The main commercial variety of coffee is the Coffea arabica specie, however, it is very susceptible to damage caused by nematodes, for this reason scions of the C. arabica specie are used on ro-busta (Coffea canephora) rootstocks to improve tolerance to these microorganisms, because they modify the organoleptic, nutraceutical and nutritional characteristics. The objective of this work was to assess the effect of five roasting degrees on commercial beans (light, medium light, medi-um, medium, medium dark and dark) in two varieties of Coffea arabica species (Colombia and Costa Rica) and their respective scions on C. canephora of the Romex variety. The scion of the Co-lombia variety with the medium dark roast had the highest concentration of caffeine, while the coffee beans of the Costa Rica variety with the light roast grade had the highest concentration of chlorogenic acid (5-CQA), while the highest acrylamide content was found in the scion of the Co-lombia variety with the medium light roast beans and nutritional content differs considerably between varieties, however, there is similarity between roasting degrees. The degree of roasting, variety and scion of coffee influences the organoleptic, nutraceutical and nutritional content of the coffee infusion.

The shoot apical meristem (SAM) gives rise to the aerial structure of plants by producing lateral organs and secondary meristems. The SAM is responsible for plant developmental patterns, thus determining plant morphology and, consequently, many agronomic traits such as the number and size of fruits and flowers and kernel yield. Our current understanding of SAM morphology and regulation is based on studies conducted mainly on some angiosperms, including economically important crops such as maize (Zea mays) and rice (Oryza sativa), and the model species Arabidopsis (Arabidopsis thaliana). However, studies in other plant species from the gymnosperm class are scant, making difficult comparative analyses that help us understand SAM regulation in diverse plant species. This limitation prevents deciphering the mechanisms by which evolution gave rise to the multiple plant structures within the plant kingdom, and determined the conserved mechanisms involved in SAM maintenance and operation. This review aims to integrate and analyze the current knowledge of SAM evolution by combining the morphological and molecular information recently reported from the plant kingdom.

Adolescence is a stage of change and transition, which together with the COVID-19 situation, has been a huge source of vulnerability and facilitated the development of emotional disorders. This study aims to analyse internalising (anxiety and depression) and externalising (anger and aggression) symptoms in adolescence according to gender, as well as personal resources (self-esteem, social competence and integration, and awareness of problems) put in place as a mechanism of protection and coping after the situation of the pandemic. The study population encompassed 445 adolescents, of whom 230 were boys and 215 were girls, between the ages of 12 and 17. A self-reported Likert-type test was used. Findings indicate that girls show greater levels of internalising (anxiety and depression) and externalising problems (anger), finding no differences for the variable aggression between the two groups. Personal resources are closely linked to emotional symptomatology, providing a source of protection in both genders. The findings indicate a maladaptive pattern for adolescents that requires early intervention within the field of education.

Background: Over the past two decades, various research teams have designed and applied instruments to measure the quality of life of families with a member who has a disability. A recent systematic review on the state of art of Family Quality of Life in early care identified that many of these studies collected data only from the mothers. The present study aimed to investigate whether there is a bias in participant selection in these types of studies. Method: A systematic review of the scientific literature was conducted in the 3 databases from the year 2000 to 2022. A total of 72 empirical studies have been identified. Results: The findings indicated that most studies examining the family quality of life were based on the information of a single informant per family unit. The profiles of participants according to the research objective is quite similar. In one third of studies the authors report that family members who participate cannot be represented by only mothers or one participant per household. Conclusions: Given the dynamic and collective nature of the construct, the application of a systemic approach is necessary.

Background: The duration of the vaccine's protective efficacy against SARS-CoV-2 is unknown. Evaluation of the clinical performance of available tests is required. Objectives: To evaluate the clinical performance of three immunoassays for the detection of IgG antibodies generated by mRNA vaccines against SARS-CoV-2. Methods: Two automated immunoassays (Euroimmun Anti-SARS-CoV-2 ELISA IgG and Abbott SARS-CoV-2 CLIA IgG) and one lateral flow immunoassay (LFIA Test Livzon IgG) were tested. 300 samples distributed in 3 groups were analyzed: 100 subjects over 18 years old and under 45 years old, 100 subjects between 45-65 years old and another 100 over 65 years old. collected before vaccination, at 21 days, 1, 2, 3 and 6 months post-vaccination. Sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, and agreement (I. Kappa) were calculated for each serological test. Results: Maximum sensitivity for IgG was 98.7%, 98.1%, and 97.8% for the ELISA Euroimmun, CLIA Abbott, and Livzon LFIA assays and maximum specificity for IgG was 99.4%, 99.9%. % and 98.4% ELISA, CLIA and LFIA respectively at 3 months after vaccination with a decrease in antibody levels from the sixth month. The best agreement was observed between ELISA and CLIA 100%; (k = 1.00). The agreement between ELIA, CLIA and LIFIA was 99% (k = 0964) at the second and third month after vaccination. Seroconversion was faster and longer lasting in the younger age groups. Conclusion: Our study showed an equivalent and homogeneous clinical performance for IgG of three immunoassays after vaccination and that the LIFIA assay is the most cost-effective, reliable and accurate for routine use in population studies of seroconversion and seroprevalence.

The current work shows the optimization in the preparation of nanosized titanium carbide (TiC) in-situ through mechanical alloying (MA). Metallic titanium (Ti) powders, along with two carbon sources, carbon nanotubes (CNTs), and stearic acid (SA), were used to reduce the particle size using a high-energy Spex800 mill. The combined use of 2 wt % of these carbon sources and n-heptane as a liquid process control agent (PCA) proved crucial in generating nanoscale powder composites through a simple and scalable synthesis process within a 4-hour timeframe. The use of 20 wt % of both carbon sources was compared to determine the ability of CNTs to form carbides and the decomposition of PCAs during mechanical milling. The result reveals structures like nanoblocks and nanolumps with and important size reduction. The structure and morphology of the composites and starting materials were evaluated through x-ray diffraction (XRD), Raman spectroscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM).

This study analyzes tree diversity and its ecological importance value in silvopastoral systems in the Sumaco Biosphere Reserve (SBR), Ecuador, along an altitudinal gradient of 400-2000 masl. Twenty-six plots distributed in low (400-700 masl), medium (701-1600 masl) and high (1601-2000 masl) zones were used. The Shannon index and the Importance Value Index (IVI), based on abundance, dominance and relative frequency, were estimated. The results show variations in the diameter structure of the trees, influenced by factors such as settlement history and pasture management. The lower and middle zones showed higher tree density and diversity, linked to regeneration and the presence of nearby forests. Species of high commercial value, such as Cedrela odorata and Jacaranda copaia, were common, reflecting knowledge of the local timber market. In the lower and middle zones, the 10 most important species accounted for more than 70% of the trees, and up to 96% in the upper zone, indicating the need for further research on abundance factors and promotion of diversification in pastures. A total of 51 tree species were identified, mostly native, 64.7% are classified by the IUCN as "Least Concern", 31.4% as "Not Evaluated", and 3.9% as "Vulnerable", specifically highlighting Cedrela odorata and Cedrela Montana. The study concludes with policy recommendations related to the importance of trees in silvopastoral systems for the conservation of species and the livelihoods of local communities, highlighting the need for responsible management of Amazonian pasturelands.

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

Different surveillance studies (2005-2015) on the presence of ESBL-producing E. coli in the northwest Spain revealed that eae-positive isolates of serotype O153:H10 were periodically detected in meat (of beef, chicken and pork), and also implicated in human diarrhea. This study aimed: i) to characterize the degree of relatedness between human and animal isolates; ii) to know if this was a geographically restricted or disseminated genetic lineage. Thirty-two isolates were conventionally typified as O153:H10-A-ST10 fimH54, fimAvMT78, traT and eae-beta1, being 21 of those CTX-M-32 or SHV-12 producers. PFGE comparison of their macrorestriction profiles showed high similarity (>85%). The plasmidome analysis revealed a stable combination of IncF (F2:A-:B-), IncI1 (STunknown) and IncX1 plasmid types, together with non-conjugative Col-like. Besides, the core genome investigation based on the cgMLST scheme from Enterobase, proved close relatedness between isolates of human and animal origin. Our results demonstrate that a hybrid MDR aEPEC/ExPEC of clonal group O153:H10-A-ST10 (CH11-54) would be playing a successful role in spreading ESBLs (CTX-M-32) in our region within different hosts, including wildlife. It would be potentially implicated in human diarrhea via food (meat) transmission. Importantly, we proved genomic evidence of a related hybrid aEPEC/ExPEC in other countries.

Personal protective equipment (P PE) rules must be respected and followed to the letter of healthcare professionals in Cameroon to avoid the transmission of infectious diseases. This research proposes solutions to the problems of non-adherence and non-compliance among healthcare workers in Cameroon towards PPE rules. Inadequate access to suitable PPE, discomfort when wearing PPE during poor quality, and a lack of training on correct PPE use are just a few of these obstacles amongst HCWs in Cameroon. Hospitals and healthcare facilities should prioritize offering thorough instruction on PPE use and pinpoint the need to adhere consistently to PPE rules to remove these obstacles. They should also ensure that all healthcare personnel have access to and a sufficient supply of the proper PPE. Through the organization of impromptu visits by surveillance teams to identify areas of support and training, there is a need for assistance from government bodies and public health groups in creating awareness of the security value of PPE use among healthcare professionals. There is a lack of PPE in health care settings in rural areas in Cameroon, thus a need for an adequate supply. Then can we put appropriate PPE policies and practices for HCWs in Cameroon, as they will keep to it.Healthcare professionals in Cameroon must comprehend that following PPE standards protects not just their selves from diseases but also their patients, coworkers, and communities. We are accountable for ensuring everyone's safety and well-being, and adhering to PPE regulations is an essential first step.

It is concerning that Cameroon's urban centers are experiencing an alarming rise in air pollution as a result of urbanization, population growth, industrial activity, and transportation emissions. We examined the causes, health impacts, research methodology, case studies, and government measures to address the urgent issue of air pollution in Cameroon's urban regions. We have emphasized how Cameroon's air pollution levels have significantly increased as a result of causes like population expansion, urbanization, industrial emissions, and automobile exhaust A thorough discussion of the negative health impacts of extended exposure to air pollution is included, with special attention to the sensitivity of the old and young. These effects include respiratory disorders, cardiovascular ailments, and early mortality. We emphasized the pressing need for all-encompassing strategies to address air pollution, such as increased public awareness campaigns, stronger emissions regulations, the development of renewable energy sources, and better waste management. The techniques employed in studies on air pollution, like as epidemiological research and air quality monitoring, are also explained to provide light on the unique health dangers that Cameroonian urban dwellers must contend with. We emphasized in our conclusion the significance of joint efforts by legislators, medical professionals, and the general people to reduce air pollution and protect public health in Cameroon in order to create a cleaner and healthier future. In order to protect public health in the future, it is imperative that Cameroon's air pollution be addressed.

The fact that real dissipative (entropy producing) processes may be detected by non–comoving observers (tilted), in systems that appear to be isentropic for comoving observers, in general relativity, is explained in terms of the information theory, in analogy with the explanation of the Maxwell's demon paradox.

This article addresses the emergence of a niche for sustainable agricultural production in the province of García Rovira, Colombia. It examines the intervention of the Colombian planning regime, which implements agendas for sustainable territorial development. However, these agendas are not adequately aligned with provincial realities, resulting in a productive decline. From a multi-level perspective, a niche of production linked to the landscape is identified, highlighting sustainable practices and innovation. The study seeks to understand how planning influences the emergence of such niches and what factors boost their transition to sustainability. Through a mixed methodology, growing sectors are highlighted, and the profiles of the producers involved are outlined. The main conclusion is that the planned intervention is inefficient, as the niche of sustainable production emerges without its clear influence. Therefore, it is proposed to re-evaluate planning using alternative analysis frameworks to detect emerging productive dynamics, serving as a basis for future plans.

Smoked cigarette butts (SCB) can be used as precursors to obtain activated carbon (AC) due to their high carbon content related to the presence of cellulose acetate and components that are retained in the tobacco combustion process. In this way, it was analyzed how the process of pyrolysis or formation of char from this residue occurs, for this a study of the kinetics of formation of char is carried out by thermogravimetry, using three heating speeds 5, 10 and 15 °C/min. Based on the data obtained, mathematical models such as Kissenger - Akahira - Sunose (KAS), Starink (STK) and Ozawa - Flynn - Wall (OFW) were used in order to identify thermodynamic parameters through the energy of activation. The char obtained was subjected to an activation treatment with KOH in order to increase the surface area and pore volume, obtaining values of 433 m2/g of BET area and 0.25 cm3/g of micropore volume. Finally, the adsorbent was applied in the removal of Cr (VI) obtaining a Qmax capacity determined by the Langmuir model of 55.8 mg/g.

Knowledge management gains space within the school organization and can contribute satisfactorily to the quality of teaching. In everyday life the school manager intuitively uses knowledge management practices without exploiting the potentials they offer or allow. In this context, the purpose of this work is to identify the level of implementation of knowledge management practices aimed at structuring the organizational processes used by the public school manager. The methodology adopted was exploratory, with a qualitative and quantitative approach. For data collection, an already validated instrument with twenty-seven questions was used. Respondents to the questionnaires, one hundred and eleven managers of the basic education schools that make up the public school system in a city in the northwestern region of Paraná, Southern Brazil. In analyzing the results, it was only at this point that we investigated only those practices that were related to the structuring of organizational processes. This decision is justified because of the responsibilities of the school manager in the execution of his work. The results indicated that the school in its daily life, makes use of practices of Knowledge Management related to the structuring of the organizational processes and that many are already applied by the managers.

This review article focuses on the role of Artificial Intelligence (AI) in transforming healthcare in Africa, specifically in combatting infectious diseases, neglected tropical diseases (NTDs), and antimicrobial resistance. We provide a comprehensive overview of the significance of AI in the healthcare industry, highlighting its urgency and importance in addressing these specific health challenges in Africa. We begin by discussing the role of AI in infectious disease surveillance and outbreak detection. We explore how AI technology can be employed for real-time tracking and prediction of outbreaks, providing examples of successful AI applications in infectious disease surveillance within the African context.Next, we examine the potential of AI-enabled diagnosis and treatment for faster and more accurate diagnoses of infectious diseases and NTDs. We highlight specific examples of AI applications in diagnosing and treating these diseases in Africa, showcasing the potential of AI to improve clinical outcomes and save lives.Furthermore, we focus on how AI-driven drug discovery and development can expedite the search for new treatments for infectious diseases and combat antimicrobial resistance. We present examples of AI applications in drug discovery within the African context, illustrating the potential for AI to revolutionize the development of effective therapeutics.In addition, we delve into how AI-powered public health interventions can enhance the design and implementation of targeted interventions. We explore how AI can optimize resource allocation and facilitate data-driven decision-making processes, providing examples of AI applications in public health in Africa.Finally, we address the challenges and limitations of implementing AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. We discuss potential barriers and ethical concerns surrounding AI applications in healthcare, aiming to encourage informed and responsible utilization of AI technologies.Overall, this review emphasizes the importance and potential of AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. It positions AI as a catalyst for revolutionizing healthcare in the region, leading to more effective disease surveillance, diagnosis, treatment, drug discovery, and public health interventions.

This work proposes a physics-based identification technique based on genetic algorithms. The main objective is to obtain a parametric matrix A that describes the time-invariant linear model of the longitudinal dynamics of an aircraft. This is achieved by proposing a fitness function based on the properties of the transition matrix and taking advantage of some of the capabilities of the genetic algorithm, mainly those of restricting the search ranges of the unknowns. In this case, such unknowns are related to the type of aircraft and flight conditions that are considered during the identification process. The proposed identification method is validated with a reliable nonlinear model that can be found in the literature, as well as with the calculation of the trim condition and linearization generally used in aircraft dynamics. In summary, this study suggests the genetic algorithm provided with the adequate fitness function, could be an appealing alternative for aircraft model identification, even when only a limited amount of data is available. Furthermore, in some cases, linearization using genetic algorithm can be more efficient than classical methods.

Extra virgin olive oil, water, and water/oil mixture (W/O) were used to fry, boil and sautée Mediterranean vegetables. We determined the variations between unused and used water and oil for the contents of total (TPC) and individual phenolic compounds measured by HPLC, and the antioxidant capacity (AC) by DPPH, FRAP and ABTS methods. The highest TPC value was found in water used to boil tomato, whereas the lowest in the EVOO from the W/O used for boiling potatoes. The TPC decreased in the processed EVOO, whereas the water was enriched after boiling. After processing, the concentrations of phenols exclusive to EVOO diminished with differentiated behavior, from complete elimination of hydroxytyrosol and tyrosol after sautéeing and W/O boiling, to conservation of pinoresinol. The transfer of phenols such as chlorogenic, gallic, dihydroxybenzoic, hydroxybenzoic and hydroxyphenylacetic acids, as well as luteolin, apigenin and vanillic acid from the vegetable to the oil was frequent when eggplant, tomato and pumpkin were cooked. The cooking water was enriched in most of the phenols analysed, as the case of chlorogenic acid and phenols exclusive to EVOO after W/O boiling. The values of AC in the fresh oil decreased or were maintained after being used to cook the vegetables. With some exceptional increases in the oil used for frying (p<0.05). The cooking techniques were classified in decreasing order according to the AC as follows: raw>deep frying>sautéing>boiling. This pattern was more consistent with DPPH results (from potato, eggplant and pumpkin) than in those of ABTS (pumpkin) and FRAP (eggplant). The water fraction recovered from boiling was enriched in Trolox equivalents being higher when EVOO was added. Phenolic content and AC in the EVOO decreased after cooking Mediterranean Diet vegetables, whereas the water was enriched after the boiling processes, particularly when oil was included.

The broad bean plant contains L-DOPA, a compound that is essential for patients with Parkin-son’s disease. However, little has been reported on other broad bean compounds that have bene-ficial effects on health. The objective was to evaluate plants of four Mexican broad bean varieties to determine the content and yield of total phenolic compounds (TPC), total flavonoids (TF), and L-DOPA, as well as to analyze the flavonoid profile and antioxidant (AA) and anti-inflammatory (AANTI) activity in vitro. Broad bean seeds were sown in the field and plants were harvested 20 days after emergence. The analyses were performed with visible UV spectrophotometry and HPLC. The variety José María produced the highest yield of TPC (9.30 g m-2), TF (8.08 g m-2) and L-DOPA (5.64 g m-2) per unit of area. The highest yields per plant were obtained with the Rojita variety: TPC (0.25 g plant-1), TF (0.21 g plant-1) and L-DOPA (0.17 g plant-1). This variety also had the highest antioxidant (CI50= 87.68 µg mL-¹) and anti-inflammatory (CI50= 74.40 mg mL-1) activi-ty, which was attributed to the L-DOPA compounds and to rutin and isoorientins, respectively. The flavonoid profile revealed the presence of rutin and isoorientins, which had not been previ-ously detected in the broad bean plant.

The healthcare situation in Africa is characterized by limited resources and a high burden of disease, presenting significant challenges to the healthcare systems in the region. The integration of Artificial Intelligence (AI) technologies in African healthcare holds immense potential for addressing these challenges and improving health outcomes. This paper aims to provide a comprehensive understanding of the current healthcare landscape in Africa and the urgent need for AI-driven solutions.In addition to discussing the potential applications of AI in African healthcare, such as disease diagnosis, treatment planning, and medical imaging analysis, this manuscript seeks to shed light on the specific challenges hindering the implementation of AI in the region. By providing detailed examples and case studies, we aim to offer insights into the obstacles that need to be overcome and potential solutions that can be pursued.By leveraging AI technologies, Africa has the opportunity to revolutionize its health systems, bridging the gap in access to quality healthcare across the continent. The objective of this review article is to not only highlight the potential benefits that AI can bring to African healthcare but also to emphasize the urgent need for action and collaboration in implementing and scaling up AI innovations in the region. By doing so, African countries can pave the way for improved health outcomes and ensure that their populations receive the healthcare services they deserve.

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

Chronic kidney disease is a critical health crisis in the US, affecting about 37 million adults. Known as "the silent killer" because it is often undiagnosed until it has reached a stage of progression. Renal dysfunction causes many adverse effects to the body's biological mechanisms, such as fluid electrolyte and pH balance, blood pressure regulation, excretion of toxins and waste, vitamin D metabolism, and hormonal regulation. Many CKD patients experience hyperkalemia, hyperphosphatemia, chronic metabolic acidosis, bone deterioration, blood pressure abnormalities, and edema. Symptoms experienced may be minimized, and the disease's progression may be slowed through an appropriate diet, which is why medical nutrition therapy is a critical aspect of the medical intervention for CKD. The current KDOQI recommendations are proposed as well as the physiological mechanisms behind the recommendations. Current biological explanations of the effects of a whole foods plant-based diet are included for possible contrast with the current renal diet. Strong evidence continues to support the importance of proper nutrition in the prevention and progression of kidney disease.

Flying-fox populations are increasingly threatened by heat events, starvation events and other stressors due to habitat clearing and human/flying-fox conflict.These factors are unlikely to resolve, meaning that a well-coordinated and timely approach to flying-fox disasters is imperative for the mitigation of further flying-fox population impacts.

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

A two scalar field model that incorporates non Riemannian Measures of integration or usually called Two Measures Theory (TMT) is introduced, in order to unify the early and present universe. In the Einstein frame, a K-essence is generated and as a consequence for the early universe, we can have an Inflation for the very early universe and then, after inflation, an early dark energy period and a late dark energy period for the present universe dark, both dark energy epochs have a consistent generation of dark energy (DE), dark matter (DM) and stiff matter. This is obtained when the scale invariance is introduced and then is spontaneously broken from the integration of the degrees of freedom associated with the modified measures. The resulting effective potentials and K-essence in the Einstein frame produce the three flat regions corresponding to the different epochs mentioned before. For the first flat region, we can associate an inflationary universe. Also assuming this first plateau, we study the inflation in the framework of the slow-roll approximation. In this scenario under the slow roll approximation, we obtain a linear combination that is a constant. The corresponding cosmological perturbations in our model are determined and we also obtain the different constraints on the parameter-space from the Planck data. The slow roll approximation can be arranged so that the transition from inflation to the next flat region can be achieved without problems. In the following two flat regions, in addition to the inflation phase, representing the Early Dark Energy and Late Dark Energy Periods, with DE and also the DM, do not need to be introduced separately, they are instead a result of a K-essence induced by the multi measures, multi field theory. Therefore the scalars generate both the DE and the DM . Also a stiff matter component is automatically generated from the K-essence theory from two scalar fields. From the perturbative analysis associated to the perturbation solution of background, we find a correlation between the two scalars. Besides, we obtain that our model during the dark epoch has a behaviour of tracking freezing mode

Despite increased hurricane intensity, the U.S. Gulf of Mexico coast has experienced dramatic coastal population increase of 24.5% from 2000 to 2016. However, in coastal Louisiana areas with dramatic wetland loss, parishes have experienced population declines and lower rates of population growth. Therefore, understanding the magnitude of the effect of wetland loss as a main driver in population loss in coastal Louisiana is critical. Using regression analysis, this study finds that wetland loss has a significant and persistent negative effect on population growth in coastal Louisiana. This effect resulted in a reduction in the population growth rate in coastal parishes over time. A counterfactual simulation was conducted to estimate the potential population size in the absence of wetland loss from 1990 to 2021. On average, the effect of 1 hectare of wetland lost causes a reduction of approximately 1000 persons. This indicates that for the year 2021, the population was approximately 18% lower than the population that would have existed in the absence of wetland loss. This research underscores the role of wetlands in providing direct and indirect benefits to people in coastal Louisiana that are ultimately reflected in its population levels.

Artificial intelligence (AI) is increasingly being used to improve the quality control of point-of-care diagnostics. This is caused by a number of factors, including the following: 1. AI can accelerate and improve testing accuracy. In comparison to humans, AI technology can review data more quickly and precisely, reducing errors and improving overall quality assurance. 2. When it comes to improving POC test findings on healthcare issues such as infectious diseases or medical crises such as heart attacks, AI can be used for sophisticated predictive analytics and modeling that aid in better decision-making. 3. Artificial intelligence facilitates process automation, increasing productivity and lowering labor costs in labor-intensive tasks such as testing and analyzing samples collected at point-of-care facilities. 4. The use of AI enables organizations implementing these solutions to gain insights from large volumes of raw diagnostic data generated faster and more accurately, allowing them to build solid frameworks around preventive care initiatives and significantly influence public health outcomes.5. Artificial intelligence (AI) has been demonstrated to be a useful tool for real-time monitoring systems that identify any problems with test results early so that they can be corrected before affected patients receive inaccurate diagnoses or treatment plans based on false information provided by diagnostic tests performed at points of care such as clinics or hospitals.Using these technologies would allow healthcare organizations to spend less on labor while still receiving exact diagnoses and rapid treatment delivery at a fraction of the cost that manual approaches required earlier.

The cornea is an avascular tissue which has attracted much attention by the uniqueness of its anatomical characteristics, it has, in proportion, an enormous size, in relation to the number of vessels, because on average few cells in the organism are away more than 30 microns of a blood vessel. However, the cornea, with a diameter of between 11 and 12 mm, is a unique example. It has been tried to explain the notable absence of blood vessels in the cornea, arguing that corneal tissues are able to take oxygen directly from the air. In this article we are explaining that based on the physicochemical characteristics of molecular oxygen and the cell membrane, cytoplasm, water, and cellular metabolism, it is not possible that epithelial corneal cells directly take oxygen from the air, instead, corneal cells have molecules that can dissociate the water molecules thereby these cells, like any other eukaryotic cells, take the oxygen from the intracell water, like plants.

Background & aims: Malnutrition in lung transplant (LT) candidates increases postoperative morbidity and mortality. Early diagnosis of malnutrition could attenuate adverse prognostic factors. This study aimed to assess the prevalence of nutritional risk and malnutrition using GLIM criteria in LT candidates and clinically characterize those with malnutrition. Methods: A prospective longitudinal study was conducted from 2000 to 2020 of LT candidates who underwent complete nutritional assessment (nutritional screening, anthropometry, bioelectrical impedance, blood laboratory tests and malnutrition diagnosis using GLIM criteria). Results: Obstructive diseases (45.6%), interstitial diseases (36.6%) and cystic fibrosis/non-cystic fibrosis bronchiectasis (15.4%) were the main conditions assessed for LT. Of the 1060 candidates evaluated, 10.6% were underweight according to BMI, 29% were at risk of malnutrition and 47% were diagnosed with malnutrition using GLIM criteria. Reduced muscle mass was the most frequent GLIM phenotypic criterion. Malnutrition was more prevalent in patients with cystic fibrosis/non-cystic fibrosis bronchiectasis (84.5%), obstructive (45.4%) and interstitial (31.3%) diseases. GLIM criteria detected some degree of malnutrition in all diseases requiring LT and identified patients with higher CRP levels and worse respiratory function, anthropometric measurements and visceral protein and lipid profiles. Conclusions: LT candidates present a high prevalence of malnutrition using the GLIM algorithm. GLIM criteria detected malnutrition in all diseases requiring LT and defined patients with worse clinical-analytical profiles.

The energy matrix worldwide has been going through difficulties in its discussions - such as irregular exploration, inefficient public policies, and arbitrariness concerning diplomatic and political definitions of those involved in this market. This work's general objective consists in analyzing associations and statistical inferences of the largest world oil producers, assimilating the contributions and singularities of this market from 1993 to 2020. Based on the Organization of the Petroleum Exporting Countries (OPEC), it was possible to identify the possible inferences and contributions of the ten largest oil producers in the world in more than two decades using statistical analysis through correlation, regression, and statistical analysis of variables. According to the research and the literature on the area, the oil market proposes support to its discussions, mainly in its productive approaches. It is possible to identify this market as a solid link to geopolitical actions, distributing the possibilities through economic bias and socio-cultural and historical factors on a global level.

A large diversity of epigenetic factors, such as microRNAs and histones modifications, are known to be capable of regulating gene expression without altering DNA sequence itself. In particular, miR-1 is considered the first essential microRNA in cardiac development. In this study, miR-1 potential role in early cardiac chamber differentiation is analyzed through specific signaling pathways. For this, we performed in chick embryos functional experiments by means of miR-1 microinjections into the posterior cardiac precursors -of both primitive endocardial tubes- committed to sinoatrial region fates. Subsequently, embryos were subjected to whole mount in situ hybridization, immunohistochemistry and RT-qPCR analysis. As a relevant nov-elty, our results revealed that miR-1 increases Tbx5, Gata4 and AMHC1, while this microRNA diminishes Mef2c expression, during early differentiation of cardiac sinoatrial region. Further-more, we observed in this developmental context that miR-1 upregulates CRABPII and RARß, and downregulates CRABPI, which are three crucial factors in retinoic acid signaling pathway. Interestingly, we also noticed that miR-1 directly interacts with HDAC4 and Calmodulin, as well as with Erk2/MAPK1, which are three key factors actively involved in Mef2c regulation. Our study shows, for the first time, a key role of miR-1 as an epigenetic regulator in early differenti-ation of cardiac sinoatrial region through orchestrating opposite actions between retinoic acid and Mef2c, fundamental to properly assign cardiac cells to their respective heart chambers. A better understanding of those molecular mechanisms modulated by miR-1 will definitely help in fields applied to therapy and cardiac regeneration and repair.

Seizure-mediated oxidative stress is a crucial mechanism in the pathophysiology of epilepsy. This study evaluated the antioxidant effects of daytime-restricted feeding (DRF) and the role of the Nrf2 signaling pathway in a lithium-pilocarpine model seizure model that induces status epilepticus (SE). We performed a lipoperoxidation assay and dihydroethidium fluorescence to measure oxidative stress markers in the hippocampus (malondialdehyde and reactive oxygen species). The protein content of Nrf2 and its downstream protein SOD2 was evaluated by Western blot. Cellular distribution of the Nrf2 and SOD2 proteins in the pyramidal cell layer of both CA1 and CA3 hippocampal subfields and astrocytes (GFAP marker) were quantified by immunofluorescence and immunohistochemistry respectively. Our results indicate that DRF reduced malondialdehyde levels and the production of reactive oxygen species. Furthermore, a significant increase in Nrf2 and SOD2 protein content was observed in animals subjected to restrictive diet. In addition, DRF increased the relative intensity of the Nfr2 fluorescence in the perinuclear and nuclear compartments of pyramidal neurons in the CA1 subfield. Nfr2 immunoreactivity and the astrocyte marker GFAP also increased their colocalization in DRF conditions. Also, SOD 2 immunoreactivity was increased in CA1 pyramidal neurons but not in CA3 region. Our findings suggest that DRF partially prevents oxidative stress by increasing the Nrf2 transcriptional factor and the SOD2 enzyme during the development of SE.

The Pashmina and Barbari are two famous goat breeds found in the wide areas of the Indo-Pak region. Pashmina is famous for its long hair-fiber (Cashmere) production while Barbari is not-selected for this trait. So, the mRNA expression profiling in the skin samples of both breeds would be an attractive and judicious approach for detecting putative genes involved in this valued trait. Here, we performed differential gene expression analysis on publicly available RNA-Seq data from both breeds. Out of 44,617,994 filtered reads of Pashmina and 55,995,999 of Barbari which are 76.48% and 73.69% mapped to the ARS1 reference transcriptome assembly respectively. A pairwise comparison of both breeds resulted in 47,159 normalized expressed transcripts while 8,414 transcripts are differentially expressed above the significant threshold. Among these, 4,788 are upregulated in Pashmina while 3,626 transcripts are upregulated in Barbari. Fifty-nine transcripts harbor 57 genes including 32 LOC genes and 24 are annotated genes which were selected on the basis of TMM counts > 500. Genes with ectopic expressions other than uncharacterized and LOC symbol genes are Keratins (KRT) and Keratin Associated Proteins (KRTAPs), CystatinA&6, TCHH, SPRR4, PPIA, SLC25A4, S100A11, DMKN, LOR, ANXA2, PRR9 and SFN. All of these genes are likely to be involved in keratinocyte differentiation, sulfur matrix proteins, dermal papilla cells, hair follicles proliferation, hair curvature, wool fiber diameter, hair transition, hair shaft differentiation and its keratinization. These differentially expressed reported genes are critically valuable for enhancing the quality and quantity of the pashmina fiber and overall breed improvement. This study will also provide important information on hair follicle differentiation for further enrichment analyses and introducing this valued trait to other goat breeds as well.

In the intricate dance between viruses and host cells, RNA-binding proteins (RBPs) serve as crucial orchestrators of gene expression and cellular processes. We will delve into the riveting realm of viral hijacking, where viruses deftly exploit host RBPs to manipulate cellular machinery for their replication and pathogenesis. Through a masterstroke of molecular subterfuge, viruses co-opt RBPs involved in various facets of RNA metabolism - from transcription to degradation - to promote viral gene expression and evade host immune defenses. This manipulation leads to global alterations in cellular RNA metabolism, impacting essential host genes vital for immune responses and homeostasis.Unveiling this clandestine alliance between viruses and RBPs is not just a scientific pursuit, but a critical imperative for devising innovative antiviral strategies to disrupt these interactions. By unraveling the intricate interplay between viral proteins and host RBPs throughout the viral life cycle - from entry to assembly - researchers aim to identify vulnerabilities that can be targeted for therapeutic intervention. Strategies such as disrupting viral protein-RBP interactions hold promise for inhibiting viral replication and curbing pathogenesis, offering a beacon of hope in the battle against viral infections.Our manuscript elucidates the indispensable roles played by RBPs in viral replication, translation, and pathogenesis, shedding light on the molecular mechanisms driving viral success. Delving deeper, it explores how viruses intricately entwine with host RBPs, manipulating cellular signaling pathways to create a hospitable environment for viral spread. By dissecting these manipulative tactics, researchers uncover new targets for antiviral therapy, envisioning a future where tailored interventions disrupt viral-host RBP interactions with precision and efficacy.As the narrative unfolds, the therapeutic implications of targeting RBPs or their interactions with viral proteins emerge as a promising frontier in the fight against viral infections. From small molecule inhibitors to RNA-based therapeutics, innovative approaches are on the horizon, offering new avenues for combatting viral diseases. We set the stage for future research, beckoning researchers to delve deeper into the molecular intricacies of viral hijacking of RBPs and charting a course towards novel therapeutic interventions that promise to reshape the landscape of antiviral therapy.\Ultimately, it beckons the scientific community to embark on a voyage of discovery, unraveling the secrets of viral hijacking of RBPs and paving the way for transformative advances in antiviral therapeutics. The stage is set for a new chapter in the battle against viral infections, where knowledge becomes the sword and innovation the shield against the pernicious machinations of viral pathogens.

An advanced, cost-effective and portable DNA biosensor capable of detecting multiple bacteria simultaneously have been developed. The biosensor consists of a fast and inexpensive potentiostat that controls the applied potential to a screen-printed electrochemical array platform functionalized with MoS2 flakes and bacteria DNA probes, and monitors the current response obtained by the use of à la carte thionine functionalized carbon nanodots (Ty-CDs) as electrochemical indicator of the hybridization event. The design of the potentiostat prioritizes achieving an optimal signal-to-noise ratio and incorporates a user-friendly interface compatible with various devices such as computers, mobile phones and tablets. The device is compact, lightweight, and manufactured at a low cost. The key components of the potentiostat include a data acquisition board capable of analyzing multiple samples simultaneously and a controller board. The results obtained confirm the ability of the developed device to successfully detect specific bacteria DNA sequences, demonstrating the reliability and performance of the developed multiplexing portable biosensor with better sensibility than using a traditional, more complex and laboratory oriented potentiostat.

Brucellosis infection induces fever, chills, sweats, headache, myalgia, arthralgia, anorexia, fa-tigue, and mood disorders. In mice, it causes a rise in IL-6, TNF-, and IFN-; and reduces sero-tonin and dopamine levels in hippocampus. There is loss in muscle strength and equilibrium and increased anxiety and hopelessness. Imipramine (ImiP) is a tricyclic antidepressant that increases the capacity of macrophages to destroy intracellular microorganisms in vivo. The effect of ImiP was evaluated in Balb/c mice infected with Brucella abortus 2308. Serum levels were determined in IFN-, IL-6, TNF-, IL-12, MCP-1, and IL-10 by FACS; the bacterial count in the spleen, by CFU; the serotonin concentration in the hippocampus, by HPLC; and strength, equilibrium, and mood by behavioral tests. Our results showed that infected vs. control mice had a significant rise in lev-els of IFN-, IL-6, TNF-, and IL-12 with a low IFN-/IL-6 ratio, elevated bacterial-counts, alter-ations in serotonin concentration at hippocampus, and decreased muscular strength, equilibrium, and mood. Infected mice treated with ImiP vs. infected mice showed: 1) improved mood; 2) in-creased hippocampal serotonin availability, splenic dendritic cells, and macrophage phagocytic activity; and 3) upturn inflammation and reduced CFU ability. Our results support that ImiP fa-vors positive outcomes in subjects handling Brucella infections likely by improving psychoim-mune resilience.

The study was carried out in zone 7 of Ecuador, in ecosystems of the Southern Montane Evergreen Forest of the Eastern Cordillera of the Andes that goes from 2200 to 3000 masl. In the Evergreen Seasonal Lower Montane Forest of Catamayo-Alamor, which ranges from 1600-2000 meters above sea level and finally in the Semideciduous Foot Montane Forest of Catamayo-Alamor, which ranges from 400-1600 meters above sea level. The objective was to know the occurrence, structure and abundance of J. neotropica. The investigation consisted of collecting secondary information on the occurrence of the species, to later verify it in situ. Six sites with areas ≥ 0.5 hectares were identified, four in the province of Loja and two in the province of Zamora Chinchipe. Regarding the structure, it was determined that there are significant statistical differences as well as in the dasometric variables between one site and another, presenting better growths El Tundo with average values in DAP(cm)= 45.16; G(m2) = 1.41; HT(m)= 19.22; HC(m)= 13; VC(m3) = 3.55; VT(m3) = 5.22. Regarding the Morisita index, the species presents adistribution pattern &gt;1. Regarding abundance, it was determined that Algeria presented a maximum of 297 (ind/ha), and La Victoria 46 (ind/ha) with a minimum.

In this research, the photocatalytic degradation of cypermethrin using Fe-TiO2 nanoparticles supported in a biomaterial was evaluated. The nanoparticles of TiO2 were synthesized by the green chemistry method assisted by ultrasound and doped by chemical impregnation using molar ratios Fe:Ti of 0, 0.05, 0.075 and 0.1, to make efficient use of direct sunlight (λ>310 nm). All nanoparticles were immobilized on the surface of spathe of coconut palm (Cocos nucifera). The degradation was carried out at room temperature and natural pH in a flat plate solar reactor, on which the composite material was subjected. The concentration of cypermethrin was determined after 12000 J/m2 of accumulated radiation from GC-MS and the resulting material was characterized by Scanning electron microscopy (SEM), Transmission electron microscopy (TEM) image and selected area electron diffraction (SAED), Fourier transform infrared spectroscopy (FTIR), UV-Vis spectrophotometry of diffuse reflectance and BET surface area BET surface area. The best results were achieved with the use of Degussa TiO2 P-25, Fe:Ti=0 and Fe:Ti=0.05 in suspension, with percentages of degradation of cypermethrin of 99.84, 99.62, and 100%, respectively. However, the materials supported on the biomaterial of coconut, they allowed to reach degradation percentages higher than 80% with the advantage that it minimizes operating costs, since they are not necessary filtering or centrifuging processes to separate the catalyst.

Resilience has emerged as a buzzword among researchers and practitioners. However, despite its popularity, there has been little progress in moving it from an elaborate metaphor describing an idyllic state of the system to a tool for planning and managing adaptation. While case study research is rich with examples of systems that have proven to be resilient or are striving to develop resilience, there is no defined approach that operationalises concepts described in the literature into the planning process. This paper helps close this gap by illustrating how facilitated modelling can be used for resilience planning in socio-ecological systems. The paper summarizes our experience using facilitated system dynamics to inform a model-based discussion of food security resilience to climate change in Guatemala. We identify at least three positive outcomes from the intervention, which a) helped to build consensus about the meaning of resilience, b) improved stakeholders understanding of adaptation and c) outlined potential policies to enhance resilience.

1960s Europe saw a large number of residential neighborhoods built to house those migrating from the countryside. Today, more than 50 years later, these neighborhoods suffer high levels of functional, social, and technical obsolescence. In response to this, University of Seville developed the Aura Strategy as an intervention methodology to find global solutions to issues in outdated neighborhoods. To provide visibility to this aspect of the Aura strategy, the retrofit proposal presented in this article provides a solution to improve the roofing of buildings in a case study neighborhood (Polígono de San Pablo, Seville) and an analysis of the results in terms of energy and financial savings for local residents. The results show that for a population of roughly 18,000 (in 2018), net savings, including energy and retrofitting costs, ranging from nearly 6.5 to over 8.6 million can be made over the 20-year life cycle span. Likewise, the results obtained on the reduction of thermal loads indicate a 72% decrease in energy consumption, equivalent to a saving of close to 4,500 tons of greenhouse gas emissions for the district and the entire life cycle time period, with the consequent benefits on the impact on air quality and and the fight against climate change. climate change.

This study investigated the presence and characteristics of Juglans neotropica in three ecosystems in Southern Ecuador: Montane Evergreen Forest, Evergreen Seasonal Lower Montane Forest, and Semideciduous Foot Montane Forest. The main focus was on the species' multipurpose nature as both a fruit and timber source. Six study sites, totaling at least 0.5 hectares each, were established, with four in Loja province and two in Zamora Chinchipe province.The results showed significant differences in dendrometric variables across the sites, with the most favorable growth recorded in The Tundo, where trees exhibited an average diameter at breast height (DBH) of 45.16 cm, basal area (G) of 1.41 m2, total height (TH) of 19.22 m, canopy height (CH) of 13 m, cubic volume (CV) of 3.55 m3, and total volume (TV) of 5.22 m3. The species displayed a clumped distribution pattern, as indicated by a Morisita index greater than 1. Regarding abundance, the highest density of 297 trees per hectare was found in Argelia, while Victoria had the lowest density of 46 trees per hectare. This research highlights the importance of Juglans neotropica as a multipurpose species, providing both valuable fruits and wood resources in the studied ecosystems of Southern Ecuador.

The purpose of the study is to analyze the trade performance of Bangladesh during the COVID-19 pandemic. The study identifies the effects of private consumption demand shock and trade disruptions due to higher trade costs caused by the pandemic on the export and import of Bangladesh in different sectors and compares the analysis results with actual data. Based on the previous literature, this study assumes the shocks in different levels such as low, medium, and high level and identifies their effects on the trade in Bangladesh. The study applies the CGE model using GTAP to measure the effects of the shocks on trade and output and compares the actual trade with the CGE simulated results. The results of the study suggest that both demand shock and trade disruptions substantially affect the export, import, and domestic output of Bangladesh during the Covid-19 pandemic. It is also evident that the higher the level of shock, the higher the impact on trade and output. The actual export and import data cross-validate the CGE analysis results and provide mixed findings on the trade performance of various sectors of Bangladesh during the pandemic.

The main purpose of the study was to study the effects of a specific rowing ergometer training program on the athletic performance of young adolescents (n=56; 11.73 ± 1.4 years old) com-pared to a workout based on general strength training. Eight-week training program was im-plemented, with four sessions per week and two-hours per session. Sample was divided in two groups: a control group (CG) that performed circuit training with exercises aimed at building general strength and an experimental group (EG) who focused on specifically training on a rowing ergometer (rowing machine). The data obtained in a rowing meter test over the compe-tition distance were analyzed to obtain the average power attained (W) at the beginning of the training, at the middle (4 weeks), at the end of the training (8 weeks) and one year after the ex-perimentation. The results show that, although both forms of training improve the average W obtained in both categories, the EG subjects (+29.94W) obtained better averages in all phases of the study compared to the CG (+5.88W). Furthermore, this increase was greater in male rowers (+ 34.06W) than in female rowers (+24.54W). These results reveal that a specific rower rowing ergometer training program has a significant effect than a general strength program and these effects can even be observed a year after the intervention.

Porcine epidemic diarrhea virus (PEDV) has affected the pork industry worldwide and during outbreaks the mortality of piglets has reached 100%. Lipid nanocarriers are commonly used in the development of immunostimulatory particles due to their biocompatibility and slow-release delivery properties. In this study, we developed a lipid nanoparticle (LNP) complex based on glycyrrhizinic acid (GA) and tested its efficacy as an adjuvant in mice immunized with the recombinant N-terminal domain (NTD) of porcine epidemic diarrhea virus (PEDV) spike (S) protein (rNTD-S). The dispersion stability analysis (Z-potential–27.6 mV) confirmed the size and charge stability of the LNP-GA, demonstrating that the particles were homogeneously dispersed and strongly anionic, that favors nanoparticles binding with the rNTD-S protein, which showed a slightly positive charge (2.11 mV) by in silico analysis. TEM image of LNP-GA revealed nanostructures with a spherical-bilayer lipid vesicle (⁓100 nm). The immunogenicity of the LNP-GA-rNTD-S complex induced an efficient humoral response 14 days after the first immunization (P &lt; 0.05) as well as an influence on the cellular immune response by decreasing serum TNF-α and IL-1β concentrations, which was associated with an anti-inflammatory effect.

Purpose The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals has created a demand for intelligent systems with the least error-prone diagnosis results to be used by less medically trained persons and save clinical time. This paper aims at investigating the development of an image-based colourimetric analysis. The purpose of recognising such tests is to support wider users to begin a colourimetric test to be used at homecare settings, telepathology, etc. Design/methodology/approach The concept of an automatic colourimetric assay detection is delivered by utilising two cases. Training Deep Learning (DL) models on thousands of images of these tests using transfer learning, this paper i) classifies the type of the assay, and ii) classifies the colourimetric results. Findings This paper demonstrated that the assay type can be recognised using DL techniques with 100% accuracy within a fraction of a second. Some of the advantages of the pre-trained model over the calibration-based approach are robustness, readiness and suitability to deploy for similar applications within a shorter period of time. Originality/value To the best of our knowledge, this is the first attempt to provide Colourimetric Assay Type Classification (CATC) using DL. Humans are capable to learn thousands of visual classifications in their life. Object recognition may be a trivial task for humans, due to photometric and geometric variabilities along with the high degree of intra-class variabilities it can be a challenging task for machines. However, transforming visual knowledge into machines, as proposed, can support non-experts to better manage their health and reduce some of the burdens on experts.

Increasingly measured data in the context of smart cities can be used to develop new and innovative business models to increase efficiency and the value of life. A time-series classification algorithm can support to automatize many different processes such as forecasting services. In order to ensure data security and privacy, Federated Learning trains a global model collaboratively on multiple clients. Having different data-distributions and data-quantities across participating clients, neural networks suffer from slow convergence and overfitting. Based on different data-distributions, data-quantities and number of clients, we develop and evaluate different data-clustering strategies to update global model weights in comparison to the state of the art. We use public time-series data, generate various synthetic datasets and train a Relational-Regularized Autoencoder for classification purposes. Our results show an improvement of model performance concerning generalization.

Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. Here we present a new methodology combining satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, applied within slope unit polygons. We studied a former mining area in southeast Spain, and the method proved useful in detecting and characterizing a considerably large number of unstable slopes. Out of 1,959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through the validation analysis (2.5 cm/year). Eventually, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear and easily comparable information to analyze slope instabilities in different settings, not limited to mining areas.

To address the question whether there is evidence that drinking water in general or mineral water in particular is effective in preventing diabetes; we performed a literature search of randomized controlled trials (PubMed). The search resulted in very few trials (N = 9) investigating this topic: one trial investigates the effect of increasing water consumption on glycemic control in diabetic patients; two trials investigate the effect of drinking water with a meal in diabetic patients; while six trials compare the effect of mineral rich water with that of low mineralized water on glucose metabolism in healthy subjects. There is evidence that increasing water consumption can improve glucose metabolism and randomized controlled trials with mineral water suggest that waters containing relevant amounts of magnesium can exert an additional effect. The role of bicarbonate; which is present in all the mineral waters used in the trials; will be discussed. Future research needs to investigate the effect of mineral water in prediabetic individuals or individuals with impaired glycemic control.

Confinement can induce substantial changes in the physical properties of macromolecules in suspension. Soft confinement is a particular class of restriction where the boundaries that constraint the particles in a region of the space are not well-defined. This scenario leads to a broader structural and dynamical behavior than the observed in systems enclosed between rigid walls. In this contribution, we study the ordering and diffusive properties of a two-dimensional colloidal model system subjected to a one-dimensional parabolic trap. Increasing the trap strength makes it possible to go through weak to strong confinement, allowing a dimensional transition from two- to one-dimension. The non-monotonic response of the static and dynamical properties to the gradual dimensionality change affects the system phase behavior. We find that the particle dynamics is connected with the structural transitions induced by the parabolic trap. In particular, at low and intermediate confinement regimes, complex structural and dynamical scenarios arise, where the softness of the external potential induces melting and freezing, resulting in faster and slower particle diffusion, respectively. Besides, at strong confinements, colloids move basically along one direction, and the whole system behaves structurally and dynamically similar to a one-dimensional colloidal system.

This study aimed to evaluate the impact of Candida albicans on subgingival biofilm formation on dental implant surfaces. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) were used to compare biofilm structure and microbial biomass in the presence and absence of the fungus after periods of 24, 48, and 72 h. Quantitative polymerase chain reaction (qPCR) was used to quantify the number of viable and total micro-organisms for each of the biofilm-forming strains. A general linear model was applied to compare CLSM and qPCR results between control and test conditions. The biofilm developed with C. albicans at 72 h had a higher bacterial biomass, with a significantly higher cell viability (p &lt; 0.05). After both 48 and 72 h of incubation, in the presence of C. albicans, there was a significant increase in counts of Fusobacterium nucleatum and Porphyromonas gingivalis and in the cell viability of Streptococcus oralis, Aggregatibacter actinomycetemcomitans, F. nucleatum, and P. gingivalis. Using a dynamic in vitro multispecies biofilm model, C. albicans exacerbated the development of the biofilm grown on dental implant surfaces, significantly increasing the number and cell viability of periodontal bacteria.

Tantalum doped ZnO structures (ZnO:Ta) were synthesized and some of their characteristics were studied. ZnO material was deposited on silicon substrates by using a hot filament chemical vapor deposition (HFCVD) reactor. The raw materials were a pill made of a mixture of ZnO and Ta₂O₅ powders, and molecular hydrogen was used as a reactant gas. Percentage of tantalum was varied from 0 to 500 mg by varying the percentage of tantalum oxide in the mixture of the pill source, by holding a fixed amount of 500 mg of ZnO in all experiments. X-ray diffractograms confirmed the presence of zinc oxide in the wurtzite phase and metallic zinc with a hexagonal structure, and no other phase was detected. Displacements to lower angles of reflection peaks, compared with those from samples without contamination, were interpreted as the inclusion of the Ta atoms in the matrix of the ZnO. This fact was confirmed by EDS and XRD measurements. From SEM images from undoped samples exhibited mostly micro sized semi-spherical structures while doped samples displayed a trend to grown as nanocrystalline rods. The presence of tantalum during the synthesis affects the way of the growth. Green photoluminescence at naked eye was observed when Ta doped samples were illuminated by ultraviolet radiation and confirmed by PL spectra. PL intensity on Ta doped ZnO varied from those undoped samples up to 8 times.

Risk attitudes are relevant factors affecting the production and investment decisions at farm level. They are key factors that are related to farmers’ attitudes towards environment and climate change. Several methodological approaches are available to measure the level of stated risk of an economic agent. The Multiple Price List (MPL) method is one of the methods that is gaining relevance. In this study we apply the MPL and relate the risk outcomes with farmers’ characteristics and their perception towards environment and climate change. Data was collected using a face to face survey carried out for a group of 370 agricultural producers of the irrigation district located in northwest of Mexico. Results showed an average risk of about 0.32, locating the agricultural producers of the region in a group with risk aversion, according to the MPL scale. The heterogeneity analysis showed that the socioeconomic factors and the perceptions towards climate change are related to the farmers´ stated risk level. Farmers who are young women with propensity to use public support to invest were shown to be greater risk lovers. Farmers in the region have perceived climate change to a greater extent like floods, hail, diseases and pests, and changing vegetation.

Clusterin (CLU) protein is involved in various pathophysiological processes including carcinogenesis and tumor progression. In recent years, the role of the secretory isoform has been demonstrated in tumor cells, where it inhibits apoptosis and favors the acquisition of resistance to conventional treatments used to treat cancer. To determine the possible therapeutic potential of inhibiting this protein, numerous studies have been carried out in this field. In this paper, we show the existing knowledge on the inhibition of this protein in different types of cancer and discuss the importance it could have in the development of new therapies directed against this pathology.

Systems Engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address Systems Engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in Industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks; along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.

Due to their contribution to human health, the production of healthy snacks has garnered the attention of both the scientific community and the food industry. This study was conducted to determine the suitability of frying and baking processing methods for producing green banana chips using two varieties: Barraganete and Dominico. The aim was to identify a treatment geared towards producing healthy snacks. Initially, the physicochemical properties of the raw materials were analyzed, revealing significant differences in starch, fat, fiber, and protein content. Subsequently, the bananas were processed into baked and fried chips. Multivariate statistical techniques such as ANCOVA, MANOVA, and post-hoc tests were applied to examine the influence of initial characteristics and detect variations attributable to the cooking method. The main findings showed that the initial protein level had a significant covariate effect on the final content in the chips. The Dominico variety generally proved more suitable for making baked chips, retaining higher percentages of protein, starch, fiber, and lower fat content than Barraganete. Baked chips showed significantly lower sodium and fat values than fried ones when differentiated by processing method. The "Dominico + Baked" treatment emerged as the superior alternative, with favourable levels of protein, starch, and low sodium and fat, positioning it as the most suitable for producing a healthy snack.

Increased connectivity between coastal lagoons and the sea is expected to entail a greater proportion of marine species in the former. Chetumal Bay, estuary of the Hondo river into the Caribbean, had a limited access to the sea until the opening of the Zaragoza Canal. We sought changes in the fish community from 1999-2001 (just after an expansion of the canal) to 2015-2018. The same fishing gear was used, in the same localities, during all seasons. Total fish abundance and mean local richness decreased, although total abundance increased in the polyhaline zone. Diversity was greater in the oligohaline zone in 1999-2001, but in the mesohaline zone in 2015-2018. Three guilds were absent in 2015-2018: medium-sized herbivores, large piscivores, and medium-sized planktivores. Abundance of small benthivores decreased by decade; medium-sized piscivores and small planktivores became more abundant in 2015-2018 in the polyhaline zone. These changes may be due to the opening of the channel, but illegal fishing outside the bay may explain the decrease in juveniles of large piscivores, and erosion in the innermost part may be destroying important habitats. Our findings can be a reference for similar situations, as coastal development and climate change interact and affect tropical estuaries.

Background and Objectives: The techniques directed to the cranial field in osteopathy are the most questioned due to the lack of scientific evidence. In osteopathic practice, manual palpation is essential and, therefore, measuring reliability is fundamental. The objective of study is to assess the reliability and validity of osteopathic treatment depending on experience. Materials and Methods: A cross-sectional study of reliability and validity was conducted. For measurements, a strain gauge was placed on the sphenobasilar synchondrosis of the skull base, and three maneuvers (lateral compression, anteroposterior compression and compression maneuver of the mastoids) were repeated 25 times each by osteopaths with different time of experience (5-10 years, 1-5 years, <1 year). Measurement averages were computed for each of the three maneuvers to verify the average effect of each group in comparison to that of the Gold Standard (GS) (>10 years of experience). Data were analyzed to check for inter- and intra-observer reliability using intra-class correlation coefficients (ICC). Results: Reliability and validity in 5-10 experience of observer 1 and observer 2 in the tree maneuvers was excellent (p<0.001) against GS. Poor or enough reproducibility and concordance were observed in osteopaths with less experience. Conclusion: Experience of osteopaths determines the efficacy of cranial maneuvers in osteopathic treatment for patients’ rehabilitation.

Oxidative stress has been implicated in cellular senescence and aging, as well as in the onset and progression of many diverse genetic and acquired diseases and conditions. The search for biomarkers of oxidative stress has become relevant to many biomedical fields using many different methods and approaches. Fluorescence methodology is advantageous because of its simplicity and high sensitivity. Fluorescent probes are frequently used to investigate the role of reactive oxygen species in oxidative stress in experimental or clinical settings, often involving the use of flow cytometry and related single-cell based technologies. To assess the specific role of reactive oxygen species in oxidative stress studies by cytometric methodologies, it is essential to detect and characterize these species accurately. However, the detection and quantitation of individual intracellular ROS is still a challenge, but different and complementary strategies may focus on other endpoints of oxidative stress. In this review we present and discuss briefly the limitations and perspectives of such approaches. Based on our results, we also provide recommendations for proper design of cytometric studies of oxidative stress in order to prevent or minimize experimental errors..

‘Arrayana’ mandarin fruits have a short postharvest life and are sensitive to chilling injury (CI) during cold storage. Brassinosteroids (BR) have been used as a sustainable technology to alleviate CI in fruits and improve postharvest quality. This study evaluated the effect of applying the 24-epibrasinolide analogue (EBR), at doses of 5 mg L-1; DI-31 analogue, at 5 and 10 mg L-1; and control, on the main physical and biochemical characteristics of 'Arrayana' mandarin stored at 4°C for 40 days and, subsequently, 7 days at room temperature (shelf life). The application of EBR and DI-31 analogues reduced the appearance of CI in the exocarp of 'Arrayana' mandarin fruits by reducing electrolyte leakage, maintaining membrane integrity, and increasing antioxidant activity and phenol content at the end of cold storage and shelf life. This was especially pronounced with 5 mg L-1 of EBR. Similarly, the BR maintained the postharvest quality of mandarins by reducing weight loss, respiratory intensity and chlorophyll degradation; increasing β-carotene; and maintaining titratable acidity, and soluble solids. Our research reports for the first time CI tolerance in Arrayana mandarin using natural (EBR) and spirostanic (DI-31), analogues and illustrates the tolerance functionality of the DI-31 analog on CI in fruit postharvest.

Soot combustion experiments with 5%O2/He were conducted using model soot, and four distinct compositions of CexPr1-xO2-δ oxides were prepared, varying nominal cerium com-positions (x=0, 0.2, 0.3, and 1). The catalyst samples were comprehensively characterized using techniques such as XRD, Raman spectroscopy, HR-TEM, N2 adsorption at −196 °C, XPS, O2-TPD, H2-TPR, and work function measurements. The Pr-rich compositions, rang-ing from Ce0.3Pr0.7O2-δ to PrO2-δ, resulted in a significant increase in the total evolved O2 amounts and enhanced catalyst reducibility. However, a decrease in textural properties of the catalysts was noted, being particularly important for the pure praseodymia under the synthesis route conducted. The catalytic activity was investigated under two contact modes of mixing between soot and catalyst: loose and tight. The results revealed that the catalytic performance is associated with the surface contact in tight contact mode and with the combination of surface/subsurface/bulk oxygen mobility and the BET surface ar-ea in loose contact mode. Notably, the T10 and T50 parameters were achieved at much lower temperatures than the uncatalyzed soot combustion, even under loose contact conditions. Specifically, the 50% conversion was achieved at 511℃ and 538℃ for Ce0.3Pr0.7O2 and Ce0.2Pr0.8O2, respectively. While no direct correlation between catalytic activity and work function was observed a significant relationship emerges between work function values and the formation of oxy-gen vacancies, whatever the conditions used for these measurements. On the other hand, the ability to generate a high population of oxygen vacancies at low temperatures, rather than the direct activation of gas-phase O2, influences the catalytic performance of Pr-doped ceria catalysts, highlighting the importance of surface/subsurface oxygen vacancy generation, which was the parameter which showed better correlation with the catalytic activity, whatever the soot conversion value or the mode of contact considered.

Hormones act as master ripening regulators. In non-climacteric fruit ABA plays a key role in ripening. Recently we confirmed in Fragaria chiloensis fruit that in response to ABA treatment the fruit induces ripening associated changes such as softening and color development. In consequence with these phenotypic changes, transcriptional variations associated with cell wall disassembly and anthocyanins biosynthesis were reported. As ABA stimulates ripening of F. chiloensis fruit, the molecular network involved in ABA metabolism was analyzed. Therefore, the expression level of genes involved in ABA biosynthesis and ABA perception were quantified during development of the fruit. Four NCED/CCDs and 6 PYR/PYLs family members were identified in F. chiloensis. Bioinformatics analyses confirmed the existence of key domains related to functional properties. Through RT-qPCR analyses the level of transcripts were quantified. FcNCED1 codifies a protein that displays crucial functional domains and the level of transcripts increased as the fruit develops and ripens, in parallel with the increment in ABA. In addition, FcPYL4 codifies for a functional ABA receptor and its expression follows an incremental pattern during ripening. The study concludes that FcNCED1 is involved in ABA biosynthesis, meanwhile FcPYL4 participates in ABA perception during ripening of F. chiloensis fruit.

Most works related to the identification of mathematical nonlinear systems make one suppose that such approaches can always be directly applied to any nonlinear system. This misconception produces a great deal of discouragement when the obtained results are not the expected ones. Thus, the current work hypothesizes that the most information one has about the mathematical structure of the model, the most precise the identification result should be. Therefore, a variant of the Sparse Identification of Nonlinear Dynamics (SINDY) approach is presented to obtain the full mathematical nonlinear model of a high-order system with coupled dynamics, namely, a commercial quadcopter. Furthermore, due to its high sensitivity to inputs, a control system is devised using the identified model to stabilize the quadcopter. This illustrates the effectiveness of the proposed identification method.

The results of the bibliographic analysis show that the most explored nanomaterials in dentistry are graphene and carbon nanotubes, and their derivatives. A detailed analysis and a comparative study on their applications show that, although they are quite similar, graphene based materials seem to be more promising for most of the applications of interest in dentistry. The bibliographic study also demonstrated the potential of zeolite based materials, although the low number of studies on their applications shows that they have not been totally explored, as well as other porous nanomaterials that found important applications in medicine, such as metal organic frameworks, have not been explored. Subsequently, it is expected that the research effort will concentrate in graphene and zeolite based materials in the incoming years. Thus, present review paper presents a detailed bibliographic study, with more than 200 references, in order to describe briefly the main achievements that have been described in dentistry using nanomaterials, compare and analyze them in a critical way, with the aim of predicting the future challenges.

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

The reverse transcription quantitative polymerase chain reaction (RT-qPCR) is an established tool for the diagnosis of RNA pathogens. Its potential for automation has caused it to be used as a presence/absence diagnostic tool even when RNA quantification is not required. This technology has been pushed to the forefront of public awareness by the COVID-19 pandemic, as its global application has enabled rapid and analytically sensitive mass testing, with the first test targeting three viral genes published within days of the publication of the SARS-CoV-2 genomic sequence. One of those, targeting the RNA-dependent RNA polymerase gene, has been heavily criticised for supposed scientific flaws at the molecular and methodological level and this criticism has been extrapolated to doubts about the validity of RT-qPCR for COVID-19 testing in general. We have analysed this assay in detail and our findings reveal some limitations, but also highlight the robustness of the RT-qPCR methodology for SARS-CoV-2 detection. Whilst our data show that some errors can be tolerated, it is always prudent to confirm that primer and probe sequences complement their intended target, since when errors do occur, they may result in a reduction in the analytical sensitivity. However, in this case it is unlikely that a mismatch will result in poor specificity or significant number of false positive SARS-CoV-2 diagnoses, especially as this is routinely checked by diagnostic laboratories as part of their quality assurance.

Small bowel non-Meckelian diverticulosis is a rare condition with only few published cases despite being described over 200 years ago. In the midst of the COVID-19 pandemic, studies suggested that a lot of patients may experience gastrointestinal manifestations. Intestinal symptoms could worsen the inflammation and infection associated with small bowel diverticulitis. Here, we present two cases: one with inflammation and rupture in a COVID-19 patient and the other as an asymptomatic detection. Furthermore, we provide a mini-review of the literature to emphasize the importance of considering this entity in the differential diagnosis of an acute abdomen.

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

Although many details remain still elusive, it became increasingly evident in recent years that mechanosensing of microenvironmental biophysical cues and subsequent mechanotransduction are strongly involved in the regulation of neuronal cell development and functioning. This review gives an overview about the current understanding of brain and neuronal cell mechanobiology and how it impacts on neurogenesis, neuronal migration, differentiation, and maturation. Therein; we are focussing particularly on the events in the cell/microenvironment interface and the decisive extracellular matrix (ECM) parameters (i.e. rigidity and nanometric spatial organisation of adhesion sites) that modulate integrin adhesion complex-based mechanosensing and mechanotransductive signalling. It will also be outlined how biomaterial approaches mimicking essential ECM features help to understand these processes and how they can be used to control and guide neuronal cell behaviour by providing appropriate biophysical cues. In addition, principal biophysical methods will be highlighted that have been crucial for the study of neuronal mechanobiology.

In this paper, the active front-end (AFE) converter topology for the total harmonic distortion (THD) reduction in a wind energy system (WES) is used. A higher THD results in serious pulsations in the wind turbine (WT) output power and in several power losses at the WES. The AFE converter topology improves capability, efficiency and reliability in the energy conversion devices; by modifying a conventional back-to-back converter, from using a single voltage source converter (VSC) to use pVSC connected in parallel the AFE converter is generated. The THD reduction is done by applying a different phase shift angle at the carrier of digital sinusoidal pulse width modulation (DSPWM) switching signals of each VSC. To verify the functionality of the proposed methodology, the WES simulation in Matlab-Simulink® is analyzed, and the experimental laboratory tests using the concept of rapid control prototyping and the real-time simulator Opal-RT® Technologies is achieved. The obtained results show a type-4 WT with total output power of 6MVA, generating a THD reduction up to 5.5 times at the WES.

Since its 2013 emergence in the Americas, chikungunya virus (CHIKV) has posed a serious threat to public health. Early and accurate diagnosis of the disease, though currently lacking in clinics, is integral to enable timely care and epidemiological response. We developed a dual detection system: a CHIKV antigen E1/E2-based enzyme-linked immunosorbent assay (ELISA) and a lateral flow test using high-affinity anti-CHIKV antibodies. The ELISA was validated with 100 PCR-tested acute Chikungunya fever samples from Honduras. The assay had an overall sensitivity and specificity of 51% and 96.67%, respectively, with accuracy reaching 95.45% sensitivity and 92.03% specificity at a Ct cutoff of 22. As the Ct value increased from 22, ELISA sensitivity decreased. We then developed and validated two lateral flow tests using independent antibody pairs. The sensitivity and specificity reached 100% for both lateral flow tests using 39 samples from Colombia and Honduras at Ct cutoffs of 20 and 27, respectively. For both lateral flow tests, sensitivity decreased as the Ct increased after 27. Because CHIKV E1/E2 are exposed in the virion surfaces in serum during the acute infection phase, these sensitive and specific assays demonstrate opportunities for early detection of this emerging human pathogen.

Groundwater models serve as support tools to among others: assess water resources, evaluate management strategies, design remediation systems and optimize monitoring networks. Thus, the assimilation of information from observations into models is crucial to improve forecasts and reduce uncertainty of their results. As more information is collected routinely due to the use of automatic sensors, data loggers and real time transmission systems; groundwater modelers are becoming increasingly aware of the importance of using sophisticated tools to perform model calibration in combination with sensitivity and uncertainty analysis. Despite their usefulness, available approaches to perform this kind of analyses still present some challenges such as non-unique solution for the parameter estimation problem, high computational burden and a need of a deep understanding of the theoretical basis for the correct interpretation and use of their results, in particular the ones related to uncertainty analysis. We present a brief derivation of the main equations that serve as basis for this kind of analysis. We demonstrate how to use them to estimate parameters, assess the sensitivity and quantify the uncertainty of the model results using an example inspired by a real world setting. We analyze some of the main pitfalls that can occur when performing such kind of analyses and comment on practical approaches to overcome them. We also demonstrate that including groundwater flow estimations, although helpful in constraining the solution of the inverse problem as shown previously, may be difficult to apply in practice and, in some cases, may not provide enough information to significantly constrain the set of potential solutions.

QPEs (Quantitative Precipitation Estimates) obtained from remote sensing or ground-based radars could complement or even be an alternative to rain gauge readings. However, to be used in operational applications, a validation process has to be carried out, usually by comparing their estimates with those of a rain gauges network. In this paper, the accuracy of two QPEs are evaluated for three extreme precipitation events in the last decade in the southeast of the Iberian Peninsula. The first QPE is PERSIANN-CCS, a satellite-based QPE. The second is a meteorological radar with Doppler capabilities that works in the C band. Pixel-to-point comparisons are made between the values offered by the QPEs and those obtained by two networks of rain gauges. The results obtained indicate that both QPEs were well below the rain gauge values, especially in extreme rainfall time slots. There seems to be a weak linear association between the value of the discrepancies and the precipitation value of the QPEs. It does not seem that radar is more accurate than PERSIANN-CCS, despite its larger spatial resolution and its commonly higher effectiveness. The main conclusion is that neither PERSIANN-CCS nor radar, without empirical calibration, are acceptable QPEs for the real-time monitoring of meteorological extremes in the southeast of the Iberian Peninsula.

Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain development, and prostate cancer, among others. State-of-the-art databases with experimental data of human, chimp, and rat effects by chemicals have been used to build machine learning classifiers and regressors and evaluate these on independent sets. Different featurizations, algorithms, and protein structures lead to dif- ferent results, with deep neural networks (DNNs) on user-defined physicochemically-relevant features developed for this work outperforming graph convolutional, random forest, and large featurizations. The results show that these user-provided structure-, ligand-, and statistically-based features and specific DNNs provided the best results as determined by AUC (0.87), MCC (0.47), and other metrics and by their interpretability and chemical meaning of the descriptors/features. In addition, the same features in the DNN method performed better than in a multivariate logistic model: validation MCC = 0.468 and training MCC = 0.868 for the present work compared to evalu- ation set MCC = 0.2036 and training set MCC = 0.5364 for the multivariate logistic regression on the full, unbalanced set. Techniques of this type may improve AR and toxicity description and predic- tion, improving assessment and design of compounds. Source code and data are available at https://github.com/AlfonsoTGarcia-Sosa/ML

Versatility, sensitivity and accuracy have made the real-time polymerase chain reaction (qPCR) a crucial tool for research as well as diagnostic applications. However, for point-of-care (PoC) use traditional qPCR faces two main challenges: long run times mean results are not available for half an hour or more and the requisite high-temperature denaturation requires more robust and pow-er-demanding instrumentation. This study addresses both issues and revised primer and probe designs, modified buffers and low ∆T protocols which, together, speed up qPCR on conventional qPCR instruments and will allow the development of robust, point-of-care devices. Our approach, called "FlashPCR", also allows efficient reverse transcription as part of a one-step RT-qPCR pro-tocol, making it universally applicable for both rapid research and diagnostic applications.

The role of agricultural transport costs in core-periphery structures has habitually been ignored in New Economic Geography (NEG) models. This is due to the convention of treating the agricultural good as the numéraire, thus implying that agricultural transportation costs are assumed to be zero in these models. For more than three decades, this has been the standard setting in spatial equilibrium analysis. The paper examines the effects of agricultural transport costs on the spatial organisation of regional structures in Peru. In doing so, the Krugman’s formulation of iceberg transport costs is modified to introduce the agricultural transport costs into the dynamic of the NEG models. We use exploratory spatial flow data analysis methods and non-spatial and spatial origin-destination flow models to explore how the regional spatial structure change when real transportation data for agricultural goods is included into the iceberg transport costs formulation. We show that agricultural transport costs generate flows that are systematically associated with flows to or from nearby regions generating thus the emergence of spatial spillovers across Peruvian regions. The results of the paper support the contention that NEG models have overshadowed the role of agricultural transport costs in determining the spatial configuration of economic activities.

The practice of spatial econometrics revolves around a weighting matrix, which is often supplied by the user on previous knowledge. This is the so called $\mathbf{W}$ issue. Probably, the aprioristic approach is not the best solution although, nowadays, there few alternatives for the user. Our contribution focuses on the problem of selecting a $\mathbf{W}$ matrix from among a finite set of matrices, all of them considerer appropriate for the case. We develop a new and simple method based on the Entropy corresponding to the distribution of probability estimated for the data. Other alternatives, which are common in current applied work, are also reviewed. The paper includes a large Monte Carlo to calibrate the effectiveness of our approach compared to the others. A well-known case study is also included.

The global polyvinyldene flouride market is estimated to reach $937,278.5 thousand by 2019, therefore to develop new membranes and gain pioneering ideas, which could create innovative business opportunities, a fundamental knowledge about membrane properties fabricated from recent commercially available PVDF polymers is highly mandatory. In this study, we successfully prepared nine non-woven supported PVDF membranes using a phase inversion precipitation method starting from a 15 wt% PVDF solution in N-methyl-2-pyrrolidone. Various membrane morphologies were obtained by using (1) PVDF polymers with diverse molecular weight in a range from 300.000 Da to 700.000 Da and (2) different temperatures of the coagulation bath (20, 40, and 60 ±2°C) used for the films precipitation. Environmental Scanning Electron Microscope (ESEM) was used for surface and cross-section morphologies characterization. Atomic Force Microscope (AFM) was employed to investigate surface roughness, while Contact Angle (CA) instrument was used for membranes wettability studies. Fourier Transform Infrared Spectroscopy (FTIR) results show that the fabricated membranes are formed by a mixture of TGTG’ chains in α phase crystalline domains and all-TTTT trans planar zigzag chains characteristic to β phase. Moreover, generated results indicate that the phases content and membrane morphologies depend on the polymer molecular weight and conditions used for the membranes preparation. The diversity of fabricated membranes could be applied by the End User Industries for different applications.

Tourism is the main economic sector in the Balearic Islands (Spain) and hotel housekeepers (HHs) are a large occupational group, in which stress is becoming a major issue. This study aims at exploring in-depth factors perceived as stressors by HHs and key-informants, and their effects on work-life balance (WLB). A qualitative design with phenomenological approach was used, conducting six focus groups with 34 HHs and 10 individual interviews with key-informants. Results were analyzed adopting the job demands-resources model and a gender perspective. High demands –e.g work overload, time pressure, physical burden...-, lack of enough resources and little control –derived from role conflict, unexpected events...- were the most important factors explaining HHs’ stress. Additionally, this imbalance was perceived as leading to health problems –mainly musculoskeletal disorders-. Working schedule was mentioned as a facilitator to WLB, whereas an imbalance between job demands and resources led to work-home conflict –preventing them from enjoying leisure time-. Multiple roles at work and at home increased their stress. HHs experienced their job as invisible and unrecognised. Regarding practical implications, our recommendations for hotel organization include reducing workload and increasing resources, which would improve the job demands-resource balance, diminish negative mental and physical outcomes and improve WLB.

: This study aims at examining how B Corporations advance Sustainable Development Goals (SDGs) in their practices by analyzing the socioenvironmental problems they address and the solutions they provide to those problems. All Argentinian B corporations, certified by early 2023 (135 companies), were investigated using a mixed approach, combining social network analysis with textual data analysis. The results showed that the environmental practices are primarily linked to waste, water, energy and chemical management, as well as product innovation. In turn, the social practices address the training, education, and well-being of employees and other stakeholders, diversity, equity and inclusion management, and the creation of an inclusive and fair environment, integrating local communities. Thus, in the flow of their sustainability practices, Argentinian B Corporations contribute to SDGs 8, 12, 13, 9, 6, 7, 5, 10, 11, 4, and 17, in line with the SDGs declared by these companies. Our findings contribute to the theoretical knowledge of the B Corp movement and have practical implications by providing inputs to improve the management of B Corporations and to guide public policies encouraging these companies to advance sustainable development dimensions lacking attention.

The absence of interdental papillae leads to the appearance of black triangle. For most patients, the appearance of these triangles is an important reason for concern and affects their social relationships. Multiple reconstruction techniques have been developed with different degrees of success and predictability. The main aim of this study was to evaluate the efficiency of hyaluronic acid (HA) injected into interproximal papillae six months after injection and to perform a systematic review and meta-analysis. After a systematic review, five articles were selected: a clinical randomised controlled trial and four clinical trials. In total, eighty-five patients with a deficiency in upper papillae in the front of the maxilla and jaw were included in the study. The height variable was evaluated (mm) six months after HA injection. In total, one hundred and four interproximal papillae were studied. Three articles showed an important difference in favour of intervention. The total result regarding in the injection of AH was favourable with an approximate average filling of 0.7 mm in the height of the interdental papilla. The injection of HA for the reconstruction of deficient papillae in the region of the upper and lower maxilla was a possible option treatment strategy.

The power of the river does not always work to the benefit of living things; rather, it has the ability to destroy human society and has negative effects on the environment. River Teesta has a prodigious significance on the riverine dweller and its changing precarious behaviour has repercussions on the lives of millions. Utilizing satellite images and 41 years of temporal analysis, the mapping of channel extraction and channel shifting has been demonstrated. Delineating the exact channel boundary is a laborious operation, but MNDWI technique is really valuable in this situation to produce valuable results. Descriptive statistics are used to analyze the Teesta River's active flow line migration trend and channel migration behaviour. A particular river's oscillating character over time has both beneficial and detrimental power, destroying important resources for environmental sustainability and human society while also providing fertile mother earth as a source of wealth. As a result, another goal of the current study was to determine how vulnerable riverine residents were. A livelihood vulnerability index (LVI) based on the riverine inhabitants' exposure, sensitivity, and capacity for adaptation was created. According to the findings, the river's erratic behaviour is putting the people who live beside it in danger. Therefore, it is vitally necessary to implement a capable management strategy to stop bank failure at the Teesta-Dharala confluence in order to save the riverine residents.

The Embodied Cognitive Behavior Therapy (ECBT) approach for the treatment of emotional disorders in clinical settings is presented. The model integrates cognitive behavioral theory, neuroscience and embodied cognition. ECBT draws from evidence of bidirectional effects between modes of bottom up (sensori-motor simulations giving rise to important basis of knowledge) and top down (abstract mental representations of knowledge) processes in psychotherapy. The paper first describes the dominance of the traditional mentalistic view of cognition and its limitations. Evidence for the embodied model of cognition and emotion is reviewed whilst highlighting its advantages as a complimentary process model to deepen and broaden talking therapies. An overview is given of the switch (e.g., the technique of balancing) between top-down and bottom-up orientation in the ECBT model as well as a clear description of the method for emotional regulation, acceptance of unwanted emotions and emotional mastery. ECBT builds on and extends the unconscious processes of the ‘Interpersonal Synchrony’ (IS) model identified by Koole and Tschacher [1], to enhance the therapeutic alliance for emotional co-regulation. A new idea is proposed that both embraces and extends the IS model: embodiment techniques of imitation and movement synchronization in the Emotional Field of our method be used in a conscious way to speed up the calming effects of co-regulation and the client’s self-regulatory capacity. The paper ends with an outline of the criteria needed to become an embodied therapist. A case study is given highlighting these aspects.

Endophytic insect pathogenic fungi have a multifunctional lifestyle; in addition to its well-known function as biocontrol agents, it may also help plants respond to other biotic and abiotic stresses, such as iron (Fe) deficiency. This study explores M. brunneum EAMa 01/58-Su strain attributes for Fe acquisition. Firstly, direct attributes include siderophore exudation (in vitro assay) and Fe content in shoots and in the substrate (in vivo assay) were evaluated for three strains of Beauveria bassiana and Metarhizium bruneum. The M. brunneum EAMa 01/58-Su strain showed a great ability to exudate iron siderophores (58.4% surface siderophores exudation) and provided higher Fe content in both dry matter and substrate compared to the control and was therefore selected for further research to unravel the possible induction of Fe deficiency responses, Ferric Reductase Activity (FRA), and relative expression of Fe acquisition genes by qRT-PCR in melon and cucumber plants.. In addi-tion, root priming by M. brunneum EAMa 01/58-Su strain elicited Fe deficiency responses at transcriptional level. Our results show an early up-regulation (24, 48 or 72 h post inoculation) of the Fe acquisition genes FRO1, FRO2, IRT1, HA1, and FIT as well as the FRA. These results highlight the mechanisms involved in the Fe acquisition as mediated by IPF M. brunneum EAMa 01/58-Su strain.

The twelve cranial nerves play a crucial role in nervous system, orchestrating a myriad of functions vital for our everyday life. These nerves are each specialized for particular tasks. Cranial Nerve I, known as the olfactory nerve, is responsible for our sense of smell, allowing us to perceive and distinguish various scents. Cranial Nerve II, or the optic nerve, is dedicated to vision, transmitting visual information from the eyes to the brain. Eye movements are governed by Cranial Nerves III, IV, and VI, ensuring our ability to track objects and focus. Cranial Nerve V controls facial sensation and jaw movement, while Cranial Nerve VII, the facial nerve, facilitates facial expressions and taste perception. Cranial Nerve VIII, or the vestibulocochlear nerve, plays a critical role in hearing and balance. Cranial Nerve IX, the glossopharyngeal nerve, affects throat sensation and taste perception. Cranial Nerve X, the vagus nerve, is a far-reaching nerve, influencing numerous internal organs such as the heart, lungs, and digestive system. Cranial Nerve XI, the accessory nerve, is responsible for neck muscle control, contributing to head movement. Finally, Cranial Nerve XII, the hypoglossal nerve, manages tongue movement, essential for speaking, swallowing, and breathing. Understanding these cranial nerves is fundamental in comprehending the intricate workings of our nervous system and the functions that sustain our daily lives.

Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA (Robotics Surgical Maneuvers) dataset provides 206 trials of common surgical training tasks performed with the da Vinci Research Kit (dVRK). In this work, we extend ROSMA dataset with two annotated subsets: ROSMAT24, which contains bounding box annotations for instrument detection, and ROSMAG40, which contains high and low level gesture annotations. We propose an annotation method that provides independent labels for the right-handed tool and the left-handed tool. For instrument identification, we validate our proposal with a YOLOv4 model in two experimental scenarios. We demonstrate the generalization capabilities of the network to detect instruments in unseen scenarios. For gesture segmentation, we propose two label categories: high-level annotations that describe gestures at a maneuvers level, and low-level annotations that describe gestures at a fine-grain level. To validate this proposal, we have designed a recurrent neural network based on a bidirectional long-short term memory layer. We present results for four cross-validation experimental setups, reaching up to a 77.35% mAP.

Predictive numerical models in the study of ground-borne vibrations generated by railway sys-tems have traditionally relied on the segmented approach of subsystems. In this approach, loads are individually applied, and the cumulative effect of rolling stock is obtained through superposi-tion. While this method serves to mitigate computational costs, it may not fully capture the com-plex interactions involved in ground-borne vibrations. Recent advancements in computational and software tools have enabled the development of more sophisticated vibrational pollution models. These advanced models encompass the entire dynamic system, from the rolling stock to the terrain, allowing for continuous simulations with a defined time step. Furthermore, the incorporation of computational contact tools between various ele-ments not only ensures temporal accuracy but also extends the analysis to the frequency domain. This paper explores the evolution of predictive numerical models in the context of ground-borne vibrations generated by trains on ballasted tracks. It highlights the shift from segmented models to continuous simulations, demonstrating the progressive advancement towards more comprehen-sive and accurate representations of railway-induced and generated vibrations in the track sur-roundings as an additional way of evaluate sustainability of infrastructures. In particular, this development of a numerical model from its inception aimed to expand upon ex-isting emission - prediction models by enriching the data with frequency-domain information. This approach has been driven by the aspiration to bridge the gap between numerical predictions and measured signals, striving for a higher level of accuracy in our obtained results. This model can predict the impact of a high-speed rail (HSR) vehicle passing on its own track. It possesses sufficient information in both the time and frequency domains to precisely characterize vibrations. This initiative marks a pivotal advancement, enabling us to more effectively capture the intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain, there's a heightened ca-pability to accurately characterize vibrations.

The ceramic sherds from approximately 20 samples of lead-glazed tableware, recovered from diverse archaeological sites, including three repurposed storage pits transformed into dumpsters within the medieval city of Santarém (13th-14th century), underwent a meticulous examination. This investigation utilized techniques such as micro-Raman, ground state diffuse reflectance absorption, and X-ray fluorescence spectroscopies, in addition to X-ray diffraction and stereomicroscopy. A parallel study was conducted on contemporaneous European ceramics (glazed sherds) sourced from archaeological sites dating back to the 13th-15th centuries in Saintonge (France), Ardenne, Zomergem, and Bruges (Belgium), as well as Surrey-Hampshire, Kingston, and Cheam (England). The colour of the ceramic bodies is predominantly white or whitish, with a few exhibiting a vivid red hue. Ceramic sherds with a light paste composition were likely crafted using kaolin clays as raw materials. Analyses of fabric, mineralogical, and elemental composition of the sherds suggest that the majority of Santarém's glazed ceramics were locally or regionally produced, potentially derived from a Pliocene kaolin-rich sand formation. However, this conclusion is not supported by the absence of discovered lead glaze kilns or workshops in Santarém for the late Middle Ages. A distinctive feature from the European workshop ceramics lies in the quartz temper content and fabric.

The human-readable simplicity with which the CSV format was devised, together with the absence of a standard that strictly defines this format, has allowed the proliferation of several variants in the dialects with which these files are written. The latter has meant that the exchange of information between data management systems, or between countries and regions, requires human intervention during the data mining and cleansing process. This has led to the development of various computational tools that aim to accurately determine the dialects of CSV files, in order to avoid data loss at data loading stage in a given system. However, the dialect detection is a complex problem and current systems have limitations or make assumptions that need to be improved and/or extended. This paper proposes a method for determining CSV file dialects through table uniformity, a statistical approach based on table consistency and records dispersion measurement along with the detection of data type over each field. The new method has a 100\% accuracy on a dataset with 148 CSV files composed of samples coming from a data load testing framework and some others added as verification of the parsing routines. In tests on truly messy data, the proposed solution outperforms the state-of-the-art tool by achieving an improvement of about 10\% in the accuracy with which dialects are detected. Furthermore, the proposed method is accurate enough to determine dialects by reading only ten records, requiring more data to disambiguate those cases where the first records do not contain the necessary information to conclude with a dialect determination.

Videogames have become educational, communicative and social tools among the youngest, favouring the acquisition of skills, abilities and values, encompassing an endless number of themes, and help to experience and to face, in the first person, a great diversity of environmental situations and ecology problems. Thus, the present article aims: a) the evaluation of a sample of 20 educational videogames about water, making use of some empirical criteria of quality; and b) the design, validation and application of an integrate quality indicator of educational videogames on water, based on the aspects of narrative, gameplay and didactics to that sample, which allows us to obtain a ranking. The findings reflect a ranking of games allows to suggest that the nature of the game (simulation, adventures, platforms or questions) does not determine the quality of the game, although generally simulations and adventure games are placed in a range of medium or high quality, as well as those games that pursue objectives related to the design and management of a territory in a sustainable way. The paper provides teachers with quality criteria based on narrative and gameplay that complement and enriches the pedagogical dimension.

Urban wind energy has emerged as an attractive source of distributed generation in cities to achieve sustainable development goals. The advance in technologies for the use of urban wind energy has turned this source into an attractive alternative for the decarbonization of cities and the energy transition. The objectives of this work are (1) to identify the potential of wind energy through numerical weather prediction (NWP) data tools and (2) to identify the roles and responsibilities of the stakeholders involved in the decision-making process. A methodology was developed in two phases and applied to a case study in the Dominican Republic. The first phase consisted of estimating the wind energy potential for the 32 provinces at a height of 10 m using open-access geographic reference systems tools provided by NASA. In the second phase, 28 stakeholders were identified through snowball sampling. The Responsible, Accountable, Consult, and Informed (RACI) matrix tool was applied to identify the roles of the 28 institutions addressed at the country level as relevant in the decision-making process for the energy sector. The annual average wind speed and energy potential for each province were determined. It was found 24 provinces have poor potential, below &lt;4.5 m/s. In the northwest and east is where there is the greatest potential, between 4.83 - 6.63 m/s. The population density was established and was observed that the provinces with greater potential are less densely populated. Through 59 interviews 28 institutions were identified and evaluated due to their relevance in decision-making for the implementation of energy projects. The MEM has strongly categorized as “A”, electricity distribution companies as “R”, energy associations and universities as “C”, and educational and justice institutions as “I”.

In this systematic review of the literature on using Machine Learning (ML) for credit risk prediction, we raise the need for financial institutions to use AI and ML to assess credit risk, analyzing large volumes of information. We posed research questions about algorithms, metrics, results, data sets, variables, and related limitations in predicting credit risk. We searched renowned databases to answer them and identified 52 relevant studies with the credit industry microfinance. Challenges and approaches in credit risk prediction using ML models we identified, difficulties with the implemented models such as the black box model, the need for explanatory artificial intelligence, the importance of selecting relevant features, addressing multicollinearity, and the problem of the imbalance in the input data. By answering the questions, we identified that the Boosted Category is the most researched family of ML models; the most commonly used metrics for evaluation are Area Under Curve (AUC), Accuracy (ACC), Recall, precision measure F1 (F1), and Precision; Research mainly uses public data sets to compare models, and private ones to generate new knowledge when applied to the real world. The most significant limitation identified is the representativeness of reality, and the variables primarily used in the microcredit industry are related data to the demographic, the operation, and payment behavior. This study aims to guide the developers of credit risk management tools and software towards the existing offer of ML methods, metrics, and techniques used to forecast it, thereby minimizing possible losses due to default and guiding risk appetite.

Our bodies produce a host of electrophilic species that can label specific endogenous proteins in cells. The signaling roles of these molecules are underactive debate. However, in our opinion it is becoming increasingly likely that electrophiles can rewire cellular signaling processes at endogenous levels. Attention is turning more to understanding how nuanced electrophile signaling in cells is. In this perspective, we describe recent work from our laboratory that has started to inform on different levels of context-specific regulation of proteins by electrophiles. We discuss the relevance of these data to the field, and to the broader application of electrophile signaling to precision medicine development, beyond the traditional views of their pleiotropic cytotoxic roles.

Antibiotics are released into the environment either directly in an unchanged form or in a partially metabolized form. The discharge is usually through untreated waste or industrial treatment effluents. The potential concern is the uptake of these antibiotics by crops irrigated by treated wastewater. This study collected wastewater from eight points at the Pagla, Kadamtali, Dhaka treatment plant. Here we consider three crucial antibiotics, Doxycycline, Ciprofloxacin, and Tetracycline, used mainly during the last two years of the pandemic. A PDA detector was used in high-performance liquid chromatography (HPLC) analysis to determine the raw and processed effluent antibiotics. The most frequently seen antibiotics in natural wastewater were Doxycycline and Ciprofloxacin, with the highest concentration of 0.23µgL-1and 0.20 µgL-1(raw water), respectively. Tetracycline was not detected in natural water. Contrarily, Doxycycline was discovered in the Pagla plant's completed water and had the highest concentration (0.12 gL-1), whereas Ciprofloxacin and Tetracycline were not found in the dead water. The findings of this study showed that Doxycycline was still present in both the raw and processed effluent. Both natural and finished wastewater was subjected to a microbial-resistant test in the presence of all three antibiotics. The results revealed that the samples detected both heterotrophic bacteria and total coliform. The viable aerobic heterotrophic bacteria ranged between 5.421 and 4.754 log cfu/ml. Total bacteria load gradually decreased in the finished wastewater.

Non-conventional resonances, both acoustic and photonic, are found in metallic particles with a toroidal nanopropeller geometry that is generated by sweeping a three-lobed 2D-shape along a spiral with twisting angle, α. For both optical and acoustic cases, the spectral location of resonances experiences a red-shift as a function of α. We demonstrate that the optical case can be understood as a natural evolution of resonances as the spiral length of the toroidal nanopropeller increases with α, implying a huge helicity dependent absorption cross section. In the case of acoustic response, two red-shifting breathing modes are identified. Additionally, even a small α allows the appearance of new low-frequency resonances, whose spectral dispersion depends on a competition between length of the generative spiral and the pitch of the toroidal nanopropeller.

Pure monocular 3D reconstruction is an ill-posed problem that has attracted the research community's interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction problem and estimate the camera’s ego-motion, so many methods have been proposed. However, most of these methods were not evaluated in large datasets, under various motion patterns, had not been tested under the same metrics, and most of them had not been evaluated following a taxonomy, making their comparison and selection difficult. In this research, we performed a comparison of ten publicly available SLAM and VO methods following a taxonomy, including one method for each category of the primary taxonomy, three machine learning-based methods, and two updates of the best methods, to identify the advantages and limitations of each category of the taxonomy and test if the addition of machine learning or the updates made on those methods improved them significantly. Thus, we evaluated each algorithm under the TUM-Mono benchmark and performed an inferential statistical analysis to identify significative differences through its metrics. Results determined that sparse-direct methods significantly outperformed the rest of the taxonomy, and fusing them with machine learning techniques significantly improves the performance of geometric-based methods from different perspectives.

A Q-switched Nd:YAG laser was focused on Pb-Ti alloy samples in several Laser Induced Breakdown experiments in order to measure the Stark parameters of several spectral lines (58) of single ionized Titanium including the 3504.89 Å, and the 3510.83 Ålines (where we aported new experimental and theoretical values).Diagnostics of the laser induced plasmas (electron density and electron temperature) was performed using Balmer’s H alpha line (6562.7 Å).Temperatures were obtained by the Boltzmann Plot technique with spectral lines of Pb I (after correction for its evident self-absorption).Subsequently, calculations by the Griem approach of the Stark broadening parameters for several spectral lines were performed using the Gaunt factors proposed by Van Regemorter and those proposed by Douglas H. Sampson. In the latter cases the values obtained were very close to the experimental values. It allows us to assume that the calculations made for the spectral lines of Ti II, without experimental information, are more accurate using the Gaunt factors proposed by Sampson.

Phosphite (Phi) has gained attention in agriculture due to its biostimulant effect on crops. This molecule has been found to benefit plant performance by providing protection against pathogens, improving yield and fruit quality, and improving nutrient and water use efficiency. It is still unclear how Phi enhances plant growth and protects against multiple stresses. It has been hypothesized that Phi acts by directly affecting the pathogens and interacting with the plant cellular components and molecular machinery to elicit defense responses. This study delves into elucidating the mechanisms underlying Phi’s beneficial effects on plants, revealing a complex interplay with fundamental signaling pathways. A RNA-seq study of Arabidopsis seedlings under optimal and limiting phosphate conditions helped us unveil Phi’s role in promoting plant growth by activating the expression of genes involved in the biosynthesis and signaling pathways associated with abscisic acid (ABA), salicylic acid (SA), and jasmonic acid (JA). Expression of ABA-related genes, known for their involvement in stress response and development regulation, is triggered by Phi treatment, contributing to enhanced resilience and growth. Simultaneously, the activation of the SA pathway, associated with defense responses, suggests Phi’s potential in bolstering plant immunity. Moreover, Phi influences JA biosynthesis and signaling, which are crucial for defense against herbivores and pathogens, thereby strengthening plants’ defenses. Our findings reveal a multifaceted mechanism through which Phi benefits Arabidopsis development. Understanding its intricate interplay with key signaling pathways opens avenues for leveraging Phi as a strategic tool to enhance plant resilience, immunity, and growth in agricultural and ecological contexts.

Background: Functional beverages are ordinary foods with components or ingredients able to provide specific health effects other than purely nutritional effect. Aim: This study aims to formulate a new functional beverage obtained from the recovery of YoAlp® whey, a bovine fermented milk obtained using autochthonous starter cultures, added with Renetta Canada/Golden Delicious-Raspberry (YWL), Renetta Canada-Aronia (YWA) and Ravèntse (YWR) fruit juices to improve the functionality of the beverage. Methods: Microbiological analysis and chemical characterization, by a proteomic approach and spectrophotometric microassay, have been conducted on beverages to investigate the expected shelf-life and potential health promoting effects. Results: The microbiological assessment confirmed the safety of the beverages and the probiotic bacteria vitality over a shelf life of seven days. Biochemical analysis performed highlight the presence of different bioactive peptides (ACE inhibitory and antioxidant), and the betacasomorphin 9 (BCM-9), marker of A2 variant of β-casein typically present in Aosta Valley cattle breeds. Moreover, high amounts of total polyphenols, which concur to the antioxidant activity values observed, have been found. Furthermore, ACE inhibitory activity is well correlated to the bioactive peptides detected. Finally, a consumer test confirmed the YoAlp® whey-based beverages appreciation. Conclusions: The production of these beverages could represent a huge opportunity for Aosta Valley’s farms to increase their income and competitiveness, creating a circular economy by recovering a by-product like whey and following sustainability and healthy trends, which are driving the food sector.

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

The optimized design of catalyst layer (CL) plays a vital role to improve the performance of polymer electrolyte membrane fuel cells (PEMFCs). The need to improve transport and catalyst activity is especially important at low Pt loading, where local oxygen and ionic transport resistances decrease the performance due to an inevitable reduction of active catalyst sites. In this work, local oxygen and ionic transport are analyzed using direct numerical simulation on virtually reconstructed microstructures. Four morphologies are examined: (i) heterogeneous, (ii) uniform, (iii) uniform vertically-aligned, and (iv) meso-porous ionomer distributions. The results show that the local oxygen transport resistance can be significantly reduced, while maintaining good ionic conductivity, through the design of high porosity CLs (ε≃0.6−0.7) with low agglomerated ionomer morphologies. Ionomer coalescence into thick films can be effectively mitigated by increasing the uniformity of thin films and reducing the tortuosity of ionomer distribution (e.g., good ionomer interconnection in supports with a vertical arrangement). The local oxygen resistance can be further decreased by the use of blended ionomers with enhanced oxygen permeability and meso-porous ionomers with oxygen transport routes in both water and ionomer. In summary, achieving high performance at low Pt loading in next-generation CLs must be accomplished through a combination of high porosity, uniform and low tortuosity ionomer distribution, and oxygen transport through activated water.