The review of previous works shows this study is the first attempt to analyse the lockdown effect using Natural Language Processing Techniques, particularly sentiment analysis methods applied at large scale. On the other hand, it is also the first of its kind to analyse the impact of COVID 19 on the university community jointly on staff and students and with a multi-country perspective. The main overall findings of this work show that the most often related words were family, anxiety, house and life. On another front, it has also been shown that staff have a slightly less negative perception of the consequences of COVID in their daily life. We have used artificial intelligence models like swivel embedding and the Multilayer Perceptron, as classification algorithms. The performance reached in terms of accuracy metric are 88.8% and 88.5%, for student and staff respectively. The main conclusion of our study is that higher education institutions and policymakers around the world may benefit from these findings while formulating policy recommendations and strategies to support students during this and any future pandemics.

This paper presents a Multilayer Perceptron and Support Vector Machine algorithms approach to predict the number of COVID19 infections in different countries of America. It intends to serve as a tool for decision-making and tackling the pandemic that the world is currently facing. The models were trained and tested using open data from the European Union repository where a time series of confirmed contagious cases was modeled until May 25, 2020. The hyperparameters as number of neurons per layer were set up using a tabu list algorithm. The countries selected to carry out the study were Brazil, Chile, Colombia, Mexico, Peru and the United States. The metrics used are Pearson's correlation coefficient (CP), Mean Absolute Error (MAE), and Mean Percentage Error (MPE). For the testing stage we obtained the following results: Brazil, CP=0.65, MAE=2508 and MPE=17%; Chile, CP=0.64, MAE=504, MPE=16%; Colombia, CP=0.83, MAE=76, MPE=9%; Mexico, CP=0.77, MAE=231, MPE=9%; Peru, CP=0.76, MAE=686, MPE=18% and the United States of America, CP=0.93, MAE=799, MPE=4%. This resulted in powerful machine learning tools although it is necessary to use specific algorithms depending on the data and the stage of the country’s pandemic.

The aim of this study was to build a tool to analyze, using artificial intelligence, the sentiment perception of users who answered two questions from the CSQ – 8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in daily life. As such, we proposed an online course where this method was applied in order to improve the quality of life of health care professionals in COVID 19 pandemic times. We also carried out an evaluation of the satis-faction level of the participants involved, with a view to establishing strategies to improve fu-ture experiences. To automatically perform this task, we used Natural Language Processing (NLP) models such as swivel embedding, neural networks and transfer learning, so as to classify the inputs into the following 3 categories: negative, neutral and positive. Due to the lim-ited amount of data available - 86 registers for the first and 68 for the second - transfer learning techniques were required. The length of the text had no limit from the user’s standpoint, and our approach attained a maximum accuracy of 93.02 % and 90.53 % respectively based on ground truth labeled by 3 experts. Finally, we proposed a complementary analysis, using com-puter graphic text representation based on word frequency, to help researchers identify relevant information about the opinions with an objective approach to sentiment. The main conclusion drawn from this work is that the application of NLP techniques in small amounts of data using transfer learning is able to obtain enough accuracy in sentiment analysis and text classification stages

In this paper, a robust nonlinear dynamic controller is designed for a wind turbine with a permanent magnet synchronous generator. The wind turbine is subject to variations in all the parameters appearing in its mathematical model. Furthermore, the wind velocity is considered unavailable for direct measurement. This situation is of particular interest in practical applications, where only the nominal parameter values are known, and accurate wind velocity measurement is challenging due to perturbations caused by the turbine itself, even with appropriate sensors. The problem addressed in this work involves tracking the reference angular velocity corresponding to the wind velocity. To achieve accurate tracking, appropriate compensation of the perturbation terms resulting from parameter uncertainties and wind estimation errors is required. To address this problem, an estimator of the wind velocity is utilized, along with high–order sliding mode parameter estimators, to ensure high–performance operation of the turbine.

Objectives: To develop a risk prediction model for the identification of features involved in the prediction of erectile dysfunction (ED) at 12 months following COVID-19 recovery. Methods: We performed an observational prospective multicentre study. Participants were classified according to their history of COVID-19: I) Patients with a past history of COVID-19; and II) Patients without a previous microbiological diagnosis of COVID-19. A total of 361 patients (Past history of COVID-19, n=166; No past history of COVID-19, n=195) were assessed from January 2022 to March 2023. Patients with a past history of COVID-19 were assessed at 12 months following COVID-19 recovery. The primary outcome measure was ED, assessed through the 5-item International Index of Erectile Function (IIEF-5). Data concerning epidemiologic variables, comorbidities and active treatment were also collected. We performed a binary logistic regression to develop a risk predictive model. Among the models developed, we selected the one with the higher Area Under the Curve (AUC). Results: The median age was 55 years in both groups. The ED prevalence was 55.9% in patients with past history of COVID-19 and 44.1% in those with no past history of COVID-19. The best predictive model developed for ED comprised 40 variables and had an AUC of 0.8. Conclusions: We developed a regression model for the prediction of ED 12 months after COVID-19 recovery. The application of our predictive tool in a community setting could eventually prevent the adverse effects of ED on cardiovascular health, and the associated unfavourable economic impact.

Objectives: To develop a machine learning-based model for the identification of features involved in the prediction of long-term erectile dysfunction (ED) after COVID-19 recovery. Methods: We performed an observational prospective multicentre study. Participants were divided into 2 groups: I) Patients with a past history of COVID-19; II) Patients without a previous microbiological diagnosis of COVID-19. A total of 361 patients (COVID-19 group, n=166, Control group; n=195) were assessed from January 2022 to March 2023. COVID-19 group patients were assessed 12 months after COVID-19 recovery; Control group patients were assessed within the same time window. The primary outcome measure was ED. A machine learning-based model including three algorithms (random forest, logistic regression and support vector machines [SVM]) was applied to perform the automatic selection of those features involved in the prediction of ED. The algorithm SVM-recursive feature elimination (RFE) was also executed. Results: The median age was 55 years in both groups. The final selection of variables in our model was: group, SARS-CoV-2 vaccination status, hypertension, diabetes, beta blocker treatment, antiplatelet therapy and coffee intake. The algorithm SVM-RFE showed that a past history of COVID-19 and SARS-CoV-2 vaccination were both long-term ED predictors in our model. Conclusions: We developed a machine learning-based model for the prediction of long-term ED following COVID-19 recovery. A past history of COVID-19 and SARS-CoV-2 vaccination were both predictors in our model. The application of our predictive tool in a community setting could avoid the adverse effects of ED and the unfavourable economic impact associated.

Current State-of-the-Art (SotA) chatbots are able to produce high quality sentences, handling different conversation topics, and larger interaction times. Unfortunately, the generated responses highly depend on the data on which they have been trained, the specific dialogue history and current turn used for guiding the response, the internal decoding mechanisms, ranking strategies, among others. Therefore, it may happen that for semantically similar questions asked by users, the chatbot may provide a different answer, which can be considered as a form of hallucination or produce confusion in long-term interactions. In this research paper, we propose a novel methodology consisting of two main phases: a) hierarchical automatic detection of topics and subtopics in dialogue interactions using a Zero-Shot learning approach, and b) detecting inconsistent answers using K-Means and the Silhouette coefficient. To evaluate the efficacy of topic and subtopic detection, we used a subset of the DailyDialog dataset and real dialogue interactions gathered during the Alexa Socialbot Grand Challenge 5 (SGC5). The proposed approach enables detecting up to 18 different topics and 102 subtopics. For the purpose of detecting inconsistencies, we manually generate multiple paraphrased questions and employ several pre-trained SotA chatbot models to generate responses. Our experimental results demonstrate a weighted F-1 value of 0.34 for topic detection, a weighted F-1 value of 0.78 for subtopic detection in DailyDialog, then 81% and 62% accuracy for topic and subtopic classification in SGC5; finally, to predict the number of different responses, we obtained a mean squared error (MSE) of 3.4 when testing smaller generative models and 4.9 in recent large language models.

Severe COVID-19 is associated with viraemia and multiple organ disease. Similar clinicopathological features have been previously seen in SARS and MERS. Clinically, the severity of SARS, MERS and COVID-19 has been associated with the presence of SARS-CoV, MERS-CoV or SARS-CoV2 viraemia in affected patients. In vitro work has looked at the pattern of viral entry and release from polarised epithelial cells infected by coronaviruses. This work has demonstrated a correlation between the severity of a coronavirus infection and the ability of the virus to reach and infect the basal surface of host cells. It has been postulated that this ability helps the virus invade the bloodstream of the host, resulting in a systemic infection with multiple organ involvement. Here we propose that basal surface release and entry of COVID-19 into and out of cells at epithelial-endothelial interface plays a key pathogenic role in severe COVID-19 disease.

Severe Covid-19 disease is associated with endothelial infection, viraemia, and multi-organ dysfunction. The process through which SARS-CoV2 causes severe disease is yet to be determined. Here, we propose that in severe Covid-19 infection, SARS-CoV2 reaches the host bloodstream by infecting endothelial cells through their basal surface. This occurs, independently of ACE2, through CD147, a putative SARS-CoV2 receptor. The pathway proposed here encourages research on the mechanisms mediating endothelial cell infection in Covid-19.

Healthcare professionals constantly face situations that reflect ecosystems’ degradation. These can negatively affect their mental health. Research suggests that hope and resilience can play an important role in this scenario, since they are related to/predict mental health in highly heterogeneous samples (considering geography, age, profession, health, etc.). In this context, the aims of the present study are: to characterize and explore the relationship between hope, resilient coping and mental health of Portuguese healthcare professionals. Using Google Forms, 276 healthcare professionals answered to the GHQ-28, the (adult) Trait Hope Scale, and the Brief Resilient Coping Scale (cross-sectional study). The minimum and maximum possible scores were reached, with the exception of the maximum score of GHQ-28-Total. Regarding Hope, 19.6% scored below the midpoint (M=43.46, SD=11.97); 29.3% revealed low resilience (M=14.93, SD=4.05); and the average of 4 of the 5 Mental Health scores (exception: Severe Depression) indicates the probability of a psychiatric case. Hope correlated with Social Dysfunction and GHQ-28-Total; resilient coping proved to be a (weak) predictor of 4 of the 5 GHQ-28 indicators (exception: Severe depression). The results support the need to promote the sample's mental health, hope and resilient coping. They also suggest that stimulating resilient coping may contribute to improving healthcare professionals’ mental health.

The aim of the present work was to evaluate the effects of Thalassia testudinum hydroethanolic extract, its polyphenolic fraction, and thalassiolin B on the activity of phase I metabolizing enzymes as well as their antimutagenic effects. Spectrofluorometric techniques were used to evaluate the effect of tested products on rat and human CYP1A and CYP2B activity. The antimutagenic effect of tested products was evaluated in benzo[a]pyrene (BP)-induced mutagenicity assay by Ames test. Finally, the antimutagenic effect of Thalassia testudinum (100 mg/kg) was assessed in a BP-induced mutagenesis in mice. The tested products significantly (p<0.05) inhibit rat CYP1A1 activity, acting as mixed-type inhibitors of rat CYP1A1 (Ki = 54.16±9.09 μg/mL, 5.96±1.55 μg/mL and 3.05±0.89 μg/mL, respectively). Inhibition of human CYP1A1 was also observed (Ki = 197.1±63.40 μg/mL and 203.10±17.29 μg/mL for the polyphenolic fraction and for thalassiolin B, respectively). In addition, the evaluated products significantly inhibit (p<0.05) benzo[a]pyrene (BP)-induced mutagenicity in vitro. Furthermore, oral doses of Thalassia testudinum (100 mg/kg) significantly reduced (p<0.05) the BP-induced micronuclei and oxidative damage, together with an increase of glutathione, in mice. In summary, Thalassia testudinum metabolites exhibit antigenotoxic activity mediated, at least, by the inhibition of CYP1A1-mediated BP biotransformation. Thus, the metabolites of T. testudinum may represent a potential source of chemopreventive compounds for adjuvant therapy of cancer.

Plant-based alternative medicine is normally grounded on empiric cultural perception, as the main objective, these practices intent to either maintain good health or to provide a route to turn-the-tide on a specific disease or ailment. Amongst the thousands of plants that have been used and studied, Neem (Azadirachta indica) seems to have a very interesting tale to tell, since its properties to ward-off certain diseases have overtime, and in a rigorous way, been proven. The preceding concise review is a collection of some of the most relevant studies today, not only focusing on the health benefits obtained by its use, but digging into the molecular mechanisms of how the properties come about. In particular, we take a look over antioxidant properties and how these mediate and mitigate important molecules such as IL-6 and TNF-, leading the way in reducing systematic damage by oxidative stress. Further, we relate this oxidative reduction to other systemic diseases such as cancer and diabetes, as these are currently becoming the most rampant killers. As of yet not all is known about the different ways of extracting or the total composition of an extract, as these may be from different parts of the plant. Therefore, we also allude to an important cautionary view where toxicological effects and conflicting outcomes arise. Overall, presented results show a great potential for the different extracts of Neem as their antioxidant activity can be taken advantage off, and potentially used in modern medicine.

All types of sports are potential application scenarios for automatic and real-time visual object and event detection. In rink hockey, the popular roller quad skate variant of hockey team sports, it is of great interest to automatically track player’s movements and positions, player’s sticks and, also, making other judgments, such as being able to locate the ball. In this work, we introduce a real-time pipeline composed by an object detection model, created specifically for rink hockey games, followed by a knowledge-based event detection module. Even in the presence of occlusions and quick motions, our deep learning object detection model effectively identifies and tracks, in real-time, important visual elements such as: ball; players; sticks; referees; crowd; goalkeeper; and goal. Using a curated dataset composed by a collection of videos of rink hockey, comprising 2525 annotated frames, we trained and evaluated the algorithm performance and compare it to state of the art object detection techniques. Our object detection model, based on YOLOv7, presents a global accuracy of 80%, and presents a good performance in terms of accuracy and speed, according to our results, making it a good choice for rink hockey applications. In our initial tests, the event detection module successfully detected one important event type in rink hockey games, the occurrence of penalties.

As a follow-up to previously published research, this paper examines the responses of a group (n=185) of professional and volunteer firefighters directly involved in fighting extreme wildfire events of the 2017 summer season in Portugal. The data used in this research stem from two open-ended questions in response to a web-based survey: i) lessons learned and ii) proposals for improving the Civil Protection service. The replies were qualitatively examined. Participants exhibit incomplete awareness of extreme wildfires, and their only answers are i) the improvement of both the current organization and the technical and human resources of the suppression model (question 1), and ii) the increase in human and material resources, the single command, the in-dependence from Civil Protection and the valorization of experience, as the main aspects for the improvement of Civil Protection (question 2). Little attention is given to prevention and to the concept of control capacity, respectively. The answers to both questions showcase scarce knowledge of the paradigm shift in reference to the prevention model. The ratios of missing re-plies to both questions were 32.43% and 47.57%, respectively. The work stands out for its novelty and originality, as to our knowledge there is a total lack of similar works in all European Union literature.

In this work, we apply ensemble formalism to a geometric agents model to study the effect of saving propensity in a system with money, credit, and debt. We calculate the partition function to obtain the total money of the system, with which we give an interpretation of the economic temperature in terms of the different payment methods available to the agents. We observe an interplay between the fraction of money that agents can save and the debt that can be financed. We also observe that the system’s entropy increases as the saved proportion increases and increases, even more, when debt is present.

The objective of this study was to analyze the effects of a pulmonary telerehabilitation (TR) program in young adults with post-COVID-19 syndrome. The information of sixteen students' medical files were analyzed and allocated to one of two groups (control=CG/experimental=EG). Twelve TR sessions were performed distantly and asynchronously at the EG patients' homes during 4-weeks. The program included diaphragmatic pattern breathing and aerobic exercises. The parameters: i) vital signs (oxygen saturation "SpO2", heart rate "HR", respiratory rate "RR" and blood pressure "BP"; ii) physical capacity “Sit-to-stand test”; iii) cardiorespiratory capacity “6-Minute Walk Test”; and iv) perceived effort "Borg scale" were assessed in both groups. The statistical analyses showed a significant decrease of RR and HR (p < 0.012) accompanied by a significant increase in SpO2 (p < 0.042), physical (p < 0.012) and respiratory (p < 0.028) capacity. The perceived effort decreased significantly in both groups (CG: p < 0.006; EG p < 0.001) only for physical but not for cardiorespiratory capacity (p < 0.106). There were no statistical changes registered in BP (p > 0.05). The current study suggests that a TR program that involves breathing and aerobics exercises is feasible and effective in treating post-COVID-19 syndrome in young patients.

The contractual relationship between the processing firm and the broiler smallholder presents incessant conflicts of interest and inequality due to technical and economic discrepancies, leading to an undervaluation of the producers' remuneration. This study aims to deepen the discussions in searching for a more balanced monetary exchange between processing firms and broiler smallholders based on scientific aspects. For this, the Emergy theory and its concepts were used in considering a representative broiler production system at Concórdia, Santa Catarina, Brazil. This study suggests the inclusion of cultural information in the Emergy-based model calculation. For the broiler smallholder, cultural information showed the highest Emergy contribution (62.95%; transformity = 1.73 ×10^8). However, only considering cultural information was not sufficient to increase the sustainability of the broiler production system. The results highlight an imbalance of the monetary exchange between agroindustry and broiler smallholder payment for both the economic and Emergy-based payment. Both estimated payments were higher than the practiced payment value (0.24 USD/broiler as well as 0.32 USD/broiler and 1.62 EmUSD/broiler, respectively). Thus, evaluating the “(eco)cost” in Emergy-based accounting recognizes that production depends not only on tangible physical resources but also on knowledge, skills and information (“iceberg of value” thinking). Policy and decision makers must, therefore consider the promotion of public policies that subside initiatives, including social and environmental welfare programmes.

The global meat industry has grown substantially, producing 357.39 million tons in 2021, with poultry and pork comprising nearly 73% of this total. However, contamination by mycotoxins, such as zearalenone (ZEA) and fumonisin B1 (FB1), presents a major issue, as these toxins resist common preservation methods. This study explores the potential of bioprotective microorganisms in mycotoxin degradation and fungal control within the animal food production chain, a sector facing significant challenges due to fungal contamination. In this study, 23 bacterial and yeast strains were tested for their ability to degrade ZEA and FB1, and to inhibit mycotoxigenic fungi. Four bacterial strains were highly effective in degrading ZEA: Bacillus amyloliquefaciens MLB3, Bacillus subtilis MLB2, Bacillus velezensis CL197, and Streptomyces griseus CECT 3276. However, no strain achieved satisfactory FB1 degradation. The strains also displayed antifungal activity, inhibiting up to 100% of fungi growth in solid media co-culture tests. Simulated swine and poultry digestion demonstrated complete ZEA degradation after 2 hours of incubation. Metabolite analysis revealed that low-toxicity conjugates were formed. These findings suggest that these bacteria hold significant promise for biotechnological applications in animal production, helping to reduce mycotoxin contamination, improve food safety, and protect both animal and human health.

The Active Distribution Networks (ADNs) are Multi-Input Multi-Output (MIMO) systems with coupled dynamics which cause interactions among the control loops of the Distributed Energy Resources (DERs). This undesired effect lead to performance degradation in the voltage control. To mitigate the effects of these unavoidable coupling, the present paper proposes a systematic design procedure based on the analysis of the interaction's sources. In details, each DER is equipped with a double loop PI to control the active and reactive powers output by the Voltage Source Converter (VSC) which connects the DER to the network's node. Furthermore, to guarantee Ancillary Services (ASs), the two loops are coupled by a simple mechanism of cooperation of the active power to voltage regulation realized by a filtered droop law. To achieve voltage regulation with reduced loop interactions, the PI parameters and the filter's pulse are designed according to a two sequential steps procedure based on the (Internal Model Control) IMC technique. Simulation studies are finally presented to demonstrate that the proposed design method achieves both reduction of the loop interaction and robust voltage control in presence of model parameter uncertainty in the MIMO model.

Currently, a wide variety of velocity profiles are used in motion control. Thus, this paper compares the energy consumption of three parabolic, trapezoidal, and S-curve profiles. We studied the case of using embedded systems since they are a powerful solution to monitor and coordinate the movement of devices and machinery in various industries combined with motion control applications. These integrated systems allow precise and efficient control of motors and actuators through control and feedback algorithms. In addition, we propose an alternative methodology for implementing motion controllers using an Advanced RISC Machine (ARM) microcontroller, which computes the trajectory and the control action in real-time. We conducted an experiment using a linear plant composed of a direct current (DC) motor coupled to an endless screw where a carriage is mounted that can move mechanically along a rail a distance of 1.16m. In addition, a 4096 pulses per revolution (PPR) encoder is connected to the motor to measure position and angular velocity, which compute the distance the carriage has moved in meters. A current sensor is used to assess the energy consumption, and 40 tests for each profile were carried out to compare the energy consumption for the three-motion profiles considering cases with and without load on the carriage.

This study uses Landsat 8 and Digital Elevation Models (DEM) to show the dominant orientations of digital lineaments and morphotectonic features between measured trends and the tectonic evolution of the Upper Guajira, Colombia, in the northernmost region of the South American plate. Data from Landsat-8 and hillshaded images of three Digital Elevation Model (DEM) images with different resolutions (SRTM: 90m, ASTER-GDEM: 30m and Alos-Palsar: 12.5m), were used for the extraction and mapping of morpholineaments, drainage network and morphological features. Lineaments were analyzed by means of north azimuth frequency, length, density distributions, lithological distributions and geochronological periods. Tectonic control was supported by using the digitized geological map created by the Colombian Geological Service (SGC). Lineaments and faults were analyzed through the interpretation of a Riedel shear model as a result of the transtensional/transpressional tectonic arrangement of the Caribbean and South American plates. The directional trends of lineaments and faults indicate two dominant directions: NE-SW and E-W. The azimuth distribution analysis of measured structures and drainage channels show similar trends, except for some differences in the predominant directions of some drainage channels. The similarity in the orientation of lineaments, faults and drainage system highlights the degree of control exerted by underlying structures on the surface geomorphological features. Drainage channel classification illustrates the morphological and neo-tectonic complexity of the region. The extracted lineaments were divided into five geochronological groups based on the main ages of host rock formations according to the Colombian Geological Service (SGC) geological map. From the Cretaceous onward, the lineament azimuth frequency rotates from a NE-SW trend to a prominent E-W direction, which resembles the translation that Caribbean plate has been undergoing since the Cretaceous. Our results confirm that Remote Sensing techniques are reliable and useful to study the morphotectonic of an area and can be applied to zones of difficult access.

Parkinson’s-disease (PD) is an incurable age-related neurodegenerative disease and its global prevalence of disability and death has increased exponentially. Although motor symptoms are the characteristic manifestations of PD, the clinical spectrum also contains a wide variety of non-motor symptoms, which are the main cause of disability and determinants of the decrease in a patient's quality of life. Noteworthy in this regard is the stress on the cardiac system that is often observed in the course of PD, however its effects have not yet been adequately researched. Here, an untargeted metabolomics approach was used to assess changes in cardiac metabolism in the 6-hydroxydopamine model of PD. Beta-sitosterol, campesterol, cholesterol, monoacylglycerol, α-tocopherol, stearic acid, beta-glycerophosphoric acid, o-phosphoethanolamine, myo-inositol-1-phosphate, alanine, valine and allothreonine, are the metabolites that significantly discriminate Parkinsonian rats from sham counterparts. Upon analysis of the metabolic pathways with the aim of uncovering the main biological pathways involved in concentration patterns of cardiac metabolites, biosynthesis of both phosphatidylethanolamine and phosphatidylcholine, glucose-alanine cycle, the glutathione metabolism and plasmalogen synthesis most adequately differentiated sham and Parkinsonian rats. Our results reveal that both lipid and energy metabolism are particularly involved in changes in cardiac metabolism in PD. These results provide insight into cardiac metabolic signatures in PD and indicate potential targets for further investigation.

The linkage between the salt wedge, tidal patterns, and the Magdalena River discharge is established by assessing the ensuing parameters: stratification (ϵ), buoyancy frequency (β), potential energy anomaly (φ), Richardson number (RL), and bottom turbulent energy production (P). The salinity, temperature, density, and water velocity data utilized were derived from MOHID 3D, a previously tailored and validated model for the Magdalena River Estuary. To grasp the dynamics of the river, a flow regime analysis was conducted during both wet and dry climatic seasons of the Colombian Caribbean. The utilization of this model aimed to delineate the estuary's spatial reach, considering flow rates spanning from 2000 to 6500 m³/s across two tidal cycles. This approach facilitates the prediction of the position, stability, and stratification degree of the salt front. Among the conclusions drawn, it is highlighted that: 1. The river flow serves as the principal conditioning agent for the system, inducing a strong estuary response to weather stations; 2. The extent of wedge intrusion and the river discharge exhibit a non-linear, inversely correlation; 3. Tidal waves cause differences of up to 1000 m in the horizontal extent of the wedge; 4. Widespread channel erosion occurs during the rainy season when the salt intrusion does not exceed 2 km; 5. Flocculation processes intensify during the transition between dry and wet seasons; 6. The stability of the salt layering and the consolidation of the FSI-TMZ are contingent upon the geometric attributes of the channel.

To mitigate pyrethroid resistance in mosquito vectors of emerging and re-emerging human pathogens, there is an urgent need to discover insecticides with novel modes of action. Natural alternatives, such as extracts derived from plants, may serve as substitutes for traditional synthetic insecticides if they prove to be sustainable, cost-effective, and safe for non-target organisms. Hemp (Cannabis sativa) is a sustainable plant known to produce various secondary metabolites with insecticidal properties, including terpenoids and flavonoids. The goal of this study was to assess the larvicidal activity of hemp leaf extract on 1st instar mosquito larvae from both pyrethroid-susceptible (PS) and pyrethroid-resistant (PR) strains of Aedes aegypti Another goal was to identify which components of the extracts were responsible for any observed larvicidal activity. We found that methanol extract of hemp leaves induced similar concentration-dependent larvicidal activity against PS (LC50: 4.4 ppm) and PR (LC50: 4.3 ppm) strains within 48 hours. Partitioning of the dried leaf extract between methanol and revealed that full larvicidal activity was restricted to the methanol fraction. Analysis of this fraction by gas chromatography-mass spectrometry and nuclear magnetic resonance showed it to be dominated by cannabidiol (CBD). Larvicidal assays using authentic CBD confirmed this compound was primarily responsible for the toxicity of hemp leaf extract against both strains. We conclude that hemp leaf extracts and CBD have the potential to serve as viable sources for the development of novel mosquito larvicides.

The objective of this research article is to determine if social and cultural capital are factors that cause inequalities in the level of knowledge in civic and citizenship education, between Latin American and European countries. To achieve this purpose, information from the National Study of Civic and Citizen Education -ICCS-, of the International Association for the Evaluation of Educational Achievement -IEA-, of the year 2016, is used. Methodologically speaking, the Educational Production Function -EPF- is estimated and subsequently, the Oaxaca-Blinder decomposition technique is applied to quantify the differences in civic and citizenship education and see how much they are explained by the characteristics of the student and their family. the school, the social and cultural capital. As a main result, educational inequalities were found in favor of European countries, and are due to a greater extent to differences in school resources, between Latin American and European countries, followed by differences in social and cultural capital, therefore, it is the European students who make the best use of and benefit from the differences in school endowments and in social and cultural capital.

Synthesis of nickel oxide nanoparticles (NiO NPs) is a low cost and ecofriendly route that brings great benefits over chemical and physical methods of synthesis. Our approach consisted of using aqueous extracts from treated waste of Manihot Esculenta (Cassava) as reducing, stabilizing and capping agents for the synthesis of NiO NPs. The results proved this approach might be a viable alternative. Extracts were mixed during 30 minutes with Ni(NO3)2.6H2O leading to NPs formation. NiO NPs were characterized through FTIR, XRD, TEM and Raman spectroscopy. NiO NPs showed different shapes and sizes around 5-10 nm in agreement with the particle size calculated by XRD Scherrer equation.

We work with reference to a well-known semiclassical model, in which quantum degrees of freedom interact with classical ones. We show that, in the classical limit, it is possible to represent classical results (e.g., classical chaos) by means a pure-state density matrix.

Antarctica has attracted increasing interest in understanding its microbial communities, metabolic potential, and as a source of microbial hydrolytic enzymes with industrial applications, for which advances in next-generation sequencing technologies have greatly facilitated the study of unculturable microorganisms. In this work, soils from seven sub-Antarctic islands and Union Glacier were studied using a whole-genome shotgun metagenomic approach. The main findings were that the microbial community at all sites was predominantly composed of the bacterial phyla Actinobacteria and Cyanobacteria, and the families Streptomycetaceae and Pseudonocardiaceae. Regarding the xenobiotic biodegradation and metabolism pathway, genes associated with benzoate, chloroalkane, chloroalkene, and styrene degradation were predominant. In addition, putative genes encoding industrial enzymes with predicted structural properties associated with improved activity at low temperatures were found, with catalases and malto-oligosyltrehalose trehalohydrolase being the most abundant. Overall, our results show similarities between soils from different Antarctic sites with respect to more abundant bacteria and metabolic pathways, especially at higher classification levels, regardless of their geographic location. Furthermore, our results strengthen the potential of Antarctic soils as a source of industrially relevant enzymes.

A growing number of studies suggest that SARS-CoV-2 could interfere with homeostatic mechanisms in the lung but the implications of this possible interference have not been fully explored in the literature. In this work, we examine the consequences that can be drawn from this hypothesis according to currently available knowledge. We suggest that one such consequence is the potential disruption of normal ventilation and perfusion of lung regions that may be distant from the infection sites. Loss of ventilation might result in local alveolar hypoxia and contribute to hypoxemia, which in turn could trigger homeostatic responses that enhance blood oxygenation by redistributing pulmonary blood circulation. Sudden changes in perfusion might then lead to the development of hydrostatic edema and eventually to vascular remodeling and inflammation. Therefore, the immune response might not be the only source of the substantial inflammation observed in lung tissues of patients with severe COVID-19, as is often assumed in the literature. The balance between the homeostatic and the immune reaction in each patient could account for the observed heterogeneity of the clinical manifestations of COVID-19.

Automatic emotion recognition using portable sensors is gaining attention due to its potential use in real-life scenarios. Existing studies have not explored Galvanic Skin Response and Photoplethysmography sensors exclusively for emotion recognition using nonlinear features with machine learning (ML) classifiers such as Random Forest, Support Vector Machine, Gradient Boosting Machine, K-Nearest Neighbor, and Decision Tree. In this study, we proposed a genuine window sensitivity analysis on a continuous annotation dataset to determine the window duration and percentage of overlap that optimize the classification performance using ML algorithms and nonlinear features, namely Lyapunov Exponent, Approximate Entropy, and Poincaré’s indices. We found an optimum window duration of 11 seconds and 16 seconds for valence and arousal, respectively, with 50% overlap, and achieved an accuracy of 0.76 in both dimensions. In addition, we proposed a Strong Labeling Scheme that kept only the extreme values of the labels, which raised the accuracy score to 0.92. Under certain conditions mentioned, traditional ML models offer a good compromise between performance and low computational cost. Our results suggest that well-known ML algorithms can still contribute to the field of emotion recognition, provided that window duration, overlap percentage, and nonlinear features are carefully selected.

One of the most important problems in the presence of epidemics and pandemics is an accurate prediction and preparedness. Scholars and experts argue that future pandemics and/or epidemics are almost inevitable events and is not whether next pandemics will happen, but when a new heath emergency will emerge. Epidemiologic models for prediction of Coronavirus Disease 2019 (COVID-19) have shown many limitations because of unpredictable dynamics of the new viral agent SARS-CoV-2 in environment and society. The main goals of this study are twofold: first, the analysis of anthropogenic activities and factors that may trigger pandemic threats; second, the planning of new directions for strategies to reduce risks that a pandemic threat emerges and/or in the initial phase to reduce vast diffusion and negative impact of new viral agents that can generate hazards and problems in public health, environment and socioeconomic systems. In particular, the investigation and understanding of sources and driving factors concerning the emergence and diffusion of new pandemics have critical aspects for strategic actions of forecast, prevention and preparation of effective policy responses to cope with next pandemic crises and health emergencies. Insights here endeavor, whenever possible, to clarify these problems to increase the knowledge of the sources and factor determining the emergence of new viral agents in order to design optimal response policies to face next pandemic diseases similar to COVID-19. .

Artificial intelligence and Quantum science supports path-breaking technologies for main technological change. The investigation goal of this study is to examine their scientific and technological development to explain drivers of these disruptive technologies. Analyses of data, based on publications and patents in quantum science and artificial intelligence, with a technometric model show that that quantum science and technology has a growth rate of 1.07, artificial Intelligence ha a rate of growth of 1.37, whereas the interaction of quantum science and artificial intelligence generates a convergent technological trajectory that has an accelerated rate of growth of 1.58, higher than trends of these technologies taken individually. These findings here clarify one of the fundamental determinants of the evolution of path-breaking technologies that can support decision making of policymakers, technology analysts and R&amp;D managers to direct R&amp;D investments towards fruitful inter-relationships between radical technologies that foster scientific and technological change in knowledge economies.

We describe the development and validation of a HPLC-MS/MS method to assess the pharmacokinetics and tumour distribution of fenretinide, a synthetic retinoid chemically related to all-trans-retinoic acid, after administration of a novel oral nanoformulation of fenretinide, called bionanofenretinide (BNF). BNF was developed to overcome the major limitation of fenretinide: its poor aqueous solubility and bioavailability due to its hydrophobic nature. The method proved to be reproducible, precise, and highly accurate for the measurement of the drug and the mains metabolites. The lower limit of quantification resulted 1 ng/mL. The curve range of 1-500 ng/mL and 50-2000 ng/mL, for plasma and tumor homogenate respectively, was appropriate for the analysis, as demonstrated by the accuracy between 96.8% and 102.4% for plasma and 96.6-102.3% for tumor. The inter-days precision and accuracy determined on quality controls at 3 different levels were in ranges of 6.9%-7.5% and 99.3-101.0% and 0.96-1.91% and 102.3-105.8% for plasma and tumour, respectively.

Optimizing intensive care resources using predicting modeling is paramount for fighting the COVID-19 pandemic. In this paper, we model the admission of COVID-19 patients in intensive care units (ICU) in Colombia using openly available data gathered from 18 March 2020 to 14 October 2020. After an intensive preprocessing of the data, we trained four different machine learning models using four different strategies for handling the imbalanced features. Our findings show that our best model (XGBoost) effectively predicts an Area Under the Curve (AUC-ROC) of 0.94, in line with the state-of-the-art results obtained in other predictive models obtained with medical data.

Origin, mechanics and properties of the Solar System are analysed in the framework of the Complete Relativity theory (by the same author). According to Complete Relativity, everything is relative. Any apparent absolutism (notably invariance to scale of dimensional constants, absolute elementariness, invariance to time) is an illusion stemming from limits imposed by [or on] polarized observers that will inevitably lead to misinterpretation of phenomena (another illusion) occurring on non-directly observable scales or even on observable but distant scales in space or time. If everything is relative, reference frames will exist where particles are planets and where planets are living beings. Earth is, therefore, analysed here in more detail, both as a particle and, as a living evolving being (of, hypothesized, extremely introverted intelligence). The analysis confirms the postulates and hypotheses of the theory (ie. existence of discrete vertical energy levels) with a significant degree of confidence. During the analysis, some new hypotheses have emerged. These are discussed and confirmed with various degrees of confidence. To increase confidence or refute some hypotheses, experimental verification is necessary. Main conclusions that stem from my research and are further confirmed in this paper are: universes are, indeed, completely relative; Solar System is a scaled (inflated, in some interpretations) Carbon isotope with a nucleus in a condensed (bosonic) state and components in various vertically excited states; life is common everywhere, albeit extroverted complex forms are present on planetary surfaces only during planetary neurogenesis; anthropogenic climate change is only a part (trigger from one perspective) of bigger global changes; major extinction events on a surface of a planet are relative extinctions, a regular part of transformation and transfer of life in the process of planetary neurogenesis.

Dance, as a performance activity, is associated with various problems. Among these challenges, sleep disturbances are notably prevalent. This study aimed to explore the potential relationship between sleep characteristics—specifically chronotype and subjective sleep quality—and psychological inflexibility in dance students. This research adopted a cross-sectional design using non-probabilistic sampling. One hundred and fourteen dance students, with a mean age of 23.87 years, participated in the study. Assessment tools included the Acceptance and Action Questionnaire-II, Pittsburgh Sleep Quality Index, and the Composite Scale of Morningness. The results revealed no gender differences in psychological inflexibility or chronotype, although women report poorer sleep quality. Differences emerged in both subjective sleep quality and chronotype when students were grouped according to low, medium, or high levels of psychological inflexibility. Those with low inflexibility, as opposed to those with high inflexibility, report better sleep quality, with no differences observed between medium and high inflexibility groups. Students with high-medium levels of psychological inflexibility showed a higher risk (OR = 6.373 times higher) of experiencing poor sleep quality compared to those with low psychological inflexibility. In terms of chronotype, the low inflexibility group is inclined to be more of a morning type than the medium and high inflexibility groups, with no differences between the latter two groups. Students categorized as having low inflexibility tend to have a longer history of dancing under the guidance of a teacher and dedicate more hours and days per week to rehearsal. The findings are discussed in terms of their educational implications for dance students.

Almost fifty years after the first installations, I identify the main lessons learned from fighting drought and poverty in Africa with direct solar-powered pumps thanks to Father Bernard Verspieren and Mali Aqua Viva. Six main findings and three main recommendations emerge from the present analysis. They are of direct relevance to all Africa’s countries whose population has gone from 438 million in 1977 to 1,308 million in 2019, with about 600 million still having no access to electricity. In place of “awareness campaigns” and extraordinary courses held by international organizations, I recommend to establish national solar energy institutes whose task will include the education of solar energy professionals giving practice-oriented workshops on solar-powered drip irrigation and rainwater harvesting throughout each Africa’s country. Said education will critically include the economic and social aspects of distributed “generation” of energy and water from sunlight and rainfall.

The use of biodegradable materials has a growing field of application due to environmental concerns, however, scientific research on incremental forming using biomaterials is scarce. Thus, this study focuses on the single point incremental forming (SPIF) process applied to a composite sheet that combines a biodegradable thermoplastic matrix (Solanyl) reinforced with natural fibres (flax). The influence of the process parameters on the final geometry is determined, evaluating the effect of the following factors: step depth, wall angle and temperature reached during the process. Additionally, a heated aqueous medium is incorporated which facilitates the formability of the composite sheets. This method is especially useful for materials that have poor formability at room temperature. The benefits of using controlled heat include the reduction of formation forces applied to the plate, improved accuracy due to the reduction of elastic recovery, and the manipulation of the samples remarkably close to the glass transition temperatures. Through this experimental study with the variables analysed, a maximum shaping depth of 310 mm is obtained. These results confirm that the single point shaping used with bioplastic materials is possible and has positive outcomes for incremental forming.

MRI shows in-vivo the three archetypal patterns of CNS volume loss underlying progressive ataxias, namely spinal atrophy (SA), cortical cerebellar atrophy (CCA) and olivopontocerebellar atrophy (OPCA). The MRI-based CNS atrophy pattern was reviewed in 128 progressive ataxias. A CNS atrophy pattern was identified in 91 conditions: SA in Freidreich’s ataxia, CCA in 5 acquired and 72 (24 dominant, 47 recessive,1 X-linked) inherited ataxias, OPCA in Multi-System Atrophy and 12 (9 dominant, 2 recessive,1 X-linked) inherited ataxias. The MRI-based CNS atrophy pattern may be useful for genetic assessment, identification of shared cellular targets, and repurposing therapies or enlargement of drugs indications in progressive ataxias.

Fostering fruitful collaboration between chemistry and physics scholars, the analysis of the differences in the practical approach to single atoms in chemistry and in physics affords a number of conceptual outcomes pointing to a more balanced relationship between chemistry and physics.

The enhanced multi-objective symbolic discretization for time series (eMODiTS) method employs a flexible discretization scheme using different value cuts for each non-equal time interval, which requires a computational cost for evaluating each objective function. Therefore, surrogate models were implemented to minimize this disadvantage. Nevertheless, each solution found by eMODiTS is a different-sized vector, so the surrogate model must be able to handle data sets under this characteristic. Consequently, this work's contribution lies in analyzing the surrogate models' implementation on the time series discretization, where each potential scheme is a real-number different-sized vector. For this reason, the surrogate model proposed was k-nearest Neighbors for regression with Dynamic Time Warping as a distance measure. Results suggest our proposal finds a suitable approximation to the final eMODiTS solutions with a functions evaluation reduction rate between 15% and 95%. However, according to Pareto front performance measures, the proposal Pareto front is competitive compared to the eMODiTS Pareto front, reaching an average Generational Distance (GD) between 0.0447 and 0.0536. Moreover, the average Hypervolume Ratio (HVR) ranges between 0.334 and 0.3891. Finally, our proposal compared against SAX-based methods presents a similar behavior regarding classification tasks and statistical tests.

With a relatively small population, Russia accesses huge oil, natural gas, coal and uranium resources, and hosts advanced nuclear energy, oil and natural gas industries. However, the combined effect of today’s low cost electricity generation via photovoltaic modules, water and wind turbines and similarly low cost storage in Li-ion battery and solar hydrogen obtained via water electrolysis will have a profound impact on Russia’s energy and automotive industries.

From professors overwhelmed by anxiety-driven e-mails from students, through faculty and administrative staff wasting valued time on e-mail minutia, misuse of electronic mail in the academy has become ubiquitous. After a brief overview of the unique features of e-mail communication, this study provides insight and guidelines to plan new educational activities on healthy and productive utilization of e-mail in the academy of the digital era. The overall aim is to prioritize scholarly deep work by focusing on teaching and research work, freeing working time wasted on unproductive use of e-mail.

A quantum time-dependent spectrum analysis, or simply, quantum spectral analysis (QSA) is presented in this work, and it’s based on Schrödinger’s equation. In the classical world, it is named frequency in time (FIT), which is used here as a complement of the traditional frequency-dependent spectral analysis based on Fourier theory. Besides, FIT is a metric which assesses the impact of the flanks of a signal on its frequency spectrum - not taken into account by Fourier theory and let alone in real time. Even more, and unlike all derived tools from Fourier Theory (i.e., continuous, discrete, fast, short-time, fractional and quantum Fourier Transform, as well as, Gabor) FIT has the following advantages, among others: a) compact support with excellent energy output treatment, b) low computational cost, O(N) for signals and O(N2) for images, c) it does not have phase uncertainties (i.e., indeterminate phase for a magnitude = 0) as in the case of Discrete and Fast Fourier Transform (DFT, FFT, respectively). Finally, we can apply QSA to a quantum signal, that is, to a qubit stream in order to analyze it spectrally.

Resistance to therapy and disease progression are the main causes of mortality in most cancers. In particular, the development of resistance is an important limitation affecting the efficacy of therapeutic alternatives for cancer, including chemotherapy, radiotherapy, and immunotherapy. Signaling pathways are largely responsible for the mechanisms of resistance to cancer treatment and progression, and multiple myeloma is no exception. p38 mitogen-activated protein kinase (p38) is downstream of several signaling pathways specific to treatment resistance and progression. Therefore, in recent years, developing therapeutic alternatives directed at p38 MAPK has been of great interest, in order to reverse chemotherapy resistance and prevent progression. In this review, we discuss recent findings on the role of p38, including recent advances in our understanding of its expression and activity as well as its isoforms, and its possible clinical role based on the mechanisms of resistance and progression in multiple myeloma.

The Eliezer and Gray physical interpretation of the Ermakov-Lewis invariant is applied as a guiding principle for the derivation of the special relativistic analog of the Ermakov-Milne-Pinney equation and associated first integral. The special relativistic extension of the Ray-Reid system and invariant is obtained. General properties of the relativistic Ermakov-Milne-Pinney are analyzed. The conservative case of the relativistic Ermakov-Milne-Pinney equation is described in terms of a pseudo-potential, reducing the problem to an effective Newtonian form. The non-relativistic limit is considered as well. A relativistic nonlinear superposition law for relativistic Ermakov systems is identified. The generalized Ermakov-Milne-Pinney equation has additional nonlinearities, due to the relativistic effects.

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

Gestational diabetes mellitus (GDM) is a common complication of pregnancy that adversely affects maternal and offspring health. A variety of risk factors, such as BMI and age, have been associated with increased risks of gestational diabetes. However, in many cases gestational diabetes occurs in healthy nulliparous women with no obvious risk factors. Emerging data suggest that the tendency to develop gestational diabetes has genetic and environmental components. Here we develop a polygenic risk score for gestational diabetes. We further investigate relationships between the genetic architecture of GDM and genetically constructed risk factors and biomarkers. Our results show that genetics can be used as an early screening tool that identifies at-risk at higher risk of GDM before its onset to propose comprehensive monitoring and preventative programs to mitigate the risks.

In the present paper we introduce the concept of orthogonal frames in Krein spaces, prove the independence of the choice of the fundamental symmetry, and from this we obtain a number of interesting properties that they satisfy. We show that there is no distinction between orthogonal frames in a Krein space and orthogonal frames in its associated Hilbert. Furthermore, we characterize frames dual to a given frame, which is a useful tool for constructing examples.

A E. Crassipes is considered a problem in different aquatic ecosystems, due to its abundance could become a solution to design and build economic and efficient treatment plants, and especially for the production of biofuels such as bioethanol. The objective of this research is to design and implement a sustainable development process between phytoremediation and bioethanol production with E. crassipes, evaluating the incidence of chromium adhered to the biomass of this plant in the production of bioethanol. Materials and methods: A system was installed to evaluate the phytoremediation with E crassipes with water loaded with chromium, determining the effectiveness of this plant to remove this heavy metal even if it is alive in a body of water. After this process, we proceeded to bring the biomass loaded with chromium to bioreactors to evaluate the production of bioethanol, assessing three types of biomass, one without chromium adhered and the other two with chromium adhered to its plant structure. There was an impact of the ethanol production of the E crassipes due to the presence of chromium, but this production can be taken into account for the assembly of an integral system of phytoremediation and bioethanol production, making the most of this biomass.

Prior work has suggested that discrimination and immigration-related stress may impede mental health care seeking and utilization among Latinx populations. These effects may be more nuanced as both discrimination and immigration-related stress may increase symptomology, particularly posttraumatic stress disorder (PTSD) and depression. Both symptoms may in turn prompt attempts to seek care. The current study examined the direct effects of discrimination and immigration-related stress on care access, as well as potentially indirect effects with PTSD and depression symptoms as mediators. Interviews and online surveys were completed with 234 Latinx residents of the Midwest assessing everyday discrimination, discrimination in healthcare, PTSD symptoms, depression symptoms, current mental health utilization, and previous unsuccessful attempts to seek care. Direct effects of discrimination and immigration-related stress were largely unrelated to care access variables. Discrimination in healthcare settings predicted both unsuccessful attempts to seek care and current use, but this effect was positive. The indirect effect was largely supported, but only for PTSD symptoms and not depression. Results indicate further investigation is necessary to understand the direct effects of discrimination on care access. Further, discrimination and immigration-related stress may indirectly prompt attempts to seek mental health care.

Background: Telemonitoring systems in cardiology have shown potential in improving chronic cardiovascular disease (CVD) management. This study aims to evaluate the impact of telemonitoring, mainly through mobile applications, on patient outcomes such as self-care, blood pressure control, quality of life, and hospitalization. Methods: We systematically reviewed studies assessing telemonitoring methods for patients with chronic CVD. The analysis included studies from various geographic regions and healthcare settings, focusing on qualitative outcomes without performing a meta-analysis. Results: Telemonitoring was found to aid in maintaining blood pressure and significantly enhance self-care abilities. Improvements in quality of life were observed in some studies, though results varied. Most studies indicated telemonitoring could effectively manage blood pressure and reduce hypertension-related complications. However, the heterogeneity of interventions and outcomes measured across trials posed challenges for a comprehensive meta-analysis. Conclusions: Integrating telemonitoring systems into routine care can significantly improve disease management and patient outcomes for chronic CVD patients. Future research should standardize telemonitoring interventions and outcome measures, conduct long-term studies, and evaluate the cost-effectiveness of these systems. Greater blindness in future randomized controlled trials and more studies on atrial fibrillation are also necessary. Significant potential exists for telemonitoring to improve patient outcomes and assist in managing chronic illnesses.

Abstract: Rhizobia are soil proteobacteria able to engage in a nitrogen-fixing symbiotic interaction with legumes which involves root rhizobial infection and bacterial invasion of new organs formed by the plant in response to the presence of appropriate bacterial partners. This interaction relies on a complex molecular dialogue between both symbionts. Bacterial N-acetyl-glucosamine oligomers called Nod factors are indispensable in most cases for early steps of the symbiotic interaction. In addition, different rhizobial surface polysaccharides, such as exopolysaccharides (EPS), may also be symbiotically relevant. EPS are acidic polysaccharides located out of the cell with little or no cell association that carry out important roles both in free-life and in symbiosis. EPS production is very complexly modulated and, frequently, co-regulated with that of Nod factors, but the type of co-regulation varies depending on the rhizobial strain. Many studies point out a signalling role of EPS-derived oligosaccharides in root infection and nodule invasion but, in certain symbiotic couples, EPS can be dispensable for a successful interaction. In summary, the complex regulation of the production of rhizobial EPS varies in different rhizobia and the relevance of this polysaccharide in symbiosis with legumes depends on the specific interacting couple.

Large-scale integration of solar energy technologies in Rome’s built environment epitomizes the needed general adoption of distributed generation via functionalization of buildings of all size and end use across the world, to become active energy generators and no longer energy users only. This paper identifies selected technology solutions and critical policy and educational initiatives to effectively achieve within the next decade (2018-2027) the widespread uptake of decentralized solar energy systems in the built environment on a global scale.

Objective: To determine the association of edentulism with different chronic diseases in Mexicans aged 60 years and over. Material and Methods: A cross-sectional study was carried out using data from the World Health Survey for Mexico, which had a probabilistic, multi-stage and cluster sampling. The results of the self-report of chronic diseases (diabetes, arthritis, depression, angina pectoris, asthma and schizophrenia) and of edentulism were analyzed. Dental data were available for 20 of the 32 States of the Mexican Republic. Statistical analysis was performed in Stata 14.0 using the svy module for complex samples. Results: In total, 4213 subjects were included, representing a population of 7,576,057 individuals. The mean age was 70.13 ± 7.82 years (limits 60 to 98). Women represented 56.2%. The chronic diseases analyzed were presented as follows: diabetes 15.0% (N = 1,132,693); arthritis 13.2% (N = 1,001,667); depression 5.5% (N = 414,912); angina pectoris 4.5% (344,315); asthma 3.6% (N = 269,287); and schizophrenia 2.2% (N = 16,988). The prevalence of edentulism was 26.3%, which represents 1,993,463 people aged 60 years and over with this characteristic. For the presence of angina in women aged 60 to 69 years (p &lt;0.05) and depression in men aged 70 years and over (p &lt;0.0001), a higher prevalence of edentulism was observed. Conclusions: In general, there was no observation of association between edentulism was observed on the different chronic diseases included in the study. In the stratified analysis, only in women aged 60 to 69 years, for angina, and in men aged 70 and over, for depression, were associated.

The corneal epithelium (CE) is spread between two domains, the outer vascularized limbus and the avascular cornea proper. Epithelial cells undergo constant migration from the limbus to the vision-critical central cornea. Coordinated with this migration the cells undergo differentiation changes where a pool of unique stem/precursor cells at the limbus yields the mature cells that reach the corneal center. Differentiation is heralded by the expression of the corneal-specific Krt12. Processing data acquired by scRNA-Seq we found that the increase of Krt12 expression occurs in four distinct steps within the limbus plus a single continuous increase in the cornea. Differential gene analysis demonstrated that these domains reflect discreet stages of CE differentiation and yielded extensive information of the genes undergoing down or up regulation in the sequential transition from less to more differentiate conditions. The approach allowed the identification of multiple gene cohorts, including a) the genes that have maximal expression in the most primitive, Krt12-negative cell cohort, which is likely to include the stem/precursor cells; b) the sets of genes that undergo continuous increase or decrease along the whole differentiation path, and c) and the genes showing maximal positive or negative correlation with the changes in Krt12.

When there is uncertainty in the value of parameters of the input random components of a stochastic simulation model, two-level nested simulation algorithms are used to estimate the expectation of performance variables of interest. In the outer level of the algorithm (n) observations are generated for the parameters, and in the inner level (m) observations of the simulation model are generated with the value of parameters fixed at the value generated in the outer level. In this article, we consider the case in which the observations at both levels of the algorithm are independent, showing how the variance of the observations can be decomposed into the sum of a parametric variance and a stochastic variance. Next, we derive central limit theorems that allow us to compute asymptotic confidence intervals to assess the accuracy of the simulation-based estimators for the point forecast and the variance components. Under this framework, we derive analytical expressions for the point forecast and the variance components of a Bayesian model to forecast sporadic demand; and we use these expressions to illustrate the validity of our theoretical results by performing simulation experiments using this forecast model.

The number of children diagnosed with autism spectrum disorder (ASD) has increased substantially over the past two decades with current research unable to fully account for this dramatic increase in prevalence. One explanation proposes that both intrinsic (e.g., genetic) and extrinsic (e.g., environmental) risk factors may be involved in the etiology of ASD. The goal of this review paper is to explore modifiable pathways for intervention in children at risk for ASD, specifically examining how early social experience may be correlated with epigenetic change in genes associated with autism. We present an innovative model which proposes that polygenic risk and social experience (via epigenetic mechanisms) may both contribute to the observed ASD phenotype. Previous research on genetic, environmental, and epigenetic mechanisms implicated in the etiology of ASD will be reviewed, with an emphasis on the oxytocin receptor gene, which is epigenetically altered by early social experience, plays a crucial role in mammalian social and cognitive development, and is associated with both genetic and epigenetic risk for ASD. Identifying intrinsic (e.g., genetic) and extrinsic (e.g., social experience) risk markers for ASD, a combination of which has not previously been examined, would transform our understanding of this condition, facilitate earlier identification of ASD risk, and guide early intervention efforts. This may have a far-reaching impact on individuals with ASD, their families, and society.

There is an urgent need to develop new therapies for cancer treatment due to high rates of resistance and tumor relapse. Moreover, chemotherapy and radiation weaken the immune system and leave patients susceptible to sudden death from infections and organ failure since antineoplastic drugs lack specificity. Hence, scientists worldwide continue the search for natural alternatives with anticancer activities and fewer side effects. In this regard, traditional medicine offers strategies for preventing and treating numerous diseases and nowadays scientific studies worldwide highlight some of the mechanisms underlying their potential as an effective alternative for the management of cancer. In Mexico, Mayan healers have been prescribed mainly medicinal plants for more than 2,000 years. Furthermore, their ethnomedical knowledge has led to drug discovery or the development of herbal remedies. Medicinal plants from the genus of Cissus remain an important element of all indigenous medical systems in Mexico including the Mayan tribes in Yucatan, particularly for the management of gastrointestinal illnesses, sores, cutaneous diseases, and tumors. In this review, we present the reported bioactivities against cancer cells of the extract and compounds from the species of Cissus with a particular focus on recent studies on the phytochemistry of C. trifoliata which is widely distributed in Mexican territory and used for tumor management in traditional medicine.

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

(1) Background: Ulcerative colitis (UC) is characterized by immune system dysregulation with frequent extraintestinal manifestations, including airways involvement. Reduction in CO diffusing capacity and functional alterations in small airways have been described. The extended analysis of Fractional Exhaled Nitric Oxide (FeNO), may distinguish the sites of production and the presence of small airways inflammation being a useful, non-invasive marker for these patient’s follow up. The aim of our study was to compare PFTs, FeNO and CANO values of UC patients with different clinical disease activity and healthy subjects to reveal lung function abnormalities and the presence of subclinical airway inflammation. (2) Methods: We enrolled 42 adult outpatients with different clinical activity stages of UC (mean age 39±13 years) and a healthy control group of 41 subjects (mean age 29±3 years). C-reactive protein (CRP) and FeNO values at different flows (50,100 and 200 ml/sec) were collected. All patients performed pulmonary function tests (PFT’s) with static volumes and diffusing capacity (DLCO). (3) Results: FENO, CANO and CRP values were significantly increased in UC patients when compared with controls (p=0.02 and p&lt;0.0001, respectively) and proportionally to the disease activity (FeNO class 3: 27.1 ppb vs class 1-2: 6.2 ppb; CANO values class 3: 8.1 ppb vs class 1-2: 2.0 ppb (p &lt; 0.0001). TLC and DLCO were significantly reduced in UC patients compared to controls (p=0.011 and p&lt;0.0001, respectively). (4) The results of this study show significant lung functional abnormalities in UC patients and suggest the presence of airway inflammation directly correlated with the disease activity suggesting an integrated approach in routine assessment.

Over the last decade, advances in our understanding about the genetic architecture of complex traits and common diseases, have increased our ability to perform susceptibility genetic testing for diseases in asymptomatic individuals. These technological developments raise complex ethical, legal and social considerations. Here we discuss a series of ethical issues associated with susceptibility genetic testing for Alzheimer's and Parkinson's disease. These include, amongst others, informed consent, disclosure of results and unexpected findings, mandatory screening, privacy and confidentiality, and stigma and genetic discrimination. As knowledge of the genetic basis of these diseases continues growing, and as genetic testing becomes more widespread, we anticipate that it will become increasingly important for scientists and clinicians to engage in the conversation about the ethical, social and policy implications of these technologies.

Given the importance of the development of urban infrastructure and environmental impacts produced by the civil construction waste (CCW), it is important to correct the handling of CCW with objective solutions that are more environmentally friendly. In that sense the present study aimed to determine indicators that make it possible to estimate the amount of CCW generated from construction sites in the city of Londrina, Parana State, Brazil. The generation of CCW was estimated in a general way, regarding the composition of its mixture, correlated to the gross areas of the buildings studied and their generated volumes of RCC. This generating rate was evaluated in a general way and specifies two types of sites: the new residential and new non-residential constructions. The data required for the development of these indicators was obtained through extensive survey and interviews carried out at the environment secretariat of the City Hall. The generating rate of CCW obtained for non-residential buildings was 0.2052m3/m2 or 170.44kg/m2, for new residential sites was 0.2054m3/m2 or 170.60kg/m2 and for new commercial or non-residential construction sites, it was 0.20453 m3/m2 or 169.85kg/m2. It was also possible to estimate the amount generated annually per inhabitant in the municipality, which is 0.60m3/inhabit.year or 498.55kg/inhabit.year.

Clinical training in medical schools in Spain is performed by rotations in university hospitals. During these internships, students are expected to acquire and master basic procedural skills. However, the assessment tools available rarely check whether these skills are completely acquired by the students. We have used an e-portfolio to determine the optimal number of times the students need to repeat a procedure to be able to perform it independently. The results were compared with the actual performance during the internships. An e-portfolio collected qualitative information about the internships. Quantitative information was also requested about the number of times each clinical skill was performed. Later, a survey asked these students and their teachers the optimal number of times each skill should be repeated before it could be considered fully acquired. The questionnaire was answered by 98.6% of the students and 70.3% of their teachers. Out of the 21 clinical skills and procedures selected, both students and their tutors agreed in a similar optimal value in 16 of them; only in five of them, teachers thought that students needed a greater number of times than that selected by the students. When these optimal values were compared with the actual values recorded in the portfolio during the internships, it was found that about half of the clinical skills were carried out less frequently than expected, thus providing an important feedback about the internships. Quantitative information collected in portfolios reveals a moderate mismatch between students and tutors perceptions of their training needs.

An impaired healing response underlies diabetic foot wounds chronicity, frequently translating in amputation, disability, and early mortality. In addition, diabetics frequently suffer of the underappreciated episode of post-epithelization ulcer recurrence. Recurrence epidemiological data are alarmingly high; so that the ulcer is considered in “remission” and not healed for the time it remains epithelialized. Recurrence may result from the conspiracy of behavioral and biological factors. Although the damaging role of behavioral, clinical predisposing factors is undebatable, the role of endogenous biological signalers that prime the residual scar tissue to recurrence has remained elusive. We propose that ulcer recurrence is deeply impinged by chronic hyperglycemia and its downstream biological effectors, which originate epigenetic drivers that enforce abnormal pathologic phenotypes to dermal fibroblasts, and keratinocytes as memory cells. Hyperglycemia-derived cytotoxic reactants accumulate and modify dermal proteins, reduce scar tissue mechanical tolerance, and disrupt fibroblasts-secretory activity. Accordingly, the combination of epigenetic and local and systemic cytotoxic signalers, induce the onset of “at-risk phenotypes” as premature skin cells aging, dysmetabolism, inflammatory, pro-degradative, and oxidative programs that may ultimately converge to scar cells demise. Unfortunately, post epithelialization recurrence rates data are missing in clinical studies of accepted ulcer healing therapies during follow-up periods. Intra-ulcer infiltration of epidermal growth factor exhibits the most consistent remission data with the lowest recurrences during 12-month follow-up. Recurrence data should be regarded as a valuable clinical endpoint during the investigational period for each emergent healing candidate.

Mandarins occupy the third group among citrus produced in Brazil. Primarily aimed at the fresh fruit market, commercial orchards have suffered significant losses in production, due to the high incidence of diseases, such as alternaria brown spot (ABS) and huanglongbing (HLB). The fact that 80% of the orchards are composed of two varieties, Ponkan mandarin and Murcott tangor, are highly susceptible to both diseases, demand intensive chemical control of the diseases in the field, which has resulted in a significant increase in production costs and a negative environmental impact. A total of one hundred and seventy-three mandarin accessions, including several species and hybrids, belonging to the Collections of the Instituto Agronômico de Campinas (IAC), were evaluated in the field, in an endemic location for the diseases. Evaluations of the incidence and severity of the diseases showed that there is a range of genotypes tolerant to ABS with potential to replace the current commercial varieties, mainly within the clementina and Willow leaf mandarin groups. Although with differences in incidence and susceptibility to HLB, there are no varieties tolerant to this disease, which significantly impacts the loss of fruit quality.

The combined influence of the North Atlantic Oscillation (NAO) and the East Atlantic (EA) patterns on the covariability of temperatures and precipitation in 35 stations of the Iberian Peninsula during the period 1950-2019 is analysed in this work. Four EA-NAO composites were defined from teleconnection patterns positive and negative phases: EA+NAO+, EA+NAO-, EA-NAO+, and EA-NAO-. Daily data of maximum and minimum temperature were used to obtain seasonal means (TX, and TN, respectively), and the covariability of these variables with accumulated seasonal rainfall (R) was studied comparing results obtained for different NAO and EA composites. Main results indicate slight differences in the spatial coverage of correlation coefficients between R and temperature variables, except in spring when the generalized negative relationship between R and TX under EA+NAO+ and EA-NAO- disappears under EA-NAO+ and EA+NAO- composites. This result may be useful to interpret and discuss historical reconstructions of Iberian climate.

One of the main problems for managing global crises is to clarify and reduces drivers of systemic weaknesses to face complex emergencies. This study here analyzes the relation between public debt, healthcare expenditures and fatality rates in the presence of pandemic crises, such as COVID-19. Statistical evidence, based on a sample of European countries, here shows that high public debt over time reduces health expenditures and increases the vulnerability of countries to face emergencies, such as COVID-19 pandemic crisis. Regression analysis with a log-log model suggests that when European countries experience a 1% increase in healthcare expenditure per capita, in general they have a 1.2% reduction in the COVID-19 fatality rate. Main implications of this study to reduce the systemic risk and vulnerability to environmental threats are that countries must reduce public debt with good governance and institutions without reducing the allocation of economic resources to the healthcare sector in order to improve the preparedness to unforeseen emergencies and crises, such as pandemics, natural disasters, conflicts, and other environmental threats.

Rice cultivation stands as a cornerstone of Sri Lanka's economy, serving as a vital source of em-ployment for rural communities. However, the constraints of limited land availability have prompted an escalating dependence on agrochemicals, notably for pest management, thereby posing significant threats to human health and the environment. This review delves into the ex-ploration of silica nanoparticles as a promising eco-friendly substitute for conventional pesticides in the context of Sri Lankan rice farming. It comprehensively examines various aspects including the synthesis methods of silica nanoparticles, their encapsulation with synthetic pesticides, and an evaluation of their efficacy in pest control. Furthermore, it sheds light on the innovative utilization of agricultural waste such as rice husk and straw in the production of silica-based nano-pesticides. This approach not only demonstrates a shift towards sustainable agricultural practices but also aligns with the principles of green chemistry and circular economy, offering a holistic solution to the challenges faced by the rice farming sector in Sri Lanka.

Several review articles about megachurch studies have been published recently concentrating their work on USA, Europe, and other parts of the world, with just a few references about Latin American megachurches. For that reason, this article aims to identify some of the characteristics of Latin American Evangelical megachurches by looking at relevant literature, especially that produced in the region, in Spanish and Portuguese, which is usually overlooked by researchers in Global North. Since this research field is still limited in Latin America, areas, where further work is necessary, are identified. Three general catalysts for the emergence of megachurches in the region, church growth methodologies, Pentecostalization, and theologies of growth, serve as guides to organize the review process. The discussion shows several potential areas of research in a variety of fields such as theology, ecclesiology, organizational theory, leadership, gender studies, and ethics, are proposed from the review.

In this review we aim to address the current status of phage therapy in the management of multidrug-resistant infections, from compassionate use cases to ongoing clinical trials, as well as the challenges this approach presents in the particular context of CF patients.

Driven by the rapid uptake of battery electric vehicles, Li-ion power batteries are increasingly reused in stationary energy storage systems, and eventually recycled to recover all the valued components. Offering an updated global perspective, this study provides a circular economy insight on lithium-ion battery reuse and recycling.

Alternaria brown spot (ABS) is a disease caused by the fungus Alternaria alternata f. sp. citri, which results in lesions on fruits, leaves, and branches of several mandarin varieties and their hybrids. Due to the high cost of fungicide application, alternative methods for controlling ABS need to be studied. Therefore, this study aimed to evaluate the use of essential oils (EOs) from different mandarin varieties to mitigate the effects of ABS. The inhibitory effect of different concentrations (1, 2, 4, 8, and 16 μL mL-1) of Fremont IAC 543 mandarin, IAC 2019Maria mandarin, Murcott IAC 221 tangor, and Late IAC 855 willowleaf. EOs on the in vitro mycelial growth of the fungus A. alternata was evaluated. Additionally, the curative and preventive effects of these EOs on ABS symptoms on detached leaves of Murcott IAC 221 tangor were also assessed. The EO of IAC 2019Maria mandarin induced less mycelial growth, and consequently, greater inhibition of the growth of the fungus A. alternata at a concentration of 16 μL mL-1. This EO was more effective in control than the other oils tested. In the detached leaf experiment, both the curative and preventive treatments at a concentration of 16 μL mL-1 showed lower values of disease severity.

Cloud platforms are widely employed in today's educational context to enhance collaborative learning and the overall quality of the teaching-learning process. In 2016, Nextcloud was im-plemented in the Faculty of Chemical Engineering at the Technological University of Havana "José Antonio Echeverría" (CUJAE), Cuba. Subsequently, an evaluative phase was conducted to ensure the continuous development of the platform. The objective was to assess the use and ac-ceptance of the Nextcloud platform from the perspective of students and professors in the Fac-ulty. An exploratory, non-experimental, and cross-sectional study was conducted. Data was col-lected through observation and a survey. Matomo Analytics tool was employed for observation, revealing low visitation numbers. The survey was based on the Unified Theory of Acceptance and Use of Technology model. Better results were obtained in positive acceptances compared to negative ones, both for professors and students. It is concluded that the evaluation of the Next-cloud platform is infrequently used by users; however, there were higher positive acceptances than negatives from the perspectives of both students and professors.

Background: Melatonin is a potent mitochondrial, cytoprotective and antioxidant molecule with potentially strong anti-aging properties. Topical melatonin has shown to improve the clinical signs of skin aging. Melatosphere™ is a new lipid-based delivery system able to improve stability and skin penetration of melatonin when used in topical formulations. No clinical studies, using objective instrumental data, are available so far regarding the positive effect of Melatosphere™ in improving wrinkles in women with mild-to-moderate skin aging. Study Aim: We evaluate, in an open prospective, evaluator-blinded trial, the effects on skin texture of 2 months treatment with a Melatosphere™ based cream. Subjects and Methods: 15 women aged >45 years with mild to moderate facial skin aging (Glogau score ≥2) participated in the trial, after their informed consent. An ANTERA 3D computer-assisted skin analysis evaluation for the assessment of coarse and fine wrinkles of the periorbital area and melanin content was performed at baseline and after two months of treatment. An evaluator-blinded Investigator Global assessment of skin elastosis, roughness, level of dyscromia, skin dryness and presence of actinic damage was also performed at the same time points using a 4-grade score from 0 (no sign) to 3 (severe sign). Results: At baseline the mean (SD) IGA score was 8.2(1.0). After 2 months the IGA score significantly decrease to 4.2(1.4) (49% reduction) (P=0.0007). ANTERA 3D evaluations showed a significant reduction in skin coarse and fine wrinkles volume in the target area of -31% and -18%, respectively. Melanin content was reduced significantly by -17%. Conclusion: Topical melatonin carried in Melatosphere improves in the short-term signs of skin aging evaluated clinically and by ANTERA 3D device in women with mild to moderate skin aging.

Single Image Super Resolution (SSIR) is a problem in computer vision where the goal is 1 to create high-resolution images from low-resolution ones. It has important applications in fields 2 such as medical imaging and security surveillance. While traditional methods such as interpolation 3 and reconstruction-based models have been used in the past, deep learning techniques have recently 4 gained attention due to their superior performance and computational efficiency. This article proposes 5 an Autoencoder based Deep Learning Model for SSIR, in particular, a light model that uses fewer 6 parameters without compromising performance. The down-sampling part of the Autoencoder 7 mainly uses 3 by 3 convolution and has no subsampling layers. The up-sampling part uses transpose 8 convolution and residual connections from the down sampling part. The model is trained using a 9 subset of the VILRC ImageNet database. The model is evaluated using quantitative metrics PSNR, 10 SSIM as well as qualitative measures such as perceptual quality. PSNR and SSIM figures as high as 11 76.06 and 0.93 are reported.

The use of medicinal plants for the therapy of diseases of the digestive system; where the Andean peoples developed various forms of administration. The objective being the identification of medicinal plants used in the therapy of ailments of the digestive system by the Andean inhabitants of Pampas, Tayacaja, Huancavelica, Peru. Methods, non-probabilistic sampling, using the “snowball” technique, carrying out semi-structured surveys, allowing information to be collected on the prevalence of ailments or diseases of the digestive system treated with medicinal plants, with inhabitants over 20 years of age participating and using the medicinal plants in the therapy of your digestive system ailments; and, exclude those inhabitants who do not comply with it. Results, 16 families, 33 genera and 34 species are reported; where the families that present the greatest abundance of species are Asteraceae, Lamiaceae; Likewise, the widely used species are Minthostachys mollis (11.9%), Aloe vera (10.4%), Clinopodium bolivianum (9%), Artemisia absinthium (9%) and Matricaria chamomilla (8.2%). Concluding with the identification of a diversity of medicinal flora, used in the therapy of diseases of the digestive system, such as stomach pain, constipation, gallbladder ailments, gastritis, gastrointestinal and liver diseases.

The progressive impairment analysis in gait from neurological diseases patients such as Hereditary Ataxias (HA) has been carried out using gait data collected with movement sensors. This research is focused on finding the minimum amount required of gait features to recognize efficiently and less intrusive way, HA patients based on data collected with iPhone movement sensors placed on the ankles from 14 HA patients and 14 healthy people. A twofold proposal is made , first a local minimum prominent peak criterion to find out the starting point of each stride, to get 10-stride window about which 56 spatial-temporal features are derived; second a search strategy based on Hill Climbing algorithm to reduce the number of gait features and sensors. The main results were the findings that with two gait patterns a 96% of classification accuracy was achieved by using K-Nearest Neighbors (KNN) and Multi-Layer Perceptron (MLP) algorithms, but in addition, MLP only right ankle sensor patterns were required which also allows to reduce the intrusion.

Solar green roofs, namely rooftops functionalized with properly selected living vegetation and photovoltaic modules, achieve an ideal symbiotic relationship in which promotion of biodiversity and onsite renewable energy production are both enhanced whereas the roof provides a wide range of environmental, health, aesthetic and economic benefits. This study provides a unified outlook of this eminent sustainable technology at the dawn of its uptake across the world, especially in polluted urban areas.

Objectives We tested the hypothesis that poor adherence is associated with a greater risk of alcohol-caused mortality and morbidities within the first year of discontinuing this medication. Materials and Methods Retrospective cohort study of 3319 individuals who received Acamprosate® in the East of Scotland in a 10-year period using a health informatics approach with record linkage of dispensing data, hospital utilization (SMR) and General Register Office of Scotland (GROS) data. Primary outcome was adherence between one to six months of initiating Acamprosate® medication. Secondary outcome was all cause morbidities and mortality. Results Of the total 3319 individuals identified, good adherence index of >80% was found in 59% of those prescribed Acamprosate® after three months and 6% after six months. There were significant linear trends of poorer adherence with increased risk of alcohol-caused mortality (HR1.2), medical morbidities especially neoplasm (HR 4.1|) and poisoning (HR 1.4) and psychiatric morbidities especially stress (HR 35.1), psychotic (HR 5.6) and neurotic disorders and directly alcohol induced conditions (7.4 HR) after adjustment for other factors within a one-year period of initiation of Acamprosate® treatment. Discussion and Conclusions Further exploratory studies using this digitalized approach should be encouraged in order to capture role of compliance to Acamprosate® and other types of medication that are known to reduce relapse into alcohol dependence and its direct relationship to mortality and morbidities in this population.

The present paper explored the possibility of discriminating between different malignant degrees of Chondrosarcoma (CS), a diffused bone tumor, and Enchondroma (EC), its benign version, through an approach based on the coupling between Confocal Raman Microscopy (CRM) and Machine Learning (ML) techniques. Recently, Raman Spectroscopy has proven to be a powerful tool for a complete grading of CS by distinguishing between grade 1, 2 and 3, and to distinguish CS from EC. In this paper, we tested some models, belonging either to ML or to the sub-type called Deep Learning (DL), showing excellent classification performances, especially the DL algorithms, with classification accuracy approaching to 100%, making the models promising for future implementations of Raman spectroscopy when applied to oncology diagnosis. In turn, we highlighted how some proper ML models result in worse classification performances but better resolution of specific chemical target compounds, possible candidate to become malignant markers, with relevant implication for a correct diagnosis.

The vehicular ad hoc network (VANET) when augmented with internet is called internet of vehicles (IoV). In the IoV, vehicles have on board units (OBUs), use communication technologies and customized software to communicate with infrastructure around them. The vehicles can have permanent connectivity and global network awareness based on cloud computing. IoV technologies are still being assessed to ensure that the network is protected from attacks, supports a dynamic vehicular mobility scenarios and meets the low latency communication requirements between the vehicles and the surrounding infrastructure. To meet these strict Quality of Service (QoS) demands, Unmanned Aerial Vehicles (UAVs) play a vital role in IoV ecosystems. An UAV can serve as a mobile roadside unit (mRSU) to transmit data between vehicles, stationery RSUs and other UAVs. The UAVs have better line of sight (LOS) connections which result in better channel states and lower path loss than fixed RSUs. Although the inclusion of UAVs in vehicular networks has improved the system performance by providing better resource management and routing solutions, the traditional optimization techniques with their limitations are often not applicable. Therefore, in recent years, research community is integrating Artificial Intelligence (AI) and Machine Learning (ML) into UAV based IoV ecosystem to better manage resource allocation, routing and mobility management issues to optimize the overall network performance. In this survey paper we review the existing research done in AI/ML based UAV-IoV networks and communications with focus on resource management and routing from year 2019 to 2023. We have studied different AI techniques, their training attributes and architectures in various research works. The limitations of AI-based approaches in terms of required computational resources, availability of real world data and AI models’ complexity for the UAV-IoV environment are also discussed. Finally, the future directions for UAV-IoV research opportunities that can leverage the full potential of AI are presented.

The discovery of more bioactive compounds for non-invasive administration has been the goal of research groups focused on pharmacotherapy. Phytonutrients have always been attractive for researchers because they are a significant source of bioactive phytochemicals, but it is challenging to determine which components show high biomedical activity. However, based on the chemical structure of these active compounds, their physicochemical properties can be calculated to predict the probability of gastrointestinal (GI) absorption after oral administration. Indeed, different researchers have proposed several rules (e.g., Lipinski's, Veber's, Ghose's, and Muegge's rules) to attain these predictions for synthetic compounds. Most phytochemicals do not fully comply with these rules even though they show high bioactivity and high GI absorption experimentally. Here, we provide a detailed methodology using web-based platforms to determine the physicochemical properties of five phytochemicals in the phytonutrients ginger, echinacea, and tobacco. Furthermore, we analyzed the calculated data and established a protocol based on the combination and integration of these rules, plus other extended parameter ranges, to reliably predict the GI absorption of natural compounds. The presented data and methodology can be beneficial for evaluating bioactive natural compounds as potential drug candidates and predicting their oral bioavailability in patients.

Hydroxychloroquine, a known antiviral metabolite of chloroquine, is increasingly used along with antibiotic azithromycin for the treatment of COVID-19 infection. In about one month India, the world’s largest manufacturer, delivered hydroxychloroquine for treating COVID-19 to over 50 countries. The therapy is being used across the world both for patients staying at home at the early phase of symptoms, as well as for patients hospitalized. We summarize achievements as of late April 2020, review possible modes of action and suggest avenues for the quick scale-up of production of hydroxychloroquine.

In the field of forensic imaging, it is important to be able to extract a “camera fingerprint” from one or a small set of images known to have been taken by the same camera (image sensor). Ideally, that fingerprint would be used to identify an individual source camera. Camera fingerprint is based on certain kind of random noise present in all image sensors that is due to manufacturing imperfections and thus unique and impossible to avoid. PRNU (Photo-Response Non-Uniformity) has become the most widely used method for SCI (Source Camera Identification). In this paper, we design a set of “attacks” to a PRNU based SCI system and we measure the success of each method. We understand an attack method as any processing that alters minimally image quality and that is designed to fool PRNU detectors (or, generalizing, any camera fingerprint detector). The PRNU based SCI system was taken from an outstanding reference that is publicly available.

The natural distribution of stress in the femur is altered when total hip arthroplasty (THA) is performed. In fact, when a stem is inserted inside the femur, there is a variation in stress due to the difference in rigidity between the material with which the stem is made and the femur. This generates the phenomenon of stress-shielding. The aim of this study is to design an optimized prosthesis that guarantees excellent rotational stability and re-duced stress shielding. Methods: through the finite element method (FEM) the mechanical behavior of the stem subjected to the loads described by ISO 7206-4: 2010 is studied. Re-sults: Through topological optimization, there is a reduction in stress shielding in the proximal zone of 31.46%. The addition of ridges on the dorsal side of the stem also im-proves rotational stability by 27.82%. Conclusions: The decrease in stiffness that is rec-orded with the optimized stem, guarantees a greater distribution of stress on the bone. The presence of dorsal ridges also favors the corticalization of the bone as it loads the bone near the dorsal ensuring further stability. The perforated prosthesis presented in this study, shows an increase in primary stability and an improvement in rotational stability. As there is also a bone regrowth inside the prosthesis.

Peri-implant diseases are defined as pathological inflammatory reactions in the tissue surrounding the osseointegrated implants. They are classified into two categories: mucositis - defined as peri-implant soft tissue inflammation and peri-implantitis - bone loss in the peri-implant region. A clinical case of a 61-years-old woman with an implant in the 46 anatomical position and a 5-year follow-up is presented. A probe depth of 5mm and a bone defect length of 35% was observed. The Implacure® Protocol was applied, with the main objective of eliminating the biofilm present on the exposed implant surface. There are multiple approaches to treat peri-implant diseases. While non-surgical treatment is essential for mucositis control, the treatment of peri-implantitis surgical treatment should be considered. Regenerative bone reconstruction promotes bone repair in the defect area and reduces bleeding during probing. To achieve that, autologous fibrin combined with Cerasorb M® was used. The proposed approach in the exposed clinical case involves the application of Implacure® Protocol, whose combination of the physical decontamination technique, together with the use of chlorhexidine and orthophosphoric acid, added with the combination Piperacillin + Tazobactam together with hyaluronic acid, provide a base that allows to regenerate bone using platelet-rich fibrin with Cerasorb M® and increase the survival time of the implant.

A proposed interpretation of the characteristics and causes of the variation in science dynamics for technological evolution is described. The theoretical approach focuses on variability in research topics that guide scientific and technological evolution. Statistical method verifies the proposed approach by applying entropy, measures of dispersion and variance decomposition. The statistical evidence, using data of four main research fields in quantum technologies, suggests the following empirical properties: a) the growth of heterogeneity in research topics is inversely proportional to the age of research fields: recent research fields have a higher variability between topics with uncertainty in evolutionary dynamics, whereas older research fields have a lower variability and more concentration in specific research topics with stable evolution towards clear directions; b) the nature of research fields has a systematic effects in variability guiding the evolution of technologies. The theoretical approach and findings clarify main characteristics and causes of the evolution of science and technologies considering the underlying homogeneity or heterogeneity in research topics, providing main implications to improve the scientific and technological forecasting that may support appropriate R&amp;D investments towards promising research fields and technologies

True randomness is necessary for the security of any cryptographic protocol, including quantum key distribution (QKD). In QKD transceivers, randomness is supplied by one or more local private entropy sources of quantum origin, which can be either passive (e.g. a beam splitter) or active (e.g. an electronic quantum random number generator). In order to understand better the role of randomness in QKD we revisit the well-known "detector blinding" attack on BB84 QKD protocol, which utilizes strong light to achieve an undetectable and complete recovery of the secret key. We present two findings. First, we show that the detector blinding attack is in fact an attack on the receiver’s local entropy source. Second, based on this insight, we propose a modified receiver station and a statistical criterion which together enable robust detection of any bright-light attack and thus restore security.

Preprints are regularly cited in peer reviewed journal articles, books and conference paper. Are preprint citations somehow less important than citations to peer reviewed research papers? This study investigates citation patterns between 2017 and 2020 for preprints published in three preprint servers, one specializing in biology (bioRxiv), one in chemistry (ChemRxiv), and another hosting preprints in all disciplines (Research Square). As evaluation of scholarship continues to largely rely on citation-based metrics, this analysis and its outcomes will be useful to inform new research-based education in today’s scholarly communication.

In most world’s countries, scholarship evaluation for tenure and promotion continues to rely on conventional criteria of publications in journals of high impact factor and grant funding. Continuing to hire and promote scholars for their achievements in research and in securing research funds exposes universities at risk because students, directly and indirectly through government funds, are the main source of revenues for academic institutions, whereas talented young researchers are those who actually carry out most of the published research. Purposeful scholarship evaluation needs to include all three areas of scholarly activity: research, teaching and mentoring, and service to society. Young scholars seeking tenure and promotion benefit from the practice of open science because it provides better and more impactful results with respect to each of the three areas of scholarship.

In the digital era in which over 4 billion people regularly access the internet, the conventional process of publishing scientific articles in academic journals following peer review is undergoing profound changes. Following physics and mathematics scholars who started to publish their work on the freely accessible arXiv server in the early 1990s, researchers of all disciplines increasingly publish scientific articles in the form of freely accessible and fully citeable preprints before or in parallel to conventional submission to academic journals for peer review. The full transition to open science, I argue in this study, requires to expand the education of students and young researchers to include scholarly communication in the digital era.

Sharing the same raw material, recycling and composting are in direct conflict with incineration of municipal solid waste in combined heath and power plants. Indeed, waste-to-energy plants in regions with high recycling rates import urban waste from other countries to use otherwise unused capacity, and raise revenues. Using the case of Italy’s second largest and economically most developed region, I discuss the economic viability of municipal solid waste incineration to produce electricity and heath in the context of the increasing role of electricity production from renewable energy sources as well as of the emerging mass-scale uptake of bioplastics. Four lessons and three guidelines aimed to local authorities and policy makers emerge from the present study.

During the last 25 years the scientific community has coexisted with the most fascinating protocol due to Quantum Physics: quantum teleportation (QTele), which would have been impossible if quantum entanglement, so questioned by Einstein, did not exist. In this work, a complete architecture for the teleportation of Computational Basis States (CBS) is presented. Such CBS will represent each of the possible 24 classical bits commonly used to encode every pixel of a 3-color-channel-image (red-green-blue, or cyan-yellow-magenta). For this purpose, a couple of interfaces: classical-to-quantum (Cl2Qu) and quantum-to-classical (Qu2Cl) are presented with two versions of the teleportation protocol: standard and simplified.

During the last century, entanglement was the bone of contention between the two main pillars of Physics: General Relativity (GR) and Quantum Mechanics (QM). This began in 1935 with the Einstein-Podolsky-Rosen paradox (EPR paradox) which concluded that although Quantum Mechanics is not wrong, it is an incomplete theory to represent physical reality. In this paper it is demonstrated that some byproducts resulting from entanglement and which we will call avatars act as a hinge that link both theories making the completeness of QM clear. Moreover, a thorough analysis of the non-locality of this effect will be carried out. Besides, it is demonstrated that entanglement is an instantaneous phenomenon and that it does not require the use of a superluminal signaling for this purpose. Finally, the avatars will also appear in each wormhole resulting from an entanglement process (WREP) demonstrating that they are traversable with an equivalent path of null length which can be crossed in a null time with all that this implies in Quantum Communications.

A simplified version of the quantum teleportation protocol is presented in here. Its experimental confirmation will have deep implications for a better understanding of Quantum Entanglement with a particular projection on Quantum Communications.

On June 8 and June 9, 2017, we gave two invited lectures at the Zelinsky Institute of Organic Chemistry (ZIOC) of the Russian Academy of Sciences, Moscow. The first lecture, “Sol-Gel Catalysts: Making Green Chemistry Possible”, focused on the practical outcomes of 25 years of research on sol-gel entrapped catalysts. The second, “Chemistry for the Bioeconomy: From Discussion to Action”, offered a critical insight to the forthcoming bioeconomy. Both lectures aroused much interest in the audience and ended with a vigorous discussion lasting about one hour. An outlook is provided herein.

Formula feeding, as an alternative to breastfeeding, offers benefits such as convenience and consistent nutrition. Among the drawbacks of formula feeding, however, is potential dilution or concentration errors in the of formula during preparation that may lead to infant health issues. The present study aimed to investigate the accuracy of caregiver measurements as they prepared infant formula under multiple conditions, compared with manufacturer specifications. A diverse sample of caregivers (N = 84) participated in this cross-over experimental study. Participants hand-scooped infant formula powder and poured water to prepare 4oz and 7oz feedings, using both a standardized set of infant formula products and participants’ own products. Linear mixed effects models were used to estimate fixed effects of target amount (4oz versus 7oz) and products (participant versus researcher) on mean absolute percent error (MAPE) of measurement. Across all conditions MAPE was significantly greater for measuring powder than for water (9.0% vs. 4.4%; p&lt;0.001) with a combined powder and water MAPE at 13.0%. Greater measurement error was associated with the odd-sized 7oz preparation and participants’ own products. We observed considerable variability and substantial error during infant formula preparation, particularly for hand-scooping of powder, which tended toward higher values than the theoretical gold standard.

Climate changes caused by anthropogenic actions can directly and indirectly affect living beings, including parasites and their hosts. Changes such as water temperature, pH, distribution of nutrients in the aquatic environment are some examples that can interfere with the fish community, whether in open water or in production systems. In this review, we will show how climate change can affect the adaptation of hosts and parasites in the aquatic environment and how these parasites can be used for environmental monitoring.

Forecasting streamflow accurately is essential to achieve an efficient integrated water resources management strategy and provide consistent support to water decision-makers. We present a simple, low-cost and robust approach for forecasting monthly and yearly streamflow during the hydrological year in course, applicable to headwater catchments. It combines the use of regression analysis techniques, the two-parameter Gamma continuous cumulative probability distribution function and the Monte Carlo method. It is based on a probabilistic comparison of the progression of the current hydrological year with the historic observed series. The methodology has been successfully applied to two headwater reservoirs within the Guadalquivir River Basin in southern Spain. The root-mean-square error and correlation coefficient were used to measure the accuracy of the model and the results showed good levels of reliability. The outputs are the probabilistic monthly and yearly streamflow and 80% confidence interval. Further reductions in prediction errors may be achieved from increasing the number of observed years. These risk-based predictions are of great value, especially, before the intensive irrigation campaign starts (usually in April), when Water Authorities are to take responsible management decisions about the best allocation of the available water volume between the different water users and environmental needs.