Biocompatible polymeric materials with potential to form functional structures in association with different therapeutic molecules have a high potential for biological, medical and pharmaceutical applications. Therefore, the protective capability of the inclusion nano-Complex formed between the sodium salt of poly(maleic acid-alt-octadecene) and a β-lactam drug (ampicillin trihydrate) on the chemical, enzymatic and biological degradation was evaluated. PAM-18Na was produced and characterized as reported previously. The formation of polymeric hydrophobic aggregates in aqueous solution was determined, using pyrene as a fluorescent probe. Furthermore, the formation of polymer-drug nano-complexes was characterized by Differential Scanning Calorimetry-DSC, viscometric, ultrafiltration/centrifugation assays, zeta potential and size measurements by dynamic light scattering-DLS. The PAM-18Na capacity to avoid the chemical degradation was studied through stress stability tests. The enzymatic degradation was evaluated from a pure β-lactamase, while the biological degradation was determined by different β-lactamase producing Staphylococcus aureus strains. When ampicillin was associated with PAM-18Na, the half-life time in acidic conditions increased, whereas both the enzymatic degradation and the minimum inhibitory concentration decreased to a 90 and 75%, respectively. These results suggest a promissory capability of this polymer to protect the β-lactam drugs against chemical, enzymatic and biological degradation.

Over the last decades, microalgal biomass has gained a significant role in the development of different high-end (nutraceuticals, colorants, food supplements, and pharmaceuticals) and low-end products (biodiesel, bioethanol, and biogas) due to rapid growth and high carbon fixing efficiency. Therefore, microalgae are considered a useful and sustainable resource to attain energy security while reducing our current reliance on fossil fuels. From the technologies available for obtaining biofuels using microalgae biomass, thermochemical processes (pyrolysis, HTL, gasification) have proven to be processed with higher viability, because they use all biomass. However, because of the complexity of the biomass (lipids, carbohydrates , and proteins), the obtained biofuels from direct thermochemical conversion have large amounts of heteroatoms (oxygen, nitrogen , and sulfur). As a solution, catalyst-based processes have emerged as a sustainable solution for the increase in biocrude production. This paper's objective is to present a comprehensive review of recent developments on catalyst mediated conversion of algal biomass. Special attention will be given to operating conditions, strains evaluated, and challenges for the optimal yield of algal-based biofuels through pyrolysis and HTL.

Over the last decades, microalgal biomass has gained a significant role in the development of different high-end (nutraceuticals, colorants, food supplements, and pharmaceuticals) and low-end products (biodiesel, bioethanol, and biogas) due to rapid growth and high carbon fixing efficiency. Therefore, microalgae are considered a useful and sustainable resource to attain energy security while reducing our current reliance on fossil fuels. From the technologies available for obtaining biofuels using microalgae biomass, thermochemical processes (pyrolysis, HTL, gasification) have proven to be processed with higher viability, because they use all biomass. However, the biocrudes obtained from direct thermochemical conversion have substantial quantities of heteroatoms (oxygen, nitrogen, and sulfur) due to the complexity of the biomass's content of chemical components (lipids, carbohydrates, and proteins). As a solution, catalyst-based processes have emerged as a sustainable solution for the increase in biocrude production. This paper's objective is to present a comprehensive review of recent developments on catalyst mediated conversion of algal biomass. Special attention will be given to operating conditions, strains evaluated, and challenges for the optimal yield of algal-based biofuels through pyrolysis and HTL.

This paper presents the implementation of a control strategy based on fuzzy logic artificial intelligence (AI) for speed regulation of an electromagnetic frequency regulator (EFR) prototype, aiming to eliminate the dependence on knowledge of physical parameters in the most diverse operating conditions. Speed multiplication is one of the most important steps in power generation wind. Gearboxes are generally used for this purpose. However, they have a reduced lifespan and a high failure rate and are still noise sources. The search for new ways to match the speed (and torque) between the turbine and the generator is an important research area to increase the energy, financial and environmental efficiency of wind systems. The EFR device is an example of an alternative technology that this team of researchers has proposed. It counts the fact of taking advantage of the main advantages of an induction machine with the rotor in a squirrel cage positively. In the first studies, the EFR control strategy consisted of the conventional PID controllers, which has several limitations widely discussed in the literature. This strategy also limits the EFR's performance, considering its entire operating range. The simulation program was developed using the Matlab/Simulink platform, while the experimental results were obtained in the laboratory emulating the EFR-based system. The EFR prototype used has 2 poles, a nominal power of 2.2 kW, and a nominal frequency of 60 Hz. Experimental results were presented to validate the efficiency of the proposed control strategy.

Tuberculosis (TB) is an infectious disease declared a global emergency by the World Health Organization and continues as one of the world’s top ten causes of death. TB diagnosis is more critical in developing countries where demanded infrastructure for detection, and treatment complicates the efforts against the disease. These aspects related to limited resources are significant, especially in areas away from the main cities, with few mechanisms to make a timely diagnosis that contributes to successfully addressing the possible patients. Artificial intelligence has begun to be essential in providing additional strategies in the diagnosis processes for health professionals’ support. This paper uses natural language processing (NLP) and machine learning (ML) techniques to create models that can supply TB diagnosis when the needed infrastructure is unavailable. Two different sources were explored: text extracted from electronic medical records (EMR) and patient clinical data (CD). Four proposals using five different machine learning models were implemented. The first two models employed ML and each data source independently. Then, two additional approaches developed a data fusion from both sources. This strategy’s employment was analyzed with physicians according to their pertinence in the process and understanding of the EMR. Finally, the results of the data fusion were compared to each source, obtaining better performance at using only the CD, where an area under the ROC curve of 69.9±2.3% was obtained. However, the advantage of analyzing physician’s reports is the availability of this information contrasted to clinical-specific data, which can be more useful in places far from the main cities without enough basic structure for its obtaining.

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the two most common neurodegenerative diseases in elderly. The key histopathological features of these diseases are the presence of abnormal protein aggregates and the progressive and irreversible loss of neurons in specific brain regions. The exact mechanisms underlying the etiopathogenesis of AD or PD remain unknown, but there is extensive evidence indicating that excessive generation of reactive oxygen species (ROS) and reactive nitrogen species (RNS) along with a depleted antioxidant system, mitochondrial dysfunction, and intracellular Ca2+ dyshomeostasis play a vital role in the pathophysiology of these neurological disorders. Due to an improvement in life expectancy, the incidence of age-related neurodegenerative diseases has significantly increased. However, there is no effective protective treatment or therapy available but rather only very limited palliative treatment. Therefore, there is an urgent need for the development of preventive strategies and disease-modifying therapies to treat AD/PD. Because dysregulated Ca2+ metabolism drives oxidative damage and neuropathology in these diseases, the identification or development of compounds capable of restoring Ca2+ homeostasis and signaling may provide a neuroprotective avenue for the treatment of neurodegenerative diseases. In addition, a set of strategies to control mitochondrial Ca2+ homeostasis and signaling has been reported, including decreased Ca2+ uptake through voltage-operated Ca2+ channels (VOCCs). In this article, we review the modulatory effects of several heterocyclic compounds on Ca2+ homeostasis and trafficking, and their ability to regulate compromised mitochondrial function and associated free radical production during the onset and progression of AD or PD. This comprehensive review also describes the chemical synthesis of the heterocycles and summarizes the clinical trial outcomes.

This paper presents a concise mathematical framework for investigating both feed-forward and backward process, during the training to learn model weights, of an artificial neural network (ANN). Inspired from the idea of the two-step rule for backpropagation, we define a notion of F_adjoint which is aimed at a better description of the backpropagation algorithm. In particular, by introducing the notions of F-propagation and F-adjoint through a deep neural network architecture, the backpropagation associated to a cost/loss function is proven to be completely characterized by the F-adjoint of the corresponding F-propagation relatively to the partial derivative, with respect to the inputs, of the cost function.

It has been proven that in standard Einstein gravity, exotic matter (i.e. matter violating the point-wise and averaged weak and null energy conditions) is required to stabilize traversable wormholes. Quantum field theory permits these violations due to the quantum coherent effects found in any quantum field . Even reasonable classical scalar fields violate the energy conditions. In the case of the Casimir effect and squeezed vacuum states, these violations have been experimentally proven. It is advantageous to investigate methods of minimizing the use of exotic matter. One such area of interest is extended theories of Einstein gravity. It has been claimed that in some extended theories, stable traversable wormholes solutions can be found without the use of exotic matter. There are many extended theories of gravity and in this review paper we first explore f(R) theories and then explore some wormhole solutions in f(R) theories including Lovelock gravity.

This article analyzes laws, normative reforms and regulations surrounding the practices and mechanisms of control over the consumption, cultivation and commercialization of cannabis. On the one hand, I investigate regulatory practices that deny rights for the consumption of cannabis classified as recreational. On the other hand, I study regulatory practices that extend rights for the production, consumption and commercialization of cannabis classified as medicinal and industrial. The empirical moment is composed of four stages and methodological tools. First, I conduct an analysis of state policies. Then, I analyze nine laws and codes on cannabis regulation from 1970 to the present. Next, I perform five semi-structured interviews. Finally, I develop two life stories of former people deprived of their liberty for cannabis cultivation and trade. In this way, I trace forms of regulation on multiple demands, knowledge, interests and beliefs. This research focuses on state regulation. Cannabis regulatory regimes are conceived as constructions of political, social and economic truths, meanings and rights. In sum, the answer to the question of how collective demands around cannabis are regulated in Ecuador stipulates that state action reinforces stigmatization and criminalization. In addition, it legitimizes moral entrepreneurs and counter-movements around cannabis.

Road markings play an important role in road safety because they provide significant information to drivers about the road. For that reason, they must be replaced when they are not correctly perceived by road users. To analyse which are the main factors that affect road marking perception over time, a test section was designed in a two-lane rural highway, running actual traffic over 18 different types of markings fabricated with different combinations of drop-on materials. Chromatic coordinates, luminance and retroreflectivity of each sample were measured during 18 months in order to study their evolution over time. The results obtained show different behaviours depending on the aggregates and application method used. An increment of the durability has been observed with the use of different layers and mixtures of glass microbeads with different sizes.

Microalgal harvesting is one of the most challenging processes in the development of algal research and development. Several methods, such as centrifugation, flocculation, and filtration, are available at the laboratory scale. However, the requirement of expensive pieces of equipment and the possibility of biomass contamination are recurring gaps that hinder the development of microalgae I+D in different parts of the world. Recently, the electroflotation has been proved as a suitable method for the harvesting of different species of microalgae and cyanobacteria. To this day, there are no companies that sell laboratory-scale electroflotation equipment; this is mainly due to the gap in the knowledge on which factors (time, mixing rate, number of electrodes, and others) will affect the efficiency of concentration without reducing the biomass quality. This paper aims to build an innovative low-cost electroflotation system under 300 USD with cheap and resistant materials. To achieve our goal, we test the interaction of three variables (time, mixing rate, and amount of electrodes) were evaluated. Results showed that an efficiency closer to 100% could be achieved under 20 minutes using >10 electrodes and 150 rpm. We hope this innovative approach can be used by different researchers to improve our knowledge of the concentration and harvesting of algae and cyanobacteria.

A 52-y/o asymptomatic male with history of hypertension, was referred to our Heart Failure Clinic due to report of hypertrophic cardiomyopathy, TTE with an increased end-diastolic thick-ness (basal inferoseptal of 23 mm, and basal anteroseptal of 21 mm). CMR demonstrated late gadolinium enhancement at the septum, anterior, inferolateral, and inferior walls with a mid-myocardial distribution, T1 mapping which reported an average T1 of 929 ms. A next-generation sequencing panel was requested. Results demonstrated hemizygosis, in the ga-lactosidase alpha gene, consistent with Fabry Disease. The replacement of the enzyme was start-ed. Extended familial genetic counseling and testing were done.

In recent years, music education in Ibero-America has been losing ground within the school environment in favor of the development of curricular systems that benefit academic results in standardized tests. Despite this, several studies in the field of cognitive neurosciences have found evidence of great relevance and in which it can be observed how music education can favor cognitive development and performance in practically all stages of human development, with important results in language tasks, attention, and executive functions such as planning, inhibition, cognitive flexibility and working memory.

The rock joint fissure slope in cold regions is prone to deformation and failure problems such as relaxation, tension and collapse under freeze-thaw (F-T) cycles. Based on the ideology of clean production and promoting the structural integrity of geotechnical projects in cold areas, this study designed and prepared aeolian-sand (AS) to replace part of river sand as a filling mortar material by taking advantage of the low cost and easy availability of AS. Investigations were carried out to determine the impact of varying proportions of AS in mortar on the microstructure and shear properties of the mortar-rock interface under F-T cycles. Therefore, F-T cycle testing, nuclear magnetic resonance (NMR) testing and shear testing were carried out on grout with different proportions of AS. The results show that the right proportion of AS replacement could enhance the shear deformation resistance and F-T resistance of the mortar-rock interface, and 30% proportion is the optimal proportion. By increasing of F-T cycles, the three types of specimens showed different degrees of particle spalling, shedding and cracking. The slurry-rock interface layer in the A (0%) group exhibited the most severe F-T deterioration, while the B (15%) group showed a lesser degree, and the C (30%) group performed the best. T2 spectrum curve and total spectrum area change law from the microscopic point of view to verify the 30% AS proportion mortar-rock interface F-T resistance is the strongest, followed by 15% AS proportion mortar, the weakest is ordinary mortar. The degradation of the mortar-rock bond is primarily due to the conversion of solid to liquid phases and the movement of internal water caused by fluctuating temperatures. The extent of F-T deterioration in the slurry-rock interface layer is greatly affected by the varying proportions of AS. The shear strength and shear stiffness of specific proportion of AS decreased with the increase of F-T cycles. For same F-T cycles, the shear strength and shear stiffness of group C (30%) were the highest, followed by group B (15%) and group A (0%). The grout material not only reinforces the F-T joint fissure slope, but also reduces the cost of grout reinforcement and promotes the clean production of geotechnical structures.

Recently a measure termed F* was described, as an interpretable transformation of the F measure, also known as the Dice coefficient. Using elementary mathematical methods, it is shown that F* is in fact identical to a previously described measure, monotonically related to the F measure, and variously termed in previous publications, dating from the late 19^th to the late 20^th century, as the ratio of verification, the Jaccard similarity measure or index, the threat score, the Tanimoto index, and the critical success index. The origins of these different terms in different disciplines (weather forecasting, ecology, machine learning) may explain the repeated independent redescription of this measure.

This paper has a twofold objective. The first aim is to present a comprehensive bibliographical analysis of journal articles and book chapters on fuzzy-random option pricing (FROP) over the WoS and SCOPUS databases. It follows PRISMA criteria and takes special care of developments in continuous time. Thus, we described the principal findings about the research streams, outlets and authors of this topic and lets us suggest further research. The second contribution is motivated by the fact that the bibliographical revision has identified a lack of developments on equilibrium models on the yield curve. This question motivates extending Vasicek’s yield curve equilibrium model to introduce fuzziness in the parameters that govern interest rate movements (speed of reversion, equilibrium short-term interest rate, and volatility). Likewise, this paper develops an empirical application on the term structure of fixed income public bonds with the highest credit rating in the Euro area.

This study investigates distillery wastewater, commonly known as vinasse, as a potential culture medium for the production of Chlorella vulgaris and its most relevant metabolites. The effect of vinasse concentration on the composition of the biomass (proteins, carbohydrates and lipids) was evaluated in treatments performed in 6-L tubular air-lift reactors. The reactors were operated at 25 °C for 18 days, in total darkness, under a continuous flow of air. Results showed a rapid growth of microalgae in the first ten days, when an average production of 0.87 g/L was reached. Then, the daily biomass productivity began to decrease, up to an average value of 11.8 g/L at the 16th day. For all treatments, there was a significant reduction in the concentration of most metabolites in the first eight days. This was likely due to the adaptation of the biomass to the new conditions, with a transition from autotrophic to heterotrophic metabolism. From the 10th day, the concentration of metabolites in the biomass began to increase, reaching a nearly constant value at the 16th day. The observed maximum concentrations (%w/w) were: 48.95% proteins, 2.88% xylose, 7.82% glucose, 4.54% arabinose, 8.28% fructose and 4.82% lipids. These values were only marginally affected by the type of treatment. Overall, the results obtained suggest that vinasse is a promising and sustainable medium for the growth of C. vulgaris and the production of valuable metabolites.

A popular approach to learning about admixture from population genetic data is by computing the allele-sharing summary statistics known as f-statistics. Compared to some methods in population genetics, f-statistics are relatively simple, but interpreting them can still be complicated at times. In addition, f-statistics can be used to build admixture graphs (multi-population trees allowing for admixture events), which provide more explicit and thorough modeling capabilities but are correspondingly more complex to work with. Here, I discuss some of these issues to provide users of these tools with a basic guide for protocols and procedures. My focus is on the kinds of conclusions that can or cannot be drawn from the results of f₄-statistics and admixture graphs, illustrated with real-world examples involving human populations.

El Olivo Cave (Pruvia de Arriba, Llanera, Asturias, Spain) is a small karst cave located in the Aboño River basin and formed in the Cretaceous limestone of the Mesozoic cover of the Cantabrian Mountains (north of the Iberian Peninsula). It contains an important upper Pleistocene sedimen-tary, archaeological and paleontological record, with abundant technological evidence and faunal remains. The archaeological record shows a first occupation that could correspond to the Middle Paleolithic and a second occupation in the Middle Magdalenian. The stratigraphic sequence inside and outside the cave was studied with geoarchaeological methodology. In this paper, the lithostratigraphic sequence is analyzed and the data from the granulometric, mineralogical, edaphological and radiometric analyses are presented. The results of these analyses enable an accurate interpretation of both the lithostratigraphy of the deposit as well as the processes re-sponsible for its formation and subsequent evolution. The available numerical dates allow us to locate the first sedimentation episode in the cave in OIS 7a, in the Middle Pleistocene, the base of the outer fluvial sedimentation in the cold OIS 3a stage of the Upper Pleistocene and the Magdalenian occupation in the Last Glacial Maximum (OIS 2) at the end of the Late Pleistocene.

This study describes the design and implementation of an electronic nose, which was applied to classify and identify hazardous gases generated in underground coal mines. For this purpose, an electrochemical sensor array was used to detect a set of toxic gases. This work illustrates the electronic components of a wireless multisensory system for the toxic gases detection on indoor environments (i.e., underground mines), which was performed with reduced size, low cost and low electrical consumption, in order to detect different compounds using the basic principle of operation of each component to be applied to the target gas. Furthermore, the sample collection, data communication and data processing in real time obtained an excellent performance for gas sensing and even to measure the concentration level of the chemical volatile compounds transmitted from different points of the detection zone. The results demonstrated that using a wireless electronic nose for toxic gases detection was possible to reach a success rate of discrimination of 97%, using principal components analysis (PCA) and Linear Discriminant Analysis (LDA).

Abstract: Despite existing several techniques for distributed sensing (temperature and strain) using standard Single Mode optical Fiber (SMF), compensating or decoupling both effects is mandatory for many applications. Currently, most of the decoupling techniques require special optical fibers and are difficult to implement with high spatial resolution distributed techniques, such as ϕ-PA-OFDR. So, this work’s objective is to study the feasibility of decoupling temperature and strain out of a ϕ-PA-OFDR readouts taken over an SMF. For this purpose, the readouts will be subjected to a study using several Machine Learning algorithms, among them, Deep Neural Networks. The motivation which underlies this target is the current blockage in the widespread use of Fiber Optic Sensors in situations where both strain and temperature change, due to the coupled dependence of currently developed sensing methods. Instead of using other types of sensors or even other interrogation methods, the objective of this work is to analyze the available information in order to develop a sensing method capable of providing information about strain and temperature simultaneously.

Background: The two-stage technique combining the Endoscopic Retrograde CholangioPancreatography (ERCP) with common bile duct (CBD) clearance carried out before the laparoscopic cholecystectomy represents the most common approach for CBD stones. Over time, different techniques have been proposed to manage cholecysto- choledocholithiasis (CCL) advantageously in one stage. Among these, the laparoendoscopic rendez-vous (LERV) addresses the CCL issue with a laparoscopic cholecystectomy with insertion of a guide wire performed at initial stage of the procedure, followed by the clearance of the bile duct carried out by the endoscopists. The goal of this study was to evaluate the efficacy and safeness of LERV procedure recording results and complications, also making a comparison between our results and current literature. Methods: We reviewed our experience of all consecutive patients with cholecysto-choledocholithiasis managed with LERV between January 2018 and December 2023. LERV success rate, operative time, length of hospital stay, stone recurrence, incidence of endoscopic and surgical complications were analysed. Results: A total of 120 patients underwent LERV in our facilities. We reported a 97% LERV success rate, 1.6% conversion-to-open rate, a median intraoperative time of 122 (range 95-220) min. The median hospital stay was 4 (range 2-38) days. An overall morbidity of 15% was reported (18/120): 15 Clavien-Dindo type 1/2, 2 type 3a and one type 3b. In two cases a re-operation during the hospital stay was necessary. At a median follow-up of 14 months (3-59) five patients experienced stone recurrence requiring redo-ERCP in two cases. Conclusion: LERV offers the significant advantage of a single stage procedure and hospitalisation along with a lower risk of post-ERCP pancreatitis, failed CBD cannulation and complications. Our experience confirms safety and effectiveness of the technique for CCL management.

Litsea martabanica root's antioxidant and AChE activity showed promise as a pesticide detoxification agent in our previous study. In addition to roots, its leaves can help mitigate pesticide exposure, although there is limited scientific evidence supporting their efficacy. However, the use of roots in many countries, such as Thailand, could contribute to environmental degradation, as highland communities traditionally cut down whole trees to obtain them. This study aims to evaluate the antioxidant activity and anti-pesticide potential of water extracts from L. martabanica leaves instead of its roots through in vitro and in vivo investigations. The findings showed that L. martabanica water extracts and fractions demonstrated varied antioxidant activity. The water extract, obtained using traditional extraction methods, was chosen for in vivo experiments. Rats received the extract followed by chlorpyrifos exposure for 16 days. Results indicated reduced acetylcholinesterase activity in chlorpyrifos-exposed rats, while treatment with leaf extract led to increased activity, suggesting its potential as a detoxifying agent. Histopathological examination revealed no liver cell necrosis and showed liver cell regeneration, indicating potential protection against free radical-induced liver damage without affecting rat liver weight or biochemical profiles. Utilizing L. martabanica leaves for healthcare purposes holds promise without negative environmental impact.

The aims of this study are to measure the technical efficiency (TE) of Cambodian household’s rice production and trying to determine its main influencing factors using the stochastic frontier production function. The study utilized primary data collected from 301 rice farmers in three selected districts of Battambang by structured questionnaires. The empirical results indicated the level of household rice output varied according to differences in the efficiency of production processes. The mean TE is 0.34 which means that famers produce 34% of rice at best practice at the current level of production inputs and technology, indicates that rice output has the potential of being increased further by 66% at the same level of inputs if farmers had been technically efficient. Furthermore, between 2013-2015 TE of household’s rice production recorded -14.3% decline rate due to highly affected of drought during dry season of 2015. Moreover, evidence reveals that land, fertilizer, and pesticide are the major influencing input factors of household’s rice production, while disaster, education of household head, family size and other crops’ cultivated area are core influencing factors decreasing TE. Conversely, the main influencing factors increasing TE are irrigated area, number of plot area and sex of household head.

The aims of this study are to measure the technical efficiency (TE) of Cambodian household’s rice production and trying to determine its main influencing factors using the stochastic frontier production function. The study utilized primary data collected from 301 rice farmers in three selected districts of Battambang by structured questionnaires. The empirical results indicated the level of household rice output varied according to differences in the efficiency of the production processes. The mean TE is 0.34 which means that famers produce 34% of rice at best practice at the current level of production inputs and technology, indicates that rice output has the potential of being increased further by 66% at the same level of inputs if farmers had been technically efficient. Furthermore, between 2013-2015, TE of household’s rice production recorded -14.3% decline rate due to highly affected of drought during dry season of 2015. Moreover, evidence reveals that land, fertilizer, and pesticide are the major influencing input factors of household’s rice production, while disaster, education of household head, family size and other crops’ cultivated area are core influencing factors decreasing TE. Conversely, the main influencing factors increasing TE are irrigated area, number of plot area and sex of household head.

The present study aims to measure the technical efficiency and establish core factors effecting rice production in Cambodia. Four-years dataset generated from the central government document “Profile on Economics and Social” of entire 25 provinces between 2012-2015 and the stochastic production frontier model (SFA) was applied. The results indicated that the level of output (quantity) of Cambodian rice production varied according to the different level of capital investment in agricultural machineries, total rice actual harvested area, and technically fertilizers application within provinces. Furthermore, evidence revealed the overall mean efficiency of rice production is 78.4% implies that there is still room to further improve technical efficiency by given the same level of inputs and technology. More importantly, the findings revealed that irrigation, production technique and amount of agricultural supporting staffs are being as the most important influencing factors of rice production’s technical efficiency in Cambodia. In conclusion, present study strongly recommends the development of irrigation systems and good water management practices to be considered and bring into more effective actions by the central government as well as related agencies for improving rice production in Cambodia in addition to capital investment and improving technical skills of supporting staffs and rural farmers.

We study in this work a dilute granular gas immersed in a thermal bath made of smaller particles with nonnegligible masses as compared with the granular ones. The kinetic theory for this system is developed and described by an Enskog--Fokker--Planck equation for the one-particle velocity distribution function. Granular particles are assumed to have inelastic and hard interactions, losing energy in collisions as accounted by a constant coefficient of normal restitution. The interaction with the thermal bath is based on a nonlinear drag force plus a white-noise stochastic force. To get explicit results of the temperature aging and steady states, Maxwellian and first Sonine approximations are developed. The latter takes into account the coupling of the excess kurtosis with the temperature. Theoretical predictions are compared with direct simulation Monte Carlo and event-driven molecular dynamics simulations. While good results for the granular temperature are obtained from the Maxwellian approximation, a much better agreement, especially as inelasticity and drag nonlinearity increase, is found when using the first Sonine approximation. The latter approximation is, additionally, crucial to account for memory effects like Mpemba and Kovacs-like ones.

In recent years, the problem of ecosystem degradation caused by human activities has become increasingly serious. Vegetation restoration is a key means to solve this problem, which has increased. To address the suitability and structural optimization of vegetation restoration in the Loess Plateau, the MaxEnt model was used to quantify the impacts of environmental and human activities on the planting suitability of vegetation restoration species at the raster scale. Three layers of trees, shrubs, and herbs with 12 common vegetation restoration species were selected. The factor index system was constructed by combining climatic, ecological, and socio-economic data, and the MaxEnt model predicted land suitability. It was found that human activities significantly increased the unsuitable planting area. This especially affected Robinia pseudoacacia in the tree layer and Amorpha fruticosa in the shrub layer. Highly suitable and moderately suitable areas were mainly located in sparsely populated areas with close water sources. Through maximum suitability optimization, it was identified that the overall spatial distribution of the three layers in the study area was relatively consistent, and the structural dominance of trees + shrubs + herbs and single herbs in the vertical structure was obvious, which were concentrated in the southwestern and northeastern parts of the study area, respectively. In addition, organic content (OC) and distance from the road to woodland (RW) were the dominant factors affecting land suitability, with a contribution rate of more than 50% and up to 80%. These results provide a scientific basis for optimizing planting structures. They are of significant theoretical and practical significance in guiding vegetation restoration work.

Anthropogenic change is associated with population growth, land use change, and changing economies. However, internal migration patterns and armed conflicts are also key drivers behind anthropogenic and demographic processes. To better understand this sort of change, we explore the spatial relationship between forced migration due to armed conflict and changing demographic factors in Colombia, a country which has a recent history of 7 million internal migrants. In addition, we use remote sensing, Google Earth Engine, as well as spatial statistical analyses of demographic data in order to measure anthropogenic change between 1984 and 2008; and we look into spatiotemporal relationships between both demographic and anthropogenic changes, which are caused by forced migration. We find, thus, that the latter is significantly and positively related to an increasing rural-urban kind of migration which originates in armed conflict, and results show that it is also negatively associated with interregional expulsion. Indeed, anthropogenic prints (term hereafter used to denote changes in nighttime satellite imagery) pertaining to different regions have had different sensitivities towards forced migration, and across different time periods. Finally we discuss how social and political phenomena such as Colombia’s armed conflict can have significant effects on the dynamics and motions of humans and territories in countries of the Global South.

The Indian meal moth, Plodia interpunctella, poses a significant threat to global agricultural products. Although pheromone-based technologies show promise for P. interpunctella management, limitations like single-sex targeting necessitate exploring complementary strategies. Vegetable-based oils represent a potential alternative, but their efficacy, sex-specificity, and interaction with sex pheromones remain unclear. To answer these questions, we first examined attraction of P. interpunctella female and male adults to ten different vegetable oils, i.e., camellia, corn, olive, peanut, rapeseed, sesame, soybean, sunflower, walnut, and a blended oil (mixture of sunflower seed, rapeseed, soybean, peanut, and sesame oils), in the semi-field conditions. Sesame, olive, and blended oils demonstrated most attractive, capturing significantly more adults compared to other oils. We then evaluated effectiveness of these three attractive oils and their combinations with P. interpunctella sex pheromone in a grain warehouse. Traps baited with these oils captured significantly more females and males compared to control traps without attractants. However, sex pheromone addition did not improve male capture and significantly reduced female capture, suggesting an inhibitory effect. Our findings highlight the potential of blended, olive, or sesame oil trap alone as alternative monitoring and trapping tools for P. interpunctella, delivering novel insights into the development of efficient integrated pest management strategies for stored products.

In this work, we explore a the different forms of a new type of modified gravity, namely f(φ) gravity. We construct the Big Rip type for the energy density and the curvature of the universe. We show that dark energy is a result of the transformation of the field φ mass (dark matter) to energy. In addition, we provide that Ω_{m}≈0,050, Ω_{DM}≈0,2, Ω_{DE}≈0,746, is in excellent agreement with observation data. We explore a generalized formalism of braneworld modified gravity. We also construct a new field equations, which generalize the Einstein field equations. We provide a relation between the extra dimension in 3-brane with the vacuum energy density. We show that the energy density of matter depends directly on the number of dimensions. We manage to find the value of the Gauss-Bonnet coupling α=1/4 which is a good agreement with the results in the literature, this correspondence creates a passage between f(R) gravity and Gauss-Bonnet gravity, this comparison leads to a number of bulk dimensions equal to D=10¹²¹+4.

In many application problems, F-transform algorithms are very efficient. In F-transform techniques, we replace the original signal or image with a finite number of weighted averages. The use of weighted average can be naturally explained, e.g., by the fact that this is what we get anyway when we measure the signal. However, most successful applications of F-transform have an additional not-so-easy-to-explain feature: the partition requirement, that the sum of all the related weighting functions is a constant. In this paper, we show that this seemingly difficult-to-explain requirement can also be naturally explained in signal-measuring terms: namely, this requirement can be derived from the natural desire to have all the signal values at different moments of time estimated with the same accuracy.

The production of vaccines of biological origin presents a tremendous challenge for researchers. In this context, animal cell cultures are an excellent alternative for the isolation and production of biologicals against several viruses since they have an affinity with viruses and a great capacity for their replicability. Different variables have been studied to know the system's ideal parameters, allowing it to obtain profitable and competitive products. Consequently, this work focuses its efforts on evaluating an alternative for producing an anti-influenza biological from MDCK cells using SuperPro Designer v8.0 software. The process uses the DMEN culture medium supplemented with nutrients as raw material for cell development; the MDCK cells were obtained from a potential scale-up with a final working volume of 500 L, four days of residence time, inoculum volume of 10%, and continuous working mode with up to a total of 7400 h/Yr of work. The scheme has the necessary equipment for the vaccine's production, infection, and manufacture with yields of up to 416,698 units/h. In addition, it was estimated to be economically viable to produce recombinant vaccines with competitive prices of up to 0.31 USD/unit.

In this paper we have defined the effect of bulk viscosity on Quintessence model and scaler field potential as well as on classical field. We have shown the same effect for modified gravity with f(R,T)= R+f(T). In the derivation we have predicted the possibility of time dependent evolution of gravitational constant G and anisotropy.

The compatibility between the de Sitter Swampland conjecture and Ho\v{r}ava-Lifshitz $F(\bar{R})$ theories with a flat FLRW metric is studied. We first study the standard $f(R)$ theories and show that the only way in which the dS conjecture can be made independent of $R$ is by considering a power law of the form $f(R)\sim R^{\gamma}$. The conjecture and the consistency of the theory puts restrictions on $\gamma$ to be greater but close to $1$. For the $F(\bar{R})$ theories described by its two parameters $\lambda$ and $\mu$ we use the equations of motion to construct the function starting with an ansatz for the scale factor in the Jordan frame of the power law form. By doing a conformal transformation on the three metric to the Einstein frame we can obtain an action of gravity plus a scalar filed by relating the parameters of the theory. The non-projectable and projectable cases are studied and the differences are outlined. The $F(\bar{R})$ function obtained consists of terms of the form $\bar{R}^{\gamma}$ with the possibility of having negative power terms. The dS conjecture leads to inequalities for the $\lambda$ parameter, in both versions it gets restricted to be greater but close to $1/3$. For the general case in which $\mu$ and $\lambda$ are considered as independent, the action contains an extra term but we propose that the conjecture is still applicable. Once again the non-projectable and projectable cases are studied. The $F$ function obtained has the same form as before, the consistency of the theory and the dS conjecture lead to a set of inequalities on both parameters that are studied numerically. In all cases $\lambda$ is restricted by $\mu$ around $1/3$ and we obtain $\lambda\to1/3$ if $\mu\to0$. Finally we consider the $f(R)$ limit $\mu,\lambda\to1$ and we obtain consistent results.

The Roman economy of the Iberian Peninsula has habitually been characterised in terms of prestige goods and economic activities such as trade, mining and metallurgy. The analysis of plant-based foods –less prestigious but more essential in everyday life– has commonly been marginalised in state-of-the-art reviews. The O Areal saltworks is exceptional in terms of the large number of organic materials it preserves, and the excellent state of that preservation. After its abandonment (end of the 3rd/4th century AD), the saltworks was briefly used as a dumping ground for the surrounding area. The site's archaeobotanical remains, preserved under anoxic, waterlogged conditions, consist of the building materials used at the saltworks, tools and other artefacts, organic objects employed in activities such as fishing, and refuse. The assemblage suggests a wide diversity of species to have been introduced into northwestern Iberia during the Roman Period, including the mulberry, peach, fig, plum, grapevine, and melon. The notable presence of other edible fruit species that normally grew wild during this period, such as chestnut, walnut, stone pine, and cherry trees, might be related to the start of their cultivation.

The article takes the case of the adoption of machine learning in a steel manufacturing process through a platform provided by a novel Canadian startup, Canvass Analytics. This way the steel company could optimize the process in a blast furnace. The content of the paper includes a conceptual framework on key factors around steel manufacturing and machine learning. Method: The article takes the case of the adoption of machine learning in a steel manufacturing process through a platform provided by a novel Canadian startup, Canvass Analytics. This way the steel company could optimize the process in a blast furnace. The content of the paper includes a conceptual framework on key factors around steel manufacturing and machine learning. Results: This case is relevant for the authors by the way the business model proposed by the startup attempts to democratize Artificial Intelligence and Machine Learning in industrial environments. This way the startup delivers value to facilitate traditional industries to obtain better operational results, and contribute to a better use of resources. Conclusion: This work is focused on opportunities that arise around Artificial Intelligence as a driver for new business and operating models. Besides the paper looks into the framework of the adoption of Artificial Intelligence and Machine Learning in a traditional industrial environment towards a smart manufacturing approach.

Several life contingency agreements are based on the assumption that policyholders have impaired life expectancy attributable to factors such as lifestyle, social class, or preexisting health issues. Quantifying two crucial variables, augmented death probabilities and the discount rate of projected cash flows, is essential for pricing such agreements. Information regarding the correct values of these parameters is subject to vagueness and imprecision, which further intensifies if impairments must be considered. This study proposes modelling mortality and interest rates using a generalization of fuzzy numbers (FNs), known as intuitionistic fuzzy numbers (IFNs). Consequently, this paper extends the literature on life contingency pricing with fuzzy parameters, where uncertainty in variables, such as interest rates and death probabilities, is modelled using FNs. While FNs introduce epistemic uncertainty, the use of IFNs adds bipolarity to the analysis by incorporating both positive and negative information regarding actuarial variables. Our analysis focuses on two agreements involving policyholders with impaired life expectancy: determining the annuity payment in a substandard annuity and pricing a life settlement over a whole life insurance policy. In particular, we emphasize modelling interest rates and survival probabilities using triangular intuitionistic fuzzy numbers (TIFNs) owing to their ease of interpretation and implementation.

Temperature Cycle Induced Deracemization (TCID) offers a promising approach to obtain enantiopure solids from racemic mixtures. By combining rapid racemization in solution and temperature swings, homochirality is theoretically achieved. Despite theoretical expectations of doubled yields compared to traditional chiral separation methods, such as in Preferential Crystallization, experimental validation remains lacking. We applied TCID to (1-(4-chlorophenyl)-4,4-dimethyl-2-(1H-1,2,4-triazol-1-yl) pentan-3-one) (Cl-TAK), introducing a post-TCID cooling step to enhance yield and a washing step to augment enantiopurity. This refinement yielded an 89.8% mass yield with 99.1% enantiomeric excess in the crystal phase (c.e.e.) within 24 hours on an 8.75g scale, showcasing improved performance with insignificant process duration extension. Additionally, we explored the stochasticity of deracemization, observing the development from low initial crystal enantiomeric excesses(1-6% c.e.e0) at a 2.5 g scale. Kinetic analysis revealed that a 2% c.e.e0 effectively mitigates chiral flipping risks and induction time in our system. Our study underscores the potential for reduced initial c.e.e. to expedite deracemization and presents a straightforward method to optimize yield and purity, facilitating industrial application.

We investigate alternative candidates to dark energy that can explain the current state of the universe in the framework of the generalized teleparallel theory of gravity f(T ) where T denotes the torsion scalar. To achieve this, we carried out a series of reconstruction taking into account to the ordinary and entropy-corrected versions of the holographic and new agegraphic dark energy models. These models used as alternative to dark energy in the literature in order describe the current state of our universe. It is remarked that the models reconstructed indicates behaviors like phantom or quintessence models. Furthermore, we also generated the EoS parameters associated to entropy-corrected models and we observed a transition phase between quintessence state and phantom state as showed by recent observational data. We also investigated on the stability theses models and we created the {r − s}. The behavior of certains physical parameters as speed of sound and the Statefinder parameters are compatible with current observational data.

In this work we present a novel steganography algorithm, based on Fractal Transform domain, combined with the principles of Cryptography. The proposed method uses a private key, which will indicate which segment of the image will be taken and encoded with the Fractal Transform, to then insert the secret bits in the transformed coefficients, thus generating the stego image.

The objective of this study was to investigate the umami characteristics of soy sauce using electronic tongue evaluation and amino acid composition and Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis. The soy sauce peptides were isolated from soy sauce using XAD-16 macroporous resin combined with ethanol solution. Results showed that the soy sauce peptide fraction eluted by 60% ethanol (SS-60%) exhibited a prominent umami taste and the umami scores were highly positively correlated with the amino acid nitrogen contents of soy sauces. The umami scores of SS-60% were significantly positively correlated with the contents of free amino acids. Especially, Phe showed the highest positive correlation with the umami scores. In addition, five characteristic ion peaks with m/z at 499, 561, 643, 649, and 855 were identified in the peptide mass fingerprinting. Therefore, this study provides new insights into the umami characteristics for the flavor evaluation and reality identification of soy sauce.

Background/Objectives: It is known that balance disorders involve occupational hazards. However, the inverse relationship (between certain occupations and an increased incidence of vertigo or dizziness) has been scarcely studied. The objective of this work was to analyze the occupation of a group of patients with vertigo, compared to economically active general population, and to evaluate the prevalence of occupational noise and/or vibration-exposure in both groups. Methods: A cross-sectional, observational, case-control study was carried out including 461 patients (220: Meniere’s disease; 73: vestibular migraine; 28: vestibular neuritis; 140: BPPV) (310 women and 151 men). These patients were compared to a control group from the general population, obtained from 6th EWCS-Spain (2015). Possible differences regarding sex, age, occupation, exposure to noise, and exposure to mechanical vibrations were analyzed. Results: Differences in distribution of occupations between patients with vertigo and general population were observed (Chi-square, p=6.142 e-30). Patients with vertigo were significantly more exposed to noise (p=8.19 e-12; OR=2,127, CI95% (1.720;2.630)) and vibrations (p=1.11 e-12; OR=2.288, CI95% (1.835;2.853)) than the control group. These differences were observed both between men and women. Conclusions: A relationship between occupational exposure to noise and/or vibrations and the presence of vertigo was observed. Protective and preventive measures could help prevent the occurrence of some diseases involving vertigo.

Here are given tight probabilistic inequalities that provide nearly best estimates for the Csiszar's f-divergence. These use the right and left psi -Hilfer fractional derivatives of the directing function f. Csiszar's f- divergence or the so called Csiszar's discrimination is used as a measure of dependence between two random variables which is a very essential aspect of stochastics, we apply our results there. The Csiszar's discrimination is the most important and general measure for the comparison between two probability measures. We give also other applications.

Revealing the spatial distribution mechanism of the coupling effect between soil water and salt is essential for managing saline-alkali farmland. This study utilized the multifractal method to analyze soil water and salt under varying water content levels in arid saline-alkali farmland. Soil samples were collected on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after a rainfall event. The findings showed that a significant decrease in soil water content, contrasting with an increase in soil salt content throughout the soil layers post-rainfall. As water content decreased, the spatial variability of soil water initially increased from S1-3 and then decreased, while the spatial variability of soil salt decreased. The spatial distribution between soil water and salt exhibited a high correlation at S3-4 (with relative water content of soil ranging from 0.52 to 0.75) due to their coupling effect. However, soil salt was unevenly leached by rainfall at high water content levels (S1-2) and precipitated at low water content levels (S5), resulting in low spatial variability correlations between soil water and salt. This study elucidated the coupling process of soil water and salt, identifying their spatiotemporal distribution mechanism in dryland agricultural areas.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Although prognosis continually improved along years, a significant proportion of patients still relapse from the disease due to leukemia resistance to therapy. Methotrexate (MTX), a folic acid antagonist, is a chemotherapy agent commonly used against ALL and a immune-system suppressant for rheumatoid arthritis, that presents multiple and complex mechanisms of action and resistance. Previous studies have shown that MTX modulates the nuclear factor kappa B (NF-κB) pathway, an important family of transcription factors involved in inflammation, immunity, cell survival, and proliferation, frequently hyperactivated in ALL. Using gene set enrichment analysis (GSEA) on publicly available gene expression data from 161 newly diagnosed pediatric ALL patients, we found “TNF-α signaling pathway” to be the most enriched Cancer Hallmark in MTX poor responder patients. Transcriptomic analysis in a panel of ALL cell lines (6 BCP-ALL and 7 T-ALL) also identified the same pathway as differentially enriched among MTX resistant cell lines, as well as in slowly dividing cells. To better understand the crosstalk between NF-κB activity and MTX resistance, we genetically modified the cell lines to express luciferase under a NF-κB biding site promoter. We observed that the fold change in NF-κB activity triggered by TNF-α (but not MTX) treatment correlated with MTX resistance and proliferation across the lines. At the individual gene level, NFKB1 expression was directly associated with a poorer clinical response to MTX, and with both an increased TNF-α-triggered NF-κB activation and MTX resistance in the cell lines. Despite these results, pharmacological inhibition (with BAY 11-7082 and parthenolide) or stimulation (with exogenous TNF-α supplementation) of the NF-κB pathway did not alter MTX resistance of the cell lines significantly, evidencing a complex interplay between MTX and NF-κB in ALL.

This paper introduces the spatial component in cross-section econometric estimations and specifically, the spatial dependence effect inherent in some of the variables involved in the modelling process. First, the spatial structure of the data from thematic maps is observed and Moran's spatial autocorrelation indicators are presented. Subsequently, the spatial weights matrix is built under different specifications. Finally, several modelling specification strategies are shown and the interpretation of the estimated coefficients. The theoretical concepts are illustrated with examples and their corresponding R software codes. This code and databases are available in a freely accessible repository in the BE2SHARE-EUDAT platform so that they can be easily reproduced.

Finding the proper entropy functional associated with the inelastic Boltzmann equation for a granular gas is a yet unsolved challenge. The original H-theorem hypotheses do not fit here and the H-functional presents some additional measure problems that are solved by the Kullback–Leibler divergence (KLD) of a reference velocity distribution function from the actual distribution. The right choice of the reference distribution in the KLD is crucial for the latter to qualify or not as a Lyapunov functional, the “homogeneous cooling state” (HCS) distribution of the freely cooling system being a potential candidate. Due to the lack of a formal proof, the aim of this work is to support this conjecture aided by molecular dynamics simulations of inelastic hard disks and spheres in a wide range of values for the coefficient of restitution (α). Our results reject the Maxwellian distribution as a possible reference, whereas reinforce the HCS one. Moreover, the KLD is used to measure the amount of information lost on using the former rather than the latter, and reveals a nonmonotonic dependence with α. Additionally, a Maxwell-demon-like velocity-inversion experiment highlights the microscopic irreversibility of the granular gas dynamics.

Being able to forecast events is of great importance in many fields, from brain behavior to earthquakes or stock markets. Because each dynamical system has intrinsic features, different statistical tools have to be used for each system. Here we study the time series of the output intensity of a fiber laser with an ordinal patterns analysis, and we look for temporal correlations in order to statistically forecast the most intense events. We set two thresholds, a low one and a high one, to distinguish between low intensity versus high intensity events. We find that when the time series is performing events below the low threshold it shows some preferred temporal patterns before performing events above a high threshold.

This research article presents the integration of participatory modeling and system dynamics as a novel methodology for the consolidation of social dynamic models for the subsequent evaluation and prioritization of green projects in Colombian post-conflict communities. In the first instance, through participatory work carried out along with the community, it was possible to identify, evaluate and systematize citizen factors in relation to the problems and needs of the region. Second, based on the results obtained, to calibrate a simulation model based on system dynamics that facilitates decision making with regard to the evaluation of green projects. The proposed methodology leads to the conclusion that, with the participation of the community and with a model based on the dynamics of variables such as supply and demand for natural resources of water and land, it is possible to warn decision makers about the variables that can lead to the maximization of investments and thus prioritize and select the most appropriate environmental, social or economic initiatives, that certainly meet the needs or expectations of the involved community. In the future, the model could be used to facilitate the management, administration and control of water and land resources by creating alerts called reserve margins.

In bone tissue engineering, ceramics have been the choice due to their excellent biological properties. But the paradigm changed with the discovery of bioactive glasses (BGs) in 1969 by Larry Hench and co-workers, due to their ability to bond to living tissues through the formation of an interfacial bone-like hydroxyapatite layer when the bioglass was put in contact with biological fluids in vivo. Among a number of tested compositions, the one exhibiting the highest bioactivity index is the well-known trademarked 45S5 Bioglass®. The topic received increasing attention particularly after 1985 when this material entered in the market of biomedical devices, inspiring many other investigations aiming at further exploring the in vitro and in vivo performances of this BG, or developing other related BG compositions. The research efforts gradually revealed a number of shortcomings of 45S5 Bioglass®, mostly derived from its high sodium content, initially intended to decrease the melting temperature and accelerating the degradation of the silicate network over time. But the extensive release of sodium from 45S5 Bioglass® in the biological fluids creates a high pH cytotoxic environment. Other serious drawbacks include a fast degradation rate, and a poor sintering ability, which hinders the reliable fabrication of porous scaffolds. Therefore, sol-gel was regarded as an attractive alternative to prepare alkali-free BG compositions. The process uses inorganic and/or organic precursors, which undergo hydrolysis and condensation at room-temperature, being less costly. When properly conducted, the sol-gel process might result in amorphous structures with all the components intimately mixed at the atomic scale. Moreover, developing new better performing materials for bone tissue engineering is a growing concern, as the ageing of the world’s population leads to lower bone density and osteoporosis. This work describes the sol-gel synthesis of a novel quaternary silicate-based BG with the composition 60 SiO2 – 34 CaO – 4 MgO – 2 P2O5 (mol%) was prepared using acidified distilled water as single solvent. By controlling the kinetics of the hydrolysis and condensation steps, an amorphous glass structure could be obtained. The results of XRD of samples calcined within the temperature range from 600-900 ºC demonstrated that amorphous nature was maintained until 800 ºC, followed by partial crystallization at 900 ºC. The specific surface area, an important factor in osteoconduction, was also evaluated over different temperatures, ranging from 160.6 ± 0.8 m2/g at 600 ºC down to 2.2 ± 0.1 m2/g at 900 ºC, being accompanied consistent changes in average pore size and agreeing pore size distribution. The immersion of the BG particles in simulated body fluid (SBF) led to the formation of an extensive apatite layer on its surface. These overall results indicate the proposed material is very promising for biomedical applications in bone regeneration and tissue engineering.

New proposals for the equation of state of four- and five-dimensional hard-hypersphere mixtures in terms of the equation of state of the corresponding monocomponent hard-hypersphere fluid are introduced. Such proposals (which are constructed in such a way so as to yield the exact third virial coefficient) extend, on the one hand, recent similar formulations for hard-disk and (three-dimensional) hard-sphere mixtures and, on the other hand, two of our previous proposals also linking the mixture equation of state and the one of the monocomponent fluid but unable to reproduce the exact third virial coefficient. The old and new proposals are tested by comparison with published molecular dynamics and Monte Carlo simulation results and their relative merit is evaluated.

The hydrocarbon generation potential of Chia Gara strata and their genetic link with produced oils from the Zagros basin are still not comprehensively investigated. Forty-seven rock samples from the Tithonian–Berriasian interval were subjected to geochemical analyses to infer organic matter enrichment, hydrocarbon potential, thermal maturity, and timing for hydrocarbon generation/expulsion and their implications regarding upcoming petroleum explorations in the Zagros basin. The results showed that the Chia Gara rock samples have fair to very-good generation potential, as confirmed by higher total organic carbon (TOC=0.68–3.95 wt%) and Rock-Eval (S1+S2=3.37–8.52 mg HC/g rock). The hydrogen index (HI=171–462) and Rock-Eval Tmax over 430 °C support the presence of Types II and mixed Types II/III kerogen. These results confirm the high generation potential of the Chia Gara Formation in the study region. 1D basin models of the KK–109 well show that over 55% of kerogens were converted into oil in the Cretaceous (77–67 Ma). Expulsion started from the Miocene until now (22–0 Ma), consistent with 0.71–0.80 of modeled Easy%Ro and 55–80 %TR. Consequently, this project confirms the potential oil expulsion from the Chia Gara Formation, which can be a resource for upcoming hydrocarbon investigation in the Zagros basin, Iraq.

Dental polymers are often advertised and selected for use in restorations based upon the flexural strength of prefabricated discs, which may not accurately reflect their performance in dental applications. The objectives of this study were, therefore, to determine whether the three-point bending (3PB) test for flexural strength would be predictive of the “crunch-the-crown” CTC test for the failure load. Three brands of polymers (Trilor, Juvora, and Pekkton) were fabricated into rectangular bars and fully contoured crowns (10 specimens of each polymer brand, 30 specimens of each shape). Bars were tested in 3PB to determine flexural strength, and crowns were CTC tested to determine failure load after luting to resin abutments. Statistical significance was evaluated by one-way ANOVA ( = 0.05) and Pearson’s correlation coefficient. The fracture mechanisms were characterized by scanning electron microscopy (SEM). There were significant differences (p < 0.05) in the mean crown failure loads (Trilor [7,033 N] > Juvora [5,217 N] > Pekkton [3,023 N]) and mean flexural strengths of the bars (Trilor [468 MPa] > Juvora [197 MPa] = Pekkton [192 MPa]). There were no correlations between flexural strength and failure load. The mode of crown fracture was different between the polymers, and included deformation (Juvora), ductile-to-brittle fracture (Pekkton), and a combination of cracks and deformation (Trilor). The flexural strength was not correlated with the corresponding crown failure load. Dental practitioners should not rely on the value of flexural strength obtained from the three-point bending test, as advertised from the manufacturer, to predict the performance of polymeric crowns.

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

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

Application of protocols without parameter standardization and rigorous controls has led manual therapy (MT) and other physiotherapy approaches to controversial outcomes. Thus, there is an urgency to carefully define standard protocols that elevate physiotherapy treatments to rigorous scientific demands. One way this can be achieved is by studying gene expression and additional physiological changes that associate to particular, parameter-controlled, treatments in animal models and translating this knowledge to properly design objective, quantitatively-monitored clinical trials. Here, we propose a Molecular Physiotherapy Approach (MPTA), requiring multidisciplinary teams, to uncover the scientific reasons behind the numerous reports of MT that historically attribute benefits to these treatments. The review focuses in the identification of MT-induced physiological and molecular responses that could be used for the treatment of fibromyalgia (FM) and CFS/ME. The systemic effect associated to mechanical-load responses is considered of particular relevance as it suggests that defined, low-pain areas could be selected for treatments with overall benefits, an aspect that might result essential to treat FM. Additionally, MT can provide muscle conditioning to sedentary patients without demanding strenuous physical effort, detrimental for CFS/ME patients, placing MT as a real option for integrative medicine programs to treat FM and CFS/ME.

Abstract: Qatar and other Gulf States have a diverse range of marine vegetation that is adapted to the stressful environmental conditions of seawater. The industrial wastewater produced by oil and gas activities adds further detrimental conditions for marine aquatic photosynthetic organ-isms on the Qatari coastlines. Thus, these organisms experience severe stress from both seawater and industrial wastewater. This review discusses the biodiversity in seawater around Qatar, as well as remediation methods and metabolic pathways to reduce the negative impacts of heavy metals and petroleum hydrocarbons produced during these activities. These methods include phyto-stabilization phyto-accumulation, phyto-volatilization, and phyto-degradation. Phy-to-degradation in particular is discussed in detail, including metabolic pathways such as alkane and aromatic-compound degradation pathways. The role of microorganisms that are adjacent to or associated with these aquatic marine organisms is discussed, including rhizosphere biodeg-radation. In this type of biodegradation, exudates are released by plant roots and supply nutrients to microorganisms in the rhizosphere, which enhances their ability to degrade organic pollutants. Special attention is paid to mangrove forests and their roles in remediating shores polluted by industrial wastewater. Seagrasses (Halodule uninervis, Halophila ovalis, and Thalassia hemprichii) and seaweeds (Chlorophyta, Phaeophyta, and Rhodophyta) around the peninsula of Qatar are also discussed.

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

A Friedmann-Lemaitre-Robertson-Walker space-time model with all curvatures k=0,±1 is explored in f(R,T) gravity. The solutions are obtained via the parametrization of the scale factor that leads to a model transiting from a decelerated universe to an accelerating one. The physical features of the model are discussed and analysed.

We analyze the behavior of relativistic spherical objects within the context of modified $f(R,T)$ gravity considering Tolman VI spacetime, where gravitational lagrangian is a function of Ricci scalar(R) and trace of energy momentum tensor(T) i.e,$ f(R,T)= R+ 2\beta T$, for some arbitrary constant $\beta$. For developing our model, we have chosen $\pounds_{m} = -p$, where $ \pounds_{m}$ represents matter lagrangian. For this investigation, we have chosen three compact stars namely PSR J1614-2230 [Mass=(1.97$\pm$ 0.4)M$_\odot$; Radius= 9.69$_{-0.02} ^{+0.02}$ Km] ,Vela X-1 [Mass=(1.77$\pm$ 0.08)M$_\odot$; Radius= 9.560$_{-0.08} ^{+0.08}$ Km] and 4U 1538-52 [Mass=(9.69)M$_\odot$; Radius= 1.97 Km]. In this theory the equation of pressure isotropy is identical to standard Einstein's theory. So all known metric potential solving Einstein's equations are also valid here. In this paper, we have investigated the effort of coupling parameter ($\beta$) on the local matter distribution. Sound of speed and adiabatic index are higher with grater values of $\beta$ while on contrary mass function and gravitational redshift are lower with higher values of $\beta$ . For supporting the theoretical results, graphical representation are also employed to analyze the physical viability of the compact stars.

Symmetry-breaking is a phenomenon that is observed in various contexts, from the early universe to complex organisms, and is considered a key puzzle in understanding the emergence of life. The presence of enantiomeric amino acids and proteins highlights its critical role. However, the origin of symmetry-breaking has yet to be comprehensively explained, particularly from an energetic standpoint. This article explores a novel approach by considering energy dissipation, specifically lost free energy, as a crucial factor in elucidating symmetry-breaking. Through a thorough thermodynamic analysis applicable to enantiomeric systems at various scales, from elementary particles to aggregated matter like crystals, we present experimental findings that establish a direct correlation between non-equilibrium free energy and energy dissipation during formation processes. Results emphasize the pivotal role of energy dissipation not only as an outcome but as the trigger for symmetry-breaking. This insight suggests that understanding the origins of complex systems, from cells to living beings and the universe itself, requires a lens focused on non-equilibrium processes, ultimately facilitating the formation of non-racemic systems.

Baeyer-Villiger monoxygenases (BVMOs) are flavin-dependant oxidative enzymes capable to catalyse the insertion of an oxygen atom between a carbonylic Csp2 and the Csp3 at the alpha position, therefore transforming linear and cyclic ketones into esters and lactones. These enzymes are dependent on nicotinamides (NAD(P)H) for the flavin reduction and subsequent reaction with molecular oxygen to furnish peroxyflavin, the ultimate responsible for the substrate oxidation. BVMOs can be included in cascade reactions, coupled to other redox enzymes such as alcohol dehydrogenases (ADHs) or ene-reductases (EREDs), so that the direct conversion of alcohols or α,β-unsaturated carbonylic compounds to the corresponding esters can be achieved. This way, it is possible to develop smart synthetic strategies with a convenient cofactor recycling, both using whole cells (native or genetically engineered) as well as isolated enzymes, via multi-steps reaction through sequential or parallel methodologies. Some examples will be commented dealing with these biotransformations, highlighting the advantages of the coupling of enzymatic steps.

In recent decades, particularly intense changes have occurred in Spanish urban areas. This is the result of demographic and urbanizing transformations that have led to a change in the city model. The predominance of compact forms has been replaced by the growing prominence of urban sprawl. Structures are now more extensive, characterized, in turn, by fragmentation and notable consumption of land in the peripheries. In medium-sized cities, the municipalities bordering the central cities have concentrated the processes of suburbanization and periurbanization. This paper addresses the process of change for 34 cities and their urban areas located in inland Spain. A proposal is made for the delimitation and characterization of urban areas, taking the municipality as the unit of analysis. At the methodological level, six variables are used, analyzed by means of multicriteria statistical techniques combined with the use of GIS tools. An Urban Transformation Index (ITU) has been developed that synthesizes urbanizing, demographic and socioeconomic dynamics. In the territorial area, the 20-minute isochrone is used as a reference. In the temporal domain, the period of analysis addresses the events of the first two decades of the twenty-first century.

The administration of regional neuraxial analgesia for pain relief during labor is widely recognized as a safe and effective method involving medication delivery into the epidural or subarachnoid space in the lower back. This study proposes an innovative semantic image segmentation methodology emphasizing enhanced interpretability using convolutional Random Fourier Features and layer-wise weighted class-activation maps tailored explicitly for foot segmentation in regional analgesia monitoring. Namely, our contribution is twofold: i) a novel Random Fourier Features layer is introduced to deal with image data to enhance three well-known architectures (FCN, UNet, and ResUNet); ii) three novel quantitive measures are presented to evaluate the interpretability of a given deep learning model devoted to segmentation tasks. Our approach is rigorously evaluated on a demanding dataset of foot thermal images from pregnant women who received epidural anesthesia. Its small size and considerable variability characterize the dataset. Our validation results demonstrate that the proposed methodology not only achieves competitive foot segmentation performance but also significantly enhances the explainability of the process, rendering it well-suited for applications such as epidural insertion during labor.

In this work, we introduce a new concepts for $\alpha$-type $F$-Suzuki contraction and $\alpha$-type $F$-weak-Suzuki contraction in the context of $b$-metric spaces. Compared to the $\alpha$-type $F$-contraction and $F$-Suzuki contraction mappings, these contractions are essentially weaker. For these type of contraction mappings, sufficient conditions are established for the fixed point's existence and uniqueness in $b$-metric spaces. As a result, the findings encompass several generalizations. To show the usability of our obtained results, we provide a supportive example and an application to a non-linear differential equation with fractional order.

In this paper, we introduce the application of Type-I fuzzy inference systems (FIS) as an alternative to improve the prioritization in the FMECA analysis applied in cyber-power grids. Classical FMECA assesses the risk level through the Risk Priority Number (RPN). The multiplication between three integer numbers computes this, called risk factors, representing the severity, occurrence, and detectability of each failure mode and are defined by a team of experts. The RPN does not consider any relative importance between the risk factors and may not necessarily represent the real risk perception of the FMECA team members, usually expressed by natural language; this is the main FMECA shortcoming criticized in the literature. Our approach considers fuzzy variables defined by FMECA experts to represent the uncertainty associated with the human language and a rule base consisting of 125 fuzzy rules to represent the risk perception of the experts. To test our approach, we select a cyber-power grid previously analyzed by the authors using the classical FMECA. The results reveal our proposed fuzzy approach as promissory to represent the uncertainty associated with expert knowledge and to perform an accurate prioritization of failure modes in the context of electrical power systems.

This paper presents a methodology to detect the erosion and progradation effects in the Atrato river delta, located in the Gulf of Urabá in Colombia using SAR (Synthetic Aperture Radar) data. Other authors have studied this area by using optical images, encountering difficulties given the persistent presence of clouds in this region. SAR imagery is rescaled, despeckled, composed, classified, registered and processed to obtain a heatmap that shows the overall changes during eight years (2016–2023) in one single image. Since this technology uses microwave active signals, the presence of clouds and other environmental phenomena was not a problem, and all the images from the selected dates could be processed and analyzed. Also, detection of the dynamic processes was obtained for every period considered in this study with respect to the previous one in time, calculating areas and detecting the regions subject to the erosion and progradation processes. The multitemporal analysis performed found that the newly created mouth is the most active area for these processes, coinciding with other studies. A comparison of these findings with the Oceanic Niño Index (ONI) showed a relative delayed coupling to the erosion process and a coupling of progradation with dry and wet seasons.

Objective: To investigate whether the relationships between acute care occupational therapy (OT) and physical therapy (PT) utilization and community discharge are moderated by functional or physical performance at discharge among individuals hospitalized with traumatic brain injury (TBI). Setting: 14 acute care hospitals in the state of Colorado. Participants: We studied 5,599 adults hospitalized with TBI between June 2018 and April 2021. Design: In a secondary analysis of de-identified electronic health record (EHR) data, multivariable moderation logistic regression models were performed to calculate odds ratios (ORs) for the likelihood of community discharge among patients who utilized OT/PT services. Main Measures: Functional (activities of daily living [ADL]) and physical (mobility) performance at discharge, OT and PT utilization, and community discharge status. Results: Overall, 67% of patients discharged to the community. The mean age of the sample was 55 years (SD = 20 years). Most participants were male (64%) and non-Hispanic white (72%). Mean hospital length of stay was 6 days (SD = 6 days). Both OT and PT utilization (OT: OR= 1.21, 95% CI [1.11, 1.33]; PT: OR= 1.22, 95% CI [1.14, 1.30]) and discharge ADL and mobility scores (ADL: OR= 1.34, 95% CI [1.30, 1.39]; mobility: OR= 1.38, 95% CI [1.33, 1.42]) were significantly and positively associated with community discharge. The OT and PT utilization-by-discharge ADL and mobility interaction terms yielded slightly negative, but statistically significant moderation effects in both models (ORs= 0.99, 95% CIs [0.98, 1.00]); indicating the magnitude of the OT and PT utilization effect diminished as ADL and mobility scores increased. Several sociodemographic characteristics and clinical factors were also independently associated with community discharge in both models (p-values

This study investigates the intricate relationship between Venezuelan migration and urban growth in Colombia from 2018 to 2021. The study employs remote sensing data and social network metrics to uncover migration patterns and their impact on urban expansion. The methodology consists of three stages. Firstly, nighttime satellite imagery is used to analyze year-over-year urban growth in Colombia. Secondly, social network data estimates Venezuelan migration, overcoming challenges of underreporting and informal border crossings. Lastly, an econometric analysis explores the quantitative link between Venezuelan migration and urban growth, integrating socioeconomic variables to address endogeneity. The findings reveal the complex interplay of Venezuelan migration, socioeconomic factors, and urban growth. The study outlines remote sensing analysis, introducing the Anthropogenic Footprint Expansion Index (AFEI) to quantify urban growth. Facebook API data estimates migration trends and explores socioeconomic impacts on urban expansion. The analysis uncovers migration, poverty, aging, and urban population proportion as key factors affecting Colombia's urban landscape. Furthermore, the research underscores how Venezuelan migration affected short-term urban expansion pre- and post-COVID-19. Migration had a notable effect before the pandemic, but this influence waned afterward. The study highlights migration's short-term nature and emphasizes age demographics' role in medium-term dynamics.

Decoherence with recurrences appear in the dynamics of the one-body density matrix of an $F = 1$ spinor Bose-Einstein condensate, initially prepared in coherent states, in the presence of an external uniform magnetic field and within the single mode approximation. The phenomenon emerges as a many-body effect of the interplay of the quadratic Zeeman effect, that breaks the rotational symmetry, and the spin-spin interactions. By performing full quantum diagonalizations very accurate time evolution of large condensates are analyzed, leading to heuristic analytic expressions for the time dependence of the density matrix, in the weak and strong interacting regimes. We are able to find accurate analytical expressions for both the decoherence and the recurrence times, in terms of the number of atoms and strength parameters, that show remarkable differences depending on the strength of the spin-spin interactions. We discuss the nature of these limits in the light of the thermodynamic limit.

The advances mobile communications has seen in recent years has rendered the radio spectrum a limited and, hence, an expensive resource. Therefore, technologies that support unlicensed access to spectrum are needed. Therefore, the adoption of novel modulation schemes becomes of utmost importance to obtain better spectral-localization and reduce the OOBE (\textit{Out of Band Emission}) inherent to OFDM (\textit{Orthogonal Frequency Division Multiplexing}) and, consequently, mitigating the interference between secondary (\textit{unlicensed}) and primary users. In this scenario, we assess the gain in the bit error probability using f-OFDM (\textit{filtered-OFDM}) in MIMO systems, both used in the 5G RANGE project.

In this paper, we classify the function space of all real-valued functions on R denoted as F(R,R) into 28 distinct blocks. Each block contains elements that share common features in terms of the cardinality of their sets of continuity and differentiability. Alongside this classification, we introduce the concept of the Connection, which reveals a special relationship structure between four well-known real-valued functions in real analysis: the Cantor function, Dirichlet function, the Thomae function, and the Weierstrass function. Despite the significance of this field, several perspectives remain unexplored.

A locally-rotationally-symmetric Bianchi-I model filled with strange quark matter (SQM) is explored in f(R, T) gravity. We take f(R, T) = R + 2 f(T) = R + 2λT, where R is the Ricci scalar, T is the trace of energy-momentum tensor and λ is an arbitrary constant. Exact solutions are obtained by assuming that the expansion scalar is proportional to the shear scalar. This yields a constant value for the deceleration parameter, q = 2, which corresponds to the decelerated phase of the universe. The model is found to be physically viable for λ < −1. SQM during early evolution mimics ultra-relativistic radiation whereas at late times, it behaves as dust, quintessence or even the cosmological constant depending on the value of λ. The effective matter acts as a stiff fluid irrespective of the matter content and of the f(R, T) terms. The model is shear free at late times but remains anisotropic throughout the evolution. In the absence of the f(R, T) terms, SQM accelerates the universe. In the specific case when SQM vanishes at late times, the effect of f(R, T) is to accelerate the universe. The model admits the possibility that SQM could be an alternative to dark energy.

We obtain exact solutions to the field equations for 5 dimensional LRS Bianchi type-I spacetime in $f(R,T)$ theory of gravity where specifically the following three cases are considered: (i) $f(R,T)=\mu(R+T)$, (ii) $f(R,T)=R \mu + R T \mu^2$ and (iii) $f(R,T)=R+\mu R^2+\mu T$ where $R$ and $T$ respectively the Ricci scalar and trace of the energy-momentum tensor. It is found that the equation of state (EOS) parameter $w$ is governed by the parameter $\mu$ involved in the $f(R,T)$ expressions. We fine-tune the parameter $\mu$ to obtain effect of phantom energy in the model, however we also restrict this parameter to obtain a stable model of the universe. It is noted that the model isotropizes at finite cosmic time.

In this work, we study the existence of strange star in the background of f(T,T) gravity in the Einstein spacetime geometry, where T is the torsion tensor and T is the trace of the energy-momentum tensor. The equations of motion are derived for anisotropic pressure within the spherically symmetric strange star. We explore the physical features like energy conditions, mass-radius relations, modified TOV equations, principal of causality, adiabatic index, redshift and stability analysis of our model. These features are realistic and appealing to further investigation of properties of compact objects in f(T,T) gravity as well as their observational signatures.

Keywords: Marine Coasts; Protected Areas; Defense and Conservation; Asbestos Cement Materials; Wastes; Contamination; Human Health Risk; Medical Geology.

heterocycles are particularly common moieties within marine natural products. Specifically, tetrahydrofuranyl rings are present in a variety of compounds which present complex structures and interesting biological activities. Focusing on terpenoids, a high number of tetrahydrofuran-containing metabolites have been isolated during the last decades. They show promising biological activities, making them potential leads for novel antibiotics, antikinetoplastid drugs, amoebicidal substances or anticancer drugs. Thus, they have attracted the attention of the synthetic community, and numerous approaches to their total syntheses have appeared. Here, we offer the reader an overview of marine-derived terpenoids and related compounds, with a special focus on their isolation, structure determination, biological profiles and total syntheses.

French Guiana, located in the Guiana Shield, is a natural reservoir for many zoonotic pathogens that are of considerable medical or veterinary importance. Until now, there are few data available on the description of parasites circulating in this area, especially on protozoan belonging to the phy-lum Apicomplexa; conversely, the neighbouring countries describe a high parasitic prevalence in animals and humans. Epidemiological surveillance is necessary, as new potentially virulent strains may emerge from these forest ecosystems, such as Amazonian toxoplasmosis. However, there is no standard tool for detecting protozoa in wildlife. In this study, we developed Meat-Borne-Parasite, a high-throughput meta-barcoding workflow for detecting Apicomplexa based on Oxford Nanopore Technologies sequencing platform using the 18S gene of fourteen Apicomplexa-positive samples collected in French Guiana. Sequencing reads were then analysed with MetONTIIME pipeline. Thanks to a scoring rule, we were able to classify as Apicom-plexa-positive 10 samples out of 14 and reveal the presence of co-carriages. The same samples were also sequenced with Illumina platform, for validation purposes. On samples identified as Apicomplexa-positive by both platforms, a strong positive correlation at up to genus level was reported. Overall, the presented workflow represents a reliable method for Apicomplexa detec-tion, which may pave the way for more comprehensive biomonitoring of zoonotic pathogens.

Landscape changes based on spectral responses allow showing plant cover changes through diversity, composition, and ecological connectivity. The spatial and temporal vegetation dynamics of the Bijagual Massif from 1986 to 2021 were analyzed as a measure of ecological integrity, conservation, and territory. The covers identified were high open forest (Hof), dense grassland of non-wooded mainland (Dgnm), a mosaic of pastures and crops (Mpc), lagoons (Lag), and bare and degraded lands (Bdl). The Bijagual Massif has 8,574.1 ha. In 1986, Dgnm occupied 42.6% of the total area, followed by Mpc (32.8%) and Hof (24.5%); by 2000, Mpc and Hof increased (43.7 and 28.1%, respectively), while Dgnm decreased (28%); by 2021, Dgnm was restricted to the northeastern zone and continued to decrease (25.2%), Mpc occupied 52.9%, Hof 21.7% and Bdl 0.1%. Of the three fractions of the connectivity probability index, only dPCintra and dPCflux contribute to ecological connectivity. Hof and Dgnm show patches with biota habitat quality and availability. Between 1986 and 2021, Dgnm lost 1,489 ha (41%) and Hof 239.5 ha (11%). Mpc replaced various covers (1,722.2 ha; 38%) in 2021. Bijagual has a valuable biodiversity potential limited by Mpc. Territorial planning and sustainable agroecological and ecotourism proposals are required due to the context of the ecosystems.

This research was carried out with the objective of analyzing the principles of social and solidarity economy in the community funds of the rural sector of Pichincha, Ecuador. Small organizations promote microcredits for local, social and economic development, representing an alternative to those managed by traditional banks. The research was descriptive, non-experimental field research. The population analyzed consisted of 220 community funds, and the size of the representative sample was 49 community organizations that practice solidarity finance. The data were collected through online questionnaires using a Likert scale, and the validity of this approach was judged by experts; the reliability of the instrument obtained was 0.95 using the Cronbach’s alpha method. The results highlight that in these organizations, the following traits prevail: associativity, self-management and organization. However, autonomy and solidarity have a negative valuation, which shows that strategies must be rethought to achieve the empowerment of the financial service. This will allow them to be sustainable and to expand with more benefits that promulgate financial activity and promote structures in rural community networks that promote local development and strengthen deficient principles as a basis for generating a greater benefit to the partners.

The purpose of this research has been to provide information about the psychological effects of confinement forced by a prolonged quarantine in a suitable adult sample of 596 Bolivians of both sexes. It was sought to explore the perceptions of the participants about their own emotional state: fears, anxieties, depressions, while they were in isolation to reduce the probability of contagion of COVID 19. Additionally, we were interested in verifying the modulating effects of resilience and self-efficacy on such emotional states. The results indicated, in the same direction of similar studies, significant relationships between high perceived loneliness, high levels of stress and anxiety, with relatively high levels of depression. Likewise, it was clear that stress, perceived loneliness, and anxiety are predictors of depression among those in conditions of forced isolation. Finally, it was found that both resilience and self-efficacy exert a clear moderating effect by attenuating the relationships of perceived loneliness and anxiety, on depression.

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

Zinc protection of galvanized steel is initially dissolved in alkaline solutions. However, passive layer is formed over time which protects the steel from corrosion. The behavior of galvanized steel exposed to strong alkaline solutions (pH values of 12.7) with a fixed concentration of sulfate ion of 0.04M is studied. Electrochemical measurement techniques such as corrosion potential, linear polarization resistance and electrochemical impedance spectroscopy are used. Synergistic effect of sulfate ion is also studied together with other anions such as chloride Cl- or bicarbonate ion HCO3- and with other cations such as calcium Ca2+, ammonium NH4+ and magnesium Mg2+. Presence of sulfate ions can depassivate the steel, leading to corrosion density of 0.3 µA/cm2 at the end of the test. The presence of other ions in the solution increases this effect. The increase in corrosion density caused by cations and anions responds to the following order (greater to lesser influence): NH4+&gt;Ca2+&gt;Mg2+ and HCO3- &gt;Cl- &gt;SO42-.

Small-cell lung cancer (SCLC) is a cancer with poor prognosis. For relapsed extensive-stage (ES) SCLC, second-line treatment options are scarce. Topotecan was the only approved treatment in this setting until 2020. Since topotecan induces significant toxicities, alternative off-label regimens are being used. This study evaluated real-world efficacy and safety of Paclitaxel Gemcitabine chemotherapy in patients with relapsed ES-SCLC. We retrospectively reviewed data from all consecutive patients with relapsed ES-SCLC who received Paclitaxel Gemcitabine chemotherapy from september 2008 to january 2022 in two centers. Patient characteristics (n=188) were: PS≥2: 24.5%; brain metastasis: 42%; platinum-sensitive disease: 41%. Patients received Paclitaxel Gemcitabine as second- (77%) third (18%) or fourth (6%) line of therapy. Median progression-free and overall survival were 2.1 (95CI 1.8–2.4) and 3.8 (95CI 3.3–4.8) months in the overall population, respectively, with 17% response rate (RR) and 28% disease-control rate. PS, history of brain radiation, platinum-sensitive disease, liver, and adrenal gland metastasis were associated with longer survival in univariate analysis. PS was the only prognostic factor in multivariate analysis, with 21% RR and 4.1 months median DOR in PS 0-1 patients. Paclitaxel Gemcitabine chemotherapy may represent a treatment option in PS0-1 relapsed SCLC.

Background and Objectives:: Hip osteoarthritis is the main cause physical disability, also has a serious impact on the efficiency and independence of older people. The aim of the study was to analyze the relationship between hip osteoarthritis and the risk of sarcopenia. Our main hypothesis was whether the risk of sarcopenia, as measured by the SARC F questionnaire , is related to the physical fitness of older people with hip osteoarthritis. Materials and Methods: The study was conducted with the participation of 177 people of aged 65 or more, diagnosed hip osteoarthritis. The subjects were assessed using the SARC F questionnaire, the Short Physical Performance Battery (SPPB) and Timed Up and Go (TUG) test. The subjects were divided into two groups depending on the result they obtained in the SARC F questionnaire (group 1- SARC F &lt;4, group 2 - SARC F ≥ 4). Results: There was a significant correlation between the results in the SARC F and the results of the TUG (p&lt;0.001) and the SPPB test, both the SPPB total score (p&lt;0.001)and its elements: SBBP chair stand test (p&lt;0.001), SPPB balance test (p&lt;0.001), SPPB gait speed test (p&lt;0.001). Logistic regression of the SPPB and TUG predictors showed that in SARC F more than 4 predicted worse SPPB and TUG outcomes. In the SARC group, F above 4 increases the odds of poorer scores in SPPB OR=1.097; CI 95% 1.053-1.146 and TUG, OR=1.096; CI 95% 1.104-1.266. Conclusion: The study showed that the results obtained in the SARC F questionnaire correlate with the possibilities of physical functioning in patients with hip osteoarthritis SARC F is an inexpensive method that can be used to assess the risk of sarcopenia. Healthcare professionals, especially in primary care, should consider assessing the risk of sarcopenia especially in people with hip osteoarthritis.

In this study, the degradable superhydrophobic Mg/P/Z/F/H (magnesi-um/poly(-caprolactone)/zinc oxide/1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFDTES)/ heating process) composite materials were prepared through one-step method for enhancing the corrosion resistance of AZ91D magnesium alloys. Electrochemical measurements showed that Mg/P/Z/F/H materials significantly improved the corrosion resistance of magnesium alloys in 3.5 wt.% NaCl. The self-cleaning, adhesion and stability tests suggested that Mg/P/Z/F/H composite materials had well self-cleaning properties, good adhesion strength and stability in wet atmosphere.

Nitric oxide (NO) is involved in physiological processes, including vasodilatation, wound healing and antibacterial activities. As NO is a free radical, designing drugs to generate therapeutic amounts of NO in controlled spatial and time manners is still a challenge. In this study, the NO donor S-nitrosoglutathione (GSNO) was incorporated into the thermoresponsive Pluronic F-127 (PL) - chitosan (CS) hydrogel, with an easy and economically feasible methodology. CS is a polysaccharide with known antimicrobial properties. Scanning electron microscopy, rheology and differential scanning calorimetry techniques were used for hydrogel characterization. The results demonstrated that the hydrogel has a smooth surface, thermoresponsive behavior and good mechanical stability. The kinetics of NO release and GSNO diffusion from GSNO-containing PL/CS hydrogel demonstrated a sustained NO/GSNO release, in concentrations suitable for biomedical applications. The GSNO-PL/CS hydrogel demonstrated a concentration-dependent toxicity to Vero cells, and antimicrobial activity to Pseudomonas aeruginosa (minimum inhibitory concentration and minimum bactericidal concentration values of 0.5 µg·mL^-1 of hydrogel, which corresponds to 1 mmol·L^-1 of GSNO). Interestingly, the concentration range in which the NO-releasing hydrogel demonstrated an antibacterial effect was not found to be toxic to the Vero mammalian cell. Thus, the GSNO-PL/CS hydrogel is a suitable biomaterial for topical NO delivery applications.

The semi-nonparametric (SNP) modeling of the return distribution has been proved to be a flexible and accurate methodology for portfolio risk management that allows two-step estimation of the dynamic conditional correlation (DCC) matrix. For this SNP-DCC model, we propose a stepwise procedure to compute pairwise conditional correlations under bivariate marginal SNP distributions, overcoming the curse of dimensionality. The procedure is compared to the assumption of Dynamic Equicorrelation (DECO), which is a parsimonious model when correlations among the assets are not significantly different but requires joint estimation of the multivariate SNP model. The risk assessment of both methodologies is tested for a portfolio on cryptocurrencies by implementing backtesting techniques and for different risk measures: Value-at-Risk, Expected Shortfall and Median Shortfall. The results support our proposal showing that the SNP-DCC model has better performance for a smaller confidence level than the SNP-DECO model, although both models perform similarly for higher confidence levels.

Petrosamine (1) – a colored pyridoacridine alkaloid from the Belizean sponge, Petrosia sp. that is also a potent inhibitor of acetylcholine esterase (AChE) – was investigated by spectroscopic and computational methods. Analysis of the petrosamine free energy landscapes, pKa and tautomerism revealed an accurate electronic depiction of the molecular structure of 1 as the di-keto form, with net charge of q = +1, rather than a dication (q = +2) under ambient conditions of isolation-purification. The pronounced solvatochromism (UV-vis) reported for 1, and related analogs, was investigated in detail and is best explained by charge delocalization and stabilization of the ground state (HOMO) of 1 rather than an equilibrium of competing tautomers. Refinement of the molecular structure of 1 by QM methods complements published computational docking studies to define the contact points in the enzyme active site that may improve design of new AChE inhibitors based on the pyridoacridine alkaloid molecular skeleton.

Predictive numerical models in the study of ground-borne vibrations generated by railway sys-tems have traditionally relied on the segmented approach of subsystems. In this approach, loads are individually applied, and the cumulative effect of rolling stock is obtained through superposi-tion. While this method serves to mitigate computational costs, it may not fully capture the com-plex interactions involved in ground-borne vibrations. Recent advancements in computational and software tools have enabled the development of more sophisticated vibrational pollution models. These advanced models encompass the entire dynamic system, from the rolling stock to the terrain, allowing for continuous simulations with a defined time step. Furthermore, the incorporation of computational contact tools between various ele-ments not only ensures temporal accuracy but also extends the analysis to the frequency domain. This paper explores the evolution of predictive numerical models in the context of ground-borne vibrations generated by trains on ballasted tracks. It highlights the shift from segmented models to continuous simulations, demonstrating the progressive advancement towards more comprehen-sive and accurate representations of railway-induced and generated vibrations in the track sur-roundings as an additional way of evaluate sustainability of infrastructures. In particular, this development of a numerical model from its inception aimed to expand upon ex-isting emission - prediction models by enriching the data with frequency-domain information. This approach has been driven by the aspiration to bridge the gap between numerical predictions and measured signals, striving for a higher level of accuracy in our obtained results. This model can predict the impact of a high-speed rail (HSR) vehicle passing on its own track. It possesses sufficient information in both the time and frequency domains to precisely characterize vibrations. This initiative marks a pivotal advancement, enabling us to more effectively capture the intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain, there's a heightened ca-pability to accurately characterize vibrations.

The oviparous blow fly Calliphora vicina has shown potential as a managed pollination species to support honeybee (Apis mellifera) usage in Australian horticulture. This blow fly species lays eggs onto carrion soon after death and the resultant larvae that hatch are necrophagous and feed on the decomposing tissues of the dead animal. Newly hatched larvae of this fly were provided with plant-based meals (soya bean and canola) and compared with animal-derived meatmeal to determine if plant-based meal could be used to mass rear this blow fly species. Both soyabean and canola meal media did not support the survival of any larvae through to adult eclosion. The addition of only 10% whole egg powder to the plant-based meals enabled survival to eclosion of 39% and 13% on soyabean and canola based medias respectively compared with 76% on animal-based meatmeal with 10% whole egg powder. Larvae fed livestock meatmeal with 10% whole dried egg powder had the fastest development to the pupal stage, the highest pupation rate, the heaviest pupae and the highest subsequent adult eclosion. This study concluded that the use of plant-based meals in the mass rearing of the blow fly C. vicina was neither viable, nor economically viable.

First, we examine how spin is treated in special relativity and the necessity of introducing spin supplementary conditions (SSC) and how they are related to the choice of a center-of-mass of a spinning particle. Next, we discuss quantum electrodynamics and the Foldy-Wouthuysen transformation which we note is a position operator identical to the Pryce-Newton-Wigner position operator. The classical version of the operators are shown to be essential for the treatment of classical relativistic particles in general relativity, of special interest being the case of binary systems (black holes/neutron stars) which emit gravitational radiation.

Solute carrier (SLC) proteins transport a wide range of substrates across biological membranes and more than 400 proteins are considered as SLCs based on its sequence. Despite it has important potential applications in drug development, the SLC superfamily is still understudied. Drosophila blot, an orphan SLC protein, regulates F-actin organization in the syncytial blastoderm and the Malpighian tubules. However, the molecular mechanism was unknown. In this study, we found Blot was localized at the furrow canal, the front of the invaginating membrane during cellularization process. Blot is required for maintaining proper morphology of furrow canal and cellularization process. By affinity purification and mass spectrometry we identified RhoGEF ELMO/DOCK complex was required for Blot-mediated F-actin organization and cellularization. Further analysis revealed that ELMO localization depends on Blot. Taken together, we propose Blot plays a role in F-actin organization as an upstream factor of ELMO by recruiting ELMO to the target membrane compartments.

Lemon oils are amongst the highest volume and most frequently traded of the flavour and fragrance essential oils. Citronellal and citral are considered the key components responsible for the lemon note with citral (neral + geranial) preferred. Of the myriad of sources of citral, the Australian myrtaceous tree, Backhousia citriodora, is considered superior. This review examines the history, natural occurrence, the cultivation, the taxonomy, the chemistry, the biological activity, the toxicology, standardisation and the commercialisation of Backhousia citriodora especially in relation to its essential oil.

The growing interest in Kv7.2/7.3 agonists originates from the involvement of these channels in several brain hyperexcitability disorders. In particular, Kv7.2/7.3 mutants have been clearly associated with epileptic encephalopathies (DEE) as well as with a spectrum of focal epilepsy disorders, often associated with developmental plateauing or regression. Nevertheless, there is a lack of available therapeutic options, considering that retigabine, the only molecule used in clinic as broad-spectrum Kv7 agonist, has been withdrawn from the market in the late 2016. This is why several efforts have been made both by both academia and industry in the search for suitable chemotypes acting as Kv7.2/7.3 agonists. In this context, in silico methods have played a major role, since the precise structures of different Kv7 homotetramers have been only recently disclosed. In the present review the computational methods used for the design of Kv.7.2/7.3 small molecule agonists and the underlying medicinal chemistry are discussed in the context of their biological and structure-function properties.

The residual multiparticle entropy (RMPE) of a fluid is defined as the difference, Δs, between the excess entropy per particle (relative to an ideal gas with the same temperature and density), s_ex, and the pair-correlation contribution, s₂. Thus, the RMPE represents the net contribution to s_ex due to spatial correlations involving three, four, or more particles. A heuristic “ordering” criterion identifies the vanishing of the RMPE as an underlying signature of an impending structural or thermodynamic transition of the system from a less ordered to a more spatially organized condition (freezing is a typical example). Regardless of this, the knowledge of the RMPE is important to assess the impact of non-pair multiparticle correlations on the entropy of the fluid. Recently, an accurate and simple proposal for the thermodynamic and structural properties of a hard-sphere fluid in fractional dimension 1 < d < 3 has been proposed [Santos, A.; López de Haro, M. Phys. Rev. E 2016, 93, 062126]. The aim of this work is to use this approach to evaluate the RMPE as a function of both d and the packing fraction ϕ. It is observed that, for any given dimensionality d, the RMPE takes negative values for small densities, reaches a negative minimum Δs_min at a packing fraction ϕ_min, and then rapidly increases, becoming positive beyond a certain packing fraction ϕ₀. Interestingly, while both ϕ_min and ϕ₀ monotonically decrease as dimensionality increases, the value of Δs_min exhibits a nonmonotonic behavior, reaching an absolute minimum at a fractional dimensionality d ≃ 2.38. A plot of the scaled RMPE Δs/|Δs_min| shows a quasiuniversal behavior in the region −0.14 ≲ ϕ − ϕ₀ ≲ 0.02.

Reliability assessment in traditional power distribution systems has played a key role in power system planning, design, and operation. Recently, new information and communication technologies have been introduced in power systems automation and asset management, making the distribution network even more complex. In order to achieve efficient energy management, the distribution grid has to adopt a new configuration and operational conditions that are changing the paradigm of the actual electrical system. Therefore, the emergence of the cyber-physical systems concept to face future energetic needs requires alternative approaches for evaluating the reliability of modern distribution systems, especially in the smart grids environment. In this paper, a reliability approach that makes use of failure modes of power and cyber network main components is proposed to evaluate risk analysis in smart electrical distribution systems. We introduce the application of Failure Modes and Effects Analysis (FMEA) method in future smart grid systems in order to establish the impact of different failure modes on their performance. A smart grid test system is defined and failure modes and their effects for both power and the cyber components are presented. Preventive maintenance tasks are proposed and systematized to minimize the impact of high-risk failures and increase reliability.

The development of electric aircrafts is becoming an important technology for achieving the goals set by the European Commission for the reduction of gases emissions by 2050 in the aeronautical transportation system. However, there is a gap between the values of specific power in commercial electric machines and the ones required for aeronautical applications. Therefore, the search for alternative materials and non-conventional designs is mandatory. One emergent solution is using superconducting machines and systems to overcome the current limits of conventional electrical machines. This work reviews the new hybrid and all-electric aircraft tendencies, complementing it with recent research on the design and development of high specific power superconducting machines. This includes the main topologies for hybrid and all-electric aircraft, with an overview of the ongoing worldwide projects of these types of aircrafts, systematizing the main characteristics of their propulsion systems. It also includes the research on superconducting machines for the purpose of high specific power, considering the impact on the redesign of aircraft systems in the electrical, cooling, and fuel source sense.

The ability of S. aureus to infect humans and cause a wide range of infections so efficiently is a consequence of the many variant virulence factors that it can produce. Superantigens (SAgs) make up a group of them and include staphylococcal enterotoxins (SE). The main objective of this study was to detect enterotoxin gene cluster (EGC) in S. aureus isolates that caused infections in Paraguayan children in the year 2017, through an observational and cross-sectional study. The detection of the EGC including the seg, sei, sem, sen, seo, and seu genes, was carried out by end-point PCR. 181 S. aureus isolates were collected, most of them caused skin and soft tissue infections (SSTI, n=140, 77%) and came from children under 6 years 50% (n=90). At least one SE gene was detected in 96% (174/181) of isolates and 24% (44/181) carried the entire EGC. An association between methicillin resistance and seg, sei, seo, and seu gene carriage (p ≤0.05) was observed. A high prevalence of EGC was detected in S. aureus isolates collected from infected children attending the main health care centers in Paraguay, its importance is due to the potential of these toxins to aggravate staphylococcal infections.