Tuberculosis (TB) caused by Mycobacterium tuberculosis remains a predominant cause of mortality, especially in low- and middle-income nations. Recently antimicrobial peptides were discovered that at low concentrations could stimulate the growth of M. tuberculosis (hormetic response). In this study, such a peptide was used to investigate the effects on the time to positivity (TTP). A systematic substitution analysis of peptide 14D was synthesized using Spot synthesis technology, resulting in 171 novel peptides. Our findings revealed a spectrum of interactions, with some peptides accelerating M. tuberculosis growth, potentially aiding in faster diagnostics, while others exhibited inhibitory effects. Notably, peptide NH2-wkivfiwrr-CONH2 significantly reduced the TTP by 25 hours compared to the wild-type peptide 14D, highlighting its potential in improving TB diagnostics by culture. Several peptides demonstrated potent antimycobacterial activity, with a minimum inhibitory concentration (MIC) of 20 µg/mL against H37Rv and a multidrug-resistant M. tuberculosis strain. Additionally, a reduction in the formation of cord-like structures was observed, which is indicative of reduced virulence and transmission potential. This study underscores the multifaceted roles of antimicrobial peptides in TB management, from enhancing diagnostic efficiency to offering therapeutic avenues against M. tuberculosis.

Antimicrobial peptides (AMPs) can directly kill Gram-positive bacteria, Gram-negative bacteria, mycobacteria, fungi, enveloped viruses and parasites. At sublethal concentrations some AMPs and also conventional antibiotics can stimulate bacteria response to increase their resilience, also called the hormetic response. That can include stimulation of growth, mobility, and biofilm production. Here, we have discovered AMPs that stimulate the growth of certain mycobacteria. Peptide 14 for example showed growth stimulating effect on M. tuberculosis, M. bovis, M. avium subsp. paratuberculosis (MAP), M. marinum, M. avium-intracellulare, M. celatum and M. abscessus. The effect was more pronounced at low bacterial inocula. The peptides induce a faster transition from the lag phase to the log phase and keep the bacteria longer in the log phase before entering the stationary phase compared to non treated control. In some cases, an increase in the division rate was observed. An initial screen using MAP and a collection of 75 peptides revealed 13 peptides with a hormetic effect. For M. tuberculosis a collection of 25 artificial peptides were screened and 9 were found to reduce the time to positivity (TTP), improving growth. A screen of 43 naturally occurring peptides, 11 fragments of naturally occurring peptides and 5 designed peptides, all taken from the APD3, identified a further 44 peptides that also lowered TTP by at least 5%. Lasioglossin LL-III (Bee) and Ranacyclin E (Frog) were the most active natural peptides, the human cathelicidin LL37 fragment GF-17 and a porcine cathelicidin protegrin-1 fragment was the most active fragment of naturally occurring peptides. Peptide 14 showed growth-stimulating activity between 50 ng/ml and 10 µg/ml whereas the stability-optimised peptide 14D had a narrow activity range of 0.1 - 1 µg/ml. Peptides identified in this study are now part of novel products improving the diagnosis of mycobacteria in humans and animals.

This paper discusses the use of networks of Inertial Measurement Units (IMU) for the reconstruction of trajectories from sensor data. Logistics is a natural application domain, to verify the quality of the handling of goods. This is a mass application and the economics of logistics impose that IMUs to be used must be low cost and use basic computational devices. The approach in the paper converts a strategy from the literature, used in the multi-target following problem, to reaching a consensus in a network of IMUs. The paper presents results on how to achieve the consensus in trajectory reconstruction, along with covariance intersection data fusion of the information obtained by all nodes in the network.

Consuming fish sustainably means consuming less and better, considering environmental, social, and economic impacts. This demands more knowledge to make informed decisions. In this study, the main goal was to understand how sustainability education can be used as a tool to raise awareness and promote new habits regarding the sustainable consumption of fish in 4th-grade students at primary school. During the COVID-19 pandemic, face-to-face and online learning methodologies were used in two different groups of students to understand whether the teaching method impacted learning. A sequential explanatory mixed methodology was applied, with a pre-test/post-test design, combined with focus group sessions. Between the pre and post-tests three learning modules were performed. The results showed that the students were unaware of many aspects related to fish sustainable consumption, but the developed activities significantly increased their knowledge of the subject and impacted students to change their consumption behaviours. It was also found that the construction of knowledge by the students after the activities was achieved either by face-to-face or online learning. Interviews from focus group sessions showed that students got to know new fish species, learned about the concept of minimum landing size and closure season and that fish are labelled like other types of food.

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.

High-throughput screening technologies continues to produce large amounts of multiomics data from different populations and cell types for various diseases, such as cancer. However, analysis of such data encounters difficulties due to cancer heterogeneity, further exacerbated by human biological complexity and genomic variability. There is a need to redefine the drug discovery development pipeline, bringing an Artificial Intelligence (AI)-powered informational view that integrates relevant biological information and explores new ways to develop effective anticancer approaches. Here, we show SynPred, an interdisciplinary approach that leverages specifically designed ensembles of AI-algorithms, links omics and biophysical traits to predict synergistic anticancer drug synergy. SynPred exhibits state-of-the-art performance metrics: accuracy – 0.85, precision – 0.77, recall – 0.75, AUROC – 0.82, and F1-score - 0.76 in an independent test set. Moreover, data interpretability was achieved by deploying the most current and robust feature importance approaches. A simple web-based application available online at http://www.moreiralab.com/resources/synpred/ was constructed to predict synergistic anticancer drug combinations requiring only the upload of the two drug SMILES to be tested, allowing easy access by non-expert researchers.

Resumo: Este estudo teve como objetivo avaliar a Saúde Mental Positiva (SPM) e a sua relação com características sociodemográficas, literacia em saúde mental e escala de vulnerabilidade psicológica (PVS) em estudantes universitários portugueses com idades compreendidas entre os 17 e os 62 anos. Foi realizado um estudo descritivo-correlacional. Uma pesquisa online foi realizada para avaliar variáveis ​​demográficas, e vários questionários foram aplicados para avaliar saúde mental positiva, vulnerabilidade psicológica e alfabetização em saúde mental. Os dados foram coletados de 1º de novembro de 2019 a 1º de setembro de 2020. No geral, 3.405 alunos participaram do estudo. Os resultados mostram que 67,8% dos alunos revelaram um alto nível de PMH, 31,6% apresentaram um nível médio de PMH e 0,6% apresentaram um nível baixo de PMH. Os estudantes do sexo masculino relataram maior satisfação pessoal (t (3170) = -2,39, p=0,017) e autonomia (t (3170) = -3,33, p=0,001), no PMH em relação ao sexo feminino. Alunos sem bolsa pontuaram mais alto (t (3.127) = -2,04, p=0,42) no PMH do que alunos com bolsa. Estudantes que não foram deslocados de casa relataram maior (t (3170) = -1,99, p=0,047) Autocontrole em PMH do que aqueles deslocados de sua casa. Estudantes universitários com resultados de PMH mais altos têm resultados de PVS mais baixos e resultados de Alfabetização mais altos. Os achados deste estudo contribuirão para identificar as necessidades de intervenção dos alunos na PMH. Estudantes universitários com resultados de PMH mais altos têm resultados de PVS mais baixos e resultados de Alfabetização mais altos. Os achados deste estudo contribuirão para identificar as necessidades de intervenção dos alunos na PMH. Estudantes universitários com resultados de PMH mais altos têm resultados de PVS mais baixos e resultados de Alfabetização mais altos. Os achados deste estudo contribuirão para identificar as necessidades de intervenção dos alunos na PMH.

ABSTRACT: Psychological vulnerability (PV) and low mental health literacy correlate negatively with higher education students' positive mental health and health behaviours. Levels of mental health literacy limit self-help, adaptative coping strategies and academic success. However, few studies examine the significant differences between students' PV, mental health literacy, positive mental health (PMH) and modifiable behaviours variables. Identifying modifiable vulnerability factors is essential when seeking and providing professional help. Method: A cross-sectional descriptive study was conducted to investigate the differences between modifiable behaviours and PV, mental health literacy, and PMH in higher education students. A sample of 3,600 undergraduate students was recruited, mostly female (78.8%), with an average age of 23 years (SD = 6.68). Results: The majority were women, did not exercise, were dissatisfied with sleep quality time per night (62.1% sleep less than 7 hours per night) and did not engage in leisure activities. Also, most respondents had PV and low literacy levels, particularly at F1, and 67.9% scored in the flourishing group. Results showed significant differences (p<0.001) between gender, age, sleep, exercise, diet, leisure activities and PV, and PMH and literacy. Conclusions: The results identified modifiable vulnerability factors that underpin the design of intervention-targeted programmes to promote literacy and PMH in higher education campuses in Portugal to foster students’ well-being and self-help strategies.

This study aims to analyze the interconnection between the concepts of digital economy and sustainability. These concepts have become popular due to awareness of climate change and increased development and adoption of technologies. Researchers, business leaders and policymakers are exploring the many ways digital technologies can be used to address sustainability issues. Using a systematic literature review with a bibliometric analysis, we examined a sample of 92 studies indexed in SCOPUS to identify research activity on this topic through April 2023. We found that 2022 had the highest number of peer-reviewed papers on the subject, with 31 publications. During the research, we also identified multiple opportunities for this interconnection, such as developing renewable energy and sustainable technological solutions, smart cities and sustainable urbanization, and sustainable consumption. These opportunities enabled by digital technologies allow companies to adopt sustainable business strategies and develop sustainable products. Despite these opportunities, the digital economy presents several challenges that can hinder efforts to achieve sustainability goals, such as increased e-waste, high energy consumption and rising carbon emissions, digital divide, job insecurity, growing monopolies, and data protection. These issues must be addressed to enable optimal use of the opportunities presented in the digital economy to promote sustainability.

The fourth industrial revolution, also known as Industry 4.0, has led to an increased transition towards automation and reliance on data-driven innovations and strategies. Companies in the manufacturing sector are heavily integrating Industry 4.0 technologies, including cloud compu-ting, cyber-physical systems (CPS), big data analytics, horizontal and vertical system integration, the internet of things (IoT), and additive manufacturing (3d printing). The interconnected systems and processes have significantly increased operational efficiency, enhanced organizational capacity to monitor and control functions, reduced costs, and improved product quality. One significant way that companies have achieved these benefits is by integrating diverse sensor technologies within these innovations, allowing critical data collection on products, equipment performance, and maintenance. The sensors connect systems and machines, allowing them to communicate and track operations for enhanced operations. While numerous research has been conducted to show the role of sensors in industry 4.0, limited studies show how these innovations can leverage product design to maximize benefits and opportunities. Given the rapidly changing market conditions, Industry 4.0 requires new products and business models to ensure companies adjust to the current and future changes. These requirements call for the evolutions in product design processes to accommodate design features and principles applicable in the current dynamic business environment. This research paper employs a systematic bibliometric literature review (LRSB) methodology to explore and synthesize data on how Industry 4.0 and sensors can leverage product design. The results show that various product design features create opportunities to be leveraged to guarantee the success of Industry 4.0 and sensor technologies. However, the research also identifies numerous challenges that undermine the ongoing transition towards intelligent factories and products.

The digital transition processes have demonstrated an enormous capacity to develop and implement sustainable solutions, which allow solving several problems such as poverty, high rates of species extinction and lack of equal opportunity. However, little attention is paid to the connection between the digital transition and sustainability. Thus, a systematic review of the bibliometric literature was developed to fill this knowledge gap and demonstrate the potential contributions of the digital transition to environmental, economic and social sustainability aspects. In environmental sustainability, the digital transition involves the application of technologies such as AI, big data analytics, IoT, and mobile technologies that are used to develop and implement sustainability solutions in areas such as sustainable urban development, sustainable production and pollution control. In economic sustainability, emerging digital technologies can drive transformation into the more sustainable circular economy, the digital sharing economy, and establish sustainable manufacturing and infrastructure design. In the digital transition to social sustainability, the studies analyzed demonstrate the need for multidimensional policy perspectives to address the current digital divide. For effective management of the digital transition that achieves sustainability goals, the study discusses alternative approaches that include innovation through experimentation, and dynamic and sustainable advantages achievable through temporary benefits.

Industry 4.0 or the Fourth Industrial Revolution is driven by innovative technologies that have profound effects on both production systems and business models. This revolution is characterized by the addition of disruptive technologies and methods. These aspects of Industry 4.0 have a significant impact on marketing and have led to an evolution to ensure that marketing activities align with technological advancements and address consumers' current needs. The purpose of this paper is to formulate and discuss future research avenues for marketing considering the changes brought by Industry 4.0. The approach taken in the paper is to review the relevant literature and focus on the key themes most important for future research on industry 4.0 and marketing. Therefore, a systematic literature review was conducted based on SCOPUS indexing online database of scientific articles, the most important peer-reviewed peer in the academic world. The paper finds that there are a number of research avenues for marketing researchers to conduct investigations on, but the most important areas are five marketing principles in Industry 4.0: cooperation, conversation, co-creation, cognitivity, and connectivity.

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.

The COVID-19 pandemic has contributed to mental health problems worldwide. Nurses are particularly prone to stress because they directly care for individuals with suspected or confirmed cases of COVID-19. The aim of this study is to explore the association between the mental health promotion strategies used by nurses during the coronavirus disease (COVID-19) outbreak and their symptoms of depression, anxiety, and stress, and to compare the strategies and symptoms of mental health nurses and non-mental health nurses. Cross-sectional study was conducted with a sample of 821 nurses. Portuguese nurses demonstrated high symptoms of depressive symptoms, stress, and anxiety. Healthy eating, physical activity, rest between shifts, maintaining social contacts, verbalizing feelings/emotions, and spending less time searching for information about COVID-19 are associated with better mental health. Mental health nurses have less depression, anxiety, and stress, and use more strategies to promote mental health than other nurses. We consider it important to promote nurses’ mental health literacy by encouraging them to develop skills and strategies aimed at improving their resilience and ability to deal with difficult situations while caring for the population.

The alcoholic fermentation process with agitation/static, followed by the acetic fermentation submerged in banana was evaluated. Kinetics parameters of alcoholic fermentation for the maximum ethanol/glycerol metabolites in agitated process was 29 and 27 h, and in static 47 and 45 h, respectively. For acetic fermentation, the kinetics parameters were medium time of 39.9 h, acetic acid yield of 53.1% and acetic acid productivity of 0.216 g/Lh. Wines from agitated/static process presented 5.73 and 6.81% (v/v) of alcohol content, respectively. Wine obtained by the static process presented higher concentrations of volatile compounds. The vinegar showed 49.2 g/L of acetic acid and the esters concentrations were higher than in wine. The wine and vinegar minerals were consistent with amount observed in the pulp, with an increase in sulphur concentration after alcoholic fermentation and decrease after acetic fermentation. Products showed chemical and composition of sensory and nutritional interest.

The WASP-Index is computed over Iberia for three monthly timescales in 1961-2020, based on an observational gridded precipitation dataset (E-OBS), and in 2021-2070, based on bias-corrected precipitation generated by a six-member climate model ensemble from EURO-CORDEX, under RCP4.5 and RCP8.5. The WASP performance in identifying extremely dry or wet events, reported by the EM-DAT disaster database, is assessed for 1961–2020. An overall good agreement between the WASP spatial patterns and the EM-DAT records is found. The areolar mean values revealed an upward trend in the frequency of occurrence of intermediate-to-severe dry events over Iberia, which will be strengthened in the future, particularly for the 12m-WASP intermediate dry events under RCP8.5. Besides, the number of 3m-WASP intermediate-to-severe wet events is projected to increase, mostly the severest events under RCP4.5, but no evidence was found for an increase in the number of more persistent (12m-WASP) wet events under both RCPs. Despite important spatial heterogeneities, an increase(decrease) of the intensity, duration, and frequency of occurrence of the 12m-WASP intermediate-to-severe dry(wet) events is found under both scenarios, mainly in the southernmost regions of Iberia, thus becoming more exposed to prolonged and severe droughts in the future, corroborating the results from previous studies.

The popular appreciation of dry white wines is most frequently directed to young wines. However, present consumption trends comprise the valorisation of aged dry white wines. Therefore, the present work was aimed at the sensory analysis of these wines with different ages to define their sensory space and to understand which factors drive their quality evaluation by experienced tasters (critics, oenologists and students). Individuals were asked to evaluate several synthetic and aesthetic attributes and to characterise the analytic sensory profile through a Check-All-That-Apply (CATA) methodology. The quality evaluations were differently correlated with wine synthetic parameters according to the taster group. For both critics and oenologists, overall quality scores were driven by persistence and complexity. Moreover, quality was also highly correlated with power for critics and with balance for oenologists. Quality scores were highly correlated with wine browning (absorbance at 420 nm) for critics. The tasting panel showed a homogeneous analytic description of aroma, taste and mouthfeel consistent with wine age. The different ages could be associated to a continuous sensory space characterised by a decreasing perception of freshness and increase in mature and mellowed descriptors. All wines shared an austere in-mouth perception elicited by their acidity, saltiness, bitterness, smoothness and dryness. The age prediction showed that most tasters failed to guess the age wines with more than roughly 13 years old, indicating that tasters were not familiar with the sensory features of white wines with 17 to 46 years old. In conclusion, experienced tasters consistently described the sensory space and recognised the high quality of aged dry white wines. Education programs may use the defined sensory spaces according to aging and to expand the range of quality perception by consumers.

Neonatal palliative care (NPC) is an integrated and holistic approach that is an integral part of the contemporary neonatal treatment delivery paradigm. It is the highest fulfillment of the notion of beneficence (doing or creating 'good') that has otherwise been neglected/underestimated by the focus of modern medicine on technology and instrumental treatments by its commitment to alleviating patient pain and quality of life. For decades, the Double-Effect Doctrine (DDE) has been used to consider and address a range of ethically questionable circumstances, often at the end of life, including euthanasia, termination of pregnancy to save maternal life, and morally justified warfare. The theory has continued to be mired in controversy as ethicists, legal scholars, theologians, and philosophers discuss the abstract concepts of moral reasoning, purpose, foresight, and other underlying moral theories. In this paper, the moral theory of DDE is discussed in its clinical application to the ethical decision-making process in neonatal palliative and end-of-life treatment, specifically 1) the administration of opioids as required for symptom control and 2) the use of palliative sedation for intractable symptom care.

With the increment of the aging population in recent years, neurodegenerative diseases exert a major global disease burden, essentially as a result of the lack of treatments that can stop the disease progression. Alzheimer’s Disease (AD) is an example of a neurodegenerative disease, that affects millions of people globally, with no effective treatment. Natural compounds have emerged as a viable therapy to fill a huge gap in AD management, and in recent years, mostly fuelled by the Covid-19 pandemic, RNA-based therapeutics have become a hot topic in the treatment of several diseases. Treatments of neurodegenerative diseases face significant limitations due to the complex and interconnected pathways that lead to their hallmarks and, also due to the necessity to cross the blood–brain barrier. Nanotechnology has contributed to surpass this bottleneck in the treatment of AD, by promoting safe and enhanced drug delivery to the brain. In particular, exosome-like nanoparticles, a hybrid delivery system combining exosomes and liposomes' advantageous features, are demonstrating great potential in the treatment of central nervous system diseases.

Fogo (Fogo island, Cape Verde Republic) is the youngest and most active volcano of the archipelago. The last eruption occurred in 2014–2015. Aiming at studying dust emissions and transport during the eruption period and assessing their impact on air quality and human health, a mineralogical and chemical characterization was undertaken in outdoor dust from all over the island, as well as in the lava resulting from this event. Air quality monitors were used to obtain concentrations of atmospheric particulate matter (PM) and gaseous pollutants. The mineralogical constitution of the samples was analysed by X-ray diffraction and Electron Microprobe, while the chemical characterization was performed through X-ray Fluorescence Spectrometry and ICP-MS. The volcanic rock was found to be tephritic to basanitic, with high potassium content. Several minerals were identified, such as titanian augite with ilmenite, basaltic hornblendes, pyrrhotites, apatites, pyroxenes, basaltic hornblendes and hematites. Concentrations of the particulate matter inhalable fraction (PM10) exceeded the 24-hour mean of 50 µg/m3 recommended by the World Health Organization. Nevertheless, total volatile organic compounds (TVOCs) showed levels lower than the worrying range. The highest levels of CO2 were recorded in more populated villages and farthest from the volcano. The Pollution Load Index (PLI) for outdoor dust collected on rooftops was always above 1, suggesting enrichment, with higher values in the dust size fraction < 63 µm. In the same way, the Contamination Factor pointed to high enrichment of As, Ni and Pb, and very high enrichment of Cd in the same size fraction. The Non-carcinogenic Hazard Quotient and Hazard Index estimated for Children suggest that health problems may arise. The Carcinogenic Risk, for all size fractions, was above the target risk. The element that most contributed to the global risk was As, followed by Pb and Co. Ingestion was the main exposure route for all size fractions. The dust size fraction that represented the highest risk was < 63 µm, mostly due to the As concentration.

Ionic liquids have been recognised as interesting solvents applicable in the efficient lignocellulosic biomass valorisation, especially in the biomass fractionation into individual polymeric components or direct hydrolysis some of biomass fractions. Considering the chemical character of ionic liquids, two different approaches, paved the way for a fractionation of biomass. The first strategy integrated a pre-treatment, hydrolysis and conversion of biomass through the employment of hydrogen-bond acidic 1-ethyl-3-methyimidazolim hydrogen sulfate ionic liquid. The second one relied on the use of a three-step fractionation process with hydrogen-bond basic 1-ethyl-3-methylimidazolium acetate to produce high purity cellulose, hemicellulose and lignin fractions. The proposed approaches were scrutinised for wheat straw and eucalyptus residues. Those different biomasses allowed understanding that enzymatic hydrolysis yields are dependent on the crystallinity of pre-treated biomass. The use of acetate based ionic liquid allowed to change crystalline cellulose I to cellulose II and consequently enhanced glucan to glucose yield to 93.14.1 mol% and 82.91.2 mol% for wheat straw and eucalyptus, respectively. Whereas for hydrogen sulfate ionic liquid, the same enzymatic hydrolysis yields were 61.6  0.2 mol% for wheat straw and only 7.90.3 mol% for eucalyptus residues. These results demonstrate the importance of either ionic liquid character or biomass type on the efficient biomass processing.

This study aims to determine the role of Industry 4.0 sensors in digital transformation. Using a systematic literature review with a bibliometric analysis, we examine a sample of 52 studies from the SCOPUS database to identify research activity on this topic until December 2022. We find that 2022 was the year with the highest number of peer-reviewed documents on the subject, with 18 publications. We also examine current themes and find that sensors can connect multiple systems and devices, thus enabling machine-to-machine communication and facilitating great precision during product designing, development, and production, thus enabling customization and improving quality. However, despite these benefits, the current sensor technologies face multiple challenges that undermine their maximum adoption.

The term fuzzy refers to things that are unclear or vague. In the real world, we often encounter a situation where we cannot determine whether the state is true or false, and fuzzy logic allows for more flexible reasoning. This is a form of multivalued logic where the truth values ​​of variables can be any real number between 0 and 1, as opposed to Boolean logic where the logical values ​​can only be 0 or 1. Fuzzy logic is therefore a problem-solving technique used to evaluate all available information and thus make the best decisions. When applied to marketing, fuzzy logic allows treating customers in an individual and personalized way, instead of being fully identified within a particular market segment. Fuzzy marketing considers the degree to which a customer belongs to certain segments and subsequently allows them to be targeted with messages that engage them emotionally. To better understand the application and importance of fuzzy logic in marketing strategy, we developed a systematic review of the bibliometric literature (LRSB). It was possible to create a connection between these concepts, marketing and fuzzy logic, to increase the efforts of marketing professionals to achieve competitiveness in the unpredictable business environment.

Big data analytics tools are the use of advanced analytic techniques targeting large and diverse volumes of data that include structured, semi-structured, and unstructured data from different sources and in different sizes from terabytes to zetabytes. The health sector is faced with the need to generate and manage large data sets from various health systems, such as electronic health records and clinical decision support systems. This data can be used by providers, clinicians, and policymakers to plan and implement interventions, detect disease more quickly, predict outcomes, and personalize care delivery. However, little attention is paid to the connection between big data analytics tools and the health sector. Thus, a systematic review of the bibliometric literature (LRSB) was developed to study how the adoption of big data analytics tools and infrastructures will revolutionize the healthcare industry. The review integrated 77 scientific and/or academic documents indexed in SCOPUS presenting up‐to‐date knowledge on current insights on how big data analytics technologies influence the healthcare sector and the different big data analytical tools used. The LRSB provides findings related to the impact of Big Data analytics on the health sector by introducing opportunities and technologies that provide practical solutions to various challenges.

The unstable international economic situation is reflected in the supply chain stress, lack or increased cost of some raw materials, fuel or semi-finished products is forcing organizations to perform new optimization initiatives in the utilization of their equipment and assets pointed to obtain the maximum value from them, while maintaining and even improving the quality of their products. The achievement of these objectives involves the reduction or minimization of equipment downtime to maintain the advantage over their competitors and ensure the organization's competitiveness. The intelligent maintenance system (IMS) provides adequate support for decision-making related to equipment maintenance, since poor maintenance results in unplanned stoppages, with the consequent additional cost and increased customer dissatisfaction, and an over-maintenance can result in an additional labor cost, time and the replacement of parts that are in good conditions. The utilization of new tools and technologies introduced by Industry 4.0 offers multiple opportunities for enhancement through communication and computerized data processing, aiming to improve the maintainability of a hydrogen compressor using neural networks based on attention mechanisms combined with linear regression.

TB and HIV continue to increase and constitute major public health concerns worldwide, mainly in resource-limited countries, showing that we are not going to end HIV if we do not also end TB. Herein, we investigated the risk factors related to HIV infection among TB patients in Luanda, the capital city of Angola. This was a retrospective cohort study conducted on the medical records of 117 TB patients from January to September 2016. Overall, the HIV/TB co-infection rate was 12%. The mean age of coinfected patients was 37.7±10.1 years. No statistically significant relationship was observed between sociodemographic or clinical features with HIV/TB co-infection (p>0.05). TB patients aged 30 years or older (OR: 4.13, p=0.072), female (OR: 1.08, p=0.898), residing in urbanized areas (OR: 1.90, p=0.578), with a history of treatment abandonment (OR: 3.74, p=0.083), with polyresistance (OR: 1.62, p=0.603), and MDR-TB (OR: 2.00, p=0.454), were more likely to have HIV/TB co-infection, while latent TB infection (OR: 0.63, p=0.559) and treatment-susceptible TB patients (OR: 0.56, p=0.616), presented a lower chance of HIV/TB coinfection. Our finding showed a slightly high HIV/TB coinfected rate, which suggests that the dual HIV/TB epidemic keeps evolving and poses a huge concern to the public health in Angola. Further studies on features related to HIV/TB coinfection and its impact on disease progression and clinical outcome in adults from high-risk Angolan communities, should be carried out to intensify and strengthen collaborative activities between national TB and HIV programs in Angola.

In this paper we use the Mellin convolution theorem, which is related to Perron's formula. Also we introduce new explicit formulae for arithmetic function which generalize the explicit formulae of Weil for other arithmetic functions different from the Von-Mangoldt function.

The international literature shows a polarised debate on the impacts of climate change on migration. Some studies find a positive linkage, whereas others find a negative one. It is, without a doubt, a complex process better considered case-specific. There is no available information on the relationship between climate change and migration in Colombia, despite past research exploring each of these subjects independently. This study intends explicitly to investigate this linkage gap. Consequently, this paper's essential contribution is that it builds a bridge between climate change scenarios and migratory science for the first time in Colombia. Despite their limitations, the theoretical and methodological framework suggested by IOM (2009b pp. 86, Section B, Chapter II) is demonstrated in this study to be very valid since it provides a methodology to predict where future flows will occur (based on past evidence). The methodological approaches of SLA and NELM explained in section A in the IV Chapter are also valuable for analysing and approaching this study's conclusions. The primary conclusions of this study indicate that the "Coffee Region," Valle, and Atlantic (or Caribbean Coast) provinces that mainly send emigrants to Spain and the US are the key internal regions responsible for most of the international migration from Colombians. The same areas are especially vulnerable to the impacts of upcoming climate change in the A1B scenario produced by the IDEAM (2010) for 2040 and 2100. Thus, future flows of migrants are expected from these regions (2040-2100). However, issues such as visa requirements or the costs associated with migration constitute international barriers to this flow. The sensitivity of these regions can also be associated with internal migration flows, more armed conflict, and forced displacement in a cyclical process. Theoretically, a resurgence of Colombia's armed conflict and displacement due to climate change can be expected. However, the need for empirical studies in Colombia to support this analysis is imperative and is the most crucial recommendation arising from this study.

DFT-D3 calculations based on structural X-ray diffraction data obtained for 3-oxo-camphorsulfonyl imine (1), camphorsulfonyl chloride (2) and seven camphor sulfonimines (O2SNC10H13NR, L1-L7) from which L2 (R=4-OHC6H4), L4 (R=4-ClC6H4) and L6 (R=3,5-(CH3)2C6H3) are new, provide information into the intra and inter molecular interactions with concomitant elucidation of the supramolecular arrangement of the compounds. The DFT D3 calculations performed in small clusters of 2 or 3 molecular units reproduce the interactions observed by X-ray analyses showing that as a general trend the structural arrangement of the molecules is driven by electronic rather than by packing parameters. In all compounds the self-assembly of 3D structures involves the sulfonyl imine group ( NSO2) either to establish hydrogen bonds, through the oxygen atoms or non-classic oxygen-aliphatic hydrogen or non-bonding interactions (NBI) which also involve the sulfonyl oxygens. Interestingly, the camphor sulfonimine compounds (L2, L3) having protic groups (R=C6H4X: X=OH, L2 or X=NH2, L3) at the aromatic imine substituents (=NR) present an extra π-π stacking which is absent in the other compounds aromatic derivatives. The X-ray analysis shows that all the reported camphor sulfonimine compounds display the E configuration with respect to the imine substituent (R). The study of the redox behavior of the compounds by cyclic voltammetry allows an insight into the solution properties of the compounds and the rationalization of the molecular interactions that stand in the solid and solution states. Camphor sulfonimine compounds (L) display appropriate binding atoms to coordinate transition metals. The herein results show that monodentate coordination through the nitrogen atom of the sulfonimine 5-membered ring to the {Ag(NO3)} metal center is favored. When this imine nitrogen atom is not itself involved in the Organic Framework DFT-D3 calculations shows that the complexation does not affect the non-covalent interactions that are reproduced in the MOF structure.

The number of people with gluten-related illnesses has been increasing and the available treatments include the introduction of a gluten-free diet. In the bakery industry, there are problems with gluten-free products, namely the important characteristics that this component gives to doughs and the low nutritional value they present. A disease that has also increased in recent years is diabetes mellitus, which is characterized by a lack of insulin and the effectiveness of its action (type 1 diabetes) or tissue insensitivity to the hormone (type 2 diabetes). In terms of treatments, there are several approaches: inhibition of digestive enzymes (α-amylase and α-glucosidase) or techniques based on mechanisms of action (stimulation of insulin production and release, insulin transport and decreased glucose absorption). Hyperglycemia is also associated with the production of reactive oxygen species, which leads to cell apoptosis. On the other hand, there was also an association with high levels of cholesterol in the body, which contributed to the development of other types of diseases. In this sense, macroalgae have been studied as a source of natural compounds and used as food supplements, due to their protein, amino acid and mineral content, and the anti-diabetic effect in controlling the glycemic index, oxidative stress and cholesterol have already been demonstrated. Seaweed emerges as a promising source of bioactive nutraceuticals for individuals with coeliac disease, diabetes, and hyperglycemia. The rising prevalence of gluten-related illnesses calls for effective treatments, and seaweed's potential in enhancing the nutritional value of gluten-free products is noteworthy. Additionally, its demonstrated anti-diabetic effects, including glycemic index control, oxidative stress reduction, and cholesterol management, make it a valuable dietary supplement. Further research is needed to explore the specific bioactivities of seaweed compounds and their mechanisms of action. Integrating seaweed-based nutraceuticals into diets could complement traditional treatments, offering potential health benefits to those with coeliac disease and diabetes.

The World Health Organization estimates that every year air pollution kills seven million people worldwide. As it is expected that climate change will affect future air quality patterns, the full understanding of the links between air pollution and climate change, and how they affect human health, are challenges of future research. In this scope, a methodology to assess the air quality impacts on health was developed. The WRF-CAMx modelling framework was applied for the medium-term future climate (considering the SSP24.5 scenario) and for the recent past (considered as baseline). Following the WHO recommendations, mortality health indicators were used to estimate health impacts of long-term exposures. For that, the Aveiro Region, in Portugal, was considered as a case study. Future climate results indicate the occurrence of higher temperatures, and lower total precipitation. Despite that, improvements in the main pollutants’ concentrations, and consequently in the reduction of the related premature deaths are foreseen, mainly due to the reduction of pollutants emissions imposed by the European legislation for the upcoming years. The applied approach constitutes an added value in this research field, being crucial to anticipate the effects of climate change on air quality and evaluate their impacts on human health.

In this work, an embroidered textile moisture sensor is presented. The sensor is based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidery conductor yarn composed by 99% pure silver plated nylon yarn 140/17 dtex. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 25% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity. Moreover, the reproducibility of the sensor performance subject to the manufacturing process variability and washing process is also evaluated. The results show that the manufacturing variability introduce a moisture measurement error up to 4%. The washing process impact on the sensor behavior after applying the first washing cycle implies a sensitivity reduction higher than 14%. Despite these effect, the textile sensor keeps its functionality and can be reused in standard conditions. Therefore, these properties point out the usefulness of the proposed sensor to develop wearable applications on health and fitness scope including the user needs to have a life cycle longer than one-time use

Digital transformation can become a complex process when workers have insufficient skills, which makes training in the digital field essential. Herein, we intended to relate digital literacy perceived by workers with their training needs for the Portuguese public sector context. Additionally, based in the Human capital theory, we also investigate which professional/demographic characteristics increase training propensity in digital fields. Through an online questionnaire, a dataset with information on 573 workers was obtained. Data analysis was made by using a probabilistic regression model and additional statistical techniques. The results revealed that workers with higher levels of education and higher professional skills have higher probability of participating in training in the digital field. On average, workers reveal low levels of digital knowledge and low participation in training in the digital fields, but the majority present a willingness to participate in future training sessions, especially in the fields of Dataset management, Cybersecurity and Communication systems. This study provides information on training in the digital field of workers in the public sector, which is essential for public organizations to better prepare for digital transformation. Additionally, it contributes to a very recent literature on digital learning, and it can be extended to other contexts.

The assessment of aridity conditions is a key factor for water management and the implementation of mitigation and adaptation policies in agroforestry systems. Towards this aim three aridity indices were computed for the Iberian Peninsula (IP): the De Martonne Index (DMI), the Pinna Combinative Index (PCI), and the Erinç Aridity Index (EAI). These three indices were first computed for the baseline period 1961‒1990, using a gridded observational data (E-OBS), and, subsequently, for the periods 2011‒2040 (short-range) and 2041‒2070 (medium-range) using an ensemble of six Regional Climate Models (RCMs) experiments generated by the EURO-CORDEX project. Two Representative Concentration Pathways (RCPs) were analyzed, an intermediate anthropogenic radiative forcing scenario (RCP4.5) and a fossil-intensive emission scenario (RCP8.5). Overall, the three indices disclose a strengthening of aridity and dry conditions in central and southern Iberia until 2070, mainly under RCP8.5. Strong(weak) statistically significant correlations were found between these indices and the total mean precipitation (mean temperature) along with projected significant decreasing(increasing) trends for precipitation(temperature). The prevalence of years with arid conditions (above 70% for 2041‒2070 under both RCPs) are projected to have major impacts in some regions, such as southern Portugal, Extremadura, Castilla-La Mancha, Comunidad de Madrid, Andalucía, Región de Murcia, Comunidad Valenciana, and certain regions within the Aragón province. The projected increase in both the intensity and persistence of aridity conditions in a broader southern half of Iberia will exacerbate the exposure and vulnerability of this region to climate change, while the risk of multi-level desertification should be thoroughly integrated into regional and national water management and planning.

Recently Palle has investigated the chiral vorticity and Cartan torsion in neutrino asymmetries. In his case he addressed this problem in Goedel s like anisotropic Einstein-Catan cosmology. In this paper we discusse how these ideas applied to sheared Bianchi types I Einstein-Cartan (EC) neutrino amisotropic cosmology, affect the handness of neutrinos in the universe. Actually here a novel concept of the chiral metric is introduced where metric functions also possess two distinct signs as in neutrino flipping or helicity. The axial anomaly equation for neutrinos in the presence of torsion and metric chirality is shown to produce left-handed neutrinos from right-handed torsion. Metric chirality is shown to be able to define how the metric would behave far away of neutrino density. Chiral flipping of the chiral neutrinos in the presence of torsion is also investigated. It is shown that when the chiral torsion is left-handed the chemical chiral potential vanishes as the universe expands.

The marketing industry is rapidly evolving, necessitating educational programs to adapt and equip graduates with relevant skills and knowledge. This systematic literature review with bibliometric analysis (SLRBA) explores the integration of Problem-Based Learning (PBL) in marketing education. PBL is an instructional strategy that empowers students to solve real-life problems by integrating theory and practice, thus fostering critical thinking and decision-making skills. Our review synthesizes data from 71 sources, highlighting the definition of PBL, strategies to promote its implementation in marketing education, and the benefits and challenges associated with this approach. The findings indicate that PBL enhances student engagement, provides hands-on experience, and prepares students for real-world marketing challenges. Strategies such as using social media, serious games, e-learning, and feedback mechanisms are discussed for their effectiveness in promoting active learning and student participation. Despite its advantages, PBL faces challenges such as resource intensiveness, student resistance, and information integrity issues. This review underscores the importance of PBL in bridging the gap between theoretical knowledge and practical application, ultimately preparing marketing students to meet the demands of the industry. The paper concludes with recommendations for future research and best practices for implementing PBL in marketing education.

Patients with heart failure have difficulty in self-care management, as daily monitoring and recognizing symptoms do not readily triggers an action to avoid hospital admissions. The purpose of this study was to understand the impact of a nurse-led complex intervention on symptom recognition and fluid restriction. A latent growth model was designed to estimate self-care management and quality of life changes on patients with heart failure and assessed by a pilot study, for three months, to sixty-three patients (33 control, 30 intervention). Patients in the control group had a higher risk of hospitalisation (IRR 11.36; p<.001) and emergency admission (IRR 4.24; p<.001) at three-months follow-up. Analysis of the time scores demonstrated that the intervention group had a clear improvement in self-care behaviours (βSlope. Assignment_group=-.881; p<.001) and in the quality of life (βSlope. Assignment_group=1.739; p<.001). This study supports that a nurse-led program on symptom recognition and fluid restriction can have a positive impact on self-care behaviours and quality of life in patients with heart failure.

Patients with heart failure have difficulty in self-care management, as daily monitoring and recognizing symptoms do not readily trigger an action to avoid hospital admissions. The purpose of this study was to understand the impact of a nurse-led complex intervention on symptom recognition and fluid restriction. A latent growth model was designed to estimate self-care management and quality of life changes on patients with heart failure and assessed by a pilot study, for three months, to sixty-three patients (33 control, 30 intervention). Patients in the control group had a higher risk of hospitalisation (IRR 11.36; p<.001) and emergency admission (IRR 4.24; p<.001) at three-months follow-up. Analysis of the time scores demonstrated that the intervention group had a clear improvement in self-care behaviours (βSlope. Assign-ment_group=-.881; p<.001) and in the quality of life (βSlope. Assignment_group=1.739; p<.001). This study supports that a nurse-led program on symptom recognition and fluid restriction can have a positive impact on self-care behaviours and quality of life in patients with heart failure.

Arbutus unedo L. is a resilient tree with a circum-Mediterranean distribution. Besides its ecological relevance, it is vital for local economies as a fruit tree. Several microorganisms are responsible for strawberry tree diseases leading to production constrictions. Thus, the development of alternative plant protection strategies is necessary and bacteria endophytes may increase their host overall fitness and productivity. As agricultural practices are a driving factor of microbiota, this paper aimed to isolate, identify and characterize endophytic bacteria from strawberry tree leaves from plants growing spontaneously in a natural environment as well as from plants growing on orchards. 62 endophytes were isolated from leaves and identified as Bacillus, Paenibacillus, Pseudomonas, Sphingomonas and Staphylococcus. Although a slightly higher number of species was found in wild plants, no differences in terms of diversity indexes were found. Sixteen isolates were tested in vitro for their antagonistic effect against A. unedo mycopathogens. B. cereus was the most effective antagonist causing a growth reduction of 20% in Glomerella cingulata and 40% in Phytophthora cinnamomi and Mycosphaerella aurantia. Also, several endophytic isolates exhibited plant growth-promoting potential. This study provides insights into the diversity of endophytic bacteria in A. unedo leaves and their potential role as growth-promoters and pathogen antagonists.

Poly(vinylidene fluoride) nanocomposites processed with different morphologies, such as porous and non-porous films and fibres, have been prepared with silica nanoparticles (SiNPs) of varying diameter (17, 100, 160 and 300 nm) which in turn have encapsulated perylenediimide (PDI), a fluorescent molecule. Structural, morphological, optical, thermal, and mechanical properties of the nanocomposites, with SiNP filler concentration up to 16 wt% were evaluated. Further, cytotoxicity and cell proliferation studies were performed. All SiNPs are negatively charged independently of the pH and more stable from pH 5 upwards. The SiNPs introduction within the polymer matrix increases the contact angle independently of the nanoparticle diameters and the smallest ones (17 nm) improve the PVDF Young modulus from 0.94 ± 0.04 GPa for the pristine polymer film to 1.05 ± 0.06 GPa. Varying filler diameter, physico-chemical, thermal and mechanical properties of the polymer matrix were not significantly affected. Finally, the SiNPs inclusion does not induce cytotoxicity in murine myoblasts (C2C12) after 72 h of contact and proliferation studies reveal that the prepared composites represent a suitable platform for tissue engineering applications, as they allow to combine the biocompatibility and piezoelectricity of the polymer with the possible functionalization and drug encapsulation and release of the SiNP.

An accurate, economical, and reliable device for detecting falls in persons ambulating with the assistance of an orthopedic walker is crucially important for the elderly and patients with limited mobility. Existing wearable devices such as wristbands are not designed for walker users, and patients may not wear them at all times. This research proposes a novel idea of attaching an internet-of-things (IoT) device with an inertial measurement unit (IMU) sensor directly to an orthopedic walker to perform real-time fall detection as well as activity logging. A dataset is collected and labeled for walker users in four activities, including idle, motion, step, and fall. Classic machine learning algorithms are evaluated using the dataset by comparing their classification performance. Deep learning with convolutional neural network (CNN) is also explored. Furthermore, the hardware prototype is designed by integrating a low-power microcontroller for onboard machine learning, an IMU sensor, a rechargeable battery, and Bluetooth wireless connectivity. The research results show the promise of improved safety and well-being of walker users.

In this work, two embroidered textile moisture sensors are characterized with three different conductive yarns. The sensors are based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidered conductor yarn. The performance comparison of 3 different type of conductive yarns has been addressed. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 30% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity and the used conductor yarns. This dependence points out the optimum conductive yarn to be used to develop wearable applications for moisture measurement.

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

The Autopoiesis and Cognition Theory (ACT), by Maturana and Varela, based on the notions of Biological Closure and Structural Coupling, is a well-known theory on how to understand biological organization [1, 2, 3]. Although, for example, the Free Energy Principle framework evokes some entailments of autopoiesis in a more formal setting [4, 5]; and ACT has been used in many fields, its impact has been restricted because it lacks quantitative analysis. Here we present a theoretical framework grounded in accepted and well-developed ideas from Mathematics and Physics which advance the understanding of the Principles of Biological Organization under the guidance of Biological Closure and Structural Coupling. The disciplines of Differential Geometry/Topology, Mechanics and Complex Dynamical Systems provide a powerful, elegant, and well-established body of knowledge to support our Biological Organization Principles (BOP) framework. In particular, Stochastic Mechanics and KAM theory (from Kolmogorov, Arnold and Moser theorem) allow us to develop, using the notions of Biological Closure and Structural Coupling, a central core of BOP termed Dynamical Closure Mechanism. Under the proposed framework, a wide variety of bio- logical phenomena can be understood, shedding new light on biological explanations. However, an understanding of biological organization may require the re-evaluation of dogmas on how we think on biology as it seems inescapable that what is needed is an integration of analysis and notions derived from mathematics, physics, and biology to generate a new landscape of ideas.

(1) Background: The purpose of this study was to investigate the relationship between IMO and burnout while assessing the contribution of job demands and resources on increasing internal orientation and worker well-being and, consequently, the levels of perceived performance; (2) Methods: Data were collected between April and December 2021 by completing an online questionnaire, developed in the Google Forms platform. The following descriptive statistics were analyzed: measures of central tendency (mean), dispersion (standard deviation), minimum value and maximum value. Next, Pearson's correlation coefficient was calculated to analyze the relationship between the variables under study.; (3) Results: The results showed the mediating effect of IMO between performance feedback and perceived performance, while burnout mediates the relationship between emotional and technology demands and perceived performance. (4) Conclusions: These conclusions demonstrate that constructive feedback might help a more efficient performance through better internal communication and the positive effects of technology demands could be the result of the interaction between personal and organizational resources.

Across Central Asia, agriculture largely depends on irrigation due to arid and semi-arid climatic conditions. Water is abstracted from rivers, which are largely fed by glacier melt. In the course of climate change, glaciers melt down so that a reduced glacier volume and reduced water runoffs are expected being available for irrigation. Tree wind breaks are one option to reduce water consumption in irrigated agriculture and build resilience against climate change. This paper therefore assessed water consumption of major crops (cotton, wheat, corn, rice, potato, and barley) in Kyrgyzstan and adjacent areas in combination with tree wind breaks. Crop water consumption was assessed through the Penman Monteith approach. Tree wind break types investigated were single rows from poplars and multiple rows with undergrowth by elm and poplar, respectively. Tree water consumption was determined through sapflow measurements. Seasonal ETo for field crops was 876 mm to 995 mm without wind breaks and dropped to less than half through multiple row wind breaks with undergrowth (50 m spacing). Tree water consumption was 1125 mm to 1558 mm for poplar and 435 mm for elm. Among the wind break crop systems, elm wind breaks resulted in highest reductions of water consumption, followed by single row poplars, at spacing of 50 m and 100 m, respectively. Yet, elm grows much slower than poplar so that poplars might be more attractive for farmers. Furthermore, single row wind breaks might by much easier to be integrated into the agrarian landscape, as they consume less space.

Algorithmic systems used in healthcare contexts are primarily developed for the benefit of the public. It is therefore essential that these systems are trusted by the individuals for whose benefit they are deployed. Drawing inspiration from the principles embedded in the testing of the safety, efficacy and effectiveness of new medicinal products, concurrent design engineering and pro-fessional certification requirements, the authors propose, for the first time, a preliminary com-petency-based ‘Algorithmic Ethics’ Effectiveness Impact Assessment’ framework for developers of AI systems used in healthcare contexts. They concluded that this set of principles should en-compass the algorithmic systems ‘production lifecycle’, to guarantee the optimized use of the AI technologies, avoiding biases and discrimination while ensuring the best possible outcomes, simultaneously increasing decision-making capacity and the accuracy of the results. As AI is as good as those who program it and the system in which it operates, the robustness and trustworthiness of their ‘creators’ and ‘deployers’, should be fostered by a certification system guaranteeing the latter’s knowledge and understanding of ethical aspects as well as their com-petencies in integrating these aspects in trustworthy AI systems when used in healthcare con-texts.

Sword-duels are interesting, from a game-theoretical perspective, as they correspond to sudden-death interactions between players (i.e., defeat means removal from the game), and where victory/defeat depend on not just skill, but also luck. Analyzing probabilities of victory streaks, given a certain level of self and others' skill, is thus relevant for any application domain that can be modeled in the same way. This paper takes inspiration from Miyamoto Musashi, famously undefeated for 61 duels, and implements a Markov-chain Monte-Carlo simulation approach to evaluate this scenario. Results suggest that a 61 victory streak can be probabilistically observed when skill level is roughly 6.5 times that of the average duelist, and with 95\% confidence when skill level is roughly 1000 times that of the average duelist. More generally, this paper provides a method for determining chances of victory streaks in game-theoretical sudden-death encounters, when both "skill" and "luck" contribute to the outcome of the encounter. Specific scenarios can be modeled by modifying the utilized Markov chain and adjusting sampled distributions as required.

Probabilistic latent semantic analysis is a statistical technique developed for information retrieval and spanned many fields. It yields intuitive and solid results. However, the rigidity of the assumptions and the iterative nature derived from the Expectation-maximization algorithm generate several problems, dividing detractors and enthusiasts. In this manuscript, we first describe the Probabilistic latent semantic analysis. After, we discuss reformulations that attempt to solve these problems. We pay special attention to the works relating Probabilistic latent semantic analysis and the Singular value decomposition Theorem. Also, Probabilistic latent semantic analysis can be the basis for other techniques, such as kernelization or probabilistic transfer learning, and those that extend the descriptive character of the Principal component analysis to an inferential tool and open a window of opportunities.

Summer annual species are the most widely grown crops in the Upper Midwest, but reliance on a summer annual system has led to excessive soil and nutrient loss when crops are not present. Integrating winter rye (Secale cereale L.), known for its hardiness and environmental benefits, into the rotation can address these issues. However, there's limited understanding of the phenotypic diversity in winter rye during key growth stages that overlap with the typical planting dates for corn (Zea mays L.), soybean [Glycine max (L.) Merr], and late-planted crops like dry bean (Phaseolus vulgaris L.). Thus, the objectives of this study were to evaluate changes in biomass accumulation and quality of winter rye and triticale (x Triticosecale Wittmack) cultivars at three growth stages. Twenty cultivars were assessed over the 2014-2015 and 2015-2016 growing seasons across three environments in Minnesota. Winter rye and triticale were harvested for biomass at the tillering, booting, and soft dough growth stages and rye biomass yield and quality [i.e., crude protein, neutral detergent fiber (NDF), and 48-hour digestibility (NDFD)] were determined following harvest. Overall, there was little variation in each parameter among the cultivars within a location and growth stage. NDFD had some variation at the soft dough stage where digestibility ranged from 273 to 324 g kg-1 at the Crookston site and 332 to 406 g kg-1 at the St. Paul site. The lack of difference between cultivars indicates a wide range of choice when selecting a winter rye cultivar.

In the field of robotics education, introductory courses would ideally utilize heavy industrial arms for hands-on learning. This would provide students with valuable experience in joint programming, which involves direct control of each joint motor in the arm to accomplish desired path planning and differential movements. This practice requires consideration of the physical dynamics of the arm. However, the use of heavy industrial arms has several drawbacks. They are large and expensive, require specialized maintenance, can pose safety risks, and they typically do not allow for direct control of the joint motors. One solution is to use a small, lightweight, toy-like arm. While these are cost-effective and provide direct access to the joint motors without posing safety risks, their lightweight construction means they exhibit minimal dynamic behavior, which limits their educational value. Another solution involves a robotic arm simulator that uses a virtual arm. However, a virtual arm doesn't offer the same level of hands-on engagement and excitement as a physical arm. We propose a hybrid solution that combines a small physical arm with a virtual arm. This approach provides students with the experience of working with an industrial arm, but without the associated difficulties. We demonstrate how this approach successfully improved the completion rate of joint programming assignments, offering a promising solution for practical robotics education.

Proteins and DNA exhibit key physical chemical properties that make them advantageous for building nanostructures with outstanding features. Both DNA and protein nanotechnology have growth notably and proved to be fertile disciplines. The combination of both types of nanotechnologies is helpful to overcome the individual weaknesses and limitations of each one, paving the way for the continuing diversification of the structural nanotechnologies. Recent studies have implemented a synergistic combination of both biomolecules to assemble unique and sophisticate protein-DNA nanostructures. These hybrid nanostructures are highly programmable and display remarkable features that create new opportunities to build in the nanoscale. This review focuses on the strategies deployed to create hybrid protein-DNA nanostructures. Here, we will discuss strategies such as polymerization, spatial directing and organizing, coating, rigidizing or folding DNA into particular shapes or moving parts. The enrichment of structural DNA nanotechnology by incorporating protein nanotechnology has been clearly demonstrated and still shows a large potential to create useful and advanced materials with cell-like properties or dynamic systems. It can be expected that structural protein-DNA nanotechnology will open new avenues in the fabrication of nano-assemblies with unique functional applications and enrich the toolbox of bionanotechnology.

Purpose To analyse diagnostic and therapeutic impact of molecular imaging TNM (miTNM) stage obtained with 18F-DCFPyL versus 18F-Fluorocholine in head to head comparison in biochemical recurrence (BCR) prostate cancer (PCa). Material and methods Patients with BCR PCa after radical treatment with previous 18F-Fluorocholine-PET/CT (negative or oligometastatic disease) were derived to 18F-DCFPyL-PET/CT. Patients were classified attending to: grade group, EAU classification, PSA, PSA doubling time (PSAdt) and PSA velocity (PSAvel). The overall detection rate (DR) and miTNM stage according to PROMISE criteria were assessed for both radiotracers and also correlation (Kappa). The influence of PSA and kinetics on both PET/CT (DR and miTNM) and predictive value of unfavourable kinetics on miTNM were determined. Cut-off PSA, PSAdt and PSAvel values able to predict PET/CT results were determined. Change in miTNM and treatment derived of 18F-DCFPyL information with respect to 18F-Fluorocholine was also evaluated. Results We studied 138 patients. 18F-DCFPyL showed a higher DR than 18F-Fluorocholine (64.5% vs 33.3%). 18F-DCFPyL and 18F-Fluorocholine detected T in 33.3% versus 19.6%, N in 27.5% versus 13.8%, M in 30.4% versus 8.7%. Both tracers DR showed significant associations with PSA and PSAvel. Significant association was only found between miTNM and PSA on 18F-Fluorocholine-PET/CT (p=0.033). For 18F-Fluorocholine and 18F-DCFPyL PET/CT a PSAdt cut-off of 4.09 and 5.59 months, respectively, were able to predict M stage. 18F-DCFPyL changed therapeutic management in 40/138 patients. Conclusion 18F-DCFPyL provides a higher DR and superior miTNM staging than 18F-Fluorocholine in restaging BCR, especially with high PSA and unfavourable PSA kinetics, showing a fair agreement to 18F-Fluorocholine.

Heat pumps are increasingly becoming a key solution in the quest for decarbonization, offering a significant advantage over traditional boilers due to their superior energy efficiency. Not only can heat pumps provide both heating and cooling, but they also achieve thermal efficiencies exceeding 500%, which can seem to defy conventional expectations. The outdoor unit of a heat pump consists of about twenty main components, one of which is a complex network of copper pipes and sheets welded to valves, connectors, and other fittings. This set involves over thirty welded joints, highlighting a significant opportunity for reducing manufacturing time through process optimization. Copper is a critical material extensively used in various applications due to its excellent thermal and electrical conductivity. However, these very properties make welding copper particularly challenging, especially when aiming to automate and streamline industrial processes. Traditionally, connecting copper pipes and fittings is done through brazing, yet, alternative methods such as LASER welding, electron beam welding, resistance welding, friction welding, and ultrasonic welding also exist. This study focuses on the ultrasonic welding of copper, aiming to identify the optimal parameters that maximize the mechanical strength of overlapping joints and ensure effective tube sealing. Experimental results showed that for copper sheets, the best outcomes were achieved with a welding time of 3 s and a pressure of 6 bar. For tube sealing, the optimal conditions were a welding time of 3 s and a pressure of 4 bar. For both scenarios, the same variables were used, retention time of 0.62 s, initial pressure of 2 bar, retention pressure of 2 bar and sonotrode rising pressure of 3 bar. The analysis reveals that ultrasonic welding of copper can achieve both robust mechanical strength and reliable sealing, making it a promising technique for industrial applications.

Mannosylerythritol lipids (MELs), one of the most promising biosurfactants (BS), are glycolipids produced by yeasts or fungi, with great environmental performance and a high compatibility with the human body. MELs besides working as typical surfactants, can form diverse structures when in the critical aggregation concentration (CAC), reducing the surface tension of water and other solutions, and being stable over a wide range of conditions. Among others, MELs present anti-microbial, antitumor, antioxidant and anti-inflammatory activity, skin and hair repair capacity, which opens possibilities for their use in applications from cosmetics and pharmaceutics to bio-remediation and agriculture. However, their market share is still low when compared to other glycolipids, due to their less developed production process and higher production cost. This re-view gathers information on the potential applications of MELs mentioned on the literature since 1993. Furthermore, it is also explored the current strategies being developed to enhance the market presence of MELs, in parallel with the ones developed for rhamnolipids and sophorolipids.

A nanostructured electrochemical bi-sensor system for analysis of milks has been developed using the Layer by Layer technique. The non-enzymatic sensor [CHI+IL/CuPcS]2, is a layered material containing a negative film of the anionic sulfonated copper phthalocyanine (CuPcS) acting as electrocatalytic material, and a cationic layer containing a mixture of an ionic liquid (IL) (1-butyl-3-methylimidazolium tetrafluoroborate) that enhances the conductivity and chitosan (CHI) that facilitates the enzyme immobilization. The biosensor ([CHI+IL/CuPcS]2-GAO) results from the immobilization of galactose oxidase on the top of the LbL layers. FTIR, UV-vis and AFM have confirmed the proposed structure and cyclic voltammetry has demonstrated the amplification caused by the combination of materials in the film. Sensors have been combined to form an electronic tongue for milk analysis. Principal Component Analysis has revealed the ability of the sensor system to discriminate between milk samples with different lactose content. Using PLS-1 calibration models, correlations have been found between the voltammetric signals and chemical parameters measured by classical methods. PLS-1 models provide excellent correlations with lactose content. Additional information about other components such as fats, proteins and acidity can also be obtained. The method developed is simple and the short response time permits its use in assaying milk samples on-line.

The strong couplings among ecological, economic, social and technological processes explains the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemics. Among complexification’s essential features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This in turn means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy and information, and a given time horizon, aiming at enhancing the co-evolutionary power of the Biosphere and its human subsystems. Giving the high-stakes, the need for effective, efficient, diverse solutions, their local-global, present-future effects, and their unforeseen short, medium and long-term impacts, achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents, harnessing the strong functional coupling between human, artificial and nonhuman biological intelligence in a no-zero-sum game to achieve sustainability.

There is currently an exponential growth in the electric vehicle market, which will require an increase in the electrical grid capacity to meet the demand of charging. If, on the one hand, the introduction of energy generation from renewable sources can be used to meet that requirement, the intermittent nature of some of these sources poses challenges to the required real time equilibrium between generation and consumption. The impossibility of controlling generation from some of these sources leads to the attempt of controlling and manage the consumption of electricity, according with the levels of generation. In this context, the emergence of smart grids has introduced mechanisms that guarantee a balance between consumption and generation of electricity. One of these mechanisms is the smart charging of electric vehicles. Effective smart charging relies on communication between the supply equipment and the electric vehicle, en-abling the adjustment of the energy transfer according with the generation levels. Thus, there is a necessity for a standardised system that guarantees this communication. In this context, the ISO 15118 standard, allows high level communication mechanisms, much beyond the basic control solutions offered by the IEC 61851-1 specification. In this context, this paper presents the development of a charge emulation system, based on the ISO 15118 communication protocol and discusses its application for demand response purposes.

Chondroitin is a glycosaminoglycan that has gained widespread use in nutraceuticals and pharmaceuticals, mainly for treating osteoarthritis. Traditionally, it has been extracted from animal cartilage but recently, biotechnological processes have emerged as a commercial alternative to avoid the risk of viral or prion contamination and offer a vegan-friendly source. Typically, these methods involve producing the chondroitin backbone using pathogenic bacteria and then modifying it enzymatically through the action of sulfotransferases. Despite the challenges of expressing active sulfotransferases in bacteria, the use of eukaryotic microorganisms is still limited to a few works using Pichia pastoris. To create a safer and efficient biotechnological platform, we have constructed a biosynthetic pathway for chondroitin production in S. cerevisiae as a proof-of-concept. Up to 125 mg/L and 200 mg/L of intracellular and extracellular chondroitin were produced, respectively. Furthermore, as genome-scale models are valuable tools for identifying novel targets for metabolic engineering, a stoichiometric model of chondroitin-producing S. cerevisiae has been developed and used in optimization algorithms. Our research has yielded several novel targets, such as uridine diphosphate(UDP)-N-acetylglucosamine pyrophosphorylase (QRI1), glucosamine-6-phosphate acetyltransferase (GNA1) or N-acetylglucosamine-phosphate mutase (PCM1) overexpression that might enhance chondroitin production, which will guide future experimental research to develop more efficient host organisms for the biotechnological production process.

Vulnerable carotid plaques are responsible for 20% of the ischemic strokes. The identification of those asymptomatic carotid plaques that will become symptomatic is essential but remains unclear. Our main goal was to investigate whether the amount of the peri-carotid adipose tissue, estimated by the extra-media thickness (EMT) is associated with the atherosclerotic characteristics at the carotid bifurcation in patients with PAD. An observational, prospective, single-center, longitudinal study was conducted. 177 patients performed carotid Doppler-ultrasound. The following data was collected: EMT, intima-media thickness (IMT), presence of carotid plaques, area of the highest plaque, and grade of internal carotid stenosis. From each carotid bifurcation a right and left EMT was determined. We analyzed both the mean EMT (calculated as the mean between the right and the left EMT) and the EMT ipsilateral to the carotid bifurcation. The presence of carotid plaques was associated with a higher mean EMT, [Median=1.14; IQR=0.66 versus Median=0.97; IQR=0.40; p=.001]. A positive correlation was found between mean EMT and IMT (right: ρ=.20; p=.010; left: ρ=.21; p=.007) and between mean EMT and area of the largest carotid plaque (right: ρ=.17; p=.036; left: ρ=.22; p=.004). Left carotid stenosis ≥ 70% was associated with higher mean EMT. [Median=1.55; IQR=0.68 versus Median=1.00; IQR=0.46; p=.019]. Patients with “acute culprit” carotid stenosis had a higher ipsilateral EMT [Left ipsilateral EMT: Median=1.46; IQR=0.63; “non-acute”: Median=0.94; IQR=0.43; p=.009; Right ipsilateral EMT: Median=2.25; IQR=0.62; “non-acute”: Median=1.00; IQR=0.51; p=.015]. This difference was not found in the contra-lateral EMT. Six months after the neurologic event, EMT ipsilateral to an “acute culprit” carotid stenosis decreased (p=.036). The amount of peri-carotid adipose tissue, estimated with EMT was associated with atherosclerosis at the carotid arteries. In particularly EMT could be a non-invasive marker of “acute culprit” carotid stenosis, easily determined in clinical practice. These findings may have implications in personalized medicine, for the determination of the best treatment approach.

Quantification of erythrocytes and leukocytes is an essential aspect of hemogram diagno- 23 sis in Veterinary Medicine. Flow cytometry analysis, laser scattering, and impedance detection are 24 standard laboratory techniques, verified by manual microscopy counting. Although single-cell scat- 25 tering is already used as a standard technology for differentiating cell counts in flow cytometry, it 26 requires capillary cell separation. The current study investigates the scattering characteristics of 27 whole blood to identify correlations with erythrocytes and leukocytes counts. The scattering infor- 28 mation present in blood samples can be classified into three types: i) geometrical scattering, which 29 occurs when non-absorbed light is reflected and scattered, ii) Mie scattering, which happens when 30 light is scattered by particles of a similar size to the wavelength, and iii) Rayleigh scattering, which occurs when light is scattered by particles that are smaller than the incident light wavelength. In 32 this study, we investigate the scattering correction coefficients of dog blood absorption spectra in 33 the visible-near infrared range, to establish direct correlations with erythrocytes and leukocytes 34 counts, using multivariate linear regression. Our findings demonstrate the possibility of using the 35 scattering properties of dog blood, which is a step towards the existence of a portable and miniatur- 36 ized hemogram diagnosis in Veterinary Clinics worldwide.

Extracellular vesicles (EVs) present a great potential for the development of new treatments in the biomedical field. To be used as therapeutics, many different sources have been used for EVs obtention, while only few studies have addressed the use of platelet derived EVs (pEVs). In fact, pEVs have been shown to intervene in different healing responses, thus some studies have evaluated their regenerative capability in wound healing or hemorrhagic shock. Even more, pEVs have proven to induce cellular differentiation, enhancing musculoskeletal or neural regeneration. However, the obtention and characterization of pEVs is widely heterogeneous and differs from the recommendations of the International Society for Extracellular Vesicles. Therefore, in this review, we aim to present the main advances in the therapeutical use of pEVs in the regenerative medicine field while highlighting the isolation and characterization steps followed. The main goal of this review is to portray the studies performed in order to enhance the translation of the pEVs research into feasible therapeutical applications.

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.

MicroRNAs are small non-coding RNAs that are implicated in several physiological processes such as cell development, proliferation, differentiation, apoptosis, immune response and angiogenesis. In the last couple of decades, several studies on miRNA profiling in OSCC have tried to associate miRNAs with clinical characteristics such as relapse, metastasis, and survival, however, the results have been found to vary considerably, sometimes even being contradictory. The main objective of our study was to analyse and verify miRNA expression in oral squamous cell carcinoma in a Spanish population. Second, we attempted to associate the identified deregulated miRNAs with molecular pathways. 8 Oral Squamous Cell Carcinoma patients and 8 healthy control samples were analysed by a microarray Affymetrix® miRNA 4.1 array plate and validated with 8 more cases using RT-qPCR. Deregulated miRNAs were studied using Diana Tools miRPath 3.0 to associate miRNA targets with molecular pathways. Microarray analysis identified 80 deregulated miRNAs (35 over-expressed and 45 under-expressed). Only miR-497-5p and miR-4417 maintained its deregulated expression after validation with qPCR. Among the molecular pathways in which deregulated miRNAs could be implicated, the most statistically significant pathway was ‘proteoglycans in cancer’. No relationship was found between miR-497-5p or miR-4417 expression and clinical or pathological parameters except of nodular affectation (high miR-4417 expression in patients with nodular affectation, p = 0.035) and radiotherapy (diminished miR-497-5p expression in patients who needed radiotherapy, p = 0.05). We have verified the altered expression of miR-497-5p and miR-4417 in Oral Squamous Cell Carcinoma samples and related the deregulated miRNAs with the ‘proteoglycans in cancer’ pathway.

Aim: Ectopic lipid accumulation, including pancreatic steatosis, exacerbates type 2 diabetes risk in susceptible individuals. Dysregulated circulating microRNAs (miRNAs) have been identified to correlate with clinical measures of pancreatitis, pancreatic cancer, and type 1 diabetes. The aim of the current study was, therefore, to examine the association between circulating abundances of candidate miRNAs and pancreatic and liver fat deposition as quantified using magnetic resonance imaging (MRI) and spectroscopy (MRS). Methods: Asian Chinese (n=34; BMI=26.7±4.2 kg/m2) and European Caucasian (n=34; BMI=28.0±4.5 kg/m2) females from the TOFI_Asia cohort underwent MRI and MRS analysis of pancreas (MR-%pancreas) and liver (MR-%liver fat) respectively to quantify ectopic lipid deposition. Plasma miRNA abundances of a subset of circulatory miRNAs associated with pancreatic and liver steatosis were quantified by qRT-PCR. Results: miR-21-3p and miR-320a-5p correlated with MR-%pancreas fat, plasma insulin and HOMA2-IR but not MR-%liver fat. MR-%pancreas fat remained associated with decreasing miR-21-3p abundance following multivariate regression analysis. Conclusions: miR-21-3p and miR-320a were demonstrated to be negatively correlated with MR-%pancreas fat, independent of ethnicity. For miR-21-3p, this relationship persists with the inclusion of MR-%liver fat in the model, suggesting the potential for wider application as a specific circulatory correlate of pancreatic steatosis.

Low back pain (LBP) is a leading cause of disability. It significantly impacts the patient’s quality of life, limits their daily living activities, and reduces work productivity. To reduce the burden of LBP, several pharmacological and non-pharmacological treatment options are available. This review summarizes the role of heat therapy in the management of LBP. First, we outline the common causes of LBP, then discuss the general mechanisms of heat therapy on (LB)P, and finally review the published evidence regarding the impact of heat therapy in patients with acute or chronic non-specific LBP. This review demonstrates that continuous, low-level heat therapy provides pain relief, improves muscular strength, and increases flexibility. Therefore, this effective, safe, easy-to-use, and cost-effective non-pharmacological pain relief option is still relevant in modern clinical practice.

In this study, the physical properties of briquettes produced from two different biomass feedstocks (sawdust and date palm trunk) and different plastic wastes were investigated, without using any external binding agent. The biomass feedstocks were blended with different ratios of two WEEE plastics (halogen-free wire and print circuit boards (PCB)) and automotive shredder residues (ASR). The briquettes production is studied at different waste proportions (10-30%), pressures (22-67 MPa) and temperatures (room-130 ˚C). Physical properties as density and durability rating were measured, usually increasing with temperature. Palm trunk gave better results than sawdust in most cases, due to its moisture content and the extremely fine particles that are easily obtained.

This paper outlines the ongoing development of a specialised mobile application to address the mental health needs of vulnerable populations in the European Union (EU). Conducted as a mixed-methods research within two EU Science and Technology Cooperation Actions, the study prioritises stakeholder feedback to identify features for initial testing and strategies to improve application uptake, using critical digital health analysis. With a focus on marginalised groups such as refugees, migrants and socio-economically disadvantaged individuals, the application aims to provide an accessible and culturally sensitive platform for mental health support, integrating evidence-based interventions such as cognitive behavioural techniques and mindfulness exercises. Key features include multilingual support, habit tracking, personalised recommendations for support and services, and real-time crisis intervention. Collaboration with stakeholders and ongoing rigorous usability testing are driving the refinement process to ensure usability, acceptability and effectiveness, underscoring the importance of user engagement in technology-based mental health interventions in the EU context and highlighting the importance of collaborative science and technology for societal benefit.

Plastid genomes are in general highly conserved given their slow evolutionary rate, thus large changes in their structure are unusual. However, when specific rearrangements are present, they are often phylogenetically informative. Asteraceae is a highly diverse family whose evolution is long driven by polyploidy (up to 48x) and hybridisation, both processes usually complicating systematic inferences. In this study, we have generated one of the most comprehensive plastome-based phylogenies of family Asteraceae, providing information about the structure, genetic diversity, and repeat composition of these sequences. By comparing the whole plastome sequences obtained, we confirmed the double inversion located in the long single copy region, for most of the species analysed (with the exception of basal tribes), a well-known feature for Asteraceae plastomes. We also show that genome size, gene order and gene content are highly conserved along the family. However, species representative of the basal subfamily Barnadesioideae -as well as in the sister family Calyceraceae - are lacking the pseudogene rps19 located in one inverted repeat. The phylogenomic analysis conducted here, based on 63 protein-coding genes, 30 transfer RNA genes and 21 ribosomal RNA genes from 36 species of Asteraceae, are overall consistent with the general consensus for the family’s phylogeny, while resolving the position of tribe Senecioneae and revealing some incongruences at tribe level between reconstructions based on nuclear and plastid DNA data.

There are different ways to analyse energy absorbance (EA) in the human auditory system. In previous research, we developed a complete finite element model (FEM) of the human auditory system. In this mentioned work, the external auditory canal (EAC), middle ear, and inner ear (spiral cochlea, vestibule, and semi-circular canals) were modelled based on human temporal bone histological sections. Multiple acoustic, structure and fluid-coupled analyses were conducted using the FEM to perform harmonic analyses in the 0.1–10 kHz range. Once the FEM had been validated with published experimental data, the FEM numerical results were used to calculate the EA or energy reflected (ER) by the tympanic membrane. This EA was also measured in clinical audiology tests which were used as a diagnostic parameter. A mathematical approach was developed to calculate the EA and ER, with numerical and experimental results showing adequate correlation up to 1 kHz. Another published FEM had adapted its boundary conditions to replicate experimental results. Here, we recalculated those numerical results by applying the natural boundary conditions of human hearing and found that the results almost totally agreed with our FEM. This boundary problem is frequent and problematic in experimental hearing test protocols: the more invasive they are, the more the results are affected. One of the main objectives of using FEMs is to explore how the experimental test conditions influence the results. Further work will still be required to uncover the relationship between the middle ear structure and EA to clarify how to best use FEMs. Moreover, the FEM boundary conditions must be more representative in future work to ensure their adequate interpretation.

An ionospheric response at middle latitudes to geomagnetic storms is not yet very well understood. Total electron content (TEC) variations associated with eight strong geomagnetic storms between 2015 and 2022 obtained from GNSS receivers in the western area of the North Atlantic (Portuguese continental and insular territory) are studied in an attempt to fill this gap. It was found that for most of the studied geomagnetic storms TEC variations are synchronous for the longitudinal ranges from 27ºW and 9ºW. In the southern part of the studied region (around 32ºN) the amplitude of TEC variations is, in general, significantly higher than in the northern part (around 39ºN). Some of the studied geomagnetic storms were associated with TEC variations that we interpret as effects of post-sunset equatorial plasma bubbles that travelled well north from their habitual region. Also, while most of the studied storms were accompanied by reports on different kind of malfunction of GNSS systems (GPS; GALILEO and other), there is no clear pattern in their appearance in dependence on the geomagnetic/ionospheric storms’ strength, commencement time, and its characteristics, in general.

Groundwater vulnerability assessment has become a useful tool for groundwater pollution pre-vention. Groundwater vulnerability maps provide useful data to protect groundwater resources. The identification of agricultural patterns is an important issue for optimized land management. The Tagus river watershed is the backbone of this survey. Naturtejo UNESCO Global Geopark, in central inland Portugal, corresponds to a rural territory. Intensive agricultural practices showed a rising tendency in the last decades. The most internationally used method for vulnerability evaluation is the DRASTIC index. In this survey, the DRASTICAI index is introduced. A new at-tribute - Anthropogenic Influence - is here added. Five levels of growing vulnerability, from low to high, can be here acknowledged. Idanha-a-Nova municipality is the most affected by intensive farming activities. A robust assessment of groundwater quality has a key role. Climate change scenarios and water scarcity are important issues in years to come. Therefore, optimized groundwater management is essential to consider in policy-making strategies.

Top-down models are defined by hardware architects to provide information on the utilization of the different hardware components. The target is to isolate the users from the complexity of the hardware architecture while giving them insight into how efficiently the code is using the resources. In this paper, we explore the applicability of 4 top-down models defined for different hardware architectures powering state-of-the-art HPC clusters (Intel Skylake, Fujitsu A64FX, IBM Power9, and Huawei Kunpeng 920) and propose a model for AMD Zen 2. We study a parallel CFD code used for scientific production to compare these 5 Top-Down models. We evaluate the level of insight achieved, the clarity of the information, the ease of use, and the conclusions that each one allows us to reach.

Transcriptional regulation constitutes a key step in gene expression regulation. Myocyte enhancer factor 2C (MEF2C) is a transcription factor of MADS box family involved in the early development of several cell types including muscle cells. Over the last decade a novel layer of complexity modulating gene regulation is emerging as non-coding RNAs have been identified, impacting in both transcriptional and post-transcriptional regulation. microRNAs represent the most studied and abundantly expressed subtype of small non-coding RNAs and their functional role have been widely documented. On the other hand, our knowledge on the transcriptional and post-transcriptional regulatory mechanisms that drive microRNA expression is still incipient. We recently demonstrated that MEF2C is able to transactive the long, but not short, regulatory element upstream of miR-23a-miR-27a-miR-24-2 transcriptional start site. However, MEF2C over-expression and silencing, respectively, displayed distinct effects on each of the miR-23a-miR-27a-miR-24-2 mature cluster members, without affecting pri-miRNA expression levels, supporting thus additional MEF2C-driven regulatory mechanisms. Within this study we demonstrated a complex post-transcriptional regulatory mechanisms directed by MEF2C in the regulation of miR-23a-miR-27a-miR-24-2 cluster members, distinctly involving different domains of the MEF2C transcription factor and the physical interaction with pre-miRNAs and RNA interacting proteins such as Ksrp, HnRNPa3 and Ddx17.

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.

Climate change and the overall increase of seawater temperature is causing a poleward shift in species distribution, which includes a phenomenon described as tropicalization of temperate regions. This work aims at reporting the first records of four species off the southwestern Iberian Peninsula, namely oceanic puffer Lagocephalus lagocephalus Linnaeus, 1758, Madeira rockfish Scorpaena maderensis Valenciennes, 1833, ornate wrasse Thalassoma pavo Linnaeus, 1758, and bearded fireworm Hermodice carunculata Pallas, 1766. These last three species, along with other occurrences of aquatic fauna and flora along the Portuguese coast, reveal an ongoing process of poleward expansion of several species for which a comprehensive survey along the entire Iberian Peninsula is urgent. The putative origins of these subtropical and tropical species off continental Portugal are discussed, as well as the urgent need of public awareness due to potential health risks resulting from the toxicity of two of the four species reported in this paper.

We compare the well known Rayleigh-Ritz variational method (RRVM) with a recently proposed approach based on supersymmetric quantum mechanics and the Gram-Schmidt orthogonalization method (SSQMGS). We apply both procedures to a particular class of double-well harmonic oscillators that had been conveniently chosen for the application of the latter approach. The RRVM eigenvalues converge smoothly from above providing much more accurate results with less computational effort. Present results show that the unproved SSQMGS upper bounds do not hold.

The utilization of eco-fonts for office printing is a sustainable, “green” printing concept, which has obvious economic benefits. As a result, it has a significant effect on environmental sustainability. This practice's fundamental problem is the decreased quality of text printed using eco-fonts compared to those printed with regular fonts. The aim of this research is eco-font efficiency estimation, i.e. determination of toner usage reduction level of inkjet-printed documents typed with this font type, as well as estimation of the extent humans perceive differences between text printed with eco-font and the one printed by its “non-eco“ equivalent. Combining the instrumental measuring method and digital image analysis, it was found that this simple principle (eco-font utilization) enables substantial toner usage reduction for an inkjet printing system. At the same time, a visual test showed that the visual experience of text printed using eco-font was sufficient. In addition, awareness of the benefits that eco-font utilization brings, change users’ attitude towards eco-font quality. The concept of removing the black pixel from this commonly used Thai font has a great potential for the sustainability printing process, and this simple solution could be applied to other languages as part of the GIT campaign.

Asthma is a significant public health concern. This study identified the provinces with the highest morbidity and mortality rates due to asthma among the working-age population (15-69 years) in the Republic of Ecuador. The secondary objective was to explain the possible differences attribut-able to occupational exposure. This nationwide ecological and exploratory study was conducted in 24 provinces between 2016 and 2019. Government databases were used as sources of infor-mation. Standardized rates were calculated for codes the J45 and J46. The hospitalization mor-bidity rate for asthma decreased from 6.51 to 5.76 cases per 100,000 working-age population, and the mortality rate has consistently been low and stable from 0.14 to 0.15 deaths per 100,000 working-age population. Geographic differences between the provinces were evident. The risk of hospitalization and death due to asthma was higher in the Pacific coast (five provinces) and the Andean region (two provinces). The high rates observed in provinces with greater agricultural and industrial development could be the main determinants of national heterogeneity and could act as occupational risk factors. The contribution of occupational hazards in each province should be examined in depth through ad hoc studies. These findings provide valuable information for creating public policies aimed at promoting and safeguarding the respiratory health of the popu-lation, particularly that of workers.

Millimeter wave antennas have significance for high-speed, high-capacity wireless communication, delivering substantial advantages and an array of applications. This literature review analyzes the historical development, assessment of performance, difficulties with design, and contemporary applications in telecommunications, radar systems, and imaging. It covers the development of technology, especially within the context of 5G and beyond, and focuses at several antenna designs that deal with technical issues including reduction and impedance matching. The review also studies the effect of design on efficiency and bandwidth, identifying research gaps and potential futures, notably in terms of 5G technology. The commitment to develop millimeter wave antenna technology for next-generation wireless networks is evident, underlining the need of continued research and development.

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

The enzymatic activities of bacterial isolates have been widely studied, but a spatial distribution of this activity is rarely focused. New antibiotic-producing microorganisms can be discovered in a more efficient manner if spatial statistical techniques are applied to the distribution of the activity of bacterial isolates in different terrains. This study is focused to generate a series of maps illustrating the spatial distribution of different soil parameters and the inhibition against relative-safe pathogens (like Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Salmonella, Pseudomonas fluorencens and Enterobacter cloacae) in an urban park in València (Spain). This spatial data has demonstrated a higher proportion of isolates was specifically allocated. This routine of data presentation is valuable for understanding bacterial population dynamics at a local level.

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

Infants’ avoidance of drop-offs has been described as an affordance learning that is not transferable between different locomotor postures. In addition, there is evidence that infants perceive and act similarly around real and water cliffs. This cross-sectional study investigated the effects of specific locomotor experiences on infants’ avoidance behaviour using the Real Cliff / Water Cliff paradigm. The experiments included 102 infants, 58 crawling, but pre-walking, infants (M_age= 11.57 months, SD = 1.65) with crawling experience ranging between 0.03 and 7.4 months (M = 2.16, SD = 1.71) and 44 walking infants (M_age = 14.82 months, SD = 1.99), with walking experience ranging between 0.13 and 5.2 months (M = 1.86, SD = 1.28). The association between crawling experience and crawlers’ avoidance of the real and water cliffs was confirmed. Importantly, crawling and total self-produced locomotor experience, and not walking experience, were associated with walkers’ avoidance behaviour on both cliffs. These results suggest that some degree of perceptual learning acquired through crawling experience was developmentally transferred to the walking posture. A longer duration of crawling experience facilitates a more rapid recalibration to the new walking capability. In addition, there was no difference in infants’ avoidance of falling on the real and the water cliff. However, infants explored the water cliff more than the real cliff, revealing more enticement to examine bodies of water than for drop-offs.

This study presents a strategic approach to developing applications focused on implementing Large Language Models using the Langchain framework in Python. Three language models are highlighted: GPT-3.5 (turbo mode), LLaMA 2, and Vicuna 7B, each with their distinctive features and capabilities. The methodology used is described in detail, including data extraction from medical reports using zero-shot prompting data extraction techniques, interaction with language models, and structured storage of results. The performance of the models in data extraction is evaluated, presenting metrics such as precision, recall, and F1 score. The results demonstrate high model capability in extracting information, although areas for improvement are identified, particularly in data extraction precision. In conclusion, the efficacy of the models in extracting information from medical histories is not considerably acknowledged, with an emphasis on the importance of improving precision and increasing the volume of trained data for future research in healthcare digitalization.

The objective is to describe infant feeding practices and the nutritional status of infants under six months among Syrian refugees in Greater Beirut, Lebanon. A cross-sectional study was conducted among Syrian refugee mothers with children under five years (July-October 2018), mothers with infants under six months were included in the analysis (n=114). Additionally, eleven focus groups discussions were conducted to explore supportive factors and barriers associated with early breastfeeding practices. The prevalence of pre-lacteal feeding was high (62.5%), whereas early initiation of breastfeeding (EIBF) was low (31%), and exclusive breastfeeding (EBF) very low (24.6%). About one-fifth of the infants were suffering from anemia (20.5%) and 9.6% were wasted. Supporting factors of adequate infant feeding practices comprised knowledge on maternal nutrition and EBF, in addition to receiving support from healthcare professionals and family members. Identified barriers included preterm delivery, pre-lacteal feeding, an at-risk waist circumference and moderate to severe depression among mothers, bottle feeding, early introduction of food, maternal health reasons, breastmilk substitutes’ distribution, and misinformation offered by mothers-in-law. To address sub-optimal feeding practices documented among Syrian refugees in our study, existing infant and young child feeding policies and programs need to be strengthened and revised to tackle the identified gaps.

In this study, we propose an augmentation method for machine learning based on relabeling data in caregiving and nursing staff indoor localization with Bluetooth Low Energy (BLE) technology. Indoor localization is used to monitor staff to patient assistance in caregiving and to gain insights into workload management. However, improving accuracy is challenging when there is a limited amount of sensor data available for training. In this paper, we propose a data augmentation method to reuse the Received Signal Strength (RSS) from different sensors by relabeling to the sensors with less samples resolving data imbalance. Standard deviation and Kullback-Leibler divergence between minority and majority class are used to measure signal pattern to find matching sensors to relabel. By matching sensors between classes, two variation of relabeling are implemented specifically full and partial matching. The performance is evaluated using real world dataset we collected for five days in a nursing care facility installed with 25 BLE beacons. Random Forest model is utilized for location recognition, and performance is compared using the weighted F1-score to account for class imbalance. By increasing the sensor data with our proposed relabeling method for data augmentation, we achieved higher minority class F1-score as compared to augmentation with Random Sampling, Synthetic Minority Oversampling Technique (SMOTE) and Adaptive Synthetic Sampling (ADASYN). Our proposed method utilizes collected sensor data by leveraging majority class samples. Full matching demonstrated a 6 to 8% improvement from the original baseline overall weighted F1-score.

Annually, an estimated 13-26 million newborns need respiratory support and 2-3 million newborns need extensive resuscitation, defined as chest compression and 100% oxygen with or without epinephrine in the delivery room. Despite such care, there is a high incidence of mortality and short-term neurologic morbidity. The poor prognosis associated with receiving chest compression alone or with medications in the delivery room raises questions as to whether improved cardiopulmonary resuscitation methods specifically tailored to the newborn could improve outcomes. This review discusses the current recommendations, mode of action, different compression to ventilation ratio, continuous chest compression with asynchronous ventilations, chest compression and sustained inflation optimal depth, and oxygen concentration during cardiopulmonary resuscitation.

In this paper, a new anode environmentally friendly for hydrogen production was developed based on 430 stainless steel with an electrodeposited cobalt layer. The novelty of this work is the cobalt source once the electrodeposition bath was obtained from recycling of spent Li-ion batteries cathode with composition LiCoO₂. The electrodeposited cobalt behaves as supercapacitor in KOH 1M. In the linear voltammetry in KOH 1M, when the overpotential reaches 370 mV, the anodic density current for 430 SS/Co is 19 mA cm⁻². Thus, the anode developed in this paper achieves the double of density current with half of production cost if compared with 316SS. Moreover the anode construction described in this paper is an excellent option for Li- ion battery recycling.

In this paper the application of recycled Li-ion batteries spent cathode (LIB-SC) combined with NaHCO₃/H₂O₂ system is presented for the first time in the literature as an alternative for degradation of potentially toxic organic molecules. The model pollutant choice was methylene blue molecule. The spent cathode composition corresponds to LiCoO₂, which was proved by the XRD and EDX. Regarding the decolorization of methylene blue solution, the addition of NaHCO₃ in comparison with only H₂O₂ reduces the complete decolorization time in 96%. This reduction occurs because the radical CO₃ is more stable than OH. In this way, the application the system proposed in this article is aimed at solving two major global problems: the disposal of cell phone batteries and the pollution of liquid effluents.

This literature review investigates the importance of simulation and measurement techniques in the development of transmission lines and antennas, which are crucial to the reliability and efficiency of communication system. It emphasizes the necessity of exact measurement and computational approaches for simulating complicated electromagnetic process, which help to optimize designs before physical prototypes are built. The review examines a variety of research articles that offer innovative solutions to improving accuracy in antenna design, scalability and cost challenges in antenna measurements, and crosstalk measurement methods. It also explores how these methodologies affect antenna design parameters such as gain, bandwidth, and radiation patterns, emphasizing the importance of correct modeling to ensure the performance of transmission lines and antennas in modern communication system. The review serves as a valuable reference for guiding future research and technological advancements in these fields.

This paper investigates the effects of air void topology on hydraulic conductivity in asphalt mixtures with porosity in the range 14%-31%. Virtual asphalt pore networks were generated using the Intersected Stacked Air voids (ISA) method, with its parameters being automatically adjusted by the means of a differential evolution optimisation algorithm, and then 3D printed using transparent resin. Permeability tests were conducted on the resin samples to understand the effects of pore topology on hydraulic conductivity. Moreover, the pore networks generated virtually were compared to real asphalt pore networks captured via X-ray Computed Tomography (CT) scans. The optimised ISA method was able to generate realistic 3D pore networks corresponding to those seen in asphalt mixtures in term of visual, topological, statistical and air void shape properties. It was found that, in the range of porous asphalt materials investigated in this research, the high dispersion in hydraulic conductivity at constant air void content is a function of the average air void diameter. Finally, the relationship between average void diameter and the maximum aggregate size and gradation in porous asphalt materials was investigated.

Plant male sterility refers to the failure in the production of fertile pollen. It occurs spontaneously in natural populations and may be caused by genes encoded in the nuclear (genic male sterility; GMS) or mitochondrial (cytoplasmic male sterility; CMS) genomes. This feature has great agronomic value for the production of hybrid seeds and has been widely used in crops, such as corn, rice, wheat, citrus, and several species of the family Solanaceae. Mitochondrial genes determining CMS have been uncovered in a wide range of plant species. The modes of action of CMS have been classified in terms of the effect they produce in the cell, which ultimately leads to a failure in the production of pollen. Male fertility can be restored by nuclear-encoded genes, termed restorer-of-fertility (Rf) factors. CMS from wild plants has been transferred to species of agronomic interest through somatic hybridization. Somatic hybrids have also been produced to generate CMS de novo upon recombination of the mitochondrial genomes of two parental plants or by separating the CMS cytoplasm from the nuclear Rf alleles

In this paper, the power quality of interconnected microgrids is managed using a Model Predictive Control (MPC) methodology which manipulates the power converters of the microgrids in order to achieve the requirements. The control algorithm is developed for the microgrids working modes: grid-connected, islanded and interconnected. The results and simulations are also applied to the transition between the different working modes. In order to show the potential of the control algorithm, a comparison study is carried out with classical Proportional-Integral Pulse Width Modulation (PI-PWM) based controllers. The proposed control algorithm not only improves the transient response in comparison with classical methods but also shows an optimal behavior in all the working modes, minimizing the harmonics content in current and voltage even with the presence of non-balanced and non-harmonic-free three-phase voltage and current systems

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and communication, anxiety, hyperactivity, and restricted interest for specific subjects. In addition to the genetic factors, multiple environmental factors have been related to the development of ASD. Animal models can serve as crucial tools for understanding the complexity of ASD and identifying potential therapeutic strategies. In this study, a chemical model of ASD has been developed in zebrafish by exposing embryos to valproic acid (VPA) from 4 to 48 hours post-fertilization. After the exposure, embryos were transferred to fish water and the effects on behavior and neurotransmitters profile were analyzed at both larval and adult stages. Larvae from VPA-treated embryos showed hyperactivity and decreased visual and vibrational escape responses, as well as an altered neurotransmitters profile, with increased glutamate and decreased acetylcholine and norepinephrine levels. Adults from VPA-treated embryos exhibited impaired social behavior characterized by larger shoal sizes and a decreased interest for their conspecifics. Neurotransmitter analysis revealed a significant decrease in dopamine and GABA levels in the brain. These results support the interest of this model in the study of ASD.

Neck lymphangiomas are rare, benign congenital malformations that predominate in childhood. Most present before the age of two. There are no risk factors related to sex, ethnic origin or predominance on either side, and they can occur in any anatomical location, although the most frequent is in the head and neck. The clinical presentation depends on its location. The most frequent symptom is the existence of a painless mass that grows slowly. Available therapeutic tools include surgery, systemic treatment, and injection of sclerosing agents.

This study aimed to conduct a cross-cultural adaptation of the development of the cat-owner/dog-owner relationship scales. The method encompassed several stages: conceptual, item, semantic, operational, measurement, and functional equivalence. Processes included translations, synthesis of translations, back-translations, consensus on the English versions, external evaluation by the original authors, expert committee evaluation, and pre-tests. The study involved surveying 342 pet owners throughout Brazil using a 20-item questionnaire. Data analyses utilized confirmatory factor analysis, covariance-based modeling, and multigroup analysis. The techniques confirmed that the scale preserved its psychometric properties and showed no variance between dog and cat owners, indicating that the measured constructs are universal and unaffected by specific cultural nuances. Hence, the cross-cultural adaptation and validation of the scale facilitate applying and testing concepts and measures in diverse contexts, enriching our understanding of the dynamics between owners and their pets (dogs and cats) in different living situations. In addition, this research holds particular significance in Brazil, given the country’s vast cultural diversity.

Traumatic Brain Injury represents a significant public health concern due to its role in traumatic death and disability, often caused by head impacts or rapid accelerations. Despite advancements in Finite Element Head Models, existing models primarily represent adult males, neglecting anatomical and physiological differences between genders and age groups. Additionally, the mechanistic roles of specific intracranial tissues, such as the dura mater, have conventionally been overlooked. To better understand the mechanical behavior of the brain and its injured regions in the context of TBI, including the dura mater, this study proposes the development of a Female Finite Element Head Model. This model, representative of a middle-aged female subject, was developed using medical image-derived geometry and finite element modeling techniques. The validation results demonstrate a similarity between the numerical displacement curves and those obtained experimentally. In the model with dura mater, the numerical results show analogous behavior to the experimental results, despite minimal variations in the amplitude of the curves. These advancements highlight the significance of including the dura mater in biomechanical brain modeling. Incorporating the dura mater in Finite Element Head Models produces more realistic results than models without it. This emphasizes the importance of enhancing biomechanical models to better represent anatomical complexity.

Flowering time is a critical stage for crop development as it regulates the ability of plants to adapt to an environment. To understand the genetic control of flowering time, a genome wide association study (GWAS) was conducted to identify the genomic regions associated with the control of this trait in durum wheat (Triticum durum Desf.). A total of 96 landraces and 288 modern lines were evaluated for days to heading, growing degree days, and accumulated day length at flowering across 13 environments spread across Morocco, Lebanon, Mauritania, and Senegal. These environments were grouped into four pheno-environments based on temperatures, day length and other climatic variables. Genotyping with 35K Axiom array generated 7,652 polymorphic SNPs in addition to 3 KASP markers associated to known flowering genes. In total, 34 significant QTLs were identified in both landraces and modern lines. Some QTLs had strong association with already known regulatory photoperiod genes, Ppd-A and Ppd-B and vernalization genes Vrn-A1, and Vrn3. However, these loci explained only 5 to 20% of variance for days to heading. Seven QTLs overlapped between the two germplasm groups in which Q.ICD.Eps-03 and Q.ICD.Vrn-17 consistently affected flowering time in all the pheno-environments, while Q.ICD.Eps-11 and Q.ICD.Ppd-12 were significant only in two pheno-environments and the combined analysis across all environments. These results help clarify the genetic mechanism controlling flowering time in durum wheat and show some clear distinctions to what is known for common wheat (Triticum aestivum L.)

Rotaviruses are highly infectious and typically transmitted by fecal-oral route via in the tropics and leading the cause of diarrheal deaths in children of developing countries, besides causing significant economic impacts like neonatal disease agents of domestic animals. This present report aims to present the clinical and diagnostic findings of two confirmed cases of rotavirus (RV) infection in orphaned Leopardus tigrinus (Schreber, 1775) and Leopardus pardalis (Linnaeus, 1758), the first register of the infection by group A rotavirus in these species. Both felids were rescued in the Pará State Amazon Brazil by the IBAMA (the Brazilian Institute of Environment and Renewable Natural Resources), and treated by veterinarians into intensive care ward in a public Environmental Park of Belém city. After the adaptation period to the quarantine, these animals showed non-specific symptoms of acute fulminant gastroenteritis. Rotavirus group A antigen was identified in blood and faecal samples of L. tigrinus analyzed by immunochromatography (ICG) and immunoassay methods (ELISA) at the Virology Laboratory of the Institute Evandro Chagas. The animals died within few days during the clinical exacerbation unresponsive to current treatment, its necropsies and histopathological analysis were performed in the Laboratory of Veterinary Pathology of the Federal Rural University of Amazonia (UFRA). Despite the compatible pathologic findings of rotavirus infection in both animals, the atypical hemorrhagic character was a curious finding, considering the presumed etiology.