SARS-CoV-2, the virus that causes theCOVID-19 disease, has been demonstrated to cause immune suppression in certain individuals. This can manifest as a reduced ability for the host's immune system to effectively control the infection. Studies have reported that patients with COVID-19 can exhibit a decline in white blood cell counts, including natural killer cells and T cells, which are integral components of the immune system's response to viral pathogens. These cells play critical roles in the immune response to viral infections, and their depletion can make it harder for the body to mount an effective defense against the virus. Additionally, the virus can also directly infect immune cells, further compromising their ability to function. Some individuals with severe COVID-19 pneumonia may develop a "cytokine storm," an overactive immune response that may result in tissue damage and organ malfunction. The underlying mechanisms of immune suppression in SARS-CoV-2 are not entirely comprehended at this time, and ongoing research is being conducted to gain a more comprehensive understanding. Research has shown that severe SARS-CoV-2 infection promotes the synthesis of IgG4 antibodies. In this work, we propose the hypothesis that the IgG4 antibody produced by B cells in response to infection by SARS-CoV2 generates immunological tolerance that prevents its elimination, and leads to persistence and chronic infection. In sum, we believe that this constitutes another immune evasion mechanism that bears striking similarities to that developed by cancer cells to evade immune surveillance.

Contemporary research has found that people with autism spectrum disorder (ASD) exhibit aberrant immunological function, with a shift toward increased cytokine production and unusual cell function. Microglia and astroglia were found to be significantly activated in immuno-cytochemical studies, and cytokine analysis revealed that the macrophage chemoattractant protein-1 (MCP-1), interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), and transforming growth factor β-1 (TGFB-1), all generated in the neuroglia, constituted the most predominant cytokines in the brain. Taurine (2-aminoethanesulfonic acid) is a promising therapeutic molecule able to increase the activity of antioxidant enzymes and ATPase, which may be protective against aluminum-induced neurotoxicity. It can also stimulate neurogenesis, synaptogenesis, and reprogramming of proinflammatory M1 macrophage polarization by decreasing mitophagy (mitochondrial autophagy) and raising the expression of the markers of the anti-inflammatory and pro-healing M2 macrophages, such as macrophage mannose receptor (MMR, CD206) and IL-10, while lowering the expression of the M1 inflammatory factor genes. Taurine also induces autophagy, which is a mechanism that is impaired in microglia cells and is critically associated with the pathophysiology of the ASD. We hypothesize here that taurine could reprogram the metabolism of M1 macrophages that are overstimulated in the nervous system of people suffering from ASD, thereby decreasing the neuroinflammatory process, neuronal death, and improving cognitive functions. Therefore, we think that taurine can serve as an important lead for the development of novel drugs for the ASD treatment.

For the first time in history, we have witnessed the origin and development of a pandemic. To handle the accelerated accumulation of viral mutations and to comprehend the virus' evolutionary adaptation in humans, an unparalleled program of genetic sequencing and monitoring of SARS-CoV-2 variants has been undertaken. Several scientists have theorized that, with the Omicron surge producing a more contagious but less severe disease, the end of COVID-19 is near. However, by analyzing the behavior shown by this virus for 2 years, we have noted that pandemic viruses do not always show a decreased virulence. Instead, it appears there is an evolutionary equilibrium between transmissibility and virulence. We have termed this concept “intermittent virulence”. The present work analyzes the temporal and epidemiological behavior of SARS-CoV-2 and suggests that there is a high possibility that new virulent variants will arise in the near future, although it is improbable that SARS-CoV-2´s virulence will be the same as was seen during the pandemic phase.

Contrary to the long-held belief that the effects of vaccines are specific for the disease they were created; compelling evidence has demonstrated that vaccines can exert positive or deleterious non-specific effects (NSEs). In this review, we compiled research reports from the last 40 years, showing that live vaccines induce positive NSEs, whereas non-live vaccines induce several negative NSEs, including increased female mortality associated with enhanced susceptibility to other infectious diseases, especially in developing countries. These negative NSEs are determined by the vaccination sequence, the antigen concentration in vaccines, the type of vaccine used (live vs. non-live), and also by repeated vaccination. We do not recommend stopping using non-live vaccines, as they have demonstrated to protect against their target disease, so the suggestion is that their detrimental NSEs can be minimized simply by changing the current vaccination sequence. High IgG4 antibody levels generated in response to repeated inoculation with mRNA COVID-19 vaccines could be associated with a higher mortality rate from unrelated diseases and infections by suppressing the immune system. Since most COVID-19 vaccinated countries are reporting high percentages of excess mortality not directly attributable to deaths from such disease, the NSEs of mRNA vaccines on overall mortality should be studied in depth.

Due to the health crisis caused by SARS-CoV-2, the creation of a new vaccine platform based on mRNA was implemented. Globally, around 13.32 billion COVID-19 vaccine doses of diverse platforms have been given, and up to this date, 69.7% of the total population received at least one injection of a COVID-19 vaccine. Although these vaccines prevent hospitalization and severe forms of the disease, increasing evidence has shown they do not produce sterilizing immunity, allowing people to suffer frequent re-infections. Recent research has also raised concerns that mRNA vaccines could induce immune tolerance, which, added to that caused by the virus itself, could complicate the clinical course of a COVID-19 infection. Furthermore, recent investigations have found high IgG4 levels in people who were administered two or more injections of mRNA vaccines. It has been suggested that an increase in IgG4 levels could have a protecting role by preventing immune over-activation, similar to that occurring during successful allergen-specific immunotherapy by inhibiting IgE-induced effects. Altogether, evidence suggests that the reported increase in the IgG4 levels detected after repeated vaccination with the mRNA vaccines is not a protective mechanism; rather, it may be a part of the immune tolerance mechanism to the spike protein that could promote unopposed SARS-CoV2 infection and replication by suppressing natural antiviral responses. IgG4-induced suppression of the immune system due to repeated vaccination can also cause autoimmune diseases, promotes cancer growth, and autoimmune myocarditis in susceptible individuals.

Background: Post-acute sequelae of SARS-CoV-2 infection (PASC) is a complicated disease that affects millions of people all over the world. Previous studies have shown that PASC impacts 10% of SARS-CoV-2 infected patients of which 50-70% are hospitalized. It has also been shown that 10-12% of those vaccinated against COVID-19 were affected with PASC and its complications. The severity and the later development of PASC symptoms is positively associated with the early intensity of the infection. Results: The generated health complications caused by PASC involve a vast variety of organ systems. Patients affected by PASC have been diagnosed with neuropsychiatric and neurological symptoms. Cardiovascular system also has been involved and several diseases such as myocarditis, pericarditis, and coronary artery diseases were reported. Chronic hematological problems such as thrombotic endothelialitis and hypercoagulability were described as a condition that could increase the risk of clotting disorders and coagulopathy in PASC patients. Chest pain, breathlessness, and cough in PASC patients were associated with respiratory system in long COVID-19 causing respiratory distress syndrome. The observed immune complications were notable, involving several diseases. Renal system also was impacted and result in raising the risk of diseases such as thrombotic issues, fibrosis, and sepsis. Endocrine gland malfunction can lead to diabetes, thyroiditis, and male infertility. Symptoms such as diarrhea, nausea, loss of appetite and taste were also among reported observations due to several gastrointestinal disorders. Skin abnormalities might be an indication of infection and long-term implications such as persistent cutaneous complaints were linked to PASC. Conclusions: Long COVID is a multidimensional syndrome with considerable public health implications, affecting several physiological systems and demanding thorough medical therapy as well as more study to address its underlying causes and long-term effects.

The aim of this work was to describe the physiological limitations induced under drought conditions in young sweet orange trees, including the crop capability to recuperate its physiological status once re-watering, and after a water withholding. The trial was conducted during two consecutive months (July and August) in two-years old sweet orange trees. Three irrigation treatments were arranged: A full irrigation treatment; (FI); a low-frequency deficit-irrigation treatment (LFDI); and a sustained-deficit irrigation (SDI) treatment. The obtained results showed that for Stem values below -1.5 MPa, significant decreases in gas exchange rates, evidencing diffusive limitations to drought stress. Additionally, there was evidence of increased osmolyte synthesis, compatible as a defensive response to prevent oxidative damage. Likewise, the isohydric behaviour observed also resulted in significant decreases in gs even for moderate stress situations. In addition, it was observed that in the LFDI treatment, the stress levels reached caused a significant increase in the levels of Pro and MDA, which were not equal to those detected in FI during the recovery periods, which leads us to assume that potential values below -1.8 MPa would be causing significant oxidative damage with no capacity for subsequent recovery, and probably affecting the final yield.

SARS-CoV-2 is a new coronavirus that has caused a worldwide pandemic. It produces severe acute respiratory disease (COVID-19), which is fatal in many cases, characterised by cytokine release syndrome (CRS). According to the World Health Organization (WHO), those who smoke are likely to be more vulnerable to infection. Here, in order to clarify the epidemiologic relationship between smoking and COVID-19, we present a systematic literature review until 28 April 2020 and a meta-analysis. It includes 18 recent COVID-19 clinical and epidemiological studies based on smoking patient status from 720 initial studies in China, USA, and Italy. The percentage of hospitalised current smokers was 7.7% (95%CI: 6.9-8.4) in China, 2.3% (95%CI: 1.7-2.9) in the USA and 7.6% (95%CI: 4.2-11.0) in Italy. These percentages were compared to the smoking prevalence of each country and statistically significant differences were found in them all (p <0.0001). By means of the meta-analysis, we offer epidemiological evidence showing that smokers were statistically less likely to be hospitalised (OR=0.18, 95%CI: 0.14-0.23, p<0.01). CRS and exacerbated inflammatory response are associated with aggravation of hospitalise patients. In this scenario, we hypothesise that nicotine, not smoking, could ameliorate the cytokine storm and severe related inflammatory response through the cholinergic-mediated anti-inflammatory pathway.

Considering nutritional qualities of gofio (Gf) and aloe vera juice (AVJ), their combination is indicated as an easy and fast source of ingest of basic bio elements. As the texture of the final product must be accepted by customers, the influence of Gf concentration on the rheological behavior of Gf/AVJ suspensions was determined. Shear thinning index of AVJ maintains unaltered despite the presence of Gf particles, although the viscosity value increases as expected. Linear viscoelastic studies on Gf/AVJ confirmed this is a viscoelastic liquid that changes from chewy to creamy texture with Gf concentration increase.

Colombia is the world's leading producer of mild washed arabica coffee and produces 12.6 million bags of green coffee, but at the same time 784,000 tons of waste biomass are dumped in open fields, of which only 5% is recovered or used. The objective of this project was to evaluate the production of platform chemicals from these coffee wastes. To achieve this, biomass characterization was carried out using proximate analysis, ultimate analysis and structural analysis. Hydrothermal valorization was carried out at a temperature range of 120-180 °C (LHW) and 180-260 °C (HTC) for one hour, the platform chemicals obtained were quantified by HPLC-IR, monitored by pH and conductivity, and the solid fraction was characterized by monitoring the functional groups in IR spectroscopy, and elemental analysis. Hydrolysis processes were obtained from 150 °C, production of platform chemicals from 180 °C and maximum concentration at 180 °C-4h, over 200 °C degradation of the products in the liquid fraction starts to take place. Homogeneous basic and acid catalysts were used to improve the yields of the reaction. The kinetics of the hydrolysis of lignocellulosic structures to sugars were also analyzed and described, and reaction orders of 1 (LHW), 3 (HTC) and their respective reaction rate equations were reported.

Biogenic-Silver nanoparticles emerge as new nanosilver platfmorm that allow to obtain silver nanoparticles via “green chemistry”. In our study we obtained biogenic-Silver nanoparticles from Iris tuberosa leaves extract. Nanoparticles were characterized by UV-vis spectroscopy, dinnamical light scattering technique and Transmission electron microscope, showing spheric and irregular nanoparticles with 5 to 50 nm in diameter. Antioxidant and antimicrobial properties were evaluated against typical microbial contaminants found in cosmetic products, showing high antioxidant and antimicrobial properties. We formulated a natural moisturizing cream with biogenic-silver nanoparticles to evaluate the preservative efficiency trought challenge test, confirming that our nanoparticles are a promising alternative to use as cosmetic preservative.

Hopfield Neural Networks (HNNs) are recurrent neural networks used to implement associative memory. Their main feature is their ability to pattern recognition, optimization, or image segmentation. However, sometimes it is not easy to provide the users with good explanations about the results obtained with them due to mainly the large number of changes in the state of neurons (and their weights) produced during a problem of machine learning. There are currently limited techniques to visualize, verbalize, or abstract HNNs. This paper outlines how we can construct automatic video generation systems to explain their execution. This work constitutes a novel approach to get explainable artificial intelligence systems in general and HNNs in particular building on the theory of data-to-text systems and software visualization approaches. We present a complete methodology to build these kinds of systems. Software architecture is also designed, implemented, and tested. Technical details about the implementation are also detailed and explained. Finally, we apply our approach for creating a complete explainer video about the execution of HNNs on a small recognition problem.

It is not established whether SARS-CoV-2 (COVID-19) patients with movement disorders, are at greater risk for more serious outcomes than the larger COVID-19 population beyond the susceptibility associated with greater age. We reviewed electronic health records and conducted telephone interviews to collect the demographics and clinical outcomes of patients seen at our Movement Disorders Center who tested positive for COVID-19 from 8 March 2020 through 6 June 2020. Thirty-six patients were identified, 23 men and 13 women, median age of 74.5 years. They primarily carried diagnoses of idiopathic Parkinson disease (n=22; 61%) and atypical parkinsonism (n=7; 19%) with the balance having other diagnoses. Twenty-seven patients (75%) exhibited alteration in mental status and fifteen (42%) had abnormalities of movement as common manifestations of COVID-19; in 61% and 31%, these were the presenting symptoms of the disease. 67% of patients in our cohort required hospitalization, and the mortality rate was 39%.. These data demonstrate that in patients with movement disorders, the likelihood of hospitalization and death after contracting COVID-19 was substantially greater than in the general population. Patients with movement disorders frequently presented with altered mental status, generalized weakness, or worsening mobility but not anosmia.

One of the most important challenges in the Machine and Deep Learning areas today is to build good models using small datasets, because sometimes it is not possible to have large ones. Several techniques have been proposed in the literature to address this challenge. This paper aims at studying the different available Deep Learning techniques and performing a thorough experimentation to analyze which technique or combination thereof improves the performance and effectiveness of the models. A complete comparison with classical Machine Learning techniques was carried out, to contrast the results obtained using both techniques when working with small datasets. Thirteen algorithms were implemented and trained using three different small datasets (MNIST, Fashion MNIST, and CIFAR-10). Each experiment was evaluated using a well-established set of metrics (Accuracy, Precision, Recall, F1, and the Matthews correlation coefficient). The experimentation allowed concluding that it is possible to find a technique or combination of them to mitigate a lack of data, but this depends on the nature of the dataset, the amount of data, and the metrics used to evaluate them.

Concrete consumption greatly exceeds the use of any other material in engineering. This is due to its good properties as construction material and the availability of its components. Nevertheless, the present worldwide construction increase and the high-energy consumption for cement production means a high environmental impact. On the other hand, one of the main problem in iron and steel industry is waste generation and by-products that must be properly processed or reused to promote the environmental sustainability. One of these by-products are blast furnace slag. Cement substitution by slag strategy achieves two goals, raw materials consumption reduction and waste management. In the present work, four different concrete mixtures are evaluated. 25% cement is substituted by different blast furnace slag. Tests are made to evaluate the advantages and drawbacks of each mixture. Depending on the origin, characteristics and treatment of the slag, concrete properties change. Certain mixtures provide proper concrete properties. Stainless steel slag produces a fluent mortar that reduces the water consumption whit a slight mechanical strength loss. Mixture with electric arc slag furnace properties are better to the reference concrete (without slag) when slag is treated similarly to the cement.

Air pollution is a global issue, and the transportation sector is recognized as the third-largest contributor to anthropogenic greenhouse gas emissions. Vehicles emit a range of chemical compounds as a direct result of the combustion process. The nature and quantity of these emissions depend on the vehicle's characteristics, road, and local weather conditions. As a result, these emissions require special attention due to the adverse effects contributing to global warming and significantly impacting human health. In this regard, diagnosing and monitoring air quality is crucial for understanding the nature and quantity of emissions generated by various sources. However, in developing countries, the necessary inputs, and data for conducting such analyses are not always available. Therefore, the purpose of this study is to estimate emissions specifically generated from road operations. To achieve this, HDM-4 calculation tool is utilized to quantitatively estimate these emissions. This tool was applied in Baja California, Mexico, on the Centinela-La Rumorosa highway. The results obtained show that annually, 372.5 tons of pollutant emissions are generated, composed of HC, CO, CO2, NOx, Par, SO2, and PB, covering a mere 128 kilometers of length within a state road network spanning 11,429 kilometers. This highlights the necessity of implementing strategies to reduce emissions or the environmental impact generated by vehicular operations on roads in developing countries.

A multilevel factorial design of 23 with 12 experiments was developed for the preparation of cellulose nanocrystals (CNC) from Agave tequilana Weber var. Azul bagasse. The studied parameters were acid type (H2SO4 and HCl), acid concentration (60 and 65 wt% for H2SO4, 2 and 8N for HCl) temperature (40 and 60°C for H2SO4, 50 and 90°C for HCl), and hydrolysis time (40, 55 and 70 min for H2SO4, 30, 115 and 200 min for HCl). The obtained CNC were physical and chemically characterized using dynamic light scattering (DLS), atomic force microscopy (AFM), Fourier-transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XDR) techniques. The size and morphology of A. tequilana CNC strongly depend on the acid type and hydrolysis parameters. The shortest CNC were obtained with H2SO4 (65 wt%, 40 °C, and 70 min) had a length of 137 ± 68 nm, width 33 ± 7 nm, and height 9.1 nm, whereas the shortest CNC obtained with HCl (2 N, 50 °C and 30 min) had a length of 216 ± 73 nm, width 69 ± 17 nm, and height 8.9 nm. CNC prepared from H2SO4 resulted shorter and thinner than those obtained with HCl. The total sulfate groups content in CNC obtained with H2SO4 increase with time agree to CSG=aebt, and increases with temperature and acid concentration.

We report on recent experimental results on β decay into self-conjugate (N=Z) nuclei with mass number 58≤A≤70. Super-allowed β decays from the Jπ=0+ ground state of a Z=N+2 parent nucleus are to the isobaric analogue state, through so-called Fermi transitions, and to Jπ=1+ states, by way of Gamow–Teller (GT) transitions. The operator of the latter decay is a generator of Wigner’s SU(4) algebra and as a consequence GT transitions obey selection rules associated with this symmetry. Since SU(4) is progressively broken with increasing A, mainly as a consequence of the spin–orbit interaction, this symmetry is not relevant for the nuclei considered here. We argue, however, that the pseudo-spin–orbit splitting can be small in nuclei with 58≤A≤70, in which case nuclear states exhibit an approximate pseudo-SU(4) symmetry. To test this conjecture, GT decay strength is calculated with use of a schematic Hamiltonian with pseudo-SU(4) symmetry. Some generic features of the GT β decay due to pseudo-SU(4) symmetry are pointed out. The experimentally observed GT strength indicates a restoration of pseudo-SU(4) symmetry for A=70.

The application of the sensors optical fiber in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking the frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum is analyzed and sensor´s properties were defined. Following, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolutions. Both resolutions are conceivable because the FDPA algorithm elaborates two evaluations of Bragg wavelength shift

Background. It is unclear whether the use of clinical prediction rules is sufficient to rule out infective endocarditis (IE) in patients with Staphylococcus aureus bacteremia (SAB) without an echocardiogram evaluation, either transthoracic (TTE) and/or transesophageal (TEE). Our primary purpose was to test the usefulness of PREDICT, POSITIVE and VIRSTA scores to rule out IE without echocardiography. Our secondary purpose was to evaluate whether not performing an echocardiogram evaluation is associated with higher mortality. Methods. We conducted a unicentric retrospective cohort including all patients with a first SAB episode from January 2015 to December 2020. IE was defined according to modified Duke criteria. We predefined threshold cut-off points to consider that IE was ruled out by means of the mentioned scores. To assess 30-day mortality, we used a multivariable regression model considering performing an echocardiogram as covariate. Results. Out of 404 patients, IE was diagnosed in 50 (12.4%). Prevalence of IE within patients with negative PREDICT, POSITIVE and VIRSTA scores was: 3.6% (95% CI 0.1-6.9%), 4.9% (95% CI 2.2-7.7%), and 2.2% (95% CI 0.2-4.3%), respectively. Patients with negative VIRSTA and negative TTE had an IE prevalence of 0.9% (95% CI 0-2.8%). Performing an echocardiogram was independently associated with lower 30-day mortality (OR 0.24 95%CI 0.10-0.54, p=0.001). Conclusion. PREDICT and POSITIVE scores were not sufficient to rule out IE without TEE. In patients with negative VIRSTA score, it was doubtful if IE could be discarded with a negative TTE. Not performing an echocardiogram was associated with worse outcomes, which might be related to presence of occult IE. Further studies are needed to assess the usefulness of clinical prediction rules in avoiding echocardiographic evaluation in SAB patients.

A via ferrata (from the German “klettersteig”, hereinafter VF) is a sports route located on forest and mountains vertical rock walls equipped with steps, chains, artificial dams, bridges and other fixed elements and which have a steel cable (safety cable) all the way along allowing users to secure their progress and avoid possible falls [1]. This article aims to analyse the state of the art of the VF sector in Spain, especially in terms of the regulations of obligatory compliance, in addition to defining the basic characteristics of the installations to ensure that these are safe for users, providing a previously non-existent summary of the most important recommendations regardless of the country where they are installed.

The purpose of this paper is to examine the role and impact of public governance on European supranational public policies that seek to foster scientific and economic growth within innovation ecosystems (IEs) through the PITCCH initiative. The PITCCH is a European innovation development initiative funded by Horizon 2020 under the 'Innovation in SMEs' measure.The research methodology for this study is based on a 10-month real-time ethnographic field study of the PITCCH project, which allowed for the observation of the project governance and the capture of the perspectives of innovation-driven small and medium enterprises (i-SMEs) in their engagement with IE stakeholders.The findings of this research demonstrate the role of public governance in providing result-oriented practical support to the IE through the lens of i-SMEs, and they contribute to the existing literature on regional economic growth supported by supranational public policies. These findings have both academic and practical applications. They enrich the current literature on this topic and provide insights for policymakers and governing representatives seeking to implement effective public policies.

This study analyzed the levels of mental workload and the presence of burnout on a sample of fashion retailing workers from Spain and its relationship with the actual Covid-19 pandemic by exploring Covid-19 pandemic predictors of burnout and mental workload. We established a prospective cross-sectional design. Participants (n = 360) answered an online survey including questions about sociodemographic data, perception of Covid-19, CarMen-Q questionnaire (workload), and MBI (burnout syndrome). We obtained data throughout October-November 2020. The results showed that participants exhibit deep concern about the Covid-19 pandemic and its influence at the work level. Although the mental workload was near the middle point of the scale, participants showed moderate to high burnout levels, revealing that the sample is at risk of experiencing higher burnout levels over time as the pandemic and associated economic crisis continue. The multidimensional regression analysis results indicated that environmental changes, work overload, somatic symptoms, insomnia, negative job expectations, and uncertainty constituted significant mental workload predictors. Insomnia, somatic symptoms, and negative job expectations constituted significant predictors for burnout. In conclusion, the uncertainty at work derived from the Covid-19 pandemic is harming the psychological wellbeing of fashion retailing workers in Spain.

Flare stacks are a key element in the safety of petrochemical and refinery industries; the correct operating conditions thereof must be ensured through a schedule for the periodic reviewing of all parts thereof. Advances in Non-Destructive Testing (NDT) in recent years and the application thereof to this field allow reliable, objective information to be obtained. This article describes and groups together the main applicable NDT techniques, analysing their advantages and disadvantages, updated with the new possibilities offered by unmanned aircraft or drones.

A metastable β-Ti alloy, Ti–10V–3Fe–3Al (wt.%), was subjected to thermos-mechanical processing including the compression test at 725°C, which is below the β transus temperature (780°C), and at strain rate of 10-3s-1. The presence of phases was determined using transmission electron microscopy and X-ray diffraction. Although the dynamic recovery took place together with slip, both deformation-induced α˝ martensite and ω were detected as other operating mechanisms for the first time in metastable-β Ti alloys deformed in α+β region. The volume fraction of stress-induced α˝ was higher than that of the same alloy deformed at room temperature due to higher strain applied. Stress-induced twinning was not operational, which could be related to the priority of slip mechanism at high temperature resulted from thermally-assisted nucleation and lateral migration of kink-pairs.

Direct yaw moment control (DYC) is an effective way to alter the behaviour of electric cars with independent drives. Controlling the torque applied to each wheel can improve the handling performance of a vehicle making it safer andfaster on a race track. The state-of-the-art literature covers the comparison of various controllers (PID, LPV, LQR, SMC, etc.) using ISO manoeuvres. However, more advanced comparison on important characteristics of the controllers performance is missed, such as the robustness of the controllers under changes in the vehicle model, steering behaviour, use of the friction circle and, ultimately, lap time on a track. In this study, we have compared the controllers according to some of the aforementioned parameters on a modelled race car. Interestingly, best lap times are not provided by perfect neutral or close-to-neutral behaviour of the vehicle, but rather by allowing certain deviations from the target yaw rate. In addition, a modified PID controller showed that its performance is comparable to other more complex control techniques such as MPC.

Parkinson’s disease is a neurodegenerative disorder characterized by oxidative stress and immune activation in the nigro-striatal pathway. Simvastatin regulates cholesterol metabolism and protects from atherosclerosis disease. Simvastatin or tween-80 was administered 7 days before sterotaxic intrastriatal administration of MPP+ (1-methyl-4-phenylpyridine) in rats. Fluorescent lipidic product formation, dopamine levels, and circling behavior were considered damage markers. Twenty-four h and six days after, the animal group lesioned with MPP+ showed significant damage in relation to the control group. Animals pretreated with simvastatin reduced significantly the MPP+-induced damage compared to MPP+ treated group. As apoptosis promotes neuroinflammation and neuronal degeneration in Parkinson’s disease, and since there is not currently a proteomic map of the Nigro striatum of rats, and assuming a high homology among the identified proteins in other rat tissues, we based the search for rat protein homologs related to the establishment of inflammation response. We demonstrate that most proteins related to inflammation are decreased in the simvastatin-treated rats. Furthermore, differential expression of antioxidant enzymes in striated tissue of rat brains was found in response to simvastatin. These results suggest that simvastatin could prevent striatal MPP+-induced damage and for the first time the molecular mechanisms involved in this protective effect.

Plastics, primarily microplastics, are among the greatest pollutants in aquatic environments. Their removal and/or degradation in these environments are crucial to ensure an optimal future of the ecosystems. In this work MnO2 particles were synthesized and characterized for the removal polystyrene microplastics as a model. MnO2 catalyzes the peroxide reaction, resulting in the formation of oxygen bubbles that propel the pollutants to the surface, achieving removal efficiencies of up to 80%. To achieve this, hydrothermal synthesis was employed using various methods. Parameters such as MnO2, microplastics and H2O2 concentrations were varied to determine the optimal conditions for microplastics recovering. The ideal conditions for a low microplastic concentrations of microplastics (10 g L-1) are 0.2 g L-1 MnO2, 1.6% of H2O2 and 0.01 triton as a surfactant. In these conditions the micromotors can recover approximately of 80% 300 nm sized polystyrene microplastic within 40 min.

Cellular agriculture is defined as the production of agricultural products from cell cultures rather than from whole plants or animals. With growing interest in cellular agriculture as a means to address the public health, environmental, and animal welfare challenges of animal agriculture, the concept of producing seafood from fish cell- and tissue-cultures is emerging as a means to address similar challenges with industrial aquaculture systems and marine capture. Cell-based seafood - as opposed to animal-based seafood - can combine developments in biomedical engineering with modern aquaculture techniques. Biomedical engineering developments such as closed-system bioreactor production of land animal cells create a basis for large scale production of marine animal cells. Aquaculture techniques such as genetic modification and closed system aquaculture have achieved marked gains in production that can pave the way for innovations in cell-based seafood production. Here, we present the current state of innovation relevant to the development of cell-based seafood across multiple species as well as specific opportunities and challenges that exist for advancing this science. The authors find that the physiological properties of fish cell- and tissue- culture may be uniquely suited to cultivation in vitro. These physiological properties, including hypoxia tolerance, high buffering capacity, and low-temperature growth conditions, make marine cell culture an attractive opportunity for scale production of cell-based seafood; perhaps even more so than mammalian and avian cell cultures for cell-based meats. This, coupled with the unique capabilities of crustacean tissue-friendly scaffolding such as chitosan, a common seafood waste product and mushroom derivative, presents great promise for cell-based seafood production via bioreactor cultivation. To become fully realized, cell-based seafood research will require more understanding of fish muscle culture and cultivation; more investigation into serum-free media formulations optimized for fish cell culture; and bioreactor designs tuned to the needs of fish cells for large scale production.

As wind turbine power requirements have evolved from the order of kilowatts (kW) to the order of several megawatts (MW), wind turbine components have been subjected to more demanding and critical operating conditions. The wind turbine must cope with higher wind loads due to larger blade sizes, which are also time-varying and ultimately higher power levels. One of the challenges in the manufacture of high-power wind turbines lies in the gearbox and consists of achieving ever greater power density without compromising efficiency, i.e., greater load capacity with lower weight (and production cost) and reduced power losses. In this paper we will analyze the influence that certain design parameters have on the size and weight of the gearbox components and therefore of the gearbox itself. For this purpose, the theoretical model of the gearbox will be planned and the influence of calculation parameters on the gearbox design will be analyzed. The influence of material, modulus and tooth width on the size and weight of the gearbox will be observed. Critical stresses are also calculated. The goal is to prepare the theoretical basis for an optimization process that will result in a gearbox as compact as possible without compromising the service life of the components.

Enzymes are the most efficient catalysts known working in an aqueous environment near room temperature. The folding of individual polymer chains to functional single-chain nanoparticles (SCNPs) offers many opportunities for the development of artificial enzyme-mimic catalysts showing both high catalytic activity and specificity. In this review, we highlight recent results obtained in the use of SCNPs as bioinspired, highly-efficient nanoreactors (3–30 nm) for the synthesis of a variety of nanomaterials (inorganic nanoparticles, quantum dots, carbon nanodots), polymers and chemical compounds, as well as nanocontainers for CO₂ capture and release.

We discuss the topic of the transparency of the Universe in gamma-rays due to the Extragalactic Background Light, and its cosmological and physical implications. Rather than a review, this is a personal account on the development of 30 years of this branch of physical science. Extensive analysis of the currently available information appears to us as revealing a global coherence among the astrophysical, cosmological, and fundamental physics data, or, at least, no evident need so far of substantial modification of our present understanding. Deeper data from future experiments will verify to what extent and in which directions this conclusion should be modified.

Abstract Women victims of abuse can suffer neuropsychological sequelae that affect memory and attention, as well psychopathological disorders such as depression. These consequences affect their daily life and physical and psychological health. Objective: To analyze sequelae that affect attention and memory, as well a possible association of these sequelae to depression. Method: A total of 68 women victims of gender-based violence participated in the study. The participants were between 15 and 62 years of age and resided in Spain at the time of data collection. The Luria DNA Battery (Neuropsychological Diagnosis of Adults) by Manga and Ramos (2000); and the Beck Depression Inventory were applied. Results: Women victims of gender-based violence suffer neuropsychological sequelae, presenting low short-term memory and attentional control; and score low on the Luria-DNA battery. Of these women, 60% suffer from some relevant type of depression, and there are significant differences according to their degree of memory. Through the HJ-Biplot, a direct relationship was found between memory and attentional control with the total score of the Luria battery. On the other hand, an inverse relationship was found between short-term memory and depression. Lastly, three well-differentiated gender clusters of women victims of gender-based violence were identified. Conclusions: A lower rate of depression is observed in women victims of abuse when they have a more intact short-term memory.

The official recommendations to manage COVID-19 in the outpatient setting focus on high-cost drugs (remdesivir, nirmatrelvir-ritonavir, molnupiravir), suffering from many problems. Therefore, one may consider also other treatments meeting these criteria: • promising effectiveness, based on favorable randomized controlled trials (RCTs) of sufficient validity. Even without definitive evidence, physicians and informed patients can consider them if they are also: • safe, to the state of knowledge • with a very favorable opportunity cost • biologically plausible/not implausible • accessible • without major commercial sponsors in the trials promoting them, and with researchers without major conflicts of interests. The main focus is on a limited group of functional foods and some their active ingredients, with further mention of other substances of different origin, yet fully meeting all the aforementioned criteria. The functional foods and substances described and discussed certainly do not cover all the known effective therapies for COVID-19 (in one case also for Long-COVID), but the only therapies proposed in this paper currently satisfy all the above criteria. The supporting scientific evidence will favor meta-analyses of RCTs that include the most definitive outcome: all-cause mortality, i.e. the outcome that most fully informed people tend to prioritize. Furthermore, the reported evidence favors clinical studies of the most valid design, i.e. RCTs.

Sustainability has been playing a major role on the world stage. As with everything in the be-ginning, it was aligned to purely environmental contexts, but with the passing of the years and the new way of producing, marketing, and consuming, this concept has encompassed other as-pects which are the way of producing products and services. In this article, to obtain information on the implementation of sustainable innovation, a search equation was formulated in the SCOPUS database, contemplating the period from 2018 to 2023 as a time interval, with a total of 62 articles. Once the search of the published articles was carried out, 7 categories were formed to classify the research topic of each of the publications with Bibliometrix software, according to the main ob-jective and methodology used in each one. In this sense, 44% of the articles published are related to open innovation, and 26% of the articles are focused on sustainable business models. At the end of the analysis of the implementation of innovation according to the articles consulted, it was possible to establish that sustainable innovation began an important work, in the mitigation of the adverse impacts.

Introduction: Studies conducted in real-life scenarios on vaccine protection against COVID-19 constitute an important global priority, but one that is currently mostly neglected in low- and middle-income countries such as Angola. Here, we analyze for the first-time vaccine protection against COVID-19 in a real-life scenario after 6 months of implementing a multi-vaccination plan in Angola, providing estimation of odds ratios in vaccinated individuals and vaccine efficacy against infection by SARS-CoV-2 in a period that coincided with the identification of the Omicron variant in the country. Methods: We used a negative test case-control design to assess the effectiveness of vaccination against confirmed SARS-CoV-2 infection. A total of 4.232 vaccinated and unvaccinated individuals with the result of a rapid antigen diagnostic test against SARS-CoV-2 performed from December 27 to 28, 2021 were included in the study. Data were extracted from the Digital Vaccination Record Platform (Rediv) of the Ministry of Health of Angola. All ethical procedures related to the authorization necessary to carry out the study were followed. Statistical analyzes were performed using version 7.5.2.0 of CDC's Epi Info. Frequency distributions and measures of central tendency were used to characterize the study universe. The general and sex-adjusted and age-adjusted odds ratios, were evaluated by comparing the chances of vaccination between cases and controls, and their associated 95% CI, which were calculated using the Mantel-Haenszel stratification method. The risk classification of Axel Kroeger, Piscoya and Alarcon was used to interpret the odds ratio. The Breslow-Day statistic was used to assess the homogeneity of the odds ratios. Vaccine efficacy was calculated using the odds ratio applying the accepted statistical vaccine efficacy formula:(1 − odds ratio) × 100. For all estimates, a P value < 0.05 was considered statistically significant. Results: The population consisted of 63.63% male and 36.37% female. The mean age was 36 years with a standard deviation of 13. 83. Regarding vaccination status, 83.27% of individuals were vaccinated and 16.73% were unvaccinated, with 21.81% positive and 78.19% negative for SARS -CoV-2. The odds of SARS-CoV-2 infection were 0.85 (95% CI 0.70 – 1.03) times lower in vaccinated compared to unvaccinated individuals, with P=0.09. The overall vaccine efficacy (VE) was 15% (95% CI -3 – 30). Conclusion: There was no statistically significant decrease in the chances of SARS-CoV-2 infection in vaccinated versus unvaccinated individuals. However, the overall vaccine efficacy was 15%.

Wind technology is considered to be among the most promising types of renewable energy sources, and due to high oil prices and growing concerns about climate change and energy security, it has been the subject of extensive considerations in recent years, including questions related to the relative sustainability of electricity production when the manufacturing, assembly, transportation and dismantling processes of these facilities are taken into account. The present article evaluates the environmental impacts, carbon emissions and water consumption, derived from the production of electric energy of the Villonaco wind farm, located in Loja-Ecuador, during its entire life cycle, using the Life Cycle Analysis method. Finally, it is concluded that wind energy has greater environmental advantages, since it has lower values of carbon and water footprints than other energy sources. Additionally, with the techniques Cumulative Energy Demand and Energy Return on Investment, sustainability in the production of electricity from wind power in Ecuador is demonstrated; and, that due to issues of vulnerability to climate change, the diversification of its energy mix is essential considering the inclusion of non-conventional renewable sources such as solar or wind, this being the only way to reduce both the carbon footprint and the water supply power.

Avian mutations in vaccine strains obtained from embryonated eggs could impair vaccine effec-tiveness. We performed a systematic review and meta-analysis of the adjusted relative vaccine effectiveness (arVE) of seed cell-cultured influenza vaccines (ccIV) compared to egg-based influ-enza vaccines (eIV) in preventing laboratory-confirmed influenza related outcomes (IRO) or IRO by clinical codes, in subjects 18 and over. We completed the literature search in January 2021; ap-plied exclusion criteria, evaluated risk of bias of the evidence, and performed heterogeneity, pub-lication bias, qualitative, quantitative and sensitivity analyses. All estimates were computed us-ing a random approach. International Prospective Register of Systematic Reviews, CRD42021228290. We identified 12 publications that reported 26 adjusted arVE results. Five publications reported 13 laboratory confirmed arVE and seven reported 13 code-ascertained arVE. Nine publications with 22 results were at low risk of bias. Heterogeneity was explained by season and risk of bias. We found a significant 11% (8 to 14%) adjusted arVE favoring ccIV in preventing any IRO in the 2017-2018 influenza season. The arVE was 3% (-01 to 7%) in the 2018-2019 influenza season. We found moderate evidence of a significant advantage of the ccIV in preventing IRO, compared to eIV, in a well-matched A(H3N2) predominant season.

Background: A new access technique was developed to reduce postoperative adverse events after the extraction of impacted maxillary wisdom teeth. Hence, this study aimed to assess the occurrence of adverse events after extraction of maxillary impacted wisdom teeth using traditional or modified access. Methods: Two different surgical incision designs were used for bilateral wisdom tooth extractions in 30 patients. The traditional incision was performed distal to the second molar in the center of the tuberosity, followed by a buccal releasing incision. After tooth extraction the wound was secured by sutures. The new technique consists of an oblique incision from the distal palatal aspect of the tuberosity towards the buccal aspect of the second molar. After tooth extraction, cyanoacrylate glue was used on the wound. Results: Lower pain was reported by patients at the site treated with the new technique (p&lt;0.01). Edema, postsurgical bleeding, and hematoma were similar in both groups. The surgical time was shorter for the new technique (p&lt;0.01). Conclusions: The new technique applied for the extraction of impacted maxillary wisdom teeth reduced postsurgical pain and the duration of surgery.

In this paper the possibility of harvesting energy from the vibrations of a plate is analyzed. The harvester takes the form of a cantilever dynamic vibration absorber equipped with a piezoelectric layer and tuned by means of a tip mass to the first mode of vibration of the plate. A mathematical model of the coupled system composed of the plate and the harvester is presented. The validity of the proposed harvester is proved by means of simulations carried out with the modal expansions approach. Simulation results highlighting the effect of harvester tuning and location are presented as well. Then the validity of the harvester is confirmed by experimental tests carried out both with a concentrated impulsive load and with a distributed pressure load. Simulations and experimental tests show that the cantilever piezoelectric dynamic vibration absorber generates open circuit voltage an order of magnitude larger than the one generated by the same piezoelectric layer when directly bonded to the plate surface.

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death worldwide. It is commonly diagnosed in advanced stages and therapeutic interventions are typically constrained to systemic chemotherapy, which yields only modest clinical outcomes. In this review, we examine recent developments in targeted therapy tailored to address distinct molecular pathway alteration required for PDAC. Our review delineates the principal signaling pathways and molecular mechanisms implicated in the initiation and progression of PDAC. Subsequently, we provide an overview of prevailing guidelines, ongoing investigations, and prospective research trajectories related to targeted therapeutic interventions, drawing insights from randomized clinical trials and other pertinent studies. This review focus on a comprehensive examination of preclinical and clinical data substantiating the efficacy of these therapeutic modalities, emphasizing the potential of combinatorial regimens and novel therapies to enhance the quality of life for individuals afflicted with PDAC. Lastly, the review delves into the contemporary application and ongoing research endeavors concerning targeted therapy for PDAC. This synthesis serves to bridge the molecular elucidation of PDAC with its clinical implications, the evolution of innovative therapeutic strategies, and the changing landscape of treatment approaches.

As a consequence of the increasing share of renewable energies and sector coupling technologies, new approaches are needed for the study, planning, and control of modern energy systems. Such new structures may add extra stress to the electric grid, as is the case with heat pumps and electrical vehicles. Therefore, the optimal performance of the system must be estimated considering the constraints imposed by the different sectors. In this research, a dispatch optimization method with an iterative grid constraint generation, decoupled from the linear unit commitment problem, is employed. From the considered scenarios, it was found that in a typical German neighborhood with 150 households, PV penetration of ∼5kWp per household can lead to curtailment of ∼60MWh per year due to line loading. Furthermore, the proposed method eliminates grid violations due to the addition of new sectors reducing the curtailment up to 60%. With the optimization of the heat pump operation, an increase of 7% of the self-consumption was achieved with similar results for the combination of battery systems and electrical vehicles. In conclusion, a safer and optimal operation of a complex energy system is fulfilled. Safer control strategies and more accurate plant sizing could be derived from this work.

Purpose: Young transgender and non-binary are exposed to situations of discrimination and have a greater risk of violence. The purpose of this study is to analyze which protective, violence and health and well-being factors have more influence on transgender and non-binary people compared to cisgender people. Method: The sample comprised 856 people between 14 and 25 years old. A survey including questions about sociodemographic information and protective, violence and health and well-being factors was designed ad hoc for this study. Results: The results show non-binary group received the least support from family and friends, higher risk of suffering cyberbullying and a higher feel isolated and unhappy. Non-binary and transgender have suffered more verbal attacks both inside and outside their school and physical attacks at school than cisgender young. Conclusions: These results are important and may contribute to promote public policies and clinical interventions to favor the integration of non-binary and transgender people in our society.

Polymer hydrogels are 3D networks consisting of hydrophilic crosslinked macromolecular chains, able to swell and retain water. Since their invention in the 1960s, they have become an outstanding pillar in the design, development, and application of engineered polymer systems suitable for biomedical and pharmaceutical applications (such as drug or cell delivery, regeneration of hard and soft tissues, wound healing, and bleeding prevention, among others). Despite several well-established synthetic routes of polymer hydrogels based on batch polymerization techniques, about fifteen years ago academia started to look for alternative methods involving simpler reaction paths, shorter reaction times, and lower energy consumption. In this context, frontal polymerization (FP) undoubtedly has become an alternative and efficient reaction model that allows for converting monomers into polymers via a localized and propagating reaction, by exploiting the formation and propagation of a “hot” polymerization front, able to self-sustain and propagate throughout the monomeric mixture. Therefore, the present work aims to summarize the main research outcomes, achieved during the last years, concerning the design, preparation, and application of FP-derived polymeric hydrogels, demonstrating the feasibility of this technique for the obtainment of functional 3D networks, and providing the reader with some perspectives for the forthcoming years.

Intermediate CAG expansions in the gene ataxin-2 (ATXN2) are a known risk factor for ALS, but little is known about their role in FTD risk. Moreover, their contribution to the risk and phenotype of patients might vary in populations with different genetic background. The aim of this study was to assess the relationship of intermediate CAG expansions in ATXN2 with the risk and phenotype of ALS and FTD in the Spanish population. Repeat-Primed PCR was performed in 620 ALS and 137 FTD patients in three referral centers of Spain to determine the exact number of CAG repeats. In our cohort, ≥27 CAG repeats in ATXN2 was associated with a higher risk of developing ALS (odds ratio [OR] = 2.666 [1.471-4.882]; p = 0.0013), but not FTD (odds ratio [OR] = 1.446 [0.558-3.574]; p = 0.44). Moreover, ALS patients with ≥27 CAG repeats in ATXN2 showed shorter survival rate compared to those with &lt;27 repeats (hazard ratio [HR] 1.74 [1.18, 2.56], p = 0.005), more frequent limb onset (odds ratio [OR] = 2.34 [1.093-4.936]; p = 0.028), as well as family history of ALS (odds ratio [OR] = 2.538 [1.375-4.634]; p = 0.002). Intermediate CAG expansions of ≥27 repeats in ATXN2 are associated with ALS risk, but not with FTD, in the Spanish population. ALS patients carrying an intermediate expansion in ATXN2 show more frequent limb onset, but worse prognosis than those without expansions. In patients carrying C9orf72 expansions, the intermediate ATXN2 expansion might increase the penetrance and modify the phenotype.

In this article, we analyse the determinants of Regulatory Quality-RQ for 193 countries in the period 2011-2020. We use a database from ESG-Environment Social Governance of the World Bank. We apply OLS, Panel Data with Fixed Effects and Panel Data with Random Effects. We found that the variables that have the most positive impact on RQ, among others, are “GHG Net Emission”, “Mean Drought Index”, and “Heat Index”. We also found that the variables that have the most negative impact on RQ are among others “Renewable Energy Consumption”, “Voice and Accountability” and “Rule of Law”. Furthermore, we have applied the k-Means algorithm optimized with the Elbow Method and we find the presence of five clusters. In adjunct, we confront eight machine learning algorithms to predict the value of RQ and we found that the best predictor is Polynomial Regression. The predictive level of RQ for the analysed countries is expected to diminish of -1,29%. In the end, we present a network analysis with the Euclidean distance and we found the presence of a structure of seven networks using augmented data.

The search for new food products that promote consumers health has always been of great interest. The dairy industry is perhaps the best example regarding the emergence of new products with claimed health benefits. Cheese whey (CW), the by-product resulting from cheese production, and second cheese whey (SCW), which is the by-product of whey cheese manufacture, have proven to be potential ingredients for the development of food products with improved nutritional characteristics and other functionalities. Nowadays, due to their nutritional quality, whey products have gained a prominent position among healthy food products. However, for long, CW and SCW were usually treated as waste or as animal feed. Due to their high organic content, these by-products can cause serious environmental problems if discarded without appropriate treatment. Small and medium size dairy companies do not have equipment and structure to process whey and second cheese whey. In these cases, generally, they are used for animal feed or discarded without an appropriate treatment, being the cause of several constraints. There are several studies regarding CW valorization and there is a wide range of whey products in the market. However, in the case of SCW remains a lack of studies regarding its nutritional and functional properties, as well as ways to reuse this by-product in order to create economic value and reduce environmental impacts associated to its disposal.

Objective: A study was made of the salivary levels of adenosine deaminase (ADA), ferritin (FRR) and total proteins in healthy individuals and in patients with oral potentially malignant disorders (OPMD), assessing the potential role of saliva as a diagnostic tool. Methods: A total of 91 subjects participated in the study, divided into two groups: 59 patients with OPMD (oral leukoplakia or oral lichen planus )and 32 healthy controls with measurements being made of salivary ADA, ferritin (FRR) and total proteins (TP). Results: There were no significant differences in salivary ADA between the OPMD group and the controls (p=0.934), though the levels of both FRR and TP were significantly higher in the OPMD group (p=0.001). Patients with oral lichen planus showed significant differences in terms of FRR (p=0.009) and TP (p=0.003). Conclusions: The promising findings of this study suggest a potential role for FRR and TP in the salivary diagnosis of OPMD. In addition, saliva appears to be a reliable tool offering an interesting alternative for the screening of large populations.

In recent times, using image-based deep learning techniques has been very useful for classifying fruits. However, mango is a particular challenge because its shelf life is directly related to the degree of maturity at the time of harvest, which is determined mainly through the visual assessment of the operators when sorting them, doing it incorrectly, coupled with the blows and compressions exposed during storage and transport, trigger the deterioration in their quality, hence the importance of this operation. In this sense, the purpose of this study focuses on designing a computational model based on Deep Learning that uses a convolutional neural network (CNN) parameterized to select mangoes according to their color tone based on their maturity stage. A dataset was established from 201 labeled images, then a CNN architecture was built, obtaining a model on which 3 criteria were evaluated: the number of convolution and grouping layers, the resolution of the input images and the number of training epochs required. As a result, an input image resolution of 32 x 32 pixels was achieved, the process included a convolution layer followed by pooling that fed another layer that processed the results and ended in an output layer with 2 neurons under the One Hot Encoding representation. The model required 20 epochs to perfect its training, achieving 96.04 % accuracy in mango image selection. This study supports the potential of CNNs in quality analysis through mango color selection, even in uncertainty scenarios.

The crucial stages in the geochemical evolution of the Earth’s crust, ocean, and atmosphere could be explained by the assumed low-energy nuclear reactions (LENR) that are triggered by seismic activity. LENR result in the fission of medium-weight elements accompanied by neutron emissions, involving Fe and Ni as starting elements, and C, N, O as resultants. Geochemical data and experimental evidences support the LENR hypothesis. A spectral analysis of the period 1955-2013 shows common cycles between interannual changes in atmospheric CO2 growth rate and global seismic-moment release, whereas the trending behavior of the atmospheric CO2 was in response to the anthropogenic emissions. Assuming a correlation between such seismic and atmospheric fluctuations, the latter could be explained by cycles of worldwide seismicity, which would trigger massively LENR in the Earth’s Crust. In this framework, LENR from active faults could be considered as a relevant cause of carbon formation and degassing of freshly-formed CO2 during seismic activity. However, further studies are necessary to validate the present hypothesis which, at the present time, mainly aims to stimulate debate on the models which regulates atmospheric CO2.

Selective mutism (SM) is an “Anxiety Disorder” characterized by a child’s “persistent inability” to communicate verbally in some (or all) contexts of social life that is associated with other cognitive-affective disorders. Cognitive-behavioural assessment and psychological intervention may be complex to be performed due to both the difficulty to administered standardized neuropsychological batteries (e.g., language-mediated tests) and the difficulty to involve family and teachers in the intervention program, respectively. Here, a single-case study is described in which a female Filipina child with SM underwent a comprehensive neuropsychological assessment and multimodal therapeutical intervention between the ages of 7 to 11 years. More specifically, the psychological intervention included cognitive-behavioral psychotherapy to both improve social-cognitive skills and learning abilities and to reduce anxiety, and speech therapy. Moreover, the parents and teachers were actively involved in the therapeutic process and they were also administered a psycho-education program. After this specific treatment, at the age of 11 years the girl began to verbalize in both therapy and school contexts, although she still was used to adopt non-verbal strategies. A parallel and gradual improvement in communicative-linguistic skills and school learning was also observed. In conclusion, the present report highlights the importance to apply an "integrated and multimodal intervention" to treat SM in children that includes also psycho-education intervention for both parents and teachers.

This study evaluates various safety aspects of standardized impacts that cyclists may suffer while wearing a bicycle helmet, by combining a partially validated finite element model of the cranio-cervical region and a newly developed bicycle helmet model. Under EN 1078 standardized impact conditions, the results of simulated impact tests show that the helmet can absorb 40% to 50 % of the total impact energy at impact velocities above 4 m/s. Further, based on a relationship between Head Injury Criterion and the risk of injury from field data, the results of the simulations suggest that minor injuries may occur at impact velocities of 10 km/h, serious injuries at 15 km/h, and severe injuries at 20 km/h. Fatal injuries will likely occur at impact velocities of 30 km/h and higher.

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

We estimate the value of Research and Development Expenditures as a percentage of GDP-RDE in the context of Environmental, Social and Governance-ESG model. We use the ESG World Bank database. We analyze data from193 countries in the period 2011-2020. We apply a set of econometric techniques i.e. Pooled Ordinary Least Squares-OLS, Panel Data with Random Effects, Panel Data with Fixed Effects, Weighted Least Squares-WLS. We found that the level of RDE is positively associated, among others, to “Nitrous Oxide Emissions” and “Scientific and Technical Journal Articles”, and negatively associated, among others to “Heat Index 35”, “Maximum 5-day Rainfall”. Furthermore, we perform a cluster analysis with the application of the k-Means algorithm optimized with the Elbow Method. The results show the presence of four clusters. Finally, we confront eight different machine-learning algorithms to predict the future value of RDE. We find that Linear Regression is the best predictive algorithms. RDE is expected to growth on average of 0.07% for the analysed countries.

After approximately 6 months of age, term breastfed infants are increasingly depending on other sources of iron to avoid iron deficiency anemia. The appropriate complementary feeding must include a balance composition of foods containing an adequate amount of macro- and micronutrients to reduce the risk of iron deficiency anemia. This study aims to compare the anemia and growth status of infants receiving commercial fortified infant cereals (FIC) with infants not receiving them. We use all complete multiple Demographic Health Surveys (DHS) from 2005 to 2018 to understand global infant feeding patterns. To better control for the strong household wealth effect in nutritional choices and possibly health awareness, we use propensity score technique as applied in outcome research to better control the effect of covariates. After matching and controlling for confounders, we did find a significant association between reduced risk of anemia and consumption of FIC. After matching and adjusting for confounders the small but positive effects of consumption of FIC on Height for age z-score and Weight for Height Z-score are no longer statistically significant.

Objective: To evaluate the use of CDK4/6 inhibitors as a risk factor for medication-related osteonecrosis of the jaw (MRONJ) in a cohort of patients with metastatic breast cancer treated with denosumab. Methods: multicentre, retrospective, observational study. All patients with breast cancer treated with denosumab (January 2011-December 2022) were included. The relationship between CDK4/6 inhibitors and MRONJ was analysed. Results: 243 patients were included, ninety-five (44.2%) used a CDK4/6 inhibitor. There were 21 patients with MRONJ. In patients treated with denosumab without CDK4/6 inhibitors the incidence of MRONJ and mean time to the occurrence of MRONJ was 6.6% (8/120) and 16.8 months (SD 7.8) respectively. In patients treated with denosumab and CDK4/6 inhibitor 13.7% (13/95) and 15.4 month (SD 8.7) respectively. The difference in the incidence was not significant (p=0.085). Conclusion: it suggest that the incidence of MRONJ in patients with metastatic breast cancer treated with denosumab was higher and the onset of MRONJ occurred earlier in the presence of CDK4/6 inhibitors. Although the difference was not significant, given that the use of this combination is very common in routine clinical practice, it would be advisable to carry out larger prospective studies to clarify the risk of this association.

This paper presents a methodology to evaluate (1) to what extent students of a higher degree in the field of education acquire sustainability competencies, and (2) to determine whether the subjects that develop the ESD achieve their learning objectives. The methodology is applied to a case study. The instruments used are the sustainability survey and the sustainability presence map developed by the EDINSOST project. The survey consists of 18 questions, and has been answered by 104 first-year students and 86 fourth-year students belonging to the Bachelor Degree in Primary Education Teaching at the University of Sevilla. The Mann-Whitney U test has been used to compare the results of the two groups, and Cohen's D has been used to measure the effect size. Students only obtain significant improvements, with 95% confidence, in three questions (Q4, Q5 and Q6), all concerning critical thinking and creativity. An improvement is also detected in question Q11, with a confidence of 90%. However, no subject in the curriculum develops the learning outcomes concerning questions Q4, Q5 and Q6, and only one subject develops the learning outcomes regarding question Q11. On the other hand, up to five subjects declare development of the learning outcomes regarding questions in which there is no improvement in student learning. These results suggest that the subjects are failing to reach their ESD learning objectives, and that the students are either trained in sustainability outside the university or the subject learning guides do not reflect the work done by the students throughout their studies

Flow field based methods are becoming increasingly popular for the analysis of interfacial shear rheology data. Such methods take properly into account the subphase drag by solving the Navier-Stokes equations for the bulk phases flows, together with the Boussinesq-Scriven boundary condition at the fluid-fluid interface, and the probe equation of motion. Such methods have been successfully implemented at the double wall-ring (DWR), the magnetic rod (MR), and the bicone interfacial shear rheometers. However, a study of the errors introduced directly by the numerical processing is still lacking. Here we report on a study of the errors introduced exclusively by the numerical procedure corresponding to the bicone geometry at an air-water interface. In our study we directly input a preset the value of the complex interfacial viscosity and we numerically obtain the corresponding flow field and the complex amplitude ratio for the probe motion. Then we use the standard iterative procedure to obtain the calculated complex viscosity value. A detailed comparison of the set and calculated complex viscosity values is made upon changing different parameters such as real and imaginary parts of the complex interfacial viscosity and frequency. The observed discrepancies yield a detailed landscape of the numerically introduced errors.

Basic features of seed dormancy are illustrated. The seed overall regulatory network governs seed metabolism and development, and it is coordinated by plant hormones. A functional model focused on abscisic acid (ABA), the foremost plant hormone in dormancy, is used as a framework to critically discuss the literature. Gibberellins (GAs) have a main role in germination, and the ABA – GAs balance is a typical feature of the seed state: ABA dominates during dormancy and GAs prevail through germination. Thus, the literature converges toward envisaging the development switch between dormancy and germination as represented by the ABA/GAs ratio. The ABA – GAs antagonism is based on mutual inhibition, a feature of the regulatory network architecture that characterizes development trajectories based on a regulatory circuit with a bistable switch. Properties of such kind of regulatory architecture are introduced step by step, and it is shown that seed development – towards either dormancy or germination – is more properly represented by a tristable regulatory circuit, whose intermediate metastable states ultimately take one or the other development trajectory. Although the ABA/GAs ratio can conveniently represent the state of the seed overall regulatory network along the seed development trajectory, specific (unknown) dormancy factors are required to determine the development trajectory. The development landscape is shown to provide a well-suited representation of seed states travelling along developmental trajectories, particularly when the states are envisioned as regulatory circuits. Looking at seed dormancy in terms of regulatory circuits and development landscapes offers a valuable perspective to improve our understanding of this biological phenomenon.

We consider a Cauchy problem for differential equations in a Hilbert space $X$. The problem is stated in a time interval $I$, which can be finite or infinite. Weuse a fixed point argument for history-dependent operators to prove the unique solvability of the problem. Then, we state and prove convergence criteria for both a general fixed point problem and thecorresponding Cauchy problem. These criteria provide necessary and sufficient conditions on a sequence $\{u_n\}$ which guarantee its convergence to the solution of the corresponding problem, in the space of both continuous and continuously differentiable functions. We then specify our results in the study of a particular differential equation governed by two nonlinear operators. Finally, we provide an application in viscoelasticity and give a mechanical interpretation of the corresponding convergence result.

Blazars are a subclass of Active Galactic Nuclei (AGN) having relativistic jets aligned within a few degrees of our line-of-sight and form the majority of the AGN detected in the TeV regime. The Fermi-Large Area Telescope (LAT) is a pair-conversion telescope, sensitive to photons having energies between 20 MeV-2 TeV, and is capable of scanning the entire gamma-ray sky every three hours. Despite the remarkable success of the Fermi mission, many questions still remain unanswered, such as the site of gamma-ray production and the emission mechanisms involved. The Asteroid Terrestrial-impact Last Alert System (ATLAS) is a high cadence all sky survey system optimized to be efficient for finding potentially dangerous asteroids, as well as in tracking and searching for highly variable and transient sources, such as AGN. In this study, we investigate possible correlations between the \textit{Fermi}-LAT observations in the 100 MeV-300 GeV energy band and the ATLAS optical data in the R-band, centered at 679 nm, for a sample of 18 TeV-detected northern blazars over 8 years of observations between 2015-2022. Under the assumption that the optical and gamma-ray flares are produced by the same outburst propagating down the jet, the strong correlations found for some sources suggest a single-zone leptonic model of emission.

This study investigated the effects of flamenco dance on mood and subjective well-being in older women. In a broader context, the question was raised about how participation in dance activities could influence the emotional well-being of this demographic group. Thirty-four older women, aged between 62 and 79 years, with a mean age of 70.11 years (SD = 5.13), voluntarily participated in the study after providing informed consent. All of them were enrolled in a 12-week flamenco dance workshop conducted by the Autoestima Flamenca Association, with one two-hour session per week. Mood measurements (sadness, anxiety, anger, and joy) were taken biweekly before and after each session, and subjective well-being assessments were conducted before and after the intervention. The results revealed significant improvements in the overall mood of the participants, as well as an increase in their subjective well-being. These improvements were observed at both the individual and group levels. In conclusion, participation in flamenco dance demonstrated a positive impact on the mood and subjective well-being of older women. These findings support the idea that physical and artistic activities, such as flamenco dance, can play an important role in promoting emotional well-being in this age group.

This paper discusses the theoretical and experimental correlations between fatigue and static strength statistical distributions. We use a two-parameter residual strength model that obeys the qualitative Strenght-Life Equal-Rank (SLERA) assumption for guidance. The modeling approach consists of recovering the model's parameters by best fitting the constant amplitude (CA) fatigue data at a given stress ratio, R, and the experimental Weibull parameters of the static strength distribution function. Once the model's parameters are fixed, its capabilities, potential, and limits are discussed by comparing its predictions with residual strength and fatigue data obtained at different stress ratios, R. Moreover, from a preliminary analysis, the theoretical extension of the model's capabilities to variable amplitude loadings is conceptualized. The application of Miner's rule is also discussed and compared with a new damage rule to analyze the fatigue responses under variable amplitude loadings.

Among the many approaches to COVID-19 prevention, the possible role of diet has so far been somewhat marginal. Nutrition is very rich in substances with a potential beneficial effect on health and some of these could have an antiviral action or in any case be important in modulating the immune system and in defending cells from the oxidative stress associated with infection. This short review draws the attention on some components of Citrus fruits and especially of the orange (Citrus sinensis), well known for its vitamin content, but less for the function of its flavonoids. Among the latter, hesperidin has recently attracted the attention of researchers, because it binds to the key proteins of the SARS-CoV-2 virus. Several computational methods, independently applied by different researchers, showed that hesperidin has a low binding energy both with the coronavirus "spike" protein, and with the main protease that transforms the early proteins of the virus (pp1a and ppa1b) into the complex responsible for viral replication. The affinity of hesperidin for these proteins is comparable if not superior to that of common chemical antivirals. The preventive efficacy of vitamin C, at dosage attainable by diet, against viral infections is controversial, but recent reviews suggest that this substance may be useful in case of increased stress on the immune system. Finally, the reasons that suggest undertaking appropriate research on the Citrus fruits addition in the diet, as a complementary prevention and treatment of COVID-19, are discussed.

The assessment of existing bridges constitutes a serious challenge for the researchers since their safety evaluation is a complex task due to several sources of uncertainty affecting the parameters identified in the knowledge process. In particular, a high level of uncertainties may arise in the case of prestressing systems requiring special investigation strategies and experimental technologies. The paper aims to investigate how the knowledge uncertainties influence the safety assessment of existing post-tensioned bridges. The semi-probabilistic approach is used, and uncertainties related to the knowledge process are described considering the number of tests, the confidence level assumed for the estimation of the problem parameters, and the measurement errors of in-situ tests. Results concerning a typical post-tensioned bridge are reported and the variability of the outcomes is discussed and compared with a reference case of “perfect knowledge”. The main results of the study confirm the general robustness of the semi-probabilistic Eurocodes safety format and provide an overview of dispersion due to different choices about the number of tests and confidence level. The measurement errors may lead to significant under-estimation of the computed structural capacity with respect to the reference one.

Background: Differential diagnosis between polymyalgia rheumatica (PMR) and seronegative elderly-onset rheumatoid arthritis (SEORA) is not easy, to the point that in the past they were considered the same entity. In these patients, sleep disorders have been scarcely assessed, and considered as expression of mood disorders such as depression and anxiety. Methods: In 38 Caucasian elderly patients (median age: 73.9 ± 8.06 years) consecutively referred to two outpatient clinics from January to May 2018 with diagnosis of PMR and SEORA, sleep impairment was assessed using the Medical Outcomes Study-Sleep scale (MOS-SS). Depression and anxiety were assessed using the Neuropsychiatric Inventory (NPI) score, with point 0 for absent and point 3 for severe. Comorbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Patients taking medications used to treat sleep disturbance or that could favor sleep disturbances were excluded. The study was approved by the local ethics committee and carried out in accordance with the Helsinki Declaration, revised 2013. Every patient signed an informed consent form at the time of the first visit. Results: MOS-SS total point in PMR patients was significantly higher than in SEORA patients (47.60 ± 8.4 vs 28.26 ± 12.4; P = 0.000). After six-month therapy with prednisone (12.5–15 mg/day, followed after 4 weeks by gradual tapering), MOS-SS total point improved in the two groups of patients, with no significant difference (17.0 ± 6.2 vs 17.8 ± 4.2; P = 0.644). No correlation was found between MOS-SS and comorbidities, and between MOS-SS, anxiety or depression. Conclusions: Our data suggest that the assessment of sleep impairment could be very useful in the differential diagnosis between PMR and SEORA. Up today, the reasons why patients with PMR have—at the time of diagnosis—a sleep impairment higher than SEORA are speculative. Further ad hoc complementary studies in multicenter cohorts are needed.

Thermostatically controlled loads have great potential to make a significant contribution to improving energy efficiency in the building sector, which is responsible for 40% of greenhouse gas emissions in the EU. This, in addition to the environmental damage, represents a huge expense in the electricity bill. Therefore, it is very important to train engineers on how to design energy management systems for TCLs. With this goal in mind, it would be very useful to have a simulation-based educational tool (SBET) to understand thermostatically controlled loads, their characteristics and possibilities in energy efficiency. In addition, it would be very useful if this tool could be introduced in engineering curricula to help students to be better trained and enter the labor market with more opportunities. Based on the shortcomings detected, this work develops a SBET specifically designed to teach about TCLs (SBET-TCLs), both about their intrinsic characteristics and their better management. To verify the developed SBET-TCL, it has been tested in a real scenario: A survey was carried out among the students of the subject 'Alternative Energy Sources' of the degrees of Industrial Engineering. The results show that the use of SBET-TCL has very positive effects on the learning process.

Since the early 1990s, the European (ESA) and Italian (ASI) space agencies have managed and distributed a huge amount of satellite-recorded SAR data to the research community and private industries. Moreover, the availability of advanced cloud computing services implementing different multi-temporal SAR interferometry techniques allows the generation of deformation time series from massive SAR images. We exploit the information provided by a large PS dataset to determine the temporal trend of ground deformation and the relative deformation rate with millimetric accuracy to analyse the spatial and temporal distribution of land subsidence induced by water pumping from a deep confined aquifer in the Northern Valle Umbra Basin (Central Italy), exploiting 24 years of Permanent Scatterers – Interferometric SAR data archives. The SAR images were acquired between 1992 and 2016 by satellite ERS1/2, ENVISAT and Sentinel 1 ESA missions, and the COSMO-SkyMed ASI mission). We observe ground velocities and deformation geometries between 1992 and 2016, with displacements of more than 70 cm and velocities of up to 55 mm/yr and the results suggest that the shape and position of the surface ground displacement are controlled by the fault activity hidden under the valley deposits.

As recent history has shown, changing climate not only threatens to increase the spread of known disease, but also the emergence of new and dangerous phenotypes. This occurred most recently with West Nile virus: a virus previously known for mild febrile illness rapidly emerged to become a major cause of mortality and long-term disability throughout the world. As we move forward, into increasingly uncertain times, public health research must begin to incorporate a broader understanding of the determinants of disease emergence – what, how, why, and when. The increasing mainstream availability of high-quality open data and high-powered analytical methods presents promising new opportunities. Up to now, quantitative models of disease outbreak risk have been largely based on just a few key drivers, namely climate and large-scale climatic effects. Such limited assessments, however, often overlook key interacting processes and downstream determinants more likely to drive local manifestation of disease. Such pivotal determinants may include local host abundance, human behavioral variability, and population susceptibility dynamics. The results of such analyses can therefore be misleading in cases where necessary downstream requirements are not fulfilled. It is therefore important to develop models that include climate and higher-level climatic effects alongside the downstream non-climatic factors that ultimately determine individual disease manifestation. Today, few models attempt to comprehensively address such dynamics: up until very recently, the technology simply hasn’t been available. Herein, we present an updated overview of current perspectives on the varying drivers and levels of interactions that drive disease spread. We review the predominant analytical paradigms, discuss their strengths and weaknesses, and highlight promising new analytical solutions. Our focus is on the prediction of arboviruses, particularly West Nile virus, as these diseases represent the pinnacle of epidemiological complexity – solution to which would serve as an effective “gatekeeper”. We present the current state-of-the-art with respect to known drivers of arbovirus outbreak risk and severity, differentially highlighting the impact of climate and non-climatic drivers. The reality of multiple classes of drivers interacting at different geospatial and temporal scales requires advanced new methodologies. We therefore close out by presenting and discussing some promising new applications of AI. Given the reality of accelerating disease risks due to climate change, public health and other related fields must begin the process of updating their research programs to incorporate these much needed, new capabilities.

Graphene hybrid-filler polymer composites have emerged as prominent materials that revolutionize heavy industries. This study encapsulates the in-depth analysis of different influential factors such as filler/graphene type, aspect ratios, dispersion methods, filler-matrix compatibility, fiber orientation, synergistic effects, different processing techniques, and post-curing conditions that affect the processing, properties and determine the resultant applications of graphene hybrid polymer composites. Additionally, it discusses the substantial role of graphene collaboration with other fillers such as carbon nanotubes, silica, nano-clays and metal oxides to produce functionalized hybrid polymer composites with synergistically enhanced tailored properties to offer solutions for heavy industries like aerospace, automotive, electronics, and energy harvesting. The review concludes with some suggestions and outlook on the future of these composite materials by emphasizing the need for continued research to fully optimize their potential.

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

In this article we investigate the determinants of marketing or organizational innovators in Europe for 36 countries in the period 2010-2019. We have used data from the European Innovation Scoreboard-EIS of the European Commission. We perform different econometric models i.e. Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. Results show that the level of marketing or organizational innovators in positively associated, among others variables to “Innovation Index”, “Innovators” and “Knowledge Intensive Service Exports”, while is negatively associated with “Sales Impacts”, “Foreign Controlled Enterprises Share of Value Added” and “Government procurement of advanced technology products”.

The work proposes a backtesting analysis in comparison between the Lee-Carter and the Cairns-Blake-Dowd mortality models, employing Italian data. The mortality data come from the Italian National Statistics Institute (ISTAT) database and span the period 1975-2014, over which we computed back-projections evaluating the performances of the models in comparisons with real data. We propose three different backtest approaches, evaluating the goodness of short-run forecast versus medium-length ones. We find that both models were not able to capture the improving shock on the mortality observed for the male population on the analyzed period. Moreover, the results suggest that CBD forecast are reliable prevalently for ages above 75, and that LC forecast are basically more accurate for this data.

Lupus nephritis (LN) is a severe complication of systemic lupus erythematosus (SLE) and is considered one of the leading causes of mortality. Multiple immunological pathways are involved in the pathogenesis of SLE, which makes it imperative to deepen our knowledge about this disease's immunopathological complexity and explore new therapeutic targets. Since an altered redox state contributes to immune system dysregulation, this document briefly addresses the role of oxidative stress (OS), oxidative DNA damage, antioxidant enzymes, mitochondrial function, and mitophagy in SLE and LN. Although adaptive immunity's participation in the development of autoimmunity is undeniable, increasing data emphasize the importance of innate immunity elements, particularly the Toll-like receptors (TLRs) that recognize nucleic acid ligands, in inflammatory and autoimmune diseases. Here, we discuss the intriguing role of TLR7 and TLR9 in developing SLE and LN. Also included are the essential characteristics of conventional treatments and some other novel and little-explored alternatives that offer options to improve renal function in LN.

Structural deformations are one of the most significant factor that affects machine tool (MT) positioning accuracy. These induced errors are complex to be represented by a model, nevertheless they need to be evaluated and predicted in order to increase the machining performance. This paper presents a novel approach to calibrate a machine tool in real-time, analyzing the thermo-mechanical errors through Fibre Bragg Grating (FBG) sensors embedded in the MT frame. The proposed configuration consists of an adaptronic structure of passive materials, Carbon Fibre Reinforced Polymers (CFRP), equipped by FBG sensors that are able to measure in real-time the deformed conditions of the frame. By using a proper thermo-mechanical kinematic model, the displacement of the end effector may be predicted and corrected when it is subjected to external undesired factors. By starting from a set of FE simulations to develop a model able to describe the MT structure stresses, a prototype has been fabricated and tested. The scope was to compare the numerical model with the experimental tests using FBG sensors. The experimental campaign has been performed varying the structure temperature over time and measuring the tool tip point (TTP) positions. The obtained results showed a substantial matching between the real and the predicted position of TTP confirming the effectiveness of the proposed calibration system.

Current smartphones incorporate different types of sensors that allow us to know our spatial position, they give us information about pressure, speed, acceleration, time, acoustic level, and other different physical magnitudes. These smartphones measure each component of the magnetic field, bearing in mind that any current perpendicular to a magnetic field produces a small potential difference, transversal to the said current, being this voltage easily measurable by Hall sensors. With the implementation of three Hall sensors, and an appropriate app, we can measure the three components of the magnetic field vector, and with this we can obtain information and deduce properties of the physical systems considered. In this paper we are exploring the use of smartphones in a physics laboratory for freshman students. To do this, we have measured, using Hall sensors, the magnetic field created by a linear quadrature, and we have obtained, first of all, its dependence on the distance between the quadrupole and the magnetic sensor. The second purpose of this work is to show that the laboratory is a powerful tool that increases the significant learning of freshman students through advanced technological tools.

We believe that a natural focus of the Physics Education Research community is on understanding and improving student learning in our physics courses. For this purpose, we are introducing smartphones in the physics laboratory. Current smartphones measure each component of the magnetic field, bearing in mind that any current perpendicular to a magnetic field produces a small potential difference, transversal to the said current, being this voltage easily measurable by Hall sensors. In this work, we have considered the magnetic field created by a linear quadrupole and we have studied its dependence on distance. Using an experimental procedure that is simple we have measured the magnetic field using the Hall sensor that most smartphones have, together with the corresponding app. The purpose of this work is to show that the laboratory is a powerful tool that increases significant learning under three conditions: 1) the practice must not be too sophisticated; 2) students must handle objects in the lab; and 3) the practice must be scientifically accurate, including the adjustments by minimum squares, and the following and necessary error calculation.

Water is a fundamental resource for ecosystems, humans, and the development of all economic sectors; it is necessary to identify and evaluate its environmental pressures or impacts. The water footprint (WF) is an appropriate indicator for the consumption of water used to produce a product. The present study uses this tool to evaluate the green and blue water requirements and the sustainability of irrigation water use for agroindustrial avocado production in Ziracuaretiro, Michoacán (2012-2021). Our analysis was based on aggregating weather and soil data at the municipal level and official government databases of avocado cultivated surface, fruit production, and water rights concessions. The analysis considers the homogeneity of information throughout the study area. We estimated that rainfed plantations require 839.03 m³/ton and irrigated plantations require 2355.80 m³/ton, with an average of 1597.47 m³/ton. In addition, we determined that avocado cultivation can demand up to 124.3% of agricultural water concessions in this municipality. In addition to the WF estimates, the analysis indicates that such studies are fundamental for decision-makers to develop and implement water use-efficiency strategies and shows the need for further research related to water consumption of avocado as a crop at more detailed scales to reduce uncertainty.

In this article we analyze the determinants and the export trend of European countries of medium and high technology products. The data were analyzed using various econometric models, namely WLS, Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects. The results show that exports of medium and high-tech products are positively associated, among other variables, with the value of “Average Annual GDP Growth”, “Total Entrepreneurial Activity” and “Sales Impacts”, and negatively associated with, among other variables, “Human Resources”, “Government and Procurement of Advanced Technology Products” and “Buyer Sophistication”. A cluster analysis was realized with the k-Means algorithm optimized with the Silhouette coefficient. The result showed the presence of only two clusters. Since this result was considered poorly representative of the industrial complexity of the European Union countries, a further analysis was carried out with the Elbow method. The result showed the presence of 6 clusters with the dominance of Germany and the economies connected to the German economy. In addition, a network analysis was carried out using the distance to Manhattan. Four complex network structures and two simplified network structures were detected. A comparison was then made between 10 machine learning algorithms for predicting the value of exports of medium and high-tech products. The result shows that the best performing algorithm is the SGD. An analysis with Augmented Data-AD was implemented with a comparison between 10 machine learning algorithms for prediction and the result shows that the Linear Regression algorithm is the best predictor. The prediction with the Augmented Data-AD allows to reduce the MAE by about 0.0022131 compared to the prediction with the Original Data-OD.

The escalating demand for multifunctional and advanced materials for growing industries has turned scientific exploration to graphene-based hybrid filler polymer composites. The introduction of graphene with other fillers into polymer matrices results in astonishing properties and thus has gained significant attention in recent years. This study addresses the significance of graphene-based hybrid filler polymer composites in progressive materials science and engineering. The paper encloses some traditional and current preparation techniques employed in the fabrication of composites and a comprehensive review of successfully prepared graphene hybrid polymer composites with enhanced mechanical, thermal, and electrical properties reported in published research. The role of different factors, e.g., filler type, aspect ratios, filler-matrix compatibility, dispersion effects, homogeneity, filler orientation through polymer matrices, and curing conditions, are summarized. Finally, the applications in heavy industries, e.g., aerospace, electronics, energy storage, and automotive sectors were also analyzed. We hope this study will serve as a practical resource for new researchers and practitioners to understand and harness the full potential of these composites in various scientific and industrial fields.

In this article we investigate the determinants of the European “Most Cited Publications”. We use data from the European Innovation Scoreboard-EIS of the European Commission for the period 2010-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Results show that the level of “Most Cited Publications” is positively associated, among others, to “Innovation Index” and “Enterprise Birth” and negatively associated, among others, to “Government Procurement of Advanced Technology Products” and “Human Resources”. Furthermore, we perform a cluster analysis with the k-Means algorithm either with the Silhouette Coefficient and the Elbow Method. We find that the Elbow Method shows better results than the Silhouette Coefficient with a number of clusters equal to 3. In adjunct we perform a network analysis with the Manhattan distance, and we find the presence of 4 complex and 2 simplified network structures. Finally, we present a confrontation among 10 machine learning algorithms to predict the level of “Most Cited Publication” either with Original Data-OD either with Augmented Data-AD. Results show that the best machine learning algorithm to predict the level of “Most Cited Publication” with Original Data-OD is SGD, while Linear Regression is the best machine learning algorithm for the prediction of “Most Cited Publications” with Augmented Data-AD.

In order to meet the Millennium Development Goals set forth by the United Nations’ Millennium Summit that took place in 2000, in New York, particularly in the area of education, the Mozambican Government decided that, from 2003 onwards, during their primary school formation, students should be passed automatically even if they do not have enough intellectual capacities that justify their progress. In fact, this decision was made during a period when there were many pupils being failed, due to various reasons. After more than 15 years of its implementation, this paper aims to analyzing the results acquired from this decision, from the point of view of the quality of education. This will be done taking into account the prevailing situation of education in Mozambique. Having considered these aspects, the paper will move on to presenting some of the challenges and opportunities that the country should consider in the area of education, as a way to bring about better outcomes and promote development, in the country.

Ultrasonography is a relevant diagnostic tool extensively used andrology of human and do-mestic animals, including dogs. The present review aimed to describe all the technologies based on ultrasound, starting with the basic B-Mode ultrasonography to the recent contrast-enhanced ultrasonography (CEUS) and the ultrasound elastography, available to assess the testicle of the dog. The principles of the different technologies and the relevant findings in normal and ab-normal testicular conditions were described and discussed. B-mode ultrasonography aims at the examination of the testis detecting focal lesions but lacks objectivization. Other technologies, such as Doppler ultrasonography, B-Flow, and CEUS allow the definition of vascular patterns, that could be measured with specific applications, such as spectral Doppler or quantitative CEUS. Finally, ultrasound elastography allows the estimation of parenchyma stiffness, in both qualitatively and quantitatively manner. Ultrasound-based technologies assist the andrology in the evaluation of the testicular function and integrity, offering valuable information to define pathological conditions that could have an impact on the health and life quality of the male dog.

Silk fibroin is a well-known biopolymer used in several applications in which the interaction with biological tissue is required. In fact, fibroin is extremely versatile and can be shaped to form several constructs useful in tissue engineering applications. Confocal imaging is usually per-formed to test the cells behaviour on the construct and in this context the fibroin autofluorescence is regarded as a problem. In addition, the autofluorescence is not intense enough to provide useful morphological images. In fact, to control study the constructs morphology other techniques are used (i.e. SEM, Micro-CT). In this work we propose a method based on the fluorescence energy transfer (FRET) to suppress the fibroin autofluorescence moving it to higher wavelength accessible to the confocal microscopy for a direct imaging.

The dynamic behaviour of a machine tool (MT) directly influences the machining performances. The adoption of lightweight structures may reduce the effects of undesired vibrations and increasing the workpiece quality. This paper aims to present and compare a set of hybrid materials that may be excellent candidate to fabricate the MT moving parts. The selected materials have high dynamic characteristics and capacity to damp mechanical vibrations. In this way, starting by the kinematic model of a milling machine that highlights the main critical factors, this study paper evaluates a number of prototypes made of Al Foam sandwiches (AFS), Al Corrugated sandwiches (ACS) and materials reinforced by carbon fibres (CFRP). A set of prototypes has been fabricated, represented the Z-axis ram of a commercial milling machine. The static and dynamical properties have been evaluated by using both FE simulations and experimental tests. The obtained results show that the proposed structures may be a valid alternative to the conventional materials of MT moving parts, increasing machining performances. In particular, the AFS prototype highlighted a damping coefficient that is 20 times greater than a conventional ram (e.g. steel). The CFRP structure is able to satisfy the machining requirements with a reduced weight of 48.5%, while the ACS prototype showed a good trade-off between stiffness and damping.

This paper proposes an innovative mechatronic piezo-actuated module to control vibrations in modern machine tools. Vibrations represent one of the main issues that compromise seriously the quality of the workpiece. The active vibration control (AVC) device is composed by a host part integrated with sensors and actuators synchronized by a regulator, able to make a self-assessment and adjust to the environmental alteration. This study presents the mechatronic model based on the kinematic and dynamic analysis of the AVC device. To ensure a real time performance, a H2-LQG controller has been developed and validated by simulations involving machine tool, PZT actuator and controller models. The Hardware-in-the-loop (HIL) architecture is adopted to control and attenuate the vibrations. A set of experimental tests has been performed to validate the AVC module on a commercial machine tool. The feasibility of the real time vibration damping is demonstrated and the simulation accuracy is evaluated.

The evaluation of robotic hands is a subjectively biased, complex process. The fields pertaining to robotic hands are human-centric in nature, making human hands a good standard for benchmark comparisons of robotic hands. To achieve this, we propose a new evaluation index, where we evaluate robotic hands on three fronts: their form, features and performance. An evaluation on how anthropomorphic robotic hands are in basic mobility, and appearance constitutes the ``Form'', while features that can be read, changed and actuated for effective control of robotic hands constitutes the ``Features''. We derived these key features from an extensive analysis of robotic hands in literature. Finally, the robotic hands carry out a series of tasks that evaluate their ``Performance''. An individual score for each category is drawn and we carry out a three-pronged analysis. We also propose an additional feature in the form of price to provide context when analysing multiple hands.

Definitions of bronchopulmonary dysplasia (BPD) or post-prematurity respiratory disease (PPRD) aim to stratify the risk of mortality and morbidity, with an emphasis on long-term respiratory outcomes. There is no univocal classification of BPD, due to its complex multifactorial nature and the substantial heterogeneity of clinical presentation. Currently, there is no definitive cure available for extremely premature very-low-birth-weight infants with BPD, and challenges in finding targeted preventive therapies persist. However, innovative stem cells-based postnatal therapies targeting BPD-free survival are emerging, which are likely to be offered in the first few days of life to higher-risk subpopulations of premature infants. Hence the need for easy-to-use noninvasive tools for a standardized, precise and reliable BPD assessment at a very early stage, to support clinical decision-making and to predict the response to treatment. In this non-systematic review, we present an overview of strategies for monitoring preterm infants with early and evolving BPD-PPRD, and make some remarks on future prospects, with a focus on near-infrared spectroscopy (NIRS).

In this article we investigate the role of “Renewable Energy Consumption” in the context of Circular Economy. We use data from the World Bank for 193 countries in the period 2011-2020. We perform several econometric techniques i.e., Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS. Our results show that “Renewable Energy Consumption” is positively associated among others to “Cooling Degree Days” and “Adjusted savings: net forest depletion” and negatively associated among others to “GHG net emissions/removals by LUCF” and “Mean Drought Index”. Furthermore, we perform a cluster analysis with the application of the k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of two clusters. Finally, we compare eight different machine learning algorithms to predict the value of Renewable Energy Consumption. Our results show that the Polynomial Regression is the best algorithm in the sense of prediction and that on average the renewable energy consumption is expected to growth of 2.61%.

Heart failure with preserved ejection fraction (HFpEF) remains a poorly characterized syndrome with many dark aspects related to different patients profile, various associated risk factors and wide aetiologies. It comprises several pathophysiological pathways related to endothelial dysfunction, myocardial fibrosis, extracellular matrix deposition and high inflammatory response. Up to now, it has been described only for clinical appearance and most common associated risk factors without an effective characterization of biological processes responsible for cardiovascular deteriorations. Recent advances in laboratory and metabolomic researches showed that HFpEF appears strictly related to specific cells and molecular mechanisms dysregulation. Some biomarkers are capable to early identify these processes adding new insights into diagnosis and risk stratification. Additionally recent advances on intermediate metabolites reflecting provide relevant information on intrinsic cellular and energetic substrate alterations. The systematic combination of clinical imaging and laboratory data may lead to a precision medicine approach providing prognostic and therapeutic advantages. Current review reports traditional and emerging biomarkers recently investigated in HFpEF setting, and it purpose a new diagnostic approach based on integrative information achieved from risk factors burden, hemodynamic dysfunction and biomarkers signature partnership.

Optimism and self-efficacy have been associated with psychological health. Empathy has also been found to promote positive functioning and to have a unique role in community health volunteering. This study investigated whether self-efficacy and optimism were associated with psychological and subjective well-being in a group of healthcare volunteers and whether empathy added incrementally to these associations. A sample of 160 Italian clown doctors volunteering in various hospitals completed self-report measures of self-efficacy, optimism, empathy, psychological well-being, and subjective well-being. Results indicated that self-efficacy and optimism were associated with both outcomes and that aspects of empathy, such as others’ perspective-taking and personal distress for others’ difficulties, incrementally added to these associations, although with opposite effects. The present study adds to previous research on the role of self-efficacy, optimism, and empathy for community health volunteers’ psychological health and offers suggestions regarding the training of this type of volunteer.

Scientific evidence increasingly supports the strong link between diet and health, acknowledging that a well-balanced diet plays a crucial role in preventing chronic diseases such as obesity, diabetes, cardiovascular issues, and certain types of cancer. This perspective opens the door to developing precision diets, particularly tailored for individuals at risk of developing cancer. It encompasses a vast research area and involves the study of an expanding array of compounds with multi-level "omics" compositions, including genomics, transcriptomics, proteomics, epigenomics, miRNomics, and metabolomics. We review here the components of the Southern European Atlantic Diet (SEAD) from both a chemical and pharmacological standpoint. The information sources consulted, complemented by crystallographic data from the Protein Data Bank, establish a direct link between SEAD and its anticancer properties. The data collected strongly suggest that SEAD offers an exceptionally healthy profile, particularly due to the presence of beneficial biomolecules in its foods. The inclusion of olive oil and paprika in this diet provides numerous health benefits, and science supports the anti-cancer properties of dietary supplements with biomolecules sourced from vegetables of the brassica genus. Nonetheless, further research is warranted in this field to gain deeper insights into the potential benefits of SEAD's bioactive compounds against cancer.

Cereals and their derivatives are the basis of human nutrition. However, cereals also contribute to the dietary exposure to toxic metals that may pose a risk. Strengthening food security and nutrition information is a high priority challenge for the Cape Verde Government. The toxic metals content (Cr, Ni, Sr, Al, Cd, Pb) has been determined in 126 samples of cereals and derivatives (rice, corn gofio, corn flour, wheat flour, corn, wheat) consumed in Cape Verde. Wheat flour samples stand out for registering the highest Sr (1.60 mg/kg), Ni (0.25 mg/kg) and Cr (0.13 mg/kg). The results show relevant Al levels (1.17 – 13.4 mg/kg) with its highest levels in corn gofio. The mean Pb average content in the cereals is 0.03 – 0.08 mg/kg with the highest level observed in corn gofio. The Al and Pb levels are lower in cereals without husks. A consumption of 100 g/day of corn gofio provide an intake of 1.34 mg Al/day (13.7% of the tolerable weekly intake established at 1 mg/kg bw/week) and 8 µg Pb/day (20% of the BMDL set at 0.63 µg/kg bw/day for nephrotoxic effects). The minimization of the dietary exposure of the Cape Verdean population to toxic metals is through the importation of higher quality cereals.

Background. Candida bloodstream infections (CBSIs) have decreased among pediatric populations in the United States, but remain an important cause of morbidity and mortality. Species distributions and susceptibility patterns of CBSI isolates diverge widely between children and adults. Awareness of these patterns can inform clinical decision-making for empiric or pre-emptive therapy of children at risk for candidemia. Methods. CBSIs occurring from 2006-2016 among patients in a large children’s hospital were analyzed for age specific trends in incidence rate, risk factors for breakthrough-CBSI and death, as well as underlying conditions. Candida species distributions and susceptibility patterns were evaluated in addition to antifungal agent use. Results. The overall incidence rate of CBSI among this complex patient population was 1.97/1,000 patient-days. About half of CBSI episodes occurred in immunocompetent children and 14% in Neonatal Intensive Care Unit (NICU) patients. Antifungal resistance was minimal: 96.7% of isolates were fluconazole-, 99% were micafungin-, and all were amphotericin susceptible. Liposomal amphotericin was the most commonly prescribed antifungal agent including for NICU patients. Overall CBSI-associated mortality was 13.7%; there were no deaths associated with CBSI among NICU patients after 2011. Conclusions. Pediatric CBSI characteristics differ substantially from those in adults. Improved management of underlying diseases and antimicrobial stewardship may further decrease morbidity and mortality from CBSI while continuing to maintain low resistance rates among Candida isolates.

The nursing process in clinical practice can be assessed using standardized language systems. The purpose is to find evidence on the effectiveness of the nursing process with standardized terminology using NANDA International, Nursing Interventions Classification, and Nursing Outcome Classification improving diag-nostic accuracy, nursing interventions, health outcomes, and people’s satisfaction. A systematic review was carried out in Medline and PreMedline, Embase, The Cochrane Library, CINAHL, SCI-EXPANDED, SSCI and Scielo and LILACS including randomized clinical trials, quasi-experimental, cohort and case-control studies. Selection and critical appraisal were conducted by two independent reviewers. The certainty of the evidence was assessed with Grading of Recommendations Assessment, Development and Evaluation Methodology. 17 studies were included with variability in the level and certainty of evidence. According to outcomes, 6 evaluated improvements in diagnostic accuracy and 11 evaluated improvements in individual health outcomes. No studies evaluated improvements in intervention efficacy or population satisfaction. There is a need to increase studies with rigorous methodologies that address diagnostic accuracy and indi-viduals’ health outcomes using NANDA International, Nursing Interventions Classification, and Nursing Outcome Classification; as well as implementing studies that evaluate the use of these terminologies for improvements in the efficacy of nurses' interventions and population satisfaction with the nursing process.

In this article, we propose a circuit to imitate the behavior of a Reward-Modulated Spike-Timing-Dependent Plasticity synapse. When two neurons in adjacent layers produce spikes, each spike modifies the thickness of the common synapse. As a result, the synapse’s ability to conduct impulses is controlled, leading to an unsupervised learning rule. By introducing a reward signal, reinforcement learning is enabled by redirecting the growth and shrinkage of synapses based on signal feedback from the environment. The proposed synapse manages the convolution of the emitted spike signals to promote either the strengthening or weakening of the synapse, which is represented as the resistance value of a memristor device. As memristors have a conductance range that may differ from the available current input range of typical CMOS neuron designs, the synapse circuit can be adjusted to regulate the spike’s amplitude current to comply with the neuron. The circuit described in this work allows for the implementation of fully interconnected layers of neuron analog circuits. This is achieved by having each synapse reconform the spike signal, thus removing the burden of providing enough power from the neurons to each memristor. The synapse circuit was tested using a CMOS analog neuron described in the literature. Additionally, the article provides insight into how to properly describe the hysteresis behavior of the memristor in Verilog-A code. The testing and learning capabilities of the synapse circuit are demonstrated in simulation using the Skywater-130nm process. The article’s main goal is to provide the basic building blocks for Deep Neural Neural Networks relying on spiking neurons and memristors as the basic processing elements to handle spike generation, propagation, and synaptic plasticity.

With confirmed COVID-19 cases surpassing the 8.5 million mark around the globe, there is an imperative need to deepen the efforts from the international scientific community to gain comprehensive understanding of SARS-CoV-2. Although the main clinical manifestations are associated with respiratory or intestinal symptoms, reports of specific and non-specific neurological signs and symptoms, both at presentation or during the course of the acute phase, are increasing. Approximately 25-40% of the patients present neurological symptoms. The etiology of these neurological manifestations remains obscure, and probably involves several direct pathways, not excluding the direct entry of the virus to the Central Nervous System (CNS) through the olfactory epithelium, circumventricular organs, or disrupted blood-brain barrier (BBB). Furthermore, neuroinflammation might occur in response to the strong systemic cytokine storm described for COVID-19, or due to dysregulation of the CNS angiotensin system. Descriptions of neurological manifestations in patients in the previous coronavirus (CoV) outbreaks have been numerous for the SARS-CoV and lesser for MERS-CoV. Strong evidence from patients and experimental models suggests that some human variants of CoV have the ability to reach the CNS and that neurons, astrocytes and/or microglia can be target cells for CoV. A growing body of evidence shows that astrocytes and microglia have a major role in neuroinflammation, responding to local CNS inflammation and/or to dysbalanced peripheral inflammation. This is another potential mechanism for SARS-CoV-2 damage to the CNS. In this work we will summarize the known neurological manifestations of SARS-CoV-2, SARS-CoV and MERS-CoV, explore the potential role for astrocytes and microglia in the infection and neuroinflammation, and compare them with the previously described human and animal CoV that showed neurotropism. We also propose possible underlying mechanisms by focusing on our knowledge of glia, neurons, and their dynamic intricate communication with the immune system.

In this article, we estimate the value of Government Expenditure on Education-GEE in the context of Environmental, Social and Governance-ESG dataset of the World Bank. We use data from 193 countries in the period 2011-2020. We use Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled Ordinary Least Squares-OLS, and Weighted Least Squares-WLS. Our results show that the value of GEE is positively associated among others to “Case of Death, by communicable disease and maternal, prenatal and nutrition conditions”, and “Unemployment”, and negatively associated among others to “Hospital Beds” and “Government Effectiveness”. Furthermore, we apply the k-Means algorithm optimized with the Elbow Method and we find the presence of four clusters. Finally, we confront eight machine learning algorithms for the prediction of the future value of GEE. We found that the Polynomial Regression is the best predictive algorithm. The Polynomial Regression predicts an increase in GEE of 7.09% on average for the analysed countries.

We analyze the question of GDP Growth-GDPG rate in the context of Environmental, Social and Governance-ESG framework. We use World Bank data for 193 countries in the period 2011-2020 using different econometric techniques i.e., Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled Ordinary Least Squares-OLS. We found that GDPG rate is positively associated, among others, to “Government Effectiveness” and “Prevalence of Undernourishment” and negatively associated among others to “Unemployment” and “Research and Development Expenditure”. Furthermore, we have applied the k-Means algorithm optimized with the Elbow method and we found the presence of four clusters in the sense of GDPG rate. Finally, we confront eight machine learning algorithms to predict the value of GDPG rate and we found that the Polynomial Regression is the best predictor. The Polynomial Regression predicts an increase of GDPG rate equal to 2.88% on average for the analysed countries.

We estimate the determinants of Emissions-COE in the context of Environmental, Social and Governance-ESG model at world level. We use data of the World Bank for 193 countries in the period 2011-2020. We found that the level of COE is positively associated, among others to “Methane Emissions”, “Research and Development Expenditures”, and negatively associated among others to “Renewable Energy Consumption” and “Mean Drought Index”. Furthermore, we have applied a cluster analysis with the k-Means algorithm optimized with the Elbow Method and we find the presence of four cluster. Finally, we apply eight machine-learning algorithms for the prediction of the future value of COE and we find that the Artificial Neural Network-ANN algorithm is the best predictor. The ANN predicts a reduction in the level of COE equal to 5.69% on average for the analysed countries.