On 2013 the Villonaco wind farm (16.5 MW), the first wind farm in continental Ecuador near the city of Loja, began operations. The power generated is delivered to the National Interconnected System (SNI), which services the city. This research confronts two sets of real data, the electricity use of the urban area of Loja, and the power generated by the Villonaco Wind Farm. Electricity use follows clearly defined daily and weekly cycles, and wind power has a seasonal behaviour. The study shows that wind power integration cannot be a long-term stable power source regardless power or generation surplus. Another essential finding is that time series can be used as a statistical source to determine the need for short- (seconds) and long- (days, weeks) term energy storage. Strategies to further the energy autonomy of the urban area through the expansion of the wind farm by a factor of 2 are discussed.

Compound parabolic concentrators are relevant systems used in solar thermal technology. With adequate tailoring, they can be used as an efficient and low-cost alternative in residential water applications. This work presents a simulation study using a ray tracing methodology. With this technique we simulate the interaction between solar rays and solar concentrator to quantify the amount of energy that impinges on the receiver at a particular time. Energy availability is evaluated in a comparison of two configurations: stationary at 21° throughout the year and multi position setup; tilted with respect to the horizontal depending on three seasonal positions: 0° for summer, 16° for spring / autumn and 32° for winter, with the objective of increasing the amount of available energy in each season. The fact that a tracking system can be dispensed with also represents an economical option for the proposed application. The results showed that at 21°, the proposed system works satisfactorily; however, by carrying out the selected angular adjustments, the overall energy availability increased by 22%, resulting in a more efficient option. The methodology developed herein proved to be a valuable tool for prototype design and performance evaluation.

Electrical power quality is one of the main elements in power generation systems. At the same time, it is one of the most significant challenges regarding stability and reliability. Due to different switching devices in this type of architecture, different kinds of power generators, and non-linear loads are used for different industrial processes. As a result of this, the need to classify and analyze Power quality disturbance (PQD) to prevent and analyze the degradation of the system reliability affected by the non-linear and non-stationary oscillatory nature. This paper presents A Novel Mul-titasking Deep Neural Network (MDL) for the Classification and Analysis of Multiple Electrical Disturbances. The characteristics are extracted with a specialized and adaptive methodology for non-stationary signals, Empirical Mode Decomposition (EMD). The methodology’s design, devel-opment, and various performance tests are carried out with 28 different difficulty levels, such as severity, disturbance duration time, and noise in the 20 dB to 60 dB signal range. MDL was devel-oped with a diverse data set in difficulty and noise, with a quantity of 4500 records of different samples of multiple electrical disturbances. The analysis and classification methodology has an average accuracy percentage of 95% with multiple disturbances. In addition, an average accuracy percentage of 90% in analyzing important signal aspects for studying electrical power quality such as crest factor, Per Unit voltage analysis, Short Term Flicker Perceptibility (Pst), and Total Harmonic Distortion (THD), among others.

The objective of this study was to analyze the effects of a pulmonary telerehabilitation (TR) program in young adults with post-COVID-19 syndrome. The information of sixteen students' medical files were analyzed and allocated to one of two groups (control=CG/experimental=EG). Twelve TR sessions were performed distantly and asynchronously at the EG patients' homes during 4-weeks. The program included diaphragmatic pattern breathing and aerobic exercises. The parameters: i) vital signs (oxygen saturation "SpO2", heart rate "HR", respiratory rate "RR" and blood pressure "BP"; ii) physical capacity “Sit-to-stand test”; iii) cardiorespiratory capacity “6-Minute Walk Test”; and iv) perceived effort "Borg scale" were assessed in both groups. The statistical analyses showed a significant decrease of RR and HR (p < 0.012) accompanied by a significant increase in SpO2 (p < 0.042), physical (p < 0.012) and respiratory (p < 0.028) capacity. The perceived effort decreased significantly in both groups (CG: p < 0.006; EG p < 0.001) only for physical but not for cardiorespiratory capacity (p < 0.106). There were no statistical changes registered in BP (p > 0.05). The current study suggests that a TR program that involves breathing and aerobics exercises is feasible and effective in treating post-COVID-19 syndrome in young patients.

The focus of this research is to analyze the results of encrypting audio using various authenticated encryption algorithms implemented in the Python cryptography library for ensuring authenticity and confidentiality of the original contents. The Advanced Encryption Standard (AES) is used as the underlying cryptographic primitive in conjunction with various modes including Galois Counter Mode (GCM), Counter with Cipher Block Chaining Message Authentication Code (CCM), and Cipher Block Chaining (CBC) with Keyed-Hashing for encrypting a relatively small audio file. The resulting encrypted audio shows similarity in the variance when encrypting using AES-GCM and AES-CCM. There is a noticeable reduction in variance of the performed encodings and an increase in the amount of time it takes to encrypt and decrypt the same audio file using AES-CBC with Keyed-Hashing. In addition, the corresponding encrypted using this mode audio spans a longer duration. As a result, AES should either have GCM or CCM for an efficient and reliable authenticated encryption integration within a workflow.

Let G be a connected Lie group with Lie algebra g. This review is devoted to studying the fundamental dynamic properties of elements in the normalizer NG of G. Through an algebraic characterization of NG we analyze the different dynamics inside the normalizer. NG contains the well-known left-invariant vector fields and the linear and affine vector fields on G. In any case, we show the shape of the solutions of these ordinary differential equations on G. We give examples in low-dimensional Lie groups. It is worth saying that these dynamics generate the linear and bilinear control systems on Euclidean spaces and the invariant and linear control systems on Lie groups. Moreover, the Jouan Equivalence Theorem shows how to extend this theory to control systems on manifolds.

In this paper, the existence of two nontrivial stationary solutions for the nonlinear Gilpin Ayala two species competition model is given by using the mountain pass lemma, and the local stability criterion of the trivial solution is given by using Lyapunov function method. Based on the local stability criterion, we give some suggestions on how to avoid the population extinction. This is, when the population is on the verge of extinction, we should try our best to avoid the diffusion behavior and reduce the diffusion coefficient, otherwise the species are easy to go extinct. Numerical example shows the effectiveness of the proposed method.

Background: Human papillomavirus (HPV) poses a significant health burden, yet the vaccine which successfully prevents HPV and its associated cancers remains underutilized. Nurses play a crucial role in patient education and advocacy for HPV vaccination. This study explores how knowledge, along with cultural, religious, and social beliefs, shapes the attitudes of Israeli nurses and nursing students toward the HPV vaccine and their advocacy efforts. Methods: A cross-sectional study was conducted from August 2023 to January 2024 using an anonymous online questionnaire distributed via Facebook groups targeting Israeli nurses and nursing students. The questionnaire assessed demographic data, HPV-related knowledge, and attitudes toward HPV vaccination. Results: The study included 458 participants (229 nurses and 229 nursing students). Significant knowledge gaps were found, with 52% of participants incorrectly believing that the vaccine can cure existing infections and 47% mistakenly believing that it is administered in a single dose. Logistic regression revealed that nurses working in community settings were more likely to have positive attitudes toward HPV vaccination (OR=2.98, 95% CI: 1.84–4.85). Higher levels of HPV-related knowledge (OR=3.35, 95% CI: 2.10–5.35) and secular or traditional religious affiliations (OR=2.45, 95% CI: 1.52–3.97) were strongly associated with positive attitudes toward and advocacy for the vaccine. Conclusions: Targeted educational programs addressing knowledge gaps, especially those tailored to Israel's cultural and religious diversity, are crucial for empowering nurses and nursing students as advocates for HPV vaccination. Enhancing their understanding of HPV can increase vaccine uptake, reduce the incidence of HPV-related diseases, and strengthen public health initiatives in Israel.

In this paper, the author utilizes Saddle Theorem and variational methods to deduce existence of at least six stationary solutions for reaction-diffusion Gilpin-Ayala competition model (RDGACM). To obtain the global stabilization of the positive stationary solution of the RDGACM, the author designs a suitable impulsive event triggered mechanism (IETM) to derive the global exponential stability of the the positive stationary solution. It is worth mentioning that the new mechanism can exclude Zeno behavior and effectively reduce the cost of impulse control through event triggering mechanism. Besides, compared with existing literature, the restrictions on the parameters of the RDGACM are relaxed so that the methods used in existing literature can not be applied to the relaxed case of this paper, and so the author makes comprehensive use of Saddle Theorem, orthogonal decomposition of Sobolev space $H_0^1(\Omega)$ and variational methods to overcome the mathematical difficulty. Numerical examples show the effectiveness of the methods proposed in this paper.

This paper aims to demonstrate that, beyond the small world of Riemann-Liouville and Caputo derivatives, there is a vast and rich world with many derivatives suitable for specific problems and various theoretical frameworks to develop, corresponding to the different paths taken. Notions of time and scale sequences are introduced and general associated basic derivatives, namely right/stretching and left/shrinking, are defined. A general framework for fractional derivative definitions is reviewed and applied to get both known and new fractional order derivatives. Several fractional derivatives are considered, mainly: Liouville, Hadamard, Euler, bilinear, tempered, q-derivative, and Hahn.

Glioblastoma is a central nervous system cancer type with a poor prognosis. One of its main features is the constant change of metabolism phenotype to support its development and progression. Mitochondria play a critical role in cellular metabolism. Acetylation on lysine residues of mitochondrial enzymes is a mechanism for regulating protein function. This modification negatively affects the mitochondrial proteome function and is counteracted by the enzyme sirtuin 3 (SIRT3). To better understand how SIRT3 regulates mitochondrial metabolism, we inhibited SIRT3 and examined by high-resolution mass spectrometry analysis the proteome and acetylome of two glioblastoma cell lines with different metabolic preferences. Our results indicate that protein synthesis machinery is regulated by lysine acetylation and plays a role in the metabolic phenotype. We also identified new SIRT3 targets not previously associated with specific functions, highlighting their potential as future targets for further study. This study shed light on the role of SIRT3 in mitochondria and its implication for cellular metabolism. We have generated knowledge at the proteome and acetylome levels on the dynamics between two glioblastoma cell lines with opposing metabolic phenotypes. Our results might guide in searching for biomarkers at both proteome and acetylome levels in glioblastoma.

Firstly, the author do dynamic analysis for reaction-diffusion Gilpin-Ayala competition model with Dirichlet boundary value, involved in harmful species. Existence of multiple stationary solutions is verified by way of Mountain Pass lemma, and the local stability result of the null solution is obtained by employing linear approximation principle. Secondly, the author utilize variational methods and LMI technique to deduce the LMI-based global exponential stability criterion on the null solution which becomes the unique stationary solution of the ecosystem with delayed feedback under a reasonable boundedness assumption on population densities. Particularly, LMI criterion is involved in free weight coefficient matrix, which reduces the conservatism of the algorithm. In addition, a new impulse control stabilization criterion is also derived. Finally, two numerical examples show the effectiveness of the proposed methods. It is worth mentioning that the obtained stability criteria of null solution presented some useful hints on how to eliminate pests and bacteria.

Ferulic acid has numerous beneficial effects for human health, which are frequently attributed to its antioxidant behavior. In this report many of them are reviewed and 185 new ferulic acid derivatives are computationally designed, using the CADMA-Chem protocol. For the later, the chemical space was sampled and evaluated. To that purpose selection and elimination scores were used, which are built from a set of descriptors accounting for ADME properties, toxicity, and synthetic accessibility. After the first screening, 12 derivatives were selected and further investigated. Their potential role as antioxidants was predicted from reactivity indexes, directed related with the formal hydrogen atom transfer and the single electron transfer mechanisms. The best performing molecules were identified by comparisons with the parent molecule and two references: Trolox and alpha-tocopherol. Their potential as polygenic neuroprotectors was investigated through the interactions with enzymes directed related with the etiologies of Parkinson’s and Alzheimer’s diseases. They are acetylcholinesterase, catechol-O-methyltransferase, and monoamine oxidase B. Based on the obtained results, the most promising candidates (FA-26, FA-118, and FA-138) are proposed as multifunctional antioxidants with potential neuroprotective effects. The findings derived from this investigation are encouraging and might promote further investigations on these molecules.

In the coming years, digital applications and services that continue to use the country's native cloud systems will be huge. By 2023, that will exceed 500 million, according to IDC. This corresponds to the sum of all applications developed in the last 40 years. If you are the one you answered, yes! This article is for you!

The chestnut tree (Castanea sativa Mill.) is gaining importance in the mountainous regions of southern Europe due to the high value of its fruits. It is essential to establish effective cultivation protocols, considering that this species is still relatively understudied. In this study, we present the outcomes of the initial establishment of a chestnut orchard conducted through a nutrient omission trial for four years. The treatments included a fertilization plan with nitrogen, phosphorus, potassium, and boron (NPKB), the control, and four other treatments corresponding to the omission of each nutrient (-NPKB, N-PKB, NP-KB, NPK-B). The -NPKB and NP-KB treatments showed significantly lower trunk circumferences and canopy volumes compared to the other treatments. The NPK-B treatment resulted in the lowest fruit production, with a total accumulated yield (2020-2022) of 0.56 kg tree–1, a value significantly lower than that of NPKB (1.12 kg tree–1) and N-PKB (1.19 kg tree–1). The assessment of nutrient concentrations in the leaves revealed plants with deficient levels of B and K in treatments that did not receive these nutrients. Conversely, N levels in the leaves in the -NPKB treatment fell within the sufficiency range (20 to 28 g kg–1). This suggests that the sufficiency range should be adjusted to higher values, given the treatment's effect on tree growth. It was also observed that the -NPKB treatment led to lower soil organic matter compared to the other treatments, likely due to reduced herbaceous vegetation development under the canopy, leading to decreased organic substrate deposition in the soil. The main findings of this study are that N and K were crucial elements for the optimal growth of chestnut trees, while B played a significant role in fruit production.

The present research project entitled "Development of a method for predicting the optimal maturity level of avocado using machine learning" aims to establish an accurate and efficient approach to assess the maturity of avocados using machine learning methodologies. This research specifically focuses on identifying the relevant physical and chemical characteristics of avocados, creating a dataset containing categorized images of maturity levels, and creating machine learning models capable of accurately predicting fruit maturity. The studies reveal that the application of machine learning, in particular convolutional neural networks and multisensor models, has the potential to transform the prediction of avocado maturity and thus improve product quality and customer satisfaction. The findings indicate that the proposed techniques achieve an accuracy rate of over 90%, demonstrating their viability for integration into mobile applications that can benefit growers and suppliers in their decision-making processes.

This paper is a detailed study on radio frequency identification (RFID) technology focused on its application for warehouse traceability in the company FRUMECAR. It highlights the importance of controlling the traceability of items in warehouses or logistics companies, highlighting the need for reliable, real-time information to effectively manage inventory and resolve incidents quickly. The paper discusses in depth what RFID is, its types, main components such as tags, readers, and antennas, as well as discussing how it works, advantages, disadvantages, and specific applications. It also examines factors such as return on investment, cost feasibility, and environmental factors that influence the implementation of RFID systems. The paper presents a practical approach, proposing RFID-based solutions to improve traceability in FRUMECAR, analyzing the current state of the company and its warehouses, with the aim of implementing an efficient system that allows real-time tracking of products.

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

Soil management in orchards can have several economic and environmental implications. In this study, three different soil management systems were compared in a dry-farmed olive grove: conventional tillage (Tillage), glyphosate-based herbicide (Herbicide) and Sheep Walking. The experiment lasted eleven years (2011-2022) and was carried out after a previous trial conducted on the same plot with the same treatments and duration (2001-2011). However, in the earlier trial, the Herbicide and Sheep Walking treatments switched positions in the plot, while the tillage treatment remained in its original place. The average total accumulated olive yields between 2011 and 2022 were 225.1, 230.9, and 245.0 kg tree–1 for the Sheep Walking, Tillage, and Herbicide treatments, respectively. However, no significant differences were observed between the treatments. The levels of total organic carbon in the soil, measured in samples collected in the last year of the study, were 41.3, 33.7, and 37.3 g kg–1, respectively for the same treatments. These findings indicated that the Tillage treatment exhibited lower soil organic matter content and reduced bioavailability of some nutrients, which raises concerns about its sustainability. On the contrary, employing Sheep Walking with an appropriate stocking rate, effectively controlling vegetation in the spring, ensured favourable soil properties and olive yields comparable to the other treatments. Moreover, the Sheep Walking approach provides supplementary advantages to the farmer, including revenue from the sale of animal products and the opportunity to transition to organic farming systems, which better align with the preferences of contemporary societies.

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

This study reports on allelic and genotypic frequencies of OCT1, OCT2, OCT3 polymorphisms among metformin-treated DMT2 patients. It also reports the association with HbA1c control on 59 DMT2 patients. They were genotyped through real-time PCR (TaqMan assays). Metformin plasmatic levels were determined through mass spectrometry. Neither the analysis of HbA1c control by SNPs in SLC22A1, SLC22A2, and SLC22A3, nor the dominant genotypic model analysis yielded statistical significance across genotypes in polymorphisms rs72552763 (p=0.4678), rs622342 (p= 0.2215), rs316019 (p=0.2209), and rs2076828 (p=0.215). HbA1c levels were different in rs72552763 (p= 0.0220) and rs622342 (p=0.0093) genotypes. The dominant genotypic model found the lowest HbA1c levels by GAT/GAT (p= 0.0058) and A/A (p=0.0108), in rs72552763 and rs622342 respectively. We may conclude that rs72552763 and rs622342 polymorphisms in SLC22A1, exercise a relevant effect in metformin response determined by HbA1c levels among Mexican-Mestizo DMT2 patients.

Currently, the use of medications during pregnancy in Latin America is common; studies with Latin American samples find that nearly 90% of pregnant women use some medication at least once during pregnancy. Furthermore, approximately 21% of the respondents self-medicated. Worldwide, the prevalence of this disease is 32%. The most common medications are nonsteroidal anti-inflammatory drugs and analgesics. Many of these drugs are available over the counter without a prescription. For this reason, a systematic review of the literature on the adverse effects on the woman and the fetus was performed. Objective: To determine the adverse effects associated with the use of nonsteroidal anti-inflammatory drugs (NSAIDs) on pregnant women and fetuses during pregnancy. Methods: Systematic literature review. The following search strategy was used for the databases: Science Direct, PubMed, Scopus and Web of Science, through September 3, 2022. The population of pregnant women without previous comorbidities was defined. The intervention of interest was the use of NSAIDs during pregnancy. The outcomes of interest were adverse effects for the mother or fetus (weight of the newborn, congenital malformations present in the fetus, systemic effects in the pregnant woman during her gestation period). The types of studies included clinical trials, cohort studies and case‒control studies. Results: 1 study included 2,985 pregnant women without previous comorbidities. The use of aspirin more frequently during pregnancy stands out. The adverse effects on the fetus were preterm birth <37 weeks, low birth weight < 2500 g and increased admission to the neonatal intensive care unit. No adverse effects were found for the mother. Conclusions: There are not enough data indicating that the use of NSAIDs during pregnancy is safe. Some studies show that the use of NSAIDs during pregnancy could be related to problems in the development and growth of the fetus and health effects for the mother during pregnancy, so it is advisable to use these drugs under medical prescription and for the shortest possible time. in the gestation stage.

Shewanella spp. are gram-negative bacteria that thrive in aquatic niches and also cause infectious diseases as opportunistic pathogens. Chromosomal integrons (CI) and mobile integrons (MI) were previously described in some Shewanella isolates. Here, we evaluated the occurrence of integrase genes, the integron systems and their genetic surroundings in the genus. We identified 22 integrase gene types, 17 of which were newly described, in different Shewanella species, evidencing multiple gain and loss events. Phylogenetic analysis showed that most of them were strain-specific, except for Shewanella algae, which seem to have co-evolve within the host as typical CIs. Noteworthy, co-existence of up to 5 different integrase genes, as well as their wide dissemination to Alteromonadales, Vibronales, Chromatiales, Oceanospirillales and Enterobacterales was observed. Identification of novel MIs suggests that lateral genetic transfer may have occurred resembling the behavior of class 1 integrons. The constant emergence of determinants associated to antimicrobial resistance worldwide, concomitantly with novel MIs in strains capable to harbor several types of integrons may be an alarming threat for the recruitment of novel antimicrobial resistance gene cassettes in the genus Shewanella, and its evolution towards the multidrug resistance.

Ixodes scapularis is the major vector of Lyme disease in the eastern United States. Each active life stage (larva, nymph, and adult) takes a blood meal either for developing and molting to the next stage (larvae and nymphs) or for oviposition (adult females). This protein-rich blood meal is the only food taken by Ixodes ticks and therefore blood digestion is very important for tick survival. Most studies on blood digestion in ticks have shown that the initial stages of digestion are carried out by cathepsin proteases within acidic digestive cells. However, most of these studies have focused on partially engorged ticks. In other hematophagous arthropods, the serine proteases play an important role in blood protein degradation. In this study, we determined transcript expression of four I. scapularis serine proteases with previously characterized roles in blood digestion. RNA interference was used for functional analysis and a trypsin-benzoyl-D, L-arginine 4-nitoanilide assay was used to measure active trypsin levels. An in vitro hemoglobinolytic assay was performed with or without serine protease inhibitor. Our data suggest that trypsin levels increase significantly after blood feeding and peaked in larvae, nymphs, and adults at 3, 1, and 1 day post host detachment, respectively. The knockdown of three previously identified serine proteases by RNAi negatively impacted blood intake, survival, fecundity, levels of active trypsin in the gut and resulted in lower hemoglobin degradation in vitro. A trypsin inhibitor, PMSF, blocked the action of trypsin in the gut extract resulting in 65% lower hemoglobin degradation. We provide evidence of the serine proteases as digestive enzymes in fully engorged, replete females. Our data also demonstrated that in addition to blood digestion, these serine proteases might have a role in blood feeding success in I. scapularis.

American Sign Language is a popular language for deaf individuals. Communication is made easier for these people through sign language. However, in a digital era like today, there is a need for these people to be able to communicate online, and even get help from technology to communicate in person with non sign language speakers. This research will present a program able to translate American sign language to plain English. This study aims to use the OpenCV library to recognize hand signals, also a trained model to identify images so that the program can then translate them to words and letters. The program uses a data set of over 2000 images which will be in this case the largest data set available. With over 90\% of accuracy it results in a basic computer program with the largest data set available that would make possible for users to communicate with a wide variety of words and expressions.

Peru has one of the highest informal employment rates in Latin America (73%). Previous studies have shown higher prevalence of poor self-perceived health (P-SPH) in informal workers compared to formal. The study’s aim is to analyse the role of working conditions in the association between informality and SPH in urban working population in Peru. We conducted a cross-sectional study based on 3098 workers from the working conditions survey of Peru 2017. Prevalence of P-SPH and exposure to poor working conditions were calculated separated by formal and informal employment and stratified by sex. Poisson regression models were used to assess the association between P-SPH and informal employment, with its prevalence ratios (PR) crude and adjusted for working conditions. Informal employment was 76% in women and 66% in men. Informal workers were more exposed to poor working conditions than formals and reported worse SPH. Workers in informal employment showed higher risk of P-SPH than formals: PR 1.38 [95% CI: 1.16 – 1.64] in women and PR 1.27 [95% CI: 1.08 – 1.49] in men. Adjustment by working conditions weakened the association in both sexes. In women, this association was only partially explained by worse working conditions 1.23 [95% CI: 1.04 – 1.46]. The negative effect on informal workers’ health is partially explained by poor working conditions. However, there is a part of the effect explained by informality per se.

Aspergillus flavus is a medically relevant fungus, particularly in tropical regions. Thermotolerance is a key virulence factor as an opportunistic pathogen, as well as its ability to form biofilms, which can impact therapeutic outcomes. To know how temperature affects the growth and biofilm formation of an A. flavus isolate, we assessed its growth on solid media and described the morphological changes during conidial germination. We also examined formation and composition of in vitro biofilm incubated at different temperatures and compared the susceptibility of planktonic and biofilm cells to antifungal agents. Our results showed that temperature promotes conidiation on solid media. The radial growth was higher at 28 °C, but total conidia was higher at 37 °C, however, conidial density was stronger at 42 °C. Moreover, incubation at 37 °C accelerates conidial germination and is the optimal temperature for biofilm formation. We described four distinct phases in A. flavus biofilm development: initiation (0-12h), consolidation (12-48h), maturation (48-72h), and dispersion (&gt;72h), where the presence of aspergillar heads was notable at 42 °C. Carbohydrates and proteins are the main components of the extracellular matrix. We observed lipid droplets within the biofilm hyphae, and mature biofilms are resistant to amphotericin B and itraconazole, with MICs exceeding 16 g/mL for both antifungals, regardless of the incubation temperature.

An impaired healing response underlies diabetic foot wounds chronicity, frequently translating in amputation, disability, and early mortality. In addition, diabetics frequently suffer of the underappreciated episode of post-epithelization ulcer recurrence. Recurrence epidemiological data are alarmingly high; so that the ulcer is considered in “remission” and not healed for the time it remains epithelialized. Recurrence may result from the conspiracy of behavioral and biological factors. Although the damaging role of behavioral, clinical predisposing factors is undebatable, the role of endogenous biological signalers that prime the residual scar tissue to recurrence has remained elusive. We propose that ulcer recurrence is deeply impinged by chronic hyperglycemia and its downstream biological effectors, which originate epigenetic drivers that enforce abnormal pathologic phenotypes to dermal fibroblasts, and keratinocytes as memory cells. Hyperglycemia-derived cytotoxic reactants accumulate and modify dermal proteins, reduce scar tissue mechanical tolerance, and disrupt fibroblasts-secretory activity. Accordingly, the combination of epigenetic and local and systemic cytotoxic signalers, induce the onset of “at-risk phenotypes” as premature skin cells aging, dysmetabolism, inflammatory, pro-degradative, and oxidative programs that may ultimately converge to scar cells demise. Unfortunately, post epithelialization recurrence rates data are missing in clinical studies of accepted ulcer healing therapies during follow-up periods. Intra-ulcer infiltration of epidermal growth factor exhibits the most consistent remission data with the lowest recurrences during 12-month follow-up. Recurrence data should be regarded as a valuable clinical endpoint during the investigational period for each emergent healing candidate.

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

Chagalapoli fruit (Ardisia compressa) is similar to Vaccinium myrtillus (berries) with high-polyphenol content. The objective of this study was to evaluate the physicochemical properties of Chagalapoli fruit and to determine the conditions for the preparation of a fermented beverage using Saccharomyces cerevisiae yeast, evaluating the impact on sensory properties. The fermentation process lasted 4 days at 27 °C, with absence of light and a fixed pH of 3.8. The phenolic contents obtained in samples according to chromatograms were 1.27 mg(EPI)/mL in filtered juice, 1.59 mg(EPI)/mL in filtered fermented beverage, 1.91 mg(EPI)/mL in partially filtered juice and 3.19 mg(EPI)/mL in partially filtered fermented beverage. An affective test was carried out to determine the sensory acceptability of the final product, evaluating the flavor, color and aroma parameters. The fermented beverage with the greatest preference on color and flavor attributes was the partially filtered fermented beverage.

The study of cell-free DNA (cfDNA) and other peripheral blood components (known as “liquid biopsies”) is promising and has been investigated especially in solid tumors. Nevertheless, it is increasingly showing greater utility in the diagnosis, prognosis, and response to treatment of hematological malignancies; in the future, it could prevent invasive techniques, such as bone marrow (BM) biopsy. Most of the studies about this topic have been focused on B cell lymphoid malignancies; some of them have shown that cfDNA can be used as a novel way for diagnosis and minimal residual monitoring in B cell lymphomas, using techniques such as next-generation sequencing (NGS). In myelodysplastic syndromes, multiple myeloma, or chronic lymphocytic leukemia, liquid biopsies may allow for an interesting genomic representation of the tumor clones affecting different lesions (spatial heterogeneity). In acute leukemias, it can be helpful in the monitoring of early treatment response and the prediction of treatment failure. In chronic lymphocytic leukemia, the evaluation of cfDNA permits the definition of clonal evolution and drug resistance in real-time. However, there are limitations such as the difficulty in obtaining sufficient circulating tumor DNA for achieving a high sensitivity to assess minimal residual disease or the lack of standardization of the method and clinical studies to confirm its prognostic impact. This review focuses on clinical applications of cfDNA on minimal residual disease in hematological malignancies.

Traditional mining activities in Zaruma-Portovelo (SE Ecuador) have led to high concentrations of pollutants in the Puyango River due to acid mine drainage (AMD) from abandoned waste. Dispersed Alkaline Substrate (DAS) passive treatment systems have shown efficacy in neutralizing acidity and retaining metals and sulfates in acidic waters, achieving near 100% retention for Fe, Al, and Cu, over 70% for trace elements, and 25% for SO₄²⁻. However, significant solid residues are generated, requiring proper geochemical and mineralogical understanding for management. This study investigates the fractionation of elements in AMD precipitates. Results indicate that trivalent metals (Fe, Al) form low-crystallinity oxyhydroxysulfate minerals such as schwertmannite and jarosite, which retain elements like As, Cr, Cu, Pb, and Zn through adsorption-coprecipitation. Sulfate removal occurs via salts like coquimbite and gypsum. Divalent metals are primarily removed through carbonate and bicarbonate phases, with minerals such as azurite, malachite, rhodochrosite, and calcite. Despite the effectiveness of DAS, leachates from the precipitates exceed regulatory thresholds for aquatic life protection, classifying them as hazardous and posing environmental risks. However, these residues offer opportunities for the recovery of valuable metals.

The differential distribution, size, and quality of urban green spaces (UGS) among localities generate a differential distribution of benefits provided to users. We analyzed the spatial distribution of five size categories of UGS among 15 municipalities of Mexico City, compared their total surface per capita and associated them with the social marginality index. We found 1,353 UGSs accessible for public use with a total area of 2,643 ha. Seventy-four percent of them had &lt;1 ha of surface area, and 51% were located in only three municipalities that were mostly middle- and high-income. These municipalities concentrated a higher area of green spaces per capita. We found a negative correlation between the marginality index and the area of UGS per municipality; the lower the marginality index, the higher the area of green spaces. We consider this a situation of environmental injustice since urban environmental services are distributed unequally with respect to marginalized populations.

Through a partnership with three Federally Qualified Health Centers (FQHCs), the local health department in Los Angeles County implemented a produce prescription program (PPR) to increase fresh fruit and vegetable purchases among patients with diabetes or prediabetes. The PPR, which began in 2020, provided eligible patients with a $40 voucher every month for 6 months to promote the purchase of fresh produce at large chain grocery stores. This qualitative assessment describes staff experiences with the PPR, documenting the facilitators and barriers they encountered while implementing the program. Fifteen clinic staff (i.e., PPR implementers) were interviewed for this assessment. Thematic analysis and coding were conducted using the ATLAS.ti software; the coding was carried out by two separate coders. Interviewees discussed the importance of having preexisting partnerships and programs to support the PPR at their clinic site. Hidden costs related to implementing the program included a large and unexpected amount of staff time devoted to enrolling patients into the program. Collecting quality data and having limited expertise to rigorously evaluate the program were other challenges. Because patients often share their food with their family, the monthly $40 incentive was generally not enough to support their needs; interviewees suggested giving a higher inventive amount to those with a larger household. Future PPR efforts and similar food incentive programs should consider these and other facilitators and barriers to implementation and sustainability, especially when making adjustments to these programs to improve services and access to food resources.

Differences are introduced as outputs of linear systems called differencers, being considered two classes: shift and scale-invariant. Several types are presented, namely: nabla and delta, bilateral, tempered, bilinear, stretching, and shrinking. Both continuous and discrete-time are described. ARMA type systems based on differencers are introduced and exemplified. In passing, the incorrectness of the usual delta difference is shown.

This paper discusses the concept of fractional derivative with complex order from the application point of view. It is shown that a fractional derivative is hermitian, if and only if the order is real. The hermitian part of complex order derivatives behave like allpass filters with almost logarithmic phase.

A very high parking occupancy can negatively influence the traffic performance of an area by causing very long cruising times. A very low parking occupancy, on the other hand, is inefficient from a space utilization perspective. Thus, this paper proposes a framework to compute the optimal parking occupancy rate over a given time horizon based on a macroscopic traffic and parking model. This rate is set high enough to ensure an efficient usage of the parking infrastructure. However, it should also guarantee a high likelihood of finding parking in order to eliminate the drivers’ time wasted in cruising for parking and the added congestion it causes. The model outputs are based on small data collection efforts and low computational costs, and they can be generated without complex simulation software using a simple numerical solver. Multiple vehicle types are included into our methodology allowing us to generate insights about the optimal parking occupancy with or without differentiated parking (i.e., parking for specific vehicles, such as fuel and electric vehicles). In times of a modal shift towards electric vehicles, cities can use our model to evaluate how much parking supply (with battery charging opportunities) they would like to dedicate to electric vehicles in order to achieve optimal traffic and parking results, and whether a differentiated or semi-differentiated parking policy is desirable. We illustrate our framework in a case study of a central area within the city of Zurich, Switzerland, showing the traffic and parking impacts (e.g., average searching time for parking, total revenue created by parking fees, optimal parking occupancy rate) for different proportions of fuel and electric vehicles in the parking demand and/or supply. Our results confirm that optimal occupancy rates are between and for most realistic scenarios. We then discuss how these rates might change depending on various demand and supply relationships, and according to different parking policies. We show that equal proportions between electric vehicles in the demand and their parking spaces in the supply lead to the best traffic performance in the area. We also provide the tools for cities to analyze their loss in performance if they do not react, e.g., to an increasing demand for electric vehicles over time. Moreover, we illustrate how some of these risks can be mitigated by having more flexible parking policies, e.g., allowing electric vehicles to use parking spaces for fuel vehicles.

The obtention of simple formulae for the Lebesgue constants arising in the the classical Fourier series approximation is presented. Both even and odd cases are treated enlarging Fejér result. Asymptotic formulae are also obtained.

The relationship between religion and politics is a constant in the history of humanity. In the specific case of Western culture, it is possible to trace an archeology of the political as an effect of theological-political devices (essentially Christian-inspired). If we add to this the evolution of politics, in modern times, towards biopolitics, then the relationship focuses on very concrete topics. This is the case of the immunological process – from a personal, social, and philosophical perspective – thoroughly analyzed by Italian philosopher Roberto Esposito. In the context of his philosophical immunology, the place of religion is mainly archaeological and is interpreted critically. This article also aims to critically analyze his position, proposing a reading close to his thought but which is, at the same time, somewhat different.

Coffee is not only a delicious beverage but also an important dietary source of natural antioxidants. We live in an oxidative world where it is impossible to avoid pollution, stress, food additives, radiation, and other sources of oxidants that eventually lead to severe health disorders. Fortunately, there are chemicals in our diet that counteract the hazards posed by the reactive species that trigger oxidative stress. They are usually referred to as antioxidants; some of them can be versatile compounds that exert such a role in various ways. This review summarizes, from a chemical point of view, the antioxidant effects of relevant molecules found in coffee. Their ways of action and trends in activity are analyzed, considering the data gathered so far from both theory and experiments. The influence of the media and pH in aqueous solution, and structure-activity relationships are discussed. The protective role of the explored compounds is examined. A particular section is devoted to derivatives of some coffee components, and another one to their bioactivity. The data used in the analysis come from theoretical anc computational protocols, which have been proven to be very usefull in this context. Hopefully, the information provided here will promote further investigations into the amazing chemistry contained in our morning cup.

Coffee is not only a delicious beverage but also an important dietary source of natural antioxidants. We live in an oxidative world where it is impossible to avoid pollution, stress, food additives, radiation, and other sources of oxidants that eventually lead to severe health disorders. Fortunately, there are chemicals in our diet that counteract the hazards posed by the reactive species that trigger oxidative stress. They are usually referred to as antioxidants; some of them can be versatile compounds that exert such a role in various ways. This review summarizes, from a chemical point of view, the antioxidant effects of relevant molecules found in coffee. Their ways of action and trends in activity are analyzed, considering the data gathered so far from both theory and experiments. The influence of the media and pH in aqueous solution, and structure-activity relationships are discussed. The protective role of the explored compounds is examined. A particular section is devoted to derivatives of some coffee components, and another one to their bioactivity. Hopefully, the information provided here will promote further investigations into the amazing chemistry contained in our morning cup.

The concept of geostationary VHTS (Very High Throughput Satellites) is based on multibeam coverage with intensive frequency and polarization reuse in addition to the use of larger bandwidths in the feeder links, in order to provide high capacity satellite links at a reduced cost per Gbps in orbit. The dimensioning and design of satellite networks based on VHTS imposes the analysis of multiple trade-offs to achieve an optimal solution in terms of cost, capacity and figure of merit of the user terminal. In this paper, we propose a new method for sizing VHTS satellite networks based on an analytical expression of the forward link CINR (Carrier-to-Interference-plus-Noise Ratio) that is used to evaluate the trade-off of different combinations of system parameters. The proposed method considers both technical and commercial requirements as inputs including the constraints to achieve the optimum solution in terms of the user G/T, the number of beams and the system cost. The cost model includes both satellite and ground segments. Exemplary results are presented with feeder links using Q/V bands, DVB-S2X and transmission methods based on CCM and VCM (Constant and Variable Coding and Modulation, respectively) in two scenarios with different service areas.

This paper proposes the use of Bayesian inference techniques to search for and obtain valid instruments in dynamic panel data models where endogenous variables may exist. The use of Principal Component Analysis (PCA) allows for obtaining a reduced number of instruments in comparison to the high number of instruments commonly used in the literature, and Monte Carlo Markov Chain (MCMC) methods enable efficient exploration of the instrument space, deriving accurate point estimates of the elements of interest. The proposed methodology is illustrated in a simulated case and in an empirical application, where the partial effect of a series of determinants on the attraction of international bank flows is quantified. The results highlight the importance of promoting and developing the private sector in these economies, as well as the importance of maintaining good levels of credit worthiness.

The global pandemic of COVID-19 accounts for more than 14,000 deaths worldwide. However, little is known about the host genetics interaction with infection and COVID-19 progression. To better understand the role of host genetics, we review the current literature, aggregate readily available genetic resources, and provide some updated analysis relevant to COVID-19 and associated phenotypes. Using the unrelated individuals in UK Biobank (total n = 337,579 across 5 populations), we aggregate human leukocyte antigen and ABO blood type frequencies. We find significant and consistent risk reduction of blood group O reported in Zhao et al. and encourage broad sharing of ABO blood type frequencies that are readily accessible across COVID-19 with mild, moderate, and severe/critical symptoms for robust inferences at https://tinyurl.com/abo-covid19. In addition, we generate polygenic risk scores (PRSs) weights for 29 blood measurements, including clinically relevant haematological measurements for COVID-19, such as lymphocyte count and percentage. Focusing on the 8 most COVID-19 clinically relevant blood measurements, we performed PRS-PheWAS analysis across 44 disease antigen measurements (n = 6,643 unrelated individuals in White British group), infectious diseases and acute respiratory infections (n = 20,928 cases and 349,000 controls across 3 population groups) and deaths (n = 1,846 cases and 368,082 controls), recorded in hospital inpatient record and death registry data, respectively, in UK Biobank, and find host genetic PRS associations with disease risk. Taken together, we anticipate these resources (https://github.com/rivas-lab/covid19) will aid in improving our understanding of host genetic risk factors playing a role in SARS-CoV-2 infection and COVID-19 disease severity.

Key performance indicators are essential for any company to enhance its competitiveness. How-ever, a common issue is the manual collection of production data using record sheets, which are later digitized on desktop computers and processed in Excel sheets. Shockingly, 41% of companies in Mexico have no plans for digitalization. This work aims to develop a Real-time Productivity Indicator Monitoring System using Industry 4.0 technologies for a medium-sized manufacturing firm specializing in die-cutting automotive parts. The Advanced Quality Planning methodology was applied to develop the Conceptual, Product, and Process Engineering and its validation. The experimental tests demonstrated a reliability level of 99.98%, which exceeded initial expectations. The primary contributions presented in this work are related to the development of algorithms, communication protocols, data analysis, and general optimization of the calculation process. The study's only limitation was the short experimentation time.

This study explores the dependence of drone acoustic detection systems performance on distance, using learning machines with different complexities, from simple linear discriminants, to deep neural networks, such as YAMNet, which exploits transfer learning. Other machine learning systems studied are the multilayer perceptron, support vector machines and random forest. These methods have been evaluated with a meticulously selected database that includes a wide variety of drone and interference sounds, previously processed by array signal processing and affected by ambient noise. Two strategies for training learning machines are considered. In the first one, they are trained with unattenuated signals, trying to preserve the information generated by the sound sources, but they are tested considering the attenuation with distance, achieving effective detection at distances up to 200 metres with some methods, especially linear discriminant. In all cases, the existence of interferences that hinder detection is considered. In the second strategy, the systems are trained and tested with attenuated signals as a function of distance. The effective detection range increases up to 300 metres for most methods and up to 500 metres for the YAMNet based detector. In addition, this second approach raises the possibility of developing specialised detectors for each distance range, thus significantly extending the effective detection range. These results underline the promising potential of acoustic detection of drones at various distances, encouraging further exploration in this research area.

This study is focused to the aquatic environments of the Sian Ka’an reserve, a World Heritage Site. We applied protocols recently developed for the rapid assessment of most animal taxa inhabiting any freshwater system, by using light traps, and DNA barcodes, represented by the mitochondrial gene Cytochrome Oxidase I (COI). We DNA barcoded 1037 specimens of mites, crustaceans, insects, and fish larvae from 13 aquatic environments close or inside the reserve, with a success rate of 99.8%. In total, 167 Molecular Operational Taxonomic Units (MOTU’s) were detected. From them we identified 43 species. All others remain as a MOTU. For analyzing the adult fish communities, we applied the non-invasive method of environmental DNA (eDNA), and identified the sequences obtained with the Barcode of Life Database (BOLD). We found 25 fish species, and other terrestrial vertebrates from this region. No alien species was found. After a comparison of the MOTU’s from all systems, we found that each water body was unique respect the communities observed. The reference library presented here represents the first step for future programs to detect any change in these ecosystems, including invasive species, or improve knowledge of freshwater zooplankton, because most of the MOTU’s are possibly new species to science.

The lymphocyte function–associated antigen-1 (LFA-1) (also CD11a/CD18 and αLβ2), is just one of many integrins in the human body, but its significance derives from its exclusive presence in leukocytes. In this review, we summarize the studies relating LFA-1 and its major ligand ICAM-1 (CD54) with cancer, through the function of lymphocytes and myeloid cells on tumor cells. We consider how LFA-1 mediates the interaction of leukocytes with tumors and the role of ICAM-1 in tumor dynamics, which can be independent of its interaction with LFA-1. A more detailed examination of LFA’s role within B-cell chronic lymphocytic leukemia is made. Finally, we discuss the role of LFA-1-harboring exosomes in tumor growth and metastasis.

Extracellular vesicles (EV) are a very heterogeneous group of cell-derived vesicles released by almost all kind of living cells. EV are involved in intercellular communication, both locally and systemically, since they induce signals and transfer their contents (proteins, lipids, RNAs) to other cells, which subsequently trigger a wide variety of biological responses in the target cells. How-ever, cell surface receptor-induced EV release is limited to cells from the immune system, includ-ing T lymphocytes. T cell receptor activation of T lymphocytes induces secretion of EV containing T cell receptor for antigen and several bioactive molecules, including proapoptotic proteins. These EV are thus specific for antigen-bearing cells, which make them ideal candidates for a cell-free, EV-dependent cancer therapy. In this review we discuss the generation of EV by T lymphocytes and some potential therapeutic approaches of these EV.

Vegetation identification using remote sensing is essential for understanding terrestrial ecosystems and monitoring climate change. This technology by providing high-resolution images of the Earth's surface from satellites, aircraft, and drones has revolutionized the way scientists study and un-derstand vegetation patterns, providing information on the distribution, structure, and health of plant communities in different regions and biomes. However, identifying vegetation in multi and hyperspectral images remains a difficult, time-consuming, and costly process. Traditional methods for vegetation mapping involve the in-terpretation of spectral indices such as the Normalized Difference Vegetation Index (NDVI), alt-hough they often suffer from limitations such as manual interpretation and limited spatial resolution of satellite images. Furthermore, machine learning techniques, artificial neural networks, decision trees, support vector machines, and random forests have shown promising results in identifying and classifying vegetation cover from hyperspectral images. However, due to the need for per-son-nel with specialized expertise, their application on a large scale is still challenging. On the other hand, correlation methods between curves have emerged as powerful and simplified tool for comparing spectral signatures of hyperspectral image pixels and efficiently classifying vegetation in a study area. Pearson's correlation coefficient and spectral angle mapper are among the most common correlation methods used in vegetation mapping. These correlation methods, among many others available, offer an easily implemented and computationally efficient approach, making them particularly useful for applications in developing countries or regions with limited resources. In this article, a comparative study of correlation/distance metrics was conducted for the detection of vegetation pixels in hyperspectral images. The study allowed for the comparison of five distance and/or correlation metrics: direct correlation, cosine similarity, normalized Euclidean distance, Bray-Curtis’s distance, and Pearson correlation. The two metrics that yielded the best accuracy results in vegetation pixel detection were direct correlation and Pearson correlation. Based on the selected methods, a vegetation detection algorithm was implemented and validated on a hyper-spectral image of the Manga neighborhood in Cartagena de Indias, Colombia. The spectral library was utilized for image processing, while the numpy and scipy libraries in the Python programming language were used for the mathematical calculation of correlations. Both the study's approach and the implemented algorithm aim to serve as a reference for conducting detection studies of various material types in hyperspectral images using open-access programming platforms.

Defining measures of network efficiency and vulnerability for networks is a pivotal aspect in modern networking paradigms. We approach this problem from a game-theoretical perspective. We will consider networks in which actors have social or economic interests modeled by means of a cooperative game. This allows to define, for each network, a family of efficiency measures and another of vulnerability measures, parameterized by the game. The proposed measures use the within groups and the between groups Myerson values. These two values respectively measure which part of the classical allocation of Myerson corresponds to the productivity of players and which part to the intermediation costs. Also, which part of total centrality in social networks is due to communication or to beteewnness. In our proposal, the efficiency of a network is the proportion of the total productivity (or centrality) that players can retain using the network topology. The intermediation costs (and the betweenness centrality) can be viewed as a weakness with a negative impact. Then, we propose to calculate vulnerability as the proportion expent by players in intermediation payments. We explore the properties of these measures and we particularize them to several structures and particular games, also analyzing their asymptotic behaviour.

The novel respiratory disease COVID-19 has reached the status of worldwide pandemic and large efforts are currently being undertaken in molecularly characterizing the virus causing it, SARS-CoV-2. The genomic variability of SARS-CoV-2 specimens scattered across the globe can underly geographically specific etiological effects. In the present study, we gather the 48,635 SARS-CoV-2 complete genomes currently available thanks to the collection endeavor of the GISAID consortium and thousands of contributing laboratories. We analyze and annotate all SARS-CoV-2 mutations compared with the reference Wuhan genome NC_045512.2, observing an average of 7.23 mutations per sample. Our analysis shows the prevalence of single nucleotide transitions as the major mutational type across the world. There exist at least three clades characterized by geographic and genomic specificity. In particular, the clade G, prevalent in Europe, carries a D614G mutation in the Spike protein, which is responsible for the initial interaction of the virus with the host human cell. Our analysis may drive local modulation of antiviral strategies based on the molecular specificities of this novel virus.

Copper-nitride (Cu3N) semiconductor material is attracting much attention as a potential, next-generation thin-film solar-light absorber in solar cells. In this communication, polycrystalline Cu3N thin films were prepared using reactive-RF-magnetron-sputtering deposition, at room temperature, onto glass and silicon substrates. The very-broadband optical properties of the Cu3N thin film layers were studied by UV-MIR (0.2-40 μm) ellipsometry and optical transmission, to be able to achieve the goal of a low-cost absorber material to replace the conventional silicon. The reactive-RF-sputtered Cu3N films were also investigated by focused ion beam scanning electron microscopy, and both FTIR and Raman spectroscopies.

This paper reviews the unilateral and bilateral, one- and two-dimensional Laplace transforms. The unilateral and bilateral Laplace transforms are compared in the one-dimensional case, leading to the formulation of the initial-condition theorem. This problem is solved with all generality in the one- and two-dimensional cases with the bilateral Laplace transform. General two-dimensional linear systems are introduced and the corresponding transfer function defined.

Several clinically useful anticancer drugs selectively kill cancer cells by inducing DNA damage; the genomic instability and DNA repair defects of cancer cells make them more vulnerable than normal cells to the cytotoxicity of DNA-damaging agents. Because epoxide-containing compounds can induce DNA damage, we have used the MTT assay to evaluate the selective cytotoxicity of three epoxyalkyl galactopyranosides against A549 lung cancer cells and MRC-5 lung normal cells. Compound (2S,3S)-2,3-Epoxydecyl 4,6-O-(S)-benzylidene-β-D-galactopyranoside (EDBGP) showed the highest selective anticancer activity and was selected for mechanistic studies. After observing that EDBGP induced cellular DNA damage (comet assay), we found that cells deficient in nucleotide excision repair were hypersensitive to the cytotoxicity of this compound; this suggests that EDBGP may induce bulky DNA adducts. EDBGP did not inhibit glycolysis (glucose consumption and lactate production). Pre-treatment of lung cancer cells with several antioxidants did not reduce the cytotoxicity of EDBGP, thereby indicating that reactive oxygen species do not participate in the anticancer activity of this compound. Finally, EDBGP was screened against a panel of cancer cells and normal cells from several tissues, including three genetically modified skin fibroblasts with increasing degree of malignancy. Our results suggest that epoxyalkyl galactopyranosides are promising lead compounds for the development of new anticancer agents.

Retailers must have accurate sales forecasts to operate their businesses efficiently and effectively and to remain competitive in the marketplace. Global forecasting models like RNNs can be a powerful tool for forecasting in retail settings, where multiple time series are often interrelated and influenced by a variety of external factors. By including covariates in a forecasting model, we can better capture the various factors that can influence sales in a retail setting. This can help improve the accuracy of our forecasts and enable better decision-making for inventory management, purchasing, and other operational decisions. In this study we investigate how the accuracy of global forecasting models is affected by the inclusion of different potential demand covariates. To ensure the significance of the study's findings, we used the M5 forecasting competition's openly accessible and well-established dataset. The results obtained from the DeepAR models, which were trained on various combinations of features including time, price, events, and IDs, suggest that individually only the features corresponding to IDs improve the baseline model. However, when all the features are used together, the best performance is achieved, indicating that the individual relevance of each feature is emphasized when the information is given jointly. Comparing the model with features to the model without features, there is an improvement of 1.76\% for MRMSSE and 6.47\% for MMASE.

By partly generalizing the Lipschitz condition of existing results to the generalized Lipschitz one, the author utilizes a fixed point theorem, variational method and Lyapunov function method to derive the unique existence of globally asymptotical input-to-state stability of positive stationary solution for Gilpin-Ayala competition model with diffusion and delayed feedback under Dirichlet zero boundary value. Remarkably, it is the first paper to derive the unique existence of the stationary solution of reaction-diffusion Gilpin-Ayala competition model, which is globally asymptotical input-to-state stability. And numerical examples illuminate the effectiveness and feasibility of the proposed methods.

The effect of embryo reinsertion immediately after embryo flushing was studied to determine its effect on luteal function, pregnancy outcome, endometrial bacterial contamination, and embryo morphology. In Experiment 1, eight mares were used during 32 cycles (8 cycles in each group): for the first two groups, inseminated mares were flushed 8 days after ovulation and prostaglandin F2α was not administered: in group EF-ET (embryo flushing and embryo transfer) the embryo was reinserted in the same donor mare, while in the EF group, no further procedure was performed. In the third group (ET), non-inseminated mares (recipients) received a Day 8 embryo 5 to 8 days after ovulation. Progesterone concentration was measured before EF/ET and 72 h after in the 3 groups. Pregnancy diagnosis was performed within 6 days of transfer. In Experiment 2, twelve mares were used during 17 cycles in two groups: EF-ET (n=11) and ET (n=6), as in Experiment 1, except that every mare was flushed 24 h after embryo transfer to retrieve the embryo. Fewer pregnancies resulted after transfer in EF-ET cycles (0(8, 0%) than in the ET group (6/8, 75%). Progesterone concentration decreased significantly (p=0.05) 72 h after EF-ET, but not in EF or ET cycles (p>0.1). Three mares from the EF-ET showed full luteolysis and signs of endometritis. In Experiment 2, more (5/6; p=0.08) grade I embryos were recovered in the ET compared to the EF-ET group (3/7); 4 embryos were graded III-IV (were broken or had signs of degeneration) in the EF-ET group, but none in the ET group. In both groups, capsule fragments were obtained as indicative of the presence of a recently destroyed embryo in the EF-ET (n=3) and ET (n=1) groups. Positive bacterial cultures were obtained in 2/11 and 1/6 embryo flushes from the EF-ET and ET groups, respectively.

In this paper is presented the design and syntheis of a dynamic output feedback neural network controller for a non-holonomic mobile robot. First the dynamic model of a non-holonomic mobile robot is presented, in which these constraints are considered for the mathematical derivation of a feasable representation for this kind of robot. Then two control strategies are provided based on kinematic control for this kind of robot. The first control strategy is based on driftless control, this means, that considering that the velocity vector of the mobile robot is orthogonal to its restriction a dynamic output feedback and neural network controller is designed in order that the control action would be zero only when the velocity of the mobile robot is zero. The Lyapunov stability theorem is implemented in order to find a suitable control law. Then another control strategy is designed for trajectory tracking purposes, which similar to the driftless controller, a kinematic control scheme is provided but suitable to implement in more sophisticated hardware. In both control strategy a dynamic control law is provided along with a feedforward neural network controller, so in this way, by the Lyapunov theory the stability and convergence to the origin of the mobile robot position coordinates is ensured. Finally, two numerical experiment are presented in order to validate the theoretical results synthetized in this research study. Discussions and conclusions are provided in order to analyze the results found in this research study.

The aim of this study was to analyze the level of specific back-health-related physical activity and exercise knowledge. This is a cross-sectional study. A representative sample of 1500 students were recruited with a confidence level of 95% and an accepted standard error of ±2.53%. Individuals were aged between 13 and 18 years old (mean age= 15.18; SD = ±1.446). Self-reported questionnaires were used to record back-health-related physical activity and exercise knowledge concerning back care in adolescents. The level of specific knowledge of back health education related to physical activity and exercise in adolescents was low (X = 2.05, SD = ±2.264). Only 10.9% of the students passed the specific knowledge test, achieving a grade equal or superior to 5. The boys average score was higher (X = 2.17, SD = ±2.312) than the girls (X = 1.94, SD = ±2.212) with statistically significant differences (p = .048). The level of specific knowledge increased with age (F = 11.531; p &lt; .001). High school students have a low level of specific knowledge. Physical Education teachers should apply the conceptual content properly. Knowledge is the first step towards changing behavioral habits. Back care education in the school curriculum is recommended.

Groupers (Epinephelidae) are ecologically important mesopredators that support valuable fisheries across the globe. Many groupers display slow growth and maturity, high longevity, ontogenetic habitat shifts, spawning-related migrations and aggregations, and protogynous hermaphroditism, which make them susceptible to overexploitation. In this review, I synthesize available information related to the management of grouper fisheries across the southeastern and Caribbean U.S. I highlight current management challenges, such as managing multispecies reef fish fisheries with growing recreational fishing effort. I discuss management interventions with limited success, such as establishing marine protected areas to improve the populations of groupers that display protogynous hermaphroditism. I also highlight management successes, such as recovering historically depleted grouper stocks, and ecosystem-based considerations in grouper stock assessments. I discuss how climate change and anthropogenic effects are expected to affect groupers. Lastly, I provide examples of stakeholders involved in monitoring and management efforts directed at grouper stocks. The purposes of this review are to demonstrate the complexities of managing grouper fisheries and provide a road map for future research and conservation efforts into these economically and ecologically relevant fishes within and beyond the region.

Computer extended Descriptive Geometry (CeDG) is a new approach to solve and build computer models of three dimensional (3D) geometrical systems through descriptive geometry procedures that have demonstrated reliability and accuracy. CeDG may calculate a parametric algebraic exact form for the spatial curves generated in the intersection of two surfaces, as well as of the flattened pattern of any developable surface involved in those encounters. This study presents first the theoretical foundations and methodology to calculate those parametric algebraic curves. Secondly, a compound hopper is defined and modelled through CeDG (implemented in GeoGebra) and CAD (Solid Edge 2023) approaches to evaluate the advantages of CeDG against CAD. The results demonstrate the robustness and accuracy of the CeDG technique for surfaces intersection and flattening and the advantages of CeDG against Solid Edge 2023 in solving the hopper case study.

The ceramic sherds from approximately 20 samples of lead-glazed tableware, recovered from diverse archaeological sites, including three repurposed storage pits transformed into dumpsters within the medieval city of Santarém (13th-14th century), underwent a meticulous examination. This investigation utilized techniques such as micro-Raman, ground state diffuse reflectance absorption, and X-ray fluorescence spectroscopies, in addition to X-ray diffraction and stereomicroscopy. A parallel study was conducted on contemporaneous European ceramics (glazed sherds) sourced from archaeological sites dating back to the 13th-15th centuries in Saintonge (France), Ardenne, Zomergem, and Bruges (Belgium), as well as Surrey-Hampshire, Kingston, and Cheam (England). The colour of the ceramic bodies is predominantly white or whitish, with a few exhibiting a vivid red hue. Ceramic sherds with a light paste composition were likely crafted using kaolin clays as raw materials. Analyses of fabric, mineralogical, and elemental composition of the sherds suggest that the majority of Santarém's glazed ceramics were locally or regionally produced, potentially derived from a Pliocene kaolin-rich sand formation. However, this conclusion is not supported by the absence of discovered lead glaze kilns or workshops in Santarém for the late Middle Ages. A distinctive feature from the European workshop ceramics lies in the quartz temper content and fabric.

Changes brought about by the Internet to Scholarly Communication and the spread of Open Access movement, have made it possible to increase the number of potential readers of published research dramatically. This two-phase study aims, at first, to assert the satisfaction of the potential for increased open access to articles published by authors at the University of Coimbra, in a context when there was no stimulus for the openness of published science other than an institutional mandate set by the University policy on Open Access (“Acesso Livre”). The satisfaction of the access openness was measured by observing the actual archiving behavior of researchers (either directly or through their agents). We started by selecting the top journal titles used to publish the STEM research of the University of Coimbra (2004-2013) by using Thomson Reuters’ Science Citation Index (SCI). These titles were available at the University libraries or through online subscriptions, some of them in open access (21%). By checking the journals' policy at the time regarding self-archiving at the SHERPA/RoMEO service, we found that the percentage of articles in Open Access (OA) could rise to 80% if deposited at Estudo Geral, the Institutional Repository of the University of Coimbra, as prescribed by the Open Access Policy of the University. As we concluded by verifying the deposit status of every single paper of researchers of the University that published in those journals, this potential was far from being fulfilled, despite the existence of the institutional mandate and favorable editorial conditions. We concluded, therefore, that an institutional mandate was not sufficient by itself to fully implement an open access policy and to close the gap between publication and access. The second phase of the study, to follow, will rescan the status of published papers in a context where the Portuguese public funding agency, the Fundação para a Ciência e a Tecnologia, introduced in 2014 a new significant stimulus for open access in science. The FCT Open Access Policy stipulates that publicly funded published research must be available as soon as possible in a repository of the Portuguese network of scientific repositories, RCAAP, which integrates the Estudo Geral.

This article explores the synergies and progression of feminism towards a comprehensive, emancipatory and sustainable policy from a theoretical point of view, particularly from a radical gender focus, suggesting the masculinist theory as a complement in the fight against the patriarchal-capitalist system, whose greatest achievement was to use a ‘feminist rhetoric’ with no feminist content, which implies a hidden reconfiguration, even more patriarchal, of the geographical borders of countries from the notion of State-nations to the entrepreneurial-nations. A theoretical model is proposed to analyse the adoption and compliance feminist behaviour in order to identify the uncompliant and unsustainable behaviour, that is, the friendly machismo or feminism light. Finally, in a preliminary manner, the foundations of a new masculinist theory and policy will be listed as a necessary step towards a deeply feminist and radical emancipatory policy.

Purpose: The impact of ethical leadership on employee emotional exhaustion has been widely analyzed. However, the effect of the leader's moral intensity on the employee's emotional state has gone unnoticed. This research seeks to show that ethical management by the leader affects employees' emotional exhaustion in accordance with the scope of the leader's moral standards. Their relationship is not necessarily linear but adopts a curvilinear pattern as a function of the leader's ethical intensity, and affective commitment acts as a mediating mechanism. Methods: A simple mediation model is used. The sample consists of 448 professionals in six organizations in the Colombian electrical sector who responded to an online questionnaire. The sampling is probabilistic by conglomerates. Findings: This research revealed that ethical behavior is voluntary in nature and develops in an environment of trust. When the ethical leader surpasses specific moral turning points, the follower's learning becomes an obligation, preventing affective fluidity. A search for acceptance implies constant consumption of resources that weakens the follower's capacity for self-regulation until it is exhausted. Furthermore, when the leader's expectations are difficult to achieve, affective commitment causes emotional ambiguity in followers, intensifying the stress associated with their role and increasing the likelihood of burnout. Originality: This research challenges conventional wisdom about the positive, linear effect of ethical leadership on employees' emotional state. It broadens the understanding of this management style and fills a crucial knowledge gap by introducing a new perspective. Practical Implications: A horizontal, balanced, and accessible leader can quickly convey a convincing ethical discourse. Emphasizing the vulnerability and importance of human beings can help prevent moral anguish and ethical distances. This, in turn, provides followers with resources to mitigate exhaustion and strengthen commitment.

This article analyses from a post-Marxist view, particularly, an ecological and gender-oriented perspective, the perception and attitudes of the Mexican people by gender, political affiliation and income level towards such current environmental issues as global warming, water shortage, water pollution and the influence of economic growth on the environment, among others. It highlights the influence of political ideology on the environment and of gender awareness on conservation and a more positive attitude towards ecological issues, despite women having usually been excluded from the administrative and decision-making arenas. A new theoretical model is proposed related to the Responsibility Footprints, a new concept more critical than the neoliberal Corporate Social Responsibility. The data for this study come from the 2012 International Social Survey Program. The results analysed brought to light some relevant questions for designing public policies that will greatly bolster initiatives to prompt better female professional involvement in the conservation of natural resources.

The COVID-19 pandemic has posed a significant global threat, leading to several initiatives for its control and management. One such initiative involves wastewater-based epidemiology, which has gained attention for its potential to provide early warning of virus outbreaks and real-time information on its spread. In this study, water samples from two wastewater treatment plants (WWTPs) located at the south east of Spain (Region of Murcia) namely Murcia, and Cartagena, were analyzed by RT-qPCR, Phylogenetic Analysis, and Machine Learning Approach. The aim was to determine whether SARS-CoV-2 detection in the WWTPs of these two cities could serve as a proxy for the virus's spread in the population. The results confirmed that the levels of SARS-CoV-2 in these wastewater samples changed concerning the number of SARS-CoV-2 cases detected in the population and variant occurrences were in line with clinical reported data. Additionally, the phylogenetic analysis showed that samples obtained in close sampling times exhibited a higher similarity than those obtained more distantly in time. A second analysis using a machine learning approach based on the mutations found in the SARS-CoV-2 spike protein was also conducted. Hierarchical Clustering (HC) was used as an efficient unsupervised approach for data analysis. Results indicated that samples obtained in October 2022 in Murcia and Cartagena were significantly different, which corresponded well with the different virus variants circulating in the two locations. The proposed methods in this study are adequate for comparing the Accumulated Natural Vector (ANV) of the SARS-CoV-2 sequences as a preliminary evaluation of potential changes in the variants that are circulating in a given population at a specific time point.

3D cell cultures have improved the evaluation of drugs for cancer therapy, due to their high similarity to solid tumors. In melanoma, autophagy appears to show a dual role depending on the progression of the disease. p62 protein has been proposed for the evaluation of autophagic flux since its expression is an indicator of the state of autophagy. Pentoxifylline (PTX) and Norcantharidin (NCTD) are drugs that have been shown to have anticancer effects in various types of cancer. In this work, B16F1 mouse melanoma cell line was used, from which two-dimensional (2D) monolayer cultures and three-dimensional (3D) organoids were carried out using the hanging drop technique. The expression of p62 was determined by western blot and immunofluorescences. Our results indicate that pentoxifylline reduces p62 expression in both types of culture. While Norcantharidin increases its expression in 3D cultures at 24 h. Therefore, these drugs could have a potential therapeutic use for the regulation of autophagy in melanoma, depending on the state of evolution of the disease.

The aim of this study was to verify the effects of blood flow restriction on movement velocity and muscle activity during the back-squat exercise. Methods: Twenty-four university students participated in this study. In two randomized 72-hours apart sessions, participants performed a 4-set protocol consisting of 30-15-15-15 repetitions performed at 30% of their one-repetition maximum in the back-squat exercise. In both sessions, neuromuscular function was monitored by surface electromyography (EMG) and movement velocity (mean propulsive velocity [MPV], peak concentric velocity [Vmax] and the effort index [EI]). Blood flow restriction (BFR) was applied during exercise in one of the experimental sessions with 80% of full arterial occlusion pressure over lower limbs. Results: BFR condition showed higher (p&lt;0.05) EI, peak and rooted mean square normalized EMG in set 1 compared to set 2. Similar MPV and Vmax were observed at each set for both BFR and control conditions. No significant differences were observed between conditions at any set. Conclusions: BFR did not imply changes in neuromuscular performance during low-intensity resistance training, but it might induce greater intra-series velocity loss and less activation of the muscles involved.

A phase 1-2, prospective, multicenter, randomized, open-label clinical trial (Code RPCEC00000382, https://rpcec.sld.cu/trials/RPCEC00000382-En/), with parallel groups, involving 1161 participants was designed to assess safety and immunogenicity of two Cuban COVID-19 vaccines (Mambisa and Abdala) in boosting COVID-19 immunity of convalescent adults after receiving one dose of either vaccine. The main safety outcome was severe vaccination adverse events occurring in &lt;5% of vaccinees. Main immunogenicity success endpoints were ≥4-fold anti-RBD IgG seroconversion or ≥20% increase in ACE2-RBD inhibitory antibodies in &gt;55% of vaccinees in Phase 1 and &gt;70% in Phase 2. Neutralizing antibody titers against SARS-CoV-2 variants were evaluated. Both vaccines were safe; no deaths or severe adverse events occurred. Mild intensity adverse events were the most frequent (&gt;73%); headache predominated for both vaccines. Phase 1 responders were 83.3% (p = 0.0018) for Abdala. Mambisa showed similar results. Phase 2 responders were 88.6% for Abdala (p &lt;0.0001) and 74.2% for Mambisa (p = 0.0412). In both phases, anti-RBD IgG titers, inhibition percentages and neutralizing antibody titers increased significantly after the booster dose. Both vaccines were safe and their immunogenicity surpassed the study endpoints.

Background: The presence of a leadership role in the nursing manager appears to be closely related to a positive and productive work environment within health settings. In some contexts, such as Mexico, the profile of the nursing manager has not been formally defined, and, sometimes those who occupy these positions do not always have sufficient training, and therefore this vocation, which is related to the social image of the nursing profession. This study aims to understand the influence of the vocation for leadership that the nursing manager has and how it can influence the work environment, through the analysis of experiences lived by health professionals with a management profile of different health environments; Methods: Qualitative study of an approximation to grounded theory using Corbin &amp; Strauss as reference, using semi-structured individual interviews as a technique, and with the participation of 10 Mexican nursing managers from second-level care hospitals; Results: The meaning of the vocation for the interviewed managers is based in the first instance on the love of the profession and the vocation to be a nurse, then on the development of leadership for decision-making in practice and is fed back with the positive effects that it generates in the work environment, helping them to better organize human resources and professional activities, and strengthening themselves with specific training on the subject and the experience acquired. ; Conclusions: An understanding model is provided about the phenomenon where two central categories were identified, the first central category is the "Management vocation and natural nursing leadership" which is the basis; The second central category is the "Explanation and influence of the managerial vocation, natural leadership and work environment in nursing". Two connection categories were also created; the connection category one "Motives, meaning, and practical vocation of managerial nursing" and the connection category two "Description of the managerial vocation, natural leadership, and work environment", said connection categories emanate from the central category one, to connect with the central category two, which contains the interaction of the managerial vocation, natural leadership, and work environment in nursing.

A correct system design can be systematically obtained from a specification model of a real-time system that integrates hybrid measurements in a realistic industrial environment, this has been carried out through complete Matlab / Simulink / Stateflow models. However, there is a widespread interest in carrying out that modeling by resorting to Machine Learning models, which can be understood as Automated Machine Learning for Real-time systems that present some degree of hybridization. An induction motor controller which must be able to maintain a constant air flow through a filter is one of these systems and it is discussed in the paper as a study case of closed-loop control system. The article discusses a practical application of ML methods that demonstrates how to replace such closed loop in industrial control systems with a Simulink block generated from neural networks to show how the proposed procedure can be applied to derive complete hybrid system designs with artificial neural networks (ANN). In the proposed ANN-based method to design a real-time hybrid system with continuous and discrete components, we use a typical design of a neural network, in which we define the usual phases: training, validation, and testing. The generated output of the model is made up of reference variables values of the cyber-physical system, which represent the functional and dynamic aspects of model. They are used to feed Simulink/Stateflow blocks in the real target system.

Elliptic scator algebra is possible in 1+n dimensions, n∈N. It is isomorphic to complex algebra in 1+1 dimensions, when the real part and any one hypercomplex component are considered. It is endowed with two representations: an additive one, where the scator components are represented as a sum; and a polar representation, where the scator components are represented as products of exponentials. Within the scator framework, De Moivre’s formula is generalized to 1+n dimensions in the so called victoria equation. This novel formula is then used to obtain compact expressions for the integer powers of scator elements. A scator in S1+n can be factored into a product of n scators that are geometrically represented as its projections onto n two dimensional planes. A geometric interpretation of scator multiplication in terms of rotations with respect to the scalar axis is expounded. The powers of scators, when the ratio of their director components is a rational number, lie on closed curves. For 1+2 dimensional scators, twisted curves in a three dimensional space are obtained. Collecting previous results, it is possible to evaluate the exponential of a scator element in 1+2 dimensions.

A robust methodology to simulate virtually the residual stresses pattern in welded steel plates is presented. The methodology is applied to the structural analysis of typical welded plates belonging to ship structures, and the effect of residual stresses on the elastoplastic behavior of plates loaded axially is analyzed in comparison to the residual stress free case, both for tension and compression and including initial imperfections. Residual stresses affect in different manner plates with different geometries; thus a parametric study is performed covering the usual range of variation of the most important plate parameters that control the strength of the plates, more precisely the slenderness and the aspect ratio. The results from finite elements analysis are compared with codes and most stablished formulations and recommendations of applicability in the prediction of load-shortening curves for hull’s bending strength evaluation, ultimate strength and ultimate strain of plate elements are made.

In this brief paper a quantum algorithm to calculate the Hamming distance of two binary strings of equal length (or messages in theory information) is presented. The algorithm calculates the Hamming weight of two binary strings in one query of an oracle. To calculate the hamming distance of these two strings we only have to calculate the Hamming weight of the xor operation of both strings. To test the algorithms the quantum computer prototype that IBM has given open access to on the cloud has been used to test the results.

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

We recently screened a series of new aziridines β-D-galactopyranoside derivatives for selective anticancer activity and identified 2-methyl-2,3-[N-(4-methylbenzenesulfonyl)imino]propyl 2,3-di-O-benzyl-4,6-O-(S)-benzylidene-β-D-galactopyranoside (AzGalp) as the most promising compound. In this article, we explore possible mechanisms involved in the cytotoxicity of this aziridine and evaluate its selective anticancer activity using cancer cells and normal cells from a variety of tissues. Our data show that AzGalp induces DNA damage (detected with the comet assay). Cells deficient in the DNA repair pathway nucleotide excision repair (NER) were hypersensitive to the cytotoxicity of this compound. These results suggest that AzGalp induces bulky DNA adducts, and that cancer cells lacking a functional NER pathway may be particularly vulnerable to the anticancer effects of this aziridine. Several experiments revealed that neither the generation of oxidative stress nor the inhibition of glycolysis played a significant role in the cytotoxicity of AzGalp. The combinations of AzGalp with either oxaliplatin or 5-fluorouracil slightly improved the ability of both anticancer drugs to selectively kill cancer cells. AzGalp also displayed selective cytotoxicity against a panel of malignant cells versus normal cells; the highest selectivity was observed for two acute promyelocytic leukemia cell lines. Additional preclinical studies are necessary to evaluate the anticancer potential of AzGalp.

In the context of global changes, Nature-Based Solutions (NBSs) increasingly draw attention as a possible way to reduce disaster risk associated with extreme hydro-meteorological events while providing human well-being and biodiversity benefits at the same time. The PHUSICOS platform is dedicated to gather and analyse relevant NBSs used to reduce disaster risk associated with extreme hydro-meteorological events in mountainous and hilly lands. To design the platform, an in-depth review of 11 existing platforms has been performed. The platform currently references 152 literature NBS cases and is continuously enriched with demonstrator sites through the contribution of NBS community. The platform also proposes a qualitative assessment of the NBSs collected according to 15 criteria related with five ambits: disaster risk reduction, technical and economical feasibility, environment, society and local economy. This paper presents the structure of the platform and a first analysis of its content.

Abstract: Understanding the reliability and sensitivity of jump testing is essential to determine the neuromuscular progress of athletes and make informed decisions. This study aimed to assess the reliability and sensitivity of countermovement jump (CMJ) and drop jump (DJ) tests metrics in female volleyball players. Sixteen semi-professional female volleyball players participated in the study. Intrasession and intersession reliability of CMJ and DJ metrics were evaluated using a randomized cross-over design. Dual force platform was used to collect data, and several dependent variables were calculated using forward dynamics. Intraclass correlation coefficients (ICC), coefficients of variation (CV) and minimum difference (MD) were calculated. The third attempt presented the highest values for both test, and changes in jump strategy in DJ. CMJ is consistent across sessions, while DJ also shows intersession differences (p<0.05) in 11 out of 15 variables. Most CMJ variables exhibit excellent reliability while DJ variables have lower reliability and higher variability. Concentric and eccentric impulses for DJ showed excellent reliability. Most CMJ variables showed excellent reliability and variability, DJ had lower reliability, higher variability, and lower sensitivity. These findings provide valuable information when assessing athletes' performance and highlight the reliability, sensitivity, and variability in jump performance for CMJ and DJ tests.

Camelina (Camelina sativa L.) is an oilseed with potential for use as a raw material in second-generation biofuels. Camelina has a seed yield of up to 2380 kg ha^-1 and contains around 45% fatty acids. Selection of a suitable site is critical for production optimization. The objective of this study was to determine Chilean agro-climatic suitability for establishing camelina as a productive alternative. Climate and soil requirements and geographical restraints were evaluated for the species, considering the climatological characteristics of its regions of origin, as well as regions where camelina is successfully grown in the rest of the world. The variables considered include factors (maximum temperatures of the warmest month, water deficits, and degree days) and limitations (altitude, geomorphology, and current land use), which permitted the evaluation of the national territory for a certain level of suitability. It was determined that 1.3% of the national territory (960,664 ha) has some degree of suitability for camelina adoption. Between the Biobío and Los Lagos regions, 49.0% of land (471,203 ha) is in the category of without thermic restrictions, with mild water restrictions, and mild soil restrictions or without information, which can be used for camelina production. The Los Ríos region had 21.4% surface area (321,176 ha) with some level of suitability for camelina, the most suitable region to establish this crop in Chile.

A theoretical model to translate the evolution over time, in early stages, of growth and accumulation of biofilm bacterial mass is introduced. The model implies the solution of a system of differential-difference master equations. The application of an algorithm like Miller´s tree term recurrence, already known for Bessel functions of first kind, allows an exact calculation of the solutions of such equations, for a wide range of parameters values and time. For biofilm model a five term recurrence is deduced and applied in a backwards computation. A suitable normalisation condition completes the reach of the solution.

This study applies several natural language processing techniques for characterizing social groups by analyzing published text in social media. The resulting computed values are proposed as features for modeling social groups and measure distances or similarities among them, along further data that could help understanding group behavior according to language usage. In this study, we have analyzed the messages published on Twitter regarding patriotism by the main political parties in Spain. The results show that lexical resources and topic modelling algorithms are useful to model different groups and serve as comparison tools to better understand the topics these groups are talking about.

Development of biomarkers of analytes with interest in clinic is an important field of study. In this work, we synthesized and analyzed the new fluorescent acetate-biomarker, Iso-PG. The mechanism of detection is the acetate buffer mediated proton transfer reaction. The rate constants involved were obtained, and we measured the change in the fluorescence lifetime produced as a consequence of the presence of acetate in the medium. Finally, we checked its potential use as acetate biomarker in synthetic serum

Natural rivers in urban areas bear significant potential to provide ecosystem services for the surrounding inhabitants. However, surface sealing by houses and street networks, urban drainage, disposal of waste and wastewater resulting from advancing urbanization usually lead to the deterioration of urban rivers and their riparian areas. This ultimately damages their ability to provide ecosystem services. This paper presents an innovative methodology for a rapid and low-cost assessment of the ecological status of urban rivers and riparian areas in developing countries under data scarce conditions. The methodology uses a combination of field data and freely available high-resolution satellite images to assess three ecological status categories: river hydromorphology, water quality, and riparian land cover. The focus here is on the assessment of proxies for biophysical structures and processes representing ecological functioning that enable urban rivers and riparian areas to provide ecosystem services. These proxies represent a combination of remote sensing land cover- and field-based indicators. Finally, the three ecological status categories are combined to quantify the potential of different river sections to provide regulating ecosystem services. The development and application of the methodology is demonstrated and visualized for each 100 m section of the Pochote River in the City of León, Nicaragua. This spatially distributed information of the ecosystem service potential of individual sections of the urban river and riparian areas can serve as important information for decision making regarding the protection, future use, and city development of these areas, as well as the targeted and tailor-made development of nature-based solutions such as green infrastructure.

A correlation between Chinese traditional architecture and cultural concepts has been established to analyze the formalization of architectural and urban patterns in relation to environmental features. In this regard, we have discussed the process of standardization from architectural elements or modules related in different levels of composition and articulated around empty spaces following ancient cosmic concepts to achieve harmony with nature. The conclusions show that Chinese architectural patterns can only be understood in relation to nature, and in turn have profound environmental values from which lessons can be learned to advance towards a more sustainable architecture.

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates Quantum Spiking Neural Networks (QSNN) and Quantum Long Short-Term Memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conduct a comparative analysis of our model against existing quantum models such as Quantum Neural Networks and their classical counterparts, elucidating its unique contributions. Through empirical results, we aim to underscore the effectiveness of our approach in optimizing energy consumption in practical scenarios.

Deep learning neural networks require an immense amount of computation, especially in the training phase of the network when networks with multiple layers of intermediate neurons need to be built. In this paper, we will focus on the PSO algorithm with the aim of significantly accelerating the DLNN training phase by taking advantage of the GPGPU architecture and the Apache Spark analytics engine for large-scale data processing tasks. PSO is a bio-inspired stochastic optimization method whose goal is to iteratively improve the solution to a (usually complex) problem by attempting to approximate a given objective. However, parallelizing an efficient PSO is not a straightforward process due to the complexity of the computations performed on the swarm of particles and the iterative execution of the algorithm until a solution close to the objective with minimal error is achieved. In the present work, two parallelizations of the PSO algorithm have been implemented , both designed for a distributed execution environment. The synchronous parallel PSO implementation ensures consistency at the cost of potential idle time due to global synchronization, while the asynchronous parallel PSO approach improves execution time by reducing the need for global synchronization, making it more suitable for large datasets and distributed environments such as Apache Spark. Both variants of PSO have been implemented to distribute the computational load supported by this algorithm –due to the costly fitness evaluation and updating of particle positions– across the different Spark cluster executor nodes to effectively achieve coarse-grained parallelism, resulting in a significant performance increase over current sequential variants of PSO.

Seafood is considered one of the main food allergen sources by the European Food Safety Authority (EFSA). It comprises several distinct groups of edible aquatic animals including fish and shellfish such as crustacean and mollusks. Recently the EFSA recognized the high risk of food allergy over the world and established the necessity of developing new methodologies for its control. Consequently, accurate, sensitive and fast detection methods for seafood allergy control and detection in food products are highly recommendable. In this work, we present a comprehensive review of the applications of the proteomics methodologies for the detection and quantification of seafood allergens. For that, two consecutive proteomics strategies (Discovery and Targeted Proteomics) applied for the study and control of seafood allergy are reviewed in detail. In addition, future directions and new perspectives were also provided.

In this paper, based on the cumulated damage generated by the cyclical application of the testing vibration profile, a methodology to determine the reliability index of the analyzed component is given. In the analysis, the testing time, component geometry, applied weight, and material resonant frequency are all of them considered by using a dynamic, and amplitude factor. Then, from the generated vibration response data of the analysis, the corresponding bending stress is determined for each one of the rows of the testing profile. And by the cyclical application of the whole testing profile, the corresponding damage is cumulated to each profile cycle until the cumulated damage is D=1. Finally, the reliability that each one of the cumulated blocks (cyclical profile application) is determined by considering, the random vibration is a stress variable. Thus, we use the cumulative damage model with the inverse power law stress/life relationship to determine the two parameter Weibull distribution used to estimate the reliability index of each cumulated block. As a numerical application, we analyze a cantilever aluminum beam Al 6061-T6.

Soil erosion seriously affects vineyards. In this study, the influence of two plant covers on soil moisture and the effect of different physiographic conditions on runoff and sediment yields were evaluated in a rainfed vineyard formed by four fields (NE Spain) during 15 months. One field had spontaneous vegetation as plant cover and three fields had a cover crop of common sainfoin. The vineyards’ rows were dry and stable, whereas the inter-row areas were wet although very variable, and the corridors were wet and very stable. Soil moisture in the inter-row areas with Common sainfoin was much higher than in the rows (62% - 70%) whereas this difference was lower with spontaneous vegetation (40%). Two runoff and sediment traps (STs) were installed in two ephemeral gullies, and 26 time-integrated surveys (TIS) done. The mean and maximum runoff yields were 9.8 and 30.7 l TIS^–1 in ST2 and 13.5 and 30.2 l TIS^–1 in ST3. The mean turbidity was 333 and 19 g l^–1, and the maximum sediment yields were 41,260 and 2,778 g TIS^–1 in ST2 and ST3. Changes in the canopy covers (grapevines and plant covers) and rainfall parameters explained the runoff and sediment dynamics.

In this paper is shown the dynamic modeling and design of a passivity based controller for the RV-3SB robot. Firstly, the dynamic modeling of the of the Mitsubishi Rv-3SB robot is done by the Euler-Lagrange formulation in order to obtain a decoupled dynamic model considering the actuators orientation besides the position of this analyzed robot. It is important to remark that the dynamic model of the RV-3SB robot is done based in the kinematic model obtention in which is developed by the implementation of screw theory. Then the passivity based controller is obtained by separating the end effector variables and the actuator variables by making an appropriate coordinate transformation. The passivity based controller is obtained by selecting an appropriate storage function and by the Lyapunov theory the passivity based control law is obtained in order to drive the error variaable, which is the difference between the measured end effector position variable and the end effector desired position variable. The passivity based controller makes that the error variable reach the origin in finite time taking into consideration the dissipation properties of the proposed controller in order to stabilizes the desired end effector position. A numerical simulation experiement is performed in order to validate the theoretical results obtained in this research study. It is verified by numerical experimentation that the proposed control strategy is efficient and effective in order to drive the error variable to the origin in comparison with other modified techniques found in the literature. Finally, the appropriate discussion and conclusion of this research study are provided.

Oral mucosa is a key player in the cancer patient and during cancer treatment. The increasing prevalence of cancer and cancer therapy associated side effects are behind the major role that oral mucosa plays in the oncological patient. Oral mucositis is a debilitating severe complication caused by early toxicity of chemo and/or radiotherapy that can restrict treatment outcome possibilities, even challenging patient’s survival. It has been referred to as the most feared cancer treatment complication. Predictive variables as to who and to what extent will be affected are still unclear. Additionally, oral mucositis is one of the sources of the increasing economic burden of cancer, not only for patients and their families but also for institutions and governments. All efforts should be implemented in the search for new approaches to minimize the apparently ineluctable outburst of oral mucositis along the cancer treatment. New perspectives derived from different approaches in explaining the interrelation between oral mucositis and oral microbiome or the similarities with genitourinary mucosa may help elucidate the biomolecular pathways and mechanisms behind oral mucosa cancer-therapy related toxicity and what is more important its management in order to minimize treatment side effects and to provide enhanced cancer support.

The main objective of this investigation was to study the effect of organizational competencies development practices on turnover intentions and whether affective commitment explains this relationship. Another of the study's objectives was to test whether these relationships vary ac-cording to the generation to which the participant belongs. The study sample consisted of 2123 participants working in Portuguese organizations. The results indicate that organizational com-petencies development practices (training, individualized support, and functional rotation) nega-tively and significantly affect turnover intentions and that affective commitment mediates this re-lationship. However, these relationships vary according to the participant's generation. For Gen-eration Y and Generation X, this mediating effect is found in all dimensions of organizational competencies development practices. For the baby boomer generation, there is only a mediating effect of affective commitment in the relationship between individualized support and turnover intentions. These results indicate that human resources should consider the generation to which the participant belongs when implementing competencies development practices.

Increasingly, systems biology is gaining relevance in basic and applied research. The combination of computational biology with wet lab produces a synergy that results in an exponential increase in knowledge of biological systems. The study of microorganisms such as Staphylococcus epidermidis RP62A enables the researcher to understand better its metabolic network, which allows the design of effective strategies to treat infections caused by this species or others. S. epidermidis is the second cause of infection in patients with joint implants, so treating its proliferation seems vital for public health. There are different approaches to the analysis of metabolic networks. Flux Balance Analysis (FBA) is one of the most widespread streams. It allows the study of large metabolic networks, their structural properties, the optimization of metabolic flux, and the search for intervention strategies to modify the state of the metabolic network. This work presents the validation of the Staphylococcus epidermidis RP62A metabolic network model elaborated by Díaz-Calvo et al.. Then, we elaborate further on the network analysis’s essential reactions, classifying them. Finally, we introduce some proposals to intervene in the network and design knock-outs.

This work is located in a growing sector within the field of renewable energies, wave energy converters (WECs). Specifically, it focuses on one of the point absorbers wave (PAWs) of the hybrid platform W2POWER. With the aim of maximising the mechanical power extracted from the waves by these WECs and reduce their mechanical fatigue, the design of five different model predictive controllers (MPCs) with hard and soft constraints has been carried out. As contribution of this paper, two of the MPCs have been designed with the addition of an embedded integrator. In order to validate the MPCs, an exhaustive study on performance and robustness is realized through simulations carried out in which uncertainties in the WEC dynamics are considered. Furthermore, looking for realistic in these simulations, an identification methodology for PAWs is proposed and validated by means of real time series of a scale prototype.

Live video streaming has become one of the main multimedia trends in networks in recent years. Providing Quality of Service (QoS) during live transmissions becomes a challenge due to the stringent requirements for low latency and minimal interruptions. This scenario has led to a high dependence on cloud services, implying a widespread usage of Internet connections, which constrains contexts where an Internet connection is not available. Thus, alternatives such as Mobile Ad Hoc Networks (MANETs) emerge as potential communication techniques. These networks operate autonomously with mobile devices serving as nodes, without the need for coordinating centralized components. However, these characteristics lead to challenges to live-video streaming, such as dynamic node topologies or periods of disconnection. Considering these constraints, this paper investigates the application of Artificial Intelligence (AI)-based classification techniques to provide adaptive streaming in MANETs. For this, a software-driven architecture is proposed to route stream in offline MANETs, predicting the stability of individual links and compressing video frames accordingly. The proposal has been implemented and assessed in a laboratory context, analyzing the model performance and QoS metrics. As a result, the model is implemented in a decision forest algorithm, which provides 95.9% of accuracy. Also, obtained latency values become assumable for video streaming, manifesting a reliable response for routing and node movements.

Diabetes mellitus is a popular life-threatening disease and patients may gradually have started suffering from other diabetes-causing diseases such as heart attacks, stroke, hypertension, blurry vision, blindness, foot ulcer, amputation, kidney damage and other organ failures before diagnosis. Early detection can help reduce the fatality of this disease. Deep learning models have proven very useful in disease detection and computer-aided diagnosis. In this work, we proposed a deep unsupervised machine learning model for early detection of diabetes using voting ensemble feature selection and deep belief neural networks (DBN). Dataset was obtained from an online repository containing responses of prediagnosed patients to direct questionnaires administered in Sylhet Diabetes Hospital in Sylhet, Bangladesh. The dataset was preprocessed and preprocessed. Features were reduced using the ensemble feature selector. The DBN model was pretrained and tuned to obtain optimal performance. The model was also compared with other models with no multiple hidden layers. The DBN performed at its relative best with F1-measure, precision and recall of 1.00, 0.92 and 1.00 respectively. We conclude that DBN is a useful tool for an unsupervised early prediction of Type II diabetes mellitus.

Microalgae are used in various biotechnological processes, such as biofuel production due to their high biomass yields, agriculture as biofertilizers, production of high-value-added products, de-contamination of wastewater, or as biological models for carbon sequestration. The number of these biotechnological applications is increasing, and as such, any advances that contribute to reducing costs and increasing economic profitability can have a significant impact. Nitrogen fixing organisms, often called diazotroph, also have great biotechnological potential, mainly in agri-culture as an alternative to chemical fertilizers. Microbial consortia typically perform more com-plex tasks than monocultures and can execute functions that are challenging or even impossible for individual strains or species. Interestingly, microalgae and diazotrophic organisms are capable to embrace different types of symbiotic associations. Certain corals and lichens exhibit this sym-biotic relationship in nature, which enhances their fitness. However, this relationship can also be artificially created in laboratory conditions with the objective of enhancing some of the biotech-nological processes that each organism carries out independently. As a result, the utilization of microalgae and diazotrophic organisms in consortia is garnering significant interest as a potential alternative for reducing production costs and increasing yields of microalgae biomass, as well as for producing derived products and serving biotechnological purposes. This review makes an effort to examine the associations of microalgae and diazotrophic organisms, with the aim of highlighting the potential of these associations in improving various biotechnological processes.

Cardiac resynchronization therapy (CRT) via biventricular pacing (BiVP-CRT) is considered a mainstay treatment for symptomatic heart failure patients with reduced ejection fraction and wide QRS. However, up to one third of patients receiving BiVP-CRT are considered non-responders to the therapy. Multiples strategies have been proposed to maximize the percentage of CRT responders including two new physiological pacing modalities that have emerged during the lasts years: His bundle pacing (HBP) and left bundle branch area pacing (LBBAP). Both pacing techniques aim at restoring the normal electrical activation of the ventricles through the native conduction system in opposition to the cell-to-cell activation of conventional right ventricular myocardial pacing. Conduction system pacing (CSP), including both HBP and LBBAP appears to be a promising pacing modality for delivering CRT and has proven to be safe and feasible in this particular setting. This article will review the current state of the art of CSP-based CRT, its limitations and future directions.