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 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.

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

In some applications of microgrid and distributed generation, it is required to feed islanded or stand-alone loads with high-quality voltage to provide low total harmonic distortion (THD). To fulfil these demands, an LC filter is connected to the output terminals of power electronics converters. A cascaded voltage and current control loop with pulse-width modulation schemes are used to regulate the voltage and current in these systems. However, these strategies have some drawbacks, particularly when multiple-input multiple-output plants (MIMO) are controlled using single-input single-output (SISO) design methods. This methodology usually produces a sluggish transient response and cross-coupling between different control loops. In this paper, a model predictive control (MPC) strategy based on the concept of optimal switching sequences (OSS) is designed to control voltage and current in an LC filter connected to a three-level neutral-point clamped converter. The strategy solves two well-formulated optimisation problems to achieve control of the LC filter variables and the voltages of the DC-link capacitors. Hardware-in-the-Loop (HIL) results are obtained to validate the feasibility of the proposed strategy, using a PLECS-RT HIL platform and a DSP Microlab Box controller. In addition to the good dynamic performance of the proposed OSS-MPC, it is demonstrated by the HIL results that the control algorithm is capable of obtaining low total harmonic distortion (THD) in the output voltage for different conditions.

Repeated exposure to environmental ozone causes a chronic state of oxidative stress. This state is present in chronic degenerative diseases and induces a loss of control of the inflammatory response. The dysfunction of redox system and failures in control the inflammatory responses are involved in a vicious circle that maintains and increases the degenerative process. Intestine also responds to secondary reactive species formed by exposure to ozone doses, generating noxious stimuli that increase degenerative damage. This review aims to elucidate how environmental pollution, mainly by ozone, induces a state of chronic oxidative stress with the loss of regulation of the inflammatory response, both in the intestine and in the brain, where the functionality of both structures is altered and plays a determining role in some neurodegenerative and chronic degenerative diseases. For this purpose, we searched for information on sites like the Cochrane Library Database, PubMed, Scopus, and Medscape. Reviewing the data published, we can conclude that environmental pollutants are a severe health problem. Ozone pollution has different pathways of action, both molecular and systemic, and participates in neurodegenerative diseases such as Parkinson's and Alzheimer's disease as well in bowel diseases as Inflammatory Bowel Disease, Crohn's Disease and Irritable Bowel Syndrome.

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.

Molecular dynamics simulation is currently the theoretical technique eligible to simulate a wide range of systems from soft condensed matter to biological systems. However, of the excellent results that the technique has arrogated, this approach remains computationally expensive, but with the emergence of the new supercomputing technologies bases on graphics processing units graphical processing units-based systems GPUs, the perspective has changed. The GPUs allow performing large and complex simulations at a significantly reduced time. In this work, we present recent innovations in the acceleration of molecular dynamics in GPUs to simulate non-Hamiltonian systems. In particular, we show the performance of measure-preserving geometric integrator in the canonical ensemble, that is, at constant temperature. We provide a validation and performance evaluation of the code by calculating the thermodynamic properties of a Lennard-Jones fluid. Our results are in excellent agreement with reported data reported from literature, which were calculated with CPUs. The scope and limitations for performing simulations of high-throughput MD under rigorous statistical thermodynamics in the canonical ensemble are discussed and analyzed.

Amphibians are widely known as a prolific source of bioactive metabolites. In this work we isolated and characterized compounds with antiparasitic activity from the oocytes of the toad Rhinella alata collected in Panama. Bio-guided isolation and structural elucidation was carried out using chromatographic and spectroscopic techniques. The organic crude extract was subjected to solid phase extraction followed by HPLC purification of the fraction with in vitro activity against Trypanosoma cruzi trypomastigotes. Seven steroids (1-7) of the bufadienolide family were isolated and their structures determined using NMR and MS analyses; of these 19-formyl-dyscinobufotalin (3) is reported as a new natural product. Compounds 1, 3-7, resulted with a good anti-trypanosomal activity profile, among these 16β-hydroxyl-hellebrigenin (1) and bufalin (7) showed significant selectivity for T. cruzi. Furthermore, molecular docking analysis showed compounds 1, 3 and 7 interact through H-bonds with the amino acid residues GLN-19, ASP-158, HIS-159 and TRP-177 from cruzipain, at the catalytic site. Given the lack of therapeutic options to currently treat the American trypanosomiasis, this work can serve as the basis for further studies that aim the development of bufadienolides or their derivatives as drugs against Chagas disease.

Crohn's disease (CD) results from an aberrant immune response against commensal microbiota in genetically susceptible hosts. However, the nature of immune defects, the microflora involved, and genetic susceptibility remain incompletely defined and controversial. This review seeks to describe the present state of association between CD and renal disease; moreover, we highlight the convergence of CD with amyloidosis that can trigger sustained inflammation, producing the pathological alteration observed in both diseases. The following MESH terms were searched in PubMed, PubMed Central (PMC), and Web of Science: “Crohn´s disease” and “renal disease.” The R RISmed package was used for PubMed and PMC. The abnormal humoral immune response is described along with alterations in immune cell migration mechanisms in CD during inflammation.

This article theoretically derives the magnetic field and vector potential produced by a steady current I flowing in an arbitrary plane loop at an arbitrary point r. Numerical examples are presented to demonstrate the behavior of the magnetic field produced by loops of various shapes such as polygons, circles, ellipses, and p-norm balls. Taking the limit as the loop shrinks to a point and the current I grows to infinity so that the magnetic dipole moment m of the loop (defined as the current I times the vector area of the loop) is kept constant, the magnetic field and vector potential are theoretically shown to converge to those of an ideal point magnetic dipole m.

In this paper a dynamic relationship between the CO2 emissions in Finland, Norway and Sweden is presented. With the help of a VAR(2) model, and using the Granger terminology, it is shown that the emissions in Finland are affecting those in Norway and Sweden. Other aspects of this dynamic relationship are presented as well.

The focus of this work lies in the construction of monitoring system designed in the form of a patch using a long-lasting potentiometric electrolyte concentration sensor from metal electrodes, in a galvanic cell configuration Mg(s)|NaCl(aq)|Cu(s). Initially, a mathematical analysis was conducted on the expected sensor output through the Nernst equation. The experimental phase involved conducting controlled tests in the laboratory using various molar concentrations of sodium chloride (NaCl) in aqueous solution. Results showed that the electrolyte sensor allows for monitoring electrolyte levels in NaCl in the range of 0.02 to 1 M/L, with electrode lifespan exceeding 10 days. On the other hand, when patch is using human sweat during controlled exercise routines, it showed the sensor's capability for monitoring changes in the subjects' hydration levels in real time. The sensor output potential is greater than 1.7 volts when the sensor electrodes are in contact with human sweat, which is equivalent to measuring molar concentrations at normal hydration and moderately high hydration levels. Sensor results indicate that the system can function in a self-powered manner without external batteries. Additionally, the extended lifespan of its electrodes allows for continuous monitoring of imbalances in the human body, showcasing the system capability for long-term health assessment.

Primary hyperoxalurias (PHs) are a group of inherited alterations of the hepatic glyoxylate metabolism. PHs classification based on gene mutations parallel a variety of enzymatic defects, and all involve the harmful accumulation of calcium oxalate crystals that produce systemic damage. These geographically widespread rare diseases have a deep impact in the life quality of the patients. Until recently, treatments were limited to palliative measures and kidney/liver transplants in the most severe forms. Efforts made to develop pharmacological treatments succeeded with the biotechnological agent lumasiran, a siRNA product against glycolate oxidase, which has become the first effective therapy to treat PH1. However, small molecule drugs have classically been preferred since they benefit from experience and have better pharmacological properties. The development of small molecule inhibitors designed against key enzymes of glyoxylate metabolism is on the focus of research. Enzyme inhibitors are successful and widely used in several diseases and their pharmacokinetic advantages are well known. In PHs, effective enzymatic targets have been determined and characterized for drug design and interesting inhibitory activities have been achieved both in vitro and in vivo. This review describes the most recent advances towards the development of small molecule enzyme inhibitors in the treatment of PHs, introducing the multi-target approach as a more effective and safe therapeutic option.

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 > 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.

Pyrolysis is a combustion process of woody biomass conducted under low or no oxygen conditions. New innovations and the need to limit open burning has resulted in numerous mobile and fixed plant pyrolysis methods that burn a variety of woody residues. Production technologies that reduce the need for open burning, the main source of potential pollutants, fall under the regulations in the Clean Air Act of 1990. This Act is the legal instrument to regulate air pollution at its source across the United States of America and it is implemented and enforced through the Environmental Protection Agency, in coordination with sister agencies. One newer innovation for reducing woody residues and emissions is an air curtain incinerator. Currently, the Clean Air Act regulates stationary solid waste incinerators, and this is also applied to mobile air curtain incinerators burning woody biomass. However, other woody biochar production methods (e.g., flame cap kilns) are not subject to these regulations. Discrepancies in the interpretation of definitions related to incineration and pyrolysis and the myriad of differences related to stationary and mobile air curtain incinerators, type of waste wood from construction activities, forest residues, and other types of clean wood make the permitting regulations confusing as permits can vary by jurisdiction. This review summarizes the current policies, regulations, and directives related to in-woods biochar production and the required permits.

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.

A remarkable strengths of deep neural networks lies in their ability to discover patterns and representations from complex data. Deep learning models can learn and refine features at different levels of abstraction, enabling them to handle complex tasks in computer vision recognition, natural language processing, and speech recognition. The ability to generalize from examples, coupled with the capacity to process vast amounts of data, empowers deep learning to achieve state-of-the-art results across a wide spectrum of applications. An argument for this ability is based on similarities between deep neural networks and the nervous system. In this report, we argue that despite the remarkable performance of deep learning, there are still gaps between deep learning and the nervous system that needs to be closed to enable deep learning doing tasks that currently only the nervous system can perform

This paper presents a critical review of key issues related to the emergence of new networks for the spread of zoonotic diseases amid the mass extinction of species. Zoonotic and infectious diseases account for approximately 70% of new and existing diseases affecting humans and animals. The initial section argues that the term "zoonoses" should not be confined to single-cause events within veterinary medicine. Instead, zoonoses should be viewed as complex, systemic phenomena shaped by interrelated factors, including environmental, sociocultural, and economic elements, influenced by anthropogenic climate change. The second section presents bioethical principles and potential strategies for those engaged in zoonotic disease prevention. The third section uses the slaughter of animals in disaster settings as a case study to illustrate the need for further clarification of normative and interspecies justice conflicts in One Health ethics. This section concludes with an outlook on "zoonoethics." Section four develops the analysis of the interlinked elements that trigger zoonoses and examines antimicrobial resistance (AMR) from an ethical and political standpoint, concluding with policy recommendations for addressing AMR. Section five offers a critical reflection, integrating contributions from zoonoethics, human ecology, and the ecotheological turn. Finally, section six concludes with a call to action and policy recommendations for an inclusive, intercultural, and gender-sensitive One Health approach.

In previous studies, drones have been used to carry out visual inspections of heritage elements. In order to complement the information obtained with the common drone, a new underwater drone model is proposed for the specific case of old bridges. The aim is to verify the applicability of underwater drones for the inspection of submerged elements of old heritage bridges, given the large number of bridge disasters and collapses linked to failures in their foundations. To this end, we carried out an underwater inspection of the visible submerged elements (submerged but not buried) of three old bridges crossing different rivers. The different locations and characteristics of these bridges allow us to draw some initial conclusions. The results of the operations carried out show that underwater drones are not only useful for this type of inspection, but that the work is much safer than with the means currently used (underwater divers). In addition, the use of drones makes it possible to study certain parameters that can anticipate subsequent foundation problems affecting the entire bridge, such as the settlement or rotation of piers or abutments.

Crohn's disease (CD) results from an aberrant immune response against the commensal microbiota in genetically susceptible hosts. However, the nature of the immune defects, the microflora involved and the genetic susceptibility remain incompletely defined and controversial. Extraintestinal manifestations occur in up to 25-35% of patients and generally precede the onset of gastrointestinal symptoms, which are often of a colonic nature and are influenced by disease activity. Renal manifestations can be considered dependent on the same immune mechanism that determines inflammatory bowel disease in CD. This review seeks to describe the current state of association between CD and kidney disease.

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

Pencil-beam Doppler scatterometers are a promising remote sensing tool for measuring ocean vector winds and currents from space. While several point designs exist in the literature, these designs have been constrained by the hardware they inherited, and the design is sub-optimal. Here, I present guidelines to optimize the design of these instruments starting from the basic sensitivity equations. Unlike conventional scatterometers or pencil-beam imagers, appropriate sampling of the Doppler spectrum and optimizing the radial velocity error lead naturally to a design that incorporates a pulse-to-pulse separation and pulse length that vary with scan angle. Including this variation can improve radial velocity performance significantly and the optimal selection of system timing and bandwidth is derived. Following this, optimization of the performance based on frequency, incidence angle, antenna length, and spatial sampling strategy are considered. It is shown that antenna length influences the performance most strongly, while the errors depend only on the square root of the transmit transmit power. Finally, a set of example designs and associated performance are presented.

The importance of knowing the advance time in drip irrigation lines lies in its precision, as this influences the proper management of water and nutrients delivery. The mathematical calculation to determine the advance time is based on the general hydraulic flow equation, which relates the fluid velocity and the cross-sectional area of the pipe to the volume of water flowing through it. However, in irrigation pipes, where the flow is a mixture of dripper properties, its pressure, the approach to solving the advance time is different, as it is the sum of individual advance times for each segment. To address this issue, Python 3.11 was used along with various libraries such as Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn to create a modeling environment and run algorithms that could predict outcomes. A program was developed that calculates the advance time for each segment of the drip line using partial velocities, and a dataset was generated that was used to train and test machine learning models. Several machine learning algorithms such as Linear Regression, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Decision Trees, and Random Forests were implemented to predict the advance time. Additionally, SciPy optimize was used to obtain multivariable equations that describe the advance time in drip irrigation lines. Results showed that the dripper flow has the greatest influence on the advance time, followed by the diameter and distance. Decision Tree and SVM models had the best accuracy with scores above 98%. Equations were found to calculate the advance time in the complete drip line and in 95% of its length, with coefficients of determination close to 99.33%. This study demonstrated the importance of understanding the relationship between dripper parameters and travel time in drip irrigation, as well as the utility of machine learning and optimization tools for predicting and modeling this phenomenon.

Exercise induced bronchoconstriction (EIB) is a common complication of athletes and individuals who exercise regularly. It is estimated that about 90% of patients with underlying asthma experience EIB. Sex differences in the prevalence of asthma have been widely reported, with higher rates in boys vs. girls before puberty, and higher rates in women than men after puberty. Because atopy has been reported to occur at higher rates in athletes than in non-athletes, in this study we investigated sex differences in EIB and atopy in athletes. A systematic literature review identified 60 studies evaluating EIB and/or atopy in post-pubertal adult athletes (n=7501). Collectively, these studies reported: 1) a 23% prevalence of EIB in athletes; 2) a higher prevalence of atopy in male athletes vs. females; 3) a higher prevalence of atopy in athletes with EIB; and 4) a significantly higher rate of atopic EIB in male vs. female athletes. Our analysis indicates that the physiological changes that occur during exercise may differentially affect male and female athletes, and suggest an interaction between male sex, exercise, and atopic status in the course of EIB. Understanding these sex differences is important to provide personalized management plans to athletes with underlying asthma and/or atopy.

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.

Alcohol use disorder (AUD) is a chronically relapsing disease characterized by loss of control in seeking and consuming alcohol (ethanol) driven by recruitment of brain stress systems. However, AUD differs among the sexes: men are more likely to develop AUD, but women progress from casual to binge drinking and heavy alcohol use more quickly. The central amygdala (CeA) is a hub of stress and anxiety, with corticotropin releasing factor (CRF)-CRF1 receptor and GABAergic signaling dysregulation occurring in alcohol dependent male rodents. However, we recently showed that GABAergic synapses in female rats are less sensitive to the acute effects of ethanol. Here, we used patch clamp electrophysiology to examine the effects of alcohol dependence on the CRF-modulation of rat CeA GABAergic transmission of both sexes. We found that GABAergic synapses of naïve female rats were unresponsive to CRF application compared males, although alcohol dependence induced a similar CRF responsivity in both sexes. In situ hybridization revealed that females had less CeA neurons containing mRNA for the CRF1 receptor (Crhr1) than males, but in dependence, the percentage of Crhr1-expressing neurons in females increased, unlike males. Overall, our data provide evidence for sexually dimorphic CeA CRF system effects on GABAergic synapses in dependence.

The stimulus-secretion coupling of glucose-induced release is generally attributed to the metabolism of the hexose in the β-cells in the glycolytic pathway and the citric acid cycle. Glucose metabolism generates an increased cytosolic concentration of ATP and of the ATP/ADP ratio that closes the ATP-dependent K+-channel at the plasma membrane by the interaction of ATP with the regulatory Kir6.2 channel subunit The resultant depolarization of the β-cells opens voltage-dependent Ca2+-channels at the plasma membrane that allow an increase of the cytosolic cation concentration that triggers the exocytosis of insulin secretory granules. The resultant secretory response evolves in time as a biphasic secretion with a first and transient peak of approximately 10 minutes duration followed by a sustained phase of secretion lasting as long as the stimulus. Whereas the first transient peak can be reproduced by a simple depolarization of β-cells with high extracellular KCl maintaining the KATP-channels open with diazoxide, the sustained phase is agreed to depend on the participation of some metabolic signal that remains to be determined Our group has been investigating for several years the participation of β-cell GABA metabolism, together with that of glucose (the β-cell “specific” nutrient secretagogue) and some other “metabolic” secretagogues (branched-chain alpha-ketoacids and a mixture of L-Leucine + L-glutamine, at supraphysiological concentrations) in their mechanism of stimulation of insulin secretion. All three types of stimuli promote the flux in the GABA shunt of rat islets by different metabolic pathways that end in the production of α-ketoglutarate. This citric acid cycle intermediary is preferentially derived to the GABA shunt instead of its continuous oxidation in the citric acid cycle. Islet content of GABA is significantly suppressed by all the stimuli and blocking the GABA shunt with gabaculine, or ϒ-vinyl-GABA (GABAT inhibitors), diminish the insulin secretory responses as well as total ATP and the ATP/ADP ratio. It is concluded that GABA metabolism is increased in parallel to glucose metabolism and is significantly contributing to the magnitude of the insulin secretory response. Its possible implication in β-cells degradation in type-2 (perhaps also in type 1) diabetes is suggested.

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.

Chronic obstructive pulmonary disease (COPD) is a multifactorial lung inflammatory disease affecting 174 million people worldwide, with a recently reported increased incidence in female patients. Patients with COPD are especially vulnerable to the detrimental effects of environmental exposures, especially from air particulate and gaseous pollutants. Exposure to air pollution severely influences COPD outcomes, resulting in acute exacerbations, hospitalizations, and death. In the current study, we conducted a review of the literature addressing air pollution induced acute exacerbations of COPD (AECOPD) in order to determine whether air pollution affects COPD patients in a sex-specific manner. We found that while the majority of studies enrolled both male and female patients, only a few reported results disaggregated by sex. Most studies had a higher enrollment of male patients, only four compared AECOPD outcomes between sexes, and only one study identified sex differences in AECOPD, with females displaying higher rates. Overall, our analysis of the literature confirmed that air pollution exposure is a trigger for AECOPD hospitalizations and revealed a significant gap in our knowledge of sex-specific effects of air pollutants on COPD outcomes, highlighting the need for more studies considering sex as a biological variable.

We aimed to delineate cardiopulmonary interactions in acute bronchiolitis and to evaluate the capacity of a combined cardiopulmonary ultrasonography to predict the need for respiratory support. This was a prospective observational single-center study that includes infants < 12 month of age admitted to a hospital due to acute bronchiolitis. All the included patients under-went clinical, laboratory and cardiopulmonary ultrasonographic evaluation at the same time point within 24 hours of hospital admission. The existence of significant correlation between car-diac and respiratory parameters was the primary outcome. The association of different cardio-pulmonary variables with the need of respiratory support higher than O2, the length of stay hos-pitalization, the PICU stay, and the duration of respiratory support were a secondary outcome. We enrolled 112 infants (median age 1 (0.5-3) months; 62% males) hospitalized with acute bron-chiolitis. Increased values of the pulmonary variables (BROSJOD score, pCO2 and LUS) showed moderate correlations with NT-proBNP and all echocardiographic parameters indicative of pulmonary hypertension and myocardial dysfunction. Up to 36 (32%) infants required respira-tory support during the hospitalization. This group presented with higher lung ultrasound score (p<0.001), and increased values of Tei index (p<0.001) and pulmonary artery pressures (p<0.001). All the analyzed respiratory and cardiac variables showed moderate to strong correlations with the LOS hospitalization and the time of respiratory support. Lung ultrasound and echocardiog-raphy showed a moderate to strong predictive accuracy for the need of respiratory support in the ROC analysis, with AUC varying from 0.74 to 0.87. Conclusion: Those cases of bronchiolitis with a worse pulmonary status presented with a more impaired cardiac status. Cardiopulmonary ul-trasonography could be a good strategy to easily identify high-risk population for a complicated acute bronchiolitis hospitalization.

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.

Ocean surface currents and winds are tightly coupled essential climate variables, and, given their short time scales, observing them at the same time and resolution is of great interest. DopplerScatt is an airborne Ka-band scatterometer that has been developed under NASA's Instrument Incubator Program (IIP) to provide a proof of concept of the feasability of measuring these variables using pencil-beam scanning Doppler scatterometry. In the first half of this paper, we present the Doppler scatterometer measurement and processing principles, paying particular attention to deriving a complete measurement error budget. Although Doppler radars have been used for the estimation of surface currents, pencil-beam Doppler Scatterometry offers challenges and opportunities that require separate treatment. The calibration of the Doppler measurement to remove platform and instrument biases has been a traditional challenge for Doppler systems, and we introduce several new techniques to mitigate these errors when conical scanning is used. The use of Ka-band for airborne Doppler scatterometry measurements is also new, and, in the second half of the paper, we examine the phenomenology of the mapping from radar cross section and radial velocity measurements to winds and surface currents. To this end, we present new Ka-band Geophysical Model Functions (GMF's) for winds and surface currents obtained from multiple airborne campaigns. We find that the wind Ka-band GMF exhibits similar dependence to wind speed as that for Ku-band scatterometers, such as QuikSCAT, albeit with much greater upwind-crosswind modulation. The surface current GMF at Ka-band is significantly different from that at C-band, and, above 4.5 m/s has a weak dependence on wind speed, although still dependent on wind direction. We examine the effects of Bragg-wave modulation by long waves through a Modululation Transfer Function (MTF), and show that the observed surface current dependence on winds is consistent with past Ka-band MTF observations. Finally, we provide a preliminary validation of our geophysical retrievals, which will be expanded in subsequent publications. Our results indicate that Ka-band Doppler scatterometry could be a feasible method for wide-swath simultaneous measurements of winds and currents from space.

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.

The Mexican Soil Mesh (MSMx) web service emerges as a pivotal tool for researchers, farmers, and policymakers in the efficient management of extensive soil databases. Built on a responsive and intelligent web design, MSMx synchronizes seamlessly with the SQL language, allowing users to selectively download variables tailored to their studies at the desired spatial scale. The programmatic structure enhances query speed, optimizes development times, and incorporates satellite programming modules for effective handling of the vast soil dataset. This paper high-lights the key features, benefits, and applications of MSMx, emphasizing its role in facilitating data-driven decision-making processes and promoting sustainable soil management practices on the continental shelf of Mexico.

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).

Non-coding RNAs (ncRNAs) comprise a diverse class of non-protein coding transcripts that regulate critical cellular processes associated with cancer. Advances in RNA-sequencing (RNA-Seq) have led to the characterization of non-coding RNA expression across different types of human cancers. Through comprehensive RNA-Seq profiling, a growing number of studies demonstrate that ncRNAs, including long non-coding RNA (lncRNAs) and microRNAs (miRNA), play central roles in progenitor B-cell Acute Lymphoblastic Leukemia (B-ALL) pathogenesis. Furthermore, due to their central roles in cellular homeostasis and their potential as biomarkers, the study of ncRNAs continues to provide new insight into the molecular mechanisms of B-ALL. This article reviews the ncRNA signatures reported for all B-ALL subtypes, focusing on technological developments in transcriptome profiling and recently discovered examples of ncRNAs with biologic and therapeutic relevance in B-ALL.

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.

Databases are by far the most valuable asset of companies. Since the need was seen not only to count but also to have some type of record of elements such as crops, animals, money, properties and that this record could be consulted and modified according to the situation, that is where the first database was born. , and after that, these databases cannot be disorganized, they also need to be managed and administered under established standards that facilitate their understanding and management not only by their creators but by the other people who subsequently administer them. Databases and database management systems have an interesting evolutionary history that deserves to be analyzed and this is the objective of this document, where it is sought to understand. Along with databases and their management systems, data mining or Data mining arises that in order not to extend ourselves so much, it is the job of finding common patterns in various data sources and in what way they can be used to predict situations or results of various circumstances; We also focus on the other topic that we will present, Oracle data mining, which roughly is to merge data mining with Oracle, which makes it a powerful tool for obtaining information and predicting results based on statistics.In this article we will study and analyze the ideas, concepts and basic examples that make up SGBD and Data Mining and, we will try to go deeper into this topic, the use of decision techniques such as advanced statistical algorithms. We also present a fictitious example of the application of these techniques: predicting which products can be sold based on their relationship with others. we will give a brief explanation of association rules, data mining cycle and the types of learning and the evolution that data mining has had.

The mechanisms underlying the establishment of asymmetric structures during development remain elusive. The wing of Drosophila is asymmetric along the Anterior-Posterior (AP) axis, despite that its growth signals that drive its growth are presumably symmetric. Here, we investigated the contribution of cell recruitment, a process that drives wing fate differentiation in Drosophila, to the asymmetric shape and pattern of the adult wing. Genetic impairment of cell recruitment results in a significant reduction in adult wing asymmetry, primarily affecting the region between longitudinal vein 5 and the wing margin (L5-M). Morphometric analysis reveals that the lack of cell recruitment results in a more symmetric wing with respect to the AP, suggesting a contribution of cell recruitment to the establishment of asymmetry in the adult wing. A close examination of the expression of the wing selector gene vestigial (vg) in wing disc does not support this hypothesis. However, the circularity of the Vg pattern significantly increase in recruitment-impaired wing disc, suggesting that while the decrease of the L5-M region in the adult wing may not be attributed to cell recruitment, it could contribute to the overall asymmetry of the adult wing. We conclude that cell recruitment, a widespread mechanism that participates in growth and patterning of several developing systems, could drive, at least partially, the asymmetric shape of the Drosophila wing.

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.

Parallel manipulators with multiple end-effectors bring us interesting advantages over conventional parallel manipulators such as improved manipulability, workspace and avoidance of singularities. In this work the kinematics of a five-bar planar parallel manipulator equipped with two end-effectors is approached by means of the theory of screws. As an intermediate step the displacement analysis of the robot is also investigated. The input-output equations of velocity and acceleration are systematically obtained by resorting to reciprocal-screw theory. In that regard the Klein form of the Lie algebra se(3) of the Euclidean group SE(3) plays a central role. In order to exemplify the method of kinematic analysis, a case study is included. Furthermore, the numerical results obtained by means of the theory of screws are confirmed with the aid of special software like ADAMS.^TM

Corruption is a legal and moral contravention that generates great concern among nations due to its erosive effects on economic growth, democracy, governance, social equity and the integrity of culture. Therefore, it is necessary to know more about the multiple variables that produce and maintain this phenomenon. This article reports the results of an experimental investigation that sought to provide elements of judgment on the influence of the structure of personal values ​​on the willingness to bribe. For this, 12 couples of young university students of both sexes interacted through a game that simulated a relationship between a corrupter and a corruptible agent, with the help of a real-time communication system, mediated by an online platform, which allowed instant and bidirectional interaction. The couples were randomly constituted and played with each other under double blind. However, the interacting members of the dyad could share values ​​or vary in their axiological structure in such a way that, while one of them could manifest anti-corruption principles, the other's commitment was not so obvious. The results confirm the importance of the axiological structure of people in the facilitation or containment of the corrupt behavior. This article also reflects on the theoretical connotations of the relationships shown.

Background: To analyze long-term outcomes in patients undergoing thoracic endovascular aortic repair (TEVAR). Methods: All consecutive 97 patients undergoing TEVAR between September 2014 and September 2022 were included in the study. Primary outcome was long-term incidence of overall death and major adverse cardiovascular and cerebrovascular events (MACCE). Results: Mean age was 70.4 years, and 22(23.2%) had cerebrovascular disease (CBVD). A total of 49(51.6%) of patients had prior cardiac surgery intervention and 8(8.5%) had prior aortic valve replacement. Twenty-eight patients(28.8%) presented with aortic dissection, 60(61.8%) had aortic aneurysm, 4(4.1%) had intramural hematoma, and 5(5.1%) had other presentations. An emergent procedure was performed in 6(6.2%) patients, an urgent procedure in 37(38.1%) patients and 54(55.7%) patients had an elective procedure. Intraoperatively, 78.3% had percutaneous TEVAR, 5.1% had ministernotomy TEVAR, while 10.3% had concomitant full sternotomy TEVAR repair. Hospital mortality was 7 patients(7.2%). At 8-years follow-up, 76% were alive, 25.8% had MACCE, 21.6% were diagnosed with endoleaks(13 patients type II and 2 patients type 1) while 10.3% un-derwent repeat intervention. Conclusions: This single center experience in patients undergoing TEVAR evidenced good short and long-term survival and MACCE. Nonetheless, almost half of the patients underwent an ur-gent/emergent procedure, clinical results were favourable for TEVAR.

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.

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 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.

Since the recent legalization of medical and recreational use of cannabis (Cannabis sativa L.) in many regions worldwide, there has been high demand for research to improve yield and quality. With the paucity of scientific literature on the topic, this study investigated the relationships between light intensity (LI) and photosynthesis, inflorescence yield, and inflorescence quality of cannabis grown in an indoor environment. After growing vegetatively for 2 weeks under a canopy-level photosynthetic photon flux density (PPFD) of ≈ 425 μmol·m-2·s-1 and an 18-h light/6-h dark photoperiod, plants were grown for 12 weeks in a 12-h light/12-h dark ‘flowering’ photoperiod under canopy-level PPFDs ranging from 120 to 1800 μmol·m-2·s-1 provided by light emitting diodes. Leaf light response curves varied both with localized (i.e., leaf-level) PPFD and temporally, throughout the flowering cycle. Therefore, it was concluded that the leaf light response is not a reliable predictor of whole- plant responses to LI, particularly crop yield. This may be especially evident given that dry inflorescence yield increased linearly with increasing canopy-level PPFD up to 1800 μmol·m-2·s-1, while leaf-level photosynthesis saturated well below 1800 μmol·m-2·s-1. The density of the apical inflorescence and harvest index also increased linearly with increasing LI, resulting in higher-quality marketable tissues and less superfluous tissue to dispose of. There were no LI treatment effects on cannabinoid potency, while there were minor LI treatment effects on terpene potency. Commercial cannabis growers can use these light response models to determine the optimum LI for their production environment to achieve the best economic return; balancing input costs with the commercial value of their cannabis products.

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.

We aimed to provide a comprehensive assessment of exercise physiology of adult Fontan patients (FP) and factors limiting functional capacity (FC). A prospective single-centre study of 37 FP aged ≥16years and 19 healthy-controls (HC), who underwent CPET on cycle-ergometer in February-March 2022. Lung function was impaired in FP, mostly mild restrictive pattern (56.8%). Mean peakVO2 was 21±5.4ml/kg/min, 55% predicted. Morphologically left-single ventricle showed higher peakVO2%predicted (57.4±14.4% vs 43.4±8.1%, p=0.045). A lower peakVO2%predicted was observed in patients with an early flattened and/or descending O2 pulse at maximal exertion (52±14% vs 62±12.5, p=0.04 and 47.6±9% vs 60±14 respectively, p=0.018) and chronotropic insufficiency (53±12% vs 69.8±20%, p=0.008). Strong positive correlation was observed between %OUES and peakVO2%predicted (r=0.726, p>0.001). PeakVO2%predicted was progressively higher as the level of physical activity increased (low-level 49.5±14%, moderate-level 55±12%, intense-level 69±20%). FP showed lower inspiratory muscle strength compared to HC but it was no statistically associated with either peakVO2 or VE/VCO2 slope. In FP OUES is a useful submaximal parameter in those who fail to reach maximal exertion. Chronotropic insufficiency and early flattened or descending oxygen pulse slope were factors associated with low peakVO2. Regular intense physical activity improves FC. Although FP have inspiratory muscle weakness, its impact on FC is unclear.

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.

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.

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.

Since its initial characterization in 2016, the interferon stimulated gene Shiftless (SHFL) has proven to be a critical piece of the innate immune response to viral infection. SHFL expression stringently restricts the replication of multiple DNA, RNA, and retroviruses with an extraordinary diversity of mechanisms that differ from one virus to the next. These inhibitory strategies include the negative regulation of viral RNA stability, translation, and even the manipulation of RNA granule formation during viral infection. Even more surprisingly, SHFL is the first human protein found to directly inhibit the activity of the -1 programmed ribosomal frameshift, a translation recoding strategy utilized across nearly all domains of life and a several human viruses. Recent literature has shown that SHFL expression also significantly impacts viral pathogenesis in mouse models, highlighting its in-vivo efficacy. To help reconcile the many mechanisms by which SHFL restricts viral replication, we provide here a comprehensive review of this complex ISG, its influence over viral RNA fate, and the implications of its functions on the virus-host arms race for control of the cell.

It is commonly believed that exposing Cannabis sativa (cannabis) plants to ultraviolet (UV) radiation can enhance Δ⁹-tetrahydrocannabinol (Δ⁹-THC) concentrations in female inflorescences and associated foliar tissues. However, a lack of published scientific studies has left knowledge-gaps in the effects of UV on cannabis that must be elucidated before UV can be utilized as a horticultural management tool in commercial cannabis production. In this study we investigated the effects of UV exposure level on photosynthesis, growth, inflorescence yield, and secondary metabolite composition of two indoor-grown cannabis cultivars: ‘Low Tide’ (LT) and ‘Breaking Wave’ (BW). After growing vegetatively for 2 weeks under a canopy-level photosynthetic photon flux density (PPFD) of ≈225 μmol·m^–2·s^–1 in an 18-h light/6-h dark photoperiod, plants were grown for 9 weeks in a 12-h light/12-h dark “flowering” photoperiod under a canopy-level PPFD of ≈400 µmol·m^–2·s^–1 and 3.5 h·d^–1 of supplemental UV radiation with UV photon flux densities (UV-PFD) ranging from 0.01 to 0.8 μmol·m^–2·s^–1 provided by light-emitting diodes (LEDs) with a peak wavelength of 287 nm (i.e., biologically-effective UV doses of 0.16 to 13 kJ·m^–2·d^–1). The severity of UV-induced morphology (e.g., whole-plant size and leaf size reductions, leaf malformations, and stigma browning) and physiology (e.g., reduced leaf photosynthetic rate and reduced F_v/F_m) symptoms worsened as UV exposure level increased. While the proportion of dry inflorescence yield that was derived from apical tissues decreased in both cultivars with increasing UV exposure level, total dry inflorescence yield only decreased in LT. The equivalent Δ⁹-THC and cannabidiol (CBD) concentrations also decreased in LT inflorescences with increasing UV exposure level. While the total terpene content in inflorescences decreased with increasing UV exposure level in both cultivars, the relative concentrations of individual terpenes varied by cultivar. The potential for using UV to enhance cannabis quality must still be confirmed before it can be used as a production tool for modern, indoor-grown cannabis cultivars.

Synthetic chalcomenite-type cupric selenite CuSeO₃∙2H₂O has been studied at room temperature under compression up to pressures of 8 GPa by means of single-crystal X-ray diffraction, Raman spectroscopy, and density-functional theory. According to X-ray diffraction, the orthorhombic phase undergoes an isostructural phase transition at 4.0(5) GPa with the thermodynamic character being first-order. This conclusion is supported by Raman spectroscopy studies which have detected the phase transition at 4.5(2) GPa and by the first-principles computing simulations. The structure solution at different pressures has provided information on the change with pressure of unit-cell parameters as well as on the bond and polyhedral compressibility. A Birch-Murnaghan equation of state has been fitted to the unit-cell volume data. We found that chalcomenite is highly compressible with a bulk modulus of 42 – 49 GPa. The possible mechanism driving changes in the crystal structure is discussed, being the behavior of CuSeO₃∙2H₂O mainly dominated by the large compressibility of the coordination polyhedron of Cu. On top of that, an assignation of Raman modes is proposed based upon density-functional theory and the pressure dependence of Raman modes discussed. Finally, the pressure dependence of phonon frequencies is also reported.

This study evaluates inequalities in the use of dental services according to place of birth before and after the economic crisis in Spain. A cross-sectional study was performed in the population aged 18 to 65 years in Spain. We used data from three Spanish National Health Surveys for years 2006 (before the crisis), 2014 and 2017 (after the crisis). Log-binomial regression was used to quantify the association between region of origin and use of dental care services before and after controlling for the selected covariates. In 2006, we found a greater probability of not using dental care services in immigrants from Asia (PR:1.36, 95% CI:1.10–1.67) and Africa (PR:1.16; 95% CI:1.05–1.28) compared to the natives. For 2014, the probability of not using dental care services was greater for all immigrants compared to the natives, with the greatest odds for those from Africa (PR:1.71; 95% CI:1.46–2.01) and Asia (PR:1.3; 95% CI:1.23–1. 47). The associations for 2017 were weaker in magnitude than the ones observed for 2014, although stronger than for 2006. This study suggests that the economic recovery did not have the same impact for natives and immigrants regardless of regions of origin, given the observed inequalities in use of dental services.

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

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.

Generative AI has gained enormous interest nowadays due to new applications like chatGPT, DALL E, Stable Difussion and Deep Fake. Particularly DALL E, Stable Difussion and others (Adobe Firefly, ImagineArt...) are able to create images from a text prompt and are also able to recreate real photographs. Due to this fact, intense research has arisen to create new image forensics applications able to distinguish between real captured images and videos and artificial ones. Detecting forgeries made with Deep Fake is one of the most researched issues. This paper is about another kind of forgery detection. The purpose of this research aims to detect photo realistic AI created images versus real photos coming from a physical camera. For this purpose, techniques that perform a pixel level feature extraction are used. First one is Photo Response Non-Uniformity (PRNU). PRNU is a special noise due to imperfections on the camera sensor that is used for source camera identification. The underlying idea is that AI images will have a different PRNU pattern. Second one is Error level analysis (ELA). This is other type of feature extraction traditionally used for detecting image editions. In fact, ELA is being used nowadays by photographers to detect manually AI created images. Both kinds of features are used to train Convolutional Neural Networks to differentiate between AI images and real photographs. Good results are obtained achieving accuracy rates over 95%. Both extraction methods are carefully assessed by computing precision/recall and F1-score measurements.

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.

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.

The World Health Organization identifies alcohol as a cause in several neoplasias of the oro-pharynx cavity, esophagus, gastrointestinal tract, larynx, liver, or female breast. This study re-views ethanol's nonoxidative and oxidative metabolism and one-carbon metabolism that en-compasses both redox and transfer reactions that influence crucial cell proliferation machinery. Ethanol favors the uncontrolled production and action of free radicals that interfere with the maintenance of essential cellular functions. We focus on the generation of protein, DNA, and lipid adducts that interfere with the cellular processes related to growth and differentiation. Ethanol's effects on stem cells responsible for building and repairing tissues are reviewed. Cancer stem cells suffer disturbances related to the expression of cell surface markers, enzymes, and transcription factors after ethanol exposure with consequent dysregulation of mechanisms related to cancer metastasis or resistance to treatments. Our analysis aims to underlie and discuss potential targets that show more sensitivity to ethanol's action and identify specific metabolic routes and metabolic realms that may be corrected to recover metabolic homeostasis after pharmacological interven-tion. Specifically, research should pay attention to reestablish metabolic fluxes by fine-tuning the functioning of specific pathways related to one-carbon metabolism and antioxidant processes.

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.

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.

The study´s goals were to determine the health status of a group of heart transplant recipients (HTR) and their level of physical activity and to compare the health status among them and with a group of healthy sedentary individuals. Fifty-four HTR and eighteen S were assigned to four groups, according to their level of physical activity (determined with The International Physical Activity Questionnaire); patients with a low, a moderate and a high level of physical activity (HTRL, HTRM and HTRH, respectively) and sedentary individuals (S). Participants underwent a basic blood analysis and several tests to assess their cardiovascular, neuromuscular, functional mobility condition and their quality of life. The S and HTRH were very similar in terms of BP, HR and blood analysis while HTRM and HTRL differed from both S and HTRH in these parameters. Regarding the cardiovascular, neuromuscular, functional mobility, and quality of life variables assessed in this study, HTRH showed the best results across all of them, followed by S, HTRM, and HTRL. It is suggested that the weekly level of physical activity of HTR should be high, what might help them to enhance their health and quality of life.

Alginate-gelatin hydrogels are extensively used in bioengineering. However, despite different formulations being utilized for growing different cell types in vitro, their pH and its effect, together with the crosslinking ions, of those formulations are still infrequently assessed. In this work we studied how these elements can affect hydrogel stability and printability and influence U2OS and NIH/3T3 cell viability and metabolism on the resulting 3D prints. In this context, 6% alginate + 2% gelatin hydrogels were prepared with 0.1 M MES buffer with pH 5.5, 6.5, 7.0 or 8.0, printed by extrusion-based 3D printing, and crosslinked immediately after printing with either CaCl2 or BaCl2. Our results showed that both the buffer pH and the crosslinking ion (Ca2+ or Ba2+) influence the swelling and degradation rates of the prints. Moreover, the buffer pH influenced the printability of the hydrogel in air, but when printed directly in a fluid-phase CaCl2 or BaCl2 crosslinking bath. In addition, both U2OS and NIH/3T3 cells showed greater cell metabolic activity on one-layer prints crosslinked with Ca2+. Besides, Ba2+ increased cell death of NIH/3T3 cells while had no effect on the U2OS cell viability. The pH of the buffer also caused an important impact on the cell behaviour. U2OS cells showed a 2.25-fold cell metabolism increase on one-layer prints prepared at pH 8.0 in comparison to those prepared at pH 5.5. Whereas, NIH/3T3 cells showed greater metabolism on one-layer prints with pH 7.0. Finally, we observed a difference on cell arrangement of the U2OS cells growing on prints prepared from hydrogels with acidic buffer in comparison to cells growing on those prepared using neutral or basic buffer. These results show that both pH and crosslinking ion influence hydrogel strength and cell behaviour.

In this article, we give a brief review of the origin of the neutrino mass in some interesting non-linear supersymmetric models with R-symmetry. These models are able to address and solve the most important problems of the particle physics and provide mechanisms for neutrino mass generation and their mixing parameters in agreement with the current experimental data. Their prediction could be experimentally tested in the near future by collider experiments.

The practice of physical activity is an effective non-pharmacological strategy for preventing and treating chronic diseases. A large body of evidence has contributed to establishing a positive correlation between a physically active lifestyle and health benefits, including enhanced vaccination responses, lower numbers of senescent T-cells, increased T-cell proliferative capacity, lower levels of inflammatory cytokines, and improved neutrophil and macrophage function. While females are generally thought to exert more robust immune responses than males in response to a variety of challenges, and both male and female sex hormones have been suggested as mediators of immune function, research on this topic has not always been designed with a sex-specific lens. The goal of this review is to summarize the available experimental and clinical evidence linking exercise and immune function in male and female subjects, with an emphasis on sex differences and sex-specific mechanisms. Overall, the available evidence indicates that moderate exercise and physical activity improves immune function in both sexes, whereas prolonged and high-intensity exercise temporarily impairs immune responses at a higher degree in females. A role of male and female sex hormones in these sex-specific effects is also discussed.

Autophagy is an essential mechanism to maintain cellular homeostasis. Besides its role in controlling the quality of cytoplasmic components, it participates in nutrient obtaining and lipid mobilization under stressful conditions. Furthermore, autophagy is involved in the regulation of systemic metabolic, a function mainly performed by neuronal populations of the arcuate nucleus of the hypothalamus. Several studies have shown that blockade of autophagy in these neurons can affect central regulation of metabolism and impact body energy balance. Moreover, hypothalamic autophagy can be altered during obesity. However, neurons are not the only cell type involved in the central regulation of metabolism. Astrocytes, essential cells for brain homeostasis, are key metabolic regulators. They can sense metabolic signals in the hypothalamus and modulate systemic functions as glucose homeostasis and feeding response. Moreover, the response of astrocytes to obesity has been widely studied. Astrocytes are important mediators of brain inflammation and can be affected by increased levels of saturated fatty acids associated to obesity. Although autophagy plays important roles for astrocyte homeostasis and functioning, the contribution of astrocyte autophagy to systemic metabolism has not been analysed. Furthermore, how obesity can impact astrocyte autophagy is poorly understood. More studies are needed in other to understand the contribution of astrocyte autophagy to metabolism.

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.

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.

The aim was to examine the sociodemographic predictors associated with changes in movement behaviours (physical activity, screen time and sleep) among toddlers and pre-schoolers during the early stages of the coronavirus disease 2019 pandemic in Chile. Caregivers of 1- to 5-year-old children completed an online survey between March 30th and April 27th, 2020. Information about the child's movement behaviours before (retrospectively) and during the pandemic, as well as family characteristics were reported. In total, 3,157 participants provided complete data (mean children age: 3.1±1.38 years). During early stages of the pandemic, time spent in physical activity decreased, recreational screen time and sleep duration increased, and sleep quality declined. Toddlers and pre-schoolers with space to play at home and living in rural areas experienced an attenuated impact of the pandemic restrictions on their physical activity levels, screen time, and sleep quality. Older children, those whose caregivers had a higher educational level, and children living in apartments had greater changes, mainly a decrease in total physical activity and increase in screen time. This study has shown the significant impact of the pandemic restrictions on movement behaviours in toddlers and pre-schoolers in Chile.

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 contrast to animals, adult organs in plants are not determined during embryogenesis but gen-erated from meristematic cells as plants advance through development. Plant development in-volves a succession of different phenotypic stages and the transition between these stages is termed phase transition. Phase transitions need to be tightly regulated and coordinated to ensure they occur under optimal seasonal, environmental conditions. Polycarpic perennials transition through vegetative stages and the mature, reproductive stage many times during their lifecycles and, in both perennial and annual species, environmental factors and culturing methods can re-verse the otherwise unidirectional vector of plant development. Epigenetic factors regulating gene expression in response to internal cues and external (environmental) stimuli influencing the plant’s phenotype and development have been shown to control phase transitions. How develop-mental and environmental cues interact to epigenetically alter gene expression and influence these transitions are not well understood and understanding this interaction is important considering the current climate change scenarios, since epigenetic maladaptation could have catastrophic con-sequences for perennial plants in natural and agricultural ecosystems. Here we review studies focussing on the epigenetic regulators of the vegetative phase change and highlight how these mechanisms might act in exogenously induced plant rejuvenation and regrowth following stress.

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.

Background: Trigeminal neuralgia associated to vascular compression, by aberrant or ectopic arterial or venous vessels, is a frequent condition in clinical practice. Management with microvascular decompression through a Minimal invasive retrosigmoidal has shown high rates of pain control, with low complication rates and excellent therapeutic results. Objective: To describe the surgical technique and clinical outcomes in terms of pain relief after microvascular decompression for trigeminal nerve, through a minimal invasive retrosigmoidal parasterional burr-hole technique. Methods: A group of patients with trigeminal neuralgia refractory to medical management who underwent microvascular decompression considering outcomes based on Visual Analogue Scale (VAS), and Barrow Neurological Institute Pain Scale (BNIPS). Added to a technical note of the surgical technique for a minimal invasive retrosigmoidal parasterional burr-hole. Results: Twenty-two patients were evaluated, clinical assessment after surgical intervention showed a decrease pain according to VAS, resulting from an average preoperative state of 9.5 ± 0.37 to a postoperative condition of 1.32 ± 1.28, exhibiting statistically significant changes (p < 0.0001, d = 9.356). On the other hand, in relation to the BNIPS scale, a decrease from an average preoperative status of 4.55 ± 0.25, to a postoperative status at 12 months of 1.73 ± 0.54 was also demonstrated, showing significant changes (p < 0.0001, d = 3.960). Conclusion: Microvascular decompression of the trigeminal nerve through a minimal invasive retrosigmoidal parasterional burr-hole is feasible and can be a safe and effective technique for the management of pain.

Metabolic syndrome is a growing global health problem. Evidence suggests that diets rich in phytochemical-containing herbs and spices can contribute to reduced risk of chronic disease. This review assesses the scope of evidence supporting the use of herbs and spices in the diet for prevention or treatment of metabolic syndrome and associated health conditions. A search of PubMed and Scopus databases was carried out to assess the available clinical or cohort evidence for culinary doses of commonly used herbs and spices. Trials that were measuring health factors related to metabolic disorders or the health of individuals with metabolic syndrome or associated diseases were included. Out of a total of 1742 papers identified, there were 146 relevant studies on black pepper, chilli, cardamom, cinnamon, coriander, cumin, fennel, fenugreek, garlic, ginger, Nigella seed, rosemary, sage and turmeric. No relevant research was found for cloves, mint, oregano, parsley or thyme. Cinnamon, fenugreek and ginger were the herbs/spices with the most published trials on them and showed promise for glycaemic control. Cardamom appears to have potential to reduce inflammatory markers, and cinnamon, ginger and turmeric for blood lipids. Patients with type 2 diabetes were the population most likely to be included in studies, but the preventative benefits of herbs/spices in healthy populations were also investigated, particularly for chilli, ginger and cinnamon. There is evidence for the beneficial effect of culinary doses of many common herbs/spices in the prevention and treatment of metabolic syndrome and associated disorders.

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.

This review was written with the aim of examining the effects that caused an insult such as a wound to an organ such as the skin. Before examining the cellular mechanisms relating to wound healing, the reader is invited to read the structure of the skin as a necessary basis for understand-ing the final aim of this review. The structure of the skin as a basis for understanding the phe-nomena relating to wound healing is addressed taking into account updated literature that ad-dresses the numerous problems of the skin microenvironment. Starting from this awareness, the paragraph dedicated to wound healing becomes complicated when this phenomenon is not im-plemented and therefore the problems dedicated to chronic wounds, keloids and hypertrophic scars are addressed, pathologies that are still difficult to understand and treat today.

In this article, we have tried to answer the questions of how an entire city's fiction was created for the development of Japanese American internment camps and in which way contributions of sustainable crafts and even art could have interceded. To this aim, we have searched the literature and reviewed archives, primarily from the American West Coast. We have found that beyond adaptation to the circumstances, the visual representation of the city's settlement, founding, and daily activities, instead of typical panoptic or somber prisons’ imagery, are depicted in the selected images and that their use precisely fostered its sustainability. This leads us to deduce that a "city fiction" was necessary for such survival and endurance and that its artistic representation was primarily involved in the state's ideological apparatus. On the other hand, fissures subtly seethed the violence exerted in the camps by stealth and in a hidden fashion. We have concluded that artistic activity justified the city's fiction, together with other examples, highlighting the conditions of systemic violence and oppression for the inmates. In this framework, the artworks generated constitute a historical document of sustainability.

TThe XPRIZE Foundation designs and operates multi-million-dollar, global competitions to incentivize the development of technological breakthroughs that accelerate humanity toward a better future. To combat the COVID-19 pandemic, the Foundation coordinated with several organizations to make available data sets about different facets of the disease and to provide the computational resources needed to analyze those data sets. This is paper is a case study of the requirements, design, and implementation of the XPRIZE Data Collaborative, a cloud-based infrastructure that enables the XPRIZE to meet its COVID-19 mission and host future data-centric competitions. We examine how a Cloud Native Application can use an unexpected variety of Cloud technologies, ranging from containers, serverless computing, to even older ones like Virtual Machines. We also search and document the effects that the pandemic had on application development in the Cloud. We include our experiences of having users successfully exercise the Data Collaborative, detailing the challenges encountered and areas for improvement and future work.

Carbon (C) is one of the most abundant elements. It is part of all living organisms and is found in all states of matter (solid, liquid, gas, and plasma). It can take the form of one of the hardest and transparent materials (diamond) or it can be flexible and dark ( graphite), with many carbonaceous materials at both extremes. In gaseous form, C is a component of several greenhouse gas emitted during the combustion of fossil fuels. Carbon movement between the atmosphere, land (biosphere and lithosphere), and ocean (hydrosphere) can alter total amounts in each pool. Human activities accelerate C movement into the atmosphere, causing increases in climate change. This shift from terrestrial and oceanic C pools to the atmosphere cause an increase in the intensity and duration of droughts, hurricanes, snowstorms, and other natural phenomenon. Although society hears about C emissions there is a lack of understanding of its importance and the need to decrease C in the atmospheric pool to avoid exacerbating climate change. Forests and biochar are two biological methods to retain C in the terrestrial pool for long time and at very low cost. This review details where C comes from, its relationship with forests, and biochar and their roles in increasing carbon sequestration to limit the impacts of climate change and continue having future sustainable forests and ecosystems services that we enjoy today.

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.

The manuscript delves into the intricacies of food production chains, offering a comprehensive breakdown of their components. Moreover, it sheds light on the initiatives orchestrated by government agencies to endorse sustainable practices and fortify areas of opportunity for producer organizations. While the context paints a broad picture, we contend that, to the best of our knowledge, there exists no comparable publication that succinctly encapsulates the role of government in bolstering food production chains. The document unfolds with a detailed exploration of the interaction mechanisms among the various components of the chain. Subsequently, it introduces a set of twelve elements meticulously outlining the multifaceted role of the government. Each element undergoes thorough scrutiny, fostering a nuanced understanding of the intricate relationship between the food production chain and the government's pivotal role in enhancing stability and efficiency. In conclusion, the manuscript not only lays bare the structural elements of food production chains but also presents a unique and in-depth analysis of the government's role, encapsulated within the framework of twelve essential elements.

The health emergency caused by Covid 19 highlighted the food dependency of many cities in the world and Cali and the cities of Valle del Cauca were no exception as they depended on food flows from other regions and countries, so these Entities are part of the corporate food system, to which their rulers delegated food security for their inhabitants. In the same territory and for the last nine years, a second-level organization has been consolidating that brings together 14 peasant agroecological markets and that despite strict confinement measures was able to continue supplying food to consumers in the municipalities of influence that have supported this initiative. The foregoing leads to think that said organization can become a platform for an agroecological food system of regional scope, for which the characteristics that said system should have according to a model based on the principles of agroecology were evaluated.

In studies of dynamic stability and power quality, it is necessary to know the mechanical parameters that determine the transient response of a wind turbine. The exact value of these parameters is not as decisive as the power curve can be, but an estimate that is far from reality can distort or even invalidate the simulation results. Despite its importance, this information, especially the inertia, but also the stiffness and damping constant of the drive-train, is hardly available for the turbine model under investigation. In this work, the different bibliographical sources that provide values of blade inertia in kg·m2 will be reviewed, and above all, those that provide a distribution of masses along the span of the blade. With this, different reliable relations will be obtained that allow calculating the inertia of the turbine rotor, based on the mass and length of the blade. When the center of gravity is also available, a very correlated expression is provided to obtain the inertia. The even rarer references to the stiffness and damping constant of the drive-train will also be reviewed.

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 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

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.