The objective of this study was to evaluate the glycemic index and the satiety response of three Mexican kinds of honey. The values of fructose ranged from 272.40-395.10 g/kg, while the glucose value ringed 232.20-355.50 g/kg. The ratio F/G of sample honey was 1.45, 1.00, and 1.17 for Highland, Multifloral, and Avocado honey, respectively. Twenty-six participants completed this study, which was previously approved by the ethics committee of the Facultad de Salud Pública y Nutrición (CE 2/2018-19). Highland and Avocado honey is classified as medium-GI (69.204.07 and 66.365.74, respectively), while Multifloral honey is classified as high-GI (74.245.98). The Highland honey presented the best satiety response. The difference in IG values and the effect of the satiety response of Highland honey could be explained by the different fractions of carbohydrates in samples and other components such as phytochemicals.

Quercetin is a flavonoid with a low molecular weight that belongs to the human diet's phenolic phytochemicals and non-energy constituents. Quercetin has a potent antioxidant capacity, being able to capture Reactive Oxygen Species (ROS), reactive nitro-gen species (RNS), and Reactive Chlorine Species (ROC), which act as reducing agents by chelating transition metal ions. Its structure has five functional hydroxyl groups, which work as electron donors and are responsible for capturing free radicals. In addition to its antioxidant capacity, it was described different pharmacological properties of Quercetin, such as carcinostatic properties, antiviral, antihypertensive, anti-inflammatory, protection of Low-Density Lipoprotein (LDL) oxidation, and inhibi-tion of angiogenesis are developed in this review.

Right atrial isomerism (RAI) is a complex entity whose treatment and outcome are heterogeneous. The aim of this study was to analyze the results obtained after cardiac surgery in patients with RAI. A retrospective study was conducted; it included patients diagnosed with RAI who underwent cardiac surgery; their follow-up was from January 1, 2010 to March 31, 2020. Demographic characteristics and perioperative conditions were described. Thirty-eight patients with RAI were included, the median age was 4 years (IQR 2-9.2), and 57.9% were men. The main diagnoses were atrioventricular canal (63.2%) and pulmonary stenosis (55.3%). The most common surgical procedures were modified Blalock‐Taussig shunt (65.8%) and total cavopulmonary connection with an extracardiac conduit fenestrated without cardiopulmonary bypass (15.9%). The use of inhaled nitric oxide was a marker of postoperative mortality in critically ill patients (OR: 10.33; 95% CI: 1.04 - 102.08; p = 0.02). The overall survival was 86.8%, with a better outcome in those who did not require reintubation (Log Rank, p < 0.01). The survival of RAI was similar to other centers of reference. Individuals with RAI should be evaluated rigorously to determine an adequate repair strategy, considering high morbidity and mortality.

Abstract: Patients with Cleft Lip Palate (CLP) require comprehensive treatment, so the people who take care of them must constantly provide care and support, along with continuous care and support from their caregivers, often extending until youth. The purpose was to compare the Quality of Life (QoL) of caregivers of children with CLP with those without the condition. A cross-sectional paired study was conducted at the Dental Clinic of the Escuela Nacional de Estudios Superiores (ENES León), National Autonomous University of Mexico (UNAM), from May to December 2021. Primary caregivers of patients with CLP (n=70) were included as well as those of the patients without CLP (n=70) of the same institution. Sample size was calculated considering an OR=2.5, establishing a convenience selection. Caregivers answered the WHOQoL Bref instrument to assess QoL. Of the total sample analyzed, 88.6% of the caregivers were female (p>0.05). Caregivers of patients with CLP reported poor QoL (64.8%), compared to caregivers in the control group (p

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

In recent times, using image-based deep learning techniques has been very useful for classifying fruits. However, mango is a particular challenge because its shelf life is directly related to the degree of maturity at the time of harvest, which is determined mainly through the visual assessment of the operators when sorting them, doing it incorrectly, coupled with the blows and compressions exposed during storage and transport, trigger the deterioration in their quality, hence the importance of this operation. In this sense, the purpose of this study focuses on designing a computational model based on Deep Learning that uses a convolutional neural network (CNN) parameterized to select mangoes according to their color tone based on their maturity stage. A dataset was established from 201 labeled images, then a CNN architecture was built, obtaining a model on which 3 criteria were evaluated: the number of convolution and grouping layers, the resolution of the input images and the number of training epochs required. As a result, an input image resolution of 32 x 32 pixels was achieved, the process included a convolution layer followed by pooling that fed another layer that processed the results and ended in an output layer with 2 neurons under the One Hot Encoding representation. The model required 20 epochs to perfect its training, achieving 96.04 % accuracy in mango image selection. This study supports the potential of CNNs in quality analysis through mango color selection, even in uncertainty scenarios.

(1) Background: During physical exercise, ventilation (VE) adapts to the intensity and characteris-tics of the effort. The breathing pattern is defined as the relationship between the tidal volume (VT) and breathing frequency (BF) for a given VE. The aim of this study was to evaluate whether inspiratory muscle training influenced the response of the breathing pattern during an incremen-tal effort in amateur cyclists. (2) Methods: 18 amateur cyclists completed an incremental test to exhaustion with gas analysis on a cycle ergometer and spirometry. Cyclists were randomly as-signed to two groups (IMTG=9; CON=9). The IMT group completed 6 weeks of inspiratory muscle training (IMT) using a PowerBreathe K3® device at 50% of the maximum inspiratory pressure (Pimax). The workload was adjusted weekly. After the 6-week intervention, the cyclists repeated the incremental exercise test with gas analysis and spirometry. The response of the breathing pat-tern was evaluated during the incremental exercise test. (3) Results: Pimax increased in the IMTG (p<0.05; +19.62%). Variables related to the breathing pattern response showed no differences be-tween groups after the intervention (EXPvsCON; p>0.05). Likewise, no differences were found in the IMTG after training (PREvsPOST; p>0.05). (4) Conclusions: IMT improved the strength of in-spiratory muscles and sports performance in amateur cyclists. These changes were not attributed to alterations in the response of the breathing pattern.

Transcription factors (TFs) and microRNAs (miRNAs) are co-actors in genome-scale decoding and regulatory networks, often targeting common genes. In this paper, we describe the algebraic geometry of both TFs and miRNAs thanks to group theory. In TFs, the generator of the group is a DNA-binding domain while, in miRNAs, the generator is the seed of the sequence. For such a generated (infinite) group $\pi$, we compute the $SL(2,\mathbb{C})$ character variety, where $SL(2,\mathbb{C})$ is simultaneously a \lq space-time' (a Lorentz group) and a \lq quantum' (a spin) group. A noteworthy result of our approach is to recognize that optimal regulation occurs when $\pi$ looks like a free group $F_r$ ($r =1$ to $3$) in the cardinality sequence of its subgroups, a result obtained in our previous papers. A non free group structure features a potential disease. A second noteworthy result is about the structure of the Groebner basis $\mathcal{G}$ of the variety. A surface with simple singularities (like the well known Cayley cubic) within $\mathcal{G}$ is a signature of a potential disease even when $G$ looks like a free group $F_r$ in its structure of subgroups. Our methods apply to groups with a generating sequence made of two to four distinct DNA/RNA bases in $\{A,T/U,G,C\}$. Several human TFs and miRNAs are investigated in detail thanks to our approach.

This study presents the design and implementation of a PLC microprocessor adhering to the IEC-61131-3 standard, executed on a Cyclone-V FPGA using a DE10-NANO development board. Our microprocessor optimizes the central processing unit by streamlining the data path, achieving a remarkable simulated response time of approximately 60 ns, equivalent to three clock cycles at a 50MHz frequency for Boolean operations. To substantiate our approach, we conducted practical experiments utilizing a FESTO conveyor station, employing relays as actuators, and incorporating optical and inductive sensors. The results underscore the feasibility of our proposed approach and serve as practical validation of its efficacy. This work introduces a promising avenue for the development of cost-effective PLCs employing SoC FPGA variants. Additionally, a thorough comparison of execution times with other early reported architectures. Our microprocessor outperforms even well-established PLCs like the S7-312, with substantial reductions in execution times of 94.54% for floating-point operations, 71.42% to 93.33% for word operations, and up to 78.57% for bit operations.

Tissue inhibitors of metalloproteinases (TIMPs) are essential players during tumor progression in various types of cancer, including breast cancer. TIMPs regulate the activity of matrix metallo-proteinases (MMPs) at different levels. However, a dual role for TIMPs in breast carcinogenesis, either promoting or inhibiting tumor progression, has been observed. By a comprehensive bioin-formatics analysis using different databases, we report that of the four TIMPs, only TIMP-1 is overexpressed in tumor breast tissue. However, TIMP-2, TIMP-3, and especially TIMP-4 present lower levels in breast tumor tissue than in normal tissue. Interestingly, high levels of TIMP-1 are associated with shorter survival in breast cancer patients. In contrast, low TIMP-2, TIMP-3, and TIMP-4 levels are associated with poor survival. Function enrichment analysis showed that TIMP-3 has the highest interactions with its target proteins and a higher number of processes re-lated to mammary carcinogenesis. We found differential expression of TIMP-1 concerning TIMP-3 and TIMP-4 in breast cancer and normal tissue. TIMP-4 has a significant relationship with cancer staging, including tumor size, lymph node spread, and metastasis. The correlation between immune cell infiltrates and TIMP expression is of great importance as they provide in-formation on breast cancer diagnosis, prognosis, progression, and response to treatment.

Followed by the aspect of respect for rights 20, the social and environmental issue has a score of 19.9, the dialogue issue is 19. In short, the proximity plan indicates that the policies used regarding the issue of generating employment and economic growth (Empresa Mantaro Perú SAC), continue to be the strategic variables in the first instance, but they are far from the social actors (rural communities of Aco, Vico, Cruz Pampa and others) and environmental (Junín environmental dialogue table) and Ombudsman's Office (rights) that are currently closer together. The actor from the Archbishop of Huancayo referred to communication is one of the driving variables of power. The proximity plan shows us that the policies used regarding the issue of generating employment and economic growth (Empresa Mantaro Perú SAC), continue to be the strategic variables in the first instance, but that they are far from the social actors (Rural Communities of Aco , Vico, Cruz Pampa and others) and environmental (Junín Environmental Dialogue Table) and Ombudsman's Office (rights) that are currently closer together. The actor from the Archbishop of Huancayo referred to communication is one of the driving variables of power. The proximity plan shows us that the policies used regarding the issue of generating employment and economic growth (Empresa Mantaro Perú SAC), continue to be the strategic variables in the first instance, but that they are far from the social actors (Rural Communities of Aco , Vico, Cruz Pampa and others) and environmental (Junín Environmental Dialogue Table) and Ombudsman's Office (rights) that are currently closer together. The actor from the Archbishop of Huancayo referred to communication is one of the driving variables of power. but they are far from the social actors (rural communities of Aco, Vico, Cruz Pampa and others) and environmental (Junín Environmental Dialogue Table) and the Ombudsman's Office (rights) that are closer together today. The actor from the Archbishopric of Huancayo referred to communication, is within the driving variables of power. but they are far from the social actors (rural communities of Aco, Vico, Cruz Pampa and others) and environmental (Junín Environmental Dialogue Table) and the Ombudsman's Office (rights) that are currently closer together. The actor of the Archbishopric of Huancayo referred to communication, is within the driving variables of power.

La minería es una industria intensiva en energía que requiere una fuente estable de electricidad. Con el aumento de la demanda de minerales y la disminución de las leyes, se espera que la demanda de energía aumente en un 36% para el 2035. Este aumento de la demanda depende del uso de combustibles fósiles ya que la electricidad producida y comprada en las empresas mineras se basan principalmente en el caso de los combustibles fósiles, los costos de los sistemas de almacenamiento de energía solar y eólica han caído a una escala sin precedentes, lo que alienta a las empresas mineras a probar estas tecnologías.Entre los factores que influyen en el uso de energía renovable, se encuentra el beneficio a la comunidad en la etapa de operación y cierre o post-cierre de un proyecto minero, el siguiente factor es el perfil de consumo eléctrico o demanda es importante para el cálculo de su almacenamiento o no, de las energías renovables a utilizar. Como tercer factor está el cálculo del consumo en los procesos. Los rangos de penetración determinarán si es posible su almacenamiento de energía, y si es posible utilizar control híbrido (solar - eólico), para ello es importante el uso de herramientas digitales como el programa Holmer, es una herramienta importante que técnica y económica.El gobierno debe tener una perspectiva que ayude en los temas regulatorios necesarios para impulsar proyectos de energía renovable con diferentes incentivos e intereses según el contexto minero.

Background and objectives: In the current context, the 2021 presidential elections in Peru distance from the social objective, not being objectively represented, that is why we analyze their validity, we determine the distances between the parties if they are extreme, the correspondences with the departments and their prospects, in the surveys we propose which departments influence the results. Methods: We use a mixed methodology, qualitative analysis, it will be multidimensional with the support of statistical methods and programs such as R Studio, worddj, Gephi, and Iramuteq. The quantitative analysis will be through factor analysis, correspondence and discriminant analysis to the data of the election Results and conclusions: The textual analysis mentions that there are dimensions such as the social issue, the results of the surveys and democracy that are far apart, regarding the electoral issue. This inculcates to work both on the part of the organisms that carry out these processes, as well as the initiative of the candidates, and the media. Regarding the quantitative analysis, it is detailed that the representative parties must be greater than 4.0 million voters, to make representative parties at the national level. The classification regarding the percentage of votes is given in three groups, highlighting the independence of the Peru Libre political party in these . In the correspondence analysis we can detail that both Fuerza Popular and Peru Libre are extremist parties. The vast majority of Peruvian citizens have an ideological tendency, intermediate between both parties. The prospective projections with a cross section give a victory to the Peru Libre party. In the discriminant analysis, the sample for the surveys focuses on 7 departments that does not include the Peruvian capital.

The La Oroya metallurgical complex reveals a process of structural or power pathology, where economic and environmental social policies lead to a citizenry without systemic freedom, characterized by environmental contamination (PAMA executed on average 67%, some processes with 0%) and sanitary (plumbosis 8.39 to 10.28 μg / dL), the economic dependence of this industry is also observed, which caused the weakening of the communities to maintain autonomy over their own destinies.The Doe Run Peru, operated the metallurgical complex, creating added value to the extractive-export chain of mineral concentrate, but also took advantage of the legal loopholes, the little coordination between the State institutions and the little authority of the supervisory institutions to get the most out of it, complying with the law in some cases, but without moral quality in some others, such as health in the oroinos.Government institutions must have strong links that provide a normative framework with prospects with sustainable development, where the beneficiary is society and not only certain interest groups. The economic benefits of the metallurgical complex operation are multiple, which begin with labor, the purchase and sale of materials and services, the collection of taxes and energy.

A single qubit may be represented on the Bloch sphere or similarly on the 3-sphere S3. Our goal is to dress this correspondence by converting the language of universal quantum computing (UQC) to that of 3-manifolds. A magic state and the Pauli group acting on it define a model of UQC as a positive operator-valued measure (POVM) that one recognizes to be a 3-manifold M3. More precisely, the d-dimensional POVMs defined from subgroups of finite index of the modular group PSL(2, Z) correspond to d-fold M3- coverings over the trefoil knot. In this paper, one also investigates quantum information on a few ‘universal’ knots and links such as the figure-of-eight knot, the Whitehead link and Borromean rings, making use of the catalog of platonic manifolds available on the software SnapPy. Further connections between POVMs based UQC and M3’s obtained from Dehn fillings are explored.

A single qubit may be represented on the Bloch sphere or similarly on the $3$-sphere $S^3$. Our goal is to dress this correspondence by converting the language of universal quantum computing (uqc) to that of $3$-manifolds. A magic state and the Pauli group acting on it define a model of uqc as a POVM that one recognizes to be a $3$-manifold $M^3$. E. g., the $d$-dimensional POVMs defined from subgroups of finite index of the modular group $PSL(2,\mathbb{Z})$ correspond to $d$-fold $M^3$- coverings over the trefoil knot. In this paper, one also investigates quantum information on a few \lq universal' knots and links such as the figure-of-eight knot, the Whitehead link and Borromean rings, making use of the catalog of platonic manifolds available on SnapPy. Further connections between POVMs based uqc and $M^3$'s obtained from Dehn fillings are explored.

We consider partition functions, in the form of state sums, and associated probabilistic measures for aperiodic substrates described by model sets and their associated tiling spaces. We propose model set tiling spaces as microscopic models for small scales in the context of quantum gravity. Model sets possess special self-similarity properties that allow us to consider implications on large and observable scales from the underlying (non-ergodic) dynamics. In particular we consider the implication of the underlying aperiodic substrate for the well known problem of time in quantum gravity, and propose a correspondence between small and large scales, the so-called ergodic correspondence, that addresses the emergence of matter properties and spacetime structure. In the process we find a possible bound in the mass spectrum of fundamental particles.

This paper investigates if Corporate Social Responsibility (CSR) reports published by a selected group of Nordic companies are aligned with the Global Reporting Initiative (GRI) standards. To achieve this goal, several natural language processing, and text mining techniques were implemented and tested. We extracted strings, corpus, and hybrid semantic similarities from the reports and evaluated the models through the intrinsic assessment methodology. A quantitative ranking score based on index matching was developed to complement the semantic valuation. The final results show that Latent Semantic Analysis (LSA) and Global Vectors for Word Representation (GloVE) are the best methods for our study. Our findings will open the door to the automatic evaluation of sustainability reports which could have a strong impact on the environment.

Polymer-based (nano)composite foams, especially those having a microcellular structure, containing suitable conductive (nano)fillers, have been shown to act as good shielding materials, hence coming as promising to act as shields in electronic devices, limiting/avoiding electromagnetic interference (EMI) pollution. Nevertheless, due to their high (micro)structural complexity, related to their multiphase nature, there is still a lot of unawareness behind the shielding mechanisms acting in these materials, coming as a necessity to study their microstructure-cellular/porous structure-properties relations, especially in terms of their electrical conductivity and EMI shielding efficiency (EMI SE). To target and control the electrical conductivity through a controlled distribution/dispersion of conductive nanofillers, single or combined (nanohybrids), as there is a direct relation between electrical conductivity and EMI SE, as well as the main EMI shielding mechanisms working on the developed microcellular structure of the foams, which are expected to be absorption-dominated or absorption/multiple reflection-based, are two of the main objectives when combining polymer foaming with the addition of conductive nanofillers. The present review work considers the recent developments and trends on polymer-based foams containing conductive nanofillers, especially carbon-based such as carbon nanotubes or graphene-based materials, as well as similar porous structures created using trending technologies such as 3D printing, for EMI shielding applications. It is divided in different sections, starting with the strategy of microcellular foaming to develop polymer-based foams with enhanced EMI shielding characteristics, especially focusing on technologies and methods using supercritical CO2 (sCO2); continuing with the use of polymer foams as templates to synthesize carbon foams with improved EMI shielding performance for high use temperature applications; the recent strategy of combining different functional (nano)fillers to create hybrid nanofillers/nanohybrids to be used at lower amounts as conductive fillers in polymer foams; the control and selective distribution of the nanofillers in terms of favoring the formation of a more effective conductive network and hence promote the enhancement of the EMI SE; the very recent use of computational approaches to tailor the EMI shielding properties of composite foams; and the very trending possibility of creating cellular components with varied porous structures from these materials using 3D printing; to finish, some future perspectives are discussed.

The evaluation of research proposals and academic careers is subject to indicators of scientific productivity. Citations are critical signs of impact for researchers, and many indicators are based on these data. The literature shows that there are differences in citation patterns between areas. The scope and depth that these differences may have to motivate the extension of these studies considering types of articles and age groups of researchers. In this work, we conducted an exploratory study to elucidate what evidence there is about the existence of these differences in citation patterns. To perform this study, we collected historical data from Scopus. Analyzing these data, we evaluate if there are measurable differences in citation patterns. This study shows that there are evident differences in citation patterns between areas, types of publications, and age groups of researchers that may be relevant when carrying out researchers’ academic evaluation.

A popular account of the mixing patterns for the three generations of quarks and leptons is through the characters $\kappa$ of a finite group $G$. Here we introduce a $d$-dimensional Hilbert space with $d=cc(G)$, the number of conjugacy classes of $G$. Groups under consideration should follow two rules, (a) the character table contains both two- and three-dimensional representations with at least one of them faithful and (b) there are minimal informationally complete measurements under the action of a $d$-dimensional Pauli group over the characters of these representations. Groups with small $d$ that satisfy these rules coincide in a large part with viable ones derived so far for reproducing simultaneously the CKM (quark) and PNMS (lepton) mixing matrices. Groups leading to physical $CP$ violation are singled out.

In Mexico there is a deficit in the production of pine resin, because it depends on natural forests. Therefore, it is necessary to select provenances and phenotypes of potential species such as P. oocarpa. The objective was to determine the difference between provenances and the variation of resin components and quality, as well as the effect of geographic and climatic factors. Resin from five provenances was collected from southern Mexico. The percentage of rosin, turpentine and water was obtained, as well as the acidity and saponification index. P. oocarpa resin had 80.94 % rosin, 7.7 % turpentine and 11.49 % water. The saponification and acidity index was 125.47 and 117.49 mg KOH.g_1, respectively. All variables showed differences (p≤ 0.0001) between provenances. The provenance contributed between 6.44 and 11.71 % to the total variance, the error contributed between 88.29 and 93.56 %. Geographic and climatic variables only had an effect on the percentage of turpentine; the correlation was negative with altitude and longitude, but positive with temperature and precipitation. The results allow defining seed collection sites for resin plantations and orienting the selection for a P. oocarpa improvement program.

The authors previously found a model of universal quantum computation by making use of the coset structure of subgroups of a free group $G$ with relations. A valid subgroup $H$ of index $d$ in $G$ leads to a \lq magic' state $\left|\psi\right\rangle$ in $d$-dimensional Hilbert space that encodes a minimal informationally complete quantum measurement (or MIC), possibly carrying a finite \lq contextual' geometry. In the present work, we choose $G$ as the fundamental group $\pi_1(V)$ of an exotic $4$-manifold $V$, more precisely a \lq small exotic' (space-time) $R^4$ (that is homeomorphic and isometric, but not diffeomorphic to the Euclidean $\mathbb{R}^4$). Our selected example, due to to S. Akbulut and R.~E. Gompf, has two remarkable properties: (a) it shows the occurence of standard contextual geometries such as the Fano plane (at index $7$), Mermin's pentagram (at index $10$), the two-qubit commutation picture $GQ(2,2)$ (at index $15$) as well as the combinatorial Grassmannian Gr$(2,8)$ (at index $28$) , (b) it allows the interpretation of MICs measurements as arising from such exotic (space-time) $R^4$'s. Our new picture relating a topological quantum computing and exotic space-time is also intended to become an approach of \lq quantum gravity'.

Revealing the time structure of physical or biological objects is usually performed thanks to the tools of signal processing like the fast Fourier transform, Ramanujan sum signal processing and many other techniques. For space-time topological objects in physics and biology, we propose a type of algebraic processing based on schemes in which the discrimination of singularities within objects is based on the space-time-spin group SL(2,C). Such topological objects possess an homotopy structure encoded in their fundamental group and the related SL(2,C) multivariate polynomial character variety contains a plethora of singularities somehow analogous to the frequency spectrum in time structures. Our approach is applied to an Akbulut cork in exotic R4, to an hyperbolic model of topological quantum computing based on algebraic surfaces and to microRNAs in genetics. Such diverse topics reveal the manifold of possibilities of using the concept of a scheme spectrum.

The methods used to introduce CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas-mediated genome editing into fruit species, as well as the impacts of the application of this technology to activate and knock out of target genes in different fruit trees species including tree development, yield, fruit quality, and tolerance to biotic and abiotic stresses have been firstly described in this review. The application of this gene editing technology could allow the development of new generations of fruit crops with improved traits by targeting different genetic segments or even could facilitate the introduction of traits in elite cultivars without changing other traits. However, at this moment, the scarcity of efficient regeneration and transformation protocols in some species, the fact that many of those procedures are the genotype-dependent or the convenience of segregating the transgenic parts of the CRISPR system represent the main handicaps limiting the potential of genetic editing techniques for fruit trees. Finally, latest news on the legislation and regulations about the use of plants modified through CRISPR/Cas systems has been also discussed.

It is shown how the secondary structure of proteins, musical forms and verses of poems are approximately ruled by universal laws relying on graph coverings. In this direction, one explores the group structure of a variant of the SARS-Cov-2 spike protein and the group structure of apolipoprotein-H, passing from the primary code with amino acids to the secondary structures organizing the foldings. Then one look at the musical forms employed in the classical and contemporary periods. Finally, one investigates in much detail the group structure of a small poem in prose by Charles Baudelaire and that of the Bateau Ivre by Arthur Rimbaud.

Every protein consists of a linear sequence over an alphabet of $20$ letters/amino acids. The sequence unfolds in the $3$-dimensional space through secondary (local foldings), tertiary (bonds) and quaternary (disjoint multiple) structures. The mere existence of the genetic code for the $20$ letters of the linear chain could be predicted with the (informationally complete) irreducible characters of the finite group $G_n:=\mathbb{Z}_n \rtimes 2O$ (with $n=5$ or $7$ and $2O$ the binary octahedral group) in our previous two papers. It turns out that some quaternary structures of protein complexes display $n$-fold symmetries. We propose an approach of secondary structures based on free group theory. Our results are compared to other approaches of predicting secondary structures of proteins in terms of $\alpha$ helices, $\beta$ sheets and coils, or more refined techniques. It is shown that the secondary structure of proteins shows similarities to the structure of some hyperbolic $3$-manifolds. The hyperbolic $3$-manifold of smallest volume --Gieseking manifold--, some other $3$ manifolds and the oriented hypercartographic group are singled out as tentative models of such secondary structures. For the quaternary structure, there are links to the Kummer surface.

Background: and objectives: Covid-19 is a global pandemic that requires a culturally integrated response in all Latin American government systems. In this study, we investigate the multidimensional associations of actions in Latin American indigenous peoples against Covid-19 Methods: We performed a data mining analysis of scientific literature records from 19 academic journals, using the topics Covid-19, mortality, indigenous peoples, and future measures, rights and actions. The literature is analyzed in a multidimensional way, either isolated or combined. It uses switchable statistical methods, the R Studio, worddj, Gephi, and Iramuteq for both textual and multidimensional analysis. Results and Conclusions: In this analysis, the literature is classified into 4 linked groups which are the indigenous people, the rights of territorial protection, the indigenous health culture, the Covid-19 pandemic with its protection efforts. Taking the indigenous peoples as an axis, we observe that the covid pandemic and the protection of their territories do not have the same force in the current context, the indigenous people are more linked to the protection of their territory. Indigenous peoples have a link of cultural strength in traditional health independent of Covid treatment. It should be noted that government agencies are taking measures regarding the covid pandemic with an effort not marked within the health culture of indigenous peoples.

One challenging problem is the representation of three-dimensional datasets that vary with time. These datasets can be though as a cloud of points that gradually deforms. But point-wise variations lack of information about the overall deformation pattern, and more importantly, about the extreme deformation locations inside the cloud. The present article applies a technique in computational mechanics to derive the strain-rate state of a time-dependent and three-dimensional data distribution, by which one can characterize its main trends of shift. Indeed, the tensorial analysis methodology is able to determine the global deformation rates in the entire dataset. With the use of this technique, one can characterize the significant fluctuations in a reduced multivariate description of an urban system and identify the possible causes of those changes: calculating the strain-rate state of a PCA-based multivariate description of an urban system, we are able to describe the clustering and divergence patterns between the districts of the city and to characterize the temporal rate in which those variations happen.

Seeds can maintain their quality for a limited time; after that, they will lose their germination ability and vigor. Some physiological and physicochemical changes in the structure of the seeds during storage can decrease the quality of the seeds which is known as aging. Therefore, detection of the strong young seeds from the old ones is a vital issue in the modern agriculture. Conventional methods of detection of the seed viability and germination are destructive, time-consuming and costly. In this research, two peanut cultivars, namely North Carolina 2 (NC-2) and Florispan were selected and three artificial aging levels were induced to them. Hyperspectral images (HSI) of the samples were acquired and the seed viability was evaluated using two pre-trained convolutional neural network (CNN) image processing models, AlexNet and VGGNet. The noise of the reflection spectra of the samples was relatively resolved and modified by combining Preprocessing techniques of moving average (MA) and standard normal variate (SNV). Using principal component analysis (PCA), the dimensions were declined and three principal components (PC) were extracted. These PCs were then used as variables in the classification of support vector machine (SVM) and linear discriminant analysis (LDA). The results showed the high capability of CNN architectures such as AlexNet and VGGNet in detection of the seed viability based on the HIS with no pre-processing and feature extraction. The mentioned architectures reached the accuracy of 0.985 and 0.986, respectively. The combination of feature extraction method of PCA with LDA and SVM classifiers showed that the use of a limited number of PCs instead of all wavelengths can decrease the complexity of modeling, while enhancing the efficiency of the models such that LDA and SVM classifiers achieved the accuracy of 0.983 and 0.986 in classification of peanut sees, respectively.

Taking a DNA-sequence, a word with letters/bases A, T, G and C, as the relation between the generators of an infinite group $\pi$, one can discriminate two important families: (i) the cardinality structure for conjugacy classes of subgroups of $\pi$ is that of a free group on $1$ to $4$ bases and the DNA word, viewed as a substitution sequence, is aperiodic. (ii) The cardinality structure for conjugacy classes of subgroups of $\pi$ is not that of a free group, the sequence is generally not aperiodic and topological properties of $\pi$ have to be determined differently. The two cases rely on DNA conformations such as A-DNA, B-DNA, Z-DNA, G-quadruplexes, etc. We found a few salient results: Z-DNA, when involved in transcription, replication and regulation in a healthy situation implies (i). The sequence of telomeric repeats comprising $3$ distinct bases, most of the time, satisfies (i). For $2$-base sequences in the free case (i) or non free case (ii), the topology of $\pi$ may be found in terms of the $SL(2,\mathbb{C})$ character variety of $\pi$ and the attached algebraic surfaces. The linking of two unknotted curves --the Hopf link-- may occur in the topology of $\pi$ in cases of biological importance, in telomeres, G-quadruplexes, hairpins and junctions, a feature we already found in the context of models of topological quantum computing. For $3$- and $4$ base sequences, other knotting configurations are noticed and a building block of the topology is the $4$-punctured sphere. Our methods have the potential to discriminate potential diseases associated to the sequences.

Our recent work has focused on the application of infinite group theory and related algebraic geometric tools in the context of transcription factors and microRNAs. We were able to differentiate between “healthy" nucleotide sequences and disrupted sequences that may be associated with various diseases. In this paper, we extend our efforts to the study of messenger RNA metabolism, showcasing the power of our approach. We investigate (i) mRNA translation in prokaryotes and eukaryotes, (ii) polyadenylation in eukaryotes, which is crucial for nuclear export, translation, stability, and splicing of mRNA, (iii) miRNAs involved in RNA silencing and post-transcriptional regulation of gene expression, and (iv) the identification of disrupted sequences that could lead to potential illnesses. To achieve this, we employ (a) infinite (finitely generated) groups fp, with generators representing the r+1 distinct nucleotides and a relation between them [e.g., the consensus sequence in the mRNA translation (i), the poly(A) tail in item (ii), and the miRNA seed in item (iii)], (b) aperiodicity theory, which connects “healthy groups" fp to free groups Fr of rank r and their profinite completion F^r, and (c) the representation theory of groups fp over the space-time-spin group SL2(C), highlighting the role of surfaces with isolated singularities in the character variety. Our approach could potentially contribute to the understanding of the molecular mechanisms underlying various diseases and help develop new diagnostic or therapeutic strategies.

The fast spread of COVID-19 constitutes a worldwide challenge to the public health, educational, and trade systems, affecting the overall wellbeing of human societies. The high transmission and mortality rates of this virus, and the unavailability of a vaccine or treatment, resulted in the decision of multiple governments to enact measures of social distancing. Thus, it is of general interest to consider the validity of the proposal for keeping a social distancing of at least 2 m from other persons to avoid the spread of COVID-19. The exposure to the bioaerosol can result in the deposition of the pathogen in the respiratory tract of the host causing disease and an immunological response. In the atmospheric context, the work evaluates the effect of aerodynamic diameter (size) of particles in carrying RNA copies of the novel coronavirus. A SARS-CoV-2 carrier person talking, sneezing, or coughing at distance of 2 m can still provide a pathogenic bioaerosol load with submicron particles that remain viable in air for up to 3 hours for exposure of healthy persons near and far from the source in a stagnant environment. The deposited bioaerosol creates contaminated surfaces, which if touched can act as a path to introduce the pathogen by mouth, nose, or eyes and cause disease.

In light of the self-simulation hypothesis, a simple form implementation of the principle of efficient language is discussed in a self-referential geometric quasicrystalline state sum model in three dimensions. Emergence is discussed in context of geometric state sum models.

The antioxidant, antimicrobial, antiproliferative, and enzyme inhibitory properties of five extracts from aerial parts of Salvia pachyphylla were examined to assess the prospective of this plant as a source of natural products with therapeutic potential. Those properties were analyzed performing a set of standard assays. The extract obtained with dichloromethane showed the most variety of components, as yielded promising results in all completed assays. Furthermore, the extract obtained with ethyl acetate exhibited that greatest antioxidant activity as well as the best xanthine oxidase inhibitory activity. Remarkably, both extracts obtained with n-hexane or dichloromethane revealed significant antimicrobial activity against the Gram-positive bacteria; also, they showed greater antiproliferative activity against three representative cell lines of the most common types of cancers in women worldwide, and against a cell line that exemplifies cancers that typically develop drug resistance. Despite that other extracts were less active, such as the methanolic or aqueous, their results are promising for the isolation and identification of novel bioactive molecules.

Transcription factors (TFs) are proteins that recognize specific DNA fragments in order to decode the genome and ensure its optimal functioning. TFs work at the local and global scales by specifying cell type, cell growth and death, cell migration, organization and timely tasks. We investigate the structure of DNA-binding motifs with the theory of finitely generated groups. The DNA ‘word’ in the binding domain -the motif- may be seen as the generator of a finitely generated group Fdna on four letters, the bases A, T, G and C. It is shown that, most of the time, the DNA-binding motifs have subgroup structure close to free groups of rank three or less, a property that we call ‘syntactical freedom’. Such a property is associated to the aperiodicity of the motif when it is seen as a substitution sequence. Examples are provided for the major families of TFs such as leucine zipper factors, zinc finger factors, homeo-domain factors, etc. We also discuss the exceptions to the existence of such a DNA syntactical rule and their functional role. This includes the TATA box in the promoter region of some genes, the single nucleotide markers (SNP) and the motifs of some genes of ubiquitous role in transcription and regulation.

We propose a conceptual model for the closeness parameter $\epsilon$, which characterizes exotic compact objects (ECOs). To estimate $\epsilon$, a thin spherical dust shell is considered, which gravitationally contracts from a specific position $r(t_{0})$ to near its gravitational radius $r(t_{2})=r_{s} + \epsilon$, in a finite time $t_{2}$, measured in the frame of a fiducial observer (FIDO). For an external observer, the shell’s kinematics is characterized by two clearly distinguishable phases: one of rapid contraction, where the shell is far away from the gravitational radius, $r(t_{0})\gg r_{s}$, and a second phase quasi-stationary, $r(t)\sim r_{s}$, where all of the shell’s mass is concentrated around the associated horizon, such that for a FIDO, a black hole (BH)is undistinguishable from a shell configured as a black shell (BS). \\ In the semi-classical approximation $E\ll \kappa_{0}l_{p}^{2}$ and tends to zero when the observation time of collapse $t_{2}$, measured by FIDO, tends to infinity; $\kappa_{0}$ and $l_{p}$ are surface gravity and Planck length, respectively. The quantum effects are significant when $\epsilon\ll r(t_{2})$ and $\epsilon$ tends to $\kappa_{0}l_{p}^{2}$. \\ Without knowing details on quantum gravity, parameter $\epsilon$ is calculated, which, in general, allows distinguishing the ECOs from BHs. Specifically, a BS (ECO) is undistinguishable from a BH.

It is shown that the representation theory of some finitely presented groups thanks to their $SL_2(\mathbb{C})$ character variety is related to algebraic surfaces. We make use of the Enriques-Kodaira classification of algebraic surfaces and the related topological tools to make such surfaces explicit. We study the connection of $SL_2(\mathbb{C})$ character varieties to topological quantum computing (TQC) as an alternative to the concept of anyons. The Hopf link $H$, whose character variety is a Del Pezzo surface $f_H$ (the trace of the commutator), is the kernel of our view of TQC. Qutrit and two-qubit magic state computing, derived from the trefoil knot in our previous work, may be seen as TQC from the Hopf link. The character variety of some two-generator Bianchi groups as well as that of the fundamental group for the singular fibers $\tilde{E}_6$ and $\tilde{D}_4$ contain $f_H$. A surface birationally equivalent to a $K_3$ surface is another compound of their character varieties.

The Kummer surface was constructed in 1864. It corresponds to the desingularisation of the quotient of a 4-torus by 16 complex double points. Kummer surface is kwown to play a role in some models of quantum gravity. Following our recent model of the DNA genetic code based on the irreducible characters of the finite group G5:=(240,105)≅Z5⋊2O (with 2O the binary octahedral group), we now find that groups G6:=(288,69)≅Z6⋊2O and G7:=(336,118)≅Z7⋊2O can be used as models of the symmetries in hexamer and heptamer proteins playing a vital role for some biological functions. Groups G6 and G7 are found to involve the Kummer surface in the structure of their character table. An analogy between quantum gravity and DNA/RNA packings is suggested.

Building roofs are sources of unwanted heat for buildings situated in zones with a warm climate. Thus, reflective coatings have emerged as an alternative to reject a significant fraction of solar energy received by roofs. In this research, the thermal behavior of concrete slab-type roofs with traditional and solar reflective coatings was simulated using a computational tool. Weather data from four cities in Mexico with a warm climate were used as boundary conditions. This tool is an in-house code based on the Finite Volume Method developed by the author to perform building components simulations. The code was validated with experimental data from previous work. A series of comparative simulations were developed, taking a gray roof as a control case. The results showed that for the roof without thermal insulation (single roof), the solar reflective coatings reduced the exterior surface between 11 and 16∘C. Consequently, the single roofs’ daily heat gain was reduced by a factor ranging between 41 and 54%. On the other hand, for the insulated roof, the reflective coatings reduced the exterior surface temperature between 17 and 21∘C. At the same time, the daily heat gain of composite roofs was reduced between 37 and 56%.

We recently proposed that topological quantum computing might be based on $SL(2,\mathbb{C})$ representations of the fundamental group $\pi_1(S^3\setminus K)$ for the complement of a link $K$ in the $3$-sphere. The restriction to links whose associated $SL(2,\mathbb{C})$ character variety $\mathcal{V}$ contains a Fricke surface $\kappa_d=xyz -x^2-y^2-z^2+d$ is desirable due to the connection of Fricke spaces to elementary topology. Taking $K$ as the Hopf link $L2a1$, one of the three arithmetic two-bridge links [the Whitehead link $5_1^2$, the Berge link $6_2^2$, the double-eight link $6_3^2$] or the link $7_3^2$, the $\mathcal{V}$ for those links contains the reducible component $\kappa_4$, the so-called Cayley cubic. In addition, the $\mathcal{V}$ for the later two links contains the irreducible component $\kappa_3$, or $\kappa_2$, respectively. Taking $\rho$ to be a representation with character $\kappa_d$ ($d<4$), with $|x|,|y|,|z| \le 2$, then $\rho(\pi_1)$ fixes a unique point in the hyperbolic space $\mathcal{H}_3$ and is conjugate to a $SU(2)$ representation (a qubit). Even though details on the physical implementation remain open, more generally, we show that topological quantum computing may be developed from the point of view of three-bridge links, the topology of the $4$-punctured sphere and Painlev\'e VI equation. The $0$-surgery on the $3$ circles of the Borromean rings L6a4 is taken as an example.

Recent advancements in artificial intelligence (AI) and deep learning have revolutionized the field of protein engineering, particularly in the area of de novo protein design. This review article explores the impact of AI-driven approaches on protein design, with a specific focus on the role of structure prediction neural networks, such as AlphaFold and RoseTTAFold. The article discusses the paradigm shift brought about by these networks, which have enabled the design of proteins with unique structures and functions that are not found in nature. The review covers various aspects of AI-driven protein design, including the use of protein language models to harness evolutionary information, the development of de novo protein design workflows utilizing deep learning, and the application of generative models like RFdiffusion and RoseTTAFold All-Atom. The article also highlights the successes and applications of AI-driven protein design across diverse domains, such as enzyme engineering, antibody design, and vaccine development. Additionally, the review identifies current challenges and future directions in the field, emphasizing the need to address limitations in modeling conformational dynamics and designing proteins for in vivo functionality. The article concludes by underscoring the potential of AI-driven protein design to transform various aspects of science and technology, while also acknowledging the importance of interdisciplinary collaboration and the development of robust pipelines for the validation and optimization of designed proteins. Overall, this comprehensive review serves as a valuable resource for researchers and practitioners interested in understanding the current state and future prospects of AI-driven protein design.

This study is a synthesis of 159 articles that were selected for their relevance to comprehend key aspects of the Massive Open Online Courses (MOOCs) phenomenon, from a discourse analysis perspective. Since 2011, MOOCs are expanding worldwide so that the number of subscribers outpointed 101 million at the end of 2018. This paper explores the question whether the MOOCs are the embodiment of the global one-world classroom or whether, instead, they represent a low-cost alternative tailored to a segment that doesn´t have enough time or resources to attend a brick-and-mortar college. In addition, the review tackles the link between motivation and low completion rates. Finally, we discuss the need to devise better methods to assess the pedagogical value of MOOCs.

The purpose of this article is to present an IoT architecture implemented in an intelligent environment, focusing on the optimization of initial conditions and device management. A general control system was developed using an open-source platform, integrating aWi-Fi network and YAML coding to enable communication and control of the IoT architecture devices. The implementation includes actuators, sensors, and control devices that, through a graphical interface, allow the visualization of the historical record of activities and real-time measurements of connected devices. The design includes specific mechanisms and the analysis of materials through tensile tests on specimens, following the ASTM E8 standard, and deformation test simulations, in which PLA demonstrated better performance compared to materials like ABS and resin. The significance of the implemented IoT system lies in an energy saving of 58% compared to conventional structures. Additionally, the study of response times for network connections showed that using an Ethernet cable resulted in a response time of 1.21 seconds, representing a reduction of 1.65 seconds compared to the second lowest value obtained.

Peanuts, owing to their composition of complex carbohydrates, plant protein, unsaturated fatty acids, and essential minerals (magnesium, iron, zinc, and potassium), hold significant potential as a vital component of the human diet. Additionally, their low water requirements and nitrogen fixation capacity make them an appropriate choice for cultivation in adverse environmental conditions. The germination ability of seeds profoundly impacts the final yield of the crop, assessing seed viability of extreme importance. Conventional methods for assessing seed viability and germination are both time-consuming and costly. To address these challenges, this study investigated Visible-Near Infrared Spectroscopy (Vis/NIR) in the wavelength range of 500-1030 nm as a non-destructive and rapid method to determine the viability of two varieties of peanut seeds: North Carolina-2 (NC-2) and Spanish flower (Florispan). The study subjected the seeds to three levels of artificial aging through heat treatment, involving incubation in a controlled environment at a relative humidity of 85% and a temperature of 50°C over 24-hour intervals. The absorbance spectra noise was significantly mitigated and corrected to a large extent by combining the Savitzky-Golay (SG) and Multiplicative Scatter Correction (MSC) methods. To identify the optimal wavelengths for seed viability assessment, a range of meta-heuristic algorithms were employed, including world competitive contest (WCC), league championship algorithm (LCA), Genetics (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), imperialist competitive algorithm (ICA), learning automata (LA), heat transfer optimization (HTS), forest optimization (FOA), discrete symbiotic organisms search (DSOS), and cuckoo optimization (CUK). These algorithms offer powerful optimization capabilities for effectively extracting relevant wavelength information from spectral data. Results revealed that all the algorithms demonstrated remarkable accuracy in predicting the allometric coefficient of seeds, achieving correlation coefficients exceeding 0.985 and errors below 0.0036, respectively. In terms of execution time, the ICA (2.3635 seconds) and LCA (44.9389 seconds) algorithms exhibited the most and least efficient performance, respectively. Conversely, the FOA and the LCA algorithms excelled in identifying the least number of optimal wavelengths (10 wavelengths). Subsequently, the seeds were classified based on the wavelengths selected by the FOA (10 wavelengths) and (DSOS (16 wavelengths) methods, in conjunction with logistic regression (LR), decision tree (DT), Multilayer Perceptron (MP), support vector machine (SVM), k-nearest neighbor (K-NN), and NaiveBayes (NB) classifiers. The DSOS-DT and FOA-MP methods demonstrated the highest accuracy, yielding values of 0.993 and 0.983, respectively. Conversely, the DSOS-LR and DSOS-KNN methods obtained the lowest accuracy, with values of 0.958 and 0.961, respectively. Overall, our findings demonstrated that Vis/NIR spectroscopy, coupled with variable selection algorithms and learning methods, presents a suitable and non-destructive approach for detecting seed viability.

Biosensors are analytical devices that utilize biological interactions to detect and quantify clinical biomarkers, contaminants, allergens, and microorganisms. They combine different disciplines including analytical chemistry, molecular biology, and electrical engineering. Biosensors operate by coupling a bioreceptor, such as nucleic acid or proteins, with a transducer that converts the biological interaction into an electrical signal. Electrochemical and optical transduction are commonly used approaches due to their high detection capability and compatibility with miniaturization. Biosensors provide both high specificity and sensitivity and can be integrated into low-cost microfluidic platforms for rapid and point-of-care applications. These attributes make these devices valuable tools in analytical chemistry, particularly for early diagnostic applications. However, conventional biosensors face challenges related to the immobilization of biorecognition elements on the transducer surface, leading to issues like lost of sensitivity and selectivity. To address these problems, the introduction of nanomaterials, particularly magnetic nanoparticles (MNPs) and magnetic beads (MBs), has been implemented. MNPs combine their magnetic properties with other interesting characteristics such as small size, high surface-to-volume ratio, and excellent biocompatibility. They can be tailored for specific applications and have been extensively used in various fields, including biosensing and clinical diagnosis. Furthermore, MNPs simplify sample preparation by isolating target analytes through magnetic separation, thus improving sensitivity, and reducing analysis time and interference phenomena. The synthesis and modification of MNPs play a crucial role in adjusting their properties for different applications. This review presents an overview of the synthesis and surface modifications of magnetic nanoparticles, their role in the development of biosensors and bioassays, and their applications across various scientific areas.

The lithium-ion batteries are widely used as a power source for portable devices, including cell phones. The useful life is about 2 years or 500 cycles, contributing to the generation of waste from electrical and electronic equipment (WEEE). Mining of lithium and cobalt damages the environment and is onerous; therefore, sustainable alternatives, such as obtaining these elements from secondary sources as recycling of lithium-ion batteries, are essential to provide the inputs used in the sector. However, the metallurgical route which will used to recovering them must be considered, due to this work aims for a more environmentally favorable process using DL-malic acid 1.5 M and instead of compared with sulfuric acid 2 M, heat pretreatment of 1 h and 3 h, and for all conditions, experiments were carried out with and without adding the oxidizing agent hydrogen peroxide. The best yields occurred in presence of H2O2 10 % v/v, and heat pretreatment of 1 h: 33.49 % Co and 4.63 % Li, and 29.78 % Co e 3.44 % Li were recovered by sulfuric acid and DL-malic acid, respectively.

Gobies and their ectoparasitic monogenean flatworms are promising models for species diversification because of their species richness. Recent decades have seen the discovery of several new species of Gyrodactylus (Monogenea: Gyrodactylidae) on European gobies, mostly in the sand goby lineage and especially in the Eastern Mediterranean. However, the monogenean fauna of other gobies is much less understood. Therefore, we scrutinized five gobiid species (34 specimens, vouchered, with some representatives sequenced), sampled in Greece, for monogenean ectoparasites. Only specimens of the giant goby Gobius cobitis were infected; they harbored Xenoligophoroides cobitis (Monogenea: Dactylogyridae) on their gills. Here we provide the first record from Greece, and the first ITS rDNA and COI sequences of the representative of this monotypic genus. Also 28S rDNA was sequenced and compared with published data from across its known distribution, suggesting clinal variation. Lack of sequence data of closely related dactylogyrid monogeneans prevents either proposing a sister-group for Xenoligophoroides, or inferring a scenario explaining the presence of a single known member of this genus on gobies. Possible hypotheses include either the ancestral long-term presence on gobiids but “missing the boat” of the diversification events in the “Gobius-lineage”, or a recent host switch from a non-gobiid host.

We find that the degeneracies and many peculiarities of the DNA genetic code may be described thanks to two closely related (fivefold symmetric) finite groups. The first group has signature $G=\mathbb{Z}_5 \rtimes H$ where $H=\mathbb{Z}_2 . S_4\cong 2O$ is isomorphic to the binary octahedral group $2O$ and $S_4$ is the symmetric group on four letters/bases. The second group has signature $G=\mathbb{Z}_5 \rtimes GL(2,3)$ and points out a threefold symmetry of base pairings. For those groups, the representations for the $22$ conjugacy classes of $G$ are in one-to-one correspondence with the multiplets encoding the proteinogenic amino acids. Additionally, most of the $22$ characters of $G$ attached to those representations are informationally complete. The biological meaning of these coincidences is discussed.

This article analyses the environmental impact of the measures imposed during the SARS-CoV-2 pandemic. We compare the evolution of atmospheric pollution levels in recent years and during lockdown, and assess the effects of the decrease in mobility and changes in patterns and lifestyles during the latter period. Thus, the reduction in the risk to human health brought about by the improvement of air quality during the months of confinement through the use of dose-response functions is estimated. The focus of the case study is the island of Tenerife. The island of Tenerife has been selected because it can serve as an example for other sites in Europe. We distinguish between the three areas with the highest population concentrations: the Metropolitan, Southern, and Northern areas. The impacts of air pollution and its relationship with changes in consumption and activity patterns are clearly distinguishable. Therefore, the lessons learned can be easily extrapolated to other areas, in both island and mainland contexts.

Currently, the textile industry is a poorly automated sector, due in part to problems in the handling of deformable leather and textile parts during production operations. In this work, several problems in the handling process of leather and textile parts are addressed, introducing methods to increase the automation of the process. A pneumatic actuator designed to pick up textile or leather parts avoiding their deformation during transport has been developed. This actuator maximizes the number of gripping points to improve handling, making it more stable and efficient. Additionally, a vision system has been implemented in the part picking task which, in conjunction with the CAD information of the part, sends the modified gripping position of the part to the robot. This allows customized handling of each textile or leather part. Finally, validation tests have been carried out on this development, both in simulations and in laboratory conditions, demonstrating its viability and direct applicability in the production line.

Wearable vital signs monitoring and specially the electrocardiogram have taken important role due to the information that provide about high-risk diseases, it has been evidenced by the needed to increase the health service coverage in home care as has been encouraged by WHO. Some wearables devices have been developed to monitor the ECG in which the location of the measurement electrodes is modified respect to the Einthoven model. However, mislocation of the electrodes on the torso can lead to the modification of acquired signals, diagnostic mistakes and misinterpretation of the information in the signal. This work presents a volume conductor evaluation and an ECG signal waveform comparison when the location of electrodes is changed, to find a electrodes’ location that reduces distortion of interest signals. In addition, effect of motion artifacts and electrodes’ location on the signal acquisition are evaluated. A group of volunteers was recorded to obtain ECG signals, the result was compared with a computational model of the heart behavior through the EA ECG, DTW and SNR methods to quantitatively determine the signal distortion. It was found that while the Einthoven method is followed, it is possible to acquire the ECG signal from the patient’s torso or back without a significant difference, and the electrodes position can be moved 6cm at most from the suggested location by the Einthoven triangle in Mason-Likar’s method.

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

Speech signals are degraded in real-life environments, product of background noise or other factors. The processing of such signals for voice recognition and voice analysis systems presents important challenges. One of the conditions that make adverse quality difficult to handle in those systems is reverberation, produced by sound wave reflections that travel from the source to the microphone in multiple directions.To enhance signals in such adverse conditions, several deep learning-based methods have been proposed and proven to be effective. Recently, recurrent neural networks, especially those with long and short-term memory (LSTM), have presented surprising results in tasks related to time-dependent processing of signals, such as speech. One of the most challenging aspects of LSTM networks is the high computational cost of the training procedure, which has limited extended experimentation in several cases. In this work, we present a proposal to evaluate the hybrid models of neural networks to learn different reverberation conditions without any previous information. The results show that some combination of LSTM and perceptron layers produce good results in comparison to those from pure LSTM networks, given a fixed number of layers. The evaluation has been made based on quality measurements of the signal's spectrum, training time of the networks and statistical validation of results. Results help to affirm the fact that hybrid networks represent an important solution for speech signal enhancement, with advantages in efficiency, but without a significan drop in quality.

This article addresses the problem of formation control of a quadrotor and one (or more) marine vehicles operating at the surface of the water with the end goal of encircling the boundary of a chemical spill, enabling such vehicles to carry and release chemical dispersants used during ocean cleanup missions to break-up oil molecules. Firstly, the mathematical models of the Medusa class of marine robots and quadrotor aircrafts are introduced, followed by the design of single vehicle motion controllers that allow these vehicles to follow a parameterized path individually using Lyapunov based techniques. At a second stage, a distributed controller using event triggered communications is introduced, enabling the vehicles to perform cooperative path following missions according to a pre-defined geometric formation. In the next step, a real time path planning algorithm is developed that makes use of a camera sensor, installed on-board the quadrotor. This sensor enables the detection in the image of which pixels encode parts of a chemical spill boundary and use them to generate and update in real time a set of smooth B-spline based paths for all the vehicles to follow cooperatively. The performance of the complete system is evaluated by resorting to 3-D simulation software, making it possible to simulate visually a chemical spill. Results from real water trials are also provided for parts of the system, where two Medusa vehicles are required to perform a static lawn-mowing path following mission cooperatively at the surface of the water.

SARS-CoV-2 infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. However, strategies to predict the course of SARS-CoV-2 infection in CVD patients at the time of hospital admission are still missing. Here, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 participants, including 20 uninfected and 37 acutely SARS-CoV-2-infected CVD patients and 37 healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T cell subsets. Moreover, we identified an immune signature characterised by mucosal-associated invariant T (MAIT) cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.

The main challenges in oil platforms are how to define optimal setpoints and decision-making for controlling variables due to many existing dynamical production uncertainties while conceding safe operation and minimizing discharge to sea and atmosphere without killing plantwide inventory. A novel scheduling model to optimize the whole essential units of an oil platform production gathering topside and subsea variables is disclosed. A proper topside and subsea scheduling model enables and creates harmony between optimal production, supply chain, costs, and market dynamics, satisfying demands, environmental and operations constraints leading to stability. The interest of the present research lies in determining the optimal topside and subsea operational settings and decision-making, establishing maximum E&P performance and production control setpoints while predicting and manipulating reservoir lifespan and its revitalization. This objective is attained through a novel multiperiod large-scale model for the planning and operational production scheduling and model predictive control (MPC) in oil platforms complying with sustainability, profitability, platform design capacities, and offloading of oil and gas to supply chains or to pipeline exportation. The present model details heat and mass transfer, PVT, flow profiles along a planning horizon and can be used to any oil platform since comprises all the essential unit operations for oil, gas, CO₂, H₂S and water. The model maximizes the total oil production over any planning horizon. The model is versatile, and decision-making can be either linear or nonlinear but rather a MILP or LP as best choice on optimizing large-scale systems. If the model is applied with auto rescheduling on site within variable hours or minutes, it becomes a real-time optimization schedule approach. Due to its high-velocity performance and robustness, a novel multi-objective function strategy, acting as an LP generic plantwide MPC with industrial scope to maximize production while controlling the process is presented, and as an example is here used to control slug flow to avoid equipment trips and inventory instability, at the same time production is maximized. The output from the decision-making was compared to actual plant data, and the results proved compliance to the design capacity with process safety and sustainability. Comparing to official Brazil's government data for oil, the case study showed superiority to the same size platforms, like FPSOs P-75 and MV32, e.g., more than 101.5% more capacity to produce oil in beginning of campaign after first oil, and 10.5% during campaign. The present work indicates that: 1) the production of millions of barrels is being delayed or left aside; 2) not scheduling production harms the environment and diminish process safety; 3) not scheduling production can create stochastic supply chain deliveries instead of organizing it by deterministic offloading days; 4) scheduling is essential to manipulate, revitalize and monitor reservoir's pressure and content under uncertainty; 5) the oil platform can be automatic optimized by a plantwide MPC reducing human activity/dependency; 6) scheduling gives more transparency to stakeholders and contractors by forecasting business data and capability, and can design, develop or enable new businesses.

Maritime ports represent an important ecosystem for pollutant emissions and, taking into account the ongoing energy transition, need to adopt new solutions to mitigate current emission levels. These emissions are partially avoidable if ships and vessels docked at the port use electric energy to feed their internal power needs instead of using their internal combustion engines. In Europe, there is an ongoing discussion on including such emissions in the European Emissions Trading System which will represent added costs for maritime operators. Onshore Power Supply systems can contribute to the ongoing energy transition by allowing the use of electric power to feed docked ships. As a first step to contribute to the development of Onshore Power Supply solutions, it is necessary to evaluate the added power needs that these systems would represent for the port. This paper presents a methodology that allows port operators to verify, straightforwardly and transparently, their power needs for Onshore Power Supply applications. The methodology is based on the historical data of docked ships at the port or quay level and provides an energy analysis of each type of vessel to determine the power to be installed at the port so that it is possible to supply energy to different types of ships and vessels simultaneously. Additionally, the implemented methodology provides economic and technical decision support factors by comparing the fuel costs with electric power costs, assessing the potential for this transition to Onshore Power Supply. The methodology is validated using a real case study for the port of Lisbon and obtained results demonstrate the potential for the installation of Onshore Power Supply in medium to large-dimension maritime ports.

This paper proposes the use of non-uniform extended surfaces installed externally to the tubes of the radiation section of fired heaters, in order to obtain a better heat flux distribution to the coils. To this end, the heat transfer mechanisms present in such equipment were studied through computational fluid dynamics (CFD), using simplified geometries that represent typical sizes of fired heaters. Also, a simplified model for the combustion was considered. Although this model oversimplifies the physics of the problem, it was able to give satisfactory results for the parameters being optimized, considering the main objective of this paper, that is to minimize the non-uniformity of heat flux in the tubes of the radiant section of fired heaters. It was possible to obtain optimized geometric parameters for different types of extended surfaces evaluated, coupling the results of these models with the Particle Swarm optimization method through the use of a response surface technique,. The results indicate a significant improvement in the uniformity of the heat flux distribution to the tubes through the use of the proposed extended surfaces. Thus, this solution reveals to be an interesting alternative to reduce the risks of fluid degradation and coking formation. Future studies must investigate the non-uniformity of the heat flux due to the presence of the flame and consider the interaction between the reactive flow and the participating medium. Nevertheless, this paper presents some results that justify the optimization of such extended surfaces taking into consideration thermal radiation.

Considering the predictions from the standard model of particle physics coupled with experimental results from particle accelerators, we discuss a scenario in which from the infinite possibilities in the Lie groups we use to describe particle physics, nature needs only the lower dimensional representations - an important phenomenology that we argue indicates nature is code theoretic. We show that the quantum deformation of the SU(2) Lie algebra at the fifth root of unity can be used to address the quantum Lorentz group representation theory through its universal covering group and gives the right low dimensional physical realistic spin quantum numbers confirmed by experiments. In this manner we can describe the spacetime symmetry content of relativistic quantum fields in accordance with the well known Wigner classification. Further connections of the fifth root of unity quantization with the mass quantum number associated with the Poincaré Group and the SU(N) charge quantum numbers are discussed as well as their implication for quantum gravity.

We set a feasible method to produce tailored collagen scaffolds and analyzed its potential for corneal engineering. Collagen-vitrigel membranes (CVM) were produced with a 1:1 ratio of Dulbecco’s Modified Eagle’s medium (DMEM), 1% antibiotics and 8% fetal bovine serum, and 5mg/mL collagen type I. Three volumes of collagen were used: 1X (2.8 L/mm2 of collagen), 2X, and 3X. Vitrification was done at 40% relative humidity (RH), 40° C, and 30 rpm using a matryoshka system set with a shaking-oven and a desiccator with a saturated K2CO3 solution. The CVM was characterized for width, microstructure, transparency, and biocompatibility using NIH3T3 cells. Surgical manipulation was assessed in an ex vivo corneal model. Constructs of corneal endothelial cells (CECs) and 2X-CVM were transplanted into five 18-month-old White New Zealand rabbits. CVM exhibited homogeneous surface and laminar organization. Membrane width increased with gel volume from 3.65µm to 7.2µm. 1X and 2X-CVM exhibited a 99% transmittance. NIH3T3 cells concentration increased 3-fold within 48 h with no significant difference among the 3 CVM (p = 0.323). The 2X-CVM was surgically manipulable. Transplantation of corneal endothelial cells (CECs) seeded over 2X-CVM restored corneal endothelium. The matrioshka system is a feasible method that yields CVM suitable for corneal engineering.

This review documents an emerging body of evidence concerning the neurological effect of polycyclic aromatic hydrocarbon (PAH) exposure, with regard to cognitive function and increased risk of neurodegeneration. Two electronic databases PubMed and Web of Science were systematically searched. The 37/428 studies selected included outcomes measuring cognitive function, neurobehavioral symptoms of impaired cognition, and pathologies associated with neurodegeneration from prenatal (21/37 studies), childhood (14/37 studies), and adult (8/37 studies) PAH exposure. Sufficient evidence surrounding prenatal exposure negatively impacting child intelligence, mental development, average overall development, verbal IQ, memory impairment, externalizing, internalizing, anxious, depressed behaviours, behavioural development and child attentiveness was found. Evidence concerning exposure during childhood and as an adult was scarce and highly heterogeneous, however presence of neurodegenerative biomarkers and increased concentrations of cryptic “self” antigens in serum and cerebrospinal fluid samples suggest a higher risk of neurodegenerative disease. Associations with lowered cognitive ability, and impaired attentiveness were found in children and memory disturbances, specifically auditory memory, verbal learning and general memory in adults. Although evidence is not yet conclusive and further research is needed the studies included supported the hypothesis that PAH exposure negatively impacts cognitive function and increases the risk of neurodegeneration in humans, and recommends considering the introduction of a variable “rural vs. urban” as covariate for adjusting analyses where the neurological functions affected (as result of our review) are outcome variables.

The present study evaluates the psychometric properties of the Conflicts in Romantic Relationships Over Facebook Use Scale with a sample of Puerto Rican adults. A total of 577 Puerto Ricans participated on this confirmatory and psychometric study. The results confirmed that the scale has a multidimensional structure. These dimensions are: Partner Facebook intrusion, Conflict over Facebook use, and Jealousy over Facebook use. A total of 18 items complied with the criteria of discrimination and presented appropriate factorial loads (6 items per dimension). The Cronbach’s Alpha indexes of the dimensions ranged between .87 and .95 and the omega coefficients ranged between .88 and .95. In summary, the instrument has the appropriate psychometric properties to continue with validation studies, as well as to be implemented in various work areas, both theoretical and applied.

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.

Abstract: Early assessment of crop development is a key aspect of precision agriculture. Shortening the time of response before a deficit of irrigation, nutrients and damage by diseases is one of the usual concerns in agriculture. Early prediction of crop yields can increase profitability in the farmer's economy. In this study we aimed to predict the yield of four maize commercial hybrids (Dekalb7508, Advanta9313, MH_INIA619 and Exp_05PMLM) using remotely sensed spectral vegetation indices (VI). A total of 10 VI (NDVI, GNDVI, GCI, RVI, NDRE, CIRE, CVI, MCARI, SAVI, and CCCI) were considered for evaluating crop yield and plant cover at 31, 39, 42, 46 and 51 days after sowing (DAS). A multivariate analysis was applied using principal component analysis (PCA), linear regression, and r-Pearson correlation. In the present study, highly significant correlations were found between plant cover with VIs at 46 (GNDVI, GCI, RVI, NDRE, CIRE and CCCI) and 51 DAS (GNDVI, GCI, NDRE, CIRE, CVI, MCARI and CCCI). The PCA indicated a clear discrimination of the dates evaluated with VIs at 31, 39 and 51 DAS. The inclusion of the CIRE and NDRE in the prediction model contributed to estimate the performance, showing greater precision at 51 DAS. The use of RPAS to monitor crops allows optimizing resources and helps in making timely decisions in agriculture in Peru.

Soil contamination with toxic heavy metals, such as lead (Pb), is a critical environmental issue with adverse effects on ecosystems. Cymbopogon citratus, known as lemongrass, is a medicinal plant with phytoremediation potential for Pb-contaminated soils, besides producing essential oil (EO) and bioactive compounds. Azospirillum brasilense is a plant growth promoting bacteria, and its inoculation into the soil can benefit plants in many ways, such as increased root growth and improved nutrient absorption. This study aimed to investigate the phytochemistry of lemongrass inoculated with A. brasilense and grown in Pb-contaminated soil to assess its responses to inoculation under different Pb levels. The experimental design was completely randomized in a 2 x 5 factorial scheme: two levels of A. brasilense (absence or presence) and five Pb levels (0, 50, 100, 300, and 500 mg Pb kg–1 of soil), totaling 60 experimental plots in ten treatments with six replicates. After four months of treatment, was analyzed total and reducing sugars, total phenolic content, flavonoids, antioxidant activity, antioxidant enzymes, proline, and EO content and composition. Soil Pb levels and A. brasilense inoculation affected phytochemical in lemongrass plants. Azospirillum inoculation reduced total sugars in the roots at all soil Pb levels, while increasing Pb levels favored a rise in sugar contents. There was an increase in flavonoid content in treatments associated with Pb and inoculated with A. brasilense. Antioxidant capacity was lower at lower Pb levels, regardless of bacterial inoculation. Enzymatic response was mainly affected by Pb concentrations between 50 and 100 mg kg–1 soil. EO content was influenced by soil Pb levels, with higher EO production at 500 mg Pb kg–1 soil and without A. brasilense inoculation. Overall, lemongrass cultivation in Pb-contaminated areas can be an alternative for phytoremediation and EO production for the industry. Moreover, A. brasilense inoculation proved to be beneficial in mitigating stress caused by high Pb concentrations in contaminated soils.

Augmented and Virtual Reality have been experiencing a rapidly growth in recent years, but there is not still a deep knowledge on their capabilities and where they could be explored. In that sense, this paper presents a study on the accuracy and repeatability of the Microsoft's HoloLens 2 (Augmented Reality device) and HTC Vive (Virtual Reality device) using an OptiTrack system as ground truth. For the HoloLens 2, the method used was hand tracking, while in HTC Vive, the object tracked was the system's hand controller. A series of tests in different scenarios and situations were performed to explore what could influence the measures. The HTC Vive obtained results in the millimetre scale, while the HoloLens 2 revealed not so accurate measures (around 2 centimetres). Although the difference can seem to be considerable, the fact that HoloLens 2 was tracking the user's hand and not an inherit controller made a huge impact. The results were considered a significant step for the on going project of developing a human-robot interface to program by demonstration an industrial robot using Extended Reality, which shows great potential to succeed based on this data.

As sessile organisms, plants face a wide range of abiotic stresses, with salinity being a prominent constraint affecting their growth, development, and productivity, particularly in arid and semi-arid regions. This study focused on understanding how salinity impacts Jatropha curcas, an important oilseed plant for biodiesel production. By examining the anatomy and ultrastructure of stomata and chloroplasts, we investigated the effects of prolonged salinity stress on J. curcas. This stress led to changes in stomatal density, stomatal index, and ostiole aperture, which case an imbalance of water conductivity in the xylem. Through transmission electron microscopy, we explored the subcellular organization of J. curcas chloroplasts and their contribution to plant photosynthetic efficiency, providing insights into their role in this process. Notably, salinity treatment resulted in a significant increase in starch granules accumulation, leading to impaired the granal and stromal grana lamellae, destroying this ultrastructure. Our findings indicate that the anatomy and ultrastructure of chloroplasts play a crucial role in influencing photosynthetic efficiency and hydraulic conductivity. This study offers new perspectives on the structure and function of chloroplasts in J. curcas, presenting innovative opportunities to develop strategies that enhance biofuel production in areas with high soil salinity.

The rationalization and modeling of an electric discharge in a fluid require the knowledge of electron swarm parameters. In this work, transport coefficients of alcohols, including methanol, ethanol, propanol, and butanol are reported. The electron energy distribution function, mean energy, reduced mobility, and diffusion coefficient, are calculated using the two-term expansion of the electron Boltzmann equation in the frame of BOLSIG+ and the Monte Carlo collision code METHES. For such, experimental and theoretical values of the electron-alcohol collision cross-section, covering a range of electron impact energy from 1 eV to 1000 eV, are employed. A temperature of 300K, reduced fields E/N between $1-10^4$ Td (1Td = $10^{-21}~\rm Vm^2$), and Plasma density of $10^{19}~\rm m^{-3}$ were used in simulations. The calculated coefficients are compared with data available from previous studies.

Enterococcus faecalis is a bacterium that can develop a multidrug resistance profile associated with the community as well as nosocomial-acquired infections. Among the treatment options for these infections are aminoglycosides combined with bacterial cell wall inhibitors such as beta-lactams, since E. faecalis is intrinsically resistant to aminoglycosides. One of its most representative resistance mechanisms is the expression of aminoglycoside-modifying enzymes, such as the aminoglycoside phosphotransferase type IIIa of E. faecalis (EfAPH(3')-IIIa). This enzyme acts by phosphorylating aminoglycosides in an ATP-dependent reaction, modifying the 3' position of hydroxyl groups of these antibiotics. Considering this scenario, 3,092 natural products obtained from the ZINC22 database were analyzed to select molecules with the highest affinity for the nucleotide-binding pocket of EfAPH(3')-IIIa, which could be potential aminoglycoside adjuvants. The molecules that showed the best-score results obtained from ensemble docking-based virtual screening were ZINC000000952700 (BS-1), ZINC000014793040 (BS-2) and ZINC000015498603 (BS-3). The most promising results were for BS-2, a flavone derivative, due to its improved stability profile in molecular dynamics simulation (average values of RMSD of 0.23 nm, and Rg of 1.94 nm), binding free energy calculations (average ΔG total of -35.3 nm), as well as better toxicological profile (lower probability of hepatotoxicity, carcinogenic, immunotoxicity, mutagenicity, and cytotoxicity effects), compared to BS-1 and BS-3. These results allow us to propose that a flavone derivative may act as an adjuvant to aminoglycosides in the treatment of E. faecalis infections, acting as an inhibitor in the nucleotide-binding pocket of EfAPH(3')-IIIa.

Model-based image reconstruction has brought improvements in terms of contrast and spatial resolution to imaging applications such as magnetic resonance imaging and emission computed tomography. However, their use for pulse-echo techniques like ultrasound imaging is limited by the fact that model-based algorithms assume a finite grid of possible locations of scatterers in a medium -- which does not reflect the continuous nature of real world objects and creates a problem known as off-grid deviation. To cope with this problem, we present a method of dictionary expansion and constrained reconstruction that approximates the continuous manifold of all possible scatterer locations within a region of interest. The expanded dictionary is created using a highly coherent sampling of the region of interest, followed by a rank reduction procedure based on a truncated singular value decomposition. We develop a greedy algorithm, based on the Orthogonal Matching Pursuit (OMP), that uses a correlation-based non-convex constraint set that allows for the division of the region of interest into cells of any size. To evaluate the performance of the method, we present results of 2-dimensional ultrasound image reconstructions with simulated data in a nondestructive testing application. Our method succeeds in the reconstructions of sparse images from noisy measurements, providing higher accuracy than previous approaches based on regular discrete models.

: Background: Overweight and obesity are major risk factors for many chronic diseases, and weight-loss interventions often include systematic exercising and nutritional supplements. The purpose of this study was to determine the independent/synergistic effects of Spirulina maxima supplementation (6-week, 4.5 g/day) and a systematic physical exercise program (6 weeks/ 2 times) on body composition and cardiorespiratory fitness of overweight and obese subjects. Methods: 27 overweight and 25 obese sedentary male subjects were assigned to four interventions through a randomized double-blind, crossover controlled trial: Physical exercise program with (SE) or without (Ex) Spirulina maxima or no-exercise program with (Sm) and without (C) Spirulina maxima. Body composition and cardiorespiratory fitness parameters were taken during a maximal intensity test. Results: As compared to C group, SE, Sm and Ex groups reduced (p < 0.05) their body fat percentage while improving their maximal oxygen uptake (VO₂max; r = −0.40), being obese subjects more benefited. Weight loss, time to reach fatigue and onset of blood lactate accumulation were improved in both Spirulina maxima supplemented groups, regardless the subjects’ body composition. Conclusions: Spirulina maxima supplementation synergistically improves the effects of systematic exercise in body composition and cardiorespiratory fitness parameters in overweight but mostly in obese adults.

Accurate power curve modelling is essential to continuously evaluate the performance of a wind turbine (WT). In this work, we characterize the wind power curves using SCADA data acquired at a frequency of 5 minutes in a wind farm (WF) consisting of 5 WTs. Regarding the non-parametric methods, we select artificial neural networks (ANNs) to make curve estimations. Given that, we have the curves provided by the manufacturer of the WTs given by some very precisely measured pair of wind speed and power points. We can evaluate the difference between the manufacturer characterization and the ones estimated with the data provided by the SCADA system. Before the estimation, we propose a method of filtering the anomalies based on the characteristics provided by the manufacturer. We use three-quarters of the available data for curve estimation and one-quarter for the test. One WT suffered a break in the test part, so we can check how the test estimates reflect this problem in its wind-power curve compared to the estimations obtained in the WTs that worked adequately.

A model for enabling the production of lower carbon cement paste is proposed in this research. The model is based on predicting the strength of cement pastes with partial replacement of wheat straw ash (WSA) and silica fume (SF), two major wastes of agricultural and industrial production. The model is set up based on response surface methodology and Box-Behnken design, and included a suite of mechanical tests with distinct replacements following a micro an meso characterization. The model shows capability for predicting strength of any cement paste, including partial substitution of WSA and/or SF at any combination level with excellent accuracy, which is verified with three validation mixtures demonstrating maximum errors of less than 6% at the three ages. The analysis of the response surface evidences that any cement replacement in the range of 0-20% WSA and above 5% SF allows the reduction of the carbon footprint by maximizing the incorporation of both wastes. The proposed model can be used by setting the required strength of cement paste and calculating the maximum possible replacement, which should contribute to making the construction industry more sustainable by utilizing local waste.

Precise HDV-RNA detection and quantification are pivotal for accurate diagnosis and monitoring of response to newly approved treatment. We evaluate the performance of three assays: Hepatitis Delta RT-PCR system, EurobioPlex HDV assay, and the RoboGene HDV RNA Quantification kit 2.0, testing 151 HBsAg-positive samples, 90 HDV-RNA negative and 61 HDV-RNA positive. We also evaluated serial dilutions of the WHO international standard for HDV, PEI 7657/12. Finally, all HDV-RNA positive samples were genotyped using a next-generation sequencing strategy. Qualitative results indicated a 100% concordance between tests. Quantitative results correlated well between tests, r2=0.703 (Vircell-vs-Eurobio), r2=0.833 (Vircell-vs-RoboGene), r2=0.835 (Robogene-vs-Eurobio). Bias index was 2.083 (Vircell-vs-Eurobio), -1.283 (Vircell-vs-RoboGene), and -3.36 (Robogene-vs-Eurobio). Using the WHO IS, Vircell overestimated the viral load by 0.98 log IU/mL, Eurobio by 1.46 log IU/mL, and RoboGene underestimated it by 0.98 log IU/mL. Fifty-nine samples were successfully genotyped (Genotype 1, n=52; Genotype 5, n=7; Genotype 6, n=1), with similar results in terms of correlation and bias. The three assays demonstrate promising performance. Their accuracy, reflected in concordance rates and quantitative analysis, makes them suitable for clinical practice. However, in the absence of assay harmonization, quantitative HDV RNA monitoring should be performed in the same laboratory and assay to avoid variability.

The aim of this study was to use latent profile analysis to identify specific profiles of burnout syndrome in combination with work engagement and to identify whether job satisfaction, psychological well-being, and other sociodemographic and work variables affect the probability of presenting a profile of burnout syndrome and low work enthusiasm. A total of 355 healthcare professionals completed the Spanish Burnout Inventory, the Utrecht Work Engagement Scale, the Job Satisfaction Scale, and the Psychological Well-Being Scale for Adults. Latent profile analysis identified 4 profiles: 1) burnout with high indolence (BwHIn); 2) burnout with low indolence (BwLIn); 3) high engagement, low burnout (HeLb); and 4) in the process of burning out (IPB). Multivariate logistic regression showed that a second job in a government health care institution; a shift other than the morning shift; being divorced, separated or widowed; and work load are predictors of burnout profiles with respect to the HeLb profile. These data are useful for designing intervention strategies according to the needs and characteristics of each type of burnout profile.

The objective of this research was to study the dynamics of moisture and nutrition at the root zone and to quantify the variables linked to efficient water management in avocado orchards of mid and high-lands of Michoacán, México, in typical Andisols of low fertility with (A)C(w2) and C(w2) climates, respectively. Using the FDR (Frequency Domain Reflectometry) technology, the dynamics of soil moisture and salinity were recorded daily at four depths: 0-15, 15-30, 30-45, and 45-60 cm. The soil moisture balance model was used to determine actual evapotranspiration (ETr), crop coefficient (Kc), and water use efficiency (WUE). Results indicated that ETr is 66-73% of the total water at 0-30 cm depth; the fertilizer absorption is limited to 0-30 cm, being negligible at deeper layers. The water use efficiency is 4.4 to 5.6 kg of fruit m-3 of applied water, and the ratio of the water use index (ETr/irrigation sheet applied, ISA) is 0.65-0.70; while the annual avocado Kc is 0.72 in Cutzato and 0.78 in Tiamba. We concluded that avocado has a low water requirement, it does not cause leaching of nutrients and/or water, the absorption of water and nutrients mostly occurs at 30 cm depth, and from a hydrological point of view, the crop is environmentally friendly.

The historical and cultural use of food as a remedy for diseases is evident in societies, such as using Hibiscus sabdariffa to address conditions like hypertension and high blood glucose. The natural biocompounds in this plant, including Delphinidin-3-Sambubioside (DS3), Quercetin (QRC), and Hibiscus Acid (HA), have been linked to various health benefits. Despite individual attention, molecular targets for these compounds remain unclear. In this study, in-silico analysis employed bioinformatic tools; including Swiss Target Prediction, ShinnyGo 0.77, KEGG, and Stringdb, to identify molecular targets, pathways, and hub genes. A PubMed literature search complemented the results. DS3 demonstrated potential modifications in genes related to nitrogen and glucose metabolism, inflammation, angiogenesis, and cell proliferation, particularly affecting the PI3K-AKT pathway. QRC displayed interconnected targets across multiple pathways, with overlap with DS3 and a focus on cancer-related pathways. HA showed distinct targets, particularly associated with nervous system-related pathways. These findings highlight the need for targeted research on the molecular effects of DS3, QRC, and HA, providing valuable insights into potential therapeutic pathways.

This article aims at presenting the results that were found in the design and implementation of a new management model of Critical Success Factors for improving the effects of research projects. The model was based on the theory of structural equations derived from factor analyses and multiple linear regression models. For achieving the purpose, the authors developed an empirical evidence analysis founded on a literature review in the knowledge area of project management. Afterwards, the process of identification of the CSFs was carried out for a group of research projects launched in Colombia as a result of the application and measurement of an instrument. They were the basis for the development of a structural relationship modeling. Also, this contributed to determine the CSFs that explain the generation of effects of research projects, and the project management execution process from which it can be carried out based on said measurement indicators.

A reliability-based criterion to estimate strength amplification factors for buildings with asymmetric yielding located within a seismic region presenting different soil conditions is proposed and applied. The approach involves the calculation of the mean annual rate of exceedance of structural demands of systems with different levels of asymmetric yielding. Two simplified mathematical expressions are developed considering different soil conditions of the valley of Mexico. The mathematical expressions depend on the ductility of the structural systems, their level of asymmetric yielding, their fundamental vibration period and the dominant period of the soil. In addition, the proposed expressions are compared with that recommended by the current Mexico City Building Code (MCBC). Since the expressions are developed with the help of simplified structural systems, the validity of such expressions is corroborated by comparing the expected ductility demand of multi-degree of freedom (MDOF) structural systems with respect to that of their equivalent simplified systems. Both structural representations are associated with a given annual rate of exceedance value of an engineering demand parameter. The expressions proposed in this study will be incorporated in the new version of the MCBC.

Abstract: The purpose of this review is to summarize recent knowledge on the main processes that occur during wound healing, including the responses of various cell types and the molecular mechanisms involved. Particular attention is also dedicated to new therapies often involved in the resolution of wounds, whether acute or chronic. Awareness of these dynamics is important for the various professional figures who are confronted with these kinds of problem daily. However, the study of the healing mechanisms has yet to be defined in detail, in fact there are alterations of variously coordinated events which lead to a delayed resolution or, as in the case of keloids, to pathological states consisting in the excessive formation of scars with consequences yet to be seen. to define. Therefore, it is necessary to know the most feasible approaches and the most effective therapies.

The initial development of seahorse juveniles is characterized by low digestion capabilities. Stable isotope analysis is an effective tool in studies of trophic food webs and animal feeding patterns. The present study provides new insights for the understanding of growth and food assimilation in early developing seahorses following a laboratory diet switch. The study was performed in early life stages of the seahorse Hippocampus reidi by assessing the influence of diet shift on changes and turnovers in carbon (δ13C) and nitrogen (δ15N) stable isotope in juveniles. Newborn seahorses were fed for 60 days following two feeding schedules (A6 and A11) based initially on copepods Acartia tonsa and subsequently on Artemia nauplii (since days 6 and 11, respectively). After prey shift, we determined δ13C and δ15N turnover rates as functions of change in either body mass (fitting model G) and days of development (fitting model D), contributions of metabolism and growth to those turnover rates, and diet-tissue discrimination factors. Survival, final dry weight and final standard length for diet A11 were higher compared to diet A6. The shift from copepods to Artemia lead to fast initial enrichments in δ13C and δ15N. Afterwards, the enrichment was gradually reduced until reaching the isotopic equilibrium with diet. In most cases, both fitting models performed similarly. The isotopic analysis revealed that 100% of tissue turnover was attributed to growth in diet A11, whereas 19-25% was endorsed to metabolism in diet A6. Diet-tissue discrimination factors were estimated for the first time in seahorse juveniles, resulting in higher estimates for diet A11 (2.9 ± 0.7‰ for δ13C; 2.5 ± 0.2‰ for δ15N) than in diet A6 (1.8 ± 0.1‰ for δ13C; 1.9 ± 0.1‰ for δ15N). This study highlights the relevance of feeding on copepods and their effect on isotopic patterns and discrimination factors in seahorse juveniles after a dietary shift. Regarding the application of the results achieved to feeding schedules in the rearing of H. reidi, a long period of feeding on copepods during the first days of development is highly recommended.

Accurately glacier mapping is crucial for understanding climate change impacts, but existing efforts may be biased due to overlooking spatial autocorrelation during map validation. To address this, we compared several widely used machine learning algorithms as gradient boosting machines (GBM), k-nearest neighbor (KNN) and random forest (RF) with parametric logistic regression (GLM) and an unsupervised remote sensing-based method (NDSI) for mapping Peru's glacier regions in a thoughtful experimental setup. Spatial and non-spatial cross-validation methods were used to evaluate model’s performance and compared with a fully independent test set. Performance differences of up to 18% were found between bias-reduced (spatial) and overoptimistic (non-spatial) cross-validation results when compared to independent test set, emphasizing the need to consider spatial autocorrelation when using machine learning for glacier mapping. K-nearest neighbors (KNN) was the overall best model across regions consistently demonstrating the highest performance followed by logistic regression (LR) and gradient boosting machines (GBM). Our novel validation approach, accounting for spatial characteristics, provides valuable insights for glacier mapping studies and future efforts on glacier retreat monitoring. Incorporating this approach improves the reliability of glacier mapping, guiding future national-level initiatives.

In the age of social media, images come from unreliable sources that may change their content to fit a narrative. Automated detection of forged images is a complex task, especially considering recent technological advances in image manipulation software. However, in the existing literature, it is possible to identify two general approaches adopted by detection methods, active and passive. Active techniques preemptively act on an image by inserting structures before any manipulation is made that can verify its authenticity. In contrast, passive methods analyze the content of an image in search of traces of manipulation. In this way, this research proposes a novel approach to image manipulation detection, combining two passive methods through neural networks, creating a generalist approach capable of detecting with greater accuracy than the methods that compose it. Furthermore, this work used a combination of four datasets available in the literature for training and evaluation. After training, the merged approach obtained an accuracy of 89.59% in the set of validation images, significantly higher than the model trained with only unaltered images, which obtained 78.64%, and the two other models trained using images with a feature selection method applied to enhance inconsistencies that obtained 68.02% for Error-Level Analysis images and 50.70% for the method using Discrete Wavelet Transform. In addition to the performance improvement, the proposed approach’s accuracy variation was lower than the other models.

Introduction: Determination of radiological bone age (BA) is a diagnostic method that consists of estimating chronological age (CA) from the bone maturation of children. Although environmental and hormonal factors can interfere with bone ossification, the process is essentially dependent on ancestral inheritance. These ethnic backgrounds are not usually considered, which can lead to biased interpretations and inadequate decision-making by pediatricians or forensic experts. The objective of this study was to determine the precision and accuracy of these radiological procedures among different ethnic groups. Methods: A qualitative systematic review carried out following MOOSE statement and previously registered in the International Prospective Registry of Systematic Reviews PROSPERO (CRD42023449512). Search was performed in MEDLINE (PubMed) (n=561), Cochrane Library (n=261), CINAHL (n=103), Web of Science (WOS) (n=181) and public institutional repositories (n=37) from inception to 31st December 2022 using Mesh as “Diagnostic Techniques and Procedures”, “Diagnostic imaging”, “Radiography”, “Age Determination by Skeleton” and free terms combining with booleans “AND” and “OR”. PEDro scale, and Risk of Bias in non-randomized Studies of Exposure (ROBINS-E) were used to assess methodological quality and risk of bias of included studies respectively. Results: 51 articles (n=19,531) were included according to the inclusion criteria previously established. There was a good to moderate methodological quality and a high to very high risk of bias. Skeletal methods for determining BA were precised in terms of intra-observer and inter-observer reliability in all ethnic groups. Regarding to accuracy of Skeletal methods in Caucasians and Hispanic children, GPA was accurate at all ages, but in youths, TW3 RUS could be a consistent alternative. In Asian and Arab, GPA and TW3 overestimated BA in adolescents near adulthood. In African youths, GPA overestimated BA while TW3 was more accurate in estimating CA. Dental and Cervical radiographic methods are equally precise but lesser accurate than Skeletal BA determination. Conclusion: Skeletal radiographic methods GPA and TW3 are both precise for BA determination among all ethnical groups, but their accuracy in estimating CA can be altered by racial bias.

Plant pathogenic fungi are the most important cause of losses in agriculture. In the face of the overuse of synthetic fungicides, natural products are an encouraging alternative to control these plant pathogenic fungi. In this study, we tested the antifungal capacity of metabolites produced by strains of the genus Streptomyces against the plant pathogenic fungi Alternaria alternata, Botrytis cinerea and Fusarium oxysporum. In addition, we investigated the feasibility of applying these metabolites in a postharvest setting for the control of B. cinerea on cherry tomato fruits. The results revealed the ability of the strains, especially Streptomyces netropsis, to inhibit the growth of plant pathogenic fungi and, in some cases, the sporulation of these fungi. In addition, we observed an interesting phenomenon in which Streptomyces strains physically encapsulated the mycelium of the fungi, which contributed to their inhibition. Finally, the protective activity of S. netropsis extract on Cherry tomato fruits infected with B. cinerea was demonstrated. In conclusion, this research opens the door to studies on the understanding of physical microbial interactions in natural environments and holds promise in agriculture, especially in the protection of agricultural products during the post-harvest stage as a safer and more sustainable alternative.

The aim of this work is to compare two softwares (MAUD and TOPAS) based on the Rietveld algorithm and to test the concept of tolerance factor using the dissolution at high temperature of yttrium into BaTiO₃. In general, both softwares give up different values of the crystalline parameters however the trends are similar in most cases but the analysis of the strain and crystallite size in the BaTiO₃ crystals suggests that, in this particular case, MAUD offered results more consistent with the expected behavior. Using the crystalline parameters calculated by Rietveld, the tolerance factor values were obtained and these data suggest even better stability in the crystalline structure than that expected using theoretical parameters. Tolerance factor concept also indicates that Ti⁴⁺ should be preferred.

This paper aims to show that sustainable behavior by firms may be impaired by regulatory restrictions. We challenge the assumption that regulation aimed at curbing greenhouse gas emissions (GHG) on the form of a target to meet the Country’s GHG emissions commitments will promote sustainable corporations. We argue that, in fact, such regulation may impair sustainability practices because it creates unintended consequences. This paper tackles the efficiency of the institutional framework chosen through the lenses of the analytical themes of fit, scale and interplay, then we use a systems dynamic approach to represent how regulation in the arenas of energy efficiency and GHG emissions reduction may withhold competitive business outcomes and corporate sustainability schemes. We exemplify and simulate a single regulation scheme and found that as a result of the institutional scheme chosen, the system is dominated by negative feedback processes resulting in lesser outcomes that would be better tackled by firms not being subject to the restrictions imposed by the regulation.

Glutamine is the most abundant and versatile amino acid in the body. In health and disease, the rate of glutamine consumption by immune cells is similar or greater than glucose. For instance, in vitro and in vivo studies have determined that glutamine is an essential nutrient for lymphocyte proliferation and cytokine production, macrophage phagocytic plus secretory activities and neutrophil bacterial killing. Glutamine release to the circulation and availability is mainly controlled by key metabolic organs, such as the gut, liver and skeletal muscles. During catabolic/hypercatabolic situations glutamine can become essential for metabolic function, but its availability may be compromised due to impairment of homeostasis in the inter-tissue metabolism of amino acids. For this reason, glutamine is currently part of clinical nutrition supplementation protocols and/or recommended for immune suppressed individuals. However, in a wide range of catabolic/hypercatabolic situations (e.g. ill/critically ill, post-trauma, sepsis, exhausted athletes) it is currently difficult to determine whether glutamine parenteral or enteral supplementation should be recommended based on the amino acid plasma concentration (glutaminemia). Although the beneficial immune based effects of glutamine supplementation is already established, many questions and evidence for positive in vivo outcomes still remain to be presented. Therefore, this paper provides an integrated review on how glutamine metabolism in key organs is important to cells of the immune system. We also discuss glutamine metabolism, action and important issues related to the effects of glutamine supplementation in catabolic situations.

This article presents a forecast model that uses a hybrid architecture of recurrent neural networks (RNN) with surface neural networks (ANN), based on historical records of exported active energy (EAE) and weather data. Two types of models were developed: the first type includes six models that use EAE records and weather variables as inputs, while the second type includes eight models that use only weather variables. Different metrics were applied to assess the performance of these models, and the best model of each type was selected. Finally, a comparison of the performance between the selected models of both types is presented, and they are validated with real data provided by a solar plant, achieving acceptable levels of accuracy. The selected model of the first type has an RMSE of 0.19, MSE of 0.03, MAE of 0.09, a correlation coefficient of 0.96, and a determination coefficient of 0.93. The other selected model of the second type showed lower precision in the metrics (RMSE = 0.24, MSE = 0.06, MAE = 0.10, Corr. Coef. = 0.95, and Det. Coef. = 0.90). Both models demonstrated good performance and acceptable accuracy in forecasting the weekly photovoltaic energy production of the solar plant.

No-show appointments in healthcare is a problem faced by medical centers around the world, and understand the factors associated with the no-show behavior is essential. In the last decades, artificial intelligence took place in the medical field and machine learning algorithms can work as a efficient tool to understand the patients behavior and to achieve better medical appointment allocation in scheduling systems. In this work, we provide a systematic literature review (SLR) of machine learning techniques applied to no-show appointments aiming at establishing the current state-of-the-art. Based on a SLR following the Kitchenham methodology, 24 articles were found and analyzed, in which the characteristics of the database, algorithms and performance metrics of each studies were synthesized. Results regarding which factors have a higher impact on missed appointment rates were analyzed too. The results indicate that the most appropriate algorithms for building the models are decision tree algorithms. Furthermore, the most significant determinants of no-show were related to the patients age, whether the patient missed a previous appointment, and the distance between the appointment and the patients scheduling.

We have suggested that the abiogenisis of life around the beginning of the Archean may have been an example of microscopic dissipative structuring of UVC pigments (the fundamental molecules of life) under the prevailing surface UV solar spectrum. In a previous article in this series, we have describe the non-equilibrium thermodynamics and the photochemical mechanisms which may have been involved in the dissipative structuring of the purines adenine and hypoxanthine from the common precursor molecules of HCN and water under UVC light. In this article we extend our analysis to include the production of the other two important purines, guanine and xanthine, from these same precursors. The photochemical reactions are presumed to occur within a fatty acid vesicle floating on a hot ocean surface exposed to the prevailing UV light. Reaction-diffusion equations are resolved under different environmental conditions. Significant amounts of adenine (∼10−5 M) and guanine (∼10−6 M) are obtained within only a few months at 80 °C under plausible initial concentrations of HCN and cyanogen (a photochemical product of HCN).

Research professors develop scientific products that impact and benefit society, but their competencies in doing so are rarely evaluated. Therefore, employing a mixed two-stage sequential design, this study developed a self-assessment model of research professors’ competencies with four domains, seven competencies, and 30 competency elements. Next, we conducted descriptive statistical analysis of those elements. In the first year, 320 respondents rated themselves on four levels: initial, basic, autonomous, and consolidated. In the assessment model’s second year, we compared 30 respondents’ results with those of their initial self-assessment. The main developmental challenge was Originality and Innovation, which remained at the initial level. Both Training of Researchers and Transformation of Society were at the basic level, and Digital Competency was at the autonomous level. Both Teaching Competence and Ethics and Citizenship attained the consolidated level. This information helps establish priorities for accelerating researchers’ training and the quality of their research.

The Puuc Biocultural State Reserve (PBSR is an unique model for tropical dry forest conservation in Mexico. Preserving forest biodiversity and carbon within the PBSR depends on the mainte-nance of low impact productive activities coordinated by multiple communal and private land-owners. In this study, we used state-of-the-art remote sensing data to investigate past spatial patterns in forest clearing dynamics and its relation to forest carbon density and forest plant species richness and diversity in the context of the forest conservation goals of the PBSR. We used a Landsat-based continuous change detection product for the 2000-2021 period and compared it to carbon density and tree species richness models generated from ALOS-2 PALSAR 2 imagery and national scale forest inventory data. The estimated error-adjusted area of detected annual forest clearings from the year 2000 until the year 2021 was 230,511 ha in total (+19,979 ha). The analysis of annual forest clearing frequency and area suggests that although forest clearing was significantly more intensive outside of the PBSR than within the PBSR during the entire 2000-2021 period, there is no evidence suggesting that the frequency and magnitude of forest clearing has changed over the years after the creation of the PBSR in 2011. An emergent hotspot analysis shows, however, that high spatiotemporal clustering of forest clearing events (hotspots) during the 2012-2021 pe-riod was less common than prior to 2011 and these more recent hotspots have been confined to areas outside the PBSR. After comparing forest clearing events to carbon density and tree species richness models, results show that land owners outside the PBSR often clear forests with lower carbon density and species diversity than land owners inside the PBSR. This suggests that, compared to land owners outside the PBSR, land owners within the PBSR might be practicing longer fallow periods allowing forests to attain higher carbon density and tree species richness and hence better soil nutrient recovery after land abandonment. In conclusion, our results show that the PBSR effectively acted as a stabilizing forest management scheme during the 2012-2021 period minimizing the impact of productive activities by lowering the frequency of forest clearing events and preserving late secondary forests within the PBSR. We recommend the continuation of efforts for providing alternative optimal field data collection strategies and modeling techniques to spatially predict key tropical forest attributes. The combination of these models with contin-uous change detection datasets will allow to reveal underlying ecological processes and generate information better adapted to forest governance scales.

The conversion of native habitats into anthropogenic ones compromises the original composition and configuration of the landscapes, influencing ecological dynamics and affecting biodiversity. Increasingly, landscape ecology has shown that these effects can only be understood if accessed at adequate spatial scales, as the scale which landscape structure is evaluated influences species responses. Here, we investigated how three variables of landscape composition (proportion of forest, coffee crop and pasture) and two of configuration (number of fragments and mean nearest neighbor distance) interfere in the richness and composition of medium and large-sized mammals considering a multiscale approach. We recorded medium and large-sized mammal species in 13 landscapes with predominantly matrices of coffee and pasture in Minas Gerais, Brazil. Then, we built distance-based linear models to identify the scale of effect of each landscape variable for both response variables considering eight scales (from 250 m to 2000 m). Finally, we verified the influence of the landscape on the richness and composition of mammals, considering the landscape variables in their respective scales of effect. We found 67% of the probable species occurring in the region. The scales of effect varied among landscape variables probably due to the different variables affect different aspects of organisms' ecological requirements. The proportion of pasture in the landscape explained the variation in species richness, while the proportion of forest explained the variation in species composition. In addition, the proportion of pasture in the landscape had a positive influence on species richness, indicating that this matrix may favor the presence of generalist species of habitat and/or this result is due to the higher concentration of species in the fragments immersed in this matrix. These results suggest that considering different responses to biodiversity is important to understand different aspects of the landscape's influence on biodiversity. In addition, the composition of the landscape is fundamental for the perpetuation of species and, therefore, both forest cover and types of matrices in the landscape must be considered to improve species conservation strategies. Finally, generalizing a spatial scale can lead to misinterpretations about the influence of the landscape on biodiversity.

Antisense technologies consist of the utilization of oligonucleotides or oligonucleotide analogs to interfere with undesirable biological processes, commonly through inhibition of expression of selected genes. This field holds a lot of promise for the treatment of a very diverse group of diseases including viral and bacterial infections, genetic disorders, and cancer. To date, drugs approved for utilization in clinics or in clinical trials target diseases other than bacterial infections. Although several groups and companies are working on different strategies, the application of antisense technologies to prokaryotes still lags with respect to those that target other human diseases. In those cases where the focus is on bacterial pathogens, a subset of the research is dedicated to produce antisense compounds that silence or reduce expression of antibiotic resistance genes. Therefore, these compounds will be adjuvants administered with the antibiotic to which they reduce resistance levels. A varied group of oligonucleotide analogs like phosphorothioate or phosphorodiamidate morpholino residues, as well as peptide nucleic acids, locked nucleic acids and bridge nucleic acids, the latter two in gapmer configuration, have been utilized to reduce resistance levels. The major mechanisms of inhibition include eliciting cleavage of the target mRNA by the host’s RNase H or RNase P, and steric hindrance. The different approaches targeted resistance to β-lactams including carbapenems, aminoglycosides, chloramphenicol, macrolides, and fluoroquinolones.

Feedback is a type of formative evaluation linked to student learning and academic achievement. However, it is not known how students perceive this process since there are no instruments to measure attitudes towards feedback. The objective of this work was to develop and validate an attitude scale towards academic feedback through an Exploratory Factor Analysis (EFA), using the principal components method and an internal consistency analysis using Cronbach's Alpha. The sample consisted of 274 students from 2015, 2016, and 2017 cohorts of pedagogy careers from five Chilean universities. The results showed the consolidation of the instrument and its final conformation in four components (Negative experience towards feedback, Effectiveness of feedback, Feedback as an opportunity, and Resistance towards feedback) with a total of 15 items, which allow measuring the students' attitude towards this written formative evaluation.

This study presents head losses (hL) and loss coefficients (K) obtained experimentally for schedule 40 PVC pipe elbows, with 90o and 45o in small commercial diameters of ½ to 1½ inches that are commonly used in small networks. The investigation was conducted on a system constructed with short pipes and fittings necessary to measure, direct, and control flow, as well as to evaluate pressure head losses at elbows. Simple water flow was used with rates of 0.342 to 0.980 lps (Q), which generated moderate Reynolds numbers (Re) of 13337 to 80221. It was found that hL showed dependence on the velocity head in all elbows, as well as that hL are greater as the diameter increases for same velocity head. The K values in the elbows tended to be constant when Q &gt; 0.75 lps, but for Q &lt; 0.75 lps the K coefficient increased inversely proportional to Q, becoming larger as the diameter increased. Likewise, the K coefficient tended to increase as Re decreased, while K tended to be constant as Re increased. The results of the experimental coefficient were compared against K values reported in the literature, where significant similarities and discrepancies were found.

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%.

The broad global distribution of freshwater clams belonging to the genus Corbicula is driven by multiple hermaphroditic lineages. These lineages, characterized by shared morphological traits and phenotypic plasticity, pose challenges to morphological identification. Genetic markers, such as the mitochondrial COI gene, play a crucial role in delineating these lineages and their ranges. Morphotypes represent observed phenotypic variations, while lineages are defined based on genetic markers. Here, we comprehensively review Corbicula's distribution in Argentina, dis-criminate extant lineages based on both morphological and genetic (COI) data, and describe variation in internal and external morphology using 15 Argentine populations. Haplotype net-works identified two mitochondrial lineages: A/R morphotype (FW5 haplotype) and C/S mor-photype (FW17 haplotype). Strikingly, despite having similar vectors, origins, and invasive stages, Corbicula lineages exhibit virtually segregated distributions. However, intermediate morphotypes and both mitochondrial haplotypes are found in sympatry in northeastern Argen-tina, suggesting the presence of hybrids due to maternal genome retention. These findings con-tribute to the clarification of the identity and distribution of Corbicula lineages in Argentina, where the genus has been found for over half a century. Similar studies are needed in other areas to better understand the invasion patterns of a successful and plastic group.