The aim of this study was to identify differentially expressed genes, biological processes and metabolic pathways related to adipogenesis and lipogenesis in calves receiving different diets during the cow-calf phase. Forty-eight uncastrated F1 Angus × Nellore males were randomly assigned to two treatments from 30 days of age to weaning: no creep feeding (G1) or creep feeding (G2). After weaning, the animals were feedlot finished for 180 days and fed a single diet containing 12.6% forage and 87.4% corn-based concentrate. Longissimus thoracis muscle samples were collected by biopsy at weaning for transcriptome analysis by RNA-Seq and at slaughter for the measurement of intramuscular fat content (IMF) and marbling score (MS). Animals of G2 had 17.2% and 14.0% higher IMF and MS, respectively (P < 0.05). We identified 947 differentially expressed genes (log2 fold change 0.5; FDR 5%); of these, 504 were up-regulated and 443 were down-regulated in G2. Part of the genes up-regulated in G2 were related to PPAR signaling (PPARA, SLC27A1, FABP3, and DBI), unsaturated fatty acid synthesis (FADS1, FADS2, SCD, and SCD5), and fatty acid metabolism (FASN, FADS1, FADS2, SCD, and SCD5). Regarding biological processes, the genes up-regulated in G2 were related to cholesterol biosynthesis (EBP, CYP51A1, DHCR24, and LSS), unsaturated fatty acid biosynthesis (FADS2, SCD, SCD5, and FADS1), and insulin sensitivity (INSIG1 and LPIN2). Cow-calf supplementation positively affected energy metabolism and lipid biosynthesis, and thus favored the deposition of marbling fat during the postweaning period. Here it was shown, in an unprecedented way, by analyzing the transcriptome, genes, pathways and enriched processes due to the use of creep feeding.

This work shows the results obtained in the synthesis of srilankite nanoparticles, (Zr, Ti)O2, and TiO2 anatase, both catalysts presented an admix of phases, anatase/rutile, and srilankite/rutile, respectively. Their performance in the production of biodiesel through the esterification of oleic acid was evaluated. The catalysts were obtained using the sol-gel process and sulfated via the impregnation method. The samples were characterized using X-ray diffraction (XRD), scan electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and Fourier-Transform Infrared Spectroscopy (FTIR) to analyze the properties in its crystalline structure, morphology, and chemical composition. Its efficiency during the esterification reaction was measured based on the decrease in free fatty acids (FFA). FFA, oleic acid was added at different weight percentages (1%, 3%, and 5% w/w). The time of reaction was 6 hours at 55 °C and the catalyst with better performance was the sulfated Srilankite/rutile, reaching a maximum conversion of up to 90%.

Cybersecurity in Critical Infrastructures, and in particular Digital Substations is a topic of wide interest for industry and academic community. One of the approaches widely used to support research on this field is the use of datasets (i.e., traffic samples collected during the operation of an infrastructure). However, generating datasets from operational electrical systems presents certain challenges: i) The generation of these datasets generally implies the operation under controlled or ideal conditions, which possible ignores the dynamics of real-world operations within a digital electrical substation; and ii) Captured data often contains sensitive information, posing challenges for publication within the research community. This paper introduces the development of a dataset for cybersecurity research, focusing on the analysis of GOOSE spoofing attacks, given the critical role of GOOSE protocol in executing operational and control actions within Digital Substations. The dataset exposes the real effect of the attack by executing unwanted operations or actions under various operational conditions, including both stable electrical system scenarios and situations where failures are present in the electrical system. The dataset was acquired from a laboratory testbed developed within a physical infrastructure that emulates the actual operation of a digital substation with two bays. Experiments allowed to observe relevant properties of the traffic associated to GOOSE protocol, and the actual vulnerability of a DS infrastructure regarding Spoofing Attacks.

Sarcopenia is an age-related condition that involves a progressive decline in muscle mass and function, leading to increased risks of falls, frailty, and mortality. Although the exact mechanisms are not fully understood, aging-related processes like inflammation, oxidative stress, reduced mitochondrial capacity, and cell apoptosis contribute to this decline. Disruption of the circadian system with age may initiate these pathways in skeletal muscle, preceding the onset of sarcopenia. At present, there is no pharmacological treatment for sarcopenia, only resistance exercise and proper nutrition may delay its onset. Melatonin, derived from tryptophan, emerges as an exceptional candidate for treating sarcopenia due to its chronobiotic, antioxidant, and anti-inflammatory properties. Its impact on mitochondria, organelle where it is synthesized and crucial in aging skeletal muscle, further highlights its potential. In this review, we discuss the influence of clock genes in muscular aging, with special reference to peripheral clock genes in the skeletal muscle, as well as their relationship with melatonin, which is proposed as a potential therapy against sarcopenia.

Abstract: Urban population growth and the expansion of the built environment, pollution, overexploitation of water, inequality in water distribution, and the impacts of climate change in future availability of water, are all elements that jeopardize urban water security. Due to the complexity of urban water systems and their relevance for urban life, a holistic and integrative perspective is therefore needed to address such challenges. In this paper, Urban Water Metabolism (UWM) has been used for comprehensively understanding water (in)security in the City of Puebla (Mexico) and its metropolitan area. Water inflows and outflows have been estimated using a Material Flow Analysis (MFA) method with data either obtained from official sources or simulated with the Monte Carlo method. Our findings show that the UWM configuration in the City of Puebla and its metropolitan area is effective for generating profits to service providers and water related business, yet ineffective to guarantee citizens’ Human Right to Water and Sanitation (HRWS), a right recognized in the Constitution of Mexico. We conclude that to advance towards an inclusive and sustainable provision of water, economic interests must be reconsidered and therefore adjusted so they can be in line with such aspirational socioecological goals. UWM accounting can therefore inform new water governance arrangements, those based on both the best available knowledge and a vibrant participation of all relevant stakeholders.

Climate change has become a major concern for developing countries given the risk that it posses on energy and food independence, and on general productivity. Despite having an energy system with low carbon intensity when compared to other Latin American countries, Colombia is already facing climate change impacts and requires urgent efforts to mitigate them. As a developing country, the challenge is bigger as policies for economic growth should be in line with the global commitment of reducing greenhouse gas emissions. With the aim of contributing to the design of climate policies, this study assesses the impact of economic development on the environment by examining the validity of the Environmental Kuznets Curve hypothesis for Colombia. Statistically validated and stable autoregressive distributed lag models are estimated for three different environmental indicators: carbon dioxide emissions, methane emissions, and ecological footprint. Moreover, the effects of other variables such as urbanization, foreign direct investment, value added of agricultural and industrial sectors, and energy use are analyzed with dynamic simulations. Empirical evidence supports a long-run equilibrium relationship among investigated variables and the existence of an inverted U-shaped EKC relationship between Gross Domestic Product (GDP) and methane emissions, and GDP and ecological footprint. Shifting to renewable energy sources and leveraging the use of cleaner technologies in agricultural and industrial sectors are found to be key for economic growth without harming the environment.

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

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

Experimental and clinical data indicates that the initiation and progress of atherosclerosis, and its clinical manifestations, are caused first by circulating apoB-100 lipoproteins that enter and are retained in the arterial intima. Extracellular sulfated proteoglycans (PGs) of the intima are the retention agents. The PGs also initiate physical and biochemical lipoprotein degradation with the production of bioactive, lipid products that trigger an inflammatory response that leads to atherosclerosis. There are many simple methods for measuring abnormalities of circulating lipoproteins and their relation to atherosclerotic cardiovascular disease (ACVD). However, limited research has been aimed to evaluate procedures that could report quantitatively about the contribution of the apo-100 lipoprotein-arterial intima PGs interaction to clinical manifestation of ACVD. In the present review we will discuss observations indicating that simple ex vivo evaluation of the affinity of apoB-100 lipoproteins for arterial PGs and glycosaminoglycans (GAGs) can give indication of its association with clinical manifestations of atherosclerosis. In addition, we will discuss molecular and cellular aspect of the apoB-100 lipoproteins association with arterial PGs that are related to atherogenesis and that support the experimental framework behind the current “Response-to-Retention” hypothesis of atherosclerosis

Psychotherapy is one of the evidence-based clinical interventions for the treatment of depression in older adults with dementia. Randomized Controlled Trials are often the first methodological choice to gain evidence, yet they are not applicable to a wide range of humanistic psychotherapies. Amongst all, the efficacy of the Gestalt therapy (GT) is under-investigated. The purpose of this paper is to present a research protocol aiming to assess the effects of a GT-based intervention on people with dementia (PWD) and the indirect influence on their family carers. The study implements the Single-Case Experimental Design with Time-Series Analysis that will be carried out in Italy and Mexico. Ten people in each country, who received a diagnosis of dementia and present depressive symptoms, will be recruited. Eight or more GT sessions will be provided whose fidelity will be assessed by the GT Fidelity Scale. Quantitative outcome measures are foreseen for monitoring participants’ depression, anxiety, quality of life, carers’ burden, and the caregiving dyad mutuality, at baseline and follow-up. The advantages and limitations of the research design are considered. If GT will result effective in the treatment of depression in PWD, it could enrich the range of evidence-based interventions provided by healthcare services.

Recent advancements in mass spectrometry have significantly enhanced our understanding of complex lipid profiles, opening new avenues for oncological diagnostics. This review highlights the importance of lipidomics in the comprehension of certain metabolic pathways and its potential for the detection and characterization of various cancers, in particular melanoma. Through detailed case studies, we demonstrate how lipidomic analysis has led to significant breakthroughs in the identification and understanding of cancer types and its potential for detecting unique biomarkers that are instrumental in its diagnosis. Additionally, the review addresses the technical challenges and future perspectives of these methodologies, including their potential expansion and refinement for clinical applications. The discussion underscores the critical role of lipidomic profiling in advancing cancer diagnostics, proposing a new paradigm in how we approach this devastating disease, with particular emphasis on its application in comparative oncology.

A construction for the systems of natural and real numbers is presented in Zermelo-Fraenkel Set Thoery, that allows for simple proofs of the properties of these systems, and practical and mathematical applications. A practical application is discussed, in the form of a Simple and Linear Fast Adder (Patent Pending). Applications to finite group theory and analysis are also presented. A method is illustrated for finding the automorphisms of any finite group $G$, which consists of defining a canonical block form for finite groups. Examples are given, to illustrate the procedure for finding all groups of $n$ elements along with their automorphisms. The canonical block form of the symmetry group $\Delta_4$ is provided along with its automorphisms. The construction of natural numbers is naturally generalized to provide a simple and sound construction of the continuum with order and addition properties, and where a real number is an infinite set of natural numbers. A basic outline of analysis is proposed with a fast derivative algorithm. Under this representation, a countable sequence of real numbers is represented by a single real number. Furthermore, an infinite $\infty\times\infty$ real-valued matrix is represented with a single real number. A real function is represented by a set of real numbers, and a countable sequence of real functions is also represented by a set of real numbers. In general, mathematical objects can be represented using the smallest possible data type and these representations are calculable. In the last section, mathematical objects of all types are well assigned to tree structures in a proposed type hierarchy.

Background: Sexually transmitted infections and pregnancy in adolescents are acknowledged public health problems in many countries. Although it is known that the proper use of condoms allows avoiding these health problems, their use in Chile is still limited, for unknown reasons. Objective: Based on planned behavioural theory, the aim was to validate a behaviour model regarding condom use by measuring the influence of the variables that predict this use among Chilean university students. Methods: A cross-sectional descriptive study was carried out in October 2016 among 151 Chilean university students belonging to the health and engineering areas. The information was collected through a self-administered survey. The sample was divided into two groups: stable and not stable relationships. Partial least squares (PLS) regression was used for the analysis. Results: It was possible to explain the condom use of the students by 57%. The attitude was the main variable related to the intention of using condoms, together with the perceived behavioural control. Additionally, there are statistically significant differences in the variables that predict condom use among students with stable relations compared to those without a stable relationship. Conclusions: The planned behavioural theory is useful for predicting condom use behaviour when students have a stable partner.

Most studies modelling population mobility and the spread of infectious diseases, particularly using meta-population-multi-patched models, tend to focus on theoretical properties and numerical simulations of such models. There is relatively scanty literature published on fit, inference and uncertainty quantification on epidemic models with population mobility. In this research, we have used three estimation techniques to solve an inverse problem and quantify its uncertainty on a human mobility-based multi-patched epidemic model, using mobile phone sensing data and COVID-19 confirmed positive cases in Hermosillo, Mexico. First, we have utilized a Brownian bridge model using mobile phone GPS data to estimate residence and mobility parameters of the epidemic model. In the second step, we have estimated the optimal model epidemiological parameters by deterministically inverting the model using a Darwinian inspired evolutionary algorithm (EA) known as the genetic algorithm (GA). The third part of the analysis involves performing inference and uncertainty quantification on the epidemic model using two Bayesian Monte Carlo sampling methods: t-walk and Hamiltonian Monte Carlo (HMC). The results show that the estimated model parameters and incidence adequately fit the observed daily COVID-19 incidence in Hermosillo. Moreover, the estimated parameters from HMC result into large credible intervals, improving their coverage for the observed and predicted daily incidences. We also observe improved predictions when using multi-patch model with mobility against the single-patch model.

Brain-computer interfaces (BCI) from electroencephalography (EEG) provide a practical approach to support human-technology interaction. In particular, motor imagery (MI) is a widely-used BCI paradigm that guides the mental trial of motor tasks without physical movement. Here, we present a deep learning methodology, named Kernel-based Regularized EEGNet (KREEGNet), leveled on Centered Kernel Alignment and Gaussian Functional Connectivity, explicitly designed for EEG-based MI classification. The approach proactively tackles the challenge of intra-subject variability brought on by noisy EEG records and the lack of spatial interpretability within end-to-end frameworks applied for MI classification. KREEGNet is a refinement of the widely accepted EEGNet architecture, featuring an additional kernel-based layer for regularized Gaussian functional connectivity estimation based on CKA. The superiority of KREEGNet is evidenced by our experimental results from binary and multi-class MI classification databases, outperforming the baseline EEGNet and other state-of-the-art methods. Further exploration of our model’s interpretability is conducted at individual and group levels, utilizing classification performance measures and pruned functional connectivities. Our approach is a suitable alternative for interpretable end-to-end EEG-BCI based on deep learning.

A mathematical model, composed of two non-linear differential equations that describe the population dynamics of CD4 T cells in the human immune system, as well as viral HIV particles, is proposed. The invariance region is determined, classical equilibria stability analysis is performed using the basic reproduction number, and numerical simulations are carried out, in order to illustrate stability results. Later, the model is modified with a delay term, which describes the time that cells require for immunological activation. This generates a two-dimensional integro-differential system, which is transformed into a system with three ordinary differential equations, via auxiliary variable use. For the new model, equilibrium points are determined, their local stability is examined, and results are studied by way of numerical simulation.

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.

A multiscale mathematical model is proposed seeking to study the propagation dynamics of the Human Immunodeficiency Virus (HIV) in a group of young people between 15 and 24 years of age, through sexual contact without protection, considering the use of antiretroviral therapy (ART) and therapeutic failure. The model consists in a scale-free complex network that follows a power law, coupled with the immunological dynamics of each individual, that is, it considers the infection by the virus in the immune system of each HIV carrier, through a system of non-linear differential equations that govern the infection’s behavior in the immune system. Propagation of the virus in the network is modelled by taking into account information from the immunological status of each person. The study found that for a population to have high HIV prevalence, it is not necessary at the beginning of the simulation time for the virus to propagate rapidly. In addition, the study proves that with a higher number of sexual partners, there will be greater prevalence of HIV in the population and that the use of ART helps to control the propagation of the infection in the population. As an interesting result, it was also found that there is a higher number of HIV carriers who abandon ART than those who have access to it.

In this work, we propose an easy and a low cost method for the synthesis of Nitrogen-Doped Graphene NDG and its silver nanowires NW functionalization NWGN. The synthesis was performed using the improved graphene oxide method, chemical reduction of graphene oxide in the presence of caffeine as green nitrogen source and the subsequently the silver nanowires growth in the surface, by the chemical reductions salts in the presence of NG. Achieving a homogeneous growing (coating) of graphene sheets. The samples were analyzed using conventional characterization techniques: SEM-EDX, XRD, FT-IR, RAMAN, TEM, HRTEM, STEM and XPS.

The intermediate filament protein vimentin constitutes a critical sensor for electrophilic and oxidative stress. We previously showed that vimentin interacts with zinc, which affects its assembly and redox sensing. Here we have used vimentin wt and C328S, an oxidation-resistant mutant showing improved NaCl-induced polymerization, to assess the impact of zinc on soluble and polymerized vimentin by light scattering and electron microscopy. Zinc acts as a switch, reversibly inducing the formation of vimentin oligomeric species. High zinc concentrations elicit optically-detectable vimentin structures with a characteristic morphology depending on the support. These effects also occur in vimentin C328S, but are not mimicked by magnesium. Treatment of vimentin with micromolar zinc induces fibril-like particles that do not assemble into filaments, but form aggregates upon subsequent addition of NaCl. In contrast, when added to NaCl-polymerized vimentin, zinc increases the diameter or induces lateral association of vimentin wt filaments. Remarkably, these effects are absent or attenuated in vimentin C328S filaments. Therefore, the zinc-vimentin interaction depends on the chemical environment and on the assembly state of the protein, leading to atypical polymerization of soluble vimentin, likely through electrostatic interactions, or to broadening and lateral association of preformed filaments through mechanisms requiring the cysteine residue. Thus, impact of zinc on vimentin assembly and redox regulation is envisaged.

We analyzed the peak spring tidal current speeds, annual mean tidal power densities (TPD) and annual energy production (AEP) obtained from experiment 06.1, referred as the "HYCOM model" throughout, of the three dimensional (3D), global model HYCOM in an area covering the Baja California Pacific and the Gulf of California. The HYCOM model is forced with astronomical tides and surface winds alone, and therefore is particularly suitable to assess the tidal current and wind-driven current contribution to in-stream energy resources. We find two areas within the Gulf of California, one in the Great Island Region and one in the Upper Gulf of California, where peak spring tidal flows reach speeds of 1.1 meters per second. Second to fifth-generation tidal stream devices would be suitable for deployment in these two areas, which are very similar in terms of tidal in-stream energy resources. However, they are also very different in terms of sediment type and range in water depth, posing different challenges for in-stream technologies. The highest mean TPD value when excluding TPDs equal or less than 50 W/m² (corresponding to the minimum velocity threshold for energy production) is of 172.8 W/m², and is found near the town of San Felipe, at (lat lon) = (31.006 -114.64); here energy would be produced during 39.00% of the time. Finally, wind-driven currents contribute very little to the mean TPD and the total AEP. Therefore, the device, the grid, and any energy storage plans need to take into account the periodic tidal current fluctuations, for optimal exploitation of the resources.

Background. The treatment for patients with high-grade gliomas includes radiation therapy and temozolomide. However, some patients do not respond to temozolomide because they have a methylation reversal mechanism through the enzyme O6-methylguanine-DNA-methyltransferase. This biomarker has been used as a prognostic factor in patients receiving treatment with temozolomide. However, not all patients respond in the same way, which suggests the existence of other genes involved in resistance to temozolomide. Materials and Methods. A group of 31 patients with high-grade gliomas was recruited and were clinically, image pattern, and pathologically characterized. The sequencing of 324 genes related to different types of cancer was performed to detect mutations. Subsequently, a statistical analysis was conducted to determine the mutated genes that were most related to resistance to treatment. Results. The genes related to the second relapse of patients with high-grade glioma after the use of temozolomide according to Stupp protocol and metronomic dose were PIK3C2B, KIT, ERBB3, and MLH1. Conclusions. Considering the results obtained, we suggest that the mutations in the four genes and the methylation of the gene promoter that codes for MGMT protein could be related to the clinical evolution of patients with high-grade gliomas and its response to treatment with temozolomide.

The measures for tackling the COVID-19 may shrink the global GDP by approximately 6% in 2020, the deepest post-war recession. As a result, the global energy demand declined by 3.8% in the first quarter of 2020. Concerning fossil fuels, this conjuncture reduced the demand drastically and collapsed the prices to historic levels. Despite the general market disruptions, renewable energy sources (RES) seem to be more resilient to the crisis because they are the only sources that will grow in demand in 2020, driven by priority dispatch. The RES´s significant growth in cumulative installed capacity in the last two decades and the significant cost reductions of RES and energy storage technologies are positive signs towards better market conditions for the global energy transition. Currently, the crisis is seen by international agencies and transition scholars as an opportunity to advance a renewable-based energy transformation. Nevertheless, this article aims at caution about another possibility: if societal changes are not urgently implemented, the crisis may weaken the global energy transition. This article examines this last possibility from a three-level perspective: 1) post-COVID economic recovery, 2) low oil and natural gas prices and competitiveness of alternative sources and, 3) reorganization of the world energy market and the OPEC+. This paper exists to stimulate debate.

The European mink (Mustela lutreola) is one of Europe's most endangered species, and it is on the brink of extinction in the Iberian Peninsula. The species' precarious situation requires the application of new ex-situ conservation methodologies that complement the existing ex-situ and in-situ conservation measures. Here, we report for the first time the establishment of a biobank of European mink mesenchymal stem cells (emMSC) and oocytes from specimens found dead in the Iberian Peninsula, either free or in captivity. New emMSC lines were isolated from different tissues: bone marrow (emBM-MSC), oral mucosa (emOM-MSc), dermal skin (emDS-MSC), oviduct (emO-MSc), endometrium (emE-MSC), testicular (emT-MSC), and adipose tissue from two different adipose depots: subcutaneous (emSCA-MSC) and ovarian (emOA-MSC). All the eight emMSC lines showed plastic adhesion, detectable expression of characteristic markers of MSCs and, when cultured under osteogenic and adipogenic conditions, differentiation capacity to these lineages. Additionally, we were able to keep 227 Cumulus-oocyte complexes (COCs) in the biobank, 97 of which are grade I or II. The European mink MSC and oocyte biobank will allow for the conservation of the species' genetic variability, the application of assisted reproduction techniques, and the development of in vitro models for studying the molecular mechanisms of infectious diseases that threaten the species' precarious situation.

Albert Einstein, shortly after publishing his General Relativity Theory (GRT) applied it to the entire universe in a paper of 1917. Einstein assumed that such a universe was static in time and possessed a uniform distribution of matter on the largest scales, obtaining a static and finite universe of spherical spatial curvature of radius R. Although this model was refuted by Edwin Hubble's discovery of the expansion of the universe, it is still often studied as a theoretical framework for some problems, such as the twin paradox. This paper will show that Einstein's static universe model leads to a privileged frame of reference, so that any observer moving at the speed v will be able to measure speeds of light other than c depending on the direction of beam transmission. The above will refute the validity of the application to this closed and static universe of the Special Relativity Theory (SRT) proposed by Einstein in 1905 in his article . In addition, a new synchronization convention and new coordinate transformations will be deduced, the "generic" transformations, which will replace those of Lorentz. Finally, the twin paradox in this universe will be solved by making use of them.

Currently, there is an increase in the aging of the population, which represents a risk factor for many diseases, including sarcopenia. Sarcopenia involves progressive loss of mass, strength, and function of the skeletal muscle. Some mechanisms include alterations in muscle structure, reduced regenerative capacity, oxidative stress, mitochondrial dysfunction, and inflammation. The zebrafish has emerged as a new model for studying skeletal muscle aging because of its numerous advantages, including histological and molecular similarity to human skeletal muscle. In this study, we used fish of 2, 10, 30, and 60 months of age. The older fish showed a higher frailty index because of reduced locomotor activity and alterations in biometric measurements. We observed changes in muscle structure with a decreased number of myocytes and an increase in collagen with aging, corresponding to alterations in the synthesis, degradation, and differentiation pathways. These changes were accompanied by mitochondrial alterations, such as a decrease in intermyofibrillar mitochondria, increased mitochondrial damage, and reduced mitochondrial dynamics. Overall, we demonstrated a similarity in the aging processes of muscle aging between zebrafish and mammals.

Data is the most valuable asset of a company or organisation nowadays, for the management of such data there are several techniques used for the storage and analysis of these data, if the organisation chooses wrongly among the alternatives it could face a very costly problem. Based on the above information we will study a very important issue today in the business world, with the global economic growth has also grown the world of technology and therefore organizations or companies also need to move forward with firm and fast pace how business evolves; Its weaknesses, strengths and the need to always be at the forefront of technological tools we will dive into the subject of business intelligence or also known as Business Intelligence (BI), Datawarehouse and Data Mining which is nothing more than a group of applications and tools that allow you to extract, transform and load some data to get to get information and knowledge in order to make a quick decision, accurate and efficient in the organization to achieve the objectives outlined. Due to the fact that there are still companies or organisations that make blind decisions in their customer or strategic processes. In order to solve this problem we rely on data mining as an alternative to minimise risks, which can lead to major and valuable losses within an organisation. In the case of a private company where data mining is applied to study patterns of customer behaviour on their own parameters of location, consumption, etc.. And third party data. The search for information is profitable for the business administration. Data mining is applied as a tool for the development of marketing tactics in competitive production and industrial sectors. This technology attempts to help perceive the attachment of databases. Data mining works on a preferential level looking for patterns, behaviours, orders or groupings that can create a model that allows us to better understand the concept and help in decision making so organisations rely on different systems such as CRM, ERP and many others, but to move from just information to generate business intelligence must be centralised in a single place where you can run data analysis of all types to discover trends that help decision making that place can be mainly a Lake or a Warehouse.

Encouraged by the administration the gentrification process has been useful in economic terms for the reactivation of socio-cultural fabrics of historic urban spaces in decline. What was initially considered an advantage has led to the touristification of historic centres, and in turn to the alter-ation of their original use. In these settings, the demographic void caused by increasingly shunning local identity has combined with pressure from excessive tourism and the obsolescence of heritage protection bodies in charge of conservation. Given the crisis affecting the definitions of the current system, this study aims to review the envi-ronmental agents of heritage value in relation to the processes of touristification and gentrification. Data obtained from different methodologies are analysed using a multidisciplinary database, a model which enables the analysis of the relevant information from the different interacting fields. The case study focuses on the historic town centre of Seville specifically between 2015 and 2020. Elements are defined as indicators for these processes and the analysis of the case study will com-prise the main results of this research.

Monkeypox is a zoonotic illness caused by the Orthopoxvirus monkeypox virus (MPXV). Since 1970, outbreaks of MPXV have occurred in several Sub-Saharan African countries. However, from May 2022 to April 2023, recent outbreaks of MPXV occurred in several countries outside of Africa, and these cases quickly spread to over 100 non-endemic countries on all continents. Because of this, in July 2022, World Health Organization declared monkeypox a Public Health Emergency of International. MPXV disproportionately affects men who have sex with men and members of the HIV-infected population. The current strategy for control and pre-exposure prophylaxis or post-exposure prophylaxis for people at high risk is vaccination. In this context, Peru has the fourth-highest number of MPXV cases in Latin America. Because of this, in this review, we describe public health indicators in Peru and reflect on the COVID-19 pandemic so that health authorities can join forces to identify and control MPXV transmission routes.

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

Currently, a large part of the wells for agricultural use located in the state of Sonora are overexploited, which generates a high degree of saline intrusion and abandonment by nearby communities. In this paper the temperature effect on the final concentration of permeate water was evaluated through voltage and intel concentration variations in a batch electrodialysis reversal process (EDR), in order to identify optimal operating conditions with emphasis on the reduction of energy consumption and cost of desalinated water. Thirty-six samples were prepared: eighteen 2,000 mg/L total dissolved solids (TDS) samples and eighteen 5,000 mg/L TDS samples; brackish well water of 639 mg/L TDS and synthetic salt were mixed to obtain those concentrations. 3 different temperatures (25, 30, 35 °C) and 2 different voltages (10 and 20 V) were tested for each sample. The best salt removal occurred in the 20 V arrays, with 18.34% higher removal for 2,000 mg/L TDS experiments and 25.05% for 5,000 mg/L experiments (average between the 25 to 35 °C tests). Temperature positively affected EDR, especially in the experiments at 10 V voltage, where increasing 10 °C increased its efficiency by 10.83% and 24.69% for 2,000 and 5,000 mg/L TDS, respectively. Energy consumption was lower with increasing temperature (35 °C), as it decreased by 1.405% and 1.613% for 2,000 and 5,000 mg/L TDS concentrations, respectively (average between 10 and 20 V tests), decreasing the cost per m3 of water.

Iron Doped TiO₂ nanoparticles (Fe-TiO₂) were synthesized and photocatalitically investigated under high and low fluence values of UV-radiation. The Fe-TiO₂ physical characterization was performed using X-ray Powder Diffraction (XRD), Brunauer-Emmett-Teller (BET) surface area analysis, Transmission Electron Microscope (TEM), Scanning Electron Microscope (SEM), Diffuse Reflectance Spectroscopy (DRS), and X-Ray Photoelectron Spectroscopy (XPS) technique. The XPS evidenced that ferric ion (Fe³⁺) was in the lattice of TiO₂ and co-dopants no intentionally added were also present due to the precursors of the synthetic method. The Fe³⁺ concentration played a key role in the photocatalytic generation of hydroxyl radical (•OH) and estriol (E3) degradation. Fe-TiO₂ materials accomplished E3 degradation, and it was found that the catalyst with 0.3 at. % content of Fe (0.3 Fe-TiO₂) enhanced the photocatalytic activity under low UV-irradiation compared with no intentionally Fe-added TiO₂ (zero-iron TiO₂) and Aeroxide^® TiO₂ P25. Furthermore, the enhanced photocatalytic activity of 0.3 Fe-TiO₂ under low UV-irradiation may have applications when radiation intensity must be controlled, as in medical applications, or when strong UV absorbing species are present in water.

Substrate integrated waveguides reduce the losses and increase the quality factor of resonators in communication filters when compared with traditional planar technologies, while maintaining their low cost and low profile characteristics. Empty substrate integrated waveguides go one step further, removing the dielectric of the substrate. One of these transmission lines is the empty substrate integrated coaxial line (ESICL), which adds the advantage of being a two conductor structure. Thus, it propagates a TEM mode, which reduces the dispersion and the bandwith limitation of other one conductor empty substrate integrated waveguides. Continuous profile filters, at the cost of being long structures, are very easy to manufacture and design (usually no optimization is needed), and they are highly insensitive to manufacturing tolerances. In this work a simple continuous profile filter, with a stop band response, is designed for the first time in the novel ESICL technology. The influence of the design parameters on the insertion losses and fractional bandwidth is discussed. A prototype has been successfully manufactured and measured. A sensitivity analysis shows the high tolerance of the proposed stop band filter to manufacturing errors.

The North Sea Offshore Grid concept has been envisioned as a promising alternative to: 1) ease the integration of offshore wind and onshore energy systems, and 2) increase the cross-border capacity between the North Sea region countries at low cost. In this paper we explore the techno-economic benefits of the North Sea Offshore Grid using two case studies: a power-based offshore grid, where only investments in power assets are allowed (i.e. offshore wind, HVDC/HVAC interconnectors); and a power-and-hydrogen offshore grid, where investments in offshore hydrogen assets are also permitted (i.e. offshore electrolysers, new hydrogen pipelines and retrofitted natural gas pipelines). We compare these scenario results with a business as usual scenario, in which offshore wind is connected radially to the shore and no offshore grid is deployed. All scenarios are run with the IESA-NS model, without any specific technology ban and under open optimization. This paper also presents a novel methodology, combining Geographic Information Systems and Energy System Models, to cluster offshore spatial data and define meaningful offshore regions and offshore hub locations. This novel methodology is applied to the North Sea region to define nine offshore clusters taking into account offshore spatial claims, and identifying suitable areas for single-use and multi-use of space for renewable energy purposes. The scenario results show that the deployment of an offshore grid provides relevant cost savings, ranging from 1% to 4.1% of relative cost decrease (2.3 bn € to 8.7 bn €) in the power-based, and ranging from 2.8% to 7% of relative cost decrease (6 bn € to 14.9 bn €) in the power-and-hydrogen based. In the most extreme scenario (H2) an offshore grid permits to integrate 283 GW of HVDC connected offshore wind and 196 GW of HVDC meshed interconnectors. Even in the most conservative scenario (P1) the offshore grid integrates 59 GW of HVDC connected offshore wind capacity and 92 GW of HVDC meshed interconnectors. When allowed, the deployment of offshore electrolysis is considerable, ranging from 61 GW to 96 GW, with capacity factors of around 30%. Finally, we also find that, when imported hydrogen is available at 2 €/kg (including production and transport costs), large investments in an offshore grid are not optimal anymore. In contrast, at import costs over 4 €/kg imported hydrogen is not competitive.

In the vaginal ecosystem there is a symbiotic relationship between the microbiota and the host, particularly Candida spp., which are considered commensals of the vaginal mucosa. During pregnancy there is an increase in hormonal secretion that alters the vaginal microbiota and favors the development of Candida infection. Several studies have shown the increased prevalence of Candida during pregnancy, as well as its association with perinatal complications and current clinical practice guidelines recommend fluconazole as the treatment of choice during pregnancy in case of infection by Candida albicans and non-albicans Candida. However, in the Mexican population, this association has not been studied. So in this study, an intentional search for colonization by Candida spp. in pregnant women who attended the obstetric triage of the Hospital Regional de Alta Especialidad de Ixtapaluca during the period from May to October 2019, and they were followed up until the end of the pregnancy. Data on age, number of pregnancies, gestational age, body mass index, and perinatal outcomes were analyzed. Of 83 patients included in the study, yeasts corre-sponding to C. albicans (12) and C. glabrata (4) were isolated in 16. In the group of patients with Candida, the maternal age range was from 15 to 36 years old, of which 7 were adolescents and 2 with advanced maternal age, with an average of 2 gestations, the range of body mass index was from 19.3 to 42.4, of which 4 were overweight and 7 obese. Perinatal complications were observed in three patients, one presented chorioamnionitis and in two the neonates were small for gestational age. No association was found between colonization by Candida spp. and the number of preg-nancies, gestational age, body mass index or perinatal results. However, it was found that age (adolescence) may be a risk factor for the development of vulvovaginitis during pregnancy.

ADHD, one of the most prevalent diseases during childhood, we still do not know its precisely origin, although oxidative/nitrosative stress and the hypothalamic-pituitary-adrenal axis are suggested contributors. Methylphenidate, among others, is the main drug used in these patients, but its effects on relevant markers and structures remain unclear. This study, involving 59 patients diagnosed with ADHD according to DSM-5 criteria, aimed to assess changes in cortisol levels (using cortisol awakening response, CAR) and oxidative/nitrosative status with the treatment. Blood samples before and 3 months after treatment with methylphenidate were used to measure oxidative and inflammatory markers, and the endogenous antioxidant activity, while saliva samples tracked cortisol awakening response (CAR). The results show a treatment-related improvement in the redox profile, with the reduction of advanced oxidation protein products (AOPP), lipid peroxidation (LPO), and nitrite plus nitrate (NOx) levels, and the increase of the enzymatic activities of glutathione reductase (GRd) and catalase (CAT). Moreover, the area under the curve (AUC) of CAR increased significantly, indicating increased reactivity of the HPA axis. These result support by the first time the involvement of the endogenous antioxidant system in the pathophysiology of ADHD.

Gold clusters protected by 3-MBA ligands (MBA = mercaptobenzoic acid, -SPhCO2H) have attracted recent interest for their unusual structures and advantageous ligand-exchange and bioconjugation properties. Azubel et al. first determined the core structure of an Au68-complex, which was estimated to have 32 ligands (3-MBA groups). To explain the exceptional structure-composition and reaction properties of this complex, and its larger homologs, Tero et al. proposed a “dynamic stabilization” via carboxyl O-H--Au interactions. Herein, we report the first results of an integrated LC/MS analysis of unfractionated samples of gold / 3-MBA clusters, spanning the narrow size range 13.4 to 18.1 kDa. Using high-throughput procedures adapted from bio-macromolecule analyses, we show that integrated capillary HPLC-ESI-MS, based upon aqueous-methanol mobile phases and ion-pairing reverse-phase chromatography, can separate several major components from the nanoclusters mixture that may be difficult to resolve by standard native gel electrophoresis due to their similar size and charge. For each component, one obtains a well-resolved mass spectrum, nearly free of adducts or signs of fragmentation. A consistent set of molecular mass determinations is calculated from detected charge-states tunable from 3- (or lower), to 2+ (or higher). One thus arrives at a series of new compositions (n, p) specific to the Au/3-MBA system. The smallest major component is assigned to the previously unknown (48, 26); the largest one is evidently (67, 30), vs. the anticipated (68, 32). Various explanations for this discrepancy are considered. A prospective is given for the several members of this novel series, along with a summary of the advantages and present limitations of the micro-scale integrated LC/MS approach to characterize such metallic-core macro-molecules, and their derivatives.

The need to carry different items, which become an extra load, is a characteristic of trail running. The aim of this study is to determine physiological-metabolic changes produced by running with extra load. Four male well-trained trail runners completed three treadmill maximal metabolic tests carrying different loads (0% (L0), 5% (L5), and 10% (L10) of their body mass) in a weighted vest. Gasses exchange was monitored to assess ventilatory thresholds 1 (VT1), and 2 (VT2), zone of maximal fat oxidation, and peak oxygen consumption (VO2peak). Heart rate (HR), power and velocity (V) were tracked for comparing their behavior. A repeated measures ANOVA showed significant differences in V (p<.001; ηp2= 0.910) as a limitation for reaching peak velocity (Vpeak) with L10 respect to L0 (p=0.001), and L5 (p=0.011). Power expression showed differences (p=0.068; ηp2= 0.592). It tended to be greater with L10 than L0 (p=0.057), despite achieving lower V. VT2 tended to occur at different %VO2peak (p=0.069; ηp2= 0.591). L5 VT2 was reached at higher %VO2peak than L0 (p=0.062), and L10 (p=0.071). ANOVA also showed a tendency to signification for V at this point (p= 0.098; ηp2= 0.538). In conclusion, L10 seems to limit Vpeak while L5 may delay VT2 expression.

Pandemic scenario has significantly changed several factors of life, including teaching, and learning at university. The development of suitable teaching materials to support university studies is mandatory to overcome distance learning difficulties and improve traditional teaching methodologies. This work explains a novel method for the preparation of teaching materials for medical sciences, but also plausible for other learning fields. An encephalon was extracted and prepared by using this methodology for teaching purposes. More than 200 students evaluated several factors of the material prepared this way, indicating a better understanding (up to 80%) of theoretical contents related to this human section, together with a high usability and good physical appearance

This research work is concerned in the exergy analysis of the continuous-convection drying of onion. The influence of temperature and air flow rate was studied in terms of exergy parameters. The energy and exergy balances were carried out taking into account the onion drying chamber. Its behaviour was analysed based on exergy efficiency, exergy loss rate, exergetic improvement potential rate and sustainability index. The exergy loss rates increase with the temperature and air flow rate augmentation. Exergy loss rate is augmented at higher drying air temperatures and flow rates because the overall heat transfer coefficient increase. On the other hand, the exergy efficiency increases with the air flow rate augmentation. This behavior is due to the energy utilization was improved because the most amount of supplied energy was utilized for the moisture evaporation. However, the exergy efficiency decreases with the temperature augmentation due to the free moisture is less, then, the moisture begins diffusing from the internal structure to the surface. The exergetic improvement potential rate values show that the onion drying process presents a high potential to improve the exergy efficiency. The sustainability index of the drying chamber varied from 1.9 to 5.1. To reduce the environmental impact of the process, the parameters must be modified in order to ameliorate the exergy efficiency of the process.

In most organizations there is an information system where data is recorded regarding events, activities, times, and variables associated with the execution of all organizational processes; this information is generally not used to its maximum potential, limited only to the registration of processes. With process mining, a field of engineering research, responsible for the design of processes through mining algorithms, it is possible to characterize bottlenecks, reprocessing, and opportunities for improvement in organizational processes. In this article, the construction of the collection and billing process is carried out in a case study of the Colombian Pharmaceutical sector supported by process mining and business intelligence. The objective of this research is oriented to the construction of the real process of a case study of the pharmaceutical sector in Colombia supported by the alpha mining algorithm, within the framework of process mining and business intelligence to facilitate decision-making at an organizational level. The result of this research is the proposal of a methodology to implement process mining in organizations in the pharmaceutical sector in Colombia supported by the Design Science Research (DSR) methodology and the construction of the real process in the billing and collection case study in the pharmaceutical sector supported by process mining, business intelligence is also used to complement the points of improvement of the accounting process in the case study. In conclusion, the artifact built in DSR shows a rigorous methodology from obtaining data, and types of documents that make up the knowledge base to proceeding to the application of the alpha mining algorithm that built the real billing and collection process of the case study, in which points of reprocessing and activities susceptible to improvements in the case study are evident. As a contribution, this article develops an alternative approach that contributes to the knowledge gap related to the actual construction of billing and collection processes in organizations, which generates an impact an alternative paradigm in the construction of organizational processes, by proposing a methodology that Builds a billing and collection process through process mining complemented by business intelligence.

The aim of this study was to assess the effect of added cultures of probiotic lactic acid bacteria on physicochemical, textural, and sensory characteristics of fresh cheese as well as their viability. Probiotic strains Lactobacillus acidophilus and L. rhamnosus were evaluated at two inoculation times (before the renneting and salting processes) following a factorial treatment arrangement. The bacterial count (log CFU g-1), acidity determination (% lactic acid), pH and percentage of syneresis were evaluated at 0, 1, 7, 14 and 21 days of refrigerated storage (4–5 °C). The texture profile analysis and an extended preference test were carried out at 21 days of storage. At the end of storage, fresh cheeses containing L. rhamnosus, added prior to the renneting process, had similar acidity values (0.18% lactic acid), pH (5.36) and percentage of syneresis (4.71%) compared to those for the cheeses without probiotics or control. Excluding adhesiveness, no differences were observed in texture profile parameters among the assessed cheeses. The fresh cheese supplemented with L. rhamnosus before the renneting process had a microorganism count greater than 6 logarithmic cycle/g, and the highest preference among treatments. The results from this study suggest that fresh cheese can be an excellent matrix for probiotic microorganisms, in particular L. rhamnosus.

Malassezia is a lipid-dependent genus of yeasts known for being an important part of the skin mycobiota. These yeasts have been associated in the development of skin disorders and cataloged as a causal agent of systemic infections under specific conditions, making them opportunistic pathogens. Little is known about the host-microbe interaction of Malassezia spp., and unraveling this implies the implementation of infection models. In this mini review we present different models that have been implemented in the fungal infections study with greater attention in Malassezia spp. infections. These models range from in vitro (cell cultures and ex vivo tissue), to in vivo (murine models, rabbits, guinea pigs, insects, nematodes, and amoebas). We additionally highlight the alternative models that reduce the use of mammals as model organisms, which have been gaining importance in the study of fungal host-microbe interactions. This is due to the fact that these systems have shown to have reliable results, which correlate with those obtained from mammalian models. Example of alternative models are Caenorhabditis elegans, Drosophila melanogaster, Tenebrio molitor, and Galleria mellonella. These are invertebrates that have been implemented in the study of Malassezia spp. infections in order to identify differences in virulence between Malassezia species.

From the various perspectives of Machine Learning (ML) and the multiple models used in this discipline, there is an approach aimed at training models for the Early Detection (ED) of anoma-lies. The early detection of anomalies is crucial in multiple areas of knowledge since identifying and classifying them allows for early decision-making and provides a better response to mitigate the negative effects caused by late detection in any system. This article presents a literature review to examine which machine learning models (MLM) operate with a focus on ED in a multidisci-plinary manner and specifically how these models work in the field of fraud detection. A variety of models were found, including Logistic Regression (LR), Support Vector Machines (SVM), De-cision Trees (DT), Random Forests (RF), Naive Bayesian Classifier (NB), K-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Extreme Gradient Boosting (XGB), among others. It was identified that MLMs operate as isolated models, categorized in this article as Single Base Models (SBM) and Stacking Ensemble Models (SEM). It was identified that MLMs for ED in multiple areas under SBM and SEM implementation achieved accuracies greater than 80% and 90%, respectively. n fraud detection, accuracies greater than 90% were reported by the authors. The article concludes that MLMs for ED in multiple applications, including fraud, offer a viable way to identify and classify anomalies robustly, with a high degree of accuracy and precision. MLMs for ED in fraud are useful as they can quickly process large amounts of data to detect and classify suspicious transactions or activities, helping to prevent financial losses.

Nonlinear optimization (NOPT) is a meaningful tool for solving complex tasks in fields like engineering, economics, and operations research, among others. However, NOPT has problems when it comes to dealing with data variability and noisy input measurements that lead to incorrect solutions. Furthermore, nonlinear constraints may result in outcomes that are either infeasible or suboptimal, such as non-convex optimization. This paper introduces a novel regularized physics-informed neural network (RPINN) framework as a new NOPT tool for both supervised and unsupervised data-driven scenarios. By using custom activation functions and regularization penalties in an artificial neural network (ANN), RPINN can handle data variability and noisy inputs. Besides, it uses physics principles to build the network architecture, computing the optimization variables based on network weights and learned features. In addition, it uses automatic differentiation training to make the system scalable and cut down on computation time through batch-based back-propagation. The test results for both supervised and unsupervised NOPT tasks show that our RPINN can provide solutions that are competitive compared to state-of-the-art solvers. In turn, RPINN’s robustness against noisy input measurements makes it particularly valuable in environments with fluctuating information. Additionally, RPINN’s ANN-based foundation offers significant flexibility and scalability.

The agricultural sector is undergoing a revolution that requires sustainable solutions to the challenges that arise from traditional farming methods. To address these challenges, technical and sustainable support is needed to develop projects that improve crop performance. This study focuses on the onion crop and the challenges presented throughout its phenological cycle. Aerial monitoring using unmanned aerial vehicles (UAV) and digital image processing were used to identify patterns in the onion crop, including humid areas, weed growth, vegetation deficits, and decreased harvest performance. An algorithm was developed to identify the patterns that most affected crop growth, as the average local production reported was 40.166 ton/ha, but only 25.00 ton/ha was reached due to blight caused by constant humidity and limited sunlight. This resulted in the death of leaves and poor development of bulbs, with 50% of the production being of medium size. It is estimated that approximately 20% of the production was lost due to blight and unfavorable weather conditions.

The bean weevil (Acanthoscelides obtectus (Say.)) is one of the main pests of stored beans in the world. Heterogeneous Inbreed Families (HIF) Population of Near Isogenic Lines (NILs) could be an exceptional strategy to study the inheritance of the resistance against A. obtectus. We developed a HIF population of NILs of R-bufa-80-12 (Phaseolus vulgaris) to study the inheritance related to bean weevil resistance and to search NILs with high resistance to the pest within the HIF population. The objective of this research was to study the inheritance in a HIF population and to identify the best lines to provide weevil resistance in bean breeding for commercial genotypes that could reduce pesticide applications. To achieve this objective, we developed a set of 148 NILs which were near-homozygous in the genome, except in the region under study. The HIF were evaluated in two environments under natural infestation with A. obtectus in free choice bioassays in a warehouse highly infested. The population showed wide variability for the traits studied, from 17.2 to 29.2 g for 100 seed weight, 0.0-0.8 for consumption in grams, 2.0-30.0 for consumption in percent and 1.2-9.6 for preference (number of adults in the bottle to the end of the experiments. The heritabilities for resistance traits were from very low to low 0.0 to 0.19. The heritability for 100 seed weight was the highest, with a value of 0.90. All traits studied in this research have a normal distribution, so they are considered to be quantitatively inherited. However, a great variability was found for the traits studied, which allows selecting lines with a high level of resistance within the R-bufa-80-12 HIF population. All traits studied in present research are of quantitative inheritance. The best lines of the HIF population for resistance to A. obtectus were the Line-45, Line-129, Line-124, Line-108 and Line-47.

This research explored the influence of spatiotemporal variations in phreatic levels and salinity on the patterns and interactions of soil mesofauna communities in a tropical urban coastal wetland. It delineated significant variations in phreatic levels and salinity, with distinct regimes characterizing different habitats and hydroperiods. A total of 120 mesofauna morphotypes across 42 taxa were identified, revealing habitat differences and similarities, and the ecosystem biodiversity. Moderate correlations were established between phreatic levels, salinity, and mesofauna richness and abundance, with habitat type and phreatic level emerging as significant predictors in the regression model. Our findings indicate that shallow phreatic levels in conjunction with oligohaline salinity conditions foster a more favorable abiotic environment, thereby promoting increased biodiversity. The study underscores the dynamic and adaptive nature of mesofauna communities in response to changing environmental conditions, offering valuable insights for effective costal urban wetland management, particularly in the context of multiple stressors such as global and regional climate change, sea level rise, and human activities. The bio-sensor capacity of soil mesofauna emerges as a vital tool for monitoring and facilitating adaptive ecosystem management, thereby ensuring their long-term health and sustainability.

A study to produce cellulose nanofibrils (CNF) from Kraft cellulose pulp, an optimal enzyme mixture, was defined using a centroid simplex mixture design. The enzyme blend contains 69% endoglucanase and 31% exoglucanase. The central composite rotational design (CCRD) optimized the CNF production process by achieving a higher crystallinity index. It thus corresponded to a solid loading of 15 g/L and an enzyme loading of 0.974. Using the Segal formula, the crystallinity index (CrI) of CNF was determined by X-ray diffraction to be 80.87%. The average diameter of nanocellulose fibers measured by scanning electron microscopy between 550 - 600 nm for the CNF prepared by enzymatic hydrolysis and between 250 - 300 nm for the CNF produced by enzymatic hydrolysis with the optimal enzyme mixture followed by ultrasonic dispersion. Finally, synergistic interactions between the enzymes involved in nanocellulose production were demonstrated, with Colby factor values greater than one.

We explore the use of industrial sources of silicon and surfactant for obtaining low-cost MCM-41 materials and evaluate their performance as CO₂ adsorbents. All of them presented a high specific surface area with different structural characteristics and textural properties. The template was removed by using thermal treatments in an air atmosphere or a washing process. Preservation of silanol groups proved to be more effective under washing or mild thermal treatment conditions with the advantage of their lower cost and environmental benefit. Surface reactivity against CO₂ was enhanced by anchoring APTS to silanol groups through wet grafting. All amino-functionalized materials showed a performance as CO₂ adsorbents comparable to those reported in the literature. Samples with a higher concentration of silanol groups showed better performance. Our studies indicate that adsorbed CO₂ is retained at least up to 50°C, and the presence of aminopropyl groups is a key issue in CO₂ chemisorption on the MCM-41 surface. The chemisorbed gas at very low pressures points to the potential use of these materials for CO₂ storage.

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.

This study focused on the impact of the treatment with the hypomethylating agent 5-Azacitidine on the redox status and inflammation in 24 MDS patients. Clinical and genetic features of MDS patients were recorded and peripheral blood samples were used to determine the activity of the endogenous antioxidant defense system (superoxide dismutase, SOD, catalase, CAT, glutathion peroxidase, GPx, and reductase, GRd, activities), markers of oxidative damage (lipid peroxidation, LPO, and advanced oxidation protein products, AOPP). Moreover, pro-inflammatory cytokines and plasma nitrite plus nitrate levels as markers of inflammation, and CoQ10 plasma levels, were also measured. Globally, MDS patients showed less redox status in terms of a reduction in the GSSG/GSH ratio and in the LPO levels, and increased CAT activity compared with healthy subjects, with not changes in SOD, GPx and GRd activities, and AOPP levels. When analyzed the evolution from early- to advanced stages of the disease, the GPx activity, GSSG/GSH ratio, LPO and AOPP increased, with a reduction in CAT. GPx changes were related with the presence of risk factors such as high-risk IPSS-R or mutational score. Besides, there was an increase in IL-2, IL-6, IL-8 and TNF-α plasma levels, with further increase of IL-2 and IL-10 from early to advanced stage of the disease. However, we did not observe any association between inflammation and oxidative stress. Finally, 5-azacitidine treatment generates oxidative stress in MDS patients, without affecting inflammation levels, suggesting that oxidative status and inflammation are two independent processes.

Federated learning techniques aim to train and build machine learning models based on distributed datasets across multiple devices, avoiding data leakage. The main idea is to perform training on remote devices or isolated data centers without transferring data to centralized repositories, thus mitigating privacy risks. Data analytics in education, in particular learning analytics, is a promising scenario to apply this approach to address the legal and ethical issues related to processing sensitive data. Indeed, given the nature of the data to be studied (personal data, educational outcomes, data concerning minors), it is essential to ensure that the conduct of these studies and the publication of the results provide the necessary guarantees to protect the privacy of the individuals involved and the protection of their data. In addition, the application of quantitative techniques based on the exploitation of data on the use of educational platforms, student performance, use of devices, etc., can account for educational problems such as the determination of user profiles, personalized learning trajectories, or early dropout indicators and alerts, among others. This paper presents the application of federated learning techniques to two learning analytics problems: dropout prediction and unsupervised student classification. The experiments allow us to conclude that the proposed solutions achieve comparable results from the performance point of view with the centralized versions, avoiding centralizing the data for training the models.

Background: Although no specific treatment for COVID 19 has been proven effective yet, some drugs with in vitro potential against SARS-CoV-2 virus have been proposed for clinical use. Hydroxychloroquine has in vitro anti-viral and immunomodulatory activity, but there is no current clinical evidence of its effectiveness on the outcome of the disease. Methods: We enrolled all 18-85 years old inpatients from Central Defense Hospital, Madrid, Spain, who were hospitalised due to COVID-19 and had a definitive outcome (either dead or discharged). We used a statistical survival analysis. Results: We analysed 220 medical records. 166 patients met the inclusion criteria. 48,8 % of patients not treated with HCQ died, versus 22% in the group of hydroxychloroquine (p=0,002). According to clinical picture at admission, hydroxychloroquine increased the mean cumulative survival in all groups from 1,4 to 1,8 times. This difference was statistically significant in the mild group. Conclusions: in a cohort of 166 patients between 18 to 85 years hospitalised with COVID-19, hydroxychloroquine treatment with an initial loading dose of 800mg improved patient survival when admitted in early stages of the disease. There was a non-statistically significant trend towards survival in all groups, which will need to be clarified in subsequent studies.

Abstract: This study aims to analyze the physico-mechanical properties and dynamic models of tissue-simulating hydrogels, specifically the photoacoustic (PA) response signals, by varying the concentrations of polyvinyl alcohol (PVA) and molecular weight (MW). A state space model (SSM) is proposed to study the PVA hydrogels to retrieve the PA-related signal's damping ratio and nat-ural frequency. Nine box-shaped PVA hydrogels containing saline solution were used, with five concentrations of PVA (7, 9, 12, 15, 20%) for MW1 and four for MW2. The results indicated that the concentration of PVA and MW played an important role in the PA wave's amplitude, arrival time, and speed of sound over the hydrogels. The SSM parameters showed that increasing PVA and MW concentrations improved the hydrogels' ability to absorb and transfer energy under the PA effect. These parameters were also found to be correlated with density and modulus of elasticity. Addi-tionally, the concentrations of PVA and MW affected the absorption and optical scattering coeffi-cients. The physical-mechanical properties, including porosity, density, and modulus of elasticity, improved as the concentration of PVA and MW increased. The ultimate goal of this study is to develop hydrogels as phantoms that can be used for tissue simulation and imaging.

The objective was to analyze the effects of adding anthocyanin delphinidin-3-O-sambubioside and cyanidin-3-O-sambubioside of Hibiscus sabdariffa L. in animal diets. Scientific articles published before 2021 in clinics, pharmacology, nutrition, and animal production were included. The grains/concentrate, metabolic exigency, and caloric stress contribute to increasing the reactive oxygen species (ROS); the excess of ROS unbalance the oxidants and antioxidants. Cyanidin-3-O-sambubioside and delphinidin-3-O-sambubioside have antioxidant, antibacterial, antiviral, and anthelmintic activities. In the rumen, anthocyanin might show interactions and/or synergisms with substrates, microorganisms, and enzymes which could reduce the fiber degradability, but increase the potential methane (CH4) emissions; since anthocyanin interferes in the biohydrogenation of fats, they increase the fat milk and meat quality. Anthocyanins reduce plasma oxidation and deposit in tissues, increasing the milk and meat antioxidant activities. Cyanidin-3-O-sambubioside and delphinidin-3-O-sambubioside act as inhibitors of the angiotensin-converting enzyme (ACEi) and rennin expression which may improve milk yield (there is not enough evidence in ruminants, though). Polyphenols affect the reproductive potential. Sub products of HS contain as many amounts of polyphenols as calyces, and their inclusion in diets would positively affect the average daily gain and fat meat quality. Including HS in ruminant diets can improve the meat and milk quality.

This research proposes an algorithm to sign messages using the ElGamal asymmetric cryptosystem, called: Digital signature algorithm based on ElGamal, Diffie-Hellman protocol and the number π (DSAπ). This proposal has a high level of security like the DSA standard, in addition, execution times are reduced in relation to it. The Diffie-Hellman protocol and the number π were used in the construction of the digital signature algorithm in conjunction with the Hash-Sha-512 function. Some experiments are presented to provide evidence that the bits on the right side of the decimal point of π appear randomly, such as: a color image was constructed of a string of consecutive bits chosen at random, of the number π. Subsequently, parameters such as: entropy, correlation, discrete Fourier transform, goodness-of-fit test χ2 were evaluated. It is mentioned that an S-box 8×8 is involved in the signature. The sensitivity of the signature was measured, that is, when small changes are made to the sender’s private key, or small changes to the message. Finally, an image was constructed using the signatures of random texts, and subsequently the randomness of its pixels was obtained, to verify that there is no relationship between the different signatures.

Chimeric antigen receptor (CAR)-T cell-based therapies have achieved substantial successes against B-cell malignancies, what has led to a growing scientific and clinical interest on extending their use to solid cancers. However, results for solid tumours have been limited up to now, in part due to the immuno-suppressive tumour microenvironment, that is able to inactivate CAR-T cell clones. In this paper we put forward a mathematical model describing the competition of CAR-T and tumour cells, accounting for their immunosuppressive capabilities. Using the mathematical model, we show that the use of large numbers of CAR-T cells targeting the solid tumour antigens could overcome the cancer immunosuppressive potential. To achieve such high levels of CAR-T cells we propose and study computationaly, the manufacture and injection of CAR-T cells targeting two antigens: CD19 and a tumour-associated antigen. We study in-silico the resulting dynamics of the disease after the injection of this product and find that the expansion of the CAR-T cell population in the blood and lymphopoietic organs could lead to the massive generation of an army of CAR-T cells targetting the solid tumour, and potentially overcoming its inmune suppression capabilities. That strategy could benefit from the combination with PD-1 inhibitors and of low tumour loads. Our computational results provide a theoretical support for the treatment of different types of solid tumours using T-cells engineered with combination treatments of dual CARs with on- and off-tumour activity and anti-PD1 drugs after completion of classical cytoreductive treatments.

Frontotemporal lobar degeneration (FTLD) belongs to a heterogeneous group of highly complex neurodegenerative diseases and represents the second cause of presenile dementia in individuals under 65. Frontotemporal-TDP is a subgroup of frontotemporal dementia characterized by the aggregation of abnormal protein deposits, predominantly transactive response DNA-binding protein 43 (TDP-43), in the frontal and temporal brain regions. These deposits lead to progressive degeneration of neurons resulting in cognitive and behavioral impairments. Limbic age-related encephalopathy (LATE) pertains to age-related cognitive decline primarily affecting the limbic system which is crucial for memory, emotions, and learning. Though distinct, emerging research suggests a potential overlap in pathogenic processes, with some cases of limbic encephalopathy displaying TDP-43 pathology. Genetic factors play a pivotal role in both disorders. Mutations in various genes, such as progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72), have been identified as causative in frontotemporal-TDP. Similarly, specific genetic variants have been associated with an increased risk of developing LATE. Understanding these genetic links provides crucial insights into disease mechanisms and the potential for targeted therapies.

Apple snails of the genus Pomacea (Mollusca: Caenogastropoda: Ampullariidae) are native to the Neotropics and exhibit high species diversity. They hold cultural and ecological significance, serving as an important protein source in Peru. However, this genus has also received broad interest worldwide due to its invasive capacity, especially in Southeast Asia, where some species such as Pomacea canaliculata (Lamarck, 1822) and P. maculata Perry, 1810 are considered significant pests. Consequently, most genetic studies have focused almost exclusively on these invasive species. In contrast, few efforts have been made to understand the evolutionary relationships of the South American native species, especially at the genomic level. In this study, we assembled and annotated the mitochondrial genome of two Pomacea species native to the Peruvian Amazon: Pomacea reevei Ampuero & Ramírez, 2023 and P. aulanieri (Deville & Huppé, 1850). Through a comprehensive comparison with available mitogenomes on NCBI, we found that the length and organization of these mitogenomes fall within the range of what is currently known in Pomacea. Comparisons between these mitogenomes with those previously published revealed differences in the overlapping of adjacent genes, the size of certain protein-coding genes (PCGs) and the secondary structure of some tRNAs which are consistent with the phylogenetic relationships between these species. These findings provide valuable insights into the systematics and genomics of the genus Pomacea.

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

Background: Acute ischemic stroke is among the main causes of mortality worldwide; a rapid and opportune diagnosis is crucial to improve a patient's outcome. MicroRNAs are quite useful for a rapid and accurate diagnosis.Methods: We perform both structural networks approach and a meta-analysis (using a random-effect model to evaluate the heterogeneity and risk bias, according to the PRISMA statement) to analyze the feasibility to develop a microRNA-based biomarker panel for an opportune AIS diagnosis. Results: Structural networks identify a set of eight miRNAs (miR-16, miR-124-3p, miR-484, miR-15a, miR-4454, miR-107, miR-125b-5p and miR-320b) as preliminary microRNA-based biomarker panel, from these only three microRNAs are significantly associated with the main risk factors of AIS, (miR-107: hypertension, 95% CI 9.74-53.24 p<0.0001, type 2 Diabetes mellitus, 95% CI 2.18-19.26); p=0.0008; miR-16 hypertension, 95% CI 1.26-3.56 p=0.0046, smoking, 95% CI 1.07-3.54 p=0.0277; and miR-15a hypertension, 95% CI 1.26-3.56 p=0.0046; smoking, 95% CI 1.07-3.54 p=0.0277). However, the meta-analysis reveals that data is highly heterogeneous and biased; and only microRNAs isolated from plasma samples and further processed in microarrays are the most reliable to distinguish AIS patients.Conclusions: Together our results show that although there are some miRNAs that seem to be associated with AIS, we are still far to develop a miRNA-based biomarker for AIS diagnosis and it is necessary to harmonize the protocols, results and include more populations for further studies otherwise we will remain throwing punches in the dark.

Solar radiation corresponds to fundamental parameters for solar photovoltaic (PV) technology. Reliable solar radiation prediction became valuable to design solar PV systems, performance, operatively efficient planning, safety operation, grid dispatch and financial characteristics. However, high quality ground-based solar radiation measurements are scarce, especially for very short-term time horizon. Most of the existent studies trained the machine learning (ML) model used dataset with time horizon of 1-hour or day, very fewer studies have been reported using a dataset with a 1-mitute time horizon. In this study, a comprehensive evaluation of nine ensemble learning algorithms (ELA) is performed to estimate the solar radiation in Santo Domingo with a 1-minute time horizon dataset collected from a local weather station. The ensemble learning evaluated included seven homogeneous ensembles; Random Forest (RF), Extra Tree (ET), Adaptive Gradient Boosting (AGB), Gradient Boosting (GB), Extreme Gradient Boosting (XGB), Light Gradient Boosting (LGBM), Histogram-based Gradient Boosting (HGB) and heterogeneous ensemble named as Voting and Stacking. RF, ET, GB, HGB were combined to develop Voting and Stacking and Linear Regression (LR) was adopted in the second layer of the Stacking. Five technical metrics, Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Coefficient of Determination (R2) were used as criteria to determine the prediction quality of the developed ensemble algorithms. Comparison of the results indicates that the HGB algorithm offers superior prediction performance among the homogeneous ensemble learning and overall, the Stacking provides the best accuracy with metric values of MSE=3218.27, RMSE= 56.73, MAE=29.87, MAPE=10.60, R2=0.964.

Several sun models suggest the radioactive balance where the concentration of greenhouse gases and the albedo effect are related to the Earth's surface temperature. There is a considerable increment of greenhouse gases due to anthropogenic activities. Climate change correlates with this alteration in the atmosphere and an increase in surface temperature. Efficient forecasting of climate change and its impacts of 1.5°C global warming above pre-industrial levels could be helpful to respond to the threat of c.c. and develop sustainably. Many studies have predicted the temperature change in the coming years. The global community has to create a model that can realize good predictions to ensure the best way to deal with the warming. Thus, we propose a finite-time thermodynamic (FTT) approach in the present work. The FTT can solve problems such as the faint young sun paradox. In addition, we use different machine learning models to evaluate our method and compare the experimental prediction and results.

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 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.

The objective of this study is to evaluate the effects of the 3D point cloud density derived from unmanned aerial vehicle (UAV) photogrammetry and structure from motion (SfM) and multi-view stereopsis (MVS) techniques, the interpolation method for generating a digital terrain model (DTM), and the resolution (grid size) of the derived DTM on the accuracy of estimated heights in small areas, where a very accurate high spatial resolution is required. A UAV-photogrammetry project was carried out on a bare soil of 13 × 13 m with a rotatory wing UAV at 10 m flight altitude (equivalent ground sample distance = 0.4 cm). The 3D point cloud was derived, and five sample replications representing 1, 2, 3, 4, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80 and 90% of the original cloud were extracted to analyze the effect of cloud density on DTM accuracy. For each of these samples, DTMs were derived using four different interpolation methods (Inverse Distance Weighted (IDW), Multiquadric Radial Basis Function (MRBF), Kriging (KR), and Triangulation with Linear Interpolation (TLI)) and 15 DTM grid size (GS) values (20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0.67, 0.5, and 0.4 cm). Then, 675 DTMs were analyzed. The results showed, for each interpolation method and each density, an optimal GS value (most of the cases equal to 1 cm) for which the Root Mean Square Error (RMSE) is minimum. IDW was the interpolator which yielded best accuracies for all combination of densities and GS. Its RMSE, considering the raw cloud, was 1.054 cm. The RMSE increased 3% when a point cloud with 80% extracted from the raw cloud was used to generate the DTM. When the point cloud included the 40% of the raw cloud, RMSE increased 5%. For densities lower than 15%, RMSE increased exponentially (45% for 1% of raw cloud). The grid size minimizing RMSE for densities of 20% or higher was 1 cm, which represents 2.5 times the ground sample distance of the pictures used for developing the photogrammetry project.

In this work epitaxial Au islands have been grown on epitaxial α-Fe2O3 thin film by pulsed laser deposition on SrTiO3(111) substrate. Both Au and α-Fe2O3 layer show an island-type growth with an average particle size of 40 and 62 nm, respectively. The crystallographic coupling of lattices is confirmed with a rotation of 30º between the in-plane crystallographic axes of α-Fe2O3(0001) structure and those of SrTiO3(111) substrate and between the in-plane crystallographic axes of Au(111) and those of α-Fe2O3(0001) structure. α-Fe2O3 is the only phase of iron oxide identified before and after its functionalization with Au nanoparticles. In addition, its structural character-istics are also preserved after Au deposition, with minor changes at short-range order. The func-tional character of the complex systems as gas sensor has been proven at room temperature. Con-ductance measurements of Au(111)/α-Fe2O3(0001)/ SrTiO3(111) system show that the incorpora-tion of Au islands on top of the α-Fe2O3(0001) layer induces an enhancement of the gas-sensing ac-tivity for CO and CH4 gas in comparison to a bare α-Fe2O3(0001) layer grown on SrTiO3(111).

X-ray crystallographic and theoretical charge density data for a series of compounds [(Co(Ts3tren))M(Co(Ts3tren))] (M = Mg, Ca, Sr and Ba) is examined. The crystal structures are isostructural and the alkaline earth metal ions have the same arrangement of donor oxygen atoms despite the large variation in ionic radii. The isomorphism of these molecules is surprising and a theoretical examination of the electronic structures, with the different metal ions along the series, provides detailed insight into their stabilities. The theoretical and experimental data are consistent and agree well. The local properties of the Co(II) ion and its donor atoms are relatively independent of the alkali earth metal.

Implementing the methodology of clinical simulation in the nursing degree course is a necessity in the European framework of higher education to acquire competences. The objectives of this research were to evaluate the strategies and techniques used during the simulations, identify the contents learned, and determine which of them are transferred to the nursing practice. We performed an observational, descriptive, and cross-sectional study from the nursing students’ perspective during the 2020-21-year course. On the one hand, our results show that the DASH scale helped us to obtain an internal validity of the simulations obtaining a mean score of 6.61 out of 7. On the other hand, the Ad Hoc scale, based on the competences were acquired in the simulations were transferred to the care practices. In conclusion, it is possible to improve care practices by integrating knowledge through clinical simulations.

Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012-2022), highlighting both the evolution of this field and its integration to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, the review sheds light on the potential implications of WBT for the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation with the EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process.

Iapetus, a Saturn moon, shows the most differentiated albedo dichotomy of the Solar System. The dark leading side has a lower albedo than the bright trailing side. Spectral data on the visible light reveal the existence of two types of materials on the surface. The darkening in the leading side is thought to be originated by the presence of organic material and carbonaceous compounds on surface, while the trailing side is covered by water ice due to migration processes from the dark side. On airless bodies like Iapetus, the surface escape speed is greater than the speed of water molecules, resulting in the retention of a H2O atmosphere that allows some species to get diffused through it. Here, there were performed simulations of the evolution of the surface temperature for each of the two hemispheres of Iapetus. The results showed a slow yet steady increment of temperatures for both sides, with a steeper slope for the dark hemisphere. It was also simulated how much energy budget can be accumulated in both sides and its consequences. Finally, we calculated the diffusion coefficients for ammonia, methane, and water ice. The results let us infer how these compounds could evolve over time.

Coronavirus disease 2019 (COVID-19) fatal outcomes have been associated with multiple cardiovascular risk factors. In new epidemic areas, such as Latin America, there is a lack of studies about this. Here, we evaluated those factors in a retrospective cohort of patients in a national reference hospital of Lima, Peru. Design. A retrospective cohort observational study was done. For this study, information was obtained from clinical records of the hospital for the cases that were laboratory-diagnosed and related, during March 6^th and April 30^th, 2020. rRT-PCR was used for the detection of the RNA of SARS-CoV-2 following the protocol Charité, Berlin, Germany, from nasopharyngeal swabs at the National Institute of Health. Calculation of the odds ratio (OR) with the respective 95% confidence interval (95% CI) was done, also logistic regression for adjusted OR (multivariate) was done. Values of p < 0.05 were considered significant for all analyses. Results. One hundred six hospitalized patients were evaluated. The mean age of patients was 61.58 years (SD 16.81). Cardiovascular risk factors among them were hypertension (46.2%), diabetes (28.3%), and obesity (28.3%), among others. Fifty-six patients died (52.8%). Mortality associated factors at the multivariate analysis were arterial hypertension (OR=1.343, 95% 1.089-1.667), myocardial injury (OR=1.303, 95% 1.031-1.642), and mechanical ventilation (OR 1.262, 95% 1.034-1.665), as associated factors. Conclusion. As observed in other regions of the world, cardiovascular risk factors represent a significant and independent threat to be considered in patients with COVID-19. Further studies and interventions in Peru and Latin America are expected.

Detailed information about graft material characteristic is crucial to evaluate their clinical outcomes. The present study evaluates the physicochemical characteristics of two xenografts manufactured on an industrial scale deproteinized at different temperatures (non-sintered and sintered) in accordance with a protocol previously used in sinus lift procedures. It compares how the physico-chemical properties influence the material performance in vivo with a histomorphometric study in retrieved bone biopsies following maxillary sinus augmentation, in 10 clinical cases. X-ray diffraction analysis revealed typical structure of hydroxyapatite for both materials. Both xenografts are porous and exhibit intraparticle pores. Strong differences were observed in terms of porosity, cristallinity, and calcium/phosphate. Histomorphometric measurements on the bone biopsies showed statistically significant differences. The physicochemical assessment of both xenografts in accordance with the protocol developed at industrial scale confirmed that these products present excelent biocompatibilitity, with characteristics similar to natural bone. The sintered HAs xenograft exhibit higher osteoconductivity although were not complete resorbable (30.80±0.88% residual material). On the other hand, the non-sintered HAs xerograft induced about 25.92±1.61% of new bone and almost complete degradation after 6 months implantation. Differences in physico-chemical characteristics found between the two HAs xenograft determine different behavior of this material.

This study explored intraindividual multidimensional profiles integrating psychosocial factors, namely, body image and satisfaction, weight-related self-stigma, positivity, and happiness, and behavioural-lifestyle factors, namely, adherence to a healthy diet, among Spanish adults with overweight or obesity. We further aimed to investigate the association of excess weight (i.e., measured body mass index, BMI) with the abovementioned multidimensional configurations. A convenience sample of adult individuals with excessive weight completed self-reports regarding the study variables, and their weight and height were measured. With a perspective centred on the individual, a cluster analysis established three distinct intraindividual psychosocial and diet-related profiles: a group of healthy individuals with excess weight; a group of individuals who were negatively affected by their excessive weight and showed the most distressed profile; and a group of dysfunctional individuals who seemed to be excessively unrealistic and optimistic regarding their excessive weight and unhealthy lifestyles. Furthermore, individuals in the affected cluster had higher obesity. The results showed that there are specific psychosocial and lifestyle profiles in the adult population with excess weight and that there are relationships among psychological, behavioural, and body-composition factors. For clinical application purposes, it is important to account for the heterogeneity within individuals who are obese.

Sweet cucumber (Solanum muricatum) sect. Basarthrum, is a neglected horticultural crop native of the Andean region. It is naturally distributed very close to potatoes (Solanum sect. Petota) and tomatoes (Solanum sect. Lycopersicon), two groups of high economic importance. To date, molecular tools for this crop are still undetermined. We here obtained the first complete chloroplast (cp) genome of sweet cucumber and compared with seven Solanaceae species. Pair-end clean reads were obtained by PE 150 library and the Illumina HiSeq 2500 platform. The complete cp genome of S. muricatum had a 155,681 bp with typical quadripartite structure, containing a large single copy (LSC) region (86,182 bp) and a small single-copy (SSC) region (18,360 bp), separated by two inverted repeat (IR) regions (25,568 bp). The annotation of chloroplast genome predicted 88 protein-coding genes (CDS), 8 ribosomal RNA (rRNA) genes, 37 transfer RNA (tRNA) genes, and one pseudogene. A total of 48 perfect microsatellites were identified, divided in mononucleotide repeats (32), followed by tetranucleotide (6) and dinucleotides (5). SSRs with trinucleotides repeats (3), pentanucleotide (1) and hexanucleotide (1) repeats motifs in these genomes were identified in lower quantity. Most of these repeats were distributed in the noncoding regions. Whole chloroplast genome comparison with the other seven Solanaceae species revealed that the small and large single copy regions showed more divergence than inverted regions. Finally, phylogenetic analysis resolved that S. muricatum is a sister species to members of sections Petota + Lycopersicum + Etuberosum. This study reports for the first time the genome organization, gene content, and structural features of the cp genome of S. muricatum. Also, this study may provide the basis for evaluating genetic diversity within Solanum, and will be useful to examine the evolutionary processes in sweet cucumber landraces.

Air quality is a topic of growing relevance on the global agenda. Two key indicators of air quali-ty, nitrogen dioxide (NO2) and carbon monoxide (CO), represent significant hazards to human health and the environment putting the sustainability of natural resources at risk. Therefore, it is imperative to regularly monitor and reduce atmospheric pollutant concentrations to mitigate their harmful consequences. This study presents an analysis of NO2 total and CO emissions in Argentina, utilizing remote sensing data. The research aims to determine the spatiotemporal distribution of NO2 and CO emissions in Argentina from 2019 to 2021. Subsequently, it seeks to establish the influence of land uses and land cover on the emission of NO2 and CO through dif-ferent climatic, anthropic, and natural indicators. The study was carried out in Argentina during the period 2019-2021, where random points were placed for the different land covers with a total of 800 points surveyed. The year with the highest CO concentration (mol/m-2) was 2020. The values were highest for tree covers and herbaceous wetland coverage in the northern part of the country. For total NO2, the highest concentrations were reached during the years 2020 and 2021. Regarding its distribution, throughout the evaluated period, the highest concentrations of total NO2 were found in the built-up and cropland coverages, with the capital of the country and the northern region of the Buenos Aires province being the most affected areas. In addition, the concentration of CO was influenced by climatic variables (atmospheric pressure, wind speed, maximum environment temperature, Palmer index), natural (height, humidity, NDVI), and ur-ban variables (distances to mining extraction, airports, power plants, urban index) for the differ-ent uses and land covers. Finally, the concentrations of total NO2 were influenced by climatic variables (Palmer index and wind speed), natural (height and NDVI), and urban variables (dis-tance to airports, power plants, industries, service stations, and open dumpsites) for the differ-ent uses and land cover. This study contributes to sustainable environmental management, ena-bling the formulation of effective strategies for mitigating emissions and promoting the long-term health and well-being of communities.

The daily path of the Sun across longitude yields night and day, but the Sun also travels across latitude on a belt 47° wide. The Sun meridian declination explains the annual budget of natural beam irradiance (NBI), which is the irradiance delivered to the Earth’s surface as a normal projec-tion from the Sun. Data for the sun meridian declination data were obtained from the geometric model. The distribution of NBI was weighed between the Tropics of Cancer and Capricorn. The variation patterns of the solar declination conform to the dynamics of pendular motion. The joint distributions of velocity or acceleration of meridian declination against declination fit circular graphs. The NBI budget fluctuates in inverse proportion to the velocity of declination, yielding 18 sun-paths per degree for latitudes above 20°, and 6 sun-paths per degree for latitudes under 20°. All sites of the planet, whose latitude coincide, whether within or between hemispheres, accumu-late an equivalent budget of NBI.

Introduction: Valproic acid (VPA) is an antiepileptic drug extensively used for treating partial and generalised seizures, acute mania and as prophylaxis for bipolar disorder. Drug-induced liver injury (DILI) persists as a significant issue related to fatal outcomes by VPA. The aim of this study was to increase our knowledge about this condition and to better identify patients affected. Methods: We conducted an observational retrospective case-control study that identified cases of DILI by VPA from the Pharmacovigilance Programme from our Laboratory Signals at La Paz University Hospital from January 2007 to December 2019. From the Therapeutic VPA Monitoring Programme, two control groups were assigned, VPA-tolerant patients and the other with patients who developed mild VPA-related hepatitis but who did not meet the DILI criteria, matched for date, age and sex. Results: A total of 60 patients were included in the study: 15 cases of DILI, 30 VPA-tolerant controls and 15 controls with mild hepatitis. Mean age for the cases was 45.7 years, 4(26.7%) were women and 5(33.34%) were children under 18 years, of them 3(20%) were fatal. Polytherapy with other antiepileptic drugs (p=0.047) and alcohol consumption (p<0.001) were associated with a greater risk of developing DILI by VPA. A diagnosis of epileptic seizure was more frequently related to DILI when compared with the VPA-tolerant controls (p<0.001). The cases developed hepatocellular hepatitis (p<0.001), while the mild hepatitis controls had a higher rate of cholestatic hepatitis (p<0.001). The laboratory lactate dehydrogenase values were statistically higher (even at baseline) in patients with DILI than in both control groups (p= 0.033 and p=0.039). Conclusions: VPA hepatotoxicity remains a considerable problem. This study offers interesting findings for characterising VPA-induced liver injury and at-risk patients.

Zn2GeO4 is considered a very promising alternative to current luminescent semiconductors. Previous results suggest that its emitted wavelength may depend on different variables, such as particle size and morphology, among others. In this work, we have prepared pure and highly homogeneous Zn2GeO4 nanorods under hydrothermal synthesis conditions with a willemite-like structure. Their luminescent properties have been explored and their band gap estimated, which are distinct to previously reported Zn2GeO4 bulk particles. Therefore, our results identify particle morphology as a crucial factor for maximizing and fine-tuning the luminesce of Zn2GeO4 nano-phosphors.

This study explored intraindividual multidimensional profiles integrating psychosocial factors, namely, body image and satisfaction, weight-related self-stigma, positivity, and happiness, and behavioural-lifestyle factors, namely, adherence to a healthy diet, among Spanish adults with overweight or obesity. We further aimed to investigate the association of excess weight (i.e., measured body mass index, BMI) with the abovementioned multidimensional configurations. A convenience sample of adult individuals with excessive weight completed self-reports regarding the study variables, and their weight and height were measured. With a perspective centered on the individual, a cluster analysis established three distinct intraindividual psychosocial and diet-related profiles: a group of healthy individuals with excess weight; a group of individuals who were negatively affected by their excessive weight and showed the most distressed profile; and a group of dysfunctional individuals who seemed to be excessively unrealistic and optimistic regarding their excessive weight and unhealthy lifestyles. Furthermore, individuals in the affected cluster had higher obesity. The results showed that there are specific psychosocial and lifestyle profiles in the adult population with excess weight and that there are relationships among psychological, behavioural, and body-composition factors. For clinical application purposes, it is important to account for the heterogeneity within individuals who are obese and to individualize the interventions, with a focus from weight change to individual's overall well-being.

Many drylands around the world have seen both soil and vegetation degradation around watering points. It can be seen in spaceborne imagery as radial brightness belts that fade with distance from the water areas. The study's primary goal was to characterize spatio-temporal land degradation/rehabilitation in the drylands of the southeast Iberian Peninsula. The brightness index of Tasseled Cap was discovered to be the best spectral transformation for enhancing the contrast between the bright-degraded areas near the points and the darker surrounding areas far from and in-between these areas. To comprehend the spatial structure present in spaceborne imagery of two desert sites and three key time periods, semi-variograms were created (mid-late 2000s, around 2015, and 2020). In order to assess spatio-temporal land-cover patterns, a geostatistical model (kriging) was used to smooth brightness index values extracted from 30 m spatial resolution images. To assess the direction and intensity of changes between study periods, a change detection analysis based on kriging prediction maps was performed. These findings were linked to the socioeconomic situation prior to and following the EU economic crisis. The study discovered that degradation occurred in some areas as a result of the region's agricultural activities being exploited.

COPD is a chronic inflammatory disease characterized by progressive airflow obstruction. Tobacco smoking is the main cause of COPD (COPD-TS), but chronic exposure to biomass smoke (COPD-BS), mainly wood smoke, is the second risk factor; both are considered to cause different phenotypes of COPD. COPD-BS is more eosinophilic than COPD-TS. The objective of the present study was to evaluate the serum level of interleukins involved in eosinophil maturation, recruitment, and survival, and their association with small airway obstruction, measuring cytokines by multiplex test (Bio-Plex) and evaluating the central airway resistance with impulse oscillometry (IOS), comparatively in patients with COPD due to biomass and smoking. The results showed that IL-1ra, IL-2, IL-4, IL-8, IL-9, IL-13, IL-17, and eotaxin were increased in COPD-BS related to COPD-TS. Resistance parameters showed that R5, X5, AX (area reactance), and R5-R20 were significantly higher in COPD-BS than in the COPD-TS group (p < 0.05). R20 was not different between the groups. These data suggest that the cytokines involved in the effect of eosinophils on airway inflammation in COPD-BS were increased compared with COPD-TS, which appears to be related to a predominance of peripheral airway obstruction in patients with COPD-BS more than in COPD-TS

The goal was to determine the personal, interpersonal, and sociocultural predictors of condom use among rural indigenous adolescents. Predictor variables were selected from Bandura's Social Cognitive Theory and Leininger's Transcultural Theory. The sample consisted of 419 Nahuas adolescents randomly selected from the total number of neighborhood blocks in a rural community in Puebla, Mexico. The instruments had acceptable psychometric characteristics (Cronbach alpha and validity scores). Multiple linear regression models were used. Results: 56.8% of participants were female, and 50.40 % were students. The mean age was M = 17.5 (SD = 0.97), and the majority (63%) identified as Catholic. Age at menarche/first ejaculation (β = -1.2, p = .038), attitude toward condom use (β = .13, p < .001), ethnic identity (β = .21, p < .001), and ability to negotiate condom use (β = .13, p < .003), predicted (R2 = 22.3) condom use. This study provides a basis for the integration of the cultural values of indigenous adolescents within interventions for sexual health promotion.

The experimental results of forces and efforts derived from the opening of incisions in the orbital cavity in a pig’s head are presented in this article. The different areas of the incision openings are related to the needs at the incision procedure for a dacryocystorhinostomy. In terms of the experimental procedure, an origin and a plane are defined so as to allow the location of the opening of the incision. The incisions are retracted along an axis of said origin. This procedure has been based on the mathematical model developed for this work, which consists of a procedure for determining the behavior of an incision when a force is applied to retract the skin. The experimental data obtained, suggests the existence of an almost linear relationship between the increment of resistance in relation to the time obtained for each opening, the same of which is deemed to be consistent with the behavior of an elastic material.

Mitigation of Anthropogenic CO2 emissions possess a major global challenge for modern societies. Herein catalytic solutions are meant to play a key role. Among the different catalysts for CO2 conversion Cu supported on molybdenum carbide is receiving increasing attention. Hence, in the present communication we show the activity, selectivity and stability of fresh-prepared -Mo2C catalysts and compare the results with those of Cu/Mo2C, Cs/Mo2C and Cu/Cs/Mo2C in CO2 hydrogenation reactions. The results showed that all the catalysts were active and the main reaction product was methanol. The results showed that copper-cesium and molybdenum effectively interact and that cesium promoted the formation of metallic Mo. While, the incorporation of copper is positive to improve the activity and selectivity to methanol, the presence of Mo0 phase was detrimental for the conversion and selectivity. Moreover, the catalysts promoted by cesium underwent redox surface transformations during the reaction that diminished their catalytic performance. The molybdenum phase in Cu/Mo2C changes during reaction leading to metallic molybdenum and tuning the catalytic activity.

Water stress is one of the main factors affecting the development of agricultural crops. An inno-vative alternative to improve tolerance to water stress is the application of biostimulants. In the present study, the efficacy and physiological and biochemical responses of different biostimulants were evaluated in beans under moderate and severe stress. The treatments consisted of three types of irrigation: FC100, without water stress, FC75, irrigation reduced by 25% (moderate water stress) and FC50, irrigation reduced by 50% (severe water stress). In the treatments with water deficit, foliar biostimulants were applied: zinc oxide nanoparticles plus chitosan, Codasil®, Osmoplant®, Stimplex® and salicylic acid. Foliar application of ZnO + chitosan nanoparticles benefited biomass accumulation and yield under moderate water stress (FC75) and Codasil® and Osmoplant® under severe water stress (FC50). Proline, free sugars and gas exchange were higher under the application of ZnO + chitosan nanoparticles under moderate water stress and under Codasil® and Osmoplant® under severe water stress. Depending on the severity of water stress, ZnO + chitosan nanoparticles, Codasil® and Osmoplant® are viable products to increase tolerance in green bean cv. Strike plants.

Using first-principles molecular dynamics (FPMD), we performed numerical simulations at 300 K to explore the interaction of a 2D MoS2 surface and a platinum atom, calculating the optical properties of the resulting material. The pristine MoS2 is a semiconductor with a gap of around 1.8 eV. The Pt atom is chemisorbed by the surface with an adsorption energy of −1.718 eV. With the adsorption of the Pt atom, the material remains a semiconductor, and its energy band gap reduces to 1.04 eV. But changes in the material's energy band structure imply substantial changes in its optical properties. The energy band structure of the 2D MoS2 with a sulfur vacancy VS shows that the material becomes a conductor, and there are significant changes in its optical properties. We also found that the Pt atom chemisorbs in a sulfur vacancy of the material, with an adsorption energy of −4.1164 eV. After the adsorption of Pt atoms in the sulfur vacancy, the material becomes a semiconductor with a band gap of 1.06 eV, and the changes in the optical absorption and reflectivity are significant.

Education 4.0 postulates the flexible combining of digital literacy, critical thinking, and problem-solving in training environments linked to real-world scenarios. Therefore, teachers are challenged to find or develop new methods and resources to integrate into their curricula to help students develop these desirable and necessary skills; hence, the question: What are the characteristics of a teacher to consider within the framework of Education 4.0? This article presents a study carried out in a higher education institution in Ecuador. The objective was to identify the teaching profile required in new careers within the framework of Education 4.0. The descriptive, exploratory methodology applied quantitative and qualitative instruments (surveys) to 337 undergraduate students in education careers and 313 graduates. It also included interviews with 20 experts in the educational field and five focus groups with 32 rectors, school principals, university professors and specialists in the educational area. The data was triangulated, and the results were categorized in (a) processes as facilitators (b), soft skills, (c) human sense and (d) use of technologies. This article may be of value to administrators, educational and social entrepreneurs, trainers, and decision-makers interested in implementing innovative training programs.

The distribution of Mexican Magnolia species´ occur under restricted climatic conditions. As many other tree species from the tropical montane cloud forests (TMCF), Magnolia species appear to be sensitive to drought. Through the use of dendrochronological techniques, this study aims to determine the climate influence on the vessel traits of M. vovidesii and M. schiedeana which are endangered tree species that are endemic to the Sierra Madre Oriental in eastern Mexico. Because most of the tree species in TMCFs are sensitive to climate fluctuations, it is necessary to investigate the differences in the climatic adaptability of the vessel architecture of these trees. This could allow us to further understand the potential peril of climate change on TMCFs. We compared vessel frequency, length and diameter in drought and non–drought years in two Mexican Magnolia species. We used tree–rings width and vessel traits to assess the drought effects on Magnolias’ diffuse–porous wood back to the year 1929. We obtained independent chronologies for M. vovidesii with a span of 75 years (1941–2016), while for M. schiedeana we obtained a span of 319 years (1697–2016). We found that temperature and precipitation are strongly associated with differences in tree–ring width (TRW) between drought and non–drought years. Our results showed anatomical differences in vessel trait response between these two Magnolia species to climatic variation. We suggest that our approach of combining dendroclimatic and anatomical techniques is a powerful tool to analyse anatomic wood plasticity to climatic variation in Magnolia species.

UAV photogrammetry development during the last decade has allowed to catch information at a very high spatial and temporal resolution from terrains with very difficult or impossible human access. This paper deals with the application of these techniques to study and produce information of very extreme topography which is useful to plan works on this terrain or monitoring it over the time to study its evolution. The methodology stars with the execution of UAV flights on the cut slope studied, one with the cam vertically oriented and other at 45º respect that orientation. Ground control points (GCPs) and check points (CPs) were measured for georeference and accuracy measurement purposes. Orthophoto was obtained projecting on a fitted plane to a studied surface. Moreover, since a digital surface model (DSM) is not able to represent faithfully that extreme morphology, information to project works or monitoring it has been derived from the point cloud generated during the photogrammetric process. An informatics program was developed to generate contour lines and cross sections derived from the point cloud, which was able to represent all terrain geometric characteristics, like several Z coordinates for a given planimetric (X, Y) point. Results yield a root mean square error (RMSE) in X, Y and Z directions of 0.053 m, 0.070 m and 0.061 m respectively. Furthermore, comparison between contour lines and cross sections generated from point cloud with the developed program on one hand and those generated from DSM on other hand, shown that the former are capable of representing terrain geometric characteristics that the latter cannot. The methodology proposed in this work has been shown as an adequate alternative to generate manageable information, as orthophoto, contour lines and cross sections, useful for the elaboration, for example, of projects for repairing or maintenance works of cut slopes with extreme topography.

From the aerial parts of Salvia ballotiflora, eleven diterpenoids were isolated, among them, four icetexanes, and one abietane (1–5), which are first reported. Their structures were established by spectroscopic means, mainly ¹H and ¹³C NMR, including 1D and 2D homo- and hetero-nuclear experiments. Most of the isolated diterpenoids were tested for their antiproliferative, anti-inflammatory, and radical scavenging activities using the sulforhodamine B assay on six cancer cell lines, the TPA induced ear edema test in mice, and the reduction of the DPPH assay, respectively. Some diterpenoids showed anti-proliferative activity, these being icetexanes 6 and 3, which were the most active with IC₅₀ (µM) = 0.27 ± 0.08 and 1.40 ± 0.03, respectively, for U251 (human glioblastoma) and IC₅₀ (µM) = 0.0.46 ± 0.05, and 0.82 ± 0.06 for SKLU-1 (human lung adenocarcinoma), when compared with adriamycin (IC₅₀ (µM) = 0.08 ± 0.003, and 0.05 ± 0.003, as the positive control, respectively. Compounds 3 and 10 showed significant reduction of the induced ear edema of 37.4 ± 2.8 and 25.4 ± 3.0% (at 1.0 µmol/ear), respectively. Compound 4 was the sole active diterpenoid in the antioxidant assay (IC₅₀ = 98. 4 ± 3.3), using α-tocopherol as positive control, IC₅₀ (µM) = 31.7 ± 1.04. The diterpenoid profile found is of chemotaxonomic relevance and reinforces the evolutionary link of S. ballotiflora with other members of the section Tomentellae.

Differences in fish assemblages’ structure and their relation with environmental variables (due to the variations in sampled seasons, habitats, and zones), were analyzed in two adjacent estuaries on the north Pacific coast of Mexico. Environmental variables and fish catches were registered monthly between August 2018 and October 2020. Multivariate analyses were conducted to define habitats and zones based on their environmental characteristics, and the effect of this variability on fish assemblages’ composition, biomass, and diversity (α and β) was evaluated. A total of 12,008 fish individuals of 143 species were collected using different fishing nets. Multivariate analyses indicated that fish assemblages’ structure was different between zones due to the presence, height, and coverage of distinct mangrove species. Additionally, factors such as depth and salinity showed effects on fish assemblages’ diversity (α and β-nestedness), which presented higher values in the ocean and remained similar in the rest of the analyzed zones and habitats. These results and the differences in species replacement (β-turnover) indicate the singularity of fish assemblages at estuaries (even in areas very close to the ocean), and the necessity to establish local management strategies for these ecosystems.

Microbial electrochemical technologies (MET) rely on the presence of the metabolic activity of electroactive bacteria for the use of solid-state electrodes for oxidizing different kind of compound, that could lead to the synthesis of chemicals, bioremediation of polluted matrices, the treatment of contaminants of interest, as well as the recovery of energy. Keeping in mind those possibilities, since the beginning of the present century, there has been a growing interest in the use of electrochemical technologies for wastewater treatment, and if possible with simultaneous power generation. In the last years, there has been a growing interest to explore the possibility of merging MET with constructed wetlands, to offer a new option of intensified wetland system that could keep a high performance with a lower footprint. Based on that interest, this paper explains the general principles of MET, and the different known extracellular electron transfer mechanisms ruling the interaction between electroactive bacteria and potential solid-state electron acceptors. Also, the adoption of those principles for the development of MET set-ups for simultaneous wastewater treatment and power generation, and the challenges that the technology face. Ultimately, the most recent developments in set-ups that merges MET with constructed wetlands are presented and discussed.

Coffee production generates significant amounts of by-products, posing challenges for waste management in the industry. Recent research has revealed that coffee by-products are rich in bioactive compounds suitable to produce functional food ingredients and nutraceuticals. In this review, we explore biorefinery strategies for extracting and utilizing bioactive compounds from coffee by-products, including the production of bio-based chemicals and materials, as well as the extraction of phenolic compounds, antioxidants, and dietary fiber for food applications. We propose a stepwise approach for the development of functional food ingredients and nutraceuticals from coffee by-products, covering the identification of needs, comprehensive characterization, in vitro and in vivo research, unraveling the mechanism of action, food and nutraceutical formulation, sensory analysis, shelf-life stability, scale-up, randomized control trials, and biostatistic and bioinformatic integration. Additionally, we discuss the market potential, regulatory issues, and technological innovation surrounding the commercialization of coffee by-product-based products. Emphasizing the importance of regulatory compliance and sustainability in the coffee industry, this review highlights the potential of coffee by-products to be transformed from waste into valuable functional food ingredients and nutraceuticals, offering a promising avenue for waste reduction and promoting sustainability in the coffee industry.

A strategy to propose solutions to health-related problems recognizes that people, animals, and the environment are interconnected. Fusarium and Neocosmospora are an example of this interaction due to the capable of infecting plants, animals, and human. This review provides information on various aspects of these relations and proposes how to approach fusariosis with a One Health methodology. Here we give a framework to understand infection pathogenesis, through the epidemiological triad and explain how the broad utilization of fungicides in agriculture may play a role in the treatment of human fusariosis. We assess how plumbing systems and hospital environments might play a role as a reservoir for animal and human infections. We explain the role of antifungal resistance mechanism in both humans and agriculture. Our review emphasizes the importance of developing interdisciplinarity research studies where aquatic animals, plants, and human disease interactions can be explored through coordination and collaborative actions.

Debris flows have generated major disasters worldwide due to their great destructive capacity, which is associated with their high energy levels and short response times. To achieve an adequate risk management of these events, it is necessary to define as accurately as possible the different hazard levels to which the territory is exposed. This article develops a new methodology to estimate this hazard based on the hydrodynamic characteristics of the flow and the granulometry of the sediments that can be mobilized by the flow. The hydrodynamic characteristics of the flow are determined through a mathematical modeling that considers the rheology of non-Newtonian flows and the different volumes of sediments that could be transported during events corresponding to different return periods. The proposed methodology was implemented in the Jamundí River basin (Colombia). The results obtained indicate that in the upper part of this basin there is a low hazard level, while in the lower part of the basin approximately 15% of the affected territory has a medium hazard level and the remaining 85% has a low hazard level. The methodology developed is simple to implement but technically rigorous since it considers all relevant aspects in the generation of debris flows.

Current environmental conditions have prompted agri-food systems to explore new strategies for improving the production of crops in a sustainable manner. The use of omeprazole (OMP) and melatonin (MEL) have been proposed as innovative strategy for crop improvement when applied as biostimulants. However, although their role in the growth of several species has been studied, the results in photosynthetic efficiency parameters are still scarce. Therefore, the objec-tive of the present study was to evaluate the effect of foliar application of OMP and MEL on bi-omass, yield, SPAD values, leaf chlorophyll fluorescence (Fv/Fm), photochemical quenching (qP), Non-photochemical quenching (NPQ), quantum yield of photosystem II (PhiPSII) and elec-tron transport rate (ETR) in bean plants. Treatments were applied separately at doses of 1, 10, and 100 µM, plus a control without application. The results obtained indicate that OMP and MEL were able to increase biomass, yield, SPAD values, as well as photochemical quenching, fluores-cence, and PhiPSII coefficients. Finally, it is concluded that foliar application of OMP and MEL at a dose of 1 and 10 µM can increase photosynthetic efficiency and decrease photoinhibition, which is reflected in higher biomass accumulation and yield in green bean plants cv. Strike.

Chronic Obstructive Pulmonary Disease (COPD) is a disease characterized by local and systemic inflammation independently of the risk factor; during the exacerbations, such inflammation is accentuated and amplified. A practical inflammatory marker and one with an applicable predictive value in the follow-up has been sought. FeNO has shown an excellent performance in that respect within the context of asthma and has also been studied in tobacco-smoke COPD (COPD-TS). In Biomass-smoke COPD (COPD-BS), this, to our knowledge, has not been evaluated. Objective: To measure FeNO levels in patients with COPD-BS and to compare these with those of patients with stable COPD-TS and in healthy controls. Methods: Transversal, observational, descriptive, comparative, and analytical study. A total of 57 patients, including 23 with COPD-BS, 17 with COPD-TS, and 17 healthy control subjects. The measurement of FeNO was carried out on all of these by means of the on-line chemiluminescence technique; the values were expressed in parts per billion (ppb) for their analysis. Results: It was observed that the FeNO values were similar between COPD-BS and COPD-TS and were significantly different between the healthy and stable COPD (both groups). No correlation was found between pulmonary function and symptoms with FeNO in any of the groups. Conclusions: The level of FeNO in stable COPD is found to be increased in a similar manner in COPD-BS and COPD-TS, with a significant difference on comparing it with that of the healthy subjects.

Anthropogenic activities have increased the amount of urban wastewater discharged into natural aquatic reservoirs confining in them a high amount of nutrients and organics contaminants. Several studies have reported that an alternative to reduce those contaminants is using consortiums of microalgae and endogenous bacteria. In this research, a genome-scale biochemical reaction network is reconstructed for the co-culture between the microalga Chlorella vulgaris and the bacterium Pesudomonas aeruginosa. Metabolic Pathway Analysis (MPA), is applied to understand the metabolic capabilities of the co-culture and to elucidate the best conditions in removing nutrients such as Phosphorus (inorganic phosphorous and phosphate) and Nitrogen (nitrates and ammonia). Theoretical yields for Phosphorus removal under photoheterotrophic conditions are calculated, determining their values as 0.042 mmol of PO₄/ g DW of C. vulgaris, 19.53 mmol of inorganic Phosphorus /g DW of C. vulgaris and 4.90 mmol of inorganic Phosphorus/ g DW of P. aeruginosa. Similarly, according to the genome-scale biochemical reaction network the theoretical yields for Nitrogen removal are 10.3 mmol of NH₃/g DW of P. aeruginosa and 7.19 mmol of NO₃ /g DW of C. vulgaris. Thus, this research proves the metabolic capacity of these microorganisms in removing nutrients and their theoretical yields are calculated.