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

The continuous tightening of legislation regulating the agricultural usage of sewage sludge in the province of Catalonia (Spain) leads us to propose its gasification to produce hydrogen-rich syngas. A thermodynamic equilibrium model was developed using Aspen Plus® to simulate the air and steam gasification of sewage sludge from a wastewater treatment plant in Catalonia. The syngas generated is analyzed in terms of composition and lower heating value (LHV), as a function of equivalence ratio (ER), gasification temperature, steam-to-biomass ratio (SBR), and moisture content (MC). Results show that air-blown gasification finds the highest LHV of 7.48 MJ/m3 at 1200ºC, ER of 0.2, and MC of 5%. Using steam as the gasifying agent, an LHV of 10.30 MJ/m3 is obtained at SBR of 0.2, MC of 5%, and 1200ºC. A maximum of 69.7% hydrogen molar fraction is obtained at 600ºC, MC of 25%, and SBR of 1.2. This study suggests using steam as a gasifying agent instead of air since it provides a higher LHV of the syngas as well as a hydrogen-richer syngas for the implementation of gasification as an alternative method to sewage sludge treatment in the region of Catalonia. Since the economic aspect should also be considered in this regard, our sensitivity analysis provided important data demonstrating that it is possible to reduce the gasification temperature without significantly decreasing the LHV.

Microplastic pollution, particularly particles smaller than 5 mm, poses significant environmental and health risks due to their potential for long-range transport and inhalation. This study provides the first long-term assessment of airborne microplastics in Porto, Portugal, over 18 months (September 2022 to March 2024). Bi-weekly samples were collected using a Microplastic Collector NILU, which were size-fractionated into five categories (>125 μm, 125-63 μm, 63-25 μm, 25-12 μm, and 12-1.2 μm), and quantified via optical microscopy. Microplastics (26 to 1,484 MPs/day/m²) and fibers (14 to 646 fibers/day/m²) showed increasing pollution trends. With a focus on the 12-1.2 μm size-range due to its classification as PM10 and PM2.5, the highest microplastic concentrations were 164 MPs/day/m² (12-1.2 μm) and 534 MPs/day/m² (25-12 μm). Recovery rates of methodology varied among polymers, with PP, PE-HD, and ABS showing high accuracy (75.9%) and PES significantly lower (26.5%). The study highlights significant temporal variability in airborne microplastic pollution, increasing trends, and the need for ongoing monitoring and targeted mitigation strategies to address associated health risks.

This research aims to analyze the impact of Social Responsibility on the performance of 216 European companies during the years 2017 to 2021. The objective of this research is to determine how the operational, financial and market performance of companies is influenced by social responsibility practices. The methodology adopted is quantitative in nature, using the estimation of dynamic models for panel data. To quantify corporate performance, this study will use, the return on assets, the return on equity and finally the Tobin's Q ratio. On the other hand, ESG (Environment, Social and Government) scores and GC Score scores will be used in order to quantify SR. The results show that SR presents not only a negative influence on the financial and operational performance of companies, but also a positive impact on market performance. This influence is even greater when distinguishing the best from the worst scores. The environment, social and government dimension shows a negative relationship with ROA and ROE, and a positive one with Tobin's Q. On the other hand, the anti-corruption and environment dimension of the GC Score, relates negatively with Tobin's Q, the human rights dimension relates negatively with ROE and ROA, and finally, the labor law dimension presents a positive relationship with ROE. Importantly, firm size positively influences this relationship, while age has a negative influence. This research offers important contributions to the literature, since from the ESG scores and the GC Score, a complete analysis of the impact of social responsibility on corporate performance is developed.

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.

The valorization of the large amount of crude glycerol formed from biodiesel industry, is of primordial necessity. One possible direction with high interest to the biorefiniery sector is the production of fuel additives as solketal, though the acetalization of glycerol with acetone. This is a chemical process that conciliates high sustainability and economic interest, since solketal contributes to the fullfilment of a Circular Economy Model through its use in biodiesel blends. The key to guarantee high efficiency and high sustainability for solketal production is the use of a recovery and recyclable heterogeneous catalyst. Some examples are already reported in the literature (first example in 2012), and this review intends to conciliate the information spreaded in this topic and established the most important reacional parameters and the main catalytic characteristics strategies to achieve high solketal production in short reaction time.

Adverse childhood experiences (ACEs) refer to traumatic life events in childhood that comprise abuse (e.g., psychological, physical, sexual), neglect (psychological and physical), indirect violence or household dysfunctions. Studies have found ACEs to be related to severe short-, medium- and long-term consequences in victims’ health. The current work consists of a real-world, multicentric, prevalence study of health outcomes in children <16 years suspected of ACEs by physicians. It relies on electronic health records and healthcare registries from a Portuguese local healthcare unit between January 2001 and December 2021 (N=40 536). Three health outcome groups were analyzed: (1) traumatic injuries and intoxications (2) mental health disorders, and (3) physical disorders. Keywords and ICD-9, ICD-10, and ICPC-2 codes from were employed. Children suspected of ACEs represent 2% (n=918). Social problems, injuries and intoxications, mental health disorders, and physical disorders arise in higher percentages in suspected victims than in non-suspected individuals. Findings uncover that child victims of ACEs may be underdiagnosed. Given the severe consequences for their current and future health, this should be taken as a critical warning for healthcare professionals. Detection and reports in health units are fundamental for early treatment, aiming to avoid an escalation of damage and prevent re-victimization.

Antimony (Sb) has gained significance as a critical raw material (CRM) within the European Union (EU) due to its strategic importance in various industrial sectors, particularly in the textile industry for flame retardants and as a component of Sb-based semiconductor materials. Moreover, Sb is emerging as a potential alternative for anodes used in lithium-ion batteries, a key element in the Energy transition. This study focused on exploring the feasibility of identifying and quantifying Sb mineralizations through the spectral signature of soils using reflectance spectroscopy, a non-invasive remote sensing technique, and by employing deep learning algorithms such as Convolutional Neural Networks (CNNs). Common signal preprocessing techniques were applied to the spectral data, and the soils were analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Despite achieving high R-squared values, the study faces a significant challenge of generalization of the model to new data. Despite the limitations, this study provides valuable insights into potential strategies for future research in this field.

Annually, the oak forests of the Zagros Mountain chains, in western Iran and northeastern Iraq, face recurring challenges posed by forest fires, particularly in the Kurdo-Zagrosian forests situated in western Iran and northeastern Iraq. Assessing fire susceptibility relies significantly on vegetation condition. Integrating in situ data, Remote Sensing (RS) data, alongside the integration of Geographical Information Systems (GIS), presents a cost-effective and precise approach to capturing environmental conditions before, during, and after fire events, minimizing the need for extensive fieldwork. This study refines and applies the Zagros Grass Index (ZGI), a local vegetation index tailored to discern between grass-covered surfaces from tree canopies in Zagros forests, identifying the grass masses as the most flammable fuel type. Utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) product as input, from 2013 to 2022, the ZGI aims to mitigate the influence of tree canopies, isolating NDVI values solely attributable to grass cover. By incorporating phenological characteristics of forest trees and grass species, the ZGI outperforms NDVI in mapping grass-covered areas that are crucial for fire susceptibility assessment in the study region. Results demonstrate a strong overlap between ZGI-based maps and recorded fire occurrences, validating the efficacy of the index in fire susceptibility estimation.

The land use land cover (LULC) map is extensively employed for different purposes. The LULC maps provided by the Portuguese National Geographic Information System (SNIG) are not ideal for continuous assessment and regular scrutiny. Machine learning (ML) algorithms applied in remote sensing (RS) data has been proven effective in image classification, object detection, and semantic segmentation. Previous studies have shown that Random Forest (RF) and Support Vector Machine (SVM) consistently achieved high accuracy for land classification. In this study, the application of RF and SVM classifiers, and object-based (OBIA) and pixel-based (PBIA) approaches with Sentinel-2A imagery was evaluated using Google Earth Engine (GEE) platform for land cover classification of a burned area in the Serra da Estrela Natural Park (PNSE), Portugal. This aimed to detect the land cover change and closely observe the burned area and vegetation recovery after the 2022 wildfire. The combination of RF and OBIA achieved the highest accuracy in all evaluation metrics. At the same time, a comparison with the Normalized Difference Vegetation Index (NDVI) map and Conjunctural Land Occupation Map (COSc) of 2023 year indicated that the SVM and PBIA map resembled the maps better.

Learning systems have been very focused on creating models that are capable of obtaining the best results in error metrics. Recently, the focus has shifted to improvement in order to interpret and explain their results. The need for interpretation is greater when these models are used to support decision making. In some areas this becomes an indispensable requirement, such as in medicine. This paper focuses on the prediction of cardiovascular disease by analyzing the well-known Statlog (Heart) Data Set from the UCI’s Automated Learning Repository. This study will analyze the cost of making predictions easier to interpret by reducing the number of features that explain the classification of health status versus the cost in accuracy. It will be analyzed on a large set of classification techniques and performance metrics. Demonstrating that it is possible to make explainable and reliable models that have a good commitment to predictive performance.

Cardiovascular (CV) morbidity and mortality are markedly increased in non-dialysis patients with chronic kidney disease (CKD). Thus, the precise management of CV risk factors involved in CKD is crucial to improving outcomes. Serum phosphate (Pi) and FGF-23 levels have been linked with a higher risk of CV events in CKD. However, the exact thresholds of Pi and FGF-23, at which the risk of adverse events increases, remain unknown. We evaluated the expression of intact FGF-23 (iFGF-23) and Pi in a non-dialysis CKD patient population (n=82; 42M:40F; median age 61 years) and investigated their association with CV and renal outcomes, in a 5-year follow-up period. At baseline, the median estimated glomerular filtration rate (eGFR), iFGF-23, and Pi were 45 ml/min/1.73m² (IQ 26.6-73.1), 69.9 µg/ml (IQ 33-117) and 3.4 mg/dL (IQ 3.3-3.9), respectively. Univariate analysis showed a strong association of both iFGF-23 and Pi with age, Charlson Comorbidity Index, hypertension, and diabetes. In addition, iFGF-23 and Pi were both associated with the composite outcome (major CV and cerebrovascular events – MACCEs, hospitalizations, and all-cause mortality) during follow-up. Moreover, Pi was independently associated with all-cause mortality during follow-up. The segmentation of the population in terciles, according to Pi (<3mg/dL; 3-3.6 mg/dL; ≥3.7 mg/dL) within reference serum levels, showed a distribution of the fatality of 0%, 20% and 80% (p =0.034), respectively. Our results reinforce the association of both iFGF-23 and Pi with composite CV outcomes in non-dialysis CKD patients and further suggest that Pi, within current reference levels, may behave as an independent risk factor for mortality in this population. It is suggested that a reassessment of Pi reference levels for early therapeutic intervention in this population may be justified.

Incorporating renewables in the power grid presents challenges for stability, reliability, and operational efficiency. Integrating Energy Storage Systems (ESS) offers a solution by managing unpredictable loads, enhancing reliability, and serving the grid. Hybrid storage solutions have gained attention for specific applications, suggesting higher performance in some respects. This paper compares the performance of hybrid energy storage systems (HESS) to single battery, evaluating their energy supply cost and environmental impact through optimization problems. The model generates an optimized dispatch, minimizing cost or environmental impact of supplying energy to a generic load while considering battery degradation. Seven technologies are assessed, with an example applied to an industrial site contrasting vanadium redox flow (VRFB) and lithium batteries considering the demand of a local load (building). The results also indicates that efficiency and degradation curves have the highest impact in the final costs and environmental functions on the various storage technologies assessed. For the simulations of the example case, a single system only outperforms the hybrid system in cases where lithium efficiency is higher than approximately 87% and vanadium is lower approximately 82%.

Urban tourism has witnessed significant growth in recent years, driven by various factors that foster the transformation of urban areas into tourist hotspots. These factors include a rising interest in culture and heritage, ongoing urban redevelopment and conversion processes, and the introduction of new experiences and activities. Two particularly influential factors contributing to this growth are low-cost travel, which facilitates more accessible access to urban destinations, and the emergence of new types of accommodation, such as short-term rental (also known as local accommodation or Airbnb-type accommodation). This sudden and continuous growth of this type of tourist accommodation brings new challenges to cities and local communities. On the positive side, it contributes to job opportunities, the dynamism of the local economy, and urban revitalization. On the other hand, it also represents more difficulty in retaining the local population in city centers, as more and more buildings are converted into hostels and tourist apartments. In this context, it becomes essential to conduct studies evaluating the impacts of these dynamics in urban areas and how they influence residents' and visitors' perspectives. Therefore, this study aims to identify the main transformations resulting from short-term rental (STR) development, focusing on the impacts felt by tourists and residents in Porto. A questionnaire was distributed to tourists and residents in Porto's city center in June 2023. The results reveal differences in opinions between tourists and residents, particularly concerning historical heritage preservation, local population relocation, and reduced housing availability for residents. Nevertheless, there is a similarity in their opinions regarding the stimulus that local accommodation brings to the economy and the rehabilitation of buildings and urban areas. This study reinforces the need to pay more attention to the future development of tourist accommodation in city centers, especially regarding local policies and territorial planning, to balance better tourism development and local communities' quality of life.

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

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

A dioxomolybdenum catalyst [(MoO2Cl2-O-MoO2Cl2)(L)] (1) (with L (1S,2S)-N,N´-bis(2-pyridinecarboxamide)-1,2-cyclohexane) was prepared and used as catalyst for the desulfurization of a multicomponent model fuel containing the most refractory sulfur compounds in real fuels. This complex showed to have a high efficiency to oxidize the aromatic benzothiophene derivative compounds present in fuels, mainly using a biphasic 1:1 model fuel/MeOH system. This process conciliates catalytic oxidative and extractive desulfurization, occurring the oxidation of the sulfur compounds in the polar organic solvent. The oxidative catalytic performance of (1) showed to be influenced by the presence of water in the system. Using 50% aq. H2O2 it was possible to reuse the catalyst and the extraction solvent MeOH during ten consecutive cycles without loss of desulfurization efficiency.

The composites of heteropolyacids (H3PW12, H3PMo12) incorporated into amine-functionalized silica materials, were used for the first time as heterogeneous catalysts in the valorisation of glycerol (a large waste from biodiesel industry) by acetalization reaction with acetone. The polyoxotungstate catalyst H3PW12@AptesSBA-15 presented higher catalytic efficiency than the phosphomolybdate, with 97% of conversion with 97% of solketal selectivity, after 60 min at 25 °C, or 91% of glycerol conversion and the same selectivity, after 5 min, performing the reaction at 60 ºC. A relation of catalytic performance and acidity of the catalyst is here presented. Furthermore, the stability of the solid catalyst was investigated and discussed.

Background: Aging impacts semantic abilities, therefore semantic exercises might be a valuable tool for cognitive stimulation in healthy older adults. However, programs in this area are limited. Methods: In the current paper, we adapted the BOX linguistic semantic program for online use via the CerUp platform. Our goal was to prepare the optimization future experience of CerUp users, including potential changes in task structure, level of difficulty and instructions, and participants’ adherence, engagement, performance accuracy, perceived difficulty, and adequacy ratings assigned to the instructions we provided that might guide future changes. Additionally, we created a map of hypothesized task-specific features that may guide tailor-made uses of the program. Results: To that end, we present preliminary results on the usability of CerUp. By analyzing task-specific usability data alongside the hypothesized map of task-specific features, we also tested the validity of the latter. Conclusions: These preliminary results on the usability of the CerUp platform highlight the potential of programs for semantic stimulation. Such findings can inform future optimizations of the program, tailored to users’ needs and effectively supporting overall language skills and general cognition.

Background/Objectives: Adolescence represents a period of heightened vulnerability to risky sexual behaviours. In Portugal, adolescents are initiating sexual activity at increasingly younger ages. Yet, there are no studies evaluating their knowledge about sexually transmitted diseases and prevention methods at an earlier stage of their development. Study how middle school ad-olescents define their sexuality and assess their level of information regarding sexuality, STI, and prevention methods. Additionally, it explores adolescents' sources of information on sexuali-ty-related issues. Methods: A cross-sectional observational study was conducted involving the application of a questionnaire to 750 9th-grade students of Vila Nova de Gaia, Porto, Portugal. The questionnaire covered topics such as perceptions of sexuality, knowledge of sexuality and STI, methods of transmission prevention, and sources of information. Results: The mean age was 14.4 years, with 19.9% reporting having already initiated sexual ac-tivity. Overall, the knowledge about sexually transmitted infections is low, pointing to 7.08 out of a maximum score of 18. Condoms and immunisation are well-recognized preventive measures, but many misconceptions persist. Better knowledge is associated with better attitudes in the likelihood of having sexual intercourse. Conclusions: This study reveals adolescents' limited sexually transmitted infections knowledge, misconceptions about prevention, and reliance on peers and the internet over trusted sources, highlighting the need for comprehensive sexual education in middle school.

This study aimed to compare the levels of physical activity and quality of life reported by Chileans with and without osteoarthritis (OA). Educational level and monthly income data were collected from eighty-two participants (62 women and 20 men), of whom 41 had OA. Concerning the medical information of the persons suffering from OA, diseases, and date of diagnosis were indicated. The International Physical Activity Questionnaire-Short Form (IPAQ-SF) and its Elderly version (IPAQ-E) estimated physical activity levels. The Short Form 36 Questionnaire (SF-36) assessed health-related quality of life. The findings indicate that non-OA subjects scored higher on all dimensions of the SF-36, including physical function, physical role, bodily pain, general health, vitality, social function, emotional role, and mental health. Individuals with OA reported better physical function and role, general health, vitality, social function, and mental health when they walked more. However, no associations were found between any physical activity levels and the degree of pain in people with OA. Our findings underscore the critical role of investigating physical activity in OA patients to enhance their quality of life, particularly in light of the increased sedentary behavior observed post-pandemic.

The current study aimed to examine the relationship between sociodemographic variables (i.e., sex, age, marital status, educational level, socioeconomic status, and working mode) and physical activity levels declared by Chilean adults. The sample comprised 483 Chilean adults, 159 men (32.9%), and 324 women (67.1%) aged from 18 to 69 years old (36.5±12.0). The participants completed an ad-hoc sociodemographic online survey that included questions about characteristics of participants such as sex, age, educational level, household income, marital status, and working mode. Vigorous, moderate, and walking activities were measured using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), a self-administered questionnaire. Results: Men declared significantly higher vigorous and moderated physical activity than women. People aged 18 to 25, single or unmarried, and with the lowest household income, showed significantly higher scores in vigorous physical activity than those aged 26 to 45, cohabiting with a partner or married, and middle household income, respectively. Regarding working mode, people working on their job site said walking more than people not working, working on hybrid, and online mode. Our findings suggest that promoting strategies that increase physical activity during the pandemic is necessary to avoid health problems.

Neurodegenerative diseases (NDs) are a set of progressive, chronic, and incurable diseases characterized by the gradual loss of neurons, culminating in the decline of cognitive and/or motor functions. Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common NDs and represent an enormous burden both in terms of human suffering and economic cost. The available therapies for AD and PD only provide symptomatic and palliative relief for a limited period and are unable to modify the diseases’ progression. Over the last decades, research efforts have been focused on developing new pharmacological treatments for these NDs. However, to date, no breakthrough treatment has been discovered. Hence, the development of disease-modifying drugs able to halt or reverse the progression of NDs remains an unmet clinical need. This review summarizes the major hallmarks of AD and PD and the drugs available for pharmacological treatment. It also sheds light on potential directions that can be pursued to develop of new, disease-modifying drugs to treat AD and PD, thereby decreasing the social and economic burdens linked to these NDs.

Recently, the Portuguese parliament approved the decriminalisation of euthanasia for incurable illnesses. As the experiences of other countries show us, it will be a matter of time before mental disorders are addressed. Studying the phenomenon, particularly in vulnerable groups, in advance is essential for proper law drafting. Therefore, instruments which allow an objective assessment and comparison between groups must be available. This study aims to explore the validation of Faria's Attitude about Euthanasia scale in Portuguese older adult patients with mixed anxiety-depressive disorder. A sample of 114 older adult patients with mixed anxiety-depressive disorder collected by convenience in the Psychiatry Department of Senhora da Oliveira Hospital in Portugal was included. The pre-final version of the scale was tested in a small group with good results. The validity of the internal structure was analysed using exploratory factorial analysis. The internal consistency study verified reliability. For construct validity, we assessed the correlation with other validated scales measuring attitudes toward euthanasia, cognitive performance, personality and empathy. Attitude about euthanasia scale showed good internal consistency. One factor was retained in the principal component analysis. Significant correlations verified construct validity. The results support the scale's usefulness and validity. This study makes available a unique instrument to assess the overall tendency of the attitudes towards euthanasia in European-Portuguese, which can be used, for example, to compare Portuguese with Brazilian older adult psychiatric patients suffering from the same disorder. Furthermore, the adapted scale paves the way for other cross-cultural translations, adaptations, validations, and comparative analyses.

Parkinson's disease (PD) is recognized as the second most prevalent primary chronic neurodegenerative disorder of the central nervous system. Clinically, PD is characterized as a movement disorder, exhibiting an incidence and mortality rate that is increasing faster than any other neurological condition. In recent years, there has been a growing interest concerning the role of the gut microbiome in the etiology and pathophysiology of PD. The establishment of a brain-gut microbiome axis is now real, with evidence denoting a bidirectional communication between the brain and the gut microbiota through metabolic, immune, neuronal, and endocrine mechanisms and pathways. Among these, the vagus nerve represents the most direct form of communication between the brain and the gut. Given the potential interactions between bacteria and drugs, it has been observed that the therapies for PD can have an impact on the composition of the microbiome. Therefore, in the scope of the present review, we will discuss the current understanding of gut microbiome on PD and whether this may be a new paradigm for treating this devastating disease.

The current surge in the deployment of web applications underscores the need to consider users' individual preferences in order to enhance their experience. In response to this, an innovative approach is emerging that focuses on the detailed analysis of interaction data captured by web browsers. This data, which includes metrics such as the number of mouse clicks, keystrokes, and navigation patterns, offers insights into user behaviour and preferences. By leveraging this information, developers can achieve a higher degree of personalization in web applications, particularly in the context of interactive elements such as online games. This paper presents the WebTraceSense project, which aims to pioneer this approach by developing a framework that encompasses a backend and frontend, advanced visualization modules, a DevOps cycle, and the integration of AI and statistical methods. The backend of this framework will be responsible for securely collecting, storing, and processing vast amounts of interaction data from various websites. The frontend will provide a user-friendly interface that allows developers to easily access and utilize the platform’s capabilities. One of the key components of this framework is the visualization modules, which will enable developers to monitor, analyse, and interpret user interactions in real-time, facilitating more informed decisions about user interface design and functionality. Furthermore, the WebTraceSense framework incorporates a DevOps cycle to ensure continuous integration and delivery, thereby promoting agile development practices and enhancing the overall efficiency of the development process. Moreover, the integration of AI methods and statistical techniques will be a cornerstone of this framework. By applying machine learning algorithms and statistical analysis, the platform will not only personalize user experiences based on historical interaction data but also infer new user behaviours and predict future preferences. In order to validate the proposed components, a case study was conducted which demonstrated the usefulness of the WebTraceSense framework in the creation of visualizations based on an existing dataset.

This article presents an innovative approach to the design of a safe adaptive backstepping control system. Tailored specifically for underactuated marine robots, the system utilizes simple sensors for enhanced practicality and efficiency. Given their operation in diverse oceanic environments fraught with various sources of uncertainties, ensuring the system's safe and robust behavior holds paramount importance in the control literature. To address this concern, this paper introduces a control strategy designed to ensure robustness at both the kinematic and dynamic levels. By emphasizing the compensation for the system uncertainties, the design integrates a straightforward fuzzy system structure. To further ensure the system's safety, a funnel surface is defined, followed by the design of a suitable nonlinear sliding surface as a function of the funnel and tracking error. Specifically leveraging the Lyapunov function, the study formally establishes the Semi-globally Practically Finite-time Stability of the closed-loop system, validated through simulations conducted on underactuated marine robots.

Background - Compared to the da Vinci platform, there is limited experience with the Hugo RAS platform for colorectal surgery in Europe. This difference is especially notable when considering a single complex procedure, such as total colectomy. Aim - To demonstrate the feasibility and safety of using the Hugo RAS for assisted total colectomy. Clinical case- Female patient: eighteen-year-old with Familial Adenomatous Polyposis (FAP). Her IBM was 19. She underwent a total colectomy with ileorectal anastomosis using the Hugo RAS platform. The procedure took 230 minutes and had no complications. The postoperative period was uneventful. She was discharged from the hospital on the third postoperative day. Conclusion - The Hugo RAS platform is one of the emergent minimally invasive robotic platforms that can be used even in total colectomy if the proper patient selection is made. The placement choice of arms and trocars was crucial to obtain a similar operative time of the single laparoscopic approach. The certification of Hugo’s new instruments, such as energy devices and staplers, will make this platform even more competitive.

Cognitive interventions vary in their level of structure, encompassing standardized and unstandardized tasks, person-centered tasks. Addressing semantic knowledge/semantic memory/semantics is important, mainly because its efficiency impacts other cognitive domains. Semantic tasks are commonly included in preventive and rehabilitation programs, typically as standardized tasks with pre-defined semantic referents. In contrast, person-centered approaches have introduced personally relevant semantics, allowing for expressive language to share thoughts and experiences. Although these approaches offer benefits beyond cognitive improvement, their lack of structure may pose challenges. Our CQ program blends structured activities with personally relevant semantics, aiming to harness the advantages of both methods. Additionally, in this review we discuss future challenges and directions in the field of semantic interventions.

Background: Young people with intellectual developmental disabilities have a persistent delay in the development of executive functions. Virtual reality (VR) is increasingly being used as a cognitive intervention tool, with significant effectiveness demonstrated in different types of populations. Methods: This pilot study aims to investigate the impact of a cognitive training program utilizing VR on young adults diagnosed with intellectual developmental disability (IDD). The participants (N=15) served as their own control group and were assessed three times: weeks 0, 8 and 16, with a rest period (0-8 weeks) and an intervention period (8-16 weeks). The assessments included measures of cognitive function, provided by E-Prime®. Results: Overall, an improvement in working memory and inhibitory control was found after the intervention, but not in sustained attention. Conclusions: These findings suggest that VR-based cognitive training holds promise as an effective intervention for enhancing cognitive abilities in young adults with intellectual developmental disability.

More than 700 anthocyanins are described so far, and many different sources are rich in these natural pigments. During the last few years, researchers have been focusing of strategies to recover and purify anthocyanins, from simple liquid-liquid extractions to more advanced supercritical CO2 extractions, however, with such a huge number of different sources, it’s extremely hard to get a simple and fast methodology that fits several sources, not only by the structural nature of the anthocyanins but also by the presence of specific groups of natural compounds. Using simple methodologies like solid-phase extraction resins represents a powerful economical and efficiency strategy. In this work, we tested several sources of structurally distinct anthocyanins, including purple basil, purple cabbage, purple sweet potato, butterfly pea flower, cornflower and wild pansy, in different resins to assess their efficiency in the obtention of anthocyanin-pure extracts. The results showed us that the combination of oasis HLB® resin followed by a cation-exchange SPE with DSC-MCAX® resulted in high-purity anthocyanin extracts for all the cases.

Diabetic foot is a serious complication that poses significant risks for diabetic people. The resulting reduction in protective sensitivity in the plantar region requires early detection to prevent the imminent ulceration and amputation. The primary method employed for evaluating this sensitivity loss is the 10 g f Semmes-Weinstein monofilament test, commonly used as a first-line procedure. However, the lack of calibration in existing devices often introduces decision errors due to unreliable feedback. In this paper, a new equipment designed to address these limitations and enhance the assessment of the sensitivity loss using the 10 g f monofilament is introduced. The proposed system automates metrological verification and evaluation processes, ensuring accurate and reliable results. Furthermore, it simulates the practitioner’s procedure, serving both as a valuable training tool and a means to provide force-feedback information. An analytical model of the monofilament buckling and deflection is also presented. The obtained results showed that the tested monofilaments had a very high error compared to the 10 g f declared by the manufacturers. It is aimed, by introducing this advanced equipment, to improve the precision and reliability of assessing the sensitivity loss. The integration of automated verification, simulation capabilities, and precise measurements shows great promise for diabetic patients, reducing the likelihood of adverse outcomes such as ulceration and amputation.

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

Studies and opinion articles present unequal conclusions concerning empathy and morality, mainly because a somewhat heterogeneous and foggy conceptual approach prevails. This scoping review aims to analyse the relationship between empathy and morality and to present a novel conceptual model of empathy applied to moral decisions.A search in PsycINFO, Scopus and PubMed identified articles addressing the relationship between empathy and morality.Thirty-two articles were included. We find an absence of a consensual definition of empathy. It is commonly defined as a predominant emotional process and a factor of bias and prejudice in moral decisions.According to our conceptual model, empathy is a distinct, complex human neuropsychological capacity that mobilises and is dependent on the proper functioning of several brain areas and balances the scales on which are Emotion and Reason, enabling the most thoughtful moral decisions possible in diverse circumstances and contexts.

Drug-induced movement disorders (DIMDs) are a group of neurological conditions caused by the use of certain medications. These disorders can significantly impact a person's quality of life and are essential to recognize and manage. This article provides an overview of the causes, symptoms, and treatment of DIMDs. DIMDs can manifest in various forms, including parkinsonism, tardive dyskinesia, dystonia, and akathisia. They are most commonly associated with medications such as neuroleptics, antidepressants, antipsychotics, antiemetics, and anticonvulsants. Risk factors for developing DIMDs include age, genetics, duration of medication use, and dose of medication. Symptoms of DIMDs can range from mild to severe and may include tremors, rigidity, bradykinesia, and involuntary movements. These symptoms can significantly impact a person's ability to perform daily activities and lead to social isolation and decreased quality of life. DIMD diagnoses are based on clinical evaluation, including a thorough medical history and physical examination. Imaging studies such as MRI or CT scans may also be used to rule out other possible causes of symptoms. Treatment of DIMDs involves the withdrawal of the offending medication if possible. Pharmacological treatments such as anticholinergic drugs, benzodiazepines, and dopamine agonists may also be used to manage symptoms. Non-pharmacological treatments such as physical, occupational, and speech therapy can also be beneficial. DIMDs are necessary neurological conditions that can significantly impact a person's quality of life. Early recognition and management of these disorders are essential for optimizing outcomes. Further research is needed to understand the underlying mechanisms of DIMDs better and to develop more effective treatments.

This narrative review synthesizes recent basic and clinical research on visual disturbances in low-light environments, highlighting evaluation techniques for these conditions. It focuses on the degradation of visual acuity under dim lighting, exacerbated by pupil dilation, known as night vision disturbances (NVD). Key contributors to NVD include optical scattering, intraocular diffraction, ocular aberrations, and uncorrected refractive errors, all significantly impacting quality of life and functional abilities. The review also examines the effects of aging, eye disorders, surgical interventions, and corneal irregularities on NVD. It details the definitions, distinctions, and measurement methodologies for various optical phenomena, using both objective and subjective approaches, such as visual function questionnaires, simulators, and the Light Distortion Analyzer (LDA). The LDA is validated for clinical characterization and quantification of light distortion, proving useful in both clinical and research settings. The review advocates for continued innovation in therapeutic interventions to improve patient outcomes and alleviate the impact of visual disturbances.

Movement disorders encompass a diverse group of neurological conditions characterized by abnormal voluntary or involuntary movements. These disorders can be classified broadly into hyperkinetic and hypokinetic disorders. Excessive, involuntary movements, including tremors, dystonia, chorea, and myoclonus characterize hyperkinetic disorders. Tremors are rhythmic, involuntary movements occurring at rest or during movement. Dystonia involves sustained muscle contractions, leading to twisting and repetitive movements or abnormal postures. Chorea manifests as brief, irregular, involuntary movements that flow from one body part to another. Myoclonus consists of sudden, brief muscle contractions, either spontaneous or in response to a stimulus. Hypokinetic disorders are characterized by a lack of movement or difficulty initiating movement, as seen in Parkinson's disease and Parkinsonism. Parkinson's disease is a progressive neurological disorder that primarily affects movement, causing tremors, stiffness, and difficulty with balance and coordination. Parkinsonism refers to a group of disorders with similar symptoms to Parkinson's disease but with different underlying causes. Diagnosing movement disorders involves a thorough clinical evaluation, including a detailed medical history and physical examination. Neuroimaging studies such as MRI, CT scans, and functional imaging techniques may be used to assess brain structure and function. Additionally, laboratory tests, including genetic testing and biochemical markers, can help diagnose certain movement disorders.

In this paper, the experimental results of the thermal sub-system of a reliable and cost-effective polygeneration solar system are presented. This polygeneration system produces heating, cooling and electricity from solar energy, which are used in an existing test-building. Heat is generated in four evacuated tube solar collectors (ETC). The heat may be used for space cooling, through a variable geometry ejector (VGE) heat pump. In order to reduce the mismatches between generation and consumption, two thermal storage tanks were added. The performance of a new thermal storage, with 400 l, able to storage both sensible and latent heat, was tested. Heating performances of the test-building were assessed. Ejector cycle tests were also performed.

Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible to occur and hence lead to economic and human catastrophes. The aim of this document is precisely to characterise the mechanical crack growth behaviour of the 51CrV4 spring steel representative of leaf springs under cyclic conditions, that is, crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio are also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons.

(1) Background: Hand hygiene practice by using alcohol-based hand sanitizers was generalized in all sectors of activity, due the COVID-19 pandemic. The aim of this study was to organize and analyze the scientific data regarding occupational exposure to hand sanitizers, with a particular focus on their use and health effects on workplace settings. (2) Methods: A rapid literature review was carried out searching on the main scientific database, namely: Web of Science Core Collection, Medline, Scielo and Current Content Connect. (3) Results: All studies analyzed included samples from healthcare professionals and eczema as well as irritant contact dermatitis were the most reported skin lesions. (4) Conclusions: The adequate implementation of hygiene and disinfection programs in workplaces is essential to guarantee the workers safety and health. Further research is needed on the effectiveness of contingency plans in different sectors of activity, particularly, in industry.

Aim: To analyze a single center's experience with Short Bowel Syndrome/ Chronic Intestinal Failure (SBS/CIF) in adult patients treated with Home Parenteral Nutrition (HPN). Materials and methods: In the last thirty years, 13 patients with SBS/CIF were included in an HPN program. Results: Between 1992 and 2023, 13 patients were included in an HPN program. The primary underlying pathology was acute mesenteric ischemia. The median age of the starting HPN was 44 years old. Most are submitted to several surgeries of extensive intestinal resection with posterior intestinal reconstruction. Five of the 13 patients have died while on HPN for a median of 42 months. The causes of death HPN-related were catheter sepsis, endocarditis with cardiac failure, or hepatic failure. One patient died due to underlying pathology: pelvic abscesses and bleeding related to radiotherapy. Eight patients remain alive with a median time of HPN of 173 months. During the HPN support, the most frequent complications were venous catheter infection and venous territory thrombosis. None of the eight patients alive have hepatic failure. Two patients recently started teduglutide, with good tolerance, and need reduction of HPN support. All these eight patients have a satisfactory quality of life (parenteral support needs range between five to two nutrition bags per week). Conclusion: HPN remains the gold standard of SBS/CIF treatment, although Teduglutide may reduce HPN needs and HPN complications and provide a better quality of life. An HPN multidisciplinary healthcare group support is essential to ensure these patients' survival and quality of life. Keywords Short bowel Syndrome, Chronic Intestinal failure, Home Parenteral Nutrition, Teduglutide, Complications of Parenteral Support.

Gold nanoparticles (AuNPs) exhibit improved optical and spectral properties compared to bulk materials, making them suitable for detection of DNA, RNA, antigens, and antibodies. Here, we describe a simple, selective, and rapid non-cross linking detection assay, using approx. 35 nm spherical Au nanoprobes, for a common mutation occurring in exon 19 of the epidermal growth factor receptor (EGFR), associated with non-small cell lung cancer cells. AuNPs were synthesized based on the seed-mediated growth method and functionalized with a specific 16 bp thiolated oligonucleotide using a pH-assisted method. Both AuNPs and Au nanoprobes proved to be highly stable and monodisperse by ultraviolet-visible spectrophotometry, dynamic light scattering (DLS) and electrophoretic light scattering (ELS). Our results indicate a detection limit of 1.5 µg mL−1 using a 0.15 nmol dm−3 Au nanoprobe concentration. In conclusion, this work is an effective possibility for a straight-forward, fast, and inexpensive alternative for the detection of DNA sequences related to lung cancer, leading to a potential platform for an early diagnosis of lung cancer patients.

Lower limb exoskeletons have the potential to reduce the prevalence of work-related musculoskeletal disorders; however, they often lack user-oriented control strategies. Human-in-the-loop (HITL) controls can adapt an exoskeleton’s assistance in real-time, to optimize the user-exoskeleton interaction. This study presents a HITL control for a knee exoskeleton to minimize the users’ physical effort, a parameter innovatively evaluated by their interaction torque with the exoskeleton (a muscular effort indicator) and metabolic cost. This work innovates by estimating the user’s metabolic cost within the HITL control through a machine-learning model. The regression model was able to estimate the metabolic cost, in real-time, with a root-mean-squared error of 0.66 W/kg and a mean absolute percentage error of 26%, making faster (10s) and less noisy estimations than a respirometer (K5, Cosmed) device. The HITL reduced the user’s metabolic cost and interaction torque by 7.3% and 32.3%, respectively, when compared to a zero-torque control. The developed HITL control surpassed both a non-exoskeleton and a zero-torque condition regarding the user’s physical effort, even for a simple task such as slow walking. Furthermore, the user-specific control enabled a lower metabolic cost than the non-user-specific assistance. This proof-of-concept demonstrated the potential for HITL controls in assisted working.

Building integrated photovoltaics (BIPV) consists of PV panels that are integrated into the building as part of the construction. This technology has advantages such as the production of electricity without necessary additional land area. This paper provides a literature review about the recent developments in urban building energy modelling, including tools and methods, and how they can be used to predict the effect of PV systems on building outdoor and indoor environments. It is also intended to provide a critical analysis on how PV systems affect the urban environment, both from an energy and a comfort point of view. The microclimate, namelly the urban heat island concept, is introduced and related with the existence of PV systems. It is concluded that urban building energy modelling (UBEM) can be effective to study the performance of PV systems in the urban environment. It allows to simultaneously predict the building energy performance and the microclimate effect. However, there is a need to develop new methodologies to overcome the challenges associated to UBEM, especially in what concerns non-geometric data, which leads to a major source of errors. and to find an effective method to predict the effect of PV systems in the urban environment.

Leaf springs are suspension components constituted of several structural and assembly components. Once the leaves are assembled, a stress state due to the assembly process is developed. Thus, the quantification of the assembly stress level should be known in order to be accounted for in the structural design. The aim of this article is precisely to quantify the assembly stress level in parabolic leaf springs for railway freight wagons. An experimental method with the aid of extensometry is considered to evaluate elastic assembly stresses. Next, a numerical model of the leaf spring assembly process with the required boundary conditions is developed to support the experimental results and allow obtaining a distribution of surface stresses along the master leaf length. The development of this work resulted in a surface stress profile along the length of the master leaf generated by the assembly process, where the deviations of the numerical outcomes regarding the analysed spots with strain gauges are mostly of little relevance.

Many natural signals exhibit a quasi-periodic behavior and are conveniently modeled as a combination of several harmonic sinusoids whose relative frequencies, magnitudes and phases vary with time. The waveform shape of those signals reflects important physical phenomena underlying their generation, which requires that those parameters be accurately estimated and modeled. In the literature, accurate phase estimation and modeling has received much less research effort than frequency estimation, or magnitude estimation. First, this paper addresses accurate DFT-based phase estimation of individual sinusoids in six scenarios involving two DFT-based filter banks and three different windows. It is shown that bias in phase estimation is less than 1E-3 radians when the SNR is equal to or larger than 2.5 dB. Taking as a reference the Cramér-Rao Lower Bound, it is shown that one particular window offers a performance of practical interest by approximating better the CRLB when signal conditions are favorable, and by minimizing the performance deviation when signal conditions are adverse. Second, this paper explains how a shift-invariant phase-related feature can be devised that characterizes harmonic phase structure, which motivates a signal processing paradigm that greatly simplifies parametric modeling, transformation and synthesis of harmonics signals, in addition to facilitating the understanding and reverse engineering of the phasegram. Theory and results are discussed in a reproducible perspective using dedicated experiments that are supported with code allowing not only to replicate figures and results in this paper, but also to expand research.

We model the financial markets as a game and make predictions using Markov chains estimators. We extract the possible patterns displayed by the financial markets, define a game where one of the players is the speculator, whose strategies depend on his/hers risk-to-reward preferences, and the market is the other player, whose strategies are the previously observed patterns. Then we estimate the market’s mixed probabilities by defining Markov chains and utilizing its transitions matrices. Afterwards, we use these probabilities to determine which is the optimal strategy for the speculator. Finally, we apply these models to real-time market data to determine its feasibility. After all, we obtained a model for the financial markets that has an outstanding performance in terms of accuracy and profitability.

Obesity is one of the most prevalent and damaging metabolic conditions and is a risk factor for the development of other disorders that define the metabolic syndrome. Recent studies have identified a significant role of AGE accumulation and RAGE signaling pathways in the underlying mechanisms that cause the chronic inflammatory response present in obesity which, ultimately, leads to adipose tissue dysfunction. Given the current interest and increasing evidence on possible therapeutic opportunities in the AGE-RAGE axis, the purpose of this work is to review the key findings on new small molecules and bioactive compounds that act as AGE or RAGE inhibitors and their effects on metabolic parameters of people with obesity. The search queries were defined according to the following PICO question: “What are the effects of AGE-RAGE antagonism on adipose tissue metabolism and other metabolic parameters of people with obesity? “. Article search was performed in three online databases: PubMed, Scopus, and Web of Science. In the end, 20 studies were selected for this review. Overall, the reviewed molecules showed beneficial effects on body weight, glucose tolerance, insulin resistance, inflammatory profile, and adipose tissue metabolism in mice models with obesity. There are still very few studies on human application of these molecules, but the ones that were reviewed revealed controversial data when compared to animal studies. Therefore, further human clinical trials should be performed to retrieve more conclusive data.

(1) Background: Mixed Reality is a technology that has gained attention due to its unique capabilities for accessing and visualizing information, becoming a valuable tool for medicine, particularly for the operating room and surgical learning; (2) Methods: A systematic review was conducted following the PRISMA guidelines to answer the research questions established using the PICO framework; (3) Results: Although implementation of Mixed Reality applications in the operations room presents some challenges, when used appropriately, it can yield remarkable results. It can make learning easier, flatten the learning curve for several procedures, and facilitate various aspects of the surgical processes; (4) Conclusion: Technical complexity, equipment costs, and steep learning curves present significant obstacles to the widespread adoption of Mixed Reality and computer-assisted evaluation. The possibility of integration of distinct medical imaging modalities and innovative functionalities holds promise for clinical applications. However, it is important to consider issues related to usability, bias, and statistical analyses need consideration. Mixed Reality offers significant benefits, but there are still open challenges such as ergonomic issues, limited field of view, and battery autonomy that must be addressed to ensure widespread acceptance.

The main objective of this study is to analyze the impact of investment in Research & Development on the performance and value of companies, that is, to try to explain how R&D investment influences the companies’ performance. For this purpose, a dynamic panel data model was estimated using the Generalized Method of Moments, which made possible to measure the impact of R&D investment on performance through the Return on Operating Assets ratio for the Portuguese companies that invested the most between 2012 to 2019. The results show that the investment in R&D is not statistically significant in explaining the operating return on assets. However, the lagged financial performance in one period, the leverage, the asset turnover ratio and the accounts payable turnover show to have impact on the variable under study.

Secondary movement disorders (SMDs) represent a heterogeneous group of neurological conditions characterized by abnormal, involuntary movements resulting from various underlying causes. This comprehensive review aims to thoroughly understand SMDs, including their epidemiology, pathophysiology, clinical manifestations, diagnostic approach, and management strategies. SMDs encompass a spectrum of movement abnormalities, including dystonia, chorea, athetosis, myoclonus, tics, and tremors. They can arise from a multitude of etiologies, such as drug-induced effects, post-infectious processes, metabolic disturbances, and structural brain lesions. The epidemiology of SMDs varies depending on the underlying cause, with some conditions being more prevalent in specific populations or age groups. Understanding the pathophysiology of SMDs is crucial for accurate diagnosis and targeted management. Diagnosing SMDs requires a comprehensive approach, including a detailed history, physical examination, laboratory investigations, neuroimaging studies, and sometimes electrophysiological studies. Management of SMDs is multifaceted and may involve pharmacological, non-pharmacological, and surgical interventions. Individualized treatment plans are essential, considering the underlying cause, severity of symptoms, and patient preferences. Emerging concepts in the field of SMDs include advancements in genetic research, identification of biomarkers, and development of novel therapeutic approaches. There is a growing focus on patient-centered care and improving the quality of life for individuals with SMDs. In conclusion, SMDs pose diagnostic and therapeutic challenges, requiring a multidisciplinary approach for optimal management. Continued research and collaboration are essential for advancing our understanding and treatment of these complex disorders.

Introduction: The repertoire of microRNAs (miRNAs) in thyroid carcinomas starts to be elucidated. Among differentiated thyroid carcinomas (DTC), papillary thyroid carcinoma (PTC) is the most common. The assessment of miRNAs expression may contribute to refine the pre-surgical diagnosis, in order to obtain a personalized and more effective treatment of patients. Aims: This study aims to evaluated 1) miRNAs expression in a series of DTC, and the association with the presence of selected genetic mutations, in order to improve diagnosis and predict biologic behavior of DTC/PTC. 2) the reliability of molecular tests in Ultrasound-guided Fine Needle Aspiration Cytology (US-FNAC) for a more precise preoperative diagnosis. Material and methods: This series includes 176 samples (98 cytology samples and 78 formalin-fixed paraffin embedded (FFPE) tissues) obtained from 106 patients submitted to surgery, being 13 benign lesions (controls) and 93 DTCs (cases). The microRNA expression was assessed for miR-146b, miR-221, miR-222, and miR-15a by quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) and the results were analyzed using the 2- ΔΔCT method, using miR16 as an endogenous control. The discriminative ability of miRNAs expression regarding PTC diagnosis was evaluated using the area under the Receiver Operating Characteristic Curve (AUC). The association of miRNAs expression, clinicopatological features and genetic alterations (BRAF, RAS and TERTp) was evaluated in PTCs. Results/Discussion: All the analyzed miRNAs showed a tendency to be over expressed in DTCs/PTCs when compared with benign lesions, both in cytology and histology samples. In cytology, miRNAs expression levels were higher in malignant than in benign tumors. In histology, corresponding discriminative abilities regarding PTC diagnosis were: miR-146b (AUC0.94, 95%CI 0.87-1), miR-221 (AUC0.79, 95%CI 0.68-0.9), miR-222 (AUC0.76, 95%CI 0.63-0.89) and miR-15a (AUC0.85, 95%CI 0.74-0.97). miR-146b showed 89% sensitivity (se) and 87% specificity (sp); mi-R221 se=68.4, sp=90; miR222 se=73, sp=70, and mi-R15a se=72, sp=80. MicroRNAs were associated with aggressive clinicopathological features and tumor progression in PTCs (p &lt; 0.05), particularly for miR-222. Our data reveals a significant association between higher expression levels of miR-146b, miR-221 and miR-222, with the presence of BRAF mutation (p&lt;0.001), and miR-146b (p=0.016) and miR-221 (p=0.010) with the presence of RAS mutation, suggesting an interplay of these mutations with miRNAs expression. Although this study has a relatively small sample size, over expression of miRNAs in cytology may contribute to a more precise preoperative diagnosis. The miRNAs showed a good discriminative ability in PTC diagnosis. The association between the miRNAs expression profile and genetic alterations results could be useful for an accurate diagnosis of DTCs/PTCs in FNAC.

Metal-organic frameworks (MOFs) have been subject of extensive scientific investigation in the last three decades and, currently, are one of the type of compounds most studied to be potentially applied in a wide range of distinct catalytic processes. Pristine MOF compounds provide several intriguing benefits for catalytic applications, including high interior surface areas and densities of active sites, allowing high catalytic reaction rates per volume, post-synthesis modified with com-plementary catalytic groups, enabling multiple functional groups to catalyze the reaction. Most of large-scale catalytic applications, including those in fuel processing, gas emission reduction and chemical synthesis, nevertheless the pristine MOFs often reveal limited stabilities and opportuni-ties for regeneration at high temperatures. As a result, the real applications of MOFs in these tech-nologies are likely to be constrained, and their controlled thermal modification aiming the prepa-ration of MOF-derivative compounds has been applied to induce crystalline structural changes and increase their structural stability, enhancing its potential applicability in more severe catalytic processes. Recent advances concerning the use of this strategy to boost the catalytic potential of the MOF-derivative compounds are outlined in this short-review article.

Introduction: This study aims to verify if elderly patients with mixed anxiety-depressive disorder are more prone to euthanasia and identify factors that interfere with their satisfaction with health and capacity for well-informed decisions. Material and Methods: The study applied a paper questionnaire composed of a sociodemographic section and a battery of scales (to assess depression, anxiety, cognitive performance, suicide risk, therapeutic adhesion, functionality, loneliness, attitude towards euthanasia, decision pattern, personality, empathy and health status) in the Psychogeriatric Unity of Senhora da Oliveira Hospital in Portugal. The sample was collected by convenience to include patients and controls of the same age. Six months later, a reassessment was done. Patients and controls were compared using descriptive statistics and a multiple-regression model.Results: A total of 114 patients and 25 controls were included. Eighty-one point six per cent of patients had four or fewer years of schooling. Contrary to controls, they presented mild depressive and anxiety symptoms, loneliness feelings, worse cognitive performance, a more fragile personality, higher personal distress and a poorer health state. No statistically significant differences were found between controls and patients regarding their attitudes towards euthanasia. Patients more favourable to euthanasia had higher empathic concern, conscientiousness and fantasy and lower personal distress.Discussion and Conclusion: When addressing euthanasia in these patients, it is crucial to ensure they are fully self-determinate and that all the necessary treatment and support are available. It may not be the case when the educational level is low and mild disease persists, significantly affecting their well-being and cognitive performance.

Research has shown that emotional states may influence the subjective experience of time. The present study involved 111 healthy adult participants and examined the impact of emotional stimuli on time perception, using a time estimation task with four conditions: in one of the conditions, participants estimated the exposure time of a black screen, wherein the duration could vary be-tween 2 to 7 s (condition without emotional interference); in the other conditions, participants es-timated the exposure time (also ranging from 2 to 7 s) of images that would induce pleasant, un-pleasant, or neutral emotions, to which participants were instructed to focus their attention (pleasant, unpleasant, or neutral emotions). The results showed that participants estimated “shorter” time intervals (underestimation) for pleasant and unpleasant images compared to the condition without interference, but no significant differences were found between the neutral condition and the condition without interference. It is suggested that increased attention to an ex-ternal stimuli, regardless of its emotional valence, produces an underestimated perception of time.

The rising prevalence of food intolerances and increased health and environmental consciousness has driven demand for free-from (FF) and organic products. This study aims to analyze consumer needs, motivations, and challenges related to these products in Portugal through an online survey with 2268 eligible responses, with a participants’ median age of 41 years, predominantly women (76.9%). Results show that 97.4% of respondents are aware of FF products, with 60.0% being regular consumers, particularly of lactose-free milk and gluten-free bread and biscuits. Significant market gaps were identified in the variety of FF bread (62.8%), pastries (49.0%), and cookies (38.4%). Consumers identified high prices (84.9%) and excessive sugar/fat content (52.1%) as the main drawbacks of FF products currently on the market. Women showed greater knowledge and purchase levels compared to men. Trust in organic certification was low (21.4%), with skepticism higher among lower-income and male participants. Despite this, 78.1% believed in the health benefits of organic products, and 72.2% agreed that increased demand could lower prices. Overall, the study highlights the need for greater products’ variety, improved transparency, and consumer education to enhance market trust and accessibility.

(1) Background: The development of generative artificial intelligence (GAI) is transforming higher education. This systematic literature review synthesizes recent empirical studies on the use of GAI, focusing on its impact on teaching, learning, and institutional practices. (2) Methods: Following PRISMA guidelines, a comprehensive search strategy was employed to locate scientific articles on GAI in higher education, published by Scopus and Web of Science between January 2023 and January 2024. (3) Results: The search identified 102 articles, with 37 meeting the inclusion criteria. These studies were grouped into three themes: the application of GAI technologies, stakeholder acceptance and perceptions, and specific use situations. (4) Discussion: Key findings include GAI’s versatility and potential use, student acceptance, and educational enhancement. However, chal-lenges such as assessment practices, institutional strategies, and risks to academic integrity were also noted. (5) Conclusions: The findings help identify potential directions for future research, including assessment integrity and pedagogical strategies, ethical considerations and policy development, the impact on teaching and learning processes, perceptions of students and instructors, technological advancements, and the preparation of future skills and workforce readiness. The study has certain limitations, particularly due to the short time frame and the search criteria, which might have varied if conducted by different researchers

Background: Strength assessment is one of the main fields in sports performance, physical rehabilitation, physical activity and health. Purpose: To compare maximal voluntary isometric contractions (MVIC) and paired voluntary isometric contractions (VIC) of knee extensors between an isokinetic dynamometer (BIODEX) and a portable and lightweight device (DINABANG). Methods: From 19 volunteers (age: 28.7±7 y; body mass: 72±10 kg and height: 173±7 cm) we obtained 114 paired MVIC measures and, from the force-time curves of these repetitions, 22507 paired VIC measures of knee extensors. Results: We observed “excellent” repeatability for MVIC (ICC:1.00; p&lt;0.001) between BIODEX (247±79.5 Nm) and DINABANG (247±74.8 Nm), with “trivial” effect (mean difference: 0.12 Nm (0.02%); 95%CI: -0.13 to 0.23 Nm; p=0.606; d=0.048). Bland-Altman plots revealed high accuracy for MVIC (bias: 0.12 Nm) and consistent distribution (precision) inside the limits of agreement (-4.81 to 5.06 Nm) and respective 95%CI. “Excellent” repeatability was also observed for VIC (ICC:1.00; p&lt;0.001) between BIODEX (219±84.1 Nm) and DINABANG (218±84.0 Nm), with “trivial” effect (0.24 Nm (0.11%); 0.08 to 0.11 Nm; p&lt;0.001; d=0.100). Bland-Altman plots revealed high accuracy for VIC (bias: 0.24 Nm) and consistent distribution (precision) inside the limits of agreement (-4.5 to 4.9 Nm) and respective 95%CI. Conclusion: DINABANG is accurate, precise and reliable for torque measurement.

Nowadays, the growing concern about improving thermal comfort in textiles, asphalt pavements and buildings has stimulated research into phase change materials (PCMs). However, the incorporation of PCMs directly causes mechanical impacts. Therefore, this study herein reported focuses on designing coaxial phase change fibres using commercial cellulose acetate (CA) or recycled CA obtained from cotton fabrics (CAt) as a coating and polyethylene glycol (PEG) 2000 as a core. The phase change fibres (PCF) were produced by wet spinning, varying the parameters: (i) CA concentration, molecular weight and source (virgin versus recycled); and (ii) PEG concentration and ejection. For phase change recycled fibres (PCFt), PEG concentration and ejection were varied. The fibres were assessed for their optical, chemical, thermal and mechanical properties. Bright-field microscopy images and Scanning Electron Microscopy (SEM) micrographs proved the coaxial structure. Fourier Transform Infrared spectroscopy (FTIR) confirmed the presence of PEG in the core. Thermogravimetric Analysis (TGA) proved the ability of PCFs to tolerate high temperatures. Differential Scanning Calorimetry (DSC) attested to the presence of PEG2000 peaks, since their melting points were close to those of virgin PEG2000, with a slight change in the PCFs and PCFts caused by the protective sheath of CA and CAt.

Short-term energy consumption forecasting crucial for the operation of new electrical en-ergy grids, not only due to their own characteristics, but also due to the new elements pre-sent in the energy matrix. Many existing models are limited by their methodologies or by considering only a narrow set of factors influencing energy consumption. This study in-troduces a pipeline for developing an energy forecasting model and evaluates the signifi-cance of factors affecting energy consumption and, consequently, forecast accuracy. The study utilizes a dataset from ISO NE (Independent System Operator New England), span-ning the total electric load of various cities in New England from January 2017 to December 2019. This dataset comprises 23 independent variables, including weather data, economic indicators, and market information. The results outline the steps involved in constructing energy forecast models using time series analysis. By carefully selecting variables and rep-resenting external factors, the study demonstrates the feasibility of generating more accu-rate predictions with reduced computational resources.

In recent decades, both in Italy and internationally, the phenomenon of abandoned industrial buildings has grown considerably, causing inevitable social, urban and economic impacts. At the same time, the cultural debate has increased awareness of the problem and the strategic role that abandoned industrial sites can play in responding to new needs. This contribution analyzes the dismantling process of the Akragas Montedison factory in Porto Empedocle, Sicily, examining the evolution of disused industrial areas from the 20th century to the present day and the possibilities of reconversion for appropriate reuse.

The article focuses on the integrated environmental accounting model called 'eValue', developed for protected areas and applied in the research programme coordinated by the Italian Ministry of the Environment and aimed at implementing an environmental accounting system for Italian Marine Protected Areas (MPAs). eValue adopts a cost-benefit analysis approach. Financial accounting based on costs and revenues is integrated with environmental accounting, which reflects environmental costs and environmental revenues, i.e. environmental benefits. The environ-mental costs assess the impacts related to human activities in the MPA expressed by calculating the carbon footprint and the environmental benefits of the marine ecosystem services calculated by applying monetary valuation techniques. The values thus estimated flow into the annual flow account, where the value produced (or consumed) by the MPA is estimated by difference. The eValue model was applied to the Porto Cesareo MPA (Italy). eValue showed that the annual benefit-cost ratio reaches a value of 3.4. Furthermore, the ratio of net benefit to public funding is 3.7, completely covering the amount of public transfers and thus summarizing the MPA overall value for money.

The COVID-19 pandemic crisis has brought about unprecedented economic and social consequences worldwide. The implementation of isolation measures, including national and international travel restrictions, significantly affected contact-intensive sectors such as tourism. During this lockdown period, Information and Communication Technology (ICT) was crucial in maintaining connectivity and enabling remote activities. Governments across the world implemented discretionary measures to mitigate the crisis's adverse effects on economic activity. This paper aims to analyze whether the level of ICT adoption and the importance of tourism influence the fiscal policy efforts pursued by governments. Based on the results of a linear regression analysis for 154 countries, the findings suggest that in countries with higher international tourism receipts, the governments had to promote higher fiscal stimulus. At the same time, ICT development diminished the efforts of the fiscal policy response to the crisis since it facilitated economic resilience. The findings of this study can contribute to understanding how governments responded to the pandemic crisis and the factors that influenced their fiscal policy decisions.

Despite its growing importance as a dry beneficiation method, there is a lack of studies exploring the fundamentals aspects of dry jigging. In this sense, this study focuses on explore some essential aspects of density-based separation in dry jigs, like pulse profile, energy consumption and, especially, stratification over time, also exploring an innovative operational strategy here called “transient pulsation”. The tests were carried out using density tracers distributed across 11 density ranges (0.4-2.4 g/cm³) and employing a base bed (gravel) to analyze their segregation in a pilot-scale dry jig. Pressure drop and active power data were acquired to measure the pulse characteristics and energy consumption. The findings suggest that establishing the dry jigging cycle is more complex than in hydraulic jigs due to the compressibility of air. Stationary pulsation tests revealed an unstable behavior of stratification over time, contrasting with traditional hydraulic jigs, while transient pulsation tests unveiled varied trends in separation quality. Energy consumption analysis underscored the significant role of the blower drive. These insights have the potential to inform operational enhancements in dry jigging.

Hydroalcoholic extracts from Malbec and Torrontés wine pomace (Vitis vinifera L.) originating from the high-altitude vineyards of Argentina's Calchaquí Valleys were characterized. Total phenolics, hydroxycinnamic acids, orthodiphenols, anthocyanins, non-flavonoid phenolics, total flavonoids, flavones/flavonols, flavanones/dihydroflavonols, and tannins were quanti-fied through spectrophotometric methods, with Malbec extract exhibiting higher concentra-tions in most of phytochemical groups when compared to Torrontés. HPLC-DAD identified more than 30 phenolic compounds in both extracts. Malbec displayed superior antiradical ac-tivity (ABTS cation, nitric oxide, and superoxide anion radicals), reduction power (iron, copper and phosphomolybdenum), hypochlorite scavenging, and iron chelating ability, compara-tively to Torrontés. The cytotoxicity assessments revealed that Torrontés affected the viability of HT29-MTX and Caco-2 colon cancer cells by 70% and 50%, respectively, at the highest tested concentration (1 mg/mL). At the same time, both extracts did not demonstrate acute toxicity in Artemia salina or in red blood cell assays at 500 µg/mL. Both extracts inhibited the lipoxygen-ase enzyme, with Malbec also reducing the tyrosinase activity and neither inhibited the xan-thine oxidase. The substantial phenolic content and diverse biological activities in Calchaquí Valleys' pomaces underline their potentialities to be valorized for pharmaceutical, cosmetic, and food industries.

Colorectal cancer (CRC) is one of the most common types of cancer worldwide. The KRAS mutation is present in 30-50% of CRC patients. This mutation confers resistance to treatment with anti-EGFR therapy. This article aims at proving that Computer Tomography (CT)-based Radiomics can predict the KRAS mutation in CRC patients. The piece is a retrospective study with 56 CRC patients from the Hospital of Santiago de Compostela, Spain. All patients had a confirmatory pathological analysis of the KRAS status. Radiomics features were obtained from the abdominal contrast enhancement CT (CECT), before applying any treatments. We used several classifiers, including adaboost, neural network, decision tree, support vector machine and random forest, to predict the presence or absence of KRAS mutation. The most reliable prediction was achieved using the adaboost ensemble on clinical patient data, with a kappa and accuracy of 53.7% and 76.8%, respectively. The sensitivity and specific were of 73.3% and 80.8%. Using texture descriptors, the best accuracy and kappa were 73.2% and 46%, respectively, with sensitivity and specificity of 76.7% and 69.2%, showing also a correlation between texture patterns on CT images and KRAS mutation. Radiomics could help manage CRC patients, and in the future, it could have a crucial role in diagnosing CRC patients ahead of invasive methods.

Marine microalgae are a rich reservoir of natural compounds, including bioactives. Nonetheless, these organisms remain fairly unexplored despite their potential biotechnological applications. Culture collections with diverse taxonomic groups and lifestyles are a good source to unlock this potential and discover new molecules for multiple applications such as the treatment of human pathologies or the production of aquaculture species. In the present work extracts from 33 strains (including 20 dinoflagellates, 4 diatoms and 9 strains from other 7 algal classes), cultivated under identical conditions were examined for antiviral, antibacterial, anti-inflammatory and anti-cancer activities. Among these, antiviral and anti-inflammatory activities were detected in a few strains while antibacterial tests showed positive results in most assays. In turn, most trials did not show any anti-cancer activity. Wide differences were observed between species within the same class, in particular dinoflagellates which were better represented in this study. These preliminary findings pave the way for in-depth characterization of extracts with highest signals in each test, identification of compounds responsible of the biological activities found, and a further screening of the CCVIEO culture collection.

This study aimed to compare the effects of a permanent ischemic stroke model (focal ischemia by thermocoagulation of pial vessels) on sensorimotor function (cylinder test and adhesive removal test), behavioral tasks (novelty habituation memory-open field task), and cerebral infarct size in adult male spontaneously hypertensive rats (SHR) and normotensive Wistar Kyoto (WKY) rats over 42 days after the occurrence of stroke. We observed that the stroke caused asymmetry in the front paws and delayed adhesive removal. These effects were spontaneously reduced in WKY rats, but not in SHR. Short- and long-term novelty habituation memories were abolished by stroke in WYK and SHR. On the 3rd day after stroke, the size of the focal cerebral infarct was the same in WKY and SHR. However, on the 7th day, the infarct size decreased in WKY rats, but not SHR. These results suggested that SAH impairment of sensorimotor recovery in rats subjected to cerebral ischemia could be related to augmented focal cerebral infarct size. Moreover, the behavioral tasks used in this study were unaffected by Systemic Arterial Hypertension. Our results highlight the need for animal models of comorbidities in stroke research.

The skin is the largest organ in the human body and serves multiple functions such as barrier protection and thermoregulation. The maintenance of its integrity and healthy structure is of paramount importance. Accordingly, technological advances in cosmetic sciences have been directed towards optimizing these factors. Plant-derived ingredients have been explored for their bioactivity profiles and sustainable sources. Grape by-products carry a group of bioactive molecules that display important biological activities. Nonetheless, many of these molecules (e.g., phenolic compounds) are unstable and susceptible to degradation. So, its encapsulation using nano/microsystems (i.e. liposomes) has been explored as a promising solution. In this work, two grape seed extracts were obtained, one from a single grape variety (GSE-Ov), and another from a mix of five grape varieties (GSE-Sv). These extracts were analysed for their antioxidant and antimicrobial activities, as well as for their chemical composition and molecular structure. The extract that showed the most promising properties was the GSE-Ov with a DPPH IC₅₀ of 0.079 mg.mL^-1. This extract was encapsulated in soy lecithin liposomes coated with pectin, with an encapsulation efficiency of 88.8%. These showed an in vitro release of polyphenols of 59.4% during 24 h. The particles displayed a zeta potential of -20.3 mV, and an average diameter of 13.6 µm. Loaded liposomes proved to be safe under 5 and 2.5 mg.mL^-1, in HaCaT and HDF cell models, respectively. Additionally, they demonstrated anti-inflammatory activity against IL-1α when tested at 2 mg.mL^-1. This work enabled the valorization of a by-product from the wine industry, by using natural extracts in skincare products.

Overcrowding in the emergency department is a problem that generates several implications for bed management, which is deemed one of a hospital's most critical processes. Effective management of hospital production capacity includes bed management processes, which can be improved in order to leverage hospital performance. Thus, this study sought to understand how bed management works and identify the main factors that influence its management. The study was performed through a case study, with data collected from semi-structured interviews and bibliographic research, which were triangulated. Thematic content analysis of the interviews and cross-analysis were performed. As a result, the main factors that influence hospital Bed management were identified: communication between teams and units; definition of performance goals; decisions shared between units; occupation and discharge planning by the teams; length of stay; the role of the nurses; and COVID-19. The greatest difficulties in the management process are related to these factors. Additionally, suggestions are provided to mitigate such reported difficulties.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

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

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

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

Regardless of the SARS-CoV-2 pandemic containment, it remains paramount to comprehensively understand its underlying mechanisms to mitigate potential future health and economic impacts, comparable to those experienced throughout the course of the pandemic. The angiotensin-converting enzyme 2 (ACE2) provide anchorage for SARS-CoV-2 binding, thus implicating that ACE and ACE2 might contribute to the variability in infection severity. This study aimed to elucidate predisposing factors influencing the disease course among people infected by SARS-CoV-2, focusing on angiotensin-converting enzyme (ACE) and ACE2 polymorphisms. Notably, despite similar demographics and comorbidities, COVID-19 patients exhibit substantial differences in prognosis. Genetic polymorphisms in ACE and ACE2 have been implicated in disease progression, prompting our investigation into their role in COVID-19 evolution. Using next-generation sequencing (NGS), we analyzed ACE and ACE2 genes in a sample group comprising six subjects infected by SARS-CoV-2. Our findings revealed a correlation between specific polymorphisms and COVID-19 outcomes. Specifically, ACE and ACE2 intronic deletions were observed in all deceased patients, suggesting a potential association with mortality. These results highlight the significance of genetic factors in shaping the clinical course of COVID-19, emphasizing the importance of further research into the impact of genetic variations on COVID-19 severity.

Digital elevation models (DEMs) have a wide range of applications and play a crucial role in many studies. Numerous public DEMs, frequently acquired using radar and optical satellite imagery, are currently available; however, DEM datasets tend to exhibit elevation values influenced by vegetation height and coverage, which can compromise the accuracy of models in representing terrain elevation. In this study, we developed a digital terrain model for South America using a novel methodology to remove vegetation bias in the Copernicus DEM GLO-30 (COPDEM) model using machine learning, Global Ecosystem Dynamics Investigation (GEDI) elevation data, and multispectral remote sensing products. Our results indicate considerable improvements compared to COPDEM in representing terrain elevation, reducing average errors (BIAS) from 9.6 m to 1.5 m. Furthermore, we evaluated our product (ANADEM) by comparison with other global DEMs, obtaining more accurate results for different conditions of vegetation fraction cover and land use. As a publicly available and open-source dataset, ANADEM will play a crucial role in advancing studies that demand accurate terrain elevation representations at large scales.

Chronic kidney disease (CKD) is characterized by a continuous decline in kidney function, often persisting for years or even a lifetime. This study presents a new exploration into the extraction and application of insect chitosan (Tenebrio molitor) targeting hemodialysis (HD). Initially, the potential of insect-derived chitosan as a sustainable and effective alternative to traditional sources (i.e. crustaceans) is demonstrated. Efficient extraction methods were developed (totaling between 6 h and 12 h), producing chitosan. Firstly, chitin was efficiently isolated from T. molitor through deproteinization and demineralization, with yields of approximately 5% (w/w). Subsequently, chitosan was obtained from the extracted chitin resulting in yields of between 65.0 ± 0.8% (w/w) and 79.3 ± 0.8% (w/w). Characterization using Fourier Transform Infrared Spectroscopy (FTIR) confirmed structural similarities with commercial chitosan and degrees of deacetylation in the 73 - 75% range. The bioactive properties of chitosan obtained from T. molitor, including antimicrobial and antioxidant activities, were evaluated. All the microorganisms tested were inhibited, exhibiting minimum lethal concentrations between 2 and 8 mg/mL, confirming the antimicrobial activity of the extracted chitosan. In addition, chitosan showed antioxidant activity in the range of 60 to 65 µmol Trolox equivalent/g, suggesting its viability for various medical applications.This study also developed a chitosan-based membrane (CH - M) culminating in a proof-of-concept phase for hemodialysis. The permeation characteristics of CH-M for urea and albumin were studied in vitro to assess their suitability as HD membranes. Urea was permeable to values of over 70% and albumin was retained.

Urbanization growth has intensified the challenge of managing and treating increasing amounts of municipal solid waste (MSW). Landfills are commonly utilized for MSW disposal because of their low construction and operation costs. However, this practice produces huge volumes of landfill leachate, a highly polluting liquid rich in ammoniacal nitrogen (NH3-N), organic compounds and various heavy metals, making it difficult to treat in conventional municipal wastewater treatment plants (WWTPs). In recent years, research has shown that microbial biofilms, developed on carriers of different materials and called “Moving Bed Biofilm Reactors” (MBBRs), may offer promising solutions for bioremediation. This study explored the biofilm development and the nitrification process of moving bed biofilms (MBBs) obtained from high am-monia-selected microbial communities. Using Crystal Violet Staining and Confocal Laser-Scanning Microscopy, we followed the biofilm formation stages correlating nitrogen removal to metagenomic analyses. Our results indicate that MBBs unveiled a 10-fold more enhanced nitrification rate than the dispersed microbial community pre-sent in the native sludge of the Porto Sant’Elpidio (Italy) WWTP. Four bacterial families, Chitinophagaceae, Comamonadaceae, Sphingomonadaceae, and Nitrosomona-daceae accumulate in structured biofilms and significantly contribute to the high ammonium removal rate of 80% in 24 hours as estimated in leachate-containing wastewaters.

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

Traumatic nerve injuries are common lesions that affect several hundred thousand humans, as well as dogs and cats. The assessment of nerve regeneration trough animal models may provide information for translational research and future therapeutic options that can be applied mutually in veterinary and human medicine, in a one health perspective. This review offers a hands-on vision about the non-invasive and conservative approaches on peripheral nerve injury, focusing the role of neurorehabilitation in nerve repair and regeneration. The peripheral nerve injury may lead to hypersensitivity, allodynia and hyperalgesia, with the possibility of joint contractures, decreasing functionality and impairing the quality of life. The question remains regarding how to improve nerve repair with surgical possibilities, but also considering electrical stimulation modalities by modulating sensory feedback, upregulation BDNF, GFNF, TrKB and adenosine monophosphate, maintaining muscle mass and modulating fatigue. This could be improved by the positive synergetic effect of exercises and physical activity with locomotor training, and other physical modalities, such as low-level laser therapy and ultrasounds. In addition, the use of cell-based therapies is an innovative treatment tool in this field. These strategies may help avoiding situations of permanent monoplegic limbs that could lead to amputation.

The necessity to investigate suitable alternatives to conventional fossil fuels has developed the interests in many renewable energy alternatives, especially biomass resources which are widely available and allow to reach both environmental and socio-economic improvements. Among the bioenergy solutions the anaerobic digestion technology makes it possible to produce biogas by reusing and valorising agricultural residues and by-products. In Southern Italy, to date, the development of biogas sector is still very limited, despite the importance of the agricultural sector, especially of citrus and olive cultivation. For this reason, in previous studies the availability of two by-products, i.e., citrus pulp and olive pomace, was analysed in order to choose the most suitable area for a sustainable development of new biogas plants according to the new Biogasdoneright concept. In this paper, after a resume of the multi-step methodology which allowed the computation of biogas production, it was demonstrated that 15.9 GWh-e electricity and 24.5 GWh-e heat per year could be generate by reusing only these two kind of by-products, and could satisfy approximate 17% of the total electricity demand of the agricultural sector (90.2 GWh-e/year) in Catania.

Water quality assessment stands as a fundamental step in water resource management. In addition to substances and organisms present in the water, land use and land cover are two factors affecting also water quality. This study analyzed the correlation and influence between water quality and land use and land cover in the Miranda River Basin (MRB) and the natural wetlands in the Pantanal Biome. Using a watershed-wide approach, results suggested that water quality management policies can be considered in terms of sub-basins (smaller planning units). The Water Quality Index (WQI) was considered GOOD or EXCELLENT throughout the MRB. It was observed that the natural wetlands have the capacity to contribute to improve WQI, with reductions in thermotolerant coliforms and turbidity; however, high values were found for thermotolerant coliforms, a temporal increasing trend of biochemical oxygen demand (BOD), and a reduction in dissolved oxygen and total phosphorus. Conversely, it was found in these flooded areas a trend of decrease in dissolved oxygen and an increase in BOD concentrations. Natural wetlands play important hydrological and ecological roles in water quality, storing, removing, and cycling nutrients. They are highly relevant areas for defining watershed management and conservation strategies, environmental protection, and providing ecosystem services.

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

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

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

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

I present in this paper Diatomic, an open-source Excel application that calculates molar ther-modynamic properties for diatomic ideal gases. This application is very easy to use and requires only a limited number of molecular constants, which are freely available online. Despite its sim-plicity, Diatomic provides methodologies and results that are usually unavailable in general quantum chemistry packages. This application uses the general formalism of statistical mechanics, enabling two models to describe the rotational structure and two models to describe the vibra-tional structure. In this work, Diatomic was used to calculate standard molar thermodynamic properties for a set of fifteen diatomic ideal gases. Special emphasis was placed on the analysis of four properties (standard molar enthalpy of formation, molar heat capacity at constant pressure, average molar thermal enthalpy and standard molar entropy), which were compared with ex-perimental values. The results obtained lead to the following main conclusions: (i) the theoretical model used to describe rotational structure has a small effect on the accuracy of the results, (ii) at moderate and high temperatures, the Morse model gives better results than the harmonic model, and (iii) at the lowest temperatures both models give similar results.

There is much discussion regarding the Sustainable Development Goals’ (SDGs) capacity to promote inclusive development. While some argue that they represent an opportunity for goal-led alignment of stakeholders and evidence-based decision-making, other voices express concerns as they perceive them as a techno-managerial framework that measures development according to quantitatively defined parameters and does not allow for local variation. We argue that the extent to which the positive or negative aspects of the SDGs prevail depends on the monitoring system’s ability to account for multiple and intersecting inequalities. The need for sub-nationally (urban) representative indicators poses an additional methodological challenge – especially in cities with intra-urban inequalities related to socio-spatial variations across neighbourhoods. This paper investigates the extent to which the SDG indicators’ representativeness could be affected by inequalities. It does so by proposing a conceptual framing for understanding the relation between inequalities and SDG monitoring, which is then applied to analyse the current methodological proposals for the indicator framework of the “urban SDG”, Goal 11. The outcome is a call for 1) a more explicit attention to intra-urban inequalities, 2) the development of a methodological approach to “recalibrate” the city-level indicators to account for the degree of intra-urban inequalities, and 3) an alignment between methodologies and data practices applied for monitoring SDG 11 and the extent of the underlying inequalities within the city. This would enable an informed decision regarding the trade-off in indicator representativeness between conventional data sources, such as censuses and household surveys, and emerging methods, such as participatory geospatial methods and citizen-generated data practices.

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

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

Background: Recent developments in our understanding of the interactions between long non-coding RNA (lncRNA) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein-RNA interaction networks. Results: Analysis of alternative splicing events across 39 lncRNA wildtype and knockout RNA-sequencing datasets from three human cell lines: HeLa (Cervical Cancer), K562 (Myeloid Leukemia), and U87 (Glioblastoma), resulted in high confidence (fdr < 0.01) identification of 4432 skipped exon events and 2474 retained intron events, implicating 759 genes to be impacted at post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockout were specific to the cell type, in agreement with the finding that genes affected by alternative splicing also displayed enriched functions in a cell type specific manner. To understand the mechanism behind this cell-type specific alternative splicing patterns, we analyzed RNA binding protein (RBP)-RNA interaction profiles across the spliced regions. Conclusions: Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron-exon junctions, in a cell type specific manner. The cellular functions affected by alternative splicing were also affected in a cell type specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs due to altered titration of the RBPs from their target loci. We propose that such lncRNA sponges can extensively rewire the post-transcriptional gene regulatory networks by altering the protein-RNA interaction landscape in a cell-type specific manner.

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

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

Antiviral peptides (AVPs) represent a promising strategy for addressing the global challenge of viral infections and their growing resistance to traditional drugs. Lab-based AVP discovery methods are resource-intensive, highlighting the need for efficient computational alternatives. In this study, we developed five non-trained but supervised Multi-Query Similarity Search Models (MQSSMs) integrated into the StarPep toolbox. Rigorous testing and validation across diverse AVP datasets confirmed the models' robustness and reliability. The top-performing model, M13+, demonstrated impressive results with an accuracy of 0.969 and a Matthew’s correlation coeffi-cient of 0.71. To assess their competitiveness, the top five models were benchmarked against 14 publicly available machine learning and deep learning AVP predictors. The MQSSMs outper-formed these predictors, highlighting their efficiency in terms of resource demand and public ac-cessibility. Another significant achievement of this study is the creation of the most comprehensive dataset of antiviral sequences to date.

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

Traditional computer vision techniques aim to extract meaningful information from images but often depend on manual feature engineering, making it difficult to handle complex real-world scenarios. Fractional Calculus (FC), which extends derivatives to non-integer orders, provides a flexible way to model systems with memory effects and long-term dependencies, making it a powerful tool for capturing fractional rates of variation. Recently, Neural Networks (NNs) have demonstrated remarkable capabilities in learning complex patterns directly from raw data, automating computer vision tasks and enhancing performance. Therefore, the use of fractional calculus in neural network-based computer vision is a powerful method to address existing challenges by effectively capturing complex spatial and temporal relationships in images and videos. This paper presents a survey of Fractional Calculus Neural Network-based (FC NN-based) computer vision techniques for denoising, enhancement, object detection, segmentation, restoration, and NN compression. The survey compiles existing FFC NN-based approaches, elucidates underlying concepts, and identifies open questions and research directions. By leveraging FC's properties, FC NN-based approaches offer a novel way to improve the robustness and efficiency of computer vision systems.

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

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

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

Interactions of soil moisture with plant root systems are very important for plant growth. For non-invasive determination of volumetric soil moisture in a rhizobox, a microwave system based on transmittance of electromagnetic waves in the microwave frequency range was developed using microstrip patch antennas. Vector Network Analyzers (VNAs) were used to measure the S-parameters at frequency ranges close to 5 GHz. A transmission system with microstrip patch antennas was developed. The result of this attenuation is in the frequency domain. The antennae were designed as resonant microstrip antennae. The antennae were placed on both sides of a rhizobox, which allowed non-invasive measuring soil moisture in the box. The attenuation (S21(dB)) was used to measure the effect of temperature, and different types of soil; as well as sensitivity, reproducibility and repeatability of the system. In this work we present quantitative results of soil moisture in rhizobox. The microwave technique, using microstrip patch antennas, is a reliable and accurate system, and showed very promising potential applications for rhizobox-based investigations of root performance.