The mutualistic interactions between the oleaginous yeast Lipomyces starkeyi and the green mi-croalga Chloroidium saccharophilum in mixed cultures were investigated to exploit possible syner-gistic effects. As a matter of facts, microalga could act as an oxygen generator for the yeast, while the yeast could provide carbon dioxide to microalga. A lignocellulosic hydrolysate from steam exploded Arundo donax (Giant reed) was used as low cost feedstock. The overall lipid content and lipid productivity obtained in the mixed culture treating the hydrolysate of Arundo donax were equal to 0.081 glipid.gbiomass-1 and 37.2 mglipid.L-1.d-1, respectively. They represented promising re-sults if compared to the model systems where synthetic media were used. This study provided new input for the integration of Single Cell Oil (SCO) production with agro-industrial feedstock and the fatty acid distribution mainly consisting of stearic (C18:0) and oleic acid (C18:1) allows promising applications in biofuels, cosmetics, food additives and other products of industrial interest.

Methicillin-resistant Staphylococcus aureus (MRSA) infections, in particular biofilm-organized bacteria, remain a clinical challenge and a serious health problem. Rifabutin (RFB), an antibiotic of the rifamycins class, has shown in previous work excellent anti-staphylococcal activity. Here, we proposed to load RFB in liposomes aiming to promote the accumulation of RFB at infected sites and consequently enhancing the therapeutic potency. Two clinical isolates of MRSA, MRSA-C1 and MRSA-C2, were used to test the developed formulations, as well as the positive control, vancomycin (VCM). RFB in free and liposomal forms displayed high antibacterial activity, with minimal inhibitory concentrations (MIC) ranging from 0.009-0.013 μg/mL and MBIC50 values ranging from 0.008-0.012 μg/mL, in planktonic and biofilm bacteria, respectively. Confocal microscopy studies demonstrated the rapid internalization of unloaded and RFB-loaded liposomes in the bacterial biofilm matrix. In murine models of systemic MRSA-C1 infection, Balb/c mice were treated with RFB formulations and VCM at 20 and 40 mg/kg of body weight, respectively. Obtained data proved the superior therapeutic effectiveness of RFB formulations compared to Control and VCM groups even using a two-fold lower therapeutic dose as demonstrated by significantly reduced bacterial burden and growth index values in major organs. In addition, RFB formulations were the only formulations associated with 100% survival. Globally, this study emphasizes the potential of RFB nanoformulations as an effective and safe approach against MRSA infections.

Shared public buildings have become centers of innovation, integrating advanced technologies to meet evolving societal needs. With a heightened emphasis on occupants’ health and well-being, these buildings serve as hubs for technological convergence, facilitating seamless connectivity and intelligent data analysis and management. Within this context, environmental monitoring emerges as a foundational element, pivotal to all aspects of building management. This article provides findings from the nationally funded RE-START project, which focuses on shared public buildings, with special regard to educational and medical facilities. The project explores enhanced indoor air quality monitoring, focusing in particular on CO2 concentration that is directly correlated with occupancy, as a fundamental element for developing health and safety protocols, energy efficiency strategies, integration of smart building technologies, and data-driven energy management. The intersection of environmental monitoring, energy efficiency, security, and IoT technologies in in indoor spaces are relevant. The outcomes of the study reveal the delicate nature of all the involved components, that need to be carefully developed in an integrated manner.

Affordances are an important concept in cognition, which can be applied to robots in order to perform a successful human-robot interaction (HRI). In this paper we explore and discuss the idea of emotional affordances and propose a viable model for implementation into HRI. We consider “2-ways” affordances: perceived object triggering an emotion, and perceived human emotion expression triggering an action. In order to make the implementation generic, the proposed model includes a library that can be customised depending on the specific robot and application’s scenario. We present the AAA (Affordance-Appraisal-Arousal) model, which incorporates Plutchik’s Wheel of Emotions, and show some examples of simulation and possible scenarios.

The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores into cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.

There is a growing trend among consumers to seek out natural foods and products with natural ingredients. This shift in consumer preferences had a direct impact on both food and pharmaceutical industries, leading to a focus of scientific research and commercial efforts to meet these new demands. The aim of this work is to review recent available scientific data on foods of interest, such as artichoke, gooseberry, and polygonoideae plants, as well as olive oil and red raspberries. Interestingly, the urgency of solutions to the climate change emergency has brought new attention to by-products of grapevine bunch stem and cane, which have been found to contain bioactive compounds with potential health benefits. There is a pressing need for a faster process of translating scientific knowledge from the laboratory to real-world applications, especially in the face of the increasing societal burden associated to non-communicable diseases (NCDs), environmental crises, the post-pandemic world, and ongoing violent conflicts around the world.

The hotel sector generates related environmental aspects from its construction process to the operation of its activities, products and services. In this way, corporate environmental management becomes directly linked, since it provides an adequate management of its resources, thus minimizing impacts. Thus, this research aims to carry out a socioeconomic and environmental diagnosis of the hotel sector in the municipality of Mossoró-RN. The study was classified in an exploratory, descriptive and explanatory way, with a qualitative-quantitative approach that is based on bibliographic, documentary and field research, carried out in 10 lodging facilities, through the application of questionnaires, on general aspects, initial environmental assessment and environmental aspects, and the data obtained were treated in Microsoft Excel software with the objective of creating a model and demonstrating results on the sustainable level of each establishment in question. The profile of the lodging facilities analyzed is characterized by 50% having from 10 to 30 rooms, 80% having between 10 and 30 employees, 80% being micro-enterprises, with 50% in an area of 750 m² to 2250 m² and 80% operating for more than 10 years. Point out a relevant result on the impacts of companies. The projects analyzed were built without any complaint for environmental crime and without negative impacts on the local population. Actions to reduce consumption were also observed, especially for the rationalization of water and energy. To this end, it points out that the adoption of the Environmental Management System (EMS) as a differential in the management of aspects and impacts of the hotel sector.

Background: Colorectal adenoma undergoes neoplastic progression via the normal epithelium-adenoma-adenocarcinoma sequence as reported in the Vogelgram. The risk of developing cancer is strongly associated with the number and size of adenoma and with the subtype. Currently, adenomatous polyps can be distinguished on the basis of histology: the prevalence are tubular, 5-15% are villous and tubular/villous. Considering the increased risk for malignant transformation described for tubular/villous adenomas, patients diagnosed with adenomatous polyposis are at increased risk of developing CRC. The Wnt/β-catenin pathway plays a key role in the onset of colorectal adenoma, in particular intestinal cells first acquire loss-of-function mutations in APC gene that induce the formation of adenomas. Methods: Wnt/β-catenin pathway APC, Wnt3a, Wnt5a, LEF1, BCL9 genes and protein expression analyses were conducted by qRT-PCR and western blot in 68 colonic samples (polyps and adjacent mucosa) from 41 patients, of which 17 affected by FAP. Ten normal colonic mucosal samples were collected from 10 healthy donors. Results: In this study both APC gene and protein resulted less expressed in colon tumor compared to the adjacent colonic mucosa. Conversely, activated β-catenin was more expressed in polyps than in the adjacent mucosa. All results confirmed literature data on carcinomas. A statistically significant correlation between Wnt3a and BCL9 both in polyps and in the adjacent mucosa underlies that the canonical Wnt pathway is activated in early colon carcinogenesis and that the adjacent mucosa is already altered. Conclusion: This is the first study analyzing the difference in expression of Wnt/β-catenin pathway in human colorectal adenomas. Understanding the progression from adenomas to colorectal carcinomas is essential for the development of new therapeutic strategies and improving clinical outcomes.

Along with climate change, the native forest replacement by exotic species, such as Eucalyptus globulus, is contributing to a highly fire-prone environment. Since E. globulus detains several post-fire regeneration strategies, sustainable practices are needed to manage eucalyptus stands. Thus, eucalyptus allelopathic potential can be used for weed control. Therefore, this study aimed at assessing the herbicidal potential of post-fire regenerated E. globulus leaves in Portulaca oleracea, and unraveling the main physiological processes disturbed by biocide application. For this, an aqueous extract prepared with fresh leaves (FLE; 617 g_{fresh weight}L^-1) and other with oven-dried leaves (DLE; 250 g_{dry weight}L^-1) were prepared and foliar-sprayed twice-a-week at different dilutions in 7-days-old purslane plants. As positive control, glyphosate was used. After five weeks, results revealed that DLE at the highest dose detained the greatest herbicidal activity against P. oleracea. To understand how DLE impacted weed physiology, several biochemical and redox-related parameters were evaluated in purslane plants treated with DLE highest dose. Results suggested an overproduction of hydrogen peroxide, causing severe oxidative damage in roots. Overall, this study showed that young E. globulus dried leaves had powerful herbicidal properties against P. oleracea and can represent a feasible approach for weed management, while reducing fire hazard.

Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder that affects women of reproductive age representing the primary cause of anovulatory infertility. The nonapeptide oxytocin (OT) plays an important role in cognitive, emotional, and reproductive functions in human beings. Oxytocin receptors are expressed in several body parts including the ovaries. Despite this, the possible role played by oxytocin in symptoms of PCOS is not clear. The present systematic review aimed at understanding, the presence of possible oxytocin level alterations in PCOS, the connection between alterations of OT levels and the symptoms of PCOS, and the effect of oxytocin administration in PCOS. After a systematic search in the principal databases, seven studies, five human and two animal, were included. Most of the studies highlighted the role played by oxytocin in fertility issues related to PCOS. Studies that analyzed oxytocin basal levels in PCOS women agreed that PCOS is associated with a reduction in the serum level of oxytocin. Two studies found that in PCOS the serum levels of oxytocin were lower than healthy controls. One human and one animal study agreed about lower levels of PCOS, confirming a possible implication of a dysfunction of OT, in the pathogenesis of PCOS.

Menin inhibitors are new and promising agents currently in clinical development that target the HOXA/MEIS1 transcriptional program which is critical for leukemogenesis in histone-lysine N-methyltransferase 2A rearranged (KMT2Ar) and in NPM1-mutated (NPM1mut) acute leukemia. The mechanism of action of this new class of agents is based on the disruption of menin-KMT2A complex (constitute of chromatin remodelling proteins), leading to the differentiation and apoptosis of AML cells expressing KMT2A or mutated NPM1. This new class of drugs has been tested alone, or in combination with synergistic drugs, in phase I and II clinical trials (AUGMENT-01 and 02, KOMET-01 and 07, SAVE, COVALENT trial and others), showing promising results in terms of response rates and safety in heavily pre-treated acute leukemia patients. In this review, we summarise the key findings on menin inhibitors, focusing on the mechanism of action and preliminary clinical data of this emerging and promising class of agents, in particular revumenib and ziftomenib.

We re-inventoried red wood ant nests (RWA) in 12 study sites (≈1281 ha) in the Westeifel Volcanic Field, Germany, in an area-wide and integrated ecosystem approach after 12 years. Combined with the re-identification of previously mapped nests using a photo database, this approach leads to more accurate nest counts in (re)inventories. A total increase of nests from 1144 (2009) to 1252 (2021), and a dramatic one for the Heidberg site by 52-fold (2009) and 85-fold (2021) compared to a 1984 inventory was observed, contrasting with earlier postulations of a decline in RWA. Early to medium mature (41-80 years) and mature (³81–140 years) spruce forests were the preferred habitat. Large increase in small nest sizes suggests an increase in new nest settlements also in clearings, despite climate-induced forest dieback over the past decade. A decline in biodiversity in the herbaceous layer was observed; highly proliferating blackberries had no negative impact on RWA nests. Monitoring of woodpecker cavities in RWA nests is suggested as an indirect indicator tool for evaluating populations in forests. Positive ground movement rates caused by the Eifel plume are suggested another factor favoring nest settlements. This study contributes to the urgent update of statistically valid data required to a) effectively substantiate the status-quo of RWA occurrences, b) protect RWA as ecosystem engineers, c) advance understanding of Geo-Bio-Interactions in the wake of climate change, and c) contribute to the German government's Insect Conservation Action Program.

Background: The mortality and severity in COVID-19 is increased in patients with comorbidities. The aim of this study was to evaluate the unknown risk of severity and mortality in COVID-19 patients with underlying kidney and liver diseases. Method: We retrieved data on the clinical features and primary composite end point of COVID-19 patients released from inception till 16^th of April 2020 from Medline and Embase. The data on two comorbidities, liver diseases and chronic kidney disease, present in COVID-19 were pooled and statistically analysed to explain the associated severity and mortality rate. Results: 142 abstracts were screened, and 41 full articles were then read. In total, 22 studies including 5595 COVID-19 patients were included in this study with case fatality rate of 16%. The prevalence of liver diseases and CKD were 3% (95%CI; 2%-3%) and 1% (95%CI; 1%-2%) respectively. In patients with COVID-19 and underlying liver diseases, 57.33% (43/75) cases were severe with 17.65% mortality. While in CKD patients with COVID-19, 83.93% (47/56) severity and 53.33% (8/15) mortality were reported. Conclusion: This study found an increased risk of severity and mortality in COVID-19 patients with liver diseases and CKD. This will allow for better clinical management and inform more stringent preventative measures for this group of patients.

This paper presents a new method to model the nonlinear behaviour of masonry double curvature structures, possibly reinforced by composite materials, by means of conventional elasto-plastic analyses. It is meant to be used in professional design, especially for assessment and retrofitting purposes, therefore based on the exploitation of the simplest nonlinear Finite Elements available in a commercial software, namely trusses with elasto-fragile and elasto-ductile behaviour (Cutoff Bars). The numerical static nonlinear analyses are carried out by considering elastic hexahedral elements for bricks and lumping nonlinearities on joints. These have been assumed in turn elastic-brittle and elastic-plastic by using 1D elements, respectively Point Contacts, under No-Tension Material hypothesis, and Cutoff Bars, assigning small tensile resistance to the material. The reinforcement, realised with FRP hooping strips, has been successfully modelled in a similar fashion, i.e. by applying perfectly bonded elastic-plastic Cutoff Bars at the extrados of the dome, where the debonding is accounted for in a conventional way limiting the tensile strength according to Italian Standards indications. The procedure is validated against benchmark models with the same geometry, using experimental data and more refined structural model results for comparison.

Taxes on the consumption of certain products have played a key role in public revenue analysis in European countries. This work aims to assess the differences in tax planning on new non-combustion products across some European territories. Through theoretical analysis, the paper has three distinct aspects. Firstly, we show the taxpayer profile in different countries. Secondly, the study analyzes the risks for the health system and the individual. Thirdly, the design of the land tax is based on previous experience and planning in Europe. This paper concludes with a case study for different countries: 1) Spain “vapers” and “smokers”, where the analysis is based on micro-data from the European Health Interview Survey 2020. 2) Sweden with the analysis of snus, shows it as a practice to reach economic savings while decreasing economic costs thanks to the nudging of consumers towards better products. The results show taxation and, specially, land taxation, should consider differences in planning in the case of new products, such as the non-combustion products, given the user per capita income and the potential lower health risks involved.

The peculiar physicochemical features of deep eutectic solvents (DESs), in particular their tunability, make them ideal media for various applications. Despite their ability to solubilize metal oxides, their use as rust removers from valuable substrates has not yet been thoroughly investigated. In this study we chosen three known DESs, consisting of choline chloride and acetic, oxalic or citric acid for evaluating their ability to remove corrosion products from a cellulose-based material as linen fabric and two different lithotypes, as travertine and granite. The artificial staining was achieved by placing a rusty iron grid on their surfaces. The DESs were applied by means of cellulose poultice on the linen fabrics, while on the rusted stone surfaces with a cotton swab. Macro- and microscopic observations, colorimetry and SEM/EDS analysis were employed to ascertain the cleaning effectiveness and the absence of side effects on the samples after treatment. Oxalic acid-based DES was capable of removing rust stains from both stone and cellulose-based samples, while choline chloride/citric acid DES was effective only on stone specimens. The results suggest a new practical application of DESs for the elimination of rust from lithic and cellulosic substrates of precious and artistic value.

Polyphenols are well-known health promoting agents, but they have some limitations due to their spontaneous oxidation. This evidence has limited their use as drugs in the last years. In this field, several chemical modifications have been proposed to overcome these restrictions; among these, the esterification seems to be the preferred. Ester derivatives could be able to reduce the bioavailability problems connected to polyphenols. On the other hand, the presence of the esterase enzymes in the body guarantees the ester hydrolysis, which in turn frees the two molecules that make it up. Lipase-catalyzed esterifications afforded several derivatives of flavonoids glycosides, in green conditions. In this short note, pancreatic porcine lipase was firstly used as a cheap bio-catalyst, to synthesize oleoyl derivatives of quercetin in aglycone form. Results demonstrated how the enzyme acyl regioselective in position C-3, with high yields and easy purification processes

We investigated fault gases (helium, radon, CO₂) in two seismically active Cenozoic sedimentary environments: a) Meinweg (in 2015) at a tectonically quiet horst structure in the Lower Rhine Embayment and b) Bodanrück (in 2012; Lake of Constance) at the Molasse Basin and part of the Freiburg–Bonndorf–Bodensee Fault Zone (FBBFZ). Both study areas were selected because recent “GeoBio-Interactions” findings showed, that red wood ants (RWA) are biological indicators of otherwise undetected degassing systems. A total of 817 soil gas samples was analyzed. Currently, Meinweg can be considered “no ants land” due to the very low background-level geogas concentrations. Thus, anomalies (Rn-CO₂) weakly trending in NE-SW extension direction emerged. This could probably indicate the onset of (re)activation of the NE-SW trending (Variscan) structures or the development of new fractures as an aftershock process of the 1992 Roermond earthquake that occurred about 15 km to the west. Results at Bodanrück (3 RWA clusters and two RWA-free corridors) revealed degassing patterns in NW-SE and NNE-SSW directions in the clusters corresponding to re-activated and recent strike-slip fault systems. No gas anomalies were found in RWA-free corridors. The RWA nest distribution was shown to be a valuable tool for identifying areas of even actively degassing spotty anomalies caused by macro- and microscale brittle deformation masked by sediment cover.

Unmanned Aerial Vehicles (UAVs) in particular multirotors are becoming the {\it de facto} tool for aerial sensing and remote inspection. In large industrial facilities, a UAV can transmit an online video stream to inspect difficult to access structures, such chimneys, deposits and towers. However, the communication range is limited, constraining the UAV operation range. This limitation can be overcome with relaying UAVs placed between the source UAV and the control station, creating a line of communication links. In this work we assume the use of a digital data packet network technology, namely WiFi, and tackle the problem of defining the exact placement for the relaying UAVs that creates an end-to-end channel with maximal delivery of data packets. We consider asymmetric communication links and we show an increase as large as $15$\% in end-to-end packet delivery ratio when compared to an equidistant placement. We also discuss the deployment of such a network and propose a fully distributed method that converges to the global optimal relay positions taking, on average, 1.4 the time taken by a centralized method.

In this short communication, following a brief introduction, we undertake a comprehensive analytical study of the weighted Simpson index. Our primary emphasis concerns the precise determination of the optimal point (minimizer) coordinates and of the minimum value of the index, a differentiable convex function, which is related to the harmonic mean concept. Furthermore, we address and solve the inversion problem and show the tight connection between both approaches. Last, we give some insights and final remarks on this subject.

olten salt reactors (MSRs) utilize salts as coolant or as the fuel and coolant together with fissile isotopes dissolved in the salt. It is necessary to therefore understand the behavior of the salts to effectively design, operate, and regulate such reactors, and thus there is a need for thermodynamic models for the salt systems. Molten salts, however, are difficult to represent as they exhibit short range order that is dependent on both composition and temperature. A widely useful approach is the modified quasichemical model in the quadruplet approximation that provides for consideration of first and second nearest neighbor coordination and interactions. Its use in the CALPHAD ap-proach to system modeling requires fitting parameters using standard thermodynamic data such as phase equilibria, heat capacity, and others. Shortcoming of the model is its inability to directly vary coordination numbers with composition or temperature. Another issue is the difficulty in fitting model parameters using regression methods without already having very good initial values. The proposed paper will discuss these issues and note some practical methods for the effective genera-tion of useful models.

Lung cancer remains the main cause of global cancer-related deaths. Currently low-dose computed tomography (LD-CT) shows a 20% reduction of mortality. However, its clinical suitability is hindered by cost, radiation, and some false positives. Thus, the discovery non-invasive and less-expensive biomarker is urgent needed. In this scenario, proteins released in biological fluids could be considered interesting biomarkers for their role in cancer development. We conducted a pioneering case-control pilot study aimed at assessing the usefulness of Raf Kinase Inhibitory Protein (RKIP) and its phosphorylated form (pRKIP) as potential early-stage lung cancer biomarkers. Urine and Blood samples of two consecutive and independent cohorts of lung cancer patients and healthy controls were screened by means of a novel experimental ELISA assay designed to evaluate both forms of the biomarker. Although urinary levels of RKIP were not statistically different between the lung cancer group and high-risk healthy group, serum ones instead increased significantly in early stage LC patients and permitted to discriminate LC patients from both low-risk (HS) and high-risk healthy subjects (HR-HS) with an overall 93% accuracy (AUC 0.93) when LC was compared to HS and 74% (AUC 0.73) when it was compared to high-risk group. Of note, the analysis of RKIP/pRKIP ratio also showed a high accuracy (90% - AUC 0.95) in discriminating LC patients from HS and more importantly, it allowed to identify LC patients compared to HR-HS, with a higher accuracy (79% - AUC 0.79) than RKIP alone. We hypothesize that serum RKIP levels may be correlated to the activation of the immune systems against the tumor during the first phases of its development. Our study identified a preliminary, non-invasive, RKIP and pRKIP profile able to discriminate with high specificity and sensitivity the early-stage lung cancer patients from high-risk Healthy Subjects. These results, although preliminary, suggest the utility of measuring RKIP/pRKIP as potential new screening test for lung cancer and provide the basis for future validation studies.

The decarbonization of the built environment, both in new construction and renovation, is crucial to mitigate its relevant impact on climate change and achieve the Paris agreement goals. This study presents a systematic LCA-based methodology to assess the whole life carbon emissions of buildings, applied to a proposal for the regeneration of one of Milan’s disused railway yards. As an entry for the 2020 Reinventing Cities competition, Scalo Lambrate is a project for a mainly residential neighborhood with a public park. Strategies to reduce carbon emissions deriving both from the operational energy and construction and maintenance were evaluated and their effects compared to a reference scenario over a time horizon of 100 years. The results show that, while the opportunities to reduce carbon emissions during the use phase are somehow limited due to the already stringent performance requirements for new builds, the use of fast-growing biogenic materials for construction materials, even if mixed with more traditional ones, can provide a significant reduction of the global warming potential over the whole life cycle, with a reduction of 70% over the baseline. The remaining emissions can be offset with afforestation initiatives that, however, must be assessed against land use issues.

Smart living, a concept that has gained increasing attention in recent years, revolves around integrating advanced technologies in homes and cities to enhance the quality of life for citizens. Sensing and human action recognition are crucial aspects of this concept. Smart living applications span various domains, such as energy consumption, healthcare, transportation, and education, which greatly benefit from effective human action recognition. This field, originating from computer vision, seeks to recognize human actions and activities using not only visual data but also many other sensor modalities. This paper comprehensively reviews the literature on human action recognition in smart living environments, synthesizing the main contributions, challenges, and future research directions. This review selects five key domains: Sensing Technology, Multimodality, Real-time Processing, Interoperability, and Resource-Constrained Processing, as they encompass the critical aspects required for successfully deploying human action recognition in smart living. These domains highlight the essential role that sensing and human action recognition play in successfully developing and implementing smart living solutions. This paper serves as a valuable resource for researchers and practitioners seeking to explore further and advance the field of human action recognition in smart living.

An airfoil is the geometric shape of a cross-section of a wing. When it is exposed to the flow of a fluid over its surface, it generates both lift and drag forces through a pressure distribution. Designing an efficient airfoil for aerodynamic applications is a complex challenge in the field of aerodynamic engineering, with the aim of achieving an optimal lift-to-drag ratio. The success of airfoil design hinges on the effective reduction of drag force under specific conditions, while simultaneously attaining the desired lift without encountering significant flow separation, such as boundary layer shedding. Furthermore, the design must adhere to lifting force limitations and meet structural requirements. In the field of airfoil design and optimization, literature review articles provide a valuable resource by offering an overview of the latest advancements in specific areas. These areas encompass a wide range of topics including the design and testing of adaptive geometry wings, such as morphing wing technology as well as the application of shape optimization techniques to enhance airfoil performance. Our goal is to provide researchers with an in-depth review of relevant articles published to date, examining the applied approaches utilized to tackle the complex problem of airfoil design and explore the methodology employed to address it, from a broad perspective on the topic.

We investigate properties of strongly useful topologies, i.e. topologies with respect to which every weakly continuous preorder admits a continuous order-preserving function. In particular, we prove that a topology is strongly useful provided that the topology generated by every family of separable systems is countable. Focusing on normal Hausdorff topologies, whose consideration is fully justified and not restrictive at all, we show that strongly useful topologies are hereditarily separable on closed sets, and we identify a simple condition under which the Lindelöf property holds.

Users of meteorological forecasts are often faced with the question of whether to make a decision now based on the current forecast or whether to wait for the next and hopefully more accurate forecast before making the decision. One would imagine that the answer to this question should depend on the extent to which there is a benefit in making the decision now rather than later, combined with an understanding of how the skill of the forecast improves, and information about the possible size and nature of forecast changes. We extend the well-known cost-loss model for forecast-based decision making to capture an idealized version of this situation. We find that within this extended cost-loss model, the question of whether to decide now or wait depends on two specific aspects of the forecast, both of which involve probabilities of probabilities. For the special case of weather and climate forecasts in the form of normal distributions we derive a simulation algorithm, and equivalent analytical expressions, for calculating these two probabilities. We apply the algorithm to forecasts of temperature and find that the algorithm leads to better decisions relative to three simpler alternative decision-making schemes. Similar problems have been studied in many other fields, and we explore some of the connections.

A striking aspect of COVID-19 is the difference in the outcome of the infection between different countries, and different ethnic groups within one country. We surveyed the literature on SARS-CoV-2 complemented with comparative publications on SARS-CoV and other coronaviruses to capture the current understanding of virus – host interactions including virus subtypes, transmission, zoonotic aspects, and potential host determinants.

The emergence of antimicrobial resistance have represented a serious threats for public health and infections due to multidrug-resistant (MDR) microorganisms represent one of the most important causes of death worldwide. The renew of old antimicrobials, such as colistin, have been proposed as valuable therapeutic alternative to the emergence of the MDR microorganisms. Although colistin is well known to presents several adverse toxic effect, its usage in clinical practice have been reconsidered due to the broad spectrum of activity to gram-negative (GN) bacteria and to the important role of “last resort” agent against MDR-GN. Despite the revolutionary prospective of treatment of this old antimicrobial molecule, many questions remain open regarding the emergence of novel phenotypic traits of resistance and the optimal usage of the colistin in clinical practice. In the last years, several forward steps have been done in the understanding of resistance determinants, clinical usage and pharmacological dosage of this molecule, however, different points regarding the role of colistin in clinical practice and the optimal pharmacokinetic/pharmacodynamic targets are not well defined yet. In this review, we summarize the mode of action, the emerging resistance determinants and its optimal administration in the treatment of difficult-to-treat infections due to MDR Gram-negative bacteria.

Dendritic cell (DC) cancer vaccines are a promising therapeutic approach, leveraging the immune system to fight tumors. These vaccines utilize DCs' ability to present tumor-associated antigens to T cells, triggering a robust immune response. DC vaccine development has progressed through three generations. The first generation involved priming DCs with tumor-associated antigens or messenger RNA outside the body, showing limited clinical success. The second generation improved efficacy by using cytokine mixtures and specialized DC subsets to enhance immunogenicity. The third generation uses blood-derived DCs to elicit a stronger immune response. Clinical trials indicate that cancer vaccines have lower toxicity than traditional cytotoxic treatments. However, achieving significant clinical responses with DC immunotherapy remains challenging. Combining DC vaccines with immune checkpoint inhibitors (ICIs) such as anti-cytotoxic T-lymphocyte Antigen 4 and anti-programmed Death-1 antibodies has shown promise by enhancing T cell responses and improving clinical outcomes. These combinations can transform non-inflamed tumors into inflamed ones, boosting ICIs' efficacy. Current research is exploring new checkpoint targets like LAG-3, TIM-3, and TIGIT, considering their potential with DC vaccines. Additionally, engineering T cells with chimeric antigen receptors or T cell receptors could further augment the anti-tumor response. This comprehensive strategy aims to enhance cancer immunotherapy, focusing on increased efficacy and improved patient survival rates.

The geographic variability of the dorsal pattern (DP) of the Italian wall lizard, Podarcis siculus, across its native range was studied with the aim to understand whether the distributions of this phenotypic trait were more shaped by allopatric differentiation rather than adaptive processes. A total of 1298 georeferenced observations scattered across the Italian peninsula and the main islands (Sicily, Corsica and Sardinia) were obtained from citizen science databases and five DPs were characterized by different shapes of the dark pattern (“reticulated”, “campestris”, “reticulated/campestris” and “striped”) or by absence of it (“concolor”). Frequencies of different DP phenotypes differ between the two main mtDNA lineages settled in central-northern and in southern Italy respectively. This pattern may be indicative of a role of long-term allopatric historical processes in determining the observed pattern. The analysis also identified a putative wide area of secondary contact, in central southern Italy, characterized by high diversity of the DP. Generalized Linear Models (GLMs), used to estimate a possible association between bioclimatic variables and the observed phenotypic variation, showed that each of the five DPs is correlated to different environmental factors and show different distribution of areas with high probability of occurrence. However, for all but one of the DPs, the area with the greatest probability does not correspond exactly to the real distribution of the DP. Conversely, the “concolor” phenotype does not seem related to any particular mtDNA lineage and it shows a preference for areas with high temperature and low rainfall. This is in agreement with the expectation of low amount of melanin of the dorsal pattern that, in the study areas, is characterized by a light uniform coloration which could confer a better thermoregulation ability in high temperatures environments avoiding overheating.

Smart Living, an increasingly prominent concept, entails incorporating sophisticated technologies in homes and urban environments to elevate the quality of life for citizens. A critical success factor for Smart Living services and applications, from energy management to healthcare and transportation, is the efficacy of human action recognition (HAR). HAR, rooted in computer vision, seeks to identify human actions and activities using visual data and various sensor modalities. This paper extensively reviews the literature on HAR in Smart Living services and applications, amalgamating key contributions and challenges while providing insights into future research directions. The review delves into the essential aspects of Smart Living, the state of the art in HAR, and the potential societal implications of this technology. Moreover, the paper meticulously examines the primary application sectors in Smart Living that stand to gain from HAR, such as smart homes, smart healthcare, and smart cities. By underscoring the significance of the four dimensions of Context Awareness, Data Availability, Personalization, and Privacy in HAR, this paper serves as a valuable resource for researchers and practitioners striving to advance Smart Living services and applications.

This review covers the last 25 years literature on analogs of suberoylanilide hydroxamic acid (SAHA, known also as Vorinostat) acting as HDAC inhibitor. In particular, the topic has been focused on the synthesis and biological activity of compounds where the phenyl group (the surface recognition moiety, CAP) of SAHA has been replaced by an azaheterocycle through a direct bond with amide nitrogen atom, and the methylene chain in the linker region is of variable length. Most of the compounds reported displayed good to excellent inhibitory activity against HDACs and in many cases showed anti-proliferative activity against human cancer cell lines.

This article analyzes the assessment of the four development levels of the Digital Teaching Competence (DTC) to recognize the needs and formulation of challenges in training and educational innovation required in the pedagogical practices of university professors under the current context of the Covid-19 pandemic. The study used an empirical-analytical methodology with a non-experimental, transactional, descriptive design. The sample design was probabilistic, estimated with 95% confidence and 5% error among 252 teachers from various faculties of the University of La Guajira. The selected instrument corresponded to the rubric's application to evaluate the university professor's digital teaching competence in Latin America. Among the study's significant results, we highlight that the rubric presented a high Cronbach's alpha reliability (α: 0.947). In the general assessment of DTC development, it was estimated that 78.2% of teachers are in the first two levels of DTC development assessment (Beginning and Middle). The evaluation rubric allows identifying challenges and opportunities that teacher training must address to advance the professional development of professors.

Achieving universal access to water and sanitation services in developing countries requires a coherent legal, political, and institutional environment, along with a clear financial strategy. Regionalizing utilities may be crucial for addressing disparities, economic inequalities, and governance challenges. Regionalization offers economies of scale, resource efficiency, knowledge sharing, and collaboration. The cornerstone will be ensuring the financial-economic viability of regional utilities, considering their social impacts in terms of affordability. The State of Santa Catarina case study is assessed. In the case of Santa Catarina, only four regional utilities currently generate sufficient revenue, without factoring in necessary investments, indicating the need to review design parameters to improve operational efficiency and increase revenues. Additional financial support may be required to ensure universal access. Tariff adjustments must strike a balance between cost-effectiveness and affordability for families.

Laser marking on polymer composite surfaces can be difficult to contrast and cause readability problems for electronic decoding equipment on production lines due to poor interaction between the laser and the fibres used to reinforce these materials. This problem can be solved with the right choice of marking parameters, resulting in savings for companies by avoiding production problems such as rejection, scrap and customer complaints. The present work uses the PBT/glass fibre composite used in the manufacture of instrument panels for motorcycles. The tests were carried out with different laser marking parameters using a Nd: YAG laser. Subsequently, the laser-marked DMC codes were analysed using a Verifier to evaluate the quality according to the ISO/IEC 29158:2020 standard. A detailed analysis of these surfaces was also carried out to observe some physical and chemical changes using SEM microscopy and EDS spectroscopy. The optical analysis showed that the lower the radiation power and pulse frequency and the higher the marking speed, the weaker the laser marking and therefore the poorer the DMC code quality, which was confirmed by the SEM. EDS spectroscopy showed that the laser marking process did not affect the chemical changes on the sample surface.

Syncope and presyncope occurring during work can affect safety and impair occupational performance. Few data are available regarding the prevalence of these events among workers. The possible role of sleep quality, mental stress and metabolic disorders in promoting syncope, presyncope and falls in workers is unknown. In the present study, 741 workers (male 35.4%; mean age 47±11 years), employed in different companies, underwent clinical evaluation and blood tests and completed questionnaires to assess sleep quality, occupational distress and mental disorders. The occurrence of syncope, presyncope and unexplained falls during their working life was assessed by an ad hoc interview. The prevalence of syncope, presyncope and falls of unknown origin was 13.9%, 27.0%, and 10.3%, respectively. The occurrence of syncope was associated with an increased risk of occupational distress (adjusted Odds Ratio aOR: 1.62, Confidence Intervals at 95%: 1.05-2.52), low sleep quality (aOR: 1.79 CI 95%: 1.16-2.77) and poor mental health (aOR: 2.43 CI 95%: 1.52-3.87). Presyncope was strongly associated with occupational distress (aOR: 1.77 CI 95%: 1.25-2.49), low sleep quality (aOR: 2.95 CI 95%: 2.08-4.18) and poor mental health (aOR: 2.61 CI 95%: 1.78-3.84), while no significant relationship was found between syncope or presyncope and metabolic syndrome. These results suggest that occupational health promotion interventions aimed at improving sleep quality, reducing stressors and increasing worker resilience might reduce syncope and presyncope events in the working population.

Many cancers utilize L-glutamine as a major energy source. This “L-glutamine addiction” involves a well-characterized pathway whereby L-glutamine is hydrolyzed by a glutaminase (GLS) to L-glutamate, which is then converted to α-ketoglutarate, the carbons of which enter the tricarboxylic acid (TCA) cycle. However, mammalian tissues/cancers possess a rarely mentioned alternative pathway (the glutaminase II pathway): L-Glutamine is transaminated to α-ketoglutaramate (KGM), followed by ω-amidase (ωA)-catalyzed hydrolysis of KGM to α-ketoglutarate. Uncertainty may prevail over the name glutaminase II which may be confused with the enzyme named glutaminase 2 (GLS2). Thus, we recently suggested a new name for the glutaminase II pathway, namely the glutamine transaminase-ω-amidase (GTωA) pathway. Herein, we 1) evaluate three recent articles that mention L-glutamine addiction, but not the GTωA pathway, 2) summarize the metabolic importance of the GTωA pathway, including its role in closing the methionine salvage pathway, and 3) as a source of anaplerotic α-ketoglutarate. An advantage of the GTωA pathway [i.e., L-glutamine + α-keto acid + H2O α-ketoglutarate + L-amino acid + +NH4] is that it is irreversible and that there is no net change in redox status, permitting α-ketoglutarate production during hypoxia. Finally, we discuss possible clinical benefits of GTωA pathway inhibitors.

Background: The concept of Quality of Work Life (QWL) has been built multidimensionally through social reproduction; it is impacted by the perceptions of each individual and by the relationship between workers and the work environment. Objective: to analyze the Work Process and QWL of assisting nurses in public health. Methods: Research in a critical paradigm, descriptive, exploratory with a qualitative approach. The population corresponds to Nurses who work in care work. Semi-structured guiding questions were applied and were analyzed with content analysis. Results: seven participants declared female; all Chilean; seven are young adults; six singles; only one has children, and one has a person dependent on her care; six are heads of household, and five receive help with housework. All have a nursing degree, five have a diploma, but none have a postgraduate. Work Process has three subcategories: work object, instrument, organization, and work conditions; the QWL category has six subcategories: definition and perception of QWL, QWL potentiating factors, QWL exhausting factors, QWL improvement strategies, the emotional burden associated with QWL, and Health problems. Conclusions: In this way, the lifestyle built by the assistance in the health area has repercussions on the quality of life and health in general.

Molecular mechanisms for N2 fixation (solar NH3) and CO2 conversion to C2+ products in enzymatic conversion (Nitrogenase), electrocatalysis, metal-complexes and plasma-catalysis are analysed and compared. It is evidenced that differently from what present in thermal and plasma-catalysis, the electrocatalysis path requires not only the direct coordination and hydrogenation of undissociated N2 molecule, but to realize a series of features present in the Nitrogenase mechanism. There is the need of i) a multi-electron and -proton simultaneous transfer, not as sequential steps, ii) forming bridging metal hydride species, iii) generate intermediates stabilized by bridging multiple metal atoms, iv) have the capability of the same sites to be effective both in N2 fixation and in COx reduction to C2+ products. Only iron oxide/hydroxide stabilized at defective sites of nanocarbons was found to have these features. This comparison of the molecular mechanisms in solar NH3 production and relations with CO2 reduction is proposed to be a source of inspiration to develop the next generation electrocatalysts to address the challenging transition to a future sustainable energy and chemistry beyond fossil fuels.

This research explored the influence of spatiotemporal variations in phreatic levels and salinity on the patterns and interactions of soil mesofauna communities in a tropical urban coastal wetland. It delineated significant variations in phreatic levels and salinity, with distinct regimes characterizing different habitats and hydroperiods. A total of 120 mesofauna morphotypes across 42 taxa were identified, revealing habitat differences and similarities, and the ecosystem biodiversity. Moderate correlations were established between phreatic levels, salinity, and mesofauna richness and abundance, with habitat type and phreatic level emerging as significant predictors in the regression model. Our findings indicate that shallow phreatic levels in conjunction with oligohaline salinity conditions foster a more favorable abiotic environment, thereby promoting increased biodiversity. The study underscores the dynamic and adaptive nature of mesofauna communities in response to changing environmental conditions, offering valuable insights for effective costal urban wetland management, particularly in the context of multiple stressors such as global and regional climate change, sea level rise, and human activities. The bio-sensor capacity of soil mesofauna emerges as a vital tool for monitoring and facilitating adaptive ecosystem management, thereby ensuring their long-term health and sustainability.

This study aimed to assess the physical characteristics of elite international soccer referees, compare them with other referee populations in the literature, and establish reference tolerance ellipses for the bioelectrical impedance vector analysis (BIVA) point graph. Forty-one elite international soccer referees (age 38.8 ± 3.6 years) participated in the study. the participants underwent body composition assessments, including dual-energy X-ray absorptiometry, BIVA, and somatotype. The Somatotype Attitudinal Distance (SAD), the two-sample Hotelling’s T2 test, and the Mahalanobis test were used to determine somatotype and bioelectrical vector differences with the literature. The average somatotype of the referees was a balanced mesomorph (2.8, 6.5, 2.8). Elite international referees significantly differed from other samples in the literature (SAD = 2.1, 2.6, 2.9 with respect to Zimbabwean, Brazilian, and South African referees, respectively). The bioelectrical vector was significantly different from the general population (T2  76.6; F = 38.8; D = 1.44; P < 0.001) and athletes (T2  25.3; F = 12.6; D = 0.8; P < 0.001). Somatotype values and tolerance ellipses from this study may be useful as a reference for developing training programs and improving the selection process of referees in soccer.

As is known, the construction industry has one of the highest occupational accidents incidence rates among all economic sectors. Currently, Building Information Modeling (BIM) appears as a tool that addresses occupational safety issues throughout the construction life cycle projects, avoiding hazards and risks and, consequently, increasing safety. This work investigates BIM methodology and related technologies application for building safety planning in construction and demonstrates the potential of this technology for the integrated implementation of safety measures during the design phase and the construction site management. The first step consisted of a literature review on the application of BIM in safety in the design and planning phases. Following, to show the potentialities of construction simulation, a case study based on BIM 4D to prevent falls from height was developed. With BIM 4D, it is possible to follow the construction process over time, giving the construction safety technicians’, designers, supervisors and managers the capability to analyse, in each phase, the potential risks and which safety measures should be implemented. BIM can effectively integrate safety measures from the design phase to the construction and use phase and do integrated safety planning within construction planning, leading to reliable safety management throughout the construction process.

: E-commerce sales surge represents a huge challenge for urban freight transport. Parcel lockers constitute a valid solution for addressing the challenges home deliveries imply. In fact, eliminating courier-consumer contact (also relevant for health-related issues, as made evident by COVID19 pandemic) and delivering in few predefined places might help coping with missed deliveries substantially. Furthermore, this option enables consolidated shipping and reducing delivery trip costs. This paper analyses and compares consumers’ preferences for alternative collection strategies. It investigates home delivery vs parcel locker use and forecasts their future market shares. This is performed based on both customers’ socio-economic variables and attributes characterising these alternative logistic fulfilment strategies. The case study considered rests upon a stated preference survey deployed in the city of Rome. The investigation specifically targets young people (i.e., population under 30 years) since they represent early adopters. Discrete choice models allow both quantifying the monetary value of parcel lockers attributes (i.e., willingness to pay measures) and estimating the potential demand for this innovative delivery scheme. Results show that distance and accessibility are the main choice determinants. Furthermore, there is an overall high propensity to adopt parcel lockers. This research can support policymakers when implementing such solutions.

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%.

GNSS receivers are nowadays commonly used in monitoring applications, e.g., in estimating crustal and infrastructure deformations. This is basically due to the recent improvements in GNSS instruments and methodologies that allow high precision positioning, 24 h availability and semiautomatic data processing. In this paper, GNSS estimated deformations on a dam structure have been analyzed and compared with pendulum data. This study has been carried out for the Eleonora D’Arborea (Cantoniera) dam, which is in the Sardinia Island. Time series of pendulum and GNSS over a time span of 2.5 years have been aligned so to be comparable. Analytical models fitting these time series have been estimated and compared. Those models were able to properly fit pendulum data and GNSS data, with standard deviation of residuals smaller than one millimeter. This encouraging results led to the conclusion that GNSS technique can be profitably applied to dam monitoring allowing a denser description, both in space and time, of the dam displacements than the one based on pendulum observations.

The present work presents and discusses experimental performance and gaseous emission results of the use of ternary mixtures of diesel oil, biodiesel and ethanol in an ASTM-CFR engine. Eight different mixtures with biodiesel content equal to 8%, 20% and 60%, and ethanol content equal to 0%, 5% and 8% were analyzed. After the selection and preparation of the mixtures, the determination of the cetane number for each one was performed following the ASTM D613 standard. After cetane number evaluation, two off-standard operating conditions were selected, and performance and emissions were obtained. A thermodynamic analysis and a Bayesian inverse approach were applied and physical quantities of interest, such as indicated work, maximum pressure, rate of heat released by the fuel, ignition delay, and combustion duration, were obtained. In-cylinder pressure data were obtained through an AVL Indicating system installed in the ASTM-CFR engine. The heating values of each mixture were determined using a bomb calorimeter and thermal and indicated efficiencies were evaluated based on the total heat released by the fuel and the indicated work. Finally, a gaseous emissions analysis was conducted to evaluate the influence of the blend compositions, as well as of their cetane numbers, on the formation of NOx, CO and CO₂.

The cosmetic industry has a history of constant modernization, with products that are increasingly sustainable and well tolerated by the customers. In the last years, the growing understanding and knowledge of the potential of marine species, as well as the application of “blue biotechnology” have been motivating new innovative solutions in this area. Marine organisms are important sources of compounds that may be applicable in cosmetics, with biological activities that include depigmentant, anti-aging or anti-bacterial properties, specifically against acne, but also as formulation promoters and facilitators. Several methods can be used to extract these molecules, but these are not free of challenges and implications – possible biological and chemical contamination, and problems with batch reproducibility, which can be associated to the intraspecific variability of the different specimens, should be considered. Alongside these, the legislative and normative framework is increasingly developed and there is a growing concern with this situation. The application of sustainability fundamentals in the production of cosmetics must respect a life cycle approach, critically analyzing each stage. In this sense, “blue biotechnology”, in constant evolution, together with the use of invasive species or marine waste products to obtain new active ingredients, emerge as innovative and sustainable solutions for the future’s cosmetics industry. This review explores various biological properties of marine-derived molecules and discusses the challenges and implications associated with extracting these compounds. It also examines recent advancements in 'blue biotechnology' and their relevance to the sustainable development of innovative cosmetics.

The development of a remote sensing system is proposed in the present study for monitoring of the electrical resistance of concrete in real time. The sensor is embedded in the concrete bulk, and the data are sent via a gateway to a computer for the data analysis. The sensibility of the sensors to the effect of the presence of a crystalline admixture has been also assessed in the study. Different cycles of drying and water penetration have been considered to assess the sensor performance in different water content conditions. Sensors have shown to capable of detecting changes in electrical resistance when humidity changes. The sensitive of the sensors to the action of waterproofing admixtures in the mortar has been also confirmed. The contribution of the temperature plays a critical role on the sensor response, and its simultaneous monitoring is recommended.

Background: Visceral leishmaniasis affects approximately 12 million people worldwide. Current existing drugs cause several side effects and resistance, the identification of new therapeutic targets for the development of new drugs is necessary. The vesicular trafficking in the parasite flagellar pocket is essential for parasite survival and proliferation, but little is known about the proteins involved in the endocytic/secretory pathways. In this work, we are describing the characterization of a transporter cargo protein SFT-2/Got-1 like in Leishmania infantum. Material and Methods: Using bioinformatics tools, the putative Got-1 protein A4HSK3 was characterized structurally and phylogenetically. Molecular biology was used to clone and express the protein and confocal fluorescence to determine its subcellular localization. Results: The Got-1 like protein presents four alpha helix TM conserved domains (aa38-aa147) characteristics of the Got-1/SFT-2 family proteins and an important Pen-2 conserved motif LGDYXXF located in the extracellular loop. Confocal microscopy suggests that Got-1/SFT-2 like is localized in the flagellar pocket, and is partially co-localized with the L. infantum presenilin-like protein. Phylogenetically, the Leishmania sp Got-1 like is contained in a subgroup of proteins clearly detached from the other Trypanosomatidae, such as T. cruzi and T. brucei. Conclusions: Our data show the presence of an important transported proteins, and its colocalization with the presenilin aspartyl protease in the flagellar pocket of the L. infantum open new perspectives to identify novel targets, which can be an alternative therapeutic strategy against leishmaniasis.

Epidemiological studies have shown that consuming olive oil rich in phenolic bioactive compounds is associated with a lower risk of neurodegenerative diseases and better cognitive performance in aged populations. Since oxidative stress is a common hallmark of age-related cognitive decline, incorporating exogenous antioxidants could have beneficial effects on brain aging. In this review, we firstly summarize and critically discuss the current preclinical evidence and the potential neuroprotective mechanisms. Existing studies indicates that olive oil phenolic compounds can modulate and counteract oxidative stress and neuroinflammation, two relevant pathways linked to the onset and progression of neurodegenerative processes. Secondly, we summarize the current clinical evidence. In contrast to preclinical studies, there is no direct evidence in humans of the bioactivity of olive oil phenolic compounds. Instead, we have summarized current findings regarding nutritional interventions supplemented with olive oil on cognition. A growing body of research indicates that high consumption of olive oil phenolic compounds is associated with better preservation of cognitive performance, conferring an additional benefit, independent of the dietary pattern. In conclusion, the consumption olive oil rich in phenolic bioactive compounds has potential neuroprotective effects. Further research is needed to understand the underlying mechanisms and potential clinical applications.

Laser-Powder Directed Energy Deposition (DED-LB/Powder) is an additive manufacturing process that is gaining popularity in the manufacturing industry due to its numerous advantages, particularly in repairing operations. However, its application is often limited to case studies due to some critical issues that need to be addressed, such as the degree of internal porosity. This paper investigates the effect of the most relevant process parameters of the DED-LB/Powder process on the level and distribution of porosity. Results indicate that, among the process parameters examined, porosity is less affected by travel speed and more influenced by powder mass flow rate and laser power. Additionally, a three-dimensional finite element transient model was introduced, which was able to predict the development and location of lack-of-fusion pores along the building direction.

Background: In a Beveridgean decentralized healthcare system, like the Italian one, where regions are responsible for their own health planning and financing, the analysis of patients’ migration appears very interesting as it has economic and social implications. The study aims to analyze both patients’ migration for hospital rehabilitation and if the beds endowment is a driver for these flows; Methods: from 2011 to 2019, admissions data were collected from the Hospital Dis-charge Cards database of the Italian Ministry of Health, population data from Italian National Institute of Statistics and data of beds endowment from the Italian Ministry of Health website. To evaluate patients’ migration, we used Gandy’s Nomogram, while to assess if beds endowments are mobility drivers, we have created two matrices, one with attraction indexes (AI) and one with escape indexes (EI). The beds endowment, for each Italian region, were correlated with AI and EI. Spearman’s test was carried out through STATA software; Results: Gandy’s Nomogram showed that only some northern regions had good hospital planning for rehabilitation. A statistically significant correlation between beds endowment and AI was found for four regions, while with EI for eight regions. Conclusions: Only some northern regions appear able to satisfy the care needs of their residents, with an attraction minus escapes positive epidemiological balance. The beds endowment seems to be a driver of Patients’ migration, mainly for escapes. Certainly, the search for mobility drivers needs further investigation given the events in Molise and Basilicata.

Laser Powder Directed Energy Deposition (LP-DED) is an Additive Manufacturing process in which a laser beam is used to generate a melt pool onto a substrate. The additional material, in form of powder material, is fed into the generated melt pool and a raised track is obtained. The LP-DED process is very powerful for different applications such as the repair operations and the production of functionally graded material, however the application is still limited and one of the main reasons is related to the lack of knowledge in the physics of the process mechanisms. The process is influenced by a huge number of parameters and three main mechanisms can be identi-fied. These mechanisms are the powder flow, the generation of the molten pool and the solidifica-tion process and for each of these mechanisms the process parameters have a different relevance. In this paper, a review of the main mechanisms and the relationship between the process parame-ters and the outcome of each step of the process is presented.

The following article analyzes the determinants of e-government in 28 European countries between 2016 and 2021. The DESI-Digital Economy and Society Index database was used. The econometric analysis involved the use of the Panel Data with Fixed Effects and Panel Data with Variable Effects methods. The results show that the value of “e-Government” is negatively associated with “Fast BB (NGA) coverage”, “Female ICT specialists”, “e-Invoices”, “Big data” and positively associated with “Open Data”, “e-Government Users”, “ICT for environmental sustainability”, “Artificial intelligence”, “Cloud”, “SMEs with at least a basic level of digital intensity”, “ICT Specialists”, “At least 1 Gbps take-up”, “At least 100 Mbps fixed BB take-up”, “Fixed Very High Capacity Network (VHCN) coverage”. A cluster analysis was carried out below using the unsupervised k-Means algorithm optimized with the Silhouette coefficient with the identification of 4 clusters. Finally, a comparison was made between eight different machine learning algorithms using "augmented data". The most efficient algorithm in predicting the value of e-government both in the historical series and with augmented data is the ANN-Artificial Neural Network.

This article analyzes the determinants of the "Broadband Price Index" in Europe. The data used refer to 28 European countries between 2016 and 2021. The database used is the Digital, Economy and Society Index-DESI of the European Commission. The data were analyzed using the following econometric techniques, namely Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS and Dynamic Panel. The value of the "Broadband Price Index" is positively associated with the DESI Index, and "Connectivity" while it is negatively associated with "Fixed Broadband Take Up", "Fixed Broadband Coverage", "Mobile Broadband", "e-Government", "Advanced Skills and Development", "Integration of Digital Technology", "At Least Basic Digital Skills ", "Above Basic Digital Skills "," At Least Basic Software Skills ". A cluster analysis was carried out below using the k-Means algorithm optimized with the Silhouette coefficient. The analysis revealed the existence of three clusters. Finally, an analysis of the machine learning algorithms was carried out to predict the future value of the "Broadband Price Index". The result shows that the most useful algorithm for prediction is the Artificial Neural Network-ANN with an estimated value equal to an amount of 9.21%.

Quantum cryptography is the field of cryptography that explores the quantum properties of matter. Its aim is to develop primitives beyond the reach of classical cryptography or to improve on existing classical implementations. Although much of the work in this field has been dedicated to quantum key distribution (QKD), some important steps were made towards the study and development of quantum oblivious transfer (QOT). It is possible to draw a comparison between the application structure of both QKD and QOT primitives. Just as QKD protocols allow quantum-safe communication, QOT protocols allow quantum-safe computation. However, the conditions under which QOT is actually quantum-safe have been subject to a great amount of scrutiny and study. In this review article, we survey the work developed around the concept of oblivious transfer in the area of theoretical quantum cryptography, with an emphasis on some proposed protocols and their security requirements. We review the impossibility results that daunt this primitive and discuss several quantum security models under which it is possible to prove QOT security.

The hazard and the carcinogenic risks due to the exposure to some potentially toxic elements by the Santiago Island (Cape Verde) population where calculated, considering soil ingestion, inhalation and dermal contact as exposure pathways. The topsoil of Santiago Island is enriched in Co, Cr, Cu, Ni, V, Zn, Mn and Cd to upper crust values. Hazard indices (HI) were calculated for these metals and As exposures, of Santiago Island population and the calculations were performed for children and adults. For children HI are higher than 1 for Co, Cr and Mn. So there is indication of potential non-carcinogenic risk for children, due to the high Co (HI=2.995), Cr (HI=1.329) and Mn (HI=1.126), values in soils. For the other elements and for adults there is no potential non-carcinogenic risk. Cancer risk was calculated for As, Cd, Cr and Ni exposures, for adults and children and the results are always lower than the carcinogenic target risk of 1x10-6, for As, Cd, and Ni. However, cancer risk are higher than the carcinogenic target risk for Cr, for adults. Regarding As, for children the fraction due to Riskingestion represents 51.6%, while Riskinhalation represents 48.0% and Riskdermalcontact represents only 0.4% of total risk. For adults Riskinhalation represents 81.3%, Riskingestion represents 16.6% and Riskdermal contact represents 2.1%. These results reflect the higher daily ingestion dose for children and the higher inhalation rate and higher dermal contact surface for adults. For the other elements and for adults the cancer risk due to Cr, Ni and Cd inhalation is always higher than for children, reflecting the higher inhalation rate for adults.

Data collection and analysis are becoming more and more important in a variety of application domains as long as the novel technologies advance. At the same time, we are experiencing a growing need for human-machine interaction with expert systems pushing research through new knowledge representation models and interaction paradigms. In particular, in the last years eHealth - that indicates all the health-care practices supported by electronic elaboration and remote communications - calls for the availability of smart environment and big computational resources. The aim of this paper is to introduce the HOLMeS (Health On-Line Medical Suggestions) framework. The introduced system proposes to change the eHealth paradigm where a trained machine learning algorithm, deployed on a cluster-computing environment, provides medical suggestion via both chat-bot and web-app modules. The chat-bot, based on deep learning approaches, is able to overcome the limitation of biased interaction between users and software, exhibiting a human-like behavior. Results demonstrate the effectiveness of the machine learning algorithms showing 74.65% of Area Under ROC Curve (AUC) when first-level features are used to assess the occurrence of different prevention pathways. When disease-specific features are added, HOLMeS shows 86.78% of AUC achieving a more specific prevention pathway evaluation.

Background: Surveys conducted in different regions of the world showed that the prevalence rates of health risk behaviors (HRBs) in university students are sometimes higher than those found in non-university populations. This study aims to identify the prevalence rates and demographic and academic environment correlates associated with HRBs among Brazilian university students. Methods: In a cross-sectional epidemiological study, a random sample of 5,310 university students answered an online questionnaire with demographic (sex, age, skin color, marital status, and paid work) and academic setting information (housing type, size of campus, year and shift of study), as well as items clustered in four HRB domains: personal safety and violence, sexual behavior and contraception, addictive substance use, and eating habits, physical activity, and sleep. The data were analyzed statistically using bivariate analysis and hierarchical multiple regression. Results: The highest prevalence rates occurred in HRBs clustered in the domain of eating habits, physical activity, and sleep (> 60%), while HRBs for personal security and violence were less prevalent (

White-rot fungi (WRF) have specific enzymes to degrade lignocellulosic and phenolic compounds. Therefore, their direct application could be an alternative to biodegrade complex lignocellulosic biomass such as olive mill solid waste (OMSW). The aim of this study was to evaluate the capacity of A. discolor and S. hirsutum to grow in OMSW as the sole substrate under static conditions and evaluate the phenolic removal compounds and lignin degradation. The lignolytic enzyme activity was determined, as was the phenolic compound removal. At the same time, lignin degradation and structural changes were evaluated by confocal laser scanning microscopy (CLSM) and scanning electron microscope (SEM), respectively. Both strains were able to grow using OMSW as the sole substrate without adding other nutrients, oxygen and/or agitation. The higher ligninolytic enzyme activity was found at day 8, and the highest phenolic removal (more than 80% with both strains) was reached after 24 days of incubation. The CLSM analysis confirmed lignin degradation through the drop in lignin fluorescence from 3967 for untreated OMSW to 235 and 221 RFU after 24 days of treatment by A. discolor and S. hirsutum respectively. The results indicate that both WRF could be suitable candidates to design an in-situ pretreatment step of OMSW, as long as in future research the WRFs have the same performance in non-sterile conditions.

Mitochondrial dysfunction plays a pivotal role in numerous complex diseases. Understanding the molecular mechanisms by which the “powerhouse of the cell” turns into the “factory of death” is an exciting yet challenging task that can unveil new therapeutic targets. The mitochondrial matrix protein CyPD is a peptidylprolyl cis-trans isomerase involved in the regulation of the permeability transition pore (mPTP). The mPTP is a multi-conductance channel in the inner mitochondrial membrane whose dysregulated opening can ultimately lead to cell death and whose involvement in pathology has been extensively documented over the past few decades. Moreover, several mPTP-independent CyPD interactions have been identified, indicating that CyPD could be involved in the fine regulation of several biochemical pathways. To further enrich the picture, CyPD undergoes several post-translational modifications that regulate both its activity and interaction to its clients. Here, we will dissect what is currently known about CyPD and critically review the most recent literature about its involvement in neurodegenerative disorders, focusing on Alzheimer’s Disease and Parkinson’s Disease, supporting the notion that CyPD could serve as a promising therapeutic target for the treatment of such conditions. Notably, significant efforts have been made to develop CyPD-specific inhibitors, which hold promise for the treatment of such complex disorders.

Radiotherapy commonly utilizes CBCT for patient positioning and treatment monitoring. CBCT is deemed to be secure for patients, making it suitable for the delivery of fractional doses. However, limitations such as a narrow field of view, beam hardening, scattered radiation artifacts, and variability in pixel intensity hinder the direct use of raw CBCT for dose recalculation during treatment. To address this issue, reliable correction techniques are necessary to remove artifacts and remap pixel intensity into HU values. This study proposes a deep-learning framework for calibrating CBCT images acquired with narrow FOV systems and demonstrates its potential use in proton treatment planning updates. Cycle-consistent GAN processes raw CBCT to reduce scatter and remap HU. Monte Carlo simulation is used to generate CBCT scans, enabling the possibility to focus solely on the algorithm’s ability to reduce artifacts and cupping effects without considering intra-patient longitudinal variability and producing a fair comparison between planning CT and calibrated CBCT dosimetry. To showcase the viability of the approach using real-world data, experiments were also conducted using real CBCT. Tests were performed on a publicly available dataset of 40 patients who received ablative radiation therapy for pancreatic cancer. The simulated CBCT calibration led to a difference in proton dosimetry of less than 2%, compared to the planning CT. The potential toxicity effect on the organs at risk decreased from about 50% (uncalibrated) up the 2% (calibrated). The gamma pass rate at 3%/2mm produced an improvement of about 37% in replicating the prescribed dose before and after calibration (53.78% vs 90.26%). Real data also confirmed this with slightly inferior performances for the same criteria (65.36% vs 87.20%). These results may confirm that generative artificial intelligence brings the use of narrow FOV CBCT scans incrementally closer to clinical translation in proton therapy planning updates.

The Urban Heat Island (UHI) is one of the more serious consequences of urbanization resulting in impacts on thermal comfort levels, heat stress, and even mortality. For Municipal Beirut, implementation of “cool” surface materials and green spaces have been recommended to counterbalance the UHI. This paper builds on previous findings on the topic of non-constructible parcels within the district of Bachoura in Municipal Beirut and examines the possibility of implementing “cool” surface or paving materials and urban vegetation which can improve thermal conditions especially during the summer period and with the viewto project the positive findings of this case study to the entire Municipal Beirut area. A numerical analysis using ENVI-met 4.0 investigates the thermal performance of these non-constructibles further to implementation of high reflective surfaces and urban vegetation within a broad neighborhood scale in Bachoura. Results show reductions in ambient temperatures up to 1K on a summer day.. Within the framework of an integrated approach to planning, this form of urban acupuncture aims for substantial UHI reduction. Energy performance of buildings further to implementation of these mitigation measures is also recommended for future studies and to validate the findings in this paper.

Background: During anatomy (topographic) chair, we prepared an anatomic piece of an older female pelvis (unknown causa mortis). Here, we present an anatomic piece prepared by medical students that helped us to better understand hypertrophic bladder pathophysiology. Methods: A traditional corpse dissection guided by an assistant professor. Results: Corpse dissection enhanced our personal experience during the medical course. It also helped us to better visualize how big a hypertrophic urinary bladder can become as the etiologic cause is not taken care. Conclusions: Despite virtual and 3D anatomy lessons, we believe corpse dissection must remain as a teaching strategy that can help to build a new generation of surgeons as well as honor the History of Medicine.

The industry is increasingly relying on fish for toxicity assessment. However, current guidelines for toxicity assessment focus on teratogenicity and mortality. From an ecotoxicological point of view, however, these endpoints may not reflect the “full picture” of possible deleterious effects that can nonetheless result in decreased fitness and/or inability to adapt to a changing environment, affecting whole populations. Therefore, assessing sublethal effects add relevant data covering different aspects of toxicity at different levels of analysis. Impacts of toxicants on neurobehavioral function have the potential to affect many different life-history traits, and are easier to assess in the laboratory than in the wild. We propose that carefully-controlled laboratory experiments on different behavioral domains – including anxiety, aggression, and exploration – can increase our understanding of the ecotoxicological impacts of contaminants, since these domains are related to traits such as defense, sociality, and reproduction, directly impacting life-history traits. The effects of selected contaminants on these tests are reviewed, focusing on larval and adult zebrafish, showing that these behavioral domains are highly sensitive to small concentrations of these substances. These strategies suggest a way forward on ecotoxicological research using fish.

Ammonia is an atmospheric pollutant, predominantly emitted from agriculture, leading acidification and eutrophication of soil and water and contributing to secondary PM2.5. The implementation of accurate emission inventories with high spatial and time resolution plays a fundamental role in the development of air modelling simulation and in the impact assessment of actions for air quality improvement. The development and release of new algorithms and the increase of data availability are supporting the implementation of machine learning approaches in environmental and air quality data analysis. In this paper we present a methodology developed by the application of the Random Forest algorithm to bottom-up local emission inventories of ammonia to validate annual time series of ammonia emissions and calculate high resolution temporal profiles. The model has been trained and tested by the hourly measurements of ammonia concentrations and atmospheric turbulence parameters starting from a constant emission scenario. The initial values of emissions are calculated based on a bottom-up emission inventory detailed at the municipal basis and considering a circular area of about 4 km radius centered on measurement sites. By comparing predicted and measured concentrations, the emissions are modified, the model's training and testing are repeated, and the model converges to a very high performance in predicting ammonia concentrations and establishing an hourly time changing emission profile. The site-specific emissions profiles, estimated by the proposed methodology, clearly show a nonlinear relation with measured concentrations and allow to identify the effect of atmospheric turbulence on pollutant accumulation. The estimated time series well confirm the available data of the emission inventories and the monthly emission profiles have been compared with estimated data from satellite.

The use of convolutional neural networks (CNNs) in image classification has become the standard method of approaching computer vision problems. Here we apply pre-trained networks to classify images of non-breaking, plunging and spilling breaking waves. The CNNs are used as basic feature extractors and a classifier is then trained on top of these networks. The dynamic nature of breaking waves is exploited by using image sequences to gain extra information and improve the classification results. We also see improved classification performance in using pre-computed image features such as the optical flow between image pairs. The inclusion of the dynamic information improves the classification between breaking wave classes. We also provide corrections to the methodology from the article from which the data originates to achieve a more accurate assessment of performance.

Climate change is an issue that is the order of the day, and among the many consequences it has on the environment one is its influence on the amount and frequency of rainfall on our planet, since our water supply depends on them. Therefore, in order to quantify these effects, a rainfall analysis has been carried out using data collected in Bilbao over the last 150 years. Thanks to this, it has been possible to observe that, although the total annual amount seems to suffer a slight decrease, hardly quantifiable with certainty, it is true that the intra-annual patterns are more concentrated at certain times of the year, with greater imbalances between one month and another than in previous years. However, taking into account the capacity of the reservoirs that supply the Greater Bilbao area, it can be concluded that this does not pose any problem for Bilbao's supply, at least at present.

Arbutus unedo L. is a small Ericaceae tree with a circum-Mediterranean distribution. It has a huge ecological impact on southern Europe forests and a great economic importance, as a source of phytochemicals with bioactive properties and for fruit production. On the foreseen climate change context, breeding towards drought tolerance is necessary in order to ameliorate plant performance. The aim of this work was therefore to study the reproduction mechanisms of strawberry tree, obtain new genetic combinations by hybridization and select genotypes more tolerant to drought stress. A morphological analysis of flowers and pollen was carried out, and controlled pollinations performed both in vitro and ex vitro. The very first approach on strawberry tree breeding by means of hybridization is also presented. Several physiological parameters were evaluated on 26 genotypes submitted to a water deficit regime. Plant behavior under drought greatly varied among genotypes, which showed a high phenotype plasticity. Three genotypes that were able to cope with water restriction without compromising net CO2 assimilation were identified as highly tolerant to drought stress. The results obtained elucidate the reproduction mechanisms of strawberry tree and open the way for a long-term breeding program based on the selection of drought tolerant plants.

Visual impairment and blindness are a growing public health problem, as they reduce the quality of life of millions of people. The management and treatment of these diseases represent a scientific and therapeutic challenge, since the different cellular and molecular actors involved in the pathophysiology are still being identified. The visual system components, particularly the retinal cells, are extremely sensitive to genetic or metabolic alterations, and immune cells activated by insults contribute to biological events that culminate with vision loss and irreversible blindness. Several ocular diseases are linked to retinal cell loss, and diseases such as retinitis pigmentosa, age-related macular degeneration, glaucoma and diabetic retinopathy are characterized by pathophysiological hallmarks that represent possibilities to study and develop novel treatments for retinal cells degeneration. Here, we present a compilation of revisited information on retinal degeneration, including pathophysiologic and molecular features, biochemical hallmarks and possible directions for novel treatments, aiming to assist as a guide for innovative research. The expansion of knowledge of the mechanistic bases of the pathobiology of eye diseases, including information on the complex interactions of genetic predisposition, chronic inflammation, and environmental and aging-related factors will allow the identification of new therapeutic strategies.

Bioactive lipids are involved in cellular signalling events with links to human disease. Many of these are involved in inflammation under normal and pathological conditions. Despite being attractive molecules from a pharmacological point of view, detection and quantification of lipids has been a major challenge. Here, we have optimised a liquid chromatography dynamic multiple reaction monitoring targeted mass spectrometry (LC-dMRM-MS) approach to profile eicosanoids and fatty acids in biological samples. In particular, by applying this analytic workflow to study a cellular model of Chronic Myeloid Leukaemia (CML), we found that intra- and extra-cellular 2-Arachidonoylglycerol (2-AG), intracellular Arachidonic Acid (AA), and extracellular Prostaglandin F_2α (PGF_2α), 5-Hydroxyeicosatetraenoic acid (5-HETE), Palmitic acid (PA, C16:0) and Stearic acid (SA, C18:0) were altered in response to immunomodulation by type I Interferon (IFN-I), a currently approved treatment for CML. Our observations indicate changes in eicosanoid and fatty acid metabolism with potential relevance in the context of cancer inflammation and CML.

The major stress-inducible Hsp70 (HSPA1A) is overexpressed in the cytosol of many highly aggressive tumor cells including glioblastoma multiforme and presented on their plasma membrane. Depending on its intracellular or membrane localization, Hsp70 either promotes tumor growth or serves as a target for NK cells. The kinetics of the membrane Hsp70 (mHsp70) density on human glioma cells (U87) was studied after different irradiation doses to define the optimal therapeutic window for Hsp70-targeting NK cells. To maintain the cells in the exponential growth phase during a cultivation period of 7 days different initial cell counts were seeded. Although cytosolic Hsp70 levels remained unchanged on days 4 and 7 after a sublethal irradiation with 2 Gy, 4 Gy and 6 Gy, a dose of 2 Gy resulted in an upregulated mHsp70 density in U87 cells which peaks on day 4 and starts to decline on day 7. Higher radiation doses (4 Gy, 6 Gy) resulted in an earlier and more rapid onset of the mHsp70 expression on days 2 and 1, respectively, followed by a decline on day 5. Membrane Hsp70 levels are higher in G2/M than in G1, however, an irradiation-induced cell cycle arrest on days 4 and 7, was not associated with an increase in the mHsp70 density. Extracellular Hsp70 concentrations increased significantly compared to sham (0 Gy) irradiated cells on days 4 and 7 but not on day 1. Functionally, elevated mHsp70 densities were associated with a significantly better lysis by Hsp70-targeting NK cells. In summary, the kinetics of changes in the mHsp70 density upon irradiation on tumor cells is time- and dose-dependent.

The growing concern about climate change and the recognition of the planet’s limits led society to look for alternatives that promote the balance between the natural and the built environment. The circular economy emerges as an alternative to the linear economic model, inspired by natural metabolisms, by circulating resources in continuous loops, where their intrinsic value is maintained and improved. This research proposes a closed-loop strategy in the built environment by studying innovative constructive solutions that aim to find use, value, and inspiration in what is considered waste. A literature review is conducted on the circular design strategies, re-use and recycle typologies, and waste transformation processes. Then, the development of a methodology for qualitative evaluation and selection of re-used and upcycled construction materials from post-consumer waste and by-products is presented and then applied to thirty-five cases of constructive solutions from plastic, wood, paper, steel, aluminium, and agricultural waste. The research reports that the developed framework is adequate. The analysed alternative materials have good environmental performance and can be used as building materials despite their functional limitations, reflecting the enormous potential of waste as a resource for the construction industry.

The Brazilian livestock is predominantly extensive, with approximately 90% of the production being sustained on pasture, which occupies around 20% of the territory. In the current climate change scenario and where cropland is becoming a limited resource, there is a growing need for a more efficient land use and occupation. It is estimated that more than half of the Brazilian pastures have some level of degradation; however there is still no mapping of the quality of pastures on a national scale. In this study, we mapped and evaluated the spatio-temporal dynamics of pasture quality in Brazil, between 2010 and 2018, considering three classes of degradation: Absent (D0), Intermediate (D1), and Severe (D2). There was no variation in the total area occupied by pastures in the evaluated period, in spite of the accentuated spatial dynamics, with a retraction in the center-south and expansion to the north, over areas of ​​native vegetation. The percentage of non-degraded pastures increased ~12%, due to the recovery of degraded areas and the emergence of new pasture areas as a result of the prevailing spatial dynamics. However, about 44 Mha of the pasture area is currently severely degraded. The dynamics in pasture quality were not homogeneous in property size classes. We observed that in the approximately 2.68 million properties with livestock activity, the proportion with quality gains was twice as low in small properties compared to large ones, and the proportion with losses was three times greater, showing an increase in inequality between properties with more and less resources (large and small, respectively). The areas occupied by pastures in Brazil present an unique opportunity to increase livestock production and make available areas for agriculture, without the need for new deforestation in the coming decades.

The targeted application of plant growth promoting rhizobacteria (PGPR) provides the key for a future sustainable agriculture with reduced pesticide application. PGPR interaction with the indigenous microbiota is poorly understood but essential to develop reliable applications. Therefore, Stenotrophomonas rhizophila SPA-P69 was applied as seed coating and in combination with a fungicide based on the active ingredients fludioxonil, metalaxyl-M, captan and ziram. Plant performance and rhizosphere composition of treated and non-treated maize plants of two field trials were analyzed. Plant health was significantly increased by treatment; however overall corn yield was not changed. By applying high-throughput amplicon sequencing of the 16S rRNA and the ITS genes, the bacterial and fungal changes in the rhizosphere due to different treatments were determined. Despite treatments had a significant impact on the rhizosphere microbiota (9- 12%), the field site was identified as main driver (27- 37%). Soil microbiota composition from each site was significantly different, which explains the site-specific effects. In this study we were able to show first indications how PGPR treatments increase plant health via microbiome shifts in a site-specific manner. This way first steps towards a detailed understanding of PGPRs and developments of consistently efficient applications in diverse environments are set.

Schistosomiasis, a disease historically associated with poverty, lack of sanitation and social inequalities, is a chronic, debilitating parasitic infection, affecting hundreds of millions of people in endemic countries. Although schistosomiasis control approach has shown that chemotherapy is capable of reducing morbidity in humans, rapid re-infection is a reminder that the impact of drug treatment on transmission control or elimination initiatives is marginal. In addition, and regardless of more than two decades of well-executed control activities based on large-scale chemotherapy, the disease is expanding in many areas including Brazil. The development of the Sm14/GLA-SE schistosomiasis vaccine is an emblematic open knowledge innovation that has successfully completed Phase I and Phase IIa clinical trials, with Phase II/III trials underway in the African continent and to be followed in Brazil. Discovery and experimental phases were long term achievements leading to a robust collection of data that are strongly supporting the presently ongoing Clinical Phase. This paper reviews the development of the Sm14 vaccine formulated with GLA-SE (Glucopyranosyl Lipid A), from the earlier experimental developments to clinical trials including the recent status of Phase II studies.

Cognitive impairment in older adults is associated with poor gait performance, physical decline, falls and poor quality of life. This paper analyzes the feasibility and efficacy of a tango-based in-tervention in older people with cognitive impairment living in nursing homes. A multicenter study, with pre and post-test, was carried out. Intervention attendance, well-being, physical abilities (Short Physical Performance Battery), walking performance, functional capacities (Katz Index), and quality of life (Quality of Life in Alzheimer’s Disease) were assessed. Fifty-four participants (84.9 ± 6.7 years, Mini Mental State Examination 14.5 ± 7.4) completed the protocol. Intervention attendance was 92%, and the mean subjective well-being after each session was 4.5 ± 0.5 (on a five-point scale). Statistically significant improvement was found in the quality of life (p = 0.030). Non statistically significant changes were found in walking performance, physical abilities, or in functional capacities. The study shows feasibility and suggests evidence for the effects of Tango therapy on well-being and quality of life. Further studies are necessary to contrast these findings and to verify the role of Tango interventions as a holistic approach to prevent functional decline in older people with cognitive impairment.

The outstanding occurrences of red wood ant nests (RWA; Formica rufa-group) at two study sites in the Oberpfalz, NE Bavaria, Germany, could be confirmed by the 2023 re-inventory (a total of 5,393 nests and an increase by ≈8 %). RWA nests preferred mature and medium mature pine-dominated forests. Standing and downed dead wood do not negatively influence nests. Nest counts with woodpecker cavities and the diversity of the herb layer increased. The highly clustered nests in NW-SE direction suggests a strong interaction between nests distributions and the tectonic environment. Our developed (re-)inventory approach in combination with the comprehensive photo database is a valuable tool for a) monitoring the entire forest habitat including woodpecker cavities and dead wood in, at and around nests, and b) identifying GeoBio-Interactions. Such a comprehensive approach leads to more accurate and realistic counts of RWA nests during (re-)inventories and provides scientific evidence of the status quo of RWA occurrence. Our results disproved the unfounded and scientifically unsubstantiated blanket statement by laymen of the ASW Landesverband Bayern e.V. that RWA nest numbers in the Oberpfalz or even in the entire Bavaria are in sharp decline. We suggest seven to eight years as a suitable time interval for re-inventories.

This review focus on a critical analysis of nanocatalysts for Advanced Reductive Processes (ARP) and Oxidation Processes (AOP) designed for the degradation of poly/perfluoroalkyl substances (PFAS) in water. Ozone, ultraviolet and photocatalyzed ARP and/or AOP will be the basic treatment technologies. Besides the review of the nanomaterials with greater potential as catalyst for advanced processes of PFAS in water, the perspectives for its future development considering sustainability considerations will be discussed. Moreover, a brief analysis of the current state of the art of the ARP and AOP for the treatment of PFAS in water will be presented.

Salivarian trypanosomes are extracellular parasites affecting humans, livestock and game animals. Trypanosoma brucei rhodesiense and Trypanosoma brucei gambiense are human infective sub-species of T. brucei causing Human African Trypanosomosis (HAT - sleeping sickness). The related T. b. brucei parasite lacks the resistance to survive in human serum, and only inflicts animal infections. Animal Trypanosomosis (AT) is not restricted to Africa, but is present on all continents. T. congolense and T. vivax are the most widespread pathogenic trypanosomes in sub-Sahara Africa. Trough mechanical transmission, T. vivax has however been introduced into South America. T. evansi is a unique animal trypanosome that is found in vast territories around the world and can cause atypical Human Trypanosomosis (aHT). All salivarian trypanosomes are well adapted to survival inside the host’s immune system. This is not a hostile environment for these parasite, but this is the place where they thrive. Here we provide an overview of the latest insights into the host-parasite interaction and the unique survival strategies allowing trypanosomes to outsmart the immune system. In addition, we review new developments in treatment and diagnosis as well the issues that have hampered the development of field-applicable anti-trypanosome vaccines for the implementation of sustainable disease control.

Indoor Positioning Systems (IPSs) are designed to provide solutions for location-based services. Wireless local area network (WLAN)-based positioning systems are the most widespread around the globe and are commonly found to have a ready-to-use infrastructure composed mostly of access points (APs). They provide useful information on signal strength to be processed by adequate location algorithms, which are not always capable of achieving the desired localization error only by themselves. In this sense, this paper proposes a new method to improve the accuracy of IPSs by optimizing some of their most relevant infrastructure components. Included are the arrangement of APs over the environment, the number of reference points (RPs), and the number of samples per location estimation test. A simulation environment is also proposed, in which the impact of key influencing factors on system accuracy is analyzed. Finally, a case study is simulated to validate an optimal combination of design parameters and its compliance with the requirements of localization error and the limited number of access points. Our simulation results clearly show that the desired localization accuracy, which is set as a goal, can be achieved while maintaining the factors already mentioned at minimal levels, which decreases both system deployment costs and computational effort.

Access to food systems is essential to sustain urban life. In this paper, we discuss the differences concerning accessibility levels to food systems among potential consumers in Belo Horizonte, Brazil. The goal was to characterize spatial mismatches regarding food opportunities and identify suitable areas for sustainable food mile solutions, such as non-motorized home delivery and purchase trips. For this, we have spatially related: (i) the population concentration; (ii) the income of households; and (iii) accessibility measures considering both the spatial structure of food retailers and the distance between households and stores, considering the food mile. We have then used spatial statistics and spatial analysis methods to determine the spatial pattern of variables and the cumulative opportunity measure for households. There is great spatial differentiation regarding the accessibility levels of food retailers and the results can be considered to support the development of policy and land use regulation that can stimulate non-motorized and collaborative delivery as an effective last-mile solution.

The term Concept has been a prominent part of investigations in psychology and neurobiology where, mostly, it is mathematically or theoretically represented. The Concepts are also studied computationally through their symbolic, distributed and hybrid representations. The majority of these approaches focused on addressing concrete concepts notion, but the view of the abstract concept is rarely explored. Moreover, most computational approaches have a predefined structure or configurations. The proposed method, Regulated Activation Network (RAN), has an evolving topology and learns representations of Abstract Concepts by exploiting the geometrical view of Concepts, without supervision. In the article, the IRIS data was used to demonstrate: the RAN's modeling; flexibility in concept identifier choice; and deep hierarchy generation. Data from IoT's Human Activity Recognition problem is used to show automatic identification of alike classes as abstract concepts. The evaluation of RAN with 8 UCI benchmarks and the comparisons with 5 Machine Learning models establishes the RANs credibility as a classifier. The classification operation also proved the RAN's hypothesis of abstract concept representation. The experiments demonstrate the RANs ability to simulate psychological processes (like concept creation and learning) and carry out effective classification irrespective of training data size.

Infertility” is a condition defined by the failure to establish a clinical pregnancy after 12 months of regular, unprotected sexual intercourse or due to an impairment of a person’s capacity to reproduce either as an individual or with his/her partner’. The authors have set out to succinctly investigate, explore and assess infertility treatments harnessing the potential of stem cells to effectively and safely treat infertility, in addition to the legal and regulatory complexities at the heart of stem cell research, with an overview of the legislative state of affairs in six major European countries. In couples who cannot benefit from assisted reproductive technologies (ART) to treat their infertility, stem cells-based approaches have been shown to be a highly promising approach. Nonetheless, lingering ethical and immunological uncertainties require more conclusive findings and data before such treatment avenues can become mainstream and applied large scale. The isolation of human embryonic stem cells (ESCs) is ethically controversial, since their collection involves the destruction of human embryonic tissue. Overall, stem cell research has resulted in important new breakthroughs in the treatment of infertility. The effort to untangle the complex web of ethical and legal issues associated with such therapeutic approaches will have to rely on evidence-based, broadly shared standards, guidelines and best practices to make sure that the procreative rights of patients can be effectively reconciled with the core values at the heart of medical ethics.

Cystatin F (CstF) is a protease inhibitor of cysteine cathepsins, including those involved in acti-vating the perforin/granzyme cytotoxic pathways. It is targeted to the endolysosomal pathway but can also be secreted to the extracellular milieu or endocytosed by bystander cells. CtsF was shown to be significantly increased in tuberculous pleurisy, and during HIV coinfection, pleural fluids display high viral loads. In human macrophages, we revealed a strong upregulation of CstF during infection with Mycobacterium tuberculosis (Mtb). CstF manipulation using RNA si-lencing led to increased proteolytic activity of lysosomal cathepsins, improving Mtb intracellular killing. Here, we investigate the impact of CstF depletion during coinfection of Mtb-infected mac-rophages with lymphocytes infected with HIV. Our results indicate that decreasing CstF released by phagocytes impacts the major pro-granzyme convertase cathepsin C of cytotoxic immune cells. Consequently, an observed increase of the granzyme B apoptotic effects leads to a significant re-duction in viral replication in HIV-infected lymphocytes. Overall, our results indicate a mecha-nism of Mtb/HIV evasion of the cytotoxic mediated pathogen killing driven by the ax-is CstF/ catC/granzymes contributing to this syndemic interaction. Ultimately, this knowledge can be crucial for developing new therapeutic approaches to control both pathogens based on manipulating CstF.

Protein oligomerzation is key to countless physiological processes, but also to abnormal amyloid conformations implicated in over 25 mortal human diseases. Angiogenin (h-ANG), a ribonuclease A family member, produces RNA fragments that regulate ribosome formation, the creation of new blood vessels and stress granule function. Too little h-ANG activity leads abnormal protein oligomerization resulting in Amyotrophic Lateral Sclerosis (ALS) or Parkinson’s disease. While a score of disease linked h-ANG mutants has been studied by X-ray diffraction, some elude crystallization. There is also debate regarding the structure that RNA fragments adopt after cleavage by h-ANG. Here, to better understand the beginning of the process that leads to aberrant protein oligomerization, the solution secondary structure and residue-level dynamics of WT h-ANG and two mutants: H13A and R121C, are characterized by multidimensional heteronuclear NMR spectroscopy under near physiological conditions. All three variants are found to adopt well folded and highly rigid structures in solution, although the elements of secondary structure are somewhat shorter than those observed in cystallography studies. R121C alters the environment of nearby residues only. By constrast, the mutation H13A affects local residues as well as nearby active site residues residues K41 and H119. The conformation characterization by CD and 1D 1H NMR spectroscopies of tRNAAla before and after h-ANG cleavage reveals a retention of most duplex structure and little or no G-quadruplex formation.

Palmitoylethanolamide (PEA) has been prescribed for neuropathic pain for several years. This study is mainly addressed to summarize what has been published on the topic in the last decades, and how appropriate the numerous prescriptions are. Among others, it examines the innovative EquiPEA^® patent, which aims to address obstacles encountered with conventional PEA formulations. EquiPEA^® seems to partially ameliorate the bioavailability and the targeted distribution. It seems to introduce novel advancements that have the potential to enhance the therapeutic effectiveness of PEA in terms of its anti-inflammatory, antioxidant, and analgesic properties. The deep literature analysis aims to examine the potential advantages of this innovative formulation, in the context of several pathological conditions that may benefit from this molecule. In particular, it investigates the potential enhanced bioavailability and targeted delivery system of EquiPEA^®. Also, it tries to understand if it can modernize the field of therapy based on PEA, thus offering a better treatment option for individuals with long-term inflammation, oxidative stress, and neuropathic or mixed pain with a neuropathic component. The study examines the possible impact of EquiPEA^® on personalized medicine strategies and its potential for translation into clinical practice. It analyses the possibilities that EquiPEA^® has in enhancing patient outcomes in a range of central nervous system and inflammatory conditions. This narrative review makes a valuable contribution to the ongoing comprehension of PEA therapy. It establishes a foundation for further exploration in research and potential uses in clinical settings.

Anthocyanins, the naturally occurring pigments responsible for most red to blue colours of flowers, fruits and vegetables, have also attracted interests because of their potential health effects. With the aim of contributing to major insights into their structure-activity relationship (SAR), we have evaluated the radical scavenging and biological activities of selected purified anthocyanin samples (PASs) from various anthocyanin-rich plant materials: two fruits (mahaleb cherry and blackcurrant) and two vegetables (black carrot and ‘Sun Black’ tomato). PASs from the above-mentioned plant material have been evaluated for their antioxidant capacity, using TEAC and ORAC assays. In human endothelial cells, we analysed the biological activity of different PASs by measuring their effects on the expression of endothelial inflammatory markers, including endothelial adhesion molecules VCAM-1 and ICAM-1. We demonstrated that all the different PASs showed biological activity. They exhibited antioxidant capacity of different magnitude, higher for samples containing non-acylated anthocyanins (typical for fruits) compared to samples containing more complex anthocyanins acylated with cinnamic acid derivatives (typical for vegetables), even though this order was slightly reversed when ORAC assay values were expressed on molar basis. Concordantly, PASs containing non-acylated anthocyanins reduced the expression of endothelial inflammatory antigens more than samples with aromatic acylated anthocyanins, suggesting the potential beneficial effect of structurally diverse anthocyanins in cardiovascular protection.

In this paper we propose a computational framework that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large number of mechanistic models in SBML that are currently stored in public databases. With the proposed framework, existing SBML mechanistic models may be upgraded to hybrid systems through the incorporation of deep neural networks into the model core, using a freely available python tool. The so-formed hybrid mechanistic/neural network models are trained with a deep learning algorithm based on the adaptive moment estimation method (ADAM), stochastic regularization and semidirect sensitivity equations. The trained hybrid models are encoded in SBML and stored back in model databases, where they can be further analyzed as regular SBML models. The application of this approach is illustrated with three well-known case studies: the threonine synthesis model in Escherichia coli, the P58IPK signal transduction model, and the Yeast glycolytic oscillations model. The proposed framework is expected to greatly facilitate the widespread use of hybrid modeling techniques for systems biology applications.

Soil texture is a key property influencing most soil physical, chemical, and biological processes and its catchment-scale spatial variation may yields insights for soil management. Texture data are generally available only at a few locations, since sampling and laboratory analyses are time consuming. Therefore, it is essential to predict soil size particles texture variability using appropriate methods. Moreover, soil texture distribution across a catchment is influenced by erosion and sedimentation processes controlled by hillslope morphology, which can be quantified through some topographic attributes. The study was aimed to evaluate the ability of a multivariate approach based on non-stationary geostatistics to merge remotely sensed high-resolution LiDAR-derived topographic attributes with Vis-NIR diffuse reflectance spectroscopy and laboratory analysis to produce high-resolution maps of soil sand content and estimation uncertainty in a forested catchment in southern Italy. Moreover, the proposed approach was compared with the commonly used univariate approach of ordinary kriging. Soil samples were collected at 135 locations within a 139 ha-forest catchment with granitic parent material and subordinately alluvial deposits, where soils classified as Typic Xerumbrepts and Ultic Haploxeralf crop out. A number of linear trend models coupled with different auxiliary variables were compared and the best one resulted the model using clay content as auxiliary variable. The improvement of estimation from using only LiDAR data (elevation) compared to the univariate (no trend) model was rather marginal.

Nanostructured carriers have been widely used in pharmaceutical formulations for dermatological treatment. They offer targeted drug delivery, sustained release, improved biostability, and low toxicity, usually presenting advantages over conventional formulations. Due to its large surface area, small size and photothermal properties, graphene oxide (GO) has the potential to be used for such applications. Nanographene oxide (GOn) presented average sizes of 197.6 ± 11.8 nm, and a surface charge of -39.4 ± 1.8 mV, being stable in water for over 6 months. 55.5 % of the mass of GOn dispersion (at a concentration of 1 mg mL-1) permeated the skin after 6 h of exposure. GOn dispersions have been shown to absorb near-infrared radiation, reaching temperatures up to 45.7 °C, within mild photothermal therapy temperature range. Furthermore, GOn in amounts superior to those which could permeate the skin were shown not to affect human skin fibroblasts (HFF-1) morphology or viability, after 24 h of incubation. Due to its large size, no skin permeation was observed for graphite particles in aqueous dispersions stabilized with Pluronic P-123 (Gt-P-123). Altogether, for the first time, GOn potential as a topic administration agent and for delivery of photothermal therapy has been demonstrated.

Pulmonary hypertension (PH) has a high mortality, and few treatment options. Adaptive immune mediators of PH in mice challenged with antigen/particulate matter (antigen/PM) has been the focus of our prior work. We identified key roles of type 2 and type 17 responses in C57BL/6 mice. Here, we focused on type 2 response related cytokines, specifically Resistin-like-molecule (RELM)α, a critical mediator of hypoxia-induced PH. Because of strain differences in the immune responses to type 2 stimuli, we compared C57BL/6J and BALB/c mice. A model of intraperitoneal antigen sensitization with subsequent, intranasal challenges with antigen/PM (ovalbumin and urban ambient PM2.5) or saline was used in C57BL/6 and BALB/c wild type or RELMα-/- mice. Vascular remodeling was assessed by histology, right ventricular (RV) pressure, RV weights and cytokines were quantified. Upon challenge with antigen/PM2.5, both C57BL/6 and BALB/c mice developed pulmonary vascular remodeling; these changes were more prominent in the C57BL/6 strain. Compared to wild type mice, RELMα-/- had significantly reduced pulmonary vascular remodeling in BALB/c, but not in C57BL/6 mice. RV weights, RV IL-33 and RV ST2-IL-33-receptor were significantly increased in BALB/c wild type mice, but not in BALB/c-RELMα-/- or in C57BL/6-wild type or C57BL/6-RELMα-/- mice. RV systolic pressures (RVSP) were higher in BALB/c compared to C57BL/6J mice, and RELMα-/- were not different from their respective wild type controls. In BALB/c mice, RELMα was a key contributor to antigen/PM2.5 induced pulmonary vascular remodeling, RV thickening and RV cytokine responses, highlighting the significance of the genetic background. The RELMα-/- animals demonstrated significantly decreased expression of RELMβ and RELM which makes these mice comparable to a situation where human RELMα levels would be significantly modified, as humans only have one RELM molecule.

Artisanal cheeses made with raw milk are highly appreciated products in Brazil. Most of these cheeses are produced in small properties across different production regions in the country, many of which have been granted a protected designation of origin. The most prominent state that manufactures these products is Minas Gerais, but production is also gaining strength in other Brazilian states. This text presents an overview of the many types of artisanal cheeses produced in the country, grouped by geographical regions, and reviews the current challenges faced by producers and government considering the safety of these cheeses.

Changes in food quality can dramatically impair zooplankton fitness, especially in eutrophic water bodies where cyanobacteria are usually predominant. Cyanobacteria are considered a food with low nutritional value, besides some species can produce bioactive secondary metabolites reported as toxic to zooplankton. Considering that cyanobacteria can limit survival, growth and reproduction of zooplankton, we hypothesized that the adverse effects of the dietary exposure of Daphnia species to saxitoxin-producing cyanobacteria depend on the relative abundance of nutitious food source in the diet. Life table experiments were conducted with different diets: 1) without nutritional restriction, where neonates were fed with diets at a constant green algae (Monoraphidium capricornutum) biomass as a nutritious food source, and increasing cyanobacterial concentration (STX-producing Raphidiopsis raciborskii), and 2) with diets consisting of different proportions of M. capricornutum (nutritious) and R. raciborskii (poor food) at a total biomass 1.0 mg C L 1. In general, the presence of high proportions of cyanobacteria promoted a decrease in Daphnia somatic growth, reproduction and intrinsic rate of population increase (r) in both diets with more pronounced effects in the nutritionally restricted diet (90% R. raciborskii). Two-way ANOVA revealed significant effects of species/clone and treatments in both assays, with significant interaction between those factors only in the second assay. Regarding the grazing assay, only D. laevis was negatively affected by increased cyanobacterial proportions in the diet. In the life table assay with constant edible food, a reduction in the reproduction parameters and the intrinsic rate of population increase (r) of all species was observed, In conclusion, we found adverse effects of the toxic cyanobacterial strain R. raciborskii on Daphnia fitness, regardless of the constant amount of nutritious food available, proving the toxic effect of R. raciborskii and the nutritional quality of the food has a greater influence on the fitness of these animals.

Machine Learning can be used for social good. In this paper, we discuss how it can be used to combat climate change and facilitate land management and farming in developing countries and in particular in Côte d’Ivoire. This paper explores models that improve land and water management and agricultural farming cultivation to contrast climate change. Côte d’Ivoire is the largest producer of cocoa beans (43%) in the world, but deforestation, lack of rainfall, drought, and climate change threaten crops and the already fragile economy of Ivorian farmers. It is important to combat climate change with methods and techniques that are affordable to the local farmers and also induce positive effects in production. We discuss the use of low-cost sensors to collect data on the soil and open data and open source software to develop AI tools. We show that using deep neural networks (YOLOv5m) is effective for detecting healthy plants and pods of cocoa from damaged ones only using mobile phone images. Focusing on a single land is not enough to combat climate change, which has different causes and involves also knowledge at a higher scale. We propose a new method of forecasting for the analysis of remote sensors. Remote sensor data come from GRACE NASA Mission and ERA5 produced by the Copernicus Climate Change Service at ECMWF. We implement a new deep neural network architecture named CIWA-net. It is based on a Fully Convolutional Neural Network (FCN) [ 1] and it is a U-net like architecture [2]. The aim of CIWA-net is to forecast Total Water Storage Anomalies (TWSA). We show the quality of our model with a comparison to a vanilla Convolutional Neural Network. CIWA-net could be used also for the detection of lands that interfere with agricultural work and yields, such as deserted areas, water-soaking soil areas, zones at risk of desertification, and poor land use. The employment of AI at the service of agriculture can decrease crop losses and waste, lower the inputs onto the soil of fertilizers, responsible for the increase of Greenhouse Gases. It could be useful to help the small farmers (at a local scale) and also the policy-makers and farmers’ cooperatives (at the regional scale) to take valid and coordinated countermeasures to improve the correct use of the lands, helping to contrast and adapt to climate change.

In the last decades, consumers are increasingly interested in organic products and they strongly demand for reliability of the traceability of the organic products they use to buy and eat. Different researches have been carried out over the years to investigate on new and reliable systems to test the authenticity of products obtained using organic cultivation methods. The monitoring of some chemical components, derived from primary and/or secondary metabolism, in horticultural organic and conventional products, has highlighted the diversity induced by the two production techniques while the difference in fertilization practices has been shown to impact on the isotopic distribution of some elements, with particular reference to nitrogen. An integrated system is proposed to validate, through the acquisition of isotopic data and other chemical and biochemical parameters, the authenticity of organic products. This approach is intended to be coupled to the application of chemometric multivariate analysis of isotopic data combined with other quality and nutraceutical parameters, giving the possibility to discriminate organic from conventional products, thanks to the different isotopic signature impressed by the different nitrogenous source combined with the qualitative pattern of the crops, significantly affected by the different treatments. The main perspectives of the presented integrated approach, based on the combined use of chemometric and analytical tools, are linked to the feasibility of applying a reliable system to authenticate productions obtained with organic fertilizers (organic agriculture) respect to those obtained with the use of synthetic fertilizers (conventional agriculture), protect and valorize virtuous farmers and support political stakeholders and decision makers to counteract food fraud.

This article presents an estimation of the hypertension risk based on a dataset on 1007 individuals. The application of a Tobit Model shows that “Hypertension” is positively associated to “Age”, “BMI-Body Mass Index”, and “Heart Rate”. The data show that the element that has the greatest impact in determining inflation risk is “BMI-Body Mass Index”. An analysis was then carried out using the fuzzy c-Means algorithm optimized with the use of the Silhouette coefficient. The result shows that the optimal number of clusters is 9. A comparison was then made between eight different machine-learning algorithms for predicting the value of the Hypertension Risk. The best performing algorithm is the Gradient Boosted Trees Regression according to the analyzed dataset. The results show that there are 37 individuals who have a predicted hypertension value greater than 0.75, 35 individuals who have a predicted hypertension value between 0.5 and 0.75, while 227 individuals have a hypertension value between 0.0 and 0.5 units.

The following article indicates the determinants of “Internet User Skills” among European countries based on the application of the database deriving from the DESI-Index. The data were analyzed using the following econometric models, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS, WLS corrected for heteroskedasticity. The Elbow method and the Silouette coefficient method were compared for the optimization of the number of clusters obtained by the k-Means algorithm. The result shows the presence of 5 clusters. A network analysis was carried out using the Euclidean distance with the result of identifying two network structures between some analyzed countries. subsequently a comparison was made between six different machine learning algorithms for the prediction of the future value of the variable of interest. The result shows that the best predictor algorithm is Gradient Boosted Tree Regression with an expected value of the predicted variable increasing by a value of 1.75%. Later a further comparison was made by comparing 6 algorithms with the increased data. The result shows that the best predictor is Simple Regression Tree. The interest variable is predicted to decrease by an amount equal to -6.099%. Statistical errors improve on average by 32.43% in the transition between the original data and the increased data.

The following article estimates the value of ICT Specialists in Europe between 2016 and 2021 for 28 European countries. The data were analyzed using the following econometric techniques, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, WLS and Pooled OLS. The results show that the value of ICT Specialists in Europe is positively associated with the following variables: "Desi Index", "SMEs with at least a basic level of digital intensity", "At least 100 Mbps fixed BB take-up" and negatively associated with the following variables: "4G Coverage","5G Coverage", "5G Readiness", "Fixed broadband coverage", "e-Government", "At least Basic Digital Skills", "Fixed broadband take-up", "Broadband price index", "Integration of Digital Technology". Subsequently, two European clusters were found by value of "ICTG Specialists" using the k-Means clustering algorithm optimized by using the Silhouette coefficient. Finally, eight different machine learning algorithms were compared to predict the value of "ICT Specialists" in Europe. The results show that the best prediction algorithm is ANN-Artificial Neural Network with an estimated growth value of 12.53%. Finally, "augmented data" were obtained through the use of the ANN-Artificial Neural Network, through which a new prediction was made which estimated a growing value of the estimated variable equal to 3.18%.