 2018 to 2023 as a time interval, with a total of 62 articles. Once the search of the published articles was carried out, 7 categories were formed to classify the research topic of each of the publications with Bibliometrix software, according to the main ob-jective and methodology used in each one. In this sense, 44% of the articles published are related to open innovation, and 26% of the articles are focused on sustainable business models. At the end of the analysis of the implementation of innovation according to the articles consulted, it was possible to establish that sustainable innovation began an important work, in the mitigation of the adverse impacts.

This paper presents a novel segmentation algorithm specially developed for applications in 3D point clouds with high variability and noise, particularly suitable for heritage building 3D data. The method can be categorized within the segmentation procedures based on edge detection. In addition, it uses a graph-based topo-logical structure generated from the supervoxelization of the 3D point clouds, which is used to make the clo-sure of the edge points and to define the different segments. The algorithm provides a valuable tool for generating results that can be used in subsequent classification tasks and broader computer applications dealing with 3D point clouds. One of the characteristics of this segmentation method is that it is unsupervised, which makes it particularly advantageous for heritage applications where labelled data is scarce. It is also easily adaptable to different edge point detection and supervoxelization algorithms. Finally, the results show that the 3D data can be segmented into different architectural elements, which is important for further classification or recognition. Extensive testing on real data from historic buildings demonstrates the effectiveness of the method. The results show superior performance compared to three other segmentation methods, both globally and in the segmentation of planar and curved zones of historic buildings.

This document presents, from environmental thinking (ecosystem - culture relations), the concept of the Main Agroecological Structure of Agroecosystems (MAS, EAP, for its acronym in Spanish), considered as a dissipative cultural structure. It discusses its possible applications (resilience, production, diversity) both inside and outside the farms. The MAS can be useful in the land planning on the farms, based on the concept of potential MAS that allows the quantification of the management of internal and external corridors, including natural vegetation. At the same time, it can be useful in the context of landscape management because it shows a series of cultural relations (economic, social, symbolic and technological) hidden from the partial analysis of landscape ecology.

We have carried out a systematic review of the scientific literature published on PM and, more specifically, on its presence in fish and seafood of interest to the population from Mediterranean area. Given its preference and wide acceptability in the scientific community, we followed the PRISMA. The potential functional and clinical toxicity in humans due to MP in fish must be considered by the chemical composition of the microplastics the presence of PM and its additives, associated contaminants and pathogens in fish and shellfish, as well as the possible effects on human health, requires improving legislation on evaluation and providing a basis for consumer protection.

Brugada Syndrome is a cardiac channelopathy closely related to lethal arrhythmias and sudden death in people without underlying structural pathology. The diagnosis is usually assumed with electrocardiographic patterns strictly limited to the right precordial leads, V1 or V2; but this is not so at all. In our article, we describe the clinical case of a patient with a novel and different electrocardiographic presentation: the typical diagnostic pattern was presented in a lower lead of the electrocardiogram, and next to it, another pattern was presented in a contiguous lead. In addition, we propose the possible association of a structural pathology (non-compaction cardiomyopathy) with Brugada Syndrome, since both share a possible common genetic origin in the SCN5A gene.

Access to broadband communications in different parts of the world has become a priority for some governments and regulatory authorities around the world in recent years. Building new digital roads and pursuing a connected society includes looking for easier access to the Internet. In general, not all the areas where people congregate are fully covered, especially in rural zones, thus restricting access to data communications and bringing inequality. In the present review article, we have comprehensively surveyed the use of three platforms to deliver broadband services to such remote and low-income areas are proposed: Unmanned Aerial Vehicles (UAV), Altitude Platforms (APS), and Low-Earth Orbit (LEO) satellites. These novel strategies support the connected and accessible world hypothesis. Hence UAVs are considered a noteworthy solution since their efficient maneuverability can aboard the rural coverage issues or not-spots.

Responsible innovation combines philanthropic and economic aspects and it is common to refer to entrepreneurs who lead it as "social entrepreneurs". The present study of 100 Mexican SMEs, provides knowledge of exploratory nature about what the models of organization are conducive to SMEs in the generation and development of responsible innovations. Through the statistical technique of cluster analysis, this study identified and characterized four models of organization according to the level of social entrepreneurship reached: (1) “The techno-scientific organization”, (2) “The techno-social organization”, (3) “The capitalist-social organization” and (4) “The capitalist organization”. While in Europe the dominant discourse about responsible innovation focuses on the control of the risk of social rejection of the advance of science and technology; in contexts such as the Mexican, the phenomenon is configured as the mechanism through which entrepreneurs articulate its technological and scientific capabilities to solve priority and specific problems of the society, however, the social impact does not crucially affect their business initiatives. The techno-scientific organization (50% of studied SMEs) is proposed as the model of organization with greater viability for Mexican entrepreneurs.

The broad bean plant contains L-DOPA, a compound that is essential for patients with Parkin-son’s disease. However, little has been reported on other broad bean compounds that have bene-ficial effects on health. The objective was to evaluate plants of four Mexican broad bean varieties to determine the content and yield of total phenolic compounds (TPC), total flavonoids (TF), and L-DOPA, as well as to analyze the flavonoid profile and antioxidant (AA) and anti-inflammatory (AANTI) activity in vitro. Broad bean seeds were sown in the field and plants were harvested 20 days after emergence. The analyses were performed with visible UV spectrophotometry and HPLC. The variety José María produced the highest yield of TPC (9.30 g m-2), TF (8.08 g m-2) and L-DOPA (5.64 g m-2) per unit of area. The highest yields per plant were obtained with the Rojita variety: TPC (0.25 g plant-1), TF (0.21 g plant-1) and L-DOPA (0.17 g plant-1). This variety also had the highest antioxidant (CI50= 87.68 µg mL-¹) and anti-inflammatory (CI50= 74.40 mg mL-1) activi-ty, which was attributed to the L-DOPA compounds and to rutin and isoorientins, respectively. The flavonoid profile revealed the presence of rutin and isoorientins, which had not been previ-ously detected in the broad bean plant.

Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with numerous negative impacts in the Chilean salmon farming industry. Although transcriptomic studies of P. salmonis and its host have been performed, dual host-pathogen proteomic approaches during infection are still missing. Considering that gene expression not always corresponds with observed phenotype, and bacteriological culture studies inadequately reflect infection conditions, to improve the existing knowledge for the pathogenicity of P. salmonis we present here a global proteomic profiling of Salmon salar macrophage-like cell cultures infected with P. salmonis LF-89. The proteomic analyses identified several P. salmonis proteins from two temporally different stages of macrophages infection; some of them related to key functions for bacterial survival in other intracellular pathogens. Metabolic differences were observed in early-stage infection bacteria, compared to late-stage infections. Virulence factors related to membrane, LPS and surface component modifications, cell motility, toxins and secretion systems also varied between the infection stages. Pilus proteins, beta-hemolysin and the T6SS were characteristic of the early-infection stage, while fimbria, upregulation of 10 toxins or effector proteins, and the Dot/Icm T4SS were representative of the late-infection stage bacteria. Previously described virulence-related genes in P. salmonis plasmids were identified by proteomic assays during infection in SHK-1 cells, accompanied by an increase of mobile-related elements. By comparing the infected and un-infected proteome of SHK-1 cells, we observed changes in cellular and ROS homeostasis, innate immune response, microtubules and actin cytoskeleton organization and dynamics, alteration in phagosome components, iron transport and metabolism, and amino acids, nucleoside and nucleotide metabolism, together with an overall energy and ATP production alteration. Our global proteomic profiling and the current knowledge of the P. salmonis infection process allowed us to propose a model of the macrophage-P. salmonis interaction.

Cosmopolitan Gram-negative cyanobacteria may affect human and animal health by contaminating terrestrial, marine and freshwater environments with toxins, such as lipopolysaccharide (LPS). The cyanobacterial genus Scytonema (S) produces several toxins, but to our knowledge the bioactivity of genus Scytonema LPS has not been investigated. We recently reported that cyanobacterium Oscillatoria sp. LPS elicited classical and alternative activation of rat microglia in vitro [1]. Thus, we hypothesized that treatment of brain microglia in vitro with either cyanobacteria S. javanicum or S. ocellatum LPS might stimulate classical and alternative activation with concomitant release of superoxide anion (O₂⁻), matrix metalloproteinase-9 (MMP-9) and cytokines and chemokines. Microglia were isolated from neonatal rats and treated in vitro with either S. javanicum LPS, S. ocellatum LPS, or E. coli LPS (positive control) in a concentration-dependent manner for 18 hours at 35.9 °C. We observed that treatment of microglia with either E. coli LPS, S. javanicum or S. ocellatum LPS generated statistically significant and concentration-dependent O₂⁻, MMP-9 and pro-inflammatory cytokines IL-6 and TNF-α, pro-inflammatory chemokines MIP-2/CXCL-2, CINC-1/CXCL-1 and MIP-1α/CCL3, and the anti-inflammatory cytokine IL-10. Thus, our results provide experimental support for our working hypothesis because both S. javanicum and S. ocellatum LPS elicited classical and alternative activation of microglia and concomitant release of O₂^-, MMP-9 and cytokines and chemokines in a concentration-dependent manner. To our knowledge this is the first report on the toxicity of cyanobacteria S. javanicum and S. ocellatum LPS to microglia, an immune cell type involved in neuroinflammation and neurotoxicity in the central nervous system.

This research investigates the application of Fused Filament Fabrication (FFF) in producing WC-10Co hardmetals, focusing binder formulations and understanding its influence on extrusion force and the influence of printing variables on green density of the samples. By examining the interplay between different binder compositions and backbone contents, the study aims to enhance the mechanical properties of the sintered parts while reducing defects inherent in the printing process. Evidence suggested that formulated feedstocks influenced the hardness of the sintered hardmetal, not due to microstructural changes but to macrostructural responses like macro defects introduced during printing, debinding and sintering of the samples. The results demonstrate the critical role of PP-MA content in improving part density and sintered hardness, suggesting the need for specific thermal debinding protocols tailored to each feedstock. The study provides insights into the formulation of feedstocks for hardmetal FFF, proposing a path toward refining manufacturing processes for better quality and performance of 3D printed hardmetal components.