(1) Background: the use of force by Public and Private Security Forces is currently an issue of great relevance because of the potential injuries that any excessive use of force by either the active or passive subjects or a deficit in the real mastery of the appropriate Physical Intervention Techniques (PIT) may cause. For this reason, certain traditionally used Physical Intervention Techniques have been questioned by scientific research studies and punished by justice. On the other hand, certain media have dealt with this matter in a biased and unfair manner by broadcasting videos where the use of force by police officer is displayed out of context. As a consequence, this problem has been brought under the spotlight, causing general uneasiness of the communities and rapidly spreading over social networks while favoring all sorts of parallel judgments. (2) Research method: A suit equipped with 19 Inertial Measurement Units (IMU) and a Biomechanics of Bodies software application for the Marras’ analysis of the data collected on trajectory, trunk twisting velocity, its sagittal angle, load, nature and severity of the injuries associated to the different intervention techniques that have been examined. (3) Results: according to the data registered, the implementation of Operational Tactical Procedures (OTP) reduces the probability of injuries and leads to a more satisfactory outcome. (4) Conclusions: the implementation of Operational Tactical Procedures, to-gether with the awareness on the risks associated to the excessive use of force by Public and Private Security Forces and Bodies, could reduce the risk of injuries suffered by both officers and citizens.

In this paper, we introduce the bicomplex Tetranacci and Tetranacci-Lucas quaternions. Moreover, we present Binet's formulas, generating functions, and the summation formulas for those bicomplex quaternions.

Clove (Syzygium aromaticum L. Myrtaceae) is an aromatic plant widely cultivated in tropical and subtropical countries, rich in volatile compounds and antioxidants such as eugenol, β-caryophyllene, and α-humulene. Clove essential oil has received considerable interest due to its wide application in the perfumery, cosmetic, health, medical, flavoring, and food industries. Clove essential oil has relevant biological activities to human health, including antimicrobial, antioxidant, and insecticide. This review describes the effect of the extraction method (hydrodistillation, steam distillation, ultrasound-assisted extraction, microwave-assisted extraction, cold pressing, and supercritical fluid extraction) on the chemical composition of essential oil and its correlation with their biological activities. Likewise, are summarized the main compounds and their reported biological activities. Furthermore, the main applications in clove essential oil in the food industry are presented. Finally, this review presents the new biological activities such as anti-inflammatory, analgesic, anesthetic, antinociceptive and anticancer, which are beneficial for human health. This review aims to compile the effect of different methods of extracting clove essential oil on chemical composition, food applications, as well as a current description of biological activities of interest to human health. Biological activities have increased interest in research into this essential oil and its future applications in the food or pharmaceutical industry.

In this paper, we define Tetranacci and Tetranacci-Lucas matrix sequences and investigate their properties.

Mexico´s inhabitants have approximately 7 million dogs and cats as pets, of which there is no accurate information about their environmental impacts as a result of their feeding and comfort requirements. The objective of this study is to compare the environmental footprint between a dog and a cat in a family environment. For this purpose, a life cycle analysis was performed including, among other factors, its feeding and waste management in one year of life. Different environmental indicators including the carbon footprint were considered. It was found that the equivalent CO2 emission of a dog is twice that estimated for a domestic cat and that the main contribution is due to the food production. The ecological footprint that is generated when satisfying the requirements for pet´s well-being impacts in the environment contributes primarily to the carbon footprint.

Bacterial endophytes (120) were isolated from six halophytes (Distichlis spicata, Cynodon dactylon, Eragrostis obtusiflora, Suaeda torreyana, Kochia scoparia, and Baccharis salicifolia). These halophiles were molecularly identified and characterized with or without NaCl conditions. Characterization was based on tests such as indole acetic acid (IAA), exopolysaccharides (EPS), and siderophores (SID) production; solubilization of phosphate (P), potassium (K), zinc (Zn), and manganese (Mn); mineralization of phytate; enzymatic activity (acid and alkaline phosphatase, phytases, xylanases, and chitinases) and mineralization/solubilization mechanisms involved (organic acids and sugars). Eleven halophiles (tolerated NaCl 2.5 M) were identified as Oceanobacillus sp. (1), Bacillus sp. (2), Nesterenkonia sp. (3), Bacillus velezensis (4), Halobacillus sp. (5), Oceanobacillus sp. (6), B. velezensis (7) Halomonas sp. (8), B. pumilus (9), Pseudomonas sp. (10) and Oceanobacillus sp. (11). Biochemical responses of nutrient solubilization and enzymatic activity varied between bacteria and the presence of NaCl. Organic acids were involved in P-mineralization and nutrient solubilization. Tartaric acid was common in the solubilization of P, Zn, and K. Maleic and vanillic acid were only detected in Zn and K solubilization, respectively. Moreover, sugars appeared to be involved in the solubilization of nutrients; fructose was detected in solubilization tests. Therefore, these bacteria should be tested as a consortium to mitigate saline stress in glycophytes under a global climate change scheme that threatens to exacerbate soil salinity.

(1) Background: This text emphasizes concerns regarding the safety of Spanish police officers at-tributed to inadequate training, employing biomechanics for the analysis and mitigation of risks during Use of Force training. The elevated global prevalence of musculoskeletal disorders under-scores the imperative for effective occupational health measures. The study concentrates on evalu-ating injury risks in novice police officers during Use of Force training. (2) Research method: The movements of police officers were captured using a Rokoko Smartsuit Pro equipped with 19 sen-sors. The Biomechanics of Bodies software processed the data, providing REBA and Marras risk scores. Statistical tests were conducted, and Operational Tactical Procedures (OTP) were inte-grated into police training. A diverse group of officers participated, categorized by training level and equipped with the Rokoko Smartsuit. (3) Results: The study evaluates police force training us-ing REBA and Marras methods. REBA scores indicate a moderate to high injury risk, suggesting effective technique design. ANOVA reveals no significant differences between training levels. Marras analysis, characterized by non-normal distribution, unveils varied risk perceptions among groups via the Kruskal-Wallis test. (4) Conclusions: The analysis of both the REBA and Marras methods implies the effectiveness of the OTP technique in reducing injury risks across dif-ferent training levels. The ANOVA test indicates no significant differences in REBA Maximum Scores between the groups. However, the Kruskal-Wallis test for Marras Probability of high-risk values suggests distinctions in medians between training levels. The combined analysis visually illustrates variations in membership regions between expert, intermediate, and novice groups.

In this paper, we introduce hybrid numbers with Fibonacci and Lucas hybrid number coefficients. We give the Binet formulas, generating functions, exponential generating functions for these numbers. Then we define an associate matrix for these numbers. In addition, using this matrix, we present two different versions of Cassini identitiy of these numbers.

In this paper, by using the q-integer, we introduce a new generalization of Fibonacci and Lucas sedenions called q-Fibonacci and q-Lucas sedenions. We present some fundamental properties of these type of sedenions such as Binet formulas, exponential generating fuctions, summation formulas, Catalan's identity, Cassini's identity and d'Ocagne's identity.

Net CO2 emissions and sequestration from European forests are the result of removal and growth of flora. To arrive at aggregated measurements of these processes at a country's level, local observations of increments and harvest rates are up-scaled to national forest areas. Each country releases these statistics through their individual National Forest Inventory using their particular definitions and methodologies. In addition, five international processes deal with the harmonization and comparability of such forest datasets in Europe, namely the IPCC, SOEF, FAOSTAT, HPFFRE, FRA (definitions follow in the article). In this study, we retrieved living biomass dynamics from each of these sources for 27 European Union member states. To demonstrate the reproducibility of our method, we release an open source python package that allows for automated data retrieval and analysis, as new data becomes available. The comparison of the published values shows discrepancies in the magnitude of forest biomass changes for several countries. In some cases, the direction of these changes also differ between sources. The scarcity of the data provided, along with the low spatial resolution, forbids the creation or calibration of a pan-European forest dynamics model, which could ultimately be used to simulate future scenarios and support policy decisions. To attain these goals, an improvement in forest data availability and harmonization is needed.

Background: Electrical conductivity of trabecular bone at 100 kHz was recently reported as a good predictor of bone volume fraction. However, to quantify its relationship with the free water (or physiological solution) content and between the conductivities of its constituents, is still unclear. Methods: In this contribution, in silico models inspired by microCT images of trabecular bovine samples were used to build realistic geometries. Finite Element Method was applied to solve the electrical problem and to robustly fit the conductivity of the constituents with literature data. The obtained effective electrical conductivity was compared to Bruggeman three media mixture model: physiological solution, bone marrow and bone matrix. Results: The values for physiological solution plus bone marrow and bone matrix that captured better the bone volume fraction in the two media Finite Element model were: σps+bm = 298.4 mS/m and σb = 21.0 mS/m, respectively. Additionally, relative good results were obtained by a three media Bruggeman mixture model with σbm= 103 mS/m, σb= 21.0 mS/m, and σps= 1200 mS/m. Simple linear relationships between the proportions of constituents depending on bone volume fraction were tested. Degree of anisotropy and fractal dimension do not show detectable changes in effective conductivity. Conclusions: These results provided some useful findings for simulation purposes: first, a higher value of electrical conductivity of bone marrow has to be used in order to obtain similar values to those experimental published data. Second, anisotropy is not detectable by conductivity measurements for small trabecular samples (cube 5 mm). Finally, the simulations presented here showed a relatively good fitting of the mixture Bruggeman model which potentially would allow both, accounting for the free water content and re-scaling the model for whole bone electrical simulations.

Vanilla pompona is the third most important commercial species of the genus Vanilla, but its morphometric variation is little known. In orchids, infraspecific variation is expressed in the labellum. This study had the objective of analyzing the floral variation of V. pompona collections from localities in Veracruz, Puebla, Jalisco and Oaxaca, Mexico. During the flowering period, we obtained 55 collections of V. pompona flowers, and in the dissected labellum of each flower 54 lines and 7 angles were measured and portrayed with the ImageJ program. With the data obtained, we performed an analysis of variance, a principal components analysis, and a cluster analysis. The results showed significant differences among the collections and localities in the means of the lines of the basal, middle, and apical regions of the labellum. Also, six morphotypes were obtained, and we found that variation was associated with factors such as the environment, geographic barriers, and pollinator pressure. Moreover, we observed variation in flowering dates in one locality of Veracruz. We concluded that there is infraspecific variation within and between the collection localities of V pompona of the Atlantic region (Puebla and Veracruz) and the Pacific region (Jalisco and Oaxaca), Mexico.

Multi-receiver encryption enables a sender to encrypt a message and transmit the ciphertext to a set of authorized users, while no one out this group of authorized users can decrypt the message. Multi-receiver encryption is of great importance in many sectors such as broadcast communication, cloud computing, wireless communications, networking applications, e-voting, lottery, and medical applications. This paper proposes an efficient multi-receiver public key encryption scheme based on Lucas sequences. The results of the computational analysis show that, projected scheme is better against renown attacks and prevailing anonymous multireceiver algorithms

Some p53 mutants lose their tumor suppressor activity and acquire new oncogenic functions, known as a gain of function. Recent studies have shown that p53 mutants can exert oncogenic effects through specific miRNAs. We identified the differentially expressed miRNA profiles of the three most frequent p53 mutants (p53R273C, p53R248Q, and p53R175H) in the Saos-2 cell line (null p53) transfected as compared with p53WT transfected cells. The association between these miRNAs and the signaling pathways in which they might participate was performed through the miRPath Software. QRT-PCR was employed to validate the miRNAs profiles. In addition, we explored if the induction of cell migration and invasion by the p53R48Q mutant was dependent on the miR-182-5p. We observed that p53 mutants have an overall negative effect on miRNA expression. Likewise, we found miRNAs differentially expressed associated with regulating Oncogenic signaling pathways. We found overexpression of miR-182-5p, which is associated with processes such as cell migration and invasion. Inhibition of mutant p53R248Q and miR-182-5p increased FOXF2-MTSS1 levels and decreased cell migration and invasion. Our results suggest that p53 mutants increase the expression of miR-182-5p, and this miRNA is also necessary to induce cell migration and invasion by the p53R248Q mutant in a cancer cell model.

The fact that real dissipative (entropy producing) processes may be detected by non–comoving observers (tilted), in systems that appear to be isentropic for comoving observers, in general relativity, is explained in terms of the information theory, in analogy with the explanation of the Maxwell's demon paradox.

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

Owing to the escalating adoption of IoT systems across various domains, the demand for mobile and wireless power sources has surged. Although conventional batteries typically serve as energy storage components, the current low-power consumption devices necessitate eco-friendly alterna-tives. In this study, we designed, fabricated, and characterized an energy harvesting device that repurposes mechanical vibrations. A three-beam design was employed to harvest energy across a broader range of potential frequencies. Finite element models were simulated to ascertain the first bending moment for both sets of beams. A nanostructured piezoelectric multilayer film made of ZnO was deposited onto an AISI 304 steel substrate, and a photosensitive resin seismic mass was implemented. Low-cost techniques generating minimal environmental waste were leveraged in the fabrication process. The piezoelectric film was deposited using a spray nebulization technique involving recycled materials and cost-effective equipment. Micrographs of the layers unveiled the presence of nanospheres with diameters of 250 nm. Employing a custom-made shaker, output voltages of 1.08 V and 180 mV, and power outputs of 1.849 µW and 16.2 nW were achieved for each set of beams. The electrical characterization was conducted using a custom-made shaker, repurposing materials for this objective.

This paper addresses the evolving landscape of electricity markets in Europe, with a focus on the integration of Renewable Energy Communities as introduced by the Renewable Energy Directive 2018/2001. Residents within a postal code area are highly incentivized to join a community, which enables them to exchange energy among themselves at lower procurement costs. Thereby, energy management systems optimize the operation of respective energy systems, with electrical load forecasting playing a key role. Given that prosumers may switch between communities on a daily basis, electricity demands within these groups will vary, leading to data that is non-stationary, discontinuous as well as non-identical and independently distributed. To encounter this issue, we propose a sophisticated forecasting model that applies federated learning, using informations from various distributed communities to learn domain-invariant features. To achieve this, we initially utilize synthetic electrical load time series at district level and aggregate them to profiles of Renewable Energy Communities with dynamic portfolios. Subsequently, we develop a forecasting model that accounts for the composition of residents of a Renewable Energy Community, adapt data pre-processing in accordance with the time series process, and detail a federated learning algorithm that incorporates weight averaging and data sharing. Following the training of various experimental setups, we ultimately evaluate their effectiveness. The findings suggest that our proposed framework is capable of effectively forecast non-stationary and discontinuous time series and that it can be applied to new, unseen data through the integration of knowledge from multiple sources.

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in-situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in-situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens, and the photographs submitted through the app were not always of sufficient quality. For this reason, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree and a near real-time quality assurance system to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was the implementation of a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to present these new features and to compare the results obtained by the citizens with authoritative LUCAS data from 2018 in terms of LULC and change in LC. We also compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. Finally, we present the results from a user survey to discuss challenges encountered during the campaign and what further improvements could be made in the future, including better in-app navigation and offline maps, making FotoQuest a model for enabling the collection of large amounts of land cover data at a low cost.

Before December 2020, Antarctica had remained free of Covid-19 cases. The main concern during the pandemic was the limited health facilities available at Antarctic stations to deal with the disease, as well as the potential impact of SARS-CoV-2 on Antarctic wildlife through reverse zoonosis. In December 2020, 60 cases emerged in Chilean Antarctic stations, disrupting the summer campaign with ongoing isolation needs. The SARS-CoV-2 RNA was detected in the wastewater of several scientific stations. In Antarctica, treated wastewater is discharged directly into the seawater. No studies currently address recovery of infectious virus particles from treated wastewater, but their presence raises the risk of infecting wildlife and initiating new replication cycles. This study highlights the initial virus detection in wastewater from Antarctic stations, identifying viral RNA via RT-qPCR targeting various genomic regions. The virus's RNA was found in effluent from two wastewater plants at Maxwell Bay and O’Higgins Station on King George Island and the Antarctic Peninsula, respectively. This study explores the potential for reverse zoonotic transmission of SARS-CoV-2 from humans to Antarctic wildlife due to the direct release of viral particles into seawater. The implications of such transmission underscore the need for continued vigilance and research.

The purpose of this work is to describe and explain the characteristics of pedagogy as a science of education, as an object, concepts and research method. The methodology assumed was the review of the history of pedagogy, especially the classics of pedagogy, those who built it with their experiences in laboratory schools. Here are listed the main concepts of pedagogy, its laws and principles; she establishes the opposition that exists between teaching-learning and education as formation of the personality; she also delimits the fields of the pedagogical method, of didactics or teaching-learning, and the methodology of educational labor that organizes the process and the educational context, the regime and the lifestyle, such as those experienced in the "colonies" or "communes" of children and adolescents, organized and directed by Neill and Makarenko. Since the present article does not derive from a primary source or from field work, as an empirical or experimental research, the results constitute the content of the article, as conclusions.

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.

In this paper, inspired by recent articles of G. Anatriello and G. Vincenzi (see \cite{Ana}), and G. Cerda-Morales (see \cite{Cer1,Cer2}), we will introduce the third-order $\overline{h}$-Jacobsthal and third-order $\overline{h}$-Jacobsthal--Lucas sequences and their associated quaternions. The new results that we have obtained extend most of those obtained in \cite{Cer2}.

In this paper, we define and investigate modified p-Leonardo, p-Leonardo-Lucas and p-Leonardo sequences as special cases of the generalized Leonardo sequence. We present Binet's formulas, generating functions, Simson formulas, and the summation formulas for these sequences. Moreover, we give some identities and matrices related with these sequences. Furthermore, we show that there are close relations between modified p-Leonardo, p-Leonardo-Lucas, p-Leonardo numbers and Fibonacci, Lucas numbers.

Laser powder bed fusion (LPBF) is an additive manufacturing process employed in many industries, for example for aerospace, automotive and medical applications. In these sectors, mainly nickel-, aluminum- and titanium-based alloys are used. In contrast, the mechanical engineering industry is interested in more wear-resistant steel alloys with higher hardness, both of which can be achieved with a higher carbon content, like in high-speed steels. Since these steels are susceptible to cracking, preheating needs to be applied during processing by LPBF. In a previous study, we applied a base plate preheating temperature of 500 °C for HS6-5-3-8 with 1.3 % carbon content. We were able to manufacture dense (p > 99.9 %) and crack-free parts from HS6-5-3-8 with a hardness > 62 HRC (as built) by LPBF. In this study, we investigate the influence of preheating temperatures up to 600 °C on hardness and microstructure dependent on part height for HS6-5-3-8. The microstructure was studied by light optical microscopy (LOM), scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). The analysis of hardness and microstructure at different part heights is necessary because state-of-the-art preheating systems induce heat only into the base plate. Consequently, parts are subjected to temperature gradients and different heat treatment effects depending on part height during the LPBF process.

A two scalar field model that incorporates non Riemannian Measures of integration or usually called Two Measures Theory (TMT) is introduced, in order to unify the early and present universe. In the Einstein frame, a K-essence is generated and as a consequence for the early universe, we can have an Inflation for the very early universe and then, after inflation, an early dark energy period and a late dark energy period for the present universe dark, both dark energy epochs have a consistent generation of dark energy (DE), dark matter (DM) and stiff matter. This is obtained when the scale invariance is introduced and then is spontaneously broken from the integration of the degrees of freedom associated with the modified measures. The resulting effective potentials and K-essence in the Einstein frame produce the three flat regions corresponding to the different epochs mentioned before. For the first flat region, we can associate an inflationary universe. Also assuming this first plateau, we study the inflation in the framework of the slow-roll approximation. In this scenario under the slow roll approximation, we obtain a linear combination that is a constant. The corresponding cosmological perturbations in our model are determined and we also obtain the different constraints on the parameter-space from the Planck data. The slow roll approximation can be arranged so that the transition from inflation to the next flat region can be achieved without problems. In the following two flat regions, in addition to the inflation phase, representing the Early Dark Energy and Late Dark Energy Periods, with DE and also the DM, do not need to be introduced separately, they are instead a result of a K-essence induced by the multi measures, multi field theory. Therefore the scalars generate both the DE and the DM . Also a stiff matter component is automatically generated from the K-essence theory from two scalar fields. From the perturbative analysis associated to the perturbation solution of background, we find a correlation between the two scalars. Besides, we obtain that our model during the dark epoch has a behaviour of tracking freezing mode

This paper presents a simple drone survey and image processing approach to identifying St. John's wort (Hypericum perforatum) on grazing land in the Hunter Valley NSW, Australia. St John’s wort is an invasive species (weed) that competes with pasture, poisons livestock, can downgrade wool with ‘vegetable fault’, and decreases property values. Identifying the locations of St John wort from the ground can be difficult due to topography, limited access, and/or larger land areas of mixed vegetation. In this study, a drone was used to survey a 174-ha grazing property in the Hunter Valley NSW (Australia). The images were stitched together using commercially available software. A unique Visual Atmospheric Resistance Index (VARI) attribute was identified and used to highlight the presence of St John’s wort in the survey area. These sub-areas were then digitised onto high resolution maps for future planning use by land managers.

(S)-Atenolol ((S)-2-(4-(2-Hydroxy-3-(isopropylamino)propoxy)phenyl)acetamide) has been synthesized in >99% ee with use of Candida antarctica lipase B from Syncozymes (Shanghai, China), in a kinetic resolution of the corresponding racemic chlorohydrin. Deprotonation of the starting phenol building block was base catalyzed. The enantiopurity of the chlorohydrin building block remained unchanged upon subsequent amination. All four steps in the synthesis protocol have been optimized compared to previously reported methods, which makes this new protocol more sustainable and in accordance with green chemistry principles compared to previously reported protocols.

Ammonia can be considered a relevant compound in the future energy sector, playing a significant role as an energy carrier, storage, or carbon-free fuel. However, the production of this molecule has a high energy demand, and the use of natural gas, which is not free of controversy due to the accidental leakage into the atmosphere produced during extraction and the fact that it is a non-renewable source, contributes to increasing greenhouse gas emissions. Reducing the process’s energy demand and carbon footprint will be essential to making ammonia a clear alternative for a carbon-free economy. Given the vast experience in ammonia production and handling, this gas seems to be the logical step forward in the evolution of the energy sector. However, the current uncertainty in the global market requires cautiousness in decision-making. Several factors may impact economic growth and human welfare, thus needing a careful assessment before taking any transcendental decisions that could affect worldwide energy prices and raw material availability.

The cornea is an avascular tissue which has attracted much attention by the uniqueness of its anatomical characteristics, it has, in proportion, an enormous size, in relation to the number of vessels, because on average few cells in the organism are away more than 30 microns of a blood vessel. However, the cornea, with a diameter of between 11 and 12 mm, is a unique example. It has been tried to explain the notable absence of blood vessels in the cornea, arguing that corneal tissues are able to take oxygen directly from the air. In this article we are explaining that based on the physicochemical characteristics of molecular oxygen and the cell membrane, cytoplasm, water, and cellular metabolism, it is not possible that epithelial corneal cells directly take oxygen from the air, instead, corneal cells have molecules that can dissociate the water molecules thereby these cells, like any other eukaryotic cells, take the oxygen from the intracell water, like plants.

Boron (B) toxicity is an important stress that negatively affects maize yield and quality production. The excessive B content in agricultural lands is a growing problem due to the increase in arid and semi-arid areas because of climate change. Recently, two Peruvian maize landraces, Sama and Pachía, were physiologically characterized based on their tolerance to B toxicity, the former being more tolerant to B excess than Pachía. However, many aspects regarding the molecular mechanisms of these two maize landraces against B toxicity are still unknown. In this study, a leaf proteomic analysis of Sama and Pachía was performed. Out of a total of 2793 proteins identified only 303 proteins were differentially accumulated. Functional analysis indicated that many of these proteins are involved in transcription and translation processes, amino acids metabolism, photosynthesis, carbohydrate metabolism, protein degradation, and protein stabilization and folding. Compared to Sama, Pachía had a higher number of differentially expressed proteins related to protein degradation, and transcription and translation processes under B toxicity conditions, which might reflect the greater protein damage caused by B toxicity in Pachía. Our results suggest that higher tolerance to B toxicity of Sama can be attributed to more stable photosynthesis that would avoid damage caused by stromal over-reduction under this stress condition.

In this paper, we study sums of finite products of Chebyshev polynomials of the first kind and Lucas polynomials and represent each of them in terms of Chebyshev polynomials of all kinds. Here the coefficients involve terminating hypergeometric functions ₂F₁ and these representations are obtained by explicit computations.

If environmental exposures are shown to cause an adverse health outcome, reducing exposure should reduce the disease risk. Links between exposures and outcomes are typically based on ‘associations’ derived from observational studies, and causality may not be clear. Randomised controlled trials to ‘prove’ causality are often not feasible or ethical. Here the history of evidence that tobacco smoking causes lung cancer – in observational studies – is compared to that of low sun exposure and/or low vitamin D status as causal risk factors for the autoimmune disease, multiple sclerosis. Evidence derives from in vitro and animal studies, as well as ecological, case-control and cohort studies, in order of increasing strength. For smoking and lung cancer, the associations are strong, consistent, and biologically plausible – the evidence is coherent or ‘in harmony’. For low sun exposure/vitamin D as risk factors for MS, the evidence is weaker, with smaller effect sizes, but coherent across a range of sources of evidence, and biologically plausible. The association is less direct – smoking is directly toxic and carcinogenic to the lung, but sun exposure/vitamin D modulate the immune system, which in turn may reduce the risk of immune attack on self-proteins in the central nervous system. Opinion about whether there is sufficient evidence to conclude that low sun exposure/vitamin D increase the risk of multiple sclerosis, is divided. General public health advice to receive sufficient sun exposure to avoid vitamin D deficiency (<50nmol/L) should also ensure any benefits for multiple sclerosis.

There is now evidence that, based on cytokine profiles, bipolar disorder (BD) is accompanied by simultaneous activation of the immune-inflammatory response system (IRS) and the compensatory immune-regulatory system (CIRS), and that both components may be associated with the staging of illness. Nevertheless, no BD studies have evaluated the IRS/CIRS ratio using CD (cluster of differentiation) molecules expressed by peripheral blood activated T effector (Teff) and T regulatory (Treg) subpopulations. This study examined T cell subsets both before and after ex vivo anti CD3/CD28 stimulation using flow cytometric immunophenotyping in 25 euthymic BD patients and 21 healthy controls as well as human cytomegalovirus (HCMV)-specific IgG antibodies. BD is associated with a significantly lowered frequency of baseline (unstimulated) CD3+CD8+CD71+ and CD4+CD25+FOXP3 and increased CD4+CD25+FOXP3+CD152+ frequencies and with lowered stimulated frequencies of CD3+CD8+CD71+, CD4+CD25+FOXP3+CD152+ and CD4+CD25+FOXP3+GARP cells and, consequently, by an increased stimulated Teff/Treg ratio. Moreover, the number of manic, but not hypomanic or depressive episodes, is significantly and negatively associated with the stimulated proportions of CD3+CD4+CD154+, and CD69+ and CD71+ expression on CD4+ and CD8+ cells, while duration of illness (≥ 10 years) is accompanied by a depleted frequency of stimulated CD152+ Treg, and CD154+ and CD71+ CD4+ T cells. BD and anti-human cytomegalovirus (HCMV) IgG levels significantly interact to decrease the expression of CD4+CD25+FOXP+GARP T phenotypes. In conclusion, BD is characterized by deficits in immune-regulatory functions while the staging of illness is characterized by additional impairments is Teff and Treg activation. HCMV seropositivity may contribute to an immune-risk phenotype associated with BD.

This article presents an in-depth review of Virtual Power Plant (VPP), its organization in the energy system and its prospects in the face of the promising future of the increasing bidirectional complexity exposed in the current scenario. A new paradigm for the operations of modern power distribution and transmission systems requires greater grid flexibility that is accompanying an extensive change in the structure of electricity markets, the fruit of the development of the renewable industry and of the growing photovoltaic systems popularized, but in contrast due to the intermittent nature cause variable uncertainties in the power system. Innovative concepts like VPP are becoming a reality, establishing an efficient and effective mechanism. The objectives and components are described in a comprehensive way, and some of the most important are pointed out and presented in detail to contribute with a description of the energy systems and the implicit research needed for sustainability and resilience in the eminent energy scenario with this technology. In addition, the literature and studies of this technology already indicate a direction of this new tool as a promising solution to manage the uncertainties of the renewable energies.

In this age of mass media and, in particular, social media-driven perception of reality, coupling disease and prophylactic opinion dynamics models can provide better insights into disease evolution than using a disease model alone. We develop in this work two disease-opinion dynamics models based on the epidemiology of the new coronavirus disease (COVID-19) and the availability or not of imperfect vaccines. We assume that susceptibility to infection decreases with the level of prophylactic attitude (personal hygiene, social distancing), and changes in prophylactic attitudes of susceptible individuals occur in response to perceived disease prevalence and vaccination coverage and efficacy in the population. We derive and discuss the disease-free equilibriums and reproduction numbers in the introduced models. We further assess the impacts of the distribution of opinions at disease introduction, the ability to detect presymptomatic, asymptomatic and symptomatic positive COVID-19 cases, the behavioural responses to the outbreak and the introduction of vaccination, and the effects of distortions of disease prevalence by public policy and mass media on disease dynamics. The insights highlighted from the proposed models are expected to make informative contributions to public policy in a context of opinion fluxes in response to perceived disease prevalence.

The study was carried out in zone 7 of Ecuador, in ecosystems of the Southern Montane Evergreen Forest of the Eastern Cordillera of the Andes that goes from 2200 to 3000 masl. In the Evergreen Seasonal Lower Montane Forest of Catamayo-Alamor, which ranges from 1600-2000 meters above sea level and finally in the Semideciduous Foot Montane Forest of Catamayo-Alamor, which ranges from 400-1600 meters above sea level. The objective was to know the occurrence, structure and abundance of J. neotropica. The investigation consisted of collecting secondary information on the occurrence of the species, to later verify it in situ. Six sites with areas ≥ 0.5 hectares were identified, four in the province of Loja and two in the province of Zamora Chinchipe. Regarding the structure, it was determined that there are significant statistical differences as well as in the dasometric variables between one site and another, presenting better growths El Tundo with average values in DAP(cm)= 45.16; G(m2) = 1.41; HT(m)= 19.22; HC(m)= 13; VC(m3) = 3.55; VT(m3) = 5.22. Regarding the Morisita index, the species presents adistribution pattern &gt;1. Regarding abundance, it was determined that Algeria presented a maximum of 297 (ind/ha), and La Victoria 46 (ind/ha) with a minimum.

In this research, the photocatalytic degradation of cypermethrin using Fe-TiO2 nanoparticles supported in a biomaterial was evaluated. The nanoparticles of TiO2 were synthesized by the green chemistry method assisted by ultrasound and doped by chemical impregnation using molar ratios Fe:Ti of 0, 0.05, 0.075 and 0.1, to make efficient use of direct sunlight (λ>310 nm). All nanoparticles were immobilized on the surface of spathe of coconut palm (Cocos nucifera). The degradation was carried out at room temperature and natural pH in a flat plate solar reactor, on which the composite material was subjected. The concentration of cypermethrin was determined after 12000 J/m2 of accumulated radiation from GC-MS and the resulting material was characterized by Scanning electron microscopy (SEM), Transmission electron microscopy (TEM) image and selected area electron diffraction (SAED), Fourier transform infrared spectroscopy (FTIR), UV-Vis spectrophotometry of diffuse reflectance and BET surface area BET surface area. The best results were achieved with the use of Degussa TiO2 P-25, Fe:Ti=0 and Fe:Ti=0.05 in suspension, with percentages of degradation of cypermethrin of 99.84, 99.62, and 100%, respectively. However, the materials supported on the biomaterial of coconut, they allowed to reach degradation percentages higher than 80% with the advantage that it minimizes operating costs, since they are not necessary filtering or centrifuging processes to separate the catalyst.

Resilience has emerged as a buzzword among researchers and practitioners. However, despite its popularity, there has been little progress in moving it from an elaborate metaphor describing an idyllic state of the system to a tool for planning and managing adaptation. While case study research is rich with examples of systems that have proven to be resilient or are striving to develop resilience, there is no defined approach that operationalises concepts described in the literature into the planning process. This paper helps close this gap by illustrating how facilitated modelling can be used for resilience planning in socio-ecological systems. The paper summarizes our experience using facilitated system dynamics to inform a model-based discussion of food security resilience to climate change in Guatemala. We identify at least three positive outcomes from the intervention, which a) helped to build consensus about the meaning of resilience, b) improved stakeholders understanding of adaptation and c) outlined potential policies to enhance resilience.

1960s Europe saw a large number of residential neighborhoods built to house those migrating from the countryside. Today, more than 50 years later, these neighborhoods suffer high levels of functional, social, and technical obsolescence. In response to this, University of Seville developed the Aura Strategy as an intervention methodology to find global solutions to issues in outdated neighborhoods. To provide visibility to this aspect of the Aura strategy, the retrofit proposal presented in this article provides a solution to improve the roofing of buildings in a case study neighborhood (Polígono de San Pablo, Seville) and an analysis of the results in terms of energy and financial savings for local residents. The results show that for a population of roughly 18,000 (in 2018), net savings, including energy and retrofitting costs, ranging from nearly 6.5 to over 8.6 million can be made over the 20-year life cycle span. Likewise, the results obtained on the reduction of thermal loads indicate a 72% decrease in energy consumption, equivalent to a saving of close to 4,500 tons of greenhouse gas emissions for the district and the entire life cycle time period, with the consequent benefits on the impact on air quality and and the fight against climate change. climate change.

This study investigated the presence and characteristics of Juglans neotropica in three ecosystems in Southern Ecuador: Montane Evergreen Forest, Evergreen Seasonal Lower Montane Forest, and Semideciduous Foot Montane Forest. The main focus was on the species' multipurpose nature as both a fruit and timber source. Six study sites, totaling at least 0.5 hectares each, were established, with four in Loja province and two in Zamora Chinchipe province.The results showed significant differences in dendrometric variables across the sites, with the most favorable growth recorded in The Tundo, where trees exhibited an average diameter at breast height (DBH) of 45.16 cm, basal area (G) of 1.41 m2, total height (TH) of 19.22 m, canopy height (CH) of 13 m, cubic volume (CV) of 3.55 m3, and total volume (TV) of 5.22 m3. The species displayed a clumped distribution pattern, as indicated by a Morisita index greater than 1. Regarding abundance, the highest density of 297 trees per hectare was found in Argelia, while Victoria had the lowest density of 46 trees per hectare. This research highlights the importance of Juglans neotropica as a multipurpose species, providing both valuable fruits and wood resources in the studied ecosystems of Southern Ecuador.

Purpose To analyse diagnostic and therapeutic impact of molecular imaging TNM (miTNM) stage obtained with 18F-DCFPyL versus 18F-Fluorocholine in head to head comparison in biochemical recurrence (BCR) prostate cancer (PCa). Material and methods Patients with BCR PCa after radical treatment with previous 18F-Fluorocholine-PET/CT (negative or oligometastatic disease) were derived to 18F-DCFPyL-PET/CT. Patients were classified attending to: grade group, EAU classification, PSA, PSA doubling time (PSAdt) and PSA velocity (PSAvel). The overall detection rate (DR) and miTNM stage according to PROMISE criteria were assessed for both radiotracers and also correlation (Kappa). The influence of PSA and kinetics on both PET/CT (DR and miTNM) and predictive value of unfavourable kinetics on miTNM were determined. Cut-off PSA, PSAdt and PSAvel values able to predict PET/CT results were determined. Change in miTNM and treatment derived of 18F-DCFPyL information with respect to 18F-Fluorocholine was also evaluated. Results We studied 138 patients. 18F-DCFPyL showed a higher DR than 18F-Fluorocholine (64.5% vs 33.3%). 18F-DCFPyL and 18F-Fluorocholine detected T in 33.3% versus 19.6%, N in 27.5% versus 13.8%, M in 30.4% versus 8.7%. Both tracers DR showed significant associations with PSA and PSAvel. Significant association was only found between miTNM and PSA on 18F-Fluorocholine-PET/CT (p=0.033). For 18F-Fluorocholine and 18F-DCFPyL PET/CT a PSAdt cut-off of 4.09 and 5.59 months, respectively, were able to predict M stage. 18F-DCFPyL changed therapeutic management in 40/138 patients. Conclusion 18F-DCFPyL provides a higher DR and superior miTNM staging than 18F-Fluorocholine in restaging BCR, especially with high PSA and unfavourable PSA kinetics, showing a fair agreement to 18F-Fluorocholine.

Soil salinity is a limiting factor in crop productivity. Inoculating crops with microorganisms adapted to salt stress is an alternative to increasing plant salinity tolerance. Few studies have simultaneously propagated arbuscular mycorrhizal fungi (AMF) and dark septate fungi (DSF) using different sources of native inoculum from halophyte plants, and evaluated their effectiveness. This study selected, in alfalfa plants as trap culture, the infectivity of 38 microbial consortia native from rhizospheric soil (19) or roots (19) coming from six halophyte plants, as well as their effectiveness in mitigating salinity stress. Inoculation with soil resulted in 26%-56% colonization by AMF and 12%-32% by DSF. Root inoculation produced 10%-56% and 8%-24% of colonization, respectively. There was no difference in the number of spores of AMF produced with both inoculum types. The effective consortia were selected based on low Na but high P and K shoot concentrations which is relevant for plant nutrition but more for salt stress mitigation. The microbial consortia selection is presented in a more novel and applicable context, which would allow for the production of native microbial inoculants adapted to salinity to diminish the harmful effects of salinity stress in glycophyte plants in the context of sustainable agriculture.

Adolescence is a stage of change and transition, which together with the COVID-19 situation, has been a huge source of vulnerability and facilitated the development of emotional disorders. This study aims to analyse internalising (anxiety and depression) and externalising (anger and aggression) symptoms in adolescence according to gender, as well as personal resources (self-esteem, social competence and integration, and awareness of problems) put in place as a mechanism of protection and coping after the situation of the pandemic. The study population encompassed 445 adolescents, of whom 230 were boys and 215 were girls, between the ages of 12 and 17. A self-reported Likert-type test was used. Findings indicate that girls show greater levels of internalising (anxiety and depression) and externalising problems (anger), finding no differences for the variable aggression between the two groups. Personal resources are closely linked to emotional symptomatology, providing a source of protection in both genders. The findings indicate a maladaptive pattern for adolescents that requires early intervention within the field of education.

Confinement can induce substantial changes in the physical properties of macromolecules in suspension. Soft confinement is a particular class of restriction where the boundaries that constraint the particles in a region of the space are not well-defined. This scenario leads to a broader structural and dynamical behavior than the observed in systems enclosed between rigid walls. In this contribution, we study the ordering and diffusive properties of a two-dimensional colloidal model system subjected to a one-dimensional parabolic trap. Increasing the trap strength makes it possible to go through weak to strong confinement, allowing a dimensional transition from two- to one-dimension. The non-monotonic response of the static and dynamical properties to the gradual dimensionality change affects the system phase behavior. We find that the particle dynamics is connected with the structural transitions induced by the parabolic trap. In particular, at low and intermediate confinement regimes, complex structural and dynamical scenarios arise, where the softness of the external potential induces melting and freezing, resulting in faster and slower particle diffusion, respectively. Besides, at strong confinements, colloids move basically along one direction, and the whole system behaves structurally and dynamically similar to a one-dimensional colloidal system.

Food allergies have increased significantly in recent decades, with shellfish being a leading cause of food allergy and anaphylaxis worldwide, affecting both children and adults. The prevalence of shellfish allergies is estimated to be approximately 0.5-2.5% of the general population, varying significantly by geographical location, age, and consumption habits. Although mollusk consumption has risen, the prevalence of mollusk allergies remains unknown. While extensive research has focused on crustacean allergies, mollusk allergies, particularly those related to gastropods, have received comparatively less attention. Clinical manifestations of shellfish allergy range from localized symptoms to life-threatening systemic reactions, such as anaphylaxis. Notably, severe bronchospasm is a predominant clinical feature in cases involving gastropods. Several allergens have been identified in mollusks, including paramyosin, tropomyosin, and sarcoplasmic calcium-binding protein. In gastropods, documented allergens include tropomyosin, paramyosin, the heavy chain of myosin, and Der p 4 amylase. Diagnosis typically involves a thorough clinical history, skin testing, in vitro quantification of immunoglobulin (Ig) E, and confirmation through oral challenge, although the latter is reserved for selected cases. This review highlights the limited research on gastropod allergy, the identified allergens to date, and the necessity for further investigations to better understand the implications of shellfish allergy within this class.

Anaerobic digestion is a biological process that transforms high-strength organic effluents into biogas with multiple benefits. However, concurrent with organics' biological transformation, a liquid phase with a high solid content is also derived from this process. Valorizing this fraction is not an easy task if an agronomic application cannot be considered as a suitable option. The thermal valorization of this fraction allows for energy extraction, but also gives rise to additional capital investment and increases the energy demand of the global process. In addition, the thermal treatment of digestate has to deal with a mineralized material. The changes in organic matter due to anaerobic stabilization were studied in the present manuscript, by evaluating the thermal behavior of samples, activation energy and organic transformation using FTIR spectroscopy. Digested samples of a mixture composed of manure and glycerin (5% v/v) were studied. The stabilization caused a dramatic decrease in aliphatic compounds, greatly increasing the mineral content of the sample. Thermal valorization of digestates must consider the lower energy content and more complex structure of these materials, with higher content of lignin and protein-type compounds.

This study aimed to evaluate the impact of Candida albicans on subgingival biofilm formation on dental implant surfaces. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) were used to compare biofilm structure and microbial biomass in the presence and absence of the fungus after periods of 24, 48, and 72 h. Quantitative polymerase chain reaction (qPCR) was used to quantify the number of viable and total micro-organisms for each of the biofilm-forming strains. A general linear model was applied to compare CLSM and qPCR results between control and test conditions. The biofilm developed with C. albicans at 72 h had a higher bacterial biomass, with a significantly higher cell viability (p &lt; 0.05). After both 48 and 72 h of incubation, in the presence of C. albicans, there was a significant increase in counts of Fusobacterium nucleatum and Porphyromonas gingivalis and in the cell viability of Streptococcus oralis, Aggregatibacter actinomycetemcomitans, F. nucleatum, and P. gingivalis. Using a dynamic in vitro multispecies biofilm model, C. albicans exacerbated the development of the biofilm grown on dental implant surfaces, significantly increasing the number and cell viability of periodontal bacteria.

Incorporating renewables in the power grid presents challenges for stability, reliability, and operational efficiency. Integrating Energy Storage Systems (ESS) offers a solution by managing unpredictable loads, enhancing reliability, and serving the grid. Hybrid storage solutions have gained attention for specific applications, suggesting higher performance in some respects. This paper compares the performance of hybrid energy storage systems (HESS) to single battery, evaluating their energy supply cost and environmental impact through optimization problems. The model generates an optimized dispatch, minimizing cost or environmental impact of supplying energy to a generic load while considering battery degradation. Seven technologies are assessed, with an example applied to an industrial site contrasting vanadium redox flow (VRFB) and lithium batteries considering the demand of a local load (building). The results also indicates that efficiency and degradation curves have the highest impact in the final costs and environmental functions on the various storage technologies assessed. For the simulations of the example case, a single system only outperforms the hybrid system in cases where lithium efficiency is higher than approximately 87% and vanadium is lower approximately 82%.

The current work shows the optimization in the preparation of nanosized titanium carbide (TiC) in-situ through mechanical alloying (MA). Metallic titanium (Ti) powders, along with two carbon sources, carbon nanotubes (CNTs), and stearic acid (SA), were used to reduce the particle size using a high-energy Spex800 mill. The combined use of 2 wt % of these carbon sources and n-heptane as a liquid process control agent (PCA) proved crucial in generating nanoscale powder composites through a simple and scalable synthesis process within a 4-hour timeframe. The use of 20 wt % of both carbon sources was compared to determine the ability of CNTs to form carbides and the decomposition of PCAs during mechanical milling. The result reveals structures like nanoblocks and nanolumps with and important size reduction. The structure and morphology of the composites and starting materials were evaluated through x-ray diffraction (XRD), Raman spectroscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM).

Risk attitudes are relevant factors affecting the production and investment decisions at farm level. They are key factors that are related to farmers’ attitudes towards environment and climate change. Several methodological approaches are available to measure the level of stated risk of an economic agent. The Multiple Price List (MPL) method is one of the methods that is gaining relevance. In this study we apply the MPL and relate the risk outcomes with farmers’ characteristics and their perception towards environment and climate change. Data was collected using a face to face survey carried out for a group of 370 agricultural producers of the irrigation district located in northwest of Mexico. Results showed an average risk of about 0.32, locating the agricultural producers of the region in a group with risk aversion, according to the MPL scale. The heterogeneity analysis showed that the socioeconomic factors and the perceptions towards climate change are related to the farmers´ stated risk level. Farmers who are young women with propensity to use public support to invest were shown to be greater risk lovers. Farmers in the region have perceived climate change to a greater extent like floods, hail, diseases and pests, and changing vegetation.

The potential of biological consortia designed for laccase production and dye treatment is discussed in this review. The poor yields in laccase production and low efficiency in dye decolorization of monoculture-based treatments has encouraged the use of designed biological consortia. A consortium is a system where the growth of two or more organisms, chosen to improve a particular bioprocess, is induced in the same medium. Chemical and natural mediators are being replaced by consortia for the production of laccases because, in addition to being less toxic, they induce new enzyme isoforms and lead to high laccase yields. On the other hand, consortia act synergistically in the decolorization of azo dyes through the enzymes they produce, so overall degradation is improved. Designed consortia are an attractive alternative still in development that could provide new biotechnological tools for the treatment of textile effluents.

The use of sustainable energy sources is a feasible alternative for fossil fuel products, which can represent a positive factor to alleviate many current environmental issues. In that sense, not only the sustainable industrial development is important, but also sustainable practices at local level, including households. Specifically, heating and cooking are one of the most important activities that require energy in households, where the role of biomass could be interesting, as it can provide an energy source with lower environmental impact. However, there is room for improvement in biomass stoves, whose adaptability to specific wastes, as well as their improvement in efficiency, should be accomplished. The aim of this work was to assess the improvement of combustion performance of a domestic stove by the implementation of a programmable logic converter for a better adaptation to different biomass samples (holm oak, pear tree, poplar and sugarcane bagasse pellets). Thus, the working regime of the stove was controlled, especially concerning the screw conveyor (to regulate pellet feeding) and flue gas fan (to change oxygen supply). As a result, better combustion performances were obtained, heat capacities from 5.66 to 8.67 kW for the selected samples. On the other hand, different improvements of the combustion stove to avoid blockages, for instance, are proposed as further steps.

Mayaro virus (MAYV) hijacks the host´s cell machinery to effectively replicate. The mitogen-activated protein kinases (MAPKs) p38, JNK and ERK1/2 have emerged as crucial cellular factors implicated in different stages of the viral cycle. However, whether MAYV uses these MAPKs to competently replicate has not yet been determined. The aim of this study was to evaluate the impact of MAPKs inhibition on MAYV replication using primary human dermal fibroblasts (HDFs) and HeLa cells. Viral yields in supernatants from MAYV-infected cells treated or untreated with inhibitors SB203580, SP600125, U0126 or Losmapimod were quantified using plaque assay. Also, viral protein expression was analyzed using immunoblot and immunofluorescence. Knockdown of p38⍺/p38β isoforms was performed in HDFs using the PROTACs molecule NR-7h. Our data demonstrated that HDFs are highly susceptible to MAYV infection. SB203580, a p38 inhibitor, reduced MAYV replication in a dose-dependent manner in both HDFs and HeLa cells. Additionally, SB203580 significantly decreased viral E1 protein expression. Similarly, knockdown or inhibition of p38⍺/p38β isoforms with NR-7h or Losmapimod, respectively, affected MAYV replication in a dose-dependent manner. Collectively, these findings suggest that p38 could play an important role in MAYV replication and could serve as a therapeutic target to control MAYV infection.

Systems Engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address Systems Engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in Industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks; along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.

Electric Transformers make up some of the most critical components of a power system. Their reliable operation is critical for an efficient power grid as well as economic viability for the transformer operators and owners. Power transformers, like other High Voltage (HV) electrical equipment experience aging and insulation degradation due to chemical, mechanical and electrical forces during their operation. Partial Dischargers (PD) are localized electrical discharges that develop within insulation systems of HV electrical equipment such as transformers. In transformers, PD occurs in different forms and various locations and insulation both internal and external of the transformer. PD originates as small pulses but tends to increase in size and intensity which can result in complete insulation failure. Monitoring partial discharges has proven to provide valuable information on the state of the insulation systems of the power transformer, allowing transformer operators to make calculated decisions for the maintenance and life of plant plans. This systematic literature review aims to systematically examine the use of machine learning techniques in classifying PD in transformers to present a complete indicator to allow for future research in the field. The systematic review surveyed a total of 81 research literature published from 2010 to 2023 that fulfilled a specific methodology which was developed as part of this study. The results revealed that supervised learning has been the most widely used Artificial Intelligence (AI) algorithm utilized, primarily in the form of Support Vector Machine (SVM). Regarding PD, the survey revealed that most researchers tend to use numerous types of PD and compare them to one another. Furthermore, the use of artificial PD defect models to simulate the occurrence of PD is widely used versus the use of actual power transformers. Most of the literature tends to not specify the physical characteristics of PD, such as the magnitude of PD, PD inception voltage and PD extinction voltage.

In recent years, the abundance of streaming data has posed significant challenges for traditional machine learning algorithms due to the dynamic nature and high volume of data. To address these challenges, this paper presents an adaptive supervised learning framework designed for data streams, leveraging the power of reproducing kernel Hilbert spaces (RKHS) while incorporating a data sparsity constraint. The proposed framework aims to adaptively update the model to efficiently handle the continuous arrival of streaming data while ensuring accurate and reliable predictions. The primary objective is to exploit the RKHS framework, which provides a rich mathematical structure for learning in high-dimensional feature spaces. By utilizing RKHS, the model can capture complex patterns and nonlinear relationships in the streaming data. Furthermore, the framework incorporates a data sparsity constraint to address the issue of limited resources and computational efficiency. The constraint promotes the selection of a subset of relevant features, reducing the dimensionality of the problem and enhancing the scalability of the learning algorithm. This constraint not only improves computational efficiency but also mitigates the effects of noisy or irrelevant features, leading to more robust and accurate predictions. To achieve adaptability, the proposed framework employs an online learning approach that incrementally updates the model parameters as new data arrives. This allows the model to adapt to concept drift and changing data distributions, ensuring its relevance and effectiveness over time. The adaptation process is guided by a mechanism that balances the exploitation of current knowledge with the exploration of new information, enabling the model to gradually evolve and refine its predictions. Experimental evaluations on various benchmark datasets demonstrate the efficacy of the proposed framework in handling streaming data. The results indicate that the adaptive supervised learning approach in RKHS with a data sparsity constraint outperforms traditional batch learning methods and exhibits superior accuracy, scalability, and adaptability in dynamic data stream scenarios. Overall, this research contributes to the development of adaptive supervised learning methods for data streams, highlighting the effectiveness of RKHS and the significance of incorporating a data sparsity constraint. The proposed framework offers a promising solution to handle the challenges posed by streaming data, paving the way for real-time, efficient, and accurate learning in diverse application domains.

Due to their contribution to human health, the production of healthy snacks has garnered the attention of both the scientific community and the food industry. This study was conducted to determine the suitability of frying and baking processing methods for producing green banana chips using two varieties: Barraganete and Dominico. The aim was to identify a treatment geared towards producing healthy snacks. Initially, the physicochemical properties of the raw materials were analyzed, revealing significant differences in starch, fat, fiber, and protein content. Subsequently, the bananas were processed into baked and fried chips. Multivariate statistical techniques such as ANCOVA, MANOVA, and post-hoc tests were applied to examine the influence of initial characteristics and detect variations attributable to the cooking method. The main findings showed that the initial protein level had a significant covariate effect on the final content in the chips. The Dominico variety generally proved more suitable for making baked chips, retaining higher percentages of protein, starch, fiber, and lower fat content than Barraganete. Baked chips showed significantly lower sodium and fat values than fried ones when differentiated by processing method. The "Dominico + Baked" treatment emerged as the superior alternative, with favourable levels of protein, starch, and low sodium and fat, positioning it as the most suitable for producing a healthy snack.

People with Down syndrome present cognitive difficulties that affect their reading skills. In this study we present results about the use of gestural interaction with Kinect sensor to improve the reading skills of students with Down syndrome. Following a case of study method for small samples with disabilities, measuring different variables related to reading skills in an experimental group and in a control group. We found improvements in the visual association, visual comprehension, sequential memory, and visual integration after this stimulation in the experimental group compared to the control group. Also, we found that the number of error and delay time of interaction decrease between sessions in the experimental group.

Filter Media (FM) sourced from recycled organic and mineral material offers a low cost and effective means of treating urban stormwater. Using recycled materials rather than from an increasingly scarce source of virgin materials (typically sandy loam soil) can ensure a sustainable long-term economy and environment. This paper presents results from the laboratory analysis and mathematical modeling to highlight the performance of recycled organic and mineral material in removing nutrients and metals from stormwater. Analysis included physical and chemical characterisation such as particle size distribution, saturated hydraulic conductivity (Ksat), bulk density, effective cation exchange capacity, and pollutant removal performance. Design mixes (DM), comprising a combination of organic and mineral materials, were characterised and used to develop/derive modelling design within the Model for Urban Stormwater Improvement Conceptualisation (MUSIC v6) [1]. Comparison is made to the Adoption Guidelines for Stormwater Biofiltration Systems - Summary Report [2] which were based on the Facility for Advancing Water Biofiltration (FAWB) guidelines to assist in the development of biofiltration systems, including the planning, design, construction and operation of those systems. An observed outcome from over two decades of biofiltration guideline development has been the exclusion of alternative biofilter materials due to claims of excessive leaching. Results from this study indicate that high nutrient and metal removal rates can be achieved over a range of hydraulic conductivities using design mixes of recycled organic and mineral materials that have a demonstrated equivalence to existing guideline specifications.

In this study, a critical review was carried out using the Web of ScienceTM Core Collection database to analyse the scientific literature published to date to identify lines of research and future perspectives on the presence of chemical pollutants in beer brewing. Beer is one of the world's most popular drinks and the most consumed alcoholic beverage. However, a widespread challenge with potential implications for human and animal health is the presence of physical, chemical and/or microbiological contaminants in beer. Biogenic amines, heavy metals, mycotoxins, nitrosamines, pesticides, acrylamide, phthalates, bisphenols, microplastics and, to a lesser extent, hydrocarbons (aliphatic chlorinated and polycyclic aromatic), carbonyls, furan-derivatives, polychlorinated biphenyls and trihalomethanes are the main chemical pollutants found during the beer brewing process. Pollution sources include raw materials, technological process steps, the brewery environment and packaging materials. Different chemical pollutants have been found during the beer brewing process, from barley to beer. Brewing steps such as steeping, kilning, mashing, boiling, fermentation and clarification are critical in reducing the levels of many of these pollutants. As a result, their residual levels are usually below the maximum levels allowed by international regulations.

Increased connectivity between coastal lagoons and the sea is expected to entail a greater proportion of marine species in the former. Chetumal Bay, estuary of the Hondo river into the Caribbean, had a limited access to the sea until the opening of the Zaragoza Canal. We sought changes in the fish community from 1999-2001 (just after an expansion of the canal) to 2015-2018. The same fishing gear was used, in the same localities, during all seasons. Total fish abundance and mean local richness decreased, although total abundance increased in the polyhaline zone. Diversity was greater in the oligohaline zone in 1999-2001, but in the mesohaline zone in 2015-2018. Three guilds were absent in 2015-2018: medium-sized herbivores, large piscivores, and medium-sized planktivores. Abundance of small benthivores decreased by decade; medium-sized piscivores and small planktivores became more abundant in 2015-2018 in the polyhaline zone. These changes may be due to the opening of the channel, but illegal fishing outside the bay may explain the decrease in juveniles of large piscivores, and erosion in the innermost part may be destroying important habitats. Our findings can be a reference for similar situations, as coastal development and climate change interact and affect tropical estuaries.

Carnivorous waterbirds have been reported to enhance wetlands diversities, control pests, bio-indicators of ecological conditions, and act as indicators of potential disease outbreaks. They also provide important ecosystem services to indigenous communities residing along wetlands. Regardless of their importance, global waterbirds populations are declining. Despite their ecological contribution to wetlands functions and ecosystem services, piscivore waterbirds have been re-ported to compete with piscivorous fish and fishermen. The aim of this study was to compare piscivorous waterbirds species and functional diversity between fish protected areas (FPA) and non-fish protected area (NFPA) in two tributaries of Zambezi River in Namibia. We also measured the degree to which patterns of guild structure between piscivore waterbirds and fish were similar between FPA and non-FPA. Species diversities were determined by calculating the Shannon Diversity Index. We calculated taxonomic diversity, functional diversity and community-based trait diversity indices for each tributary. Generally, species diversities were not significantly different between FPA and NFPA (P > 0.05). However, all functional diversities indices calculated were significantly different between FPA an NFPA (P < 0.05 for all comparisons). This was partly due to food item, weight and movement type that were associated with each site.

Oxidative stress has been implicated in cellular senescence and aging, as well as in the onset and progression of many diverse genetic and acquired diseases and conditions. The search for biomarkers of oxidative stress has become relevant to many biomedical fields using many different methods and approaches. Fluorescence methodology is advantageous because of its simplicity and high sensitivity. Fluorescent probes are frequently used to investigate the role of reactive oxygen species in oxidative stress in experimental or clinical settings, often involving the use of flow cytometry and related single-cell based technologies. To assess the specific role of reactive oxygen species in oxidative stress studies by cytometric methodologies, it is essential to detect and characterize these species accurately. However, the detection and quantitation of individual intracellular ROS is still a challenge, but different and complementary strategies may focus on other endpoints of oxidative stress. In this review we present and discuss briefly the limitations and perspectives of such approaches. Based on our results, we also provide recommendations for proper design of cytometric studies of oxidative stress in order to prevent or minimize experimental errors..

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

Traumatic cardiac arrest has a high mortality. We report the case of a 65 years old women who presented a cardiac arrest following traffic accident. Examinations concluded to a tension gastro thorax with a delayed diagnosis. Naso gastric tube insertion was for many authors a temporary care while waiting for surgery. We report on the diagnostic difficulties found in the literature and a recent review of published cases.

Mass customization, small batch sizes, high variability of product types and a changing product portfolio during the life cycle of an industrial plant are current trends in the industry. Due to an increasing decoupling of the development of software and hardware components in an industrial context, compatibility problems within industrial control systems arise more and more frequently. In this publication, a strategy concept for compatibility testing is derived and discussed by means of literature review and applied research. This 4-phased strategy concept identifies incompatibilities between software and hardware components in the industrial control environment and enables test engineers to detect problems at an early stage. By automating the compatibility test on an external I-PC, the test can be run both when new software is installed on the industrial controller and when the controller is restarted. Thus, changes to the components are constantly detected and incompatibilities are avoided. Furthermore, early incompatibility detection can ensure that a system remains permanently operational. Based on a discussion, additionally strategies are identified to consolidate the robustness and applicability of the presented concept.

Hormones act as master ripening regulators. In non-climacteric fruit ABA plays a key role in ripening. Recently we confirmed in Fragaria chiloensis fruit that in response to ABA treatment the fruit induces ripening associated changes such as softening and color development. In consequence with these phenotypic changes, transcriptional variations associated with cell wall disassembly and anthocyanins biosynthesis were reported. As ABA stimulates ripening of F. chiloensis fruit, the molecular network involved in ABA metabolism was analyzed. Therefore, the expression level of genes involved in ABA biosynthesis and ABA perception were quantified during development of the fruit. Four NCED/CCDs and 6 PYR/PYLs family members were identified in F. chiloensis. Bioinformatics analyses confirmed the existence of key domains related to functional properties. Through RT-qPCR analyses the level of transcripts were quantified. FcNCED1 codifies a protein that displays crucial functional domains and the level of transcripts increased as the fruit develops and ripens, in parallel with the increment in ABA. In addition, FcPYL4 codifies for a functional ABA receptor and its expression follows an incremental pattern during ripening. The study concludes that FcNCED1 is involved in ABA biosynthesis, meanwhile FcPYL4 participates in ABA perception during ripening of F. chiloensis fruit.

The results of the bibliographic analysis show that the most explored nanomaterials in dentistry are graphene and carbon nanotubes, and their derivatives. A detailed analysis and a comparative study on their applications show that, although they are quite similar, graphene based materials seem to be more promising for most of the applications of interest in dentistry. The bibliographic study also demonstrated the potential of zeolite based materials, although the low number of studies on their applications shows that they have not been totally explored, as well as other porous nanomaterials that found important applications in medicine, such as metal organic frameworks, have not been explored. Subsequently, it is expected that the research effort will concentrate in graphene and zeolite based materials in the incoming years. Thus, present review paper presents a detailed bibliographic study, with more than 200 references, in order to describe briefly the main achievements that have been described in dentistry using nanomaterials, compare and analyze them in a critical way, with the aim of predicting the future challenges.

The implementation of sustainable practices, such as the use of renewable sources and efficient technologies, is crucial for reducing climate change. Energy efficiency is highly important on a global scale due to its relationship with climate change, aiming to minimize environmental impact. In Spain, renewable energy policies have increased self-sufficiency and reduced the use of fossil fuels. Optimizing energy consumption in residences, buildings, and industries is essential for improving efficiency. This was taken into consideration for conducting this study, focusing on the residential sector. The desire to understand the level of energy efficiency in Extremadura drove this project, which focuses on collecting and analyzing data on a set of homes located in the au-tonomous community of Extremadura, with the purpose of evaluating their energy efficiency. To achieve this, a computer tool will be employed to provide a detailed view of the different levels of energy efficiency present in the community. In addition to data collection and analysis, research will be conducted to identify areas for improvement. This will allow proposing a series of specific measures that users can implement to optimize energy efficiency in their homes, adapting them to the particular characteristics of each residence.

In this work we explore the utilization of plasmonic resonance (PR) in silver nanowires to enhance the performance of organic solar cells. Plasmonic resonance is a phenomenon in which nanoscale conductive materials exhibit oscillation of conduction electrons, resulting in the creation of an electric field. Enhancing light absorption is crucial for improving organic solar cell efficiency and incorporating metallic nanostructures to induce surface plasmon resonance (SPR) shows promise in achieving this goal. We discuss the two key mechanisms of plasmonic effects: far-field scattering and near-field resonance modes. Far-field scattering extends the optical path of incident light, while near-field plasmonic effects involve localized surface plasmon resonance (LSPR) and plasmonic cavity modes, enhancing absorption by strengthening electric fields near the nanostructures. Silver nanowires are the focus of this study, and finite-difference time-domain (FDTD) simulation software is used to investigate their plasmonic resonance behavior in a ZnO/Silver nanowires/ZnO (ZAZ) electrode structure. The simulations reveal the dominance of LSPR in this configuration, with intense electric fields inside the nanowire and propagation into the surrounding medium, offering opportunities for enhanced light absorption in the organic solar cell's active layer.

In this paper, the active front-end (AFE) converter topology for the total harmonic distortion (THD) reduction in a wind energy system (WES) is used. A higher THD results in serious pulsations in the wind turbine (WT) output power and in several power losses at the WES. The AFE converter topology improves capability, efficiency and reliability in the energy conversion devices; by modifying a conventional back-to-back converter, from using a single voltage source converter (VSC) to use pVSC connected in parallel the AFE converter is generated. The THD reduction is done by applying a different phase shift angle at the carrier of digital sinusoidal pulse width modulation (DSPWM) switching signals of each VSC. To verify the functionality of the proposed methodology, the WES simulation in Matlab-Simulink® is analyzed, and the experimental laboratory tests using the concept of rapid control prototyping and the real-time simulator Opal-RT® Technologies is achieved. The obtained results show a type-4 WT with total output power of 6MVA, generating a THD reduction up to 5.5 times at the WES.

Recent technological advancements such as IoT and Big Data have granted industries extensive access to data, opening up new opportunities for integrating Artificial Intelligence (AI) across various applications to enhance production processes. We can cite two critical areas where AI can play a key role in industry such as product quality control and predictive maintenance. This paper presents a survey of AI applications in the domain of Industry 4.0, with a specific focus on product quality control and predictive maintenance. Experiments were conducted using two datasets, incorporating different machine learning and deep learning models from the literature. Furthermore, this paper provides an overview of the AI solution development approach for product quality control and predictive maintenance. This approach includes several key steps, such as data collection, data analysis, model development, model explanation, and model deployment.

Groundwater models serve as support tools to among others: assess water resources, evaluate management strategies, design remediation systems and optimize monitoring networks. Thus, the assimilation of information from observations into models is crucial to improve forecasts and reduce uncertainty of their results. As more information is collected routinely due to the use of automatic sensors, data loggers and real time transmission systems; groundwater modelers are becoming increasingly aware of the importance of using sophisticated tools to perform model calibration in combination with sensitivity and uncertainty analysis. Despite their usefulness, available approaches to perform this kind of analyses still present some challenges such as non-unique solution for the parameter estimation problem, high computational burden and a need of a deep understanding of the theoretical basis for the correct interpretation and use of their results, in particular the ones related to uncertainty analysis. We present a brief derivation of the main equations that serve as basis for this kind of analysis. We demonstrate how to use them to estimate parameters, assess the sensitivity and quantify the uncertainty of the model results using an example inspired by a real world setting. We analyze some of the main pitfalls that can occur when performing such kind of analyses and comment on practical approaches to overcome them. We also demonstrate that including groundwater flow estimations, although helpful in constraining the solution of the inverse problem as shown previously, may be difficult to apply in practice and, in some cases, may not provide enough information to significantly constrain the set of potential solutions.

Following the development of tyrosine kinase inhibitors (TKI), the survival of patients with chronic myeloid leukaemia (CML) drastically improved. With the introduction of these agents, CML is now considered a chronic disease, for some patients. Taking into consideration the side effects, toxicity, and high cost, discontinuing TKIs became a goal for patients with chronic phase CML. Patients who achieved deep molecular response (DMR) and discontinued TKI, remained in treatment-free remission (TFR). Currently, the data from the published literature demonstrate that 40-60% of patients achieve TFR, with relapses occurring within the first six months. In addition, almost all patients who relapsed regained a molecular response upon re-treatment, indicating TKI discontinuation is safe. However, there is still a gap in the understanding the mechanisms behind TFR, and whether there are prognostic factors that can predict the best candidates who qualify for TKI discontinuation with a view to keeping them in TFR. Furthermore, the information about a second TFR attempt and the role of gradual de-escalation of TKI before complete cessation is limited. This review highlights the factors predicting success or failure of TFR. In addition, it ex-amines the feasibility of a second TFR attempt after the failure of the first one, and the current guidelines concerning TFR in clinical practice.

Background: The validation of measuring instruments in health is a requirement to be able to use them safely and reliably. The Short Physical Performance Battery (SPPB) tool is an instrument widely used in the clinic and validated in numerous countries and languages and for different populations. The objective of this research was to determine the psychometric properties of SPPB for a sample composed of institutionalized Spanish older adults. Methods: Multicenter study of the psychometric properties of the Short Physical Performance Battery tool with a convenience sample of 194 institutionalized older adults. Reliability (internal consistency), validity (construct validity and convergent validity) tests were performed. Results: The results show a very good internal consistency, construct validity and convergent validity. In addition, the factorial structure of the SPPB is provided, which reflects that it is a unidimensional scale. Conclusions: In conclusion, the Short Physical Performance Battery is a valid and reliable tool for use with institutionalized older adults. Its use is recommended as part of the Comprehensive Geriatric Assessment for the evaluation of the physical or functional sphere. Authors should include one of the following statements about the registration status of the manuscript here: This study was prospectively registered and approved by the Ethics Committee of the University of Burgos (IR 11/2018).

The effect of sonication on the molecular characteristics of poliacrylic acid (Carbopol® Ultrez 10) and its rheological behavior in aqueous dispersions and microgels containing 0.25 wt. % of the polymer was analyzed in this work by rheometry, weight-average molecular weight (Mw) measurements via static light scattering (SLS), Fourier transform infrared (FTIR) spectroscopy and confocal microscopy. For this, the precursor dispersion and the microgels were sonicated in a commercial ultrasound bath at constant power and different times. We observed a softening of the microgel microstructure consisting of a systematic decrease in its shear modulus, yield stress and viscosity with increasing sonication time, while their overall Herschel-Bulkley (H-B) behavior was preserved. SLS measurements evidenced a reduction of Mw of polyacrylic acid with sonication time. Separately, FTIR measurements indicate that sonication produces scission in the C-C links of the Carbopol® backbone, which results in chains with the same chemistry but lower molecular weight. Finally, confocal microscopy measurements revealed a concomitant diminution of the size of the microsponge domains with sonication time, which is reflected in a softer microstructure resulting from reduction of the molecular weight of polyacrylic acid. The present results indicate that both the microstructure and the rheological behavior of Carbopol® microgels, in particular, and complex fluids in general, may be manipulated or tailored by high-power ultrasonication.

The role of agricultural transport costs in core-periphery structures has habitually been ignored in New Economic Geography (NEG) models. This is due to the convention of treating the agricultural good as the numéraire, thus implying that agricultural transportation costs are assumed to be zero in these models. For more than three decades, this has been the standard setting in spatial equilibrium analysis. The paper examines the effects of agricultural transport costs on the spatial organisation of regional structures in Peru. In doing so, the Krugman’s formulation of iceberg transport costs is modified to introduce the agricultural transport costs into the dynamic of the NEG models. We use exploratory spatial flow data analysis methods and non-spatial and spatial origin-destination flow models to explore how the regional spatial structure change when real transportation data for agricultural goods is included into the iceberg transport costs formulation. We show that agricultural transport costs generate flows that are systematically associated with flows to or from nearby regions generating thus the emergence of spatial spillovers across Peruvian regions. The results of the paper support the contention that NEG models have overshadowed the role of agricultural transport costs in determining the spatial configuration of economic activities.

The practice of spatial econometrics revolves around a weighting matrix, which is often supplied by the user on previous knowledge. This is the so called $\mathbf{W}$ issue. Probably, the aprioristic approach is not the best solution although, nowadays, there few alternatives for the user. Our contribution focuses on the problem of selecting a $\mathbf{W}$ matrix from among a finite set of matrices, all of them considerer appropriate for the case. We develop a new and simple method based on the Entropy corresponding to the distribution of probability estimated for the data. Other alternatives, which are common in current applied work, are also reviewed. The paper includes a large Monte Carlo to calibrate the effectiveness of our approach compared to the others. A well-known case study is also included.

Within the framework of multiblock data analysis, a unified approach of supervised methods is discussed. It encompasses multiblock redundancy analysis (MB-RA) and multiblock partial least squares (MB-PLS) regression. Moreover, we develop new supervised strategies of multiblock data analysis, which can be seen as variants of one or the other of these two methods. They are respectively refered to as multiblock weighted redundancy analysis (MB-WRA) and multiblock weighted covariate analysis (MB-WCov). The four methods are based on the determination of latent variables associated with the various blocks of variables. They are derived from clear optimization criteria whose aim is to maximize either the sum of the covariances or the sum of squared covariances between the latent variable associated with the response block of variables and the block latent variables associated with the various explanatory blocks of variables. We also propose indices to help better interpreting the outcomes of the analyses. The methods are illustrated and compared based on simulated and real datasets.

: This study aims at examining how B Corporations advance Sustainable Development Goals (SDGs) in their practices by analyzing the socioenvironmental problems they address and the solutions they provide to those problems. All Argentinian B corporations, certified by early 2023 (135 companies), were investigated using a mixed approach, combining social network analysis with textual data analysis. The results showed that the environmental practices are primarily linked to waste, water, energy and chemical management, as well as product innovation. In turn, the social practices address the training, education, and well-being of employees and other stakeholders, diversity, equity and inclusion management, and the creation of an inclusive and fair environment, integrating local communities. Thus, in the flow of their sustainability practices, Argentinian B Corporations contribute to SDGs 8, 12, 13, 9, 6, 7, 5, 10, 11, 4, and 17, in line with the SDGs declared by these companies. Our findings contribute to the theoretical knowledge of the B Corp movement and have practical implications by providing inputs to improve the management of B Corporations and to guide public policies encouraging these companies to advance sustainable development dimensions lacking attention.

The normal and Poisson distribution assumptions in the normal-Poisson mixed effects regression model are often too restrictive for many real count data. Several works have independently relaxed the Poisson conditional distribution assumption for counts or the normal distribution assumption for random effects. This work couples some recent advances in these two regards to develop a skew t–discrete gamma regression model in which the count outcomes have full dispersion flexibility and random effets can be skewed and heavy tailed. Inference in the model is achieved by maximum likelihood using pseudo-adaptive Gaussian quadature. The use of the proposal is demonstrated on a popular owl sibling negotiation data. It appears that, for this example, the proposed approach outperforms models based on normal random effects and the Poisson or negative binomial count distribution.

Most existing flexible count regression models allow only approximate inference. Balanced discretization is a simple method to produce a mean-parametrizable flexible count distribution starting from a continuous probability distribution. This makes easy the definition of flexible count regression models allowing exact inference under various types of dispersion (equi-, under- and overdispersion). This study describes maximum likelihood (ML) estimation and inference in count regression based on balanced discrete gamma (BDG) distribution and introduces a likelihood ratio based latent equidispersion (LE) test to identify the parsimonious dispersion model for a particular dataset. A series of Monte Carlo experiments were carried out to assess the performance of ML estimates and the LE test in the BDG regression model, as compared to the popular Conway-Maxwell-Poisson model (CMP). The results show that the two evaluated models recover population effects even under misspecification of dispersion related covariates, with coverage rates of asymptotic 95% confidence interval approaching the nominal level as the sample size increases. The BDG regression approach, nevertheless, outperforms CMP regression in very small samples (n = 15 − 30), mostly in overdispersed data. The LE test proves appropriate to detect latent equidispersion, with rejection rates converging to the nominal level as the sample size increases. Two applications on real data are given to illustrate the use of the proposed approach to count regression analysis.

Voice cloning, an emerging field in the speech processing area, aims to generate synthetic utterances that closely resemble the voices of specific individuals. In this study, we investigate the impact of various techniques on improving the quality of voice cloning, specifically focusing on a low-quality dataset. To contrast our findings, we also use two high-quality corpora for comparative analysis. We conduct exhaustive evaluations of the quality of the gathered corpora in order to select the most suitable audios for the training of a Voice Cloning system. Following these measurements, we conduct a series of ablations by removing audios with lower SNR and higher variability in utterance speed from the corpora in order to decrease their heterogeneity. Furthermore, we introduce a novel algorithm that calculates the fraction of aligned input characters by exploiting the attention matrix of the Tacotron 2 Text-to-Speech (TTS) system. This algorithm provides a valuable metric for evaluating the alignment quality during the voice cloning process. We present the results of our experiments, demonstrating that the performed ablations significantly increase the quality of synthesised audios for the challenging low-quality corpus. Notably, our findings indicate that models trained on a 3-hour corpus from a pre-trained model exhibit comparable audio quality to models trained from scratch using significantly larger amounts of data.

Objective: The goal of this study was to analyse the attitudes and perceptions of emergency and mental health nurses through the validation of the SM-GIBED scale in specialised care in Spain on alcoholics and other drug-dependent patients. Design and Setting: This cross-sectional study was developed using the Spanish hospital version of the Seaman-Mannello scale to denominate the SM-GIBED scale. Participants: 170 Emergency and Mental Health Nursing from five Spanish Hospitals. Intervention: Self-administered questionnaire to analiyse the perceptions and attitudes about the drug addict and the alcoholic. Primary and Secondary Outcome Measures: A descriptive and inferential analysis of the study variables was carried out. A psychometric analysis was performed to validate the scale. Results: A total of 170 questionnaires were collected from 257 healthcare workers. Overall, 99.1% of the participants had contact with drug-dependent patients during their professional experience. Nearly 75% had difficulties in treating them. The psychometric analysis of the SM-GIBED scale in the Spanish context obtained values of KMO = 0.655 and Bartlett's test p < 0.000. Cronbach's alpha of 0.738 was obtained from the reliability analysis. A reliability analysis of each of the SM-GIBED questions found no case with an alpha lower than 0.71. In conclusion, positive aspects include an ingratiating attitude and subject-to-subject communication when nurses self-define as empathic and non-paternalistic. Among the negative aspects, there is a lack of communication skills and assertiveness with these patients. This highlights a certain degree of resignation and dissatisfaction when working with drug addicts.

Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA (Robotics Surgical Maneuvers) dataset provides 206 trials of common surgical training tasks performed with the da Vinci Research Kit (dVRK). In this work, we extend ROSMA dataset with two annotated subsets: ROSMAT24, which contains bounding box annotations for instrument detection, and ROSMAG40, which contains high and low level gesture annotations. We propose an annotation method that provides independent labels for the right-handed tool and the left-handed tool. For instrument identification, we validate our proposal with a YOLOv4 model in two experimental scenarios. We demonstrate the generalization capabilities of the network to detect instruments in unseen scenarios. For gesture segmentation, we propose two label categories: high-level annotations that describe gestures at a maneuvers level, and low-level annotations that describe gestures at a fine-grain level. To validate this proposal, we have designed a recurrent neural network based on a bidirectional long-short term memory layer. We present results for four cross-validation experimental setups, reaching up to a 77.35% mAP.

Industry 4.0 is in continuous technological growth that benefits all sectors of industry and society in general. This article reviews the concept of Digital Twin (DT) and the interest of its application in photovoltaic installations. A comparison is made on how other authors use the DT approach in photovoltaic installations to improve the efficiency of the renewable energy generated and consumed, the energy prediction and the reduction of the operation and maintenance costs of the photovoltaic installation. It is reviewed how, by providing real-time data and analysis, DTs enable more informed decisions in the solar energy sector. The objectives of the review are to study the digital twin technology and to analyze its application and implementation in photovoltaic systems.

Corneal ulcers are a common and potentially vision-threatening condition in horses that can be challenging to treat with conventional therapies alone. This case report describes the successful treatment of a non-healing corneal ulcer in a 28-year-old Hispano-Bretón mare using the secretome derived from adipose tissue-derived mesenchymal stem cells (ASCs). Despite initial treatment with antibiotics, anti-inflammatory drugs, and surgical debridement, the corneal ulcer failed to heal properly, exhibiting persistent epithelial defects and stromal complications. As an alternative regenerative approach, the ASC secretome, a rich source of trophic factors, cytokines, and extracellular vesicles, was topically administered to the affected eye. Remarkably, within one week of secretome treatment, the clinical signs of blepharospasm and epiphora resolved, and the corneal ulcer exhibited complete re-epithelialization, regained transparency, and reduced neovascularization. No recurrence was observed during the 1.5-year follow-up period. This case highlights the potential therapeutic benefits of ASCs secretome in promoting corneal wound healing and suggests its promise as a novel cell-free therapy for treating refractory corneal ulcers in horses.

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advance in technologies for the use of urban wind energy has turned this source into an attractive alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open-access geographic reference systems tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consult, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found 24 provinces have poor potential, below &lt;4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 - 6.63 m/s. The population density was established and was observed that the provinces with greater potential are less densely populated. Through 59 interviews 28 institutions were identified and evaluated due to their relevance in decision-making for the implementation of energy projects. The MEM has strongly categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

The abundant use of lithium-ion batteries (LIBs) in a wide variety of electric devices and vehicles will generate a large number of depleted batteries, which contain several valuable metals such as Li, Co, Mn, and Ni present in the structure of the cathode material (LiMO2). The present work investigates chemical, technological, and environmental aspects in the treatment of such wastes, development of a methodology for the extraction of lithium, cobalt, nickel, manganese, and graphite by a carbochlorination pyrometallurgical process. Mixtures of cathode and anode materials (called black mass, mixed oxides of Li, Co, Ni, Mn, and graphite) from different LIBs, carbon black (as reducing agent), and CaCl2 (as chlorinating agent) were used. Non-isothermal thermogravimetric tests up to 850°C and isothermal tests at 700°C of the mixtures in an inert atmosphere were carried out. It was experimentally observed that the LiMO2-C-CaCl2 reaction takes place at 700°C. LiCl, Ni, and Co were obtained as final products, and to a lesser extent, CoO, NiO, and MnO2. CaCO3 was also obtained as a by-product. The obtained results show that carbochlorination is an efficient and effective alternative route for the extraction and recovery of metals from different LIBs, focused on the sustainability and circular economy

Understanding the relationships between land cover/urban structure patterns and air pollutants is key to sustainable urban planning and development. In this study, we employ a mobile monitoring method to collect PM_2.5 and BC data in the city of Philadelphia, PA during the summer of 2019 and apply the Structure of Urban Landscapes (STURLA) methodology to examine relationships between urban structure and atmospheric pollution. We find that, while PM_2.5 and BC vary by STURLA class, many of the differences in pollutant concentrations between classes are not significant. However, we also find that the proportions in which STURLA components are present throughout the urban landscape can be used to predict urban air pollution. Among frequently sampled STURLA classes, gpl hosted the highest PM_2.5 concentrations on average (16.60 _± 4.29 µg/m³), while tgbwp hosted the highest BC concentrations (2.31 _± 1.94 µg/m³). Furthermore, STURLA combined with machine learning modeling was able to correlate PM_2.5 (R²= 0.68, RMSE 2.82 µg/m³) and BC (R² = 0.64, RMSE 0.75 µg/m³) concentrations with the urban landscape and spatially interpolate concentrations where sampling did not take place. These results demonstrate the efficacy of the STURLA methodology in modeling relationships between air pollution and land cover/urban structure patterns.

This paper presents a novel improvement of MuSIASEM (Multiscale Integrated Analysis of the Societal and Ecological Metabolism) by incorporating a new regional analysis of the electricity metabolism across levels. An analysis of Mexico illustrates this toolkit and shows that the industry sector had Economic Energy Intensity (EEI) with 40.3 MWh/MMXN reached a higher value than the commerce and services sector with 0.84 MWh/MMXN. Regarding the Economic Labor Productivity (ELP) indicator (AV/h), the industrial sector with 208.5 TMXN/Kh reached a higher value than the Commercial and services sector with 114.3 TMXN/Kh. With reference to the Exosomatic Metabolic Rate (EMR), the Household sector obtained 59.3 KWh/Kh whereas the paid sector reached 2,486.4 KWh/Kh. Disaggregation of the EMR indicator into economic sectors shows that the Industrial sector obtained 8.4 KWh/Kh and the commercial and services sector reached 0.10 KWh/Kh. The lack of complete data for the agricultural sector does not allow us to calculate EEI, ELP, and EMR indicators accurately. Considering the analysis of indicators by regions, regarding the EEI rate, the Central region had the lowest value with 12.7 MWh/MMXN, followed by the Northeast with 21.4 MWh/MMXN and Western with 29.4 MWh/ MMXN, which means that they require less electricity to produce more added value. In terms of the ELP indicator, it was found regions with higher values were Northeast with 182.3 MMXN/Mh, Central with 177.5 MMXN/Mh, and North with 127 MMXN/Mh, which means that these regions produce more added value per hour of work. About the EMR, it is observed that regions in the northern part of the country had higher values: Northwest with 337 KWh/Kh, Baja California Sur with 334 KWh/Kh, Baja California with 328 KWh/Kh, North with 313 KWh/Kh and Northeast with 274 KWh/Kh, which means that these regions consume more electricity per hour. This innovative approach is useful for governance because it helps to understand and reduce asymmetries across regions, resulting in more social equality and a better economic equilibrium across sectors and regions.

In this systematic review of the literature on using Machine Learning (ML) for credit risk prediction, we raise the need for financial institutions to use AI and ML to assess credit risk, analyzing large volumes of information. We posed research questions about algorithms, metrics, results, data sets, variables, and related limitations in predicting credit risk. We searched renowned databases to answer them and identified 52 relevant studies with the credit industry microfinance. Challenges and approaches in credit risk prediction using ML models we identified, difficulties with the implemented models such as the black box model, the need for explanatory artificial intelligence, the importance of selecting relevant features, addressing multicollinearity, and the problem of the imbalance in the input data. By answering the questions, we identified that the Boosted Category is the most researched family of ML models; the most commonly used metrics for evaluation are Area Under Curve (AUC), Accuracy (ACC), Recall, precision measure F1 (F1), and Precision; Research mainly uses public data sets to compare models, and private ones to generate new knowledge when applied to the real world. The most significant limitation identified is the representativeness of reality, and the variables primarily used in the microcredit industry are related data to the demographic, the operation, and payment behavior. This study aims to guide the developers of credit risk management tools and software towards the existing offer of ML methods, metrics, and techniques used to forecast it, thereby minimizing possible losses due to default and guiding risk appetite.

Our bodies produce a host of electrophilic species that can label specific endogenous proteins in cells. The signaling roles of these molecules are underactive debate. However, in our opinion it is becoming increasingly likely that electrophiles can rewire cellular signaling processes at endogenous levels. Attention is turning more to understanding how nuanced electrophile signaling in cells is. In this perspective, we describe recent work from our laboratory that has started to inform on different levels of context-specific regulation of proteins by electrophiles. We discuss the relevance of these data to the field, and to the broader application of electrophile signaling to precision medicine development, beyond the traditional views of their pleiotropic cytotoxic roles.

Children from rural areas face numerous possibilities for neurodevelopmental conditions that may compromise their well-being and optimal development. Neuropsychology and electroencephalography (EEG) have shown strong agreement in detecting correlations between these two variables and suggest an association with specific environmental and social risk factors. The present meta-analysis aims to integrate the qualitative and quantitative EEG findings, their relationship with cognitive impairment in children living in vulnerable or rural environments, and the main risk factors influencing EEG abnormalities. The method for this purpose was based on a systematic string-based review from Ebscohost and Web of Science, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Qualitative and quantitative analyses were conducted from the outcomes that complied with the selected criteria. A total of 92 records were identified; however, only 20 were eligible, considering 11 for qualitative and 9 for quantitative analysis. The findings highlight a significant amount of literature on EEG and its relation with cognitive impairment from studies in children with epilepsy and malnutrition. In general, there is evidence about the advantages of implementing EEG diagnosis and research techniques in children living under risk conditions. Further research is needed to better describe and integrate the state of the art regarding EEG features extraction.

Pure monocular 3D reconstruction is an ill-posed problem that has attracted the research community's interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction problem and estimate the camera’s ego-motion, so many methods have been proposed. However, most of these methods were not evaluated in large datasets, under various motion patterns, had not been tested under the same metrics, and most of them had not been evaluated following a taxonomy, making their comparison and selection difficult. In this research, we performed a comparison of ten publicly available SLAM and VO methods following a taxonomy, including one method for each category of the primary taxonomy, three machine learning-based methods, and two updates of the best methods, to identify the advantages and limitations of each category of the taxonomy and test if the addition of machine learning or the updates made on those methods improved them significantly. Thus, we evaluated each algorithm under the TUM-Mono benchmark and performed an inferential statistical analysis to identify significative differences through its metrics. Results determined that sparse-direct methods significantly outperformed the rest of the taxonomy, and fusing them with machine learning techniques significantly improves the performance of geometric-based methods from different perspectives.

Phosphite (Phi) has gained attention in agriculture due to its biostimulant effect on crops. This molecule has been found to benefit plant performance by providing protection against pathogens, improving yield and fruit quality, and improving nutrient and water use efficiency. It is still unclear how Phi enhances plant growth and protects against multiple stresses. It has been hypothesized that Phi acts by directly affecting the pathogens and interacting with the plant cellular components and molecular machinery to elicit defense responses. This study delves into elucidating the mechanisms underlying Phi’s beneficial effects on plants, revealing a complex interplay with fundamental signaling pathways. A RNA-seq study of Arabidopsis seedlings under optimal and limiting phosphate conditions helped us unveil Phi’s role in promoting plant growth by activating the expression of genes involved in the biosynthesis and signaling pathways associated with abscisic acid (ABA), salicylic acid (SA), and jasmonic acid (JA). Expression of ABA-related genes, known for their involvement in stress response and development regulation, is triggered by Phi treatment, contributing to enhanced resilience and growth. Simultaneously, the activation of the SA pathway, associated with defense responses, suggests Phi’s potential in bolstering plant immunity. Moreover, Phi influences JA biosynthesis and signaling, which are crucial for defense against herbivores and pathogens, thereby strengthening plants’ defenses. Our findings reveal a multifaceted mechanism through which Phi benefits Arabidopsis development. Understanding its intricate interplay with key signaling pathways opens avenues for leveraging Phi as a strategic tool to enhance plant resilience, immunity, and growth in agricultural and ecological contexts.

This study investigates water consumption in two areas with limited water resources – the Salar de Atacama and Salar de Atacama-Vertiente Pacifico basins in Chile's Antofagasta Region – with the aim of developing strategies that incorporate social and environmental aspects into water management. A qualitative approach was employed that involved a focus group with four water management representatives and surveys of the general population (156 responses). Additionally, the current state of water rights in the basins was examined and the feasibility of the proposed strategies was assessed. The findings reveal that the mining industry's development approach is viewed negatively, mainly due to inadequate community engagement, confidential consumption data, and limited government oversight. Adopting a comprehensive water stewardship approach that considers social and environmental factors would help mitigate the adverse effects of mining on communities. Therefore, improved management and transparent collaboration among stakeholders are essential for responsible water resource use in mining.

The COVID-19 pandemic has obliged Governments all around the world to take confinement and social 13 distancing measures. The reduction of leisure and production activities on beaches and ports have 14 disappeared direct and indirect contamination such as plastics, hydrocarbon spill, microbiological loads, 15 noise level, etc. leading to temporary improved environmental conditions, converting the beaches 16 similar to Marine Protected Areas. Some conditions are briefly analyzed through local surveys and in situ 17 observations in the popular beaches and ports of Salinas, Manta and Galápagos. 97-99 % of surveyed 18 people agreed that beaches have notoriously improved during confinement at least from visual 19 observation. On a scale from 1 (worst) to 5 (best), the beaches were rated 2.23 and 2.83 (less than 20 acceptable) before quarantine, and 4.48 and 4.33 after it for Salinas and Manta respectively. The 21 beaches have less garbage in general and plastic, even though there has been an increase in plastic and 22 face mask production around the world. In Salinas, 72%, and 23 % of surveyed people have seen small 23 pelagic fish, whilst in Manta 75%, and 41% of people saw the same, but also 17% of people have seen 24 whales (humpback and shark-whales) and dolphins practically swimming on the beach. Manta rays, 25 turtles, and other types of species were also observed. In Galapagos beaches, turtles have been 26 observed many more times than usual. The main plausible reason is the decrease in noise level. It is 27 recommended to take this unique opportunity, to construct a baseline data and information on physical, 28 chemical, biological, microbiological coastal oceanographic science, and from them to establish a proper 29 Coastal Zone Management based on beach description, water, and beach quality, human dimension, 30 and economic value indexes. This data and information construction should ideally be done before the 31 beaches are open.

We explore an idea put forward many years ago by Zeldovich and Novikov concerning the existence of compact objects endowed with arbitrarily small mass. The energy-density of such objects, which we call “Ghost stars”, is negative in some regions of the fluid distribution, producing a vanishing total mass. Thus, the interior is matched on the boundary surface to Minkowski space-time. Some exact analytical solutions are exhibited and their properties are analyzed. Observational data that could confirm or dismiss the existence of this kind of stellar object, is commented.