Air pollution is an important public health issue. High levels of carbon monoxide in the atmosphere are hazardous to human health. Studies regarding the concentration of this and other gases in the atmosphere allow political actions to manage and reduce the emission of pollutants. In this context, this paper studied the annual, seasonal and daily variations of carbon monoxide (CO) concentration for the Metropolitan Region of São Paulo (MRSP). We studied three sites in the MRSP, chosen due to the longer time series and the localities. Two of them are located in areas under the influence of heavy vehicle traffic (Osasco and Congonhas) and the third one in a city park (Ibirapuera Park). The results showed high influence of gasoline vehicles on CO emission. In the annual scale, instead of following the increasing number of vehicles, CO emission and concentration decreased due to improvements in emission technology. CO emission showed a seasonal, weekly and diurnal cycle. The highest values of mean concentration were observed in June/July for Osasco (2.20 ppm), Congonhas (2.04 ppm) and Ibirapuera (1.04 ppm), during the morning, due to weak dispersion of the polluting gases.

This work is a generalization of the Lopez-Ruiz, Mancini and Calbet (LMC); and Shiner, Davison and Landsberg (SDL) complexity measures, considering that the state of a system or process is represented by a dynamical variable during a certain time interval. As the two complexity measures are based on the calculation of informational entropy, an equivalent information source is defined and, as time passes, the individual information associated to the measured parameter is the seed to calculate instantaneous LMC and SDL measures. To show how the methodology works, an example with economic data is presented.

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

We have modelled the energy consumption of prototype and real buildings under present and future climatic conditions with the EnergyPlus model to develop a better understanding of the relationship between changing climate conditions and energy demand. We have produced detailed meteorological information with 50 meters of spatial resolution through dynamical downscaling process combining regional, urban and computational fluid dynamics models which include the effects of the buildings on urban wind patterns. The city of Madrid has been chosen for our experiment. The impact on energy demand and their respective economic cost are calculated for year 2100 versus 2011 based on two IPCC climate scenarios, RCP 4.5 (stabilization of emissions) and RCP 8.5 (not reduction of emissions). Findings show that climate change will have a significant impact on the energy demand for buildings. Space heating demand will be increased by the RCP 4.5 and cooling demand will be increased for the RCP 8.5 in the analysed buildings.

Among the leading immersive technologies, Augmented Reality is one of the most promising and empowering to support designers in production environments. This research investigates the application of mobile augmented reality, based on the Web, as a mediation tool focused on cognitive activities of reading and understanding of Technical Drawings in the production and assembly for Tailor Made projects of the scenographic industry. In this context, the research presents a method to use the WebAR to improve the reading of technical drawings, seeking efficiency on the visualization of models and the exchange of information between professionals, involved in the processes of design, production and assembly of products, in the scope of scenography. This mediation tool was developed using Web AR platforms, compatible with native libraries (ARCore and ARKit) to ensure, first, compatibility with commonly used devices that workers or businesses can access, and secondly, to leverage hybrid tracking techniques that combine vision and sensors to improve the reliability of augmented reality viewing. The proposed solution adopts multiple tracking and navigation techniques in order to expand Space Skills components to provide greater exploratory freedom to users. The research process took place in the light of the Design Science Research Methodology and the DSR-Model, since it aimed to develop a solution to a practical problem, as well as to produce knowledge from this process. Field experiments were conducted in two real companies, with end users on their respective mobile devices, in order to evaluate usability and behavioral intent, through the Acceptance, Intent and Use of Technology questionnaires; and perceived mental workload, NASA-TLX. The experimental results show that the adoption of this tool reduces the cognitive load in the process of reading technical drawings and project´s understanding. In general, it´s usability and intent to use provide significant levels of satisfaction, being positively accepted by all participants involved in the study.

In an era characterized by rapid technological advancements, economic fluctuations, and global competition, adaptability and resilience have become critical success factors for businesses navigating uncertainty and complexity. This article explores the role of enterprise agility in today’s business landscape at Latam branch of Tata Consultancy Services (TCS), where organizations face complex and diverse operations. We aim to examine how companies can become more agile in the face of emerging challenges and seize opportunities swiftly to drive growth and deliver value. Since 2014, the division has embarked on an agile transformation journey to drive growth, deliver value, foster innovation, and build resilience in an increasingly dynamic environment. We scrutinize an approach to measuring and enhancing enterprise agility, employing statistical analysis and continuous improvement methodologies to tackle real-world challenges while offering valuable insights and recommendations for organizations aiming to implement similar systems. The results of an agile transformation in a certain company’s Latam branch serve as a compelling case study, demonstrating how the implementation of targeted measures and continuous improvement can significantly bolster enterprise agility. Methodologically, our work applies a novel sequence of parametric statistical tests which, to the best of our knowledge, have not been used in the industry to validate the results of business agility metrics. In future work, we aim to create a new workflow considering non-parametric tests to address data with other statistical distributions. We conclude our work by proposing a sequence of steps for organizations to implement business agility metrics.

The thermomechanical and viscoelastic properties of a glass fiber polyethylene terephthalate glycol (GF/PETG) continuous unidirectional (UD) tape were investigated using differential scanning calorimetry (DSC), thermo-mechanical analysis (TMA), and dynamic mechanical analysis (DMA). The study identified five operational conditions based on Army Regulation 70-38 Standard. The DSC results revealed a glass transition temperature of 78.0 ± 0.3°C, guiding the selection of temperatures for TMA and DMA tests. TMA provided the coefficient of thermal expansion in three principal directions, consistent with known values for PETG and GF materials. DMA tests, including strain sweep, temperature ramp, frequency sweep, creep, and stress relaxation, defined the linear viscoelastic region and temperature-dependent properties of the material. The frequency sweep indicated an increase in modulus with rising frequency, identifying several natural frequency modes. Creep and stress relaxation tests showed time-dependent behavior, with strain increasing under higher loads and stress decreasing over time for all tested input values. Viscoelastic models fitted to the data yielded R² values of 0.99, demonstrating good agreement. The study successfully measured thermo-mechanical and viscoelastic properties across various conditions, providing insights into how temperature influences the material's mechanical response under extreme conditions.

Somatic cell nuclear transfer (SCNT) has great potential in the replication of high commercial value animals, threatened wild species for conservation purposes, and transgenic animals for biomedical purposes. However, SCNT has a low success rate, due to intrinsic factors of the technique itself, which will lead to low rates of embryonic development and epigenetic alterations in the cloned embryos. The objective of the present study was to evaluate the effect of OF-UF on the intracellular concentration of ROS, GSH, and the development of Ovis aries cloned and parthenogenetic embryos. The results did not show a beneficial effect on the development of parthenogenetic and cloned embryos at concentrations of 0.5% OF-UF. Furthermore, at 1% OF-UF, an adverse effect was observed in cloned embryos at the blastocyst stage and 2% OF and UF in parthenogenetic embryos in the first divisions. A decrease in ROS and GSH levels was observed in the parthenogenetic blastocysts treated with 1% OF-UF, but not in the clones, in which a higher concentration of GSH and a similar concentration of ROS was observed. No effect was observed of OF-UF on embryonic development and redox balance on sheep clone embryos by Handmade Cloning.

This article aims to serve as a guide for the construction of supply chain simulation models designed with a lean approach, using Promodel software. To achieve this, a supply chain was designed for a fictitious company located in the City of Celaya, Guanajuato and a set of suppliers located in different cities within the same State. It was used as a google tool to define the distances between each of the companies. As a final result, a representative model of a supply chain was obtained, as well as a methodology that allows the construction of lean supply chains regardless of the number of companies that comprise it. The effect of the variability in the delivery times between suppliers was incorporated into the simulation model, as well as an equation that calculates the pollution emissions of the vehicles that integrate the network that moves the products between the companies. With this work it is possible to represent networks of supply chains of real world companies, where the variability and contamination factor is included, to facilitate the decision making regarding the number of vehicles, inventory levels, quantities to be shipped, frequency in the shipments, etc. with the purpose of contaminating as little as possible and at the same time preventing interruptions in the supply chain using the least amount of resources possible.

In the broader landscape of cryptocurrency risk management, this study delves into the nuanced estimation of Value at Risk (VaR) for a uniformly weighted portfolio of cryptocurrencies, employing the bivariate Normal Inverse Gaussian distribution renowned for its semi-heavy tails. Utilizing high-frequency data spanning from January 1st, 2017, to October 25th, 2022, with a primary focus on Bitcoin and Ethereum, our research seeks to accentuate the resilience of VaR methodology as a paramount risk assessment tool. The essence of our investigation lies in advancing the comprehension of VaR accuracy by quantitatively comparing observed returns of both cryptocurrencies with their corresponding estimated values, with a central theme being the endorsement of the Normal Inverse Gaussian distribution as a potent model for risk measurement, particularly in the domain of high-frequency data. To bolster the statistical reliability of our results, we adopt a forward test methodology, showcasing not only a contribution to the evolution of risk assessment techniques in Finance but also underscoring the practicality of sophisticated distributional models in econometrics. Our findings not only contribute to the refinement of risk assessment methods but also highlight the applicability of such models in precisely modeling and forecasting financial risk within the dynamic realm of cryptocurrencies, epitomized by the case study of Bitcoin and Ethereum.

Biosensors are measurement devices that can sense several biomolecules, and are widely used for the detection of relevant clinical pathogens such as bacteria and viruses, showing outstanding results. Because of the latent existing risk of facing another pandemic like the one we are living due to COVID-19, researchers are constantly looking forward to developing new technologies for diagnosis and treatment of infections caused by different bacteria and viruses. Regarding that, nanotechnology has improved biosensors design and performance through the development of materials and nanoparticles that enhance their affinity, selectivity, and efficacy in detecting these pathogens, such as employing nanoparticles, graphene quantum dots, and electrospun nanofibers. Therefore, this work aims to present a comprehensive review that exposes how biosensors work in terms of bacterial and viral detection, and the nanotechnological features that are contributing to achieving a faster yet still efficient COVID-19 diagnosis at the point-of-care.

The coffee leaf miner Leucoptera coffeella (Guérin-Mèneville & Perrottet), is a key pest in coffee producing countries. During their development, the larvae feed on the palisade parenchyma of the leaves forming mines. As a result, the photosynthetic area of the plant decreases, affecting coffee production. Despite the severity of the damage caused by coffee leaf miner (CLM), morphological aspects of the larval development and the adult genitalia remain unknown. It is important to identify more susceptible targets to an efficient and narrow control by natural or synthetic approaches, relies on determining the larval instars. Equally important is the sexing of the adult, in experiments aiming efficient ways to control CLM, as the study of pheromone-based control methods. This work presents the first morphological description of the four larval instars and the adult genitalia of L. coffeella. In each larval instar, we measured the Mean ± SD (mm) of the cephalic capsules (1^st 0,14±0,03; 2^nd 0,25±0,04; 3^rd 0,32±0,03; 4^th 0,42±0,03) and observed the following morphological details: primary setae, prolegs, crochets and ecdysial line of the cephalic capsule. In the adults, we observed the sexual structures present in both genitalia: male - bulbus ejaculatorius, valva, anellus, gnathos and aedeagus and female - ovipositor, sclerite and corpus bursae. The dissection of the adult specimens confirmed that the external morphology corresponds to the correct sex attribution in CLM adults. These results may support innovative and improved control strategies for CLM Integrated Pest Management (IPM).

The in vitro production and cryopreservation of mammalian embryos generate reactive oxygen species (ROS) due to conditions of the system that can overcome their antioxidant protection. Resveratrol is an antioxidant used in in vitro systems improving blastocyst rates, but its effect on antioxidant enzymes such as glutathione (GSH) in embryos produced by in vitro fertilization (IVF) after vitrification has not been reported. The objective of this study was to evaluate the effect of resveratrol in the in vitro maturation medium (IVM) of sheep oocytes (Ovis aries) on the levels of ROS and GSH in embryos produced by IVF subjected to vitrification. Resveratrol was added at 0µM, 0.25µM, 0.5µM and 1µM during oocyte in vitro maturation (IVM). Matured oocytes were fertilized with thawed ram sperm. Embryos were cultured in sequential media until blastocysts, then were vitrified for 24 h and after heating they were stained with DCFH-DA (2',7'-dichlorodihydrofluorescein diacetate) to determine the presence of ROS and with Cell Tracker Blue® for the presence of GSH. The quantitative values of ROS and GSH were obtained through the Image J image processor. The results showed that resveratrol increases GSH and decreases ROS production (p<0.05). It is concluded that its use in sheep oocytes during IVM has a beneficial effect on embryos produced by IVF subjected to vitrification, protecting them from oxidative damage by promoting the synthesis of antioxidants.

Serotonergic neurons constitute one of the main systems of neuromodulators, whose diffuse projections regulate the functions of the cerebral cortex. Serotonin (5-HT) is known to play a crucial role in the differential modulation of cortical activity related to behavioral contexts. Certain aspects of the 5-HT signaling framework hint at its potential role as a modulator of activity-dependent synaptic changes within the critical period of the primary visual cortex (V1). Cells of the serotonergic system are among the first neurons to differentiate and operate. During postnatal development, ramifications from raphe nuclei become massively distributed in the visual cortical area, remarkably increasing the availability of 5-HT for the regulation of excitatory and inhibitory synaptic activity. A substantial amount of evidence has demonstrated that synaptic plasticity at pyramidal neurons of the superficial layers of V1 critically depends on a fine regulation of the balance between excitation and inhibition (E/I). Therefore, 5-HT could play an important role in controlling this balance, providing the appropriate excitability conditions that favor synaptic modifications. In order to explore this possibility, the present work used in vitro intracellular electrophysiological recording techniques to study the effects of 5-HT on the E/I balance of V1 layer 2/3 neurons, during the critical period. Serotonergic modulation of the E/I balance has been analyzed on spontaneous activity, evoked synaptic responses, and long-term depression (LTD). Our results pointed out that the predominant action of 5-HT implies a reduction of the E/I balance. 5-HT promoted LTD at excitatory synapses while blocking LTD at inhibitory synaptic sites, thus shifting the Hebbian alterations of synaptic strength towards lower levels of E/I balance.

Significant problems have arisen in the last years, such as climate change, global warming, and hunger. These complications are correlated with the depletion and exploitation of natural resources and environmental contamination. Due to overcrowding, the list of challenges for the next few years is growing. A comprehensive approach was made to the agro-industrial production of Avocado (Persea americana) and the management of all its biomass waste. So, bioprocesses and biorefinery can be used to produce high added-value products. A large number of residues are composed of lignin and cellulose. They have many potentials to be exploited sustainably for chemical and biological conversion; physical, chemical, and natural treatments improve the following operations. There are some applications to many fields such as pharmaceutical, medical, material engineering, and environmental remediation. Possible pathways are mentioned to take advantage of Avocado as biofuels, drugs, bioplastics, and even in the environmental part and emerging technologies such as nanotechnology using bioprocesses and biotech. In conclusion, Avocado and its waste could be transformed into high value-added products in industries above to mitigate global warming and save non-renewable energy.

This review evaluates the trajectory and sustainability of the global and Mexican aquaculture industry. Globally, the sector is experiencing rapid growth, catalyzed by evolving consumption patterns and technological advancements. Notwithstanding the benefits, environmental concerns necessitate an urgent shift towards sustainable practices. The focus then narrows to Mexico's aquaculture, tracing its history from the late 19th century. With an emphasis on species diversification, the country's sector demonstrates resilience and potential, with an impressive yield of 249,613.71 tons in 2021 despite regional consolidation. However, persistent challenges such as technological limitations, funding shortages, and access to quality seeds hinder progress. Risks, including disease outbreaks, negative environmental impact, economic volatility, regulatory compliance, and climate change, further underscore the need for sustainable strategies. With government support and unique geographical and climatic advantages, Mexico shows promise for a significant % growth projection of 25% over the next five years. This review underscores the importance of embracing technological innovation, implementing sustainable practices, and enacting supportive legislation for the long-term success of the aquaculture sector worldwide, with a particular focus on Mexico.

Currently, metal nanoparticles have varied uses for different medical, pharmaceutical, and agricultural applications. Nano-biotechnology combined with green chemistry has great potential for the development of novel and necessary products that benefit human activities, while encourages the reduction of hazardous reagents for nanoparticle production. Green chemistry has an important role due to its contribution to unconventional synthesis methods of gold and silver nanoparticles from plant extracts, which have exhibited antimicrobial potential among other outstanding properties. Biodiversity-rich countries need to collect and convert knowledge from biological resources into processes, compounds, methods, and tools, which need to be achieved along with sustainable use and exploitation of biological diversity. Therefore, this review focuses on the importance of metal nanoparticles, the use of plant extract for their synthesis as well as other available methods, and the relevant antimicrobial activity that can be exploited in a sustainable model of agricultural management through a modern nanotechnological approach.

The main purpose of this paper is to present a system to detect extrusion failures in Fused Deposition Modelling (FDM) 3D printers by sensing that the filament is moving forward properly. After several years using these kind of machines, authors detected that there is not any system to detect the main problem in FDM machines. Authors thought in different sensors and used the Weighted Objectives Method, one of the most common evaluation methods, for comparing design concepts based on an overall value per design concept. Taking into account the obtained scores of each specification, the best choice for this work is the optical encoder. Once the sensor is chosen, it is necessary to design de part where it will be installed without interfering with the normal function of the machine. To do it, photogrammetry scanning methodology was employed. The developed device perfectly detects the advance of the filament without affecting the normal operation of the machine. Also, it is achieved the primary objective of the system, avoiding loss of material, energy and mechanical wear, keeping the premise of making a low-cost product that does not significantly increase the cost of the machine. This development has made it possible to use the printer with remains coil filament, which were not spent because they were not sufficient to complete an impression and also printing models in two colours with only one extruder.

Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. Here we present a new methodology combining satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, applied within slope unit polygons. We studied a former mining area in southeast Spain, and the method proved useful in detecting and characterizing a considerably large number of unstable slopes. Out of 1,959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through the validation analysis (2.5 cm/year). Eventually, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear and easily comparable information to analyze slope instabilities in different settings, not limited to mining areas.

According to the International Union for Conservation of Nature Red List, the scalloped hammerhead (Sphyrna lewini) is a critically endangered species, primarily due to intense fishing and other anthropogenic effects such as pollution. Nowadays, plastic debris contamination is a subject of concern due to its extensive presence in the sea and the digestive tracts of many fish species. The possible effects of plastic debris as a vector of other pollutants are still unknown. We analyzed the digestive tract of hammerhead sharks to investigate the correlation between plastic and other anthropic debris contamination and feeding habits in the eastern region of the Gulf of California. A total of 58 specimens were analyzed from the coastal area, revealing a plastic occurrence frequency of 79.3%. Of these, 91.4% corresponded to fibers, and 8.6% to fragments. The composition of the polymers was primarily cellulose (64.4%). According to their diet, these organisms exhibit benthopelagic habits, feeding both in the water column and on the seabed. These results indicate a high level of contamination of anthropogenic cellulosic microfibers in the area. This changed according to the year, indicating that the anthropic debris ingestion is related to the discharges of human activities and their seasonality rather than to a selection process by the sharks. Although cellulosic microfibers are recognized as a biomaterial, they can harm marine species, posing an additional threat to this iconic shark.

In the last years, advances in materials engineering based on adaptive electronics have found a new paradigm to optimize drawbacks in signal processing. A two-layer MnO/ZnO:Zn heterostructure envisioned for frequency adaptive electronic signal processing is synthesized by sputtering where the use of internal states allows reconfigurability to obtain new operating modes at different frequency input signals. An X-Ray Diffraction (XRD) is performed on each layer, MnO:Mn had a cubic and ZnO:Zn a hexagonal structure with preferential growth in [111] and [002] directions respectively. It is determined that the coupling in this heterojunction is compatible with a mismatch less 1 % due texture in each layer which implies a low number of defects. An electrical characterisation with an oscilloscope and signal generator was carried out to obtain the time-response signals and current-voltage (I-V) curves where no degradation is detected when changing from a range of frequencies (100 Hz – 1 MHz). An equivalent circuit is proposed to explain the effects in the interface. Finally, the MnO/ZnO:Zn heterojunction delivers states that are stable, repeatable, and reproducible and it demonstrates how the interaction of the materials can be used in adaptive device applications applying frequencies and internal states as to create new and innovative design schematics, reducing the numbers of components/connections in a system for future sustainable electronics.

Acerola (Malpighia spp.) is a tropical plant genus of shrubs and trees whose fruit is rich in nutrients and bioactive compounds. However, its production generates significant waste that could pose an environmental issue. This review aims to summarize recent research on the potential uses of acerola wastes, including the extraction of bioactive compounds such as polyphenols, carotenoids, and pectins, as well as the development of materials such as nanomaterials, chitosan, and biofuels. Additionally, the paper discusses the potential medical applications of acerola wastes, such as wound healing, antioxidant, and anticancer effects. Finally, the paper explores the challenges and opportunities of using acerola waste as a sustainable source of raw materials and energy. The findings suggest that acerola waste could be a valuable resource for developing high-value products and promoting sustainable production practices in the fruit industry.

Pineapple is a highly demanded fruit in international markets, thanks to its unique appearance and flavor, high fiber content, vitamins, folic acid, and minerals. It makes the pineapple production and processing market a significant source of income for producing countries, such as Costa Rica. Nowadays, its processing produces a large amount of waste with negative consequences for the environment. However, pineapple waste is an essential source of cellulose, hemicellulose, lignin, and other high-value products like enzymes (bromelain). These by-products can be obtained by pineapple waste biorefinery, generating an additional source of export goods and foreign currency, framing pineapple processing in the concept of the circular economy. This review discusses how incorporating biorefinery in the pineapple production processes can contribute to the post-COVID 19 economy in Costa Rica. Pineapple production in Costa Rica is explored, and the contamination of generated residues is delineated. Furthermore, the primary processes for by-product extraction via biorefinery, their general characteristics and applications in the medical field, and their contribution to the circular economy are presented.

This study contributes to the Sybil nodes detecting algorithm in Online Social Networks (OSNs). As major communication platforms, online social networks get significantly guarded from malicious activity. A thorough literature review identified various detection and prevention Sybil attack algorithms. Additional exploration of distinct reputation systems and their practical application led to the study’s discovery of machine learning algorithms, i.e., the KNN, Support Vector Machines, and Random Forest algorithms. The study details the data cleansing process for the employed dataset in its process for optimizing the computational demands required to train machine learning algorithms, achieved through dataset partitioning. Such a process led to explaining and analysis of conducting experiments and comparing their results. Such experiments demonstrate the algorithm’s ability to detect Sybil nodes in OSNs (100% accuracy in SVM, 99.6% in Random Forest, and 97% in KNN algorithms); thus concluding by proposing future research opportunities.

After the ban on tributyltin-based antifouling paints, DCOIT (4,5-Dichloro-2-octylisothiazol-3(2H)-one) became one of the most used antifouling biocides. DCOIT is a pseudo-persistent contaminant in port areas and is toxic to non-target species, but its ability to bioaccumulate and be transferred along the trophic chain remains unknown. This study aimed to preliminarily investigate the bioaccumulation, trophic transfer, and biomagnification of DCOIT and SiNC-DCOIT (DCOIT immobilized in silica mesoporous nanocapsules) from the microalga Tetraselmis chuii to the mussel Mytilus galloprovincialis during exposure experiments considering 24 h of uptake followed by 72 h depuration. Mussels rapidly internalized and metabolized both DCOIT and SiNC-DCOIT. The predator-prey biomagnification factors (BMFTL) suggested that both forms of the biocide can be trophically transferred, with higher concentrations of DCOIT and SiNC-DCOIT in mussels than in microalgae (BMFTL &gt; 1). However, the bioaccumulation and bioconcentration factors indicated a low bioaccumulation capability in the short term, suggesting that the depuration rate overcomes the uptake. Our findings contribute to the development of environmental risk assessments for DCOIT and SiNC-DCOIT, but do not exclude the possibility of DCOIT bioaccumulation in the long-term in areas with constant input of DCOIT. Further studies are needed to understand these processes under continuous exposure scenarios to DCOIT.

In the context of energy conversion from renewable sources to distribution grids (insulated or not), a converter is often required to transfer energy from a low voltage source, towards three-phase grids. This paper presents the HW design, the simulation results and the conversion performance of a CSI converter intended to interface low voltages renevable sources to three-phase grids. The main focus of this paper is to obtain the best performance in terms of voltage increase towards the output stage while maximizing the conversion efficiency. In comparison with the currently used energy conversion systems for small photovoltaic systems, hereafter some solutions were adopted to level and maximize the energy flow from the source to the DC-link and improve the quality of current supplied in terms of harmonic distortion. The proposed system is composed of two conversion stages: the first, voltage-to-current, the second current-to-current via a three-phase CSI bridge modulated with SVM technique. The stages are not completely decoupled from an electrical point of view, therefore, in order to mitigate the effects of these interactions, synchronization strategies have been adopted.

The natural history of COVID-19 caused by SARS-CoV-2 is extremely variable, ranging from asymptomatic infection, to pneumonia, and to complications eventually fatal. We propose here the first model, explaining how the outcome of first, crucial 10-15 days after infection, hangs on the balance between the cumulative dose of viral exposure and the efficacy of the local innate immune response (natural IgA and IgM antibodies, MBL). If SARS-CoV-2 runs the blockade of this innate immunity and spreads from the upper airways to the alveoli in the early phases of the infections, it can replicate with no local resistance, causing pneumonia and releasing high amounts of antigens. The delayed and strong adaptive immune response (high affinity IgM and IgG antibodies) that follows, causes severe inflammation and triggers mediator cascades (complement, coagulation, and cytokine storm) leading to complications often requiring intensive therapy and being, in some patients, fatal. Strenuous exercise and high flow air in the incubation days and early stages of COVID-19, facilitates direct penetration of the virus to the lower airways and the alveoli, without impacting on the airway’s mucosae covered by neutralizing antibodies. This allows the virus to bypass the efficient immune barrier of the upper airways mucosa in young and healthy athletes. In conclusion, whether the virus or the adaptative immune response reach the lungs first, is a crucial factor deciding the fate of the patient. This “quantitative and time-sequence dependent” model has several implications for prevention, diagnosis, and therapy of COVID-19.

The self-assembly is an intriguing process of great importance in general soft matter and thus re-ceives an ever-growing scientific interest. Its most trivial example is the entropy-driven crystalli-zation of hard spheres. Past works have established the similarities and differences in the phase behavior of monomers and chains made of hard spheres. In the present work, inspired by the dif-ference in the melting points of the pure components, we study, through Monte Carlo simulations, the phase behavior of athermal mixtures composed of fully flexible polymers and individual monomers of uniform size. We analyze how the relative number fraction and the packing density affect crystallization and the established ordered morphologies. A synergetic effect is observed in the crystallization leading to synchronous crystallization of the two species. Structural analysis of the resulting ordered morphologies shows perfect mixing and thus no phase separation, which could split the system into polymer-rich and monomer-rich domains. Due to the constraints imposed by chain connectivity, the local environment of the individual spheres is systematically more spherical and more symmetric compared to the one of spheres belonging to chains. In general, increasing polymer content leads to reduction of the degree of crystallinity. According to the present findings, relative concentration is another determining factor to control the phase behavior of hard colloidal systems based on polymers.

In this work, the influence of catalyst reuse and reaction time on the yield and quality of organic liquid products (OLP) obtained in a cracking pilot plant at 450 °C and 1.0 atm has been systematically investigated. The distillation of OLP produced 04 (four) distilled fractions. The quality of the biofuels was certified by physical-chemical analysis, as well as FT-IR and GC-MS analysis. The experimental results showed the feasibility of applying the spent sodium carbonate twice in catalytic cracking of vegetable oils. The physical-chemical properties (density, viscosity, acid value, saponification value, and flash point) of OLP decrease as the reaction time increases. The distillation of OLP yields 62.35% (wt.), producing green-like gasoline, kerosene, and diesel fractions rich in hydrocarbons. Therefore, biofuels-like fractions produced by distillation of OLP have a great potential for replacing partially petroleum derived fuels.

Somatic cell nuclear transfer (SCNT) is a reproductive biotechnology with great potential in the reproduction of different species of zootechnical interest, including sheep. This study aimed to carry out a bibliometric analysis of scientific papers published on the application of SCNT in sheep reproduction in the period 1997-2023. The search involved the Science Citation Index Expanded and Social Sciences Citation Index databases of the Main Collection of Web of Sciences with different descriptors. A total of 124 scientific papers were analyzed for different bibliometric indicators using VOSviewer software. Since 2001, the number of SCNT-related documents published concerning sheep reproduction increased and has fluctuated in ensuing years. The main authors, research groups, institutions, countries, documents and journals with the highest number of publications related to SCNT in sheep reproduction were identified, as well as the topics that address the research papers according to the terms: somatic cell, embryo, oocyte, gene expression, SCNT, and sheep.

Polyalcohol liquefaction can be done by acid or basic catalysis producing polyols with different properties. This study compared the mechanical properties of foams produced using polyols from liquefied Cytisus scoparius obtained by acid and basic catalysis and using two different foam catalysts. The differences were monitored using FTIR analysis. Acid-catalyzed liquefaction yielded 95.1 %, with the resultant polyol having an OH index of 1081 mg KOH/g while basic catalysis yielded 82.5 %, with a similar OH index of 1070 mg KOH/g. Generally, compressive strength with dibutyltin dilaurate (DBTDL) ranged from 16 - 31 kPa (acid-liquefied polyol) and 12 -21 kPa (base-liquefied polyol), while with stannous octoate (TIN), it ranged from 17 - 42 kPa (acid) and 29 - 68 kPa (base). Increasing water content generally decreased the compressive modulus and strength of foams. Higher water content led to a higher absorption at 1670 cm-1 in the FTIR spectrum due to the formation of urea. Higher isocyanate indices generally improved compressive strength, but high amounts led to unreacted isocyanate that could be seen by a higher absorption at 2265 cm-1 and 3290 cm-1. DBTL was shown to be the best foam catalyst due to higher trimer conversion seen in the spectra by a higher absorption at 1410 cm-1. Acid and base-derived polyols lead to different polyurethane foams with different FTIR spectra, particularly with a higher absorption at 1670 cm-1 for foams from acid-derived liquefaction.

Brushless Synchronous Machines (BSM) are replacing conventional synchronous machines with static excitation in generation facilities due to the absence of sparking and lower maintenance. However, this excitation system makes challenging measuring electric parameters in the rotor. This fact highly difficult the detection of ground faults, which are the most common type of electrical fault in electric machines. In this paper, a ground fault detection method for BSM is proposed. It is based on an inductive AC/DC rotating current sensor installed in the shaft. In case of a ground fault in the rotating parts of the BSM, a fault current will flow through the rotor’s sensor, inducing voltage in its stator. Analyzing the frequency components of the induced voltage the detection of a ground fault in the rotating elements is possible. The ground faults detection method proposed covers the whole rotor and discern between DC and AC sides. To corroborate the detection method, experimental tests have been performed using a prototype of this sensor connected to laboratory synchronous machines achieving satisfactory results.

The high transmissibility, rapid evolution, and immune escape of SARS-CoV-2 variants can influence the course of infection and, in turn, morbidity and mortality in COVID-19, posing a challenge in controlling transmission rates and contributing to the emergence and spread of new variants. The factors that shape viral genetic variation are consequently essential for understanding the evolution and transmission of SARS-CoV-2, especially in vaccinated individuals where immune response plays a role in the progression and spread of this disease. This study assessed. In this context, we evaluated the impact of immunity induced by the CoronaVac vaccine (Butantan/Sinovac) on intra-host genetic diversity, analyzing 118 whole-genome sequences of SARS-CoV-2 from unvaccinated and vaccinated patients infected with the Gamma variant. Vaccination with CoronaVac favors negative selection at the intra-host level in different genomic regions and prevent greater genetic diversity of SARS-CoV-2, which may help reduce the emergence of new mutations, reinforcing the importance of vaccination in reducing virus transmission.

Piperine, an active plant alkaloid from black pepper (Piper nigrum), has several pharmacological effects: antioxidant, anti-inflammatory and immunomodulatory, which involves inhibiting molec-ular events associated with various stages of cancer development. The aim of this study was to investigate the molecular mechanisms of action of piperine in relation to its potential anticancer effect on head and neck cancer cells. Parameters related to neoplastic potential, analysis of cyto-kine, protein and gene expression were investigated in the head and neck cancer cell lines (HEp-2 and SCC-25) treated with piperine. The results of the tests indicated that piperine modified mor-phology, inhibited viability and the formation of cell colonies. Piperine promoted genotoxicity by triggering apoptosis and cell cycle arrest in G2/M and S. A decrease in cell migration was also observed, and decreased expression of MMP2/9 genes. Piperine also reduced the expression of inflammatory molecules (PTGS2 and PTGER4), regulated the secretion of cytokines (IF-y and IL-8) and modulated the expression of ERK and p38. These results suggest that piperine exerts anti-cancer effects on tumor cells, and could be a promising natural treatment by regulating signaling pathways associated with head and neck cancer.

Background: The study demonstrates the sustainable synthesis of translucent zinc oxide (ZnO) nanowires using Moringa seed extract, highlighting eco-friendly and sustainable approaches. Methods: Characterization techniques such as X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) confirmed the formation of ZnO nanostructures with diverse morphologies, including nanowires and spherical clusters. Results: The synthesized ZnO nanowires exhibited remarkable photocatalytic activity, achieving over 89% degradation efficiency of methylene blue (MB) under UV light within 80 minutes, demonstrating their potential for wastewater treatment applications. Conclusions: The research findings support Sustainable Development Goals (SDGs) related to clean water, climate action, and life below water and on land, highlighting the role of eco-friendly nanostructures in environmental remediation. The dual advantage of Moringa seed extract, providing both a sustainable synthesis route and health benefits due to its rich content of vitamins and phytochemicals, underscores the potential of integrating natural resources in nanotechnology for environmental and health applications.

The paper presents the main experimental capabilities of the automatic system for the study of the interaction between porous media and atmosphere. This system is one of the possible variants of patent 2-241-477. The paper shows the result of a drying and wetting study of a tailings sample. The sample is 32 cm in height and 29 cm in diameter. The saturation and drying process was carried out at 26 degrees Celsius at the sample surface, an air velocity of 2 m/s and a relative humidity of 60%. The recharge applied to the column surface was 0.3 cm3/cm2/minute. The results show the effectiveness of the system in controlling the spatial-temporal variation of different physical properties of the porous medium in the vertical and surface profile. The controlled variables include volumetric water content, suction, relative humidity, sample weight variation due to recharge or drying, shrinkage, temperature, etc. The experiment shows how the tailings saturate very quickly but dry very slowly. Tailings consolidation occurs in the drying and wetting processes, being higher in the first one.

Low-frequency audible noise generated by the magnetostriction effect inherent to the operation of power transformers has become a major drawback, especially in cases where the electrical substation is located in urban areas subject to strict environmental regulations that imposes sound pressure limits, differing for day and night periods. Such regulations apply a +5 dB penalty if a tonal component of noise is present, which is clearly the case of magnetostriction noise, typically concentrated at twice the industrial frequency (50 Hz or 60 Hz, depending on the country). The strategy used to eliminate the tonal characteristics, therefore contributing to establish compliance with the applicable regulation and to alleviate the discomfort it causes to the human ear, consisted in superimposing to the substation noise a masking sound synthesized from “sounds of nature” with suitable intensities, to flatten the noise spectrum while enhancing the soundscape. The masking system (heavy-duty speakers powered by a microprocessor platform) was validated at an already judicialized urban scenario. Measurement results confirmed that the masking solution was capable of flattening the tonal frequencies, whose beneficial effect yielded the cancellation of the public civil action filed by the neighbors. The proposed solution is ready to be replicated to other scenarios.

The coffee industry loses millions of dollars annually worldwide due to the Coffee Berry Borer (CBB); these losses imply a decrease in quality and production. Traps are used to monitor their flight and for pest control. The main objective was to determine the flight pattern and trap capture percentages of the CBB population over time using column traps (CTs) in two independent field experiments. CTs were composed of four traps installed at four different heights 0.5, 1.5, 2.5, and 3.5m above ground. Our results demonstrated a significant difference in CBB capture by traps placed at different heights above the ground. The CT capture maintained a pattern throughout this study's lag; the lower the height, the greater the percentage of CBBs captured. In Experiments A and B, the traps placed at 0.5m caught 67% and 85% of the CBBs captured, respectively. Furthermore, the trap set at 1.5m above the ground in the multi-level CT showed a higher capture percentage than the individually placed trap (also at 1.5m). The pattern of the capture and proportion of the CBB in the CTs were maintained throughout the study despite the season, changes in temperature, and relative air humidity. We suggested that CTs could be explored as a useful tool for capturing the CBB, considering its monitoring and management.

There are increasing calls in education for deeper integration of disciplines and better preparation for the personal and job challenges of a fast-changing and smarter society. Thus, we need to search for new effective didactic strategies. However, current classrooms are isolated. They practically never connect. This hinders the exchange of ideas. It inhibits imitation and recombination, the basic blocks of cultural evolution and innovation. In this paper, we analyze online inter-class tournaments. These are lessons where entire elementary or middle school classes interconnect synchronously and play an educational game. These are new types of academic activities, and only possible thanks to digital communication technology. In this paper, we examine four online tournaments, we analyze how feasible it is to carry them out and the benefits they bring. One tournament is for teaching machine learning and statistics. The second one teaches the conservation of momentum in physics and an engineering optimization challenge. The third tournament is for learning to solve word problems. The fourth one is for teaching natural and sexual selection along with developing statistical and population thinking. We found that these inter-class tournaments are feasible to implement in schools and that they are a promising mechanism to facilitate imitation, recombination, and innovation of teaching strategies.

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

By defining a constant probabilistic orbit of and iterated functions, the stability dynamics of these functions in possible interactions through connectivity provides the formation of a dynamic fixed point as a metric space between both iterated functions. The presence of a dynamic fixed point identifies qualitatively phases of iteration time lengths and interaction orbits of the event. Qualitative results show that the greater the average distance from one of the functions to the fixed point of the other (all possible solutions), the higher the iteration expression on time (false asymptotic effect) of one of the functions and in the opposite hand, the lower the average distance, the higher orbit’s interactions proximity between iterated functions (stability). This feature reveals asymptotic (well-defined) behavior between functions f and g within a well-defined Lyapunov stability.

Ants have a very sophisticated olfactory system; their communication is based on the interpretation of chemical trails known as semiochemicals. The escamolera ant (Liometopum apiculatum), has behaviors and physiological responses is induced by semiochemicals, without however, these have not been studied. Using an electronic nose analysis (e-nose) and chromatographic techniques, semiochemicals of L. apiculatum in nests, foraging trails and dissected the gasters were evaluated. Data were analyzed with multivariate statistics and a logistic regression model based on predictors (ant counts) and the semiochemicals identified in pre-season (PRE), season (TEM) and post-season (POS) of larval collecting. From the general pattern of volatiles with a natural separation in POS and a partial distribution between PRE and TEM 32 semiochemicals were identified inside the nests, those who can induce the behavioral responses of trail-following, alarm, aggression, and nestmate recognition. Trail counts indicated that ant traffic was higher in POS and that the presence of certain semiochemicals (response variable) have good fit in the model regression. These findings are intended to provide useful information and support decision-making for the conservation and sustainable use of L. apiculatum in central Mexico.

Pineapple is a highly demanded fruit in international markets, thanks to its unique appearance and flavor, high fiber content, vitamins, folic acid, and minerals. It makes the pineapple production and processing market a significant source of income for producing countries, such as Costa Rica. Nowadays, its processing produces a large amount of waste with negative consequences for the environment. However, pineapple waste is an essential source of cellulose, hemicellulose, lignin, and other high-value products like enzymes (bromelain). These by-products can be obtained by pineapple waste biorefinery, generating an additional source of export goods and foreign currency, framing pineapple processing in the concept of the circular economy. This review discusses how incorporating biorefinery in the pineapple production processes can contribute to the post-COVID 19 economy in Costa Rica. Pineapple production in Costa Rica is explored, and the contamination of generated residues is delineated. Furthermore, the primary processes for by-product extraction via biorefinery, their general characteristics and applications in the medical field, and their contribution to the circular economy are presented.

The Canal of Aragon and Catalonia (CAC) is 134 km long and irrigates 105,000 ha (131 irrigation user communities) and it is own by the River Ebro’s Water Agency. The aqueducts are located between km 67 and 71 of the canal and were designed by the Civil Engineer Félix de los Ríos Martín in 1907. The cross-section of both aqueducts, Coll de Foix and Capedevila, was extended within the framework of the project by Fernando Hué Herrero in 1962 in order to reach design flows of 26.1 m3/s and 25.7 m3/s, respectively. The structural performance of the aqueducts has been satisfactory, nevertheless the hydraulic capacity has reduced over the years. As a result, the irrigation user communities have expressed the need to extend the cross-section of the aqueducts to meet the irrigation demands. Given the age of the structure and the different design considerations at the time, it is paramount to verify the structural reliability of the aqueducts in the new load configuration. Therefore, the objective of the paper is to present the structural safety analysis conducted and describe the new extended cross-section for both aqueducts (maintaining the original structural typology).

The revolutionary idea of complementary intelligence involves a unique strategy in which artificial intelligence (AI) works with human cognitive abilities embodied by natural intelligence (NI), creating a harmonious partnership instead of engaging in a competitive relationship. This innovative concept can potentially revolutionize how we approach scientific research and discovery. This cutting-edge process capitalizes on pooling the vast information from various distinct and autonomous sources to generate forecasts that frequently outshine human perspectives by significant margins, leading to groundbreaking advancements in scientific development based on hybrid intelligence. Multilayer networks extend traditional network theory to adjacent layers linked through copula nodes. Artificial intelligence, with its retrieval capacity to collect and interpret big data, sharply increases the number of nodes and their linking interpretation. This process, amplified by multilayer networks, dramatically improves the scalability of the networked ecosystem. Multilayer networks can represent NI and AI in complementary hyperplanes, connecting them with copula nodes and edge properties. Thus, it is possible to measure the interaction of NI and AI, assessing their scalable value co-creation properties. This study examines the interaction of NI and AI with an innovative and multidisciplinary approach. A theoretical framework of these related concepts precedes practical insights for possible applications in future research.

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual energy imaging remains relatively untapped, possibly due to its intricate workflow and intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is neces-sary for an appropriate clinical use. The aims of this paper are to review physical and technical basis of DECT acquisition and analysis, to discuss advantages and limitations of DECT in dif-ferent clinical scenarios, to review technical constraints in material labeling and quantification, and to evaluate cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radioge-nomics

The heat and matter transfer during glucose catabolism in living systems and their relation with entropy production are a challenging subject of the classical thermodynamics applied to biology. In this respect, an analogy between mechanics and thermodynamics has been performed via the definition of the entropy density acceleration expressed by the time derivative of the rate of entropy density and related to heat and matter transfer in minimum living systems. Cells are regarded as open thermodynamic systems that exchange heat and matter resulting from irreversible processes with the intercellular environment. Prigogine’s minimum energy dissipation principle is reformulated using the notion of entropy density acceleration applied to glucose catabolism. It is shown that, for out-of-equilibrium states, the calculated entropy density acceleration is finite and negative and approaches as a function of time a zero value at global thermodynamic equilibrium for heat and matter transfer independently of the cell type and the metabolic pathway. These results could be important for a deeper understanding of entropy generation and its correlation with heat transfer in cell biology with special regard to glucose catabolism representing the prototype of irreversible reactions and a crucial metabolic pathway in stem cells and cancer stem cells.

In the last decade, the integration of robots into agricultural tasks has significantly transformed food production from planting to harvest. The precision and efficiency of a robot allow for specialized crop management in cases such as; plant disease identification, optimization of water and fertilizer use, monitoring of environmental and soil conditions, among others. That is, the adoption of robots in agricultural practices through intelligent automation increases crop yields and decreases environmental impact. Intelligent automation faces contemporary challenges such as climate change and population growth, promoting sustainable food security. Therefore, this article presents a review of the state of the art of modular robots and their applications in agriculture. Modular robots have the ability to reconfigure and adapt to different tasks, promoting versatile solutions for the agricultural sector. These solutions are linked to the robot's control systems, which can be centralized, decentralized, and hybrid. Firstly, centralized control allows for unified management and coordination in high-precision tasks. Secondly, the decentralized approach offers flexibility and robustness in changing environments where adaptability is required. Thirdly, hybrids incorporate features of both control types balancing control and autonomy to increase efficiency and effectiveness in practical applications. In some cases, control systems incorporate bio-inspired motion control techniques, where the robot mimics natural movements and behaviors to improve its adaptability in performing a task. For example, the chemosynthesis model, which is a biological process where bacteria convert an inorganic compound into energy, has been adapted for individual robots to explore and navigate their environment. Therefore, this article presents an overview of modular robots, the incorporation of bio-inspired motion control techniques, and their convergence towards the sustainable solution of contemporary problems in the agro-industry.

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.

This work aimed to synthesize new N-rich triazole compounds. In this article we describe the synthesis of three different 1,2,4-triazole-based systems starting from 1,3-diaminoguanidine hydrochloride monohydrate. The structure of the obtained crystals was established by single-crystal X-Ray diffraction. The high nitrogen content of the synthetized compounds makes them building blocks for the application in the High-Energy-Density material science.

Hazelnut shells (HS), scientifically known as Corylus avellana L. shells, are a waste produced in companies that process nuts. The main objective of this study was to find an efficient way to maximize the chemical potential of HS by solubilizing the hemicelluloses, which could then be used to recover sugars and at the same time increase the lignin content of this material in order to produce adhesives or high strength foams. In order to optimize the pre-hydrolysis process, two different temperatures (160 and 170 C) and times varying from 15 to 180 min were tested. All the remaining solid materials were then liquefied by polyalcohols with acid catalysis. The chemical composition of hazelnut shells was determined before and after the pre-hydrolysis. All the process was monitored by FTIR-ATR by determining the spectra of solids and liquids after pre-hydrolisis and liquefactions steps. The highest solubilization of hazelnut shells was found for 170 C and 180 min, resulting in a 25.8% solubilization. Chemical analysis after the hydrolysis process showed a gradual increase in the solubilization of hemicelluloses as both the temperature and time of the reactor were increased. Simultaneously, the percentages of α-cellulose and lignin in the material also increased with rises in temperature and duration. FTIR-ATR allowed for the detection of significant spectral changes in the hazelnut shells from their initial state to the solid residue and further into the liquefied phase. This confirmed that pre-hydrolysis was effective in enhancing the chemical composition of the material, making it more suitable for the production of adhesives or polyurethane foams with enhanced mechanical strength.

The climate and its changes are major risk factors for agricultural activities because agricultural systems are highly affected by climatic factors such as temperature, rain, humidity, wind, and solar radiation. While some agricultural areas of the world are irrigated, the vast majority rely on natural rainfall patterns. Farmers will consume more water as a result of climate change and experience less water availability, resulting in a decrease in production capacity. As one of the most important natural phenomena affecting agricultural productivity, drought is a limiting environment for plant growth. The response of plants to water stress is complex and involves coordination between gene expression and its integration with hormones. It has been shown that bacteria have mechanisms to reduce water stress in these plant species and promote greater growth. The underlined mechanism involves root-to-shoot phenotypic changes in growth rate, architecture, hydraulic conductivity, water conservation, plant cell protection, and damage restoration through integrating phytohormones modulation, stress-induced enzymatic apparatus, and metabolites. This review demonstrates how plant growth-promoting bacteria can mitigate negative effects associated with water stress in plants and provide examples of technology conversion in agroecosystems.

The European Union's recent decision to renew the authorization for the use of glyphosate until 15 December 2033 stimulates the scientific discussion all around the world regarding its toxicity or otherwise for humans. Glyphosate is a chemical used by millions of tons in the last 50 years worldwide to drying weeds in cultivated fields, greenhouses, roadsides. Concern has been raised in many quarters about the possible presence in the food chain and the consequent adverse effects on health: both aspects that argue in favor of toxicity and those that instead may indicate limited toxicity of glyphosate are here discussed. The great debate that has been generated requires further investigations and field measurements to understand its fate once dispersed in the environment and its concentration in the food chain. Hence the need for validated analytical methods that are available to analysts in the field. In the present review, methods for the analytical determination of glyphosate and its main metabolite, AMPA, are discussed, with a specific focus on chromatographic techniques applied to cereal products. The experimental procedures are explained in any detail, including cleanup, derivatization, and instrumental conditions to give the laboratories involved enough information to proceed with the implementation of this line of analysis. The prevalent chromatographic methods used are LC-MS/MS, GC-MS/SIM, and GC-MS/MS but sufficient indications are also given to those laboratories that wish to use the simpler HPLC-FLD, HPLC-UV, GC-NPD or GC-FPD techniques for screening purposes. Concentrations from literature measured in wheat, corn, barley, rye, oats, soybean, and cereal-based foods are reported together with the regulatory status in various parts of the world and the accumulation mechanism. As for the accumulation in cereals, available data show that glyphosate tends to accumulate more in wholemeal flours than in refined ones, that its concentration in the product strictly depends on the treatment period (the closer it is to the time of harvesting, the higher the concentration) and that in cold climates the herbicide tends to persist in the soil for a long time.

The number of physical devices connected to the Internet such as vehicles, household appliances and other "things" has been steadily increasing in recent years, thus forming the basis for the Internet of Things (IoT). IoT ecosystem extends beyond country borders and application domains, combining thousands of versatile devices that differ in terms of their structures, capabilities, and available resources. It is therefore not surprising that the landscape of wireless communication technologies and the degree of IoT devices available today is excessively broad and diverse. Interference between networks leads to frame collisions and consequent packet loss. Frame collisions occur when two or more packets overlap in time and frequency and use the same Long Range (LoRa) parameters, i.e. the same Spreading Factor (SF), Bandwidth (BW) and Carrier Frequency (CF). When most devices use the same configuration, collision probability is higher. The probability of frame collisions is also affected by traffic characteristics, particularly the periodicity of the transmission and the payload size. Larger payload sizes and more frequent transmissions accumulate with higher Time on Air (ToA) and channel occupancy [1]. Transmission powers and the location of the gateways also influences this situation. The aim of this experimental work is to verify the effects of collisions and interference in Long Range Wide Area Network (LoRaWAN), regarding the periodicity of transmissions and the payload sizes in a context of an inter-SF interference scenario. And to validate measuring tools like Received Signal Strength Indicator (RSSI), ToA and Packet Delivery Ratio (PDR) in the reliability of a network. We validate our conclusions by analyzing ToA according with RSSI and different data sizes, the RSSI for different SFs and different data sizes and finally the packet loss through the PDR for a better understanding of the reliability of packet transmission in our link. In the end we conclude that in an environment with inter-SF interference, the choice of SFs and packet lengths impacts ToA. When dealing with multiple devices near gateways, different SFs and varying packet lengths can lead to increased latency and longer ToA. Consequently, the risk of packet loss becomes more significant, especially if the signal-to-interference ratio (SIR) is low. This limitation will therefore affect scalability, particularly in Non-Line-Of-Sight (NLOS) scenarios.

COVID-19, caused by the SARS-CoV-2 virus, has spread around the world and killed around 6.9 million people. Rapid and accurate diagnosis is essential for preventing and controlling the disease, reducing transmission and consequently saving lives. RT-PCR is the gold standard test used to detect the disease. However, the test is expensive and the result is time-consuming, which makes mass testing difficult, especially in countries with limited resources. In addition, the test has high analytical specificity and low diagnostic sensitivity, which leads to false-negative results. Several studies in the literature report the presence of hematological and biochemical alterations in infected patients and use these alterations with machine learning algorithms to help diagnose the disease. Therefore, this article presents the results obtained by different neural network architectures based on Adaptive Resonance Theory (ART) for the diagnosis of COVID-19. The study was conducted in two distinct stages: the first consisted of selecting the best ART network among several, using three open-access datasets and comparing the results with the literature. In the second stage, the chosen model was tested on a dataset containing patients from various hospitals in four countries. In addition, the model was subjected to external validation, including data from a country not present during the training and adjustment of the model, in order to validate the robustness and generalization capacity of the model. The results obtained by the ART networks in this study are promising, outperforming not only classical models, but also the deep learning models often used in the literature. Validation on data from different countries strengthens the model’s reliability and effectiveness.

We report a photonic-based radio frequency (RF) arbitrary waveform generator (AWG) using a soliton crystal micro-comb source with a free spectral range (FSR) of 48.9 GHz. The comb source provides over 80 wavelengths, or channels, that we use to successfully achieve arbitrary waveform shapes including square waveforms with a tunable duty ratio ranging from 10% to 90%, sawtooth waveforms with a tunable slope ratio of 0.2 to 1, and a symmetric concave quadratic chirp waveform with an instantaneous frequency of sub GHz. We achieve good agreement between theory and experiment, validating the effectiveness of this approach towards realizing high-performance, broad bandwidth, nearly user-defined RF waveform generation.

We report a broadband radio frequency (RF) channelizer with up to 92 channels using a coherent microcomb source. A soliton crystal microcomb, generated by a 49 GHz micro-ring resonator (MRR), is used as a multi-wavelength source. Due to its ultra-low comb spacing, up to 92 wavelengths are available in the C band, yielding a broad operation bandwidth. Another high-Q MRR is employed as a passive optical periodic filter to slice the RF spectrum with a high resolution of 121.4 MHz. We experimentally achieve an instantaneous RF operation bandwidth of 8.08 GHz and verify RF channelization up to 17.55 GHz via thermal tuning. Our approach is a significant step towards the monolithically integrated photonic RF receivers with reduced complexity, size, and unprecedented performance, which is important for wide RF applications ranging from broadband analog signal processing to digital-compatible signal detection.

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

A numerical approach for generating a limited number of water demand scenarios and estimating their occurrence probabilities in a Water Distribution Network (WDN) is proposed. This approach makes use of the demand scaling laws in order to consider the natural variability and spatial correlation of nodal consumptions. The scaling laws are employed to determine the statistics of nodal consumption as a function of the number of users and the main statistical features of the unitary user's demand. Besides, consumption at each node is considered to follow a Gamma probability distribution. A high number of groups of cross-correlated demands, i.e., scenarios, for the entire network were generated using Latin Hypercube Sampling (LHS) and the numerical procedure proposed by Iman and Conover. The Kantorovich distance is used to reduce the number of scenarios and estimate their corresponding probabilities, while keeping the statistical information on nodal consumptions. By hydraulic simulation, the whole number of generated demand scenarios was used to obtain a corresponding number of pressure scenarios on which the same reduction procedure was applied. The probabilities of the reduced scenarios of pressure were compared with the corresponding probabilities of demand.

This article presents a unique set of voltage and current data from a public building and acquired using a hybrid measurement solution that combines Python and Grafana. The transversal purpose consists of contributing to the community with a vision of the quality of the supply more oriented to the monitoring of the state of the network, providing a more realistic vision, which allows a better understanding, and the adoption of the best decisions to achieve the efficient energy management and thus optimize the operation and maintenance of power systems. The work focuses on higher order statistical estimators that, combined with exploratory data analysis techniques, improve the characterization of the shape of the stress signal. These techniques and data, together with the acquisition and monitoring system, present a unique combination in the line of low-cost measurement solutions. It also incorporates the underlying benefit of the contribution to industrial benchmarking. The paper also includes a computational comparison between Python and LabVIEW to elicit the performance of the measurement solution.

In today’s business landscape, customer retention has become a critical factor for sustainable growth. Many companies continue to focus on acquisition, which leads to high costs and constant customer turnover. This article highlights the importance of retention, proposing a shift in focus toward loyalty as the key to maximizing customer lifetime value (LTV). Improving retention not only increases LTV but also reduces acquisition costs, enhances virality, and provides financial stability. This paper introduces a scientific approach that allows companies to identify the underlying causes of low retention through observation, hypothesis formulation, and controlled experimentation. Using tools such as data analysis and A/B testing, companies can iteratively optimize their retention strategy, adjusting interventions in real-time based on the results obtained. Continuous experimentation emerges as an indispensable tool for navigating market complexity, enabling organizations to learn and adapt quickly. This data-driven approach not only improves retention but also drives long-term growth by building strong relationships with customers. In an increasingly competitive environment, companies that prioritize retention and experimentation are better positioned to achieve resilient and profitable growth.

Interoperable multilayer networks are pivotal and transformative in public digital health. They not only enhance the delivery of healthcare services but also contribute significantly to improving public health outcomes. Through better accessibility, efficiency, and data-driven decision-making, these networks are revolutionizing how we approach public health. The seamless data exchange and integration they facilitate across different healthcare systems and providers can lead to substantial cost savings for public healthcare systems. These networks pave the way for a more efficient and effective healthcare system by reducing redundancies, optimizing resource allocation, and minimizing unnecessary procedures. This study combines the pressing issues of public digital health with the innovative interpretation of multilayer network theory, proposing practical solutions that inspire academics and practitioners alike.Public digital health is not just about improving care access and patient engagement. It is also about ensuring the financial sustainability of our healthcare systems. Innovative multilayer network analysis is critical in this game, improving interoperability and reducing spatial and temporal constraints. These networks streamline processes and improve efficiency by easing complex interactions within healthcare systems. This process, in turn, allows healthcare providers to deliver high-quality care at a lower cost, transforming, whenever possible, in-patients and out-patients into home-patients. Networks are a cornerstone and a beacon of hope for transforming public digital health. They are increasing the Value for Money and enhancing a patient-centric approach, making us optimistic about the future of healthcare.This study shows that revolutionizing digital healthcare methodologies has a profound impact on crucial elements like resilience, interoperability, and patient well-being within public health. The enhancement of interoperability facilitates the smooth flow of data exchange across various platforms and healthcare providers, fostering improved collaboration and decision-making processes and elevating the safety of patients.

The search for growth and sustainability in any organization largely depends on its ability to carry out digital transformation and agility processes. These processes are essential to adapt to an increasingly changing and competitive business environment, allowing companies to be more efficient and effective in creating an unbreakable bond with their customers. This manuscript addresses the importance of detecting and eliminating anti-patterns in organizational culture for a successful digital and agile transformation. During the early stages of the transformation process, prejudices and paradigms rooted in the organization can become an obstacle to change. The goal of this writing is to offer a practical guide for leaders and teams in organizations seeking successful cultural transformation. Effective strategies are proposed to overcome the challenges faced by organizations during this early stage. In summary, the key steps to be followed in the initial stages of digital transformation with agility are described, including the importance of establishing strong leadership, defining a clear vision and scope of the transformational process, among others. A set of recommendations will be provided to overcome recurring anti-patterns, such as lack of stakeholder participation and commitment, lack of proper planning, and confusion of roles and responsibilities.

Despite decreasing anthropogenic mercury (Hg) emissions in Europe and the banning and restriction of many persistent organic pollutants (POPs) under the Stockholm Convention, Mediterranean marine mammals still have one of the highest body burdens of persistent pollutants in the world. Moreover, the Mediterranean basin is one of the most sensitive to climate change, with likely changes in the biogeochemical cycle and bioavailability of Hg, primary productivity, and the length and composition of pelagic food webs. The availability of food resources for marine mammals is also affected by widespread overfishing and the increasing number of alien species colonizing the basin. After reporting the most recent findings on the biogeochemical cycle of Hg in the Mediterranean Sea and the physico-chemical and bio-ecological factors determining its exceptional bioaccumulation in odontocetes, this review discusses possible future changes in the bioavailability of the metal. Recent ocean-atmosphere-land models predict that in mid-latitude seas, water warming (which in the Mediterranean is 20% faster than the global average) is likely to decrease the solubility of Hg and favor the escape of the metal to the atmosphere. However, the basin has been affected for thousands of years by natural and anthropogenic inputs of metals, and climate change with sea level rise (3.6 ± 0.3 mm year-1 in the last two decades) and the frequency of extreme weather events will likely remobilize large amount of legacy Hg from soils, riverine and coastal sediments. Moreover, possible changes in pelagic food webs and food availability could determine dietary shifts and lower growth rates in Mediterranean cetaceans, increasing their Hg body burden. Although adult marine mammals have evolved the ability to detoxify monomethylmercury (MMHg) and store the metal in the liver and other organs as insoluble Hg-Se crystals, in Mediterranean populations more exposed to the metal, this process can deplete the biological pool of Se, increasing their susceptibility to infectious diseases and autoimmune disorders. Mediterranean mammals are also among the most exposed in the world to legacy POPs, micro- and nanoplastics and contaminants of emerging interest. Concomitant exposure to these synthetic chemicals may pose a much more serious threat than the Se depletion. Unfortunately, as shown by literature data summarized in this review, the most exposed populations are those living in the NW basin, the main feeding and reproductive area for most Mediterranean cetaceans, declared a sanctuary for their protection since the 2002. Thus, while emphasizing the adoption of all available approaches to mitigate anthropogenic pressure with fishing and maritime traffic, it is recommended to direct future research efforts towards the assessment of possible biological effects, at individual and population level, of chronic and simultaneous exposure to Hg, legacy POPs, contaminants of emerging interest and microplastics.

With the term neuroinflammation has defined the typical inflammatory response of the brain closely related to the onset of many neurological diseases. Neuroinflammation is well known, but its mechanisms and pathways are not entirely comprehended. Currently, some progress has been achieved through many efforts and research. Consequently, new cellular and molecular mecha-nisms, diverse from conventional ones, are emerging. In listing some of those that will be the sub-ject of our description and discussion, essential are the important role of peripheral and infiltrated monocytes and clonotypic cells, alterations in gut/brain axis, dysregulation of the apelinergic sys-tem, as well as changes in the endothelial glycocalyx of blood-brain barrier, variation in expres-sion of some genes and levels of the encoding molecules by microRNAs (miRNAs), or other epige-netic factors and distinctive transcriptional factors, as well as the role of autophagy, ferroptosis, sex differences and modifications in the circadian cycle. Such mentioned mechanisms can add significant pieces in understanding the complex etiological puzzle of neuroinflammation. In addi-tion, they could represent biomarkers and targets of neurodegenerative diseases, in increase in our old populations.

This study investigates the integration of natural intelligence (NI) and artificial intelligence (AI) within traditional firms, proposing a multilayer network framework to enhance economic value. The research explores the central question: How can the integration of NI and AI, facilitated by copula nodes, drive economic value creation in digitized firms? Through empirical testing across multiple industries—namely manufacturing, retail, and finance—the study evaluates the cost-benefit improvements associated with AI adoption. The findings reveal substantial efficiency gains, improved decision-making, and notable cost reductions, validating the proposed model's predictions. The study emphasizes the critical role of copula nodes in optimizing interactions between NI and AI, ensuring that their integration yields maximum economic benefits. By providing a novel framework for quantifying AI's economic impact within digitized firms, this research fills a significant gap in the literature on multilayer networks and intelligent systems. The practical implications are profound, offering a strategic pathway for firms to enhance profitability and competitiveness in the digital age.

Audio recording in classrooms is a common practice in educational research, with applications ranging from detecting classroom activities to analysing student behaviour. Previous research has employed neural networks for classroom activity detection and speaker role identification. However, these recordings are often affected by background noise that can hinder further analysis, and the literature has only sought to identify noise with general filters and not specifically designed for classrooms. Although the use of high-end microphones and environmental monitoring can mitigate this problem, these solutions can be costly and potentially disruptive to the natural classroom environment. In this context, we propose the development of a neural network model that can specifically detect and filter out background noise in classroom recordings. This model would allow the use of lower quality recordings without compromising analysis capability, thus facilitating data collection in natural educational environments and reducing the costs associated with high-end recording equipment.

This manuscript explores the significance of continuous improvement in software development and digital product management, highlighting its role in addressing challenges and achieving superior results in today's dynamic business landscape. Drawing on Lean Thinking and Agile principles, the paper emphasizes the importance of customer focus, multidisciplinary collaboration, respect for people, inspection and adaptation, experimentation, incremental delivery, and continuous feedback in driving continuous improvement. It identifies key problems associated with the lack of continuous improvement, including quality issues, stagnation, inefficiency, lack of learning, lack of participation and collaboration, and lack of adaptability. To overcome these challenges, the paper proposes a solution that leverages agile events and interactions, such as sprint retrospectives and daily scrum meetings, and introduces a "kaizen board" as a visual tool to manage and monitor the continuous improvement process. The manuscript highlights the benefits of continuous improvement in terms of quality enhancement, efficiency gains, improved customer satisfaction, and adaptability to change. It stresses the need for fostering a culture of learning and constant adaptation, and provides insights on applying continuous improvement across different dimensions: product, process, team, and culture. The paper concludes by emphasizing the significance of commitment and active participation from all team members for achieving sustainable progress and success in digital transformation efforts.

Mountain systems within the Mediterranean region, e.g. the Pyrenees, are very sensitive to climate change. In the present study, we quantified the magnitude of extreme precipitation events and the number of days with torrential precipitation (daily precipitation ≥ 100 mm) in all the rain gauges available in the Pyrenees for the 1981-2015 period, analyzing the contribution of the synoptic scale in this type of events. The easternmost (under the Mediterranean influence) and north-westernmost (under Atlantic influence) areas of the Pyrenees registered the highest number of torrential events. The heaviest events are expected in the eastern part, i.e. 400 mm day-1 for a return period of 200 years. Northerly advections over the Iberian Peninsula, which present a low zonal index, i.e. im-plying a stronger meridional component, give rise to torrential events over the western Pyrenees; and easterly advections favour extreme precipitation over the eastern Pyrenees. The air mass travels a long way, from the east coast of North America, bringing heavy rainfall to the western Pyrenees. In the case of the torrential events over the eastern Pyrenees, the air mass causing the events in these areas is very short and originates in the Mediterranean Basin. The NAO index has no influence upon the occurrence of torrential events in the Pyrenees, but these events are closely related to certain Mediterranean teleconnections such as the WeMO

Micro-combs [1-4] - optical frequency combs generated by integrated micro-cavity resonators – offer the full potential of their bulk counterparts [5,6], but in an integrated footprint. The discovery of temporal soliton states (DKS – dissipative Kerr solitons) [4,7-11] as a means of mode-locking micro-combs has enabled breakthroughs in many fields including spectroscopy [12,13], microwave photonics [14], frequency synthesis [15], optical ranging [16,17], quantum sources [18,19], metrology [20,21] and more. One of their most promising applications has been optical fibre communications where they have enabled massively parallel ultrahigh capacity multiplexed data transmission [22,23]. Here, by using a new and powerful class of micro-comb called “soliton crystals” [11], we achieve unprecedented data transmission over standard optical fibre using a single integrated chip source. We demonstrate a line rate of 44.2 Terabits per second (Tb/s) using the telecommunications C-band at 1550nm with a spectral efficiency – a critically important performance metric - of 10.4 bits/s/Hz. Soliton crystals exhibit robust and stable generation and operation as well as a high intrinsic efficiency that, together with a low soliton micro-comb spacing of 48.9 GHz enable the use of a very high coherent data modulation format of 64 QAM (quadrature amplitude modulated). We demonstrate error free transmission over 75 km of standard optical fibre in the laboratory as well as in a field trial over an installed metropolitan optical fibre network. These experiments were greatly aided by the ability of the soliton crystals to operate without stabilization or feedback control. This work demonstrates the capability of optical soliton crystal micro-combs to perform in demanding and practical optical communications networks.

We demonstrate a photonic RF integrator based on an integrated soliton crystal micro-comb source. By multicasting and progressively delaying the input RF signal using a transversal structure, the input RF signal is integrated discretely. Up to 81 wavelengths are provided by the microcomb source, which enable a large integration time window of ~6.8 ns, together with a time resolution as fast as ~84 ps. We perform signal integration of a diverse range of input RF signals including Gaussian pulses with varying time widths, dual pulses with varying time intervals and a square waveform. The experimental results show good agreement with theory. These results verify our microcomb-based integrator as a competitive approach for RF signal integration with high performance and potentially lower cost and footprint.

Different polyurethanes (PUs) were synthesized with polycarbonate polyols of molecular weights 500, 1000 and 2000 Da. Their self-healing abilities at 20 °C were tested and their structural, thermal, and mechanical properties were analyzed. The PUs made with polycarbonates of molecular weights 500 (YC500) and 1000 Da (YC1000) exhibited self-healing at 20 °C and the self-healing time of YC1000 was the shortest. The high mobility of the short polymeric chains, the absence of crystallinity and the low degree of micro-phase separation favored self-healing at 20 °C in YC500. However, the presence of tack and the existence of allophanate species and urethane-carbonate and urea-carbonate hydrogen bonds disfavored self-healing. Consequently, the self-healing time at 20 °C of YC500 was longer than expected. On the other hand, YC1000 exhibited an “equilibrium” between the urethane-carbonate and urea-carbonate hydrogen bonds and carbonate-carbonate interactions among the soft segments, so a particular structural order was produced which was associated to its fastest self-healing at 20 °C. The PU made with the polycarbonate of molecular weight 2000 Da did not exhibit self-healing at 20 °C because its significant micro-phase separation and the presence of semi-crystalline soft domains.

Two polyurethanes (PUs) were similarly synthesized by reacting a cycloaliphatic isocyanate with 1,4 butanediol and two polyols of different nature (polyester, polycarbonate diol) with molecular weights of 1000 Da. The PU made with polycarbonate diol polyol (YCD) was the only showing intrinsic self-healing at 20 °C. For assessing the mechanism of intrinsic self-healing of YCD, a structural characterization by molecular weights determination, infrared and X-ray photoelectronic spectroscopies, differential scanning calorimetry, X-ray diffraction, thermal gravimetric analysis and dynamic mechanical thermal analysis was carried out. It was concluded that the self-healing at 20 °C of YCD was due to non-covalent dynamic exchange interactions among the carbonate groups of the soft segments. Therefore, the chemical nature of the polyol played a key role in developing PUs with intrinsic self-healing at 20 °C.

We consider an evolutionary model of social coordination in a 2x2 game where two groups of players prefer to coordinate on different actions. Players can pay a cost to learn their opponent's group: if they pay it, they can condition their actions on the groups. We assess the stability of outcomes in the long-run using stochastic stability analysis. We find that three elements matter for the equilibrium selection: the group size, the strength of preferences, and the information's cost. If the cost is too high, players never learn the group of their opponents in the long-run. If one group is stronger in preferences for its favorite action than the other, or its size is sufficiently large compared to the other group, every player plays that group's favorite action. If both groups are strong enough in preferences, or if none of the group's size is large enough, players play their favorite actions and miscoordinate in inter-group interactions. Lower levels of the cost favor coordination. Indeed, when the cost is low, in inside-group interactions, players always coordinate on their favorite action, while in inter-group interactions, they coordinate on the favorite action of the group that is stronger in preferences or large enough.

The Steepest Descent (or Ascent) algorithm is one of the most widely used algorithms in Science, Technology, Engineering, and Mathematics (STEM). However, this powerful mathematical tool is neither taught nor even mentioned in K12 education. We study whether it is feasible for elementary school students to learn this algorithm, while also aligning with the standard school curriculum. We also look at whether it can be used to create enriching activities connected to children’s real-life experiences, thus enhancing the integration of STEM and fostering Computational Thinking. To address these questions, we conducted an empirical study in two phases. In the first phase, we tested the feasibility with teachers. In a face-to-face professional development work-shop with 457 mathematics teachers actively participating using an online platform, we found that after a 10-minute introduction they could successfully apply the algorithm and use it in a couple of models. They were also able to complete two complex and novel tasks: selecting models and adjusting the parameters of a model that uses the steepest descent algorithm. In a second phase, we tested the feasibility with 90 fourth graders from 3 low Socioeconomic Status (SES) schools. Using the same introduction and posing the same questions, we found that they were able to understand the algorithm and successfully complete the tasks on the online platform. Additionally, we found that close to 75% of the students completed the two complex modeling tasks and performed similarly to the teachers.

The Steepest Descent (or Ascent) algorithm is one of the most widely used algorithms in Science, Technology, Engineering, and Mathematics (STEM). However, this powerful mathematical tool is neither taught nor even mentioned in K12 education. We study whether it is feasible for elementary school students to learn this algorithm, while also aligning with the standard school curriculum. We also look at whether it can be used to create enriching activities connected to children’s real-life experiences, thus enhancing the integration of STEM and fostering Computational Thinking. To address these questions, we conducted an empirical study in two phases. In the first phase, we tested the feasibility with teachers. In a face-to-face professional development work-shop with 457 mathematics teachers actively participating using an online platform, we found that after a 10-minute introduction they could successfully apply the algorithm and use it in a couple of models. They were also able to complete two complex and novel tasks: selecting models and adjusting the parameters of a model that uses the steepest descent algorithm. In a second phase, we tested the feasibility with 90 fourth graders from 3 low Socioeconomic Status (SES) schools. Using the same introduction and posing the same questions, we found that they were able to understand the algorithm and successfully complete the tasks on the online platform. Additionally, we found that close to 75% of the students completed the two complex modeling tasks and performed similarly to the teachers.

Mexico has a great diversity of cacti, however, many of their fruits have not been studied in greater depth. Several bioactive compounds available in cacti juices extract have demonstrated nutraceutical properties. Two cactus species are interesting for their biologically active pigments, which are chico (Pachycereus weberi (J. M.Coult.) Backeb)) and jiotilla (Escontria chiotilla (Weber) Rose)). Hence, the goal of this work was to evaluate the bioactive entities, i.e., betalains, total phenolic, vitamin C, antioxidant activity, and mineral content in the extract of the above-mentioned P. weberi and E. chiotilla. Then, clarified extracts were evaluated for their antioxidant activity and cytotoxicity (cancer cell lines) potentialities. Based on the obtained results, Chico fruit extract was found to be a good source of vitamin C (27.19±1.95 mg L-Ascorbic acid/100g fresh sample). Moreover, chico extract resulted in a high concentration of micronutrients, i.e., potassium (517.75±16.78 mg/100 g) and zinc (2.46±0.65 mg/100 g). On the other hand, Jiotilla has a high content of biologically active pigment, i.e., betaxanthins (4.17±0.35 mg/g dry sample). The antioxidant activities of clarified extracts of chico and jiotilla were 80.01±5.10 and 280.88±7.62 (DPPH method), respectively. From the cytotoxicity perspective against cancer cell lines, i.e., CaCo-2, MCF-7, HepG2, and PC-3, the clarified extracts of chico showed cytotoxicity in CaCo-2 (49.7±0.01) and MCF-7 (45.56±0.05). Normal fibroblast cell line (NIH/3T3) was used as a control for comparison purposes. While, jiotilla extract had cytotoxicity against HepG2 (47.31±0.03) and PC-3 (53.65±0.04). These results demonstrated that Chico and jiotilla are good resources of biologically active constituents with nutraceuticals potentialities.

We explores the relational, dynamic elements of Complex Buildings, a type of architecture designed to incubate uses, located in urban areas with high housing density. The uses of Complex Buildings concern different elements, including the network of agents using or managing them, the environment, and the activities and functions that take place occasionally, temporarily or permanently. Data was gathered through ethnographic research lasting 6 months and a chronotopian approach was used to describe time and space. We analyzed and discussed the interaction of the elements of Complex Buildings through a cellular automaton model, a computational method that simulates the growth of complex systems. It was used here to generate patterns that suggest configurations of uses that can optimize management and therefore increase economic and social capital. The cellular automaton model was also used to develop an abstraction of the Centquatre, a public cultural center in Paris. This center is a good example of a Complex Building, being based on a public-private partnership and having an architectural configuration designed to host a wide range of art, social and productive activities. The building includes a large central space used as an urban public area open to different types of people. The importance of this case study lies in its capacity to produce economic value by combining different uses, and also by welcoming different people to the public space. Regarding the building as a living organism, the cellular automaton model reveals the determinant nature of the concepts of configuration, compatibility of uses and economic value generated by the presence of people. We argue that this approach makes it possible to show that the space-time design and public space dimensions are determinant factors in Complex Buildings.

Numerous studies on evaporative cooling systems have been conducted globally, but there is a scarcity of investigations in eastern Africa. The few studies undertaken in this region have primarily focused on their application in food storage and preservation, rather than for building purpose. The goal of this study is to review the most recent advancements in evaporative cooling technology, which would be relevant in eastern Ethiopia and could provide adequate cooling, give adequate thermal comfort, use less energy, and minimize environmental effect in hot and dry areas. There aren't many studies on evaporative cooling systems for building applications in Eastern Africa as a whole, thus this review has taken into account studies conducted in regions with climates similar to eastern Ethiopia. This study covers the classification, operation, and performance of evaporative cooling systems in hot and dry climate. Evaporative cooling systems work well in hot and dry climates, as revealed by this review study.

COVID-19 was a terrible worldwide pandemic that caused a global public health crisis, with numerous deaths and a severe economic depression. To suppress the spread of COVID-19 and initiate patient isolation and contact tracing to reduce its effect, early diagnosis was required, with real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test being the most widely used. However, the RT-PCR test was sometimes found to be lengthy and inaccurate and; for that reason, in many cases of severe complications of COVID-19 pneumonia, chest screening with radiography imaging was preferred. In this paper, we carried out a study for COVID-19 detection from computed tomography images, and compared the obtained results using deep learning (DL) and support vector machine (SVM). The findings showed that, despite the excellent results shown by deep learning, the accuracy in predicting COVID-19 using SVM, in the presence of small databases, was slightly higher than DL. The execution time using SVM was also shorter

The textile and clothing (T&amp;C) industry, despite its significant contribution to the European economy, is one of the most polluting industries globally. Therefore, the EU's Green Deal has identified the T&amp;C sector as a strategic area for allocating public funding and transitioning towards a circular economy (CE). In this context, the “Circular Design for Natural Fibers” project, financed by the PNRR MICS “Made in Italy Circolare e Sostenibile” programme, focuses on enhancing the use of natural fibrous material, related by-products and waste from local production chains. In the research, a crucial aspect is the evaluation of the effectiveness of circularity through life cycle approaches, such as LCA, LCC, S-LCA and LCSA, for environmental, economic and social sustainability evaluation, respectively. A systematic review was carried out, to provide a synthesis of the available scientific evidence regarding the life cycle approaches in the international/national context within the production, processing, and post-consumer supply chains of natural fibers. The study identifies gaps in the literature on life cycle evaluation approaches for natural fibers. Specifically, the LCA approach appears preponderant compared to the others. The paper offers insights for researchers and professionals interested in improving the sustainability of natural fiber production processes and the evaluation of their overall sustainability.

The article analyzes Bernoulli 's binary sequences in representation of empirical events about the distribution of natural resources and population sizes. Considering the event as a nonlinear system, and consisting of two dependent random variables, with memory and probabilities in maximum finite or infinite lengths, constant and equal to ½ for both variables (stationary process). The expressions of the possible trajectories remain constant in sequences that are repeated alternating the presence or absence of one of the variables at each iteration (asymmetric). There are constant oscillations in the event except if the variables X₁ and X₂ are regulated as a function of time Y. It is observed that the variables X₁ and X₂ assume in time T_k → ∞ specific behaviors (geometric variable) that can be used as management tools for random systems. In this way, the article seeks to know from this analyzes, the maximum entropy of information in the system by a theoretical view and how to model resources distribution or containment in the given problem.

Cities require flexible and participatory planning methodologies to address complex and evolving urban challenges. In Italy, the legislative framework is defined at the Regional level, according to the National laws and jurisprudence. The Lombardy region introduced the Planning Document (PD) in the Territorial Government Plan (PGT), as a strategic tool capable of adapting to changes. Based on a strategic vision, this document is useful to guide concrete actions for urban transformation, actively involving stakeholders, including citizens. The PD has the role to translate the political program into an urban planning design. So, the role it has is both technical and political. The political dimension is usually deepened in the strategic component of the document. Following the formation process of the whole city plan, the authors define the key strategies in the PD for a healthier urban future for the city of Voghera. It emerges as a balanced urban development that combines economic growth, environmental preservation, and community well-being. In the paper the authors synthesize the Voghera’s PD as an example of strategic planning that interacts with the practical planning actions and that guides both the public and the private decisions about the city development towards a healthier city.

In manufacturing chatter is an unwanted phenomenon that can lead to product quality reduction and tool wear. Real time chatter detection is key to preventing these issues and improving overall machining efficiency. In this paper we propose an unsupervised chatter detection method using autoencoders (AE) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm that uses internal signals of Computer Numerical Control (CNC) machines. The proposed method starts by using an AE to extract features from raw internal signals collected from CNC machines. This step reduces the dimensionality of the data and captures the underlying patterns of chatter. Then the extracted features are fed into DBSCAN clustering algorithm which is a density based algorithm that groups similar data points and identifies outliers. We tested the proposed method with real world data collected from various CNC machines. The results show that our unsupervised chatter detection method has high accuracy, precision and recall, can detect chatter and distinguish it from normal machining. Also the method is robust to noise and can adapt to dynamic machining conditions. In summary our work presents an unsupervised chatter detection method using AE and DBSCAN clustering that uses internal signals of CNC machines. This method is a reliable and efficient solution for real time chatter detection so manufacturers can improve product quality, optimize machining process and reduce tool wear during machining.

The present study aims at investigating the relationship between Initial Public Offerings (IPOs) variables mainly underpricing on one hand, and the brand value measures on the other. Our final data set is 104 international brand companies. We implement empirical approach using hierarchical OLS regression and descriptive statistics. We show that underpricing is positively related to brand value which emphasizes the marketing role of going public and underpricing in enhancing brand equity through the product market, which additionally confirms some information asymmetry models. We also find that on average brand companies had not been recognized as brands at the IPO time. Moreover, we show the positive role of private equity in enhancing brand value, additionally, the non-linear association between underpricing and brand value is not evident. Finally, we draw some policy implication and suggestions for future research.

Glucose is a simple sugar molecule. The sugar molecule is chemically symbolised as C6H12O6. This means that the glucose molecule contains 6 carbon atoms (C), 12 hydrogen atoms (H) and 6 oxygen atoms (O). In human blood, the molecule glucose circulates as blood sugar. Normally after eating or drinking, our body breaks down the sugars in food and uses them to obtain energy for our cells. To do this, our pancreas produces insulin. Insulin "pulls" sugar from the blood and puts it into the cells for use. If someone has diabetes, their pancreas can't produce enough insulin. As a result, the level of glucose in the blood rises. This can lead one to many potential complications, including blindness, disease, nerve damage, amputation, stroke, heart attack and damage to blood vessels etc. In this study, a non-invasive method for monitoring blood glucose has been developed and is therefore easily usable. The device developed can measure the glucose level continuously and eliminates the disadvantages of the invasive system. Near-IR sensors (optical sensors) were used to estimate the concentration of glucose in the blood; these sensors have a wavelength of 940 nm. The sensor is placed on the tip of the finger and the output of the optical sensor is then connected to the microcontroller at the analogue input. Another sensor used, but only to provide more medical information was the heartbeat sensor. After processing and regression analysis, the glucose level is predicted, and data is sent via the Bluetooth network to a developed APP. The results of the implemented device were compared with available invasive methods. The study consists of a hardware platform inserted into an armband and then a small black parallelepiped-shaped box in which the optical sensors are inserted. The hardware consists of a microcontroller, a Near-IR optical sensor, a heartbeat sensor and a Bluetooth module.

Visual thinking leverages spatial mechanisms in animals for navigation and reasoning. Therefore, given the challenge of abstract mathematics and logic, spatial reasoning-based teaching strategies can be highly effective. Our previous research verified that innovative box and ball coloring activities help teach elementary school students complex notions like quantifiers, logical connectors, and dynamic systems. However, given the richness of the activities, correction is slow, error-prone, and demands high attention and cognitive load from the teacher. Moreover, feedback to the teacher should be immediate. Thus, we propose to provide the teacher with real-time help with LLMs. We explored various prompting techniques with and without context Zero shot, Few shot, Chain of Thought, Visualization of Thought, Self Consistency, logicLM and Emotional to test GPT-4o’s visual, logical, and correction capabilities. We obtained that Visualization of Thought and Self Consistency techniques enabled GPT-4o to correctly evaluate 90% of logical-spatial problems that we tested. Additionally, we propose a novel prompt combining some of these techniques that achieved 100% accuracy on a testing sample, excelling in spatial problems and enhancing logical reasoning.

The innate immune system is the first line of defense against pathogens. It’s composition includes barriers, mucus and other substances as well as phagocytic and other cells. The purpose of the paper is to analyze in general grounds the immune system and the body immunity to cancer. Simple ideas and the qualitative theory of differential equations are used along with general principles such as the minimization of the pathogen load and economy of resources. In the simplest linear model, the annihilation rate of pathogens in any tissue should be greater than the pathogen’s average rate of growth. When nonlinearities are added, a reference value for the number of pathogens is set, and a stability condition emerges, which relates strength of regular threats, barrier height and annihilation rate. On the other hand, in cancer immunity, the linear model leads to an expression for the lifetime risk, which accounts for both the effects of carcinogens (endogenous or external) and the immune response. The stability condition allows a comparison of immunity in different tissues. The way the tissue responds to an infection shows a correlation with the way it responds to cancer. These statements are formulated at the qualitative level, but may and deserve to be quantitatively checked.

In sustainable agriculture, plant nutrients are the most important elements. Biofertilizers introduce microorganisms that improve the soil nutrients and increase their accessibility to crops. In order to meet the demands of a growing population, healthy crops need to be produced using the right type of fertilizers to provide them with all the major nutrients they require. However, an increasing dependency on chemical fertilizers is destroying the environment and negatively af-fecting the health of humans. Thus, using microbes as bioinoculants as the best replacement of chemical fertilizers as eco-friendly way for plant growth and soil fertility is believed to be the best method for improving plant growth and soil fertility. In sustainable agriculture, these microbes provide significant benefits to crops. In addition to colonizing plant systems (epiphytic, endo-phytic, and rhizospheric), beneficial microbes play a key role in absorbing nutrients from surrounding ecosystems. Plant associate microbes can promote plant growth regardless of natural and extreme conditions. Plant growth promoting microbes promote plant growth through a variety of direct and indirect methods, such as nitrogen fixation, plant growth hormone production, siderophores, HCN, several hydrolytic enzymes, and potassium, zinc, and phosphorus solubilization. Research on biofertilizers has been extensive and even available, which demonstrates how these microbes can deliver nutrients to crops in sufficient quantities to enhance their yield. This review examines in detail the direct and indirect mechanisms of PGPR action and their interaction in plant growth and resistance.

To identify soil microbial communities, it is essential to understand their phenotypic and genetic characteristics. Plant growth-promoting rhizobacteria (PGPR) are bacteria capable of promoting plant growth. In addition, rhizobacteria also serve as biological control agents. In addition to fixing atmospheric nitrogen, solubilising insoluble phosphate and secreting hormones such as indoloacetic acid, kinetics and gibberellins, plant growth-promoting rhizobacteria help plants grow directly. Furthermore, they facilitate plant growth indirectly by inducing systemic resistance, siderophores, antibiotics, lytic enzymes, hydrogen cyanide production and stress regulation. This review examines in detail the direct and indirect mechanisms of PGPR action and their interaction in plant growth and resistance.

In this study electrophoretic deposition (EPD) technique is used to prepare chitosan-based coatings with enhanced antibacterial activity suitable for bone implants applications. We designed, prepared and compared physic-chemical and biological properties of coatings obtained with commercial chitosan, chitosan enriched with silver nanoparticles and chitosan obtained from insects. With the aim to consider the sustainability issue, silver nanoparticles were directly prepared in the chitosan solution by laser ablation in liquid technique, avoiding the use of chemicals and limiting the production of wastes. Moreover, a sustainable source of chitosan such as Hermetia Illucens exuviae was considered. The EPD process was optimized by adjusting parameters like voltage and deposition time to achieve ideal coating thickness and adhesion. The prepared films were characterized by spectroscopic and microscopic techniques such as SEM, XRD, and FTIR. Antimicrobial tests against E. coli and S. aureus revealed that silver nanoparticles enhanced the antibacterial properties of the polymer, whereas biological evaluation using the WST8 test on MG63 human osteoblasts-like cells showed that all coatings are non-toxic. Finally, chitosan obtained from insect showed comparable properties with respect to the commercial polymer, suggesting it could replace seafood-derived chitosan in biomedical applications, whereas the Ag@chitosan composite demonstrated superior antibacterial activity without compromising its biocompatibility.

The scratch test consists in pushing a tool across the surface of a material at a given penetration depth or applied load. It has several applications in Science and Engineering including strength testing, damage and quality control of thin films and coatings. Despite numerous attempts in scientific literature, the application of scratch test to characterizations of fracture properties remains a heavily controversial topic. Therefore, this investigation arises as an experimental study in order to assess the fracture toughness using scratch test. A study on the effect of cryogenic treatment, performed after tempering, on fracture toughness, via scratch test experiments, of different tool steels has been made. A laboratory investigation on AISI D2, AISI M2 and X105CrCoMo18 steel confirms the possibility of increasing the fracture toughness by carrying out the cryogenic treatment after the usual heat treatment

Chipman contends, in stark contrast to the conventional view, that utility is not a real number but a vector and is inherently lexicographic in nature. According to these views, it will be proved that, for every preordered topological space (X,≾,t), the assumption t to be finer than the order topology t≾ on (X,t), i.e. t⊇t≾, and the assumption the quotient topology t∣∼≾ that is defined on the preordered set (X∣∼,≾∣∼) of indifference classes of ≾ to be Hausdorff imply that a cardinal number κ and a (complete) preorder ≲ on {0,1}κ that is coarser than the lexicographical ordering ≤lex on {0,1}κ, i.e. ≤lex⊂≲, can be chosen in such a way that there exists a continuous order-embedding ϑ:(X,≾,t)⟶({0,1}κ,≲,t≤lex). This theorem will be compared with a theorem that, in particular, describes necessary and sufficient conditions for ≾ to have a continuous multi-utility representation.

This study addresses the influence of working conditions on Work-Related Quality of Life (WRQOL) among Spanish healthcare professionals. The research seeks to elucidate the mediating roles of job engagement and burnout, and the moderating effects of resilience and self-efficacy, in this relationship. Methods: The study included 374 healthcare workers from Spain, encompassing physicians, nurses, and nursing assistants. It employed a methodological approach using validated instruments to assess psychosocial risks, work-life quality, job engagement, burnout, and resilience. Data were gathered through self-reported questionnaires. Results: Key findings indicate a negative association between working conditions and WRQOL. Job engagement and burnout significantly mediated this relationship, accounting for 19% to 33% of the variance in WRQOL. Notably, lack of support emerged as a strong negative factor for work-related quality of life. Additionally, resilience moderated the relationship between lack of support and burnout. Conclusions: The study concludes that improving working conditions could increase WRQOL. Interventions aimed at enhancing engagement and addressing burnout may be effective. The moderating role of resilience suggests that strategies to enhance resilience could also be beneficial. These findings hold significant implications for policy formulation and human resources planning in healthcare, emphasizing the need for enhanced workplace support and the development of resilience among health workers.

Optical artificial neural networks (ONNs) — analog computing hardware tailored for machine learning [1,2] — have significant potential for ultra-high computing speed and energy efficiency [3]. We propose a new approach to architectures for ONNs based on integrated Kerr micro-comb sources [4] that is programmable, highly scalable and capable of reaching ultra-high speeds. We experimentally demonstrate the building block of the ONN — a single neuron perceptron — by mapping synapses onto 49 wavelengths of a micro-comb to achieve a high single-unit throughput of 11.9 Giga-FLOPS at 8 bits per FLOP, corresponding to 95.2 Gbps. We test the perceptron on simple standard benchmark datasets — handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. This performance is a direct result of the record small wavelength spacing (49GHz) for a coherent integrated microcomb source, which results in an unprecedented number of wavelengths for neuromorphic optics. Finally, we propose an approach to scaling the perceptron to a deep learning network using the same single micro-comb device and standard off-the-shelf telecommunications technology, for high-throughput operation involving full matrix multiplication for applications such as real-time massive data processing for unmanned vehicle and aircraft tracking.

Objectives: To assess the short-term impact of a single global stretching session on plantar pressures and lumbar range of motion (RoM) over one week in sedentary university students. Design: A randomised controlled trial with two parallel groups. Participants: Sixty-four university students were randomly assigned to a stretching group or control group. The stretching group received a single session of global stretching and the control group remained seated for the same length of time as the stretching session. Main outcome measures: Lumbar RoM and plantar pressures were assessed before, immediately after, 48 hours after, and 7 days after intervention. Results: Group-by-time interaction was significant for lumbar lateral flexion (p = 0.044), right maximal pressure (p = 0.003), left maximal pressure (p = 0.008), right mean pressure (p = 0.025), left mean pressure (p = 0.002), and maximal pressure minus mean pressure in right foot (p = 0.007). The model with plantar pressures showed a significant difference for group-by-time interaction (p = 0.010).Conclusion: Global stretching seems to counteract the ill-effects of prolonged sitting up to seven days with respect to plantar pressure in standing without improving lumbar ROM

A new discrete distribution for count data called extended biparametric Waring (EBW) distribution is developed. Its name is related to the fact that, in a specific configuration of its parameters, it can be seen as a biparametric version of the univariate generalized Waring (UGW) distribution, a well-known model for the variance decomposition into three components: randomness, liability and proneness. Unlike the UGW distribution, the EBW can model both overdispersed and underdispersed data sets. In fact, the EBW distribution is a particular case of a UWG distribution when its first parameter is positive; otherwise, it is a particular case of a Complex Triparametric Pearson (CTP) distribution. Hence, this new model inherits most of their properties and, moreover, it helps to solve the identification problem in the variance components of the UGW model. We compare the EBW with the UGW by a simulation study, but also with other over and underdispersed distributions through the Kullback-Leibler divergence. Additionally, we have carried out a simulation study in order to analyse the properties of the maximum likelihood parameter estimates. Finally, some application examples are included which show that the proposed model provides similar or even better results than other models, but with fewer parameters.

The current management of colorectal cancer liver metastasis (CRCLM) patients involves a multidisciplinary approach with surgical resection remaining the primary curative option. The advances in liver surgery have improved outcomes, enabling more patients to undergo surgery successfully. In addition, the development of imaging software has improved the preoperative planning and patient selection for surgery and other interventions. Systemic therapies, such as targeted therapies and immunotherapies have enhanced the chances of complete resection. Targeted agents in combination with chemotherapy, have shown efficacy in downstaging tumors and increasing resectability.

Beetles are by far one of the most successful and diverse insect species. A part of this success is attributed to their elytra which provide various functions such as protection to their bodies from mechanical forces and the harmful environmental factors. In this study, Stag beetle (Lucanus cervus) elytra were first examined for their overall flexural properties and were observed to have a localized shape retaining snap-through mechanism which could play a crucial role in energy absorption, e.g. during battles and falls from heights. The snap-through mechanism was validated using theoretical calculations and also finite element simulations. Elytra were also characterized to examine their puncture and wear resistance. Our results show that elytra resisted puncture up to a force of 1.8±0.4 N and have puncture resistance compared to that of commercially available puncture resistant gloves. The measured values of modulus and hardness of elytra exocuticle were 10.3±0.8 GPa and 0.7±0.1 GPa. Using the hardness to modulus ratio as an indicator of wear resistance, the estimated value was observed to be in the range of wear resistant biological materials. Thus, our study demonstrates different mechanical properties of the stag beetle elytra which can be explored to design shape retaining bio-inspired composites with enhanced puncture and wear resistance.

The present study investigates the impact of electrode surface roughness on the electrofreezing of water. This research focuses on how the electrode roughness induced by a laser treatment affects the nucleation and growth of ice crystals under controlled electric fields. To achieve this, a series of experiments were conducted using deionized water samples placed between electrodes with varying surface roughness. The electrodes, fabricated with the Al6061 T6 alloy were structured via the Laser Shock Processing (LSP) method. For this purpose, the pulsed densities during the LSP process were varied from 900 to 2500 pulses/cm2. The increase of the pulse density was correlated to the surface structuring and to the microstructural features and average roughness of the LSP-treated Al6061 alloy. A wavy-like microstructure was induced upon the LSP treatment with average roughnesses between ~ 3.5 and 6 µm at the selected pulse densities. The results indicate that electrode roughness significantly influences the electrofreezing process. Rougher electrodes were found to lower the nucleation temperature compared to smoother ones, suggesting enhanced ice nucleation activity. The findings are attributed to the increased electric field concentration at the asperities of the rough surfaces, which may facilitate the alignment of water molecules and the formation of critical ice nuclei.