According to the growing concern of various focus groups, in regard to the mitigation of the negative impacts generated because of the tourism, has born the interest of proposing sustainable tourism projects derivatives of the feeling within the communities (1) Background: the aim is to propose a differentiated diagnosis of the Subsystems (biophysical and anthropic) and their relationship with traditional-rational knowledge; (2) Methods: from the Theory of Complex Systems was propose the Harmonic Tourism Methodology, that try to correlation the subsystem and knowledge in the community of San Juan Tlahuica Atzingo, State of Mexico (4) Conclusions: Among the most outstanding results that are on the one hand, we must work through tourism projects to the rescue and preservation of natural and cultural resources, reassessing them through the strengthening of social cohesion. On the other hand, the application of this case allowed us to visualize that it is necessary to consolidate the elements and steps of the methodology in order to apply it to different communities that are beginning their journey in the field of the tourism and that can improve and potentiate their resources, seeking harmony between them.

Background: Deficiency of alpha-1 antitrypsin (AAT1) is a rare disorder that represents a significant health threat and early diagnostic a priority issue. We investigate the usefulness of the serum protein electrophoresis (SPE) as an opportunistic screening tool for AAT1 deficiency. Methods: For 6 months, all SPE carried out for any reasons were evaluated in our center. In those with less than 3% of Alpha-1 globulins, AAT1 concentrations were studied. The SERPINA1 gene was subsequently sequenced in those subjects displaying concentrations below 100 mg/dL. Results: Out of the total, 14 patients (0.3%) were identified with low AAT1 concentrations, 11 of them agreeing to enter the study. Of those, mutations in the SERPINA1 gene were discovered in 10 subjects (91%). Heterozygous mutations were detected in 7 patients; 3 had the c.1096G>A mutation (p.Glu366Lys; Pi*Z), 2 the c.863A>T mutation (p.Glu288Val; Pi*S), one the c.221_223delTCT mutation (p.Phe76del; Pi*Malton) having the last one the c.1066G>A (p.Ala356Thr) mutation not previously described. Finally one patient had the c.863A>T mutation in homozygosis whereas two double heterozygous patients c.863A> T/ c.1096G>A were detected. Conclusions: an altered result in the concentration of AAT1 anticipates a mutation in the SERPINA1 gene in a manner close to 91%. The relationship between a decrease in the Alpha-1 globulin band of the SPE and an alteration in the AAT1 concentration is direct in basal states of health. The SPE is presented as a highly sensitive test for opportunistic screening of AAT1 deficiency.

Primary hyperoxalurias (PHs) are a group of inherited alterations of the hepatic glyoxylate metabolism. PHs classification based on gene mutations parallel a variety of enzymatic defects, and all involve the harmful accumulation of calcium oxalate crystals that produce systemic damage. These geographically widespread rare diseases have a deep impact in the life quality of the patients. Until recently, treatments were limited to palliative measures and kidney/liver transplants in the most severe forms. Efforts made to develop pharmacological treatments succeeded with the biotechnological agent lumasiran, a siRNA product against glycolate oxidase, which has become the first effective therapy to treat PH1. However, small molecule drugs have classically been preferred since they benefit from experience and have better pharmacological properties. The development of small molecule inhibitors designed against key enzymes of glyoxylate metabolism is on the focus of research. Enzyme inhibitors are successful and widely used in several diseases and their pharmacokinetic advantages are well known. In PHs, effective enzymatic targets have been determined and characterized for drug design and interesting inhibitory activities have been achieved both in vitro and in vivo. This review describes the most recent advances towards the development of small molecule enzyme inhibitors in the treatment of PHs, introducing the multi-target approach as a more effective and safe therapeutic option.

Data from NASA’s Soil Moisture Active Passive Mission (SMAP) and from the California Cooperative Oceanic Fisheries Investigations (CalCOFI) were used to examine the freshening that occurred during 2015-2016 in the Southern California Current System. Overall the freshening was found to be related to the 2014-2016 Northeast Pacific Warm Anomaly. The primary goal was to determine the feasibility of using SMAP data to observe the surface salinity signal associated with the warming. As a first step direct comparisons were done with salinity from the CalCOFI data at one-meter depth. During 2015 SMAP was saltier than CalCOFI by 0.5 PSU, but biases were reduced to < 0.1 PSU during 2016. South of 33°N, and within 100 km of the coast, SMAP was fresher in 2015 by almost 0.2 PSU. CalCOFI showed freshening of 0.1 PSU. North of 33°N SMAP and CalCOFI saw significant freshening in 2016, SMAP by 0.4 PSU and CalCOFI by 0.2 PSU. Differences between SMAP and CalCOFI are consistent with the increased stratification in 2015 and changes in the mixed layer depth.

As synthetic/artificial life forms become more abundant and sophisticated, an increasing number of bizarre creatures - xenobots, robots, soft A-life entities, genetically engineered organisms, etc. - are invading our society. Therefore, we need to bring order to all this, to establish what is living and what is not. Here, I intend to classify all these non-natural entities and clarify their status with reference to their consideration or not as living beings, leaving the door open to an uncertain future in which perhaps we can see how "the artificial" and "the natural" merge to originate something new. To order all this "new biodiversity" and to also give entry to viruses (which are excluded of the three-domains tree of life), I propose the creation of a new domain, Lithbea (from the name: life-in-the-border entities), in which all these new human-made entities as well as the viruses will be included. Within this domain there would be two kingdoms, Virus and Humade (contraction of human-made), based on their origin, natural or human-made. A brief description of each component of Lithbea is included and the implications for society and biology of this “new biodiversity” is briefly discussed.

The ecosystem is an essential biological concept linking the living and the inanimate and represents the main structural and functional unit of nature. The biodiversity that exists on our planet can be organized into closely interconnected living worlds: acellular (viruses and capsidless genetic elements), prokaryotic (bacteria and archaea), and eukaryotic (all nucleated organisms). I want to highlight the presence of viruses as components of biodiversity because they are often overlooked in many studies despite their essential ecological and evolutionary role. Furthermore, I propose seven distinctive hallmarks that are inherent to any ecosystem: biodiversity, physical environment, hierarchy, interactivity, openness, “homecostasis”, and evolutionary. From the interaction and coupling of these living worlds with the environment (the environmental world), I define the ecosystem as a specific and dynamic ensemble of living and non-living worlds that functions as an open, hierarchical, and evolving system. This complex web of interactions that we call ecosystem can be graphically represented as a triangle reflecting the dynamic equilibrium between all the worlds. Finally, I propose a new way of graphically relating the ecosystem to biodiversity by taking the ecosystem as the nucleus from which all living worlds emerge.

What is life, what is the difference between something that is alive and something that is not, are viruses living beings, or what would life be like elsewhere in the universe, are questions that still do not have clear-cut answers fully accepted by the scientific community. Based on the fundamental attributes of all living things, I define life as a process that takes place in very ordered organic structures and is characterized by being automatic, interactive and evolutionary. I also define a living being as an organic, highly ordered, automatic, interacting and evolutionary system, and a robot as an ordered automatic and interacting system. Based on this definition and what we know about the biology of viruses, I maintain that they should be considered as living entities. Finally, I explain why if there were life elsewhere in the universe, it would be very similar to what we know on our planet.

We know that living matter must behave in accordance with the universal laws of physics and chemistry. However, these laws are insufficient to explain the specific characteristics of the vital phenomenon and, therefore, we need new principles, intrinsic to biology, which are the basis for developing a theoretical framework for understanding life. Here I propose what I call the seven commandments of life (the Vital Order, the Principle of Inexorability, the Central Dogma, the Tyranny of Time, the Evolutionary Imperative, the Conservative Rule, the Cooperating Thrust) as a set of principles that help us explain the vital phenomenon from an evolutionary perspective. In a metaphorical way, we can consider life like an endless race in which living beings are the runners, who are changing as the race goes on (the evolutionary process), and the commandments the rules.

Background The high incidence of diverticulitis and hemorrhoidal proctitis episodes in the population imposes an important healthcare and economic burden. Aim To determine the association between intake of certain plant foods and diverticulitis and hemorrhoidal proctitis episodes. Methods Case-control study with quantitative food frequency questionnaire focusing on selected plant foods and derived products. These were grouped by main chemical components into: ethanol, caffeine/theine/theobromine, capsaicin, alliin, acids, eugenol, and miscellaneous foods like curcumin. We quantified intake according to 24-h recall, either on a 1-4 scale (no intake, low, moderate, high intake) or as the number of units consumed (e.g. cups of tea/coffee, n of oranges or lemons); this value was multiplied by the number of reported intake days per week (1-7). Overall intake was expressed as a continuous variable obtained by successively multiplying the score for each food category, and the result was transformed into a common logarithm (range 0.3 to 27.7). Cases and controls were compared using the chi-squared test, student’s t test, odds ratio (OR) and 95% confidence interval (CI), and predictive analysis (multiple logistic regression). Results The sample included 410 cases and 401 controls, who were similar in mean age and gender distribution. The mean score for overall intake of included plant foods was 6.3 points (standard deviation [SD] 4.5), and this was significantly higher in cases (8.5 points, SD 5.3) than in controls (4.1 points, SD 1.2; p < 0.001). Overall intake was similar in cases presenting diverticulitis or hemorrhoidal proctitis. Cases had 13 times the odds of being in the upper quartile for overall intake (> 7 points) compared to controls (OR 13.2, 95% CI 8.3 to 20.8, p < 0.001). Predictive logistic regression models showed that the chemical food group most closely associated with diverticulitis and hemorrhoidal proctitis was capsaicin, followed by ethanol, eugenol, caffeine/theine/theobromine, and acids. The OR for age was near the null value. Neither alliin nor miscellaneous food groups showed any association. Conclusions High, frequent consumption of some plant foods and derived products increases the risk of presenting symptoms of diverticulitis and hemorrhoidal proctitis.

This paper presents the experimental implementations of the mathematical models and algorithms developed in Part I. Two experiments are carried out. The first experiment aims at the determinations of the correction coefficients of the mathematical model. The dot grid target is measured and the measurement data are processed by our developed and validated algorithms introduced in Part I. The values of the coefficients are indicated and analysed. Uncertainties are evaluated with implementation of the Monte Carlo method. The second experiment measures a different area of the dot grid target. The measurement results are corrected according to the coefficients determined in the first experiment. The mean residual between the measured points and their corresponding certified values reduced 29.6% after the correction. The sum of squared errors reduced 47.7%. The methods and the algorithms for raw data processing, such as data partition, fittings of dots’ centres, K-means clustering, etc., are the same for both two experiments. The experimental results demonstrate that our method for the correction of the errors produced by the movement of lateral stage of confocal microscope is meaningful and practicable.

Background: This study investigates microvascular changes in the dermis and muscle following a balneotherapy regimen prescribed by therapeutic protocols. Methods: Thirty-five inpatients participated in a two-week balneal course involving the application of mud and hypersaline water. Mud was applied outdoors in the summer as cold mud ointment and indoors year-round as mud packs or mud baths alternated with hypersaline water baths. Biopsies of the skin and muscle were obtained twenty-four hours post-discharge and prepared histologically. Results: Analysis focused on the epidermis, dermis, and muscle. Microvascular changes observed included increased caliber and number of open capillaries, as well as the presence of angiogenesis vessels. Statistical analysis showed significant differences in angiogenesis vessels between cold mud ointment and mud pack treatments compared to control and mud bath groups. A higher number of angiogenesis vessels were observed in the dermis in the mud pack group and in the muscle with mud cold ointment. Repeated thermal stimulation with mud and hypersaline water over two weeks produced histologically evident tissue modifications, persisting in the dermis and muscle at least twenty-four hours post-treatment completion.

It was recently shown that urban networks might exhibit two different critical points, one for the percolation of congested links through the network, and another one for the flow of vehicles through the network. It was observed that the percolation critical point happens after the flow critical point, where network throughput is maximized. This result is important because if a causal relationship exists between these two processes, it can be leveraged for improving control methods to avoid network collapse. This paper presents the results of numerical experiments to understand the possible causal relationship between the percolation and flow processes by focusing on the relative timing between the two critical points. The goal is to understand the impacts of important factors such as: (i) urban network type: long- and short-block networks, (ii) signal timing control type: fixed, random, responsive, and (iii) route choice: turning proportions at intersections. We find that the threshold density $k^*_c$ to determine if a link is congested has the main impact on the timing of the percolation transition, where lower values trigger earlier transitions. This implies that $k^*_c$ can be set such that the percolation transition happens before the flow critical point, opening the door for improved congestion management strategies. If $k^*_c$ is set to the average network critical density, maximum network throughput happen simultaneously with the percolation transition. Surprisingly, it appears that these results, and more generally, the relationship between the percolation and flow processes is independent of (i) and (ii) above.

Huntington’s Disease (HD) is a devastating neurodegenerative disorder caused by a CAG trinucleotide repeat expansion in the HTT gene, for which no disease modifying therapies are currently available. Much of the recent research has focused on developing therapies to directly lower HTT expression, and while promising, these therapies have presented several challenges regarding administration and efficacy. Another promising therapeutic approach is the modulation of HTT post-translational modifications (PTMs) that are dysregulated in disease and have shown to play a key role in HTT toxicity. Among all PTMs, modulation of HTT phosphorylation has been proposed as an attractive therapeutic option due to the possibility of orally administering specific kinase effectors. One of the kinases described to participate in HTT phosphorylation is Protein Kinase CK2. CK2 has recently emerged as a target for the treatment of several neurological and psychiatric disorders, although its role in HD remains controversial. While pharmacological studies in vitro inhibiting CK2 resulted in reduced HTT phosphorylation and increased toxicity, genetic approaches in mouse models of HD have provided beneficial effects. In this review we discuss potential therapeutic approaches related to the manipulation of HTT-PTMs with special emphasis on the role of CK2 as a therapeutic target in HD.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

The human immunodeficiency virus (HIV) continues to pose a significant global health challenge, with millions of people affected and new cases emerging each year. While various treatment and prevention methods exist, including antiretroviral therapy and non-vaccine approaches, developing an effective vaccine remains the most crucial and cost-effective solution to combat the HIV epidemic. Despite significant advancements in HIV research, the HIV vaccine field has faced numerous challenges, and only one clinical trial has demonstrated a modest level of efficacy. This review delves into the history of HIV vaccines and the current efforts in HIV prevention, emphasizing pre-clinical vaccine development using the non-human primate model (NHP) of HIV infection. NHP models offer valuable insights into potential preventive strategies for combating HIV, and they play a vital role in informing and guiding the development of novel vaccine candidates before they can proceed to human clinical trials.

Road pavement monitoring represents the baseline to the pavement maintenance process. To quickly fix a damaged road, relevant authorities need a high-efficiency methodology that allows them to obtain data describing the current conditions of a network of roads. In urban areas, large-scale monitoring campaigns may be more expensive and not fast enough to describe how pavement degradation has evolved over time. Furthermore, at low speeds, many technologies are inadequate for monitoring the streets. In such a context, employing black box equipped vehicles to perform a routine inspection could be an excellent starting point. However, the vibration-based methodologies used to detect road anomalies are strongly affected by the speed of these vehicles. In this study, a statistical method was to analyze the effects of speed on road pavement conditions at different severity levels through the data recorded by taxi vehicles. Likewise introduced was a process that overcomes the speed effect when considering road surface conditions. The methodology proposed has succeeded in predicting the right damage severity level based on only two recorded parameters: speed and pavement deterioration index.

In hydraulic systems, energy dissipation can be significant. The pressure drops that can occur in the hydraulic circuit, influenced by the adopted drive architecture, result in an absorbed power often significantly greater than that required by the mechanical system. In this paper, a comparative study of energy efficiency among five drive common architectures in industrial hydraulic axes is carried out. The analysis is applied to a hydraulic blanking press with variable speed and force, a fairly frequent industrial system, e.g. in the production of semi-finished brass products. Standard, regenerative, high-low, variable displacement pump and variable speed drive for a fixed displacement pump configurations have been analysed and compared. An adequate and optimized sizing of the various components of the system has been carried out in each case and subsequently the energy consumption has been estimated for a load cycle common to all the considered cases. The results show that the choice of power generation architecture of the hydraulic system has a very significant impact on energy efficiency and consequently operating costs and carbon footprint. The performed quantification of the potential energy efficiency of the considered drive architectures can be very useful in guiding energy-conscious choices.

Water is a fundamental resource for ecosystems, humans, and the development of all economic sectors; it is necessary to identify and evaluate its environmental pressures or impacts. The water footprint (WF) is an appropriate indicator for the consumption of water used to produce a product. The present study uses this tool to evaluate the green and blue water requirements and the sustainability of irrigation water use for agroindustrial avocado production in Ziracuaretiro, Michoacán (2012-2021). Our analysis was based on aggregating weather and soil data at the municipal level and official government databases of avocado cultivated surface, fruit production, and water rights concessions. The analysis considers the homogeneity of information throughout the study area. We estimated that rainfed plantations require 839.03 m³/ton and irrigated plantations require 2355.80 m³/ton, with an average of 1597.47 m³/ton. In addition, we determined that avocado cultivation can demand up to 124.3% of agricultural water concessions in this municipality. In addition to the WF estimates, the analysis indicates that such studies are fundamental for decision-makers to develop and implement water use-efficiency strategies and shows the need for further research related to water consumption of avocado as a crop at more detailed scales to reduce uncertainty.

A photovoltaic-thermal (PVT) collector is a solar-based micro-cogeneration system which generates simultaneously heat and power for buildings. The novelty of this paper is to conduct energy and exergy analysis on PVT collector performance under two different European climate conditions. The performance of the PVT collector is compared to a PV panel. Finally, the PVT design is optimized in terms of thermal and electrical exergy efficiencies. The optimized PVT designs are compared to the PV panel performance as well. The main focus is to find out if the PVT is still competitive with the PV panel electrical output, after maximizing its thermal exergy efficiency. The PVT collector is modelled into Matlab/Simulink to evaluate its performance under varying weather conditions. The PV panel is modelled with the CARNOT toolbox library. The optimization is conducted using Matlab gamultiobj-function based on Non-Dominated Sorting Genetic Algorithm-II (NSGA-II). The results indicated 7.7% higher annual energy production in Strasbourg. However, the exergy analysis revealed a better quality of thermal energy in Tampere with 72.9% higher thermal exergy production. The electrical output of the PVT is higher than from the PV during the summer months. The thermal exergy- driven PVT design is still competitive compared to the PV panel electrical output.

Cognitive scientists have paid very little attention to magic as a distinctly human activity capable of creating situations or events that are considered impossible because they violate expectations and conclude with the apparent transgression of well-established cognitive and natural laws. And even though magic techniques appeal to all known cognitive processes from sensing, attention and perception to memory and decision making, the relation between science and magic has so far been mostly unidirectional, with the primary goal of unraveling how magic works. Building up from the deconstruction of a classic magic trick, we provide here a cognitive foundation for the use of magic as a unique and largely untapped research tool to dissect cognitive processes in tasks arguably more natural than those usually exploited in artificial laboratory settings. Magicians can submerge every spectator into the precise experimental protocol they have previously designed, accounting with ease for both circumstantial and social contexts. Magicians do not base the success of their experiments in statistical measures that smear out the individual in favor of an average spectator that we know never exists in the real world. They target each and everyone in the audience and, often, with a complete accomplishment. Magicians deliver their cognitive manipulations in real-time, in tight closed-loop with the audience, and in a single trial (they cannot afford to repeat the trick if it fails). Magic has also an inherent and strong social component, merging the private cognitive processes of each spectator with the group dynamics. Finally, when combined with the wide range of precise measuring and wearable technologies available today, magic paves the way for a road not taken towards real-world cognitive science. We dare to speculate that some of the mysteries of how the brain works may be trapped in the split realities present in each magic effect.

The period of study in the online environment can be a very demanding trial for students and masters, especially for those who are not familiar with computer technology. This is largely due to a complex of factors that come from the changes to which they are subjected, such as: leaving the parental home and settling into another living environment (living in dormitories or other forms of accommodation) but also settling with an unfamiliar and very different educational environment from what they were familiar with. Along with all the changes occurring in the family and social plan, the students had to adapt to the educational system made exclusively online. Higher educa-tion institutions in Romania use, as a method of knowledge transmission, traditional learning methods, namely they use face-to-face lecture-type courses in a lecture hall or practical and ex-planatory activities in a seminar/laboratory room. The emergence of this pandemic forced higher education institutions to switch to an online teaching mode for all types of activities included in the educational process.

Citizen participation has always been of vital importance in decision-making processes and, likewise, joint work in the formulation and execution of projects that respond to territorial needs. This in order to ensure the best impact of public or private investment, optimizing the result and community articulation. For this reason, this investigation proposes a methodology of evaluation and prioritization of projects based on an approach integrated between the modelling in dynamics systems (SDM) and the Analytical process network (ANP), in which the citizen factors are used as qualitative and quantitative variables inside the posed balance sheet model. This is how the model developed by the Stella Architect software, it offers to the decision makers approximate information about the reality of the community, especially those who were affected by the Colombian conflict and where the expectations of a comprehensive repair could disrupt the socioeconomic system and reveal more pressing interests than those of the central government. The methodology is described by the information gotten through the participatory workshops done in the California county that belongs to the Magdalena region, this is a very affected region by the conflict in Colombia. The investigation results confirm the useful of, first of all, the use of the modelling as an information-generating tool by allowing the simulation of relevant variables in the evaluation and prioritization of projects at different moments of time and, in second place, use the knowledge of the experts that expose the ANP method for establishing the importance of each variable compared with other variables and, likewise of each project compared to the rest of the alternatives in each of the different instants of time in which the evaluation is carried out, given that the results could change in any time, the official ranking is showed after an optimization process with partial results.

On the 6th September at 03:08AM local time, the Iburi-Hokkaido Earthquake, only 33 km deep triggers >5,000 co-seismic mass-movements in the hills in a 25 km radius from the epicenter. Although the majority of the mass-movements occurred in complex-geometry valley with the coalescence of deposits, a small sub-set of 59 events deposited on the semi-horizontal val-ley-floor generating separated deposits that were studied in the present contribution. The aim of the present contribution was to contribute to the existing databases of empirical relationships based on planform and vertical dataset, and to define the scalars of those relations that charac-terize the mass-movements of the Iburi-Hokkaido earthquake, with the overarching goal of generating predictors for hazard-mapping. To reach these objectives, the methodology relies on LiDAR data flown in the aftermath of the earthquake as well as aerial photographs. Using Geo-graphical Information Science (GIS) tools planform and vertical parameters were extracted to calculate the power-law relations between areas and volume, between the Fahrböschung and the volume of the deposits, as well as other geometric relationships. Results have shown that the relation S=k〖V_d〗^(2/3) where S is the surface area of a deposit and Vd the volume, and k a scalar that is function of S: k=2.1842 ln⁡(S)-10.167 with a R2 of 0.52, and this relation is improved for the open-slope mass-movements but not the valley-confined ones, that present more varia-bility. The Fahrböschung for events that started as valley-confined mass-movements was Fc = -0.043ln(D) + 0.7082 with a R2 of 0.5m while for open-slope mass-movements, the Fo = -0.046ln(D) + 0.7088 with a R2 of 0.52. These results contribute to the growing co-seismic land-slide database and they can also be the base to understand the role of the counter-slopes and complex topography on the spread and distance travelled by the mass-movement deposits.

This article presents a review of resources for batteries with a specific focus on sustainability aspects related to raw materials, electrode and electrolyte chemistries suitable for the automobile industry. We emphasize the importance of prioritizing sustainability in battery technology evolution, which is expected to shift towards earth-abundant materials. One notable advancement in this direction is the utilization of glass solid-state electrolytes, known for their high ionic conductivity, low electronic conductivity, and high dielectric constant. However, our review suggests that further research should explore synthesis methods to modify anisotropic properties, enhancing the performance of solid-state electrolytes, particularly in facilitating the flow of ions.

The realm of natural language processing has always been fascinated by the intricacies of sentence semantics. The emergence of context-aware word representations, especially from pre-trained models like ELMO and BERT, has revolutionized several semantic tasks including but not limited to, question answering, text categorization, and sentiment analysis. Despite these advancements, the integration of supplementary knowledge, particularly syntactic, to augment semantic comprehension in models remains an area ripe for exploration. This paper introduces the Syntactic Enhancement Network (SEN), a pioneering method for synergizing syntactic elements with established pre-trained language models. Our approach encompasses a dual-phase evaluation: initially, we delve into the syntactic augmentation of both RNN-based and Transformer-based language models; subsequently, we test our SEN's proficiency in two specific domains: the task of sentence completion and the extraction of biological relationships. The results are striking, with SEN achieving a stellar 91.2% accuracy in sentence completion—surpassing baseline models by a substantial 37.8%. In the context of biological relation extraction, SEN demonstrates competitive prowess with a 75.1% F1 score.

: BACKGROUND: The prevalence of smoking among students is a growing concern, particular-ly among medical students. Being associated with stress, competitiveness, and various social in-fluences, smoking can have detrimental effects on self-esteem and self-efficacy and may create a vicious cycle that may contribute to students’ well-being and academic performance out-comes.METHODS: A cross-sectional study on 456 medical students was conducted via an online survey using structured questionnaires on socio-demographic characteristics, smoking habits, nicotine dependence, self-esteem, and self-efficacy. RESULTS: The prevalence of smoking was 31.1% The scores of self-esteem and self-efficacy were positively correlated with smoking habits (W1=0.957, W2=0.975, P<0.05). Students presented rather low smoking addiction with male stu-dents having slightly higher scores than female students on self-esteem and self-efficacy, mili-tary students had higher self-esteem scores than civilians with physical activity having a posi-tive correlation with non-smoking behavior. CONCLUSION: According to our results, self-esteem and self-efficacy were slightly positively correlated with smoking habits. Furthermore, there was no statistically significant association between other social factors and smoking. Our results may develop a theoretical basis for medical students’ psychological variables studying for further implementation of university educational programs and preventive interventions em-powering students towards an overall better quality of life, addressing, among others, smoking behaviors.

The management of wounds is a significant issue that impacts individuals, healthcare systems, and society at large. This study evaluates Rigemed D (RD), a novel compound extracted from Bovine Colostrum with a unique combination of 20 different growth factors and exosomes, known for its exceptional properties in promoting cell proliferation and regeneration. This study aims to determine the effects of different doses of RD on cell survival (using CCK8) and to assess its antioxidant effect using the Comet assay in the presence of hydrogen peroxide (H2O2) on two human cell types, fibroblasts and immortalised keratinocytes (HaCat cell line). The study results revealed that RD, at doses of 1, 1.5, and 2 % v/v, significantly improved cell viability four, six, and 12 times, respectively, compared to the control group (p < 0.00001). Furthermore, the Comet assay showed a two-fold reduction in DNA damage in RD-treated cells at 2% v/v without and with H2O2 (p < 0.001). The effect of RD on cell proliferation and migration was evaluated using a scratch assay on fibroblasts and HaCat cells. The findings demonstrated a four-fold increase in cell proliferation and migration at 1 and 24 hours (p < 0.001). Immunohistochemistry confirmed this claim (p < 0.001). Also, angiogenesis induction of RD was assessed on human vein umbilical endothelial cells (HUVEC), showing that RD significantly enhanced the proliferation of endothelial HUVEC cells (p < 0.0001). In conclusion, RD is a promising vitalising compound with exceptional capabilities in promoting cell proliferation, migration, and regeneration. It also shows a significant antioxidant effect and has the potential to support all phases of wound healing involving cell proliferation, re-epithelialisation, angiogenesis, and tissue maturation. Hence, the present formulation presents a promising foundation for developing a 3D bio-printed membrane, potentially expediting the wound healing process.

The development of biofuels and biodiesel industry specifically, has resulted in the generation of large amounts of glycerol as a surplus. The conversion of glycerol, into chemicals with indus-trial interest, through anaerobic fermentation using E. coli as a biocatalyst is an attractive alter-native to improve economic performance in the biodiesel industry, for example through the bi-otransformation of residual glycerol into ethanol. For 2019, the size of the global ethanol market was valued at $ 89.1 billion US dollar. Biodiesel can be produced from several materials like rapeseed, palm, soya, corn, palm kernel, frying oil or olive-pomace oil (OPO). The last, can be extracted from alperujo, byproduct of olive oil process. However, olive-pomace oil converting into biodiesel is not enough established to achieve a global olive-oil/biodiesel derived process with minimized waste generation. Traditionally biodiesel production process produces an equivalent of 10% by mass of glycerol as a waste or by-product. This work explores the conver-sion of residual glycerol into chemicals like ethanol and hydrogen with a focus on projecting raw material potential availability from OPO, contributing to the promotion of the use of biofu-els and biodegradable compounds.

As traffic congestion gets worse year by year in metropolitan areas, cities search for solutions to improve their traffic performance and reduce their environmental impacts. This paper focuses on parking pricing and congestion pricing and their short-term effects not only on traffic congestion but also on the potential revenue for a city. We develop an easy to implement multimodal macroscopic traffic and parking search model for a central area based on aggregated data at the network level. Our methodology allows us to analyze how introducing parking pricing inside a network, or a congestion toll combined with a park and ride (P+R) scheme can affect the drivers’ decision between entering the network by car (private vehicle) or using P+R instead. This decision directly influences the number of drivers using P+R, and this impacts, in turn, the traffic performance. Based on such analysis, a city can get valuable insights to evaluate whether congestion pricing is a necessity or if the traffic improvements resulting from implementing parking pricing strategies are sufficient when combined with P+R facilities. A search algorithm is used to find the best trade-off between the parking fees and the congestion toll. Any additional revenue collected through these schemes can then be used to improve public transport or the P+R facilities themselves. With minor data collection efforts and little computational costs compared to most existing parking and congestion pricing models, we illustrate our proposed framework in a case study of an area with a high parking demand for public parking spaces within the city of Zurich, Switzerland. Results show that parking pricing combined with P+R is indeed a viable option compared to congestion pricing for improving traffic performance, even if parking pricing schemes do not target all the drivers.

Bartonella spp. bacteria can be found around the globe and are the causative agents of multiple human diseases. The most well-known infection is called cat-scratch disease, which causes mild lymphadenopathy and fever. As our knowledge of these bacteria grows, new presentations of disease have been recognized with serious manifestations. Not only has more severe disease been associated with these bacteria, but Bartonella species have also been discovered in a wide range of mammals and the pathogens’ DNA can be found in multiple vectors. This review will focus on some common mammalian reservoirs as well as the suspected vectors in relation to disease transmission and prevalence. Understanding the complex interactions between these bacteria, their vectors, and reservoirs as well as the breadth of infection by Bartonella around the world will help toassess the impact of Bartonellosis on public health.

By using geodesic equations to obtain a gravitational potential generated from a point-like source, we end up in the concept of a nearly Newtonian gravity to analyse effective potentials of quasi-circular orbits. By means of an approximate solution from an axially static and symmetric Weyl metric, we study an effective gravitational potential to obtain its related rotation curves, orbital planes and orbits. Moreover, using as initial condition a Plummer sphere, some prospects on star cluster disruption are also discussed in this framework.

We fabricate paper-supported semiconducting devices by rubbing a layered molybdenum disulfide (MoS₂) crystal onto a piece of paper, similarly to the action of drawing/writing with a pencil on paper. We show that the abrasion between the MoS₂ crystal and the paper substrate efficiently exfoliates the crystals, breaking the weak van der Waals interlayer bonds and leading to the deposition of a film of interconnected MoS₂ platelets. Employing this simple method, that can be easily extended to other 2D materials, we fabricate MoS₂-on-paper broadband photodectectors with spectral sensitivity from the ultraviolet (UV) to the near-infrared (NIR). We also used these paper-based photodetectors to acquire pictures of objects by mounting the photodetectors in a homebuilt single-pixel camera setup.

As more end devices are getting connected, the Internet will become more congested. A variety of congestion control techniques have been developed either on transport or network layers. Active Queue Management (AQM) is a paradigm that aims at mitigating the congestion on the network layer by active buffer control to avoid overflow. However, finding the right parameters for an AQM scheme is challenging, due to the complexity and dynamics of the networks. On the other hand, the Explicit Congestion Notification (ECN) mechanism is a solution that makes visible incipient congestion on the network layer to the transport layer. In this work, we propose to exploit the ECN information to improve AQM algorithms by applying Machine Learning techniques. Our intelligent method uses an artificial neural network to predict congestion and an AQM parameter tuner based on reinforcement learning. The evaluation results show that our solution can enhance the performance of deployed AQM, using the existing TCP congestion control mechanisms.

The aim of the paper is to analyze the experimental results of the influence of elevated temperatures and strain rate on the mechanical and structural properties of steel 42CrMo4. The experiments were based on uniaxial tension and compression tests at high temperatures between 700 °C and 1000 °C and strain rates range 0.0018 - 0.1 s^-1. The influence of temperature and strain rate on yield stress, strain to fracture, hardness, structural changes, and fracture characteristics were analyzed. Due to the dynamic recrystallization phenomenon present during the hot tensile tests, an increase in the flow stress is observed at the beginning of the deformation, after which it decreases until the fracture. By increasing the deformation temperature from 700 °C to 1000 °C, the tensile stress decreases significantly for all strain rates. The increase in the strain rate leads to the increase in the tensile stress. In compression tests by increasing the strain rate, the true strain is slightly increasing, but this depends on the temperature. The non-uniformity of deformations obtained at different values of the strain rate and temperature were also analyzed. Analysis by scanning electron microscopy showed the ductile behavior of the material. The degree of damage of the material caused by the presence of cavities increases by increasing the deformation temperature. For all the presented deformation conditions, the presence of the fracture through the ductile fracture mechanism was produced by the localized of necking and the coalescence of microvoids. By increasing the deformation temperature and reducing the strain rate, the fracture behavior of 42CrMo4 steel can be improved.

The use of the voice of the customer as a main input to guide decision making towards customer centricity strategies has become a necessity for companies. This research proposes a structured method of textual processing using the KDD (Knowledge Discovery Databases) methodology applied to the tweets of users of Colombian public sector companies, through the analysis of temporal sentiments and topic modeling to identify the areas in which actions should be taken to improve the perception of service. To fulfill such purpose, tweets from January to June 2022 are processed, followed by a temporal analysis of the evolution of the sentiment based on 3 enriched dictionaries; after, the LDA (Linear Discriminant Analysis) algorithm is implemented to find the areas with ailment for the user, in addition to propose a method to homologate the CIER (Comisión de Integración Energética Regional) survey. Finally, metrics are detailed to follow up the perception of the service. It is concluded that for the Acueducto the topic with the highest number of complaints is related to "Water truck request", for Enel "Servide Outages" and for Vanti: " Case solution and request information". Also, the homologation of 3 of the 5 pillars on which the CIER survey is based is presented.

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

For a long time, the transition to adulthood was seen as a troubled period where good development was synonymous with the absence of problems. Positive Youth Development (PYD) emerged as a holistic and strength-based perspective that focuses on the fact that young people may have the internal and external resources for healthy and successful development through five dimensions (5C’s) that empower them: Perceived Competence, Confidence, Character, Connection, and Caring. The aim of this study was to examine the relationship between the global PYD factor (and the 5C’s) and risk behaviors, in addition to analyzing gender differences. This study showed the results of a cross-sectional study of 1044 emerging adults from 11 Spanish universities in 2021. Data collection was performed by applying an online self-report measure. The results showed that the Character was protective against substance abuse, mainly in women, while the connection was related to the participation of betting money and online betting in men. Caring was protective against money bets in the men’s sample. However, controversial results were found regarding Perceived competence, which had a positive association with substance abuse, money bets, and drunk driving. It seems that high levels of Perceived competence, rather than objective competence, were associated with engagement in various risk behaviors, especially in the absence of other C´s. These results are discussed regarding the promotion of PYD to improve successful development and may suggest the need to foster healthy lifestyles and prevent risky behaviors in youth through the 5C's promotion programs within the university context.

The genus Fusarium includes several agronomically important and toxin-producing species, that are worldwide distributed and can cause a wide range of diseases. Crown and stalk rots and grain infections are among the most severe symptoms that Fusarium spp. can cause on maize. The disease development usually occurs during germination, but it may also affect the later phases of plant growth. The purpose of this study was to investigate the diversity and the patho-genicity of 41 isolates recovered from symptomatic seedlings collected in Northern Italy, and from seeds with five different geographical origins during 2019 and 2020. The pathogenicity was tested and confirmed on 23 isolates causing rotting on maize seedlings. A multi-locus phylogeny analysis, based on four genomic loci (tef1-α, rpb2, calm and tub2), was performed for 23 repre-sentative isolates. Representative isolates were identified as species belonging to three species complexes (SC). Fusarium verticillioides and F. annulatum in the F. fujikuroi SC. Fusarium commune was identified in the F. nisikadoi SC, and three different lineages were found in the Fusarium ox-ysporum SC. This study reports F. annulatum, and two lineages of the Fusarium oxysporum SC as maize pathogens for the first time in Italy.

Background: Meniere disease (MD) is an inner ear disorder associated with comorbidities such as autoimmune diseases or migraine. This study describes clinical and cytokine profile in MD according to the age of onset of the condition. Methods: A cross-sectional study including 83 MD patients: 44 with early onset MD (EOMD, <35 years old), and 39 with late onset MD (LOMD, > 50 years old), 64 patients with migraine and 55 controls was carried out. Clinical variables and cytokines levels of CCL3, CCL4, CCL18, CCL22, CXCL1 and IL-1β were compared among the different groups. Results: CCL18 levels were higher in patients with migraine or MD than in controls. Elevated levels of IL-1β were observed in 11.4% EOMD and in 10.3% LOMD patients and these levels were not dependent on the age of individuals. EOMD had a longer duration of the disease (p=0.004) and a higher prevalence of migraine than LOMD (p=0.045). Conclusions: Patients with EOMD have a higher prevalence of migraine than LOMD, but migraine is not associated with any cytokine profile in patients with MD. The levels of CCL18, CCL3 and CXCL4 were different between patients with MD or migraine and controls.

In this work, we report synthesis of Cu, Pt and Pd doped SnO₂ powders and their comparative CO gas sensing studies. Dopants were incorporated into SnO₂ nanostructures using chemical and impregnation methods by using urea and ammonia as precipitation agents. The synthesized samples were characterized using X-ray diffraction (XRD), Raman spectroscopy, Scanning electron microscopy (SEM) and High resolution transmission electron microscopy (HR-TEM). The presence of dopants within the SnO₂ nanostructures was evidenced from HR-TEM. Doped powders utilizing chemical methods with urea as precipitation agent presented higher sensitivities compared to the remaining, which is due to the formation of uniform and homogeneous particles resulted from the temperature assisted synthesis. The particle sizes of doped SnO₂ nanostructures were in the range of 40-100 nm. An enhanced sensitivity around 1783 was achieved with Cu doped SnO₂ when compared with two other dopants i.e., Pt (1200) and Pd: SnO₂(502). The high sensitivity of Cu: SnO₂ is due to formation of CuO and its excellent association and dissociation in the presence of CO with adsorbed atmospheric oxygen at sensor operation temperatures resulted in high conductance. Cu: SnO₂ may be an alternative and cost effective sensor for industrial applications.

Heavy metals are dangerous contaminants constituting a threat to human health because they persist in soils and are easily transferred into the food chain, causing damages to human health. Among heavy metals, nickel appears to be one of the most dangerous responsible for different disorders. Public health protection requires nickel detection in environment and food chains; a simple, rapid and sensitive method to detect nickel contamination is represented by biosensors. In this paper we report the setup of a whole-cell based system, in which protoplasts, obtained from Nicotiana tabacum leaves, were used as transducers to detect the presence of heavy metal ions and, in particular, nickel ions. Protoplasts were genetically modified with a plasmid containing the GFP reporter gene under the promoter region of a sunflower small HSP gene control. By this device the presence of heavy metal ions was detected. Thus, the possibility to use this whole-cell system as a novel tool to detect the presence of nickel ions in food matrices was assessed.

Three-dimensional matrices are a new strategy used to tackle type I diabetes; a chronic metabolic disease characterized by the destruction of beta pancreatic cells. Type I collagen is an abundant extracellular matrix (ECM), component that has been used to support cell growth. However, pure collagen possesses some difficulties including low stiffness and strength, and high susceptibility to cell-mediated contraction. Therefore, we developed a collagen hydrogel with a poly(ethylene glycol) diacrylate (PEGDA) interpenetrating network (IPN), functionalized with vascular endothelial growth factor (VEGF) to mimic the pancreatic environment for the sustenance of beta-pancreatic cells. We analyzed the physicochemical characteristic of the hydrogels and found that they were successfully synthesized. The mechanical behavior of the hydrogels improved with the addition of VEGF, and the swelling degree and the degradation were stable over time. In addition, it was found that 5 ng/mL VEGF-functionalized collagen/PEGDA IPN hydrogels sustained and enhanced viability, proliferation, respiratory capacity and functionality of beta pancreatic cells. Hence, this is a potential candidate for future preclinical evaluation, which may be favorable for diabetes treatment.

Lifestyle has been associated with breast cancer risk through different pathways, including oxidative stress. Antioxidant enzymes are endogenous defense mechanisms against oxidative stress damage, and this response might be modulated by the genetic variation in these enzyme-codifying genes. This study aimed to analyze the synergistic effect of an antioxidant Healthy Lifestyle Index (HeLiX) composed of principal components of Western dietary pattern, alcohol consumption, smoking and physical activity, and genetic polymorphisms in the first-line antioxidant response family genes SOD, GPX, and CAT on breast cancer risk. We included 176 SNPs, and only CAT rs554576 remained significant after correction for multiple comparisons. Breast cancer odds were reduced at the highest (T3) and medium (T2) tertiles of the HeLiX. When stratified by HeLiX, we observed a reduced risk of breast cancer with at least one T-allele, and the effect increased in a dose-dependent manner. Compared to the reference category (HeLiX T1 and AA genotype), women at the HeLiX T3 with AT and TT genotypes in postmenopausal women showed an OR = 0.15 (95% CI 0.07–0.32). For HeLiX T2 and AT genotype OR = 0.26 (95% CI 0.13–0.54); for TT genotype OR = 0.24 (95% CI 0.12–0.45). For premenopausal women, at the HeLiX T3 and AT genotype OR = 0.29 (95% CI 0.13–0.62); for the TT genotype OR = 0.21 (95% CI 0.08–0.51). We also observed an inverse association for HeLiX T2 and TT genotype (OR 0.39 95% CI 0.17–0.87). Our study shows a significant synergistic gene-environment interaction on an additive scale, contributing to understanding pathways involved in breast cancer etiology and prevention.

Defensive behavior is a function of specific survival circuits, the “aversive brain system”, that are thought to be conserved across vertebrates, and involve threat detection and the organization of defensive responses to reduce or eliminate threat. In mammals, these circuits involve amygdalar and hypothalamic subnuclei and midbrain circuits. The increased interest in teleost fishes as model organisms in neuroscience created a demand to understand which brain circuits are involved in defensive behavior. Telencephalic and habenular circuits represent a “forebrain circuit” for threat processing and organization of responses, being important to mounting appropriate coping responses. Specific hypothalamic circuits organize neuroendocrine and neurovegetative outputs, but are the less well-studied in fish. A “midbrain circuit” is represented by projections to interneurons in the optic tectum which mediate fast escape responses via projections to the central gray and/or the brainstem escape network. Threatening stimuli (especially visual stimuli) can bypass the “high road” and directly activate this system, initiating escape responses. Increased attention to these circuits in an evolutionary framework is still needed.

Hillslope and mountain roads are often the source of erosion, which in turn can lead to larger landslides and other types of mass-movements. For this reason, low-cost repeat surveys that can be done by practitioners and not solely scientists and engineers is essential. To solve this issue the present contribution shows the testing and applicability of a mix of SfM-MVS and low-cost SLAM technology to provide erosion information. The low-cost SLAM generated between 300 ~ 900 points per square meter, while SfM-MVS created between ~11,000 to 900,000 points. The density is however a trade-off against a spatially varying error, although the variability at the road-cut scale only ranges from 2 cm vertically to 2.5 cm in x,y,z based on the C2C algorithm. Furthermore, this error tends to be more important in the higher section of the cutout (further away from the sensor and at a flatter angle). It is thus possible to measure small-scale roadside change, providing that the change is in the range of >5 cm (adding the maximum potential error twice) and providing that the road-cut is such that the sensors can be brought close to the surface (camera or sensor on a pole). The authors suggest that it can be a solution for state and agencies with limited funding and that cannot afford regular laser or for roadside that are difficult to access.

This work exclusively focuses on the assessment of the thermal performance of a multifunctional facade panel incorporating PCM in foam layers, recurring to a hot box heat flux meter method to determine the thermal transmittance (U-value). The experimental setup is based on the steady-state approach using climatic chambers, assuring a stable thermal environment. Even small fractions of PCM achieved a small reduction in thermal amplitude. Numerical simulations using Ansys Fluent were developed to evaluate the performance of PCM use over a wide range of temperature boundary conditions and operating modes. These numerical models were calibrated and validated using the results of experimental tests, achieving a correlation factor of 0.9674, thus accurately representing a real-world scenario. The decrement factor (f) was used to analyse the data. It was identified that the efficiency of the panel and size of the optimum region increased with the PCM fraction growth. The simulated behaviour was optimum when the input mean temperature is of 20 °C for a room temperature of between 18-20 °C. The results show the significant potential of the multi-layered panel and the thermal regulator effect of the PCM incorporated on indoor space temperature to reach good thermal comfort levels.

This paper establishes methods that quantify the structure of statistical interactions within a given data set using the characterization of information theory in cohomology by finite methods, and provides their expression in terms of statistical physic and machine learning. Following [1–3], we show directly that k multivariate mutual-informations (I_k) are k-coboundaries. The k-cocycles are given by I_k = 0, which generalize statistical independence to arbitrary dimension k. The topological approach allows to investigate Shannon’s information in the multivariate case without the assumptions of independent identically distributed variables. We develop the computationally tractable subcase of simplicial information cohomology represented by entropy H_k and information I_k landscapes. The I₁ component defines a self-internal energy functional U_k, and (−1)^k I_k,k≥2 components define the contribution to a free energy functional G_k of the k-body interactions. The set of information paths in simplicial structures is in bijection with the symmetric group and random processes, provides a topological expression of the 2nd law and points toward a discrete Noether theorem (1st law). The local minima of free-energy, related to conditional information negativity and the non-Shannonian cone of Yeung [4], characterize a minimum free energy complex. This complex formalizes the minimum free-energy principle in topology, provides a definition of a complex system, and characterizes a multiplicity of local minima that quantifies the diversity observed in biology. Finite data size effects and estimation bias severely constrain the effective computation of the information topology on data, and we provide simple statistical tests for the undersampling bias and for the k-dependences following [5]. We give an example of application of these methods to genetic expression and cell-type classification. The maximal positive I_k identifies the variables that co-vary the most in the population, whereas the minimal negative I_k identifies clusters and the variables that differentiate-segregate the most. The methods unravel biologically relevant I₁₀ with a sample size of 41. It establishes generic methods to quantify the epigenetic information storage and a unified epigenetic unsupervised learning formalism.

The double burden of malnutrition (DBM) is escalating in low- and middle-income countries (LMICs), including in Rwanda, most notably in urbanizing areas. The 2019-2020 Rwanda Demographic Health Survey (DHS) revealed 33% of children under 5 are stunted while 42% of women in urban areas are overweight or obese. This coexistence has contributed to a surge in non-communicable diseases (NCDs), particularly in secondary cities. Using the World Health Organization’s (WHOs) “double-duty action” (DDA) concept, this study aims to identify and evaluate interventions with double-duty potential in Rwanda, focusing on the districts of Rusizi and Rubavu. Guided by Hawkes et al.’s conceptual framework for identifying DDA entry points, a desk review of national policies pinpointed 4 programs with DDA potential: early childhood development (ECD) centers, the school feeding program, farmer field schools (FFS), and the provision of nutrition-sensitive direct support. In-person interviews with key stakeholders assessed their implementation and a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis informed context-specific recommendations for their improvement. Recommendations include targeting beliefs surrounding nutrition, improving trainings for community educators, enhancing parent – particularly father – involvement, and close follow-up. These findings offer actionable strategies for governments and nutrition stakeholders and may benefit similar interventions in other rapidly urbanizing LMICs.

This study investigates the suitability of the timestamp approach algorithm for predicting blood pressure (BP) using wearable and comfortable devices, showcasing its accuracy even with low-frequency sampled signals. Developed within the SINTEC European project, the algorithm utilizes Electrocardiogram (ECG) and Photoplethysmogram (PPG) sensors, demonstrating promising results in both laboratory and hospital settings. The research emphasizes the algorithm’s potential to transform continuous and non-invasive BP monitoring through wearable technology, offering frequent measurements with minimal discomfort. While the study shows promise, further exploration is needed, focusing on optimizing machine learning coefficients for long-term monitoring applications and addressing potential changes over time. Technological improvements, including the implementation of edge computing algorithms, hold the key to enhancing BP accuracy, denoising techniques, and integrating alarm systems for future wearable solutions. This study emphasizes the adaptability of the algorithm for diverse healthcare environments, paving the way for broader applications in convenient and reliable BP monitoring.

Several questions regarding the evolution of SARS-CoV-2 remain poorly elucidated. One of these questions is the possible evolutionary impact of SARS-CoV-2 after the infection in domestic animals. In this study, we aimed to evaluate the potential role of cats as generators of relevant SARS-CoV-2 lineages during the pandemic. A total of 105 full-length genome viral sequences obtained from naturally infected cats during the pandemic were evaluated by distinct evolutionary algorithms. Analyses were enhanced, including a set of highly related SARS-CoV-2 sequences recovered from human populations. Our results showed the apparent high susceptibility of cats to the infection SARS-CoV-2 compared with other animal species. Evolutionary analyses indicated that the phylogenomic characteristics displayed by cat populations were influenced by the dominance of specific SARS-CoV-2 genetic groups affecting human populations. However, disparate dN/dS rates at some genes between populations recovered from cats and humans suggested that infection in these two species may suppose a different evolutionary constraint for SARS-CoV-2. Interestingly, the branch selection analysis showed evidence of the potential role of natural selection in the emergence of 5 distinct cat lineages during the pandemic. Although these lineages were apparently irrelevant to public health during the pandemic, our results suggested that additional studies are needed to understand the role of other animal species in the evolution of SARS-CoV-2 during the pandemic.

Glioblastoma (GBM), the most common and aggressive primary brain tumor in adults, remains one of the least treatable cancers. Current standard of care—combining surgical resection, radiation, and alkylating chemotherapy—results in a median survival of only 15 months. Despite decades of investment and research into the development of new therapies, most candidate anti-glioma compounds fail to translate into effective treatments in clinical trials. One key issue underlying this failure of therapies that work in pre-clinical models to generate meaningful improvement in human patients is the profound mismatch between drug discovery systems—cell cultures and mouse models—and the actual tumors they are supposed to imitate. Indeed, current strategies that evaluate the effects of novel treatments on GBM cells in vitro fail to account for a wide range of factors known to influence tumor growth. These include secreted factors, the brain’s unique extracellular matrix, circulatory structures, the presence of non-tumor brain cells, and nutrient sources available for tumor metabolism. While mouse models provide a more realistic testing ground for potential therapies, they still fail to account for the full complexity of tumor-microenvironment interactions, as well as the role of the immune system. Based on the limitations of current models, researchers have begun to develop and implement novel culture systems that better recapitulate the complex reality of brain tumors growing in situ. A rise in the use of patient derived cells, creative combinations of added growth factors and supplements, may provide a more effective proving ground for the development of novel therapies. This review will summarize and analyze these exciting developments in 3D culturing systems. Special attention will be paid to how they enhance the design and identification of compounds that increase the efficacy of radiotherapy, a bedrock of GBM treatment.

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

Several optimization models of irreversible reverse cycle machines have been developed based on different optimization criteria in the literature, most of them using linear heat transfer laws at the source and sink. This raises the issue how close to actual operation conditions they are, since the heat transfer law on the phase-change processes is dependent on ΔT3. This paper addresses this issue by proposing a general model for study and optimization of thermal machines with two heat reservoirs applied to a Carnot-like refrigerator, with non-linear heat transfer laws and internal and external irreversibility. The optimization was performed using First and Second Law of Thermodynamics and Lagrange multipliers method. Thus, several constraints were imposed to the system, also different objective functions were considered, allowing finding the optimum operating conditions, as well as the limited variation ranges of the system parameters. Results show that the nature of the heat transfer laws affects the optimum values of system parameters for obtaining maximum performances and also their magnitude. Sensitivity studies with respect to system several parameters are presented. The results contribute to the understanding of the system limits in operation under different constraints and allow choosing the most convenient variables in given circumstances.

Granular cell tumors (GCTs), known also as Abrikossoff tumors, are rare tumors that originates from Schwann cells that primarily localize in the tongue, skin, and submucosal tissues and involve the gastrointestinal tract in 11% of cases. We present a case of a young woman who first presented to our centre in 2018, for an EGDS to assess a thickening of the esophageal wall, seen on a CT. In that occasion, a diagnosis of Abrikossoff tumor was made. She underwent endoscopic resection with subsequent yearly follow-up without evidence of recurrence. 5 Years later, on a routine colonoscopy, we found numerous white submucosal formations in all of the explored tracts, with a histological examination compatible with GCT. Her daughter presented with a white nodule on her tongue, also diagnosed as GCT. Her daughter was also diagnosed with GCT of the tongue a few months later.

The triangulation process represents a violation of the boundary between parental and child relational subsystems which, in turn, affects family dynamics and relationships. The paper, with distinct reference to marital conflict and divorced couples, describes the main causes of the triangulation process and its impact on children (and adolescents) as significant third participants within the parental conflict. Besides, it fo-cuses on long-term consequences associated with triangulation process to parental conflict exposure, that can adversely affect the well-being of children during their life-cycle, and even into adulthood. A data-search was carried out for articles to be included in the review and articles were retrieved from different electronic databases (first: Scopus and Web of Science, then: PsychINFO, Google Scholar, EBSCO and ScienceDirect,). After having initially considered 152 articles, 58 studies were selected for this research. A qualitative analysis was conducted on selected studies, focusing on: (1) different types of triangulation commonly used in intergenerational family relationships; (2) an updated summary of the research around the impact of triangulation on the well-being of children and the parent-child conflict; and (3) the main characteristics of successful intervention of preventative and psychotherapeutic treatments. In conclusion, the results, examining the long-term effects of the triangulation process, highlight the developmental paths of children that are more exposed and at risk, and focuses on the importance of preventing the intergenerational transmission of marital conflict, as a way to reduce mental health costs and to improve the well-being of children and families who are all involved in these conflicting and destructive dynamics.

The brown seaweed Alaria esculenta is the second most cultivated species in Europe and it is therefore of interest to expand its application in developing food products. In this study, a lactic acid bacteria consortium (LAB consortium) consisting of three Lactiplantabacillus plantarum strains (relative abundance ~ 94%) and a minor amount of a Levilactobacillus brevis strain (relative abundance of ~ 6%) was investigated for its ability to ferment carbohydrates available in brown seaweed. The consortium demonstrated ability in fermenting glucose, mannitol, galactose, mannose, and xylose, of which glucose and mannitol were the most favored substrates; no growth was observed on fucose, mannuronic and guluronic acid. The consortium used different pathways for carbohydrate utilization and produced lactic acid as the main metabolite. In glucose fermentations, only lactic acid was produced, but use of mannitol as carbohydrate source, resulted in co-production of lactic acid, ethanol and succinate. Xylose fermentation resulted in acetate production. The consortium was also able to utilize laminari-oligosaccharides (DP 2-4), obtained after enzymatic hydrolysis of laminarin, and produced lactic acid as metabolite. The consortium could grow directly on A. esculenta, resulting in a pH decrease to 3.8 after 7 days of fermentation. Incubation of the same seaweed at corresponding conditions without inoculation resulted in spoilage of the seaweed by endogenous bacteria.

(1) Background: Adolescent well-being is a multifaceted construct embedded in family, school, and peer socialization contexts. By adopting a social-psychological perspective we test the association between three sources of support (parents, teachers, peers) and specific components of subjective well-being (cognitive, affective, global-and-domain-specific) to determine whether there is a functional specialization of the role that these crucial socialization agents play for adolescents to attain well-being in specific life domains. (2) Methods: Cross-sectional Albanian data from Wave 3 of the Children’s Worlds International Survey (www.isciweb.org) were used, including 2,339 adolescents (age range 9-13; girls = 49.3%). A structural equation model (SEM) was employed to explore associations between supportive relationships with parents, teachers, and peers and adolescent well-being. (3) Results: Findings support a functional specialization hypothesis as parental support was significantly related to global cognitive and affective well-being; teacher support was significantly related with school satisfaction; and significant relations were found between peer support and almost all well-being variables (context-free, domain-based life satisfaction and affective subjective well-being). (4) Conclusions: Findings contribute to a more nuanced understanding of the role of supportive relationships with adults and peers in adolescents’ proximal socialization contexts (family, school, peer groups) and specific components of subjective well-being.

Background: Acute ischemic stroke is among the main causes of mortality worldwide; a rapid and opportune diagnosis is crucial to improve a patient's outcome. MicroRNAs are quite useful for a rapid and accurate diagnosis.Methods: We perform both structural networks approach and a meta-analysis (using a random-effect model to evaluate the heterogeneity and risk bias, according to the PRISMA statement) to analyze the feasibility to develop a microRNA-based biomarker panel for an opportune AIS diagnosis. Results: Structural networks identify a set of eight miRNAs (miR-16, miR-124-3p, miR-484, miR-15a, miR-4454, miR-107, miR-125b-5p and miR-320b) as preliminary microRNA-based biomarker panel, from these only three microRNAs are significantly associated with the main risk factors of AIS, (miR-107: hypertension, 95% CI 9.74-53.24 p<0.0001, type 2 Diabetes mellitus, 95% CI 2.18-19.26); p=0.0008; miR-16 hypertension, 95% CI 1.26-3.56 p=0.0046, smoking, 95% CI 1.07-3.54 p=0.0277; and miR-15a hypertension, 95% CI 1.26-3.56 p=0.0046; smoking, 95% CI 1.07-3.54 p=0.0277). However, the meta-analysis reveals that data is highly heterogeneous and biased; and only microRNAs isolated from plasma samples and further processed in microarrays are the most reliable to distinguish AIS patients.Conclusions: Together our results show that although there are some miRNAs that seem to be associated with AIS, we are still far to develop a miRNA-based biomarker for AIS diagnosis and it is necessary to harmonize the protocols, results and include more populations for further studies otherwise we will remain throwing punches in the dark.

With a longer-term goal of addressing the comparative behavior of the aqueous halides F$^-$, Cl$^-$, Br$^-$, and I$^-$ on the basis of quasi-chemical theory (QCT), here we study structures and free energies of hydration clusters for those anions. We confirm that energetically optimal $(\mathrm{H_2O})_n\mathrm{X}$ clusters, with X = Cl$^-$, Br$^-$, and I$^-$, exhibit \emph{surface} hydration structures. Computed free energies based on optimized surface hydration structures utilizing a harmonic approximation, typically (but not always) disagree with experimental free energies. To remedy the harmonic approximation, we utilize single-point electronic structure calculations on cluster geometries sampled from an AIMD (\emph{ab initio} molecular dynamics) simulation stream. This \emph{rough-landscape} procedure is broadly satisfactory and suggests unfavorable ligand crowding as the physical effect corrected. Nevertheless, this procedure can break down when $n \gtrsim 4$, with the characteristic discrepancy resulting from a relaxed definition of clustering in the identification of $(\mathrm{H_2O})_n\mathrm{X}$ clusters, including ramified structures natural in \emph{physical cluster theories.} With ramified structures, the central equation for the present rough-landscape approach can acquire some inconsistency. Extension of these physical cluster theories in the direction of QCT should remedy that issue, and should be the next step in this research direction.

The surge in popularity of Delta-8 Tetrahydrocannabinol (D8-THC) products, coupled with a lack of stringent regulation and oversight, has given rise to concerns regarding consumer safety and compliance with existing laws. This article delves into the challenges posed by the unregulated sale of D8-THC products, emphasizing the potential for contamination with prohibited constituents, including Delta-9 Tetrahydrocannabinol (D9-THC). The 2018 Farm Bill dictates that D9-THC concentrations must not exceed 0.3%, necessitating precise testing methods for accurate validation. Existing testing procedures, particularly involving High-Performance Liquid Chromatography (HPLC), face difficulties in distinguishing between D8 and D9 peaks, necessitating adjustments in parameters to enhance accuracy. The development of more refined testing methodologies is crucial for companies to ensure compliance, prevent adverse health effects, and provide consumers with accurately characterized cannabinoid profiles in the products they purchase.

Chronic stress, culminating in burnout, evolves gradually and is notoriously difficult to detect due to vague symptoms and individuals' hesitance to acknowledge their struggles. To expedite the identification and recognition of this condition, enabling timely psychological intervention, the integration of Artificial Intelligence (AI) is increasingly considered. This research does not assert the feasibility of an AI system managing all aspects of chronic stress's impact. However, it highlights the capability of current technology to detect stress indicators based on quantifiable data like Heart Rate (HR) and organizational climate dimensions. Although other physiological markers such as oximetry, skin galvanic response, and EKG have been explored, they have not shown reliable differentiation between stress and joy. Focused on the unique context of school principals in the Bedouin regions of Israel, this study investigates the interplay between HR, organizational climate, and stress levels. It introduces a novel application of a fuzzy logic tool that combines HR and organizational climate metrics to aid in stress diagnosis. This tool incorporates the psychologist's expertise to provide real-time data crucial for developing effective coping strategies. While the AI-supported fuzzy system does not replace professional psychological intervention, it significantly enhances the speed of condition identification and intervention planning, thus shortening the response time to stress-related issues in educational leadership within culturally specific settings. The application of such AI-driven tools is pivotal for sustaining the well-being and effectiveness of educational leaders, thereby supporting the broader goal of educational sustainability.

We assessed depression, anxiety, and stress in healthcare workers (HCWs) in 2023 and the evo-lution of depression in 2023 compared with 2022. In September-November 2023, 181 HCWs from the Infectious Diseases Hospital, Cluj-Napoca, Romania, completed the Depression, Anxiety, and Stress 21 Scale (DASS-21 R), the Patient Health Questionnaire-9 (PHQ-9), and the Hamilton Anxiety Rating Scale (HAM-A). The prevalence of moderate-to-severe levels was 13.81% for DASS-Depression, 18.79% for DASS-Anxiety, 16.02% for DASS-Stress, 19.89% for PHQ-9, and 12.16% for HAM-A. Moderate-to-severe PHQ-9 clinical depression was found in 19.89% of respondents, and moderate-to-severe HAM-A clinical anxiety in 12.16%. Moderate-to-severe PHQ-9 depres-sion was significantly lower in the 2023 study group (19.89%, N=181) compared with 2022 (30.60%, N=114) (p=0.036), also within the 2022-2023 follow-up study group (N=88) (p=0.026). We did not find significant statistical differences between those infected vs. non-infected, vaccinated vs. non-vaccinated, working with vs. non-working with SARS-CoV-2 infected patients. Males were significantly more stressed (p=0.018) and anxious (p=0.034), and physicians in training had the highest prevalence of moderate-to-severe depression (31.60%), followed by physicians (25.64%). In 2023, depression, anxiety, and stress symptoms decreased but remained within a concerning range. By addressing these psychological issues, we can prevent professional crises in the healthcare system.

Statistical based reconstruction methods and signal processing tooling techniques are implemented and used to detect delaminations or debondings within composite items. From literature it appears that, although a single procedure for the estimation of the structural health is a fast solution, a multiple analysis based on different reconstruction methods or different damage parameters could provide more detailed information about the location and the severity of possible failures. This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on ultrasonic guided waves (GW) tomographic technique and piezoelectrics (PWAS) in pitch-catch configuration. In this sense, this work evidences an improvement in damage detection when the cross-correlation is included as part of the GW-based system for damage assessment approach. The specimens used as test structures to demonstrate the validity of the methodology derive from an aircraft wing test article where damages are specified as skin delamination produced by low energy impact.

Since its emergence, COVID-19 has caused a great impact in health and social terms. Governments and health authorities have attempted to minimize this impact by enforcing different mandates. Recent studies have addressed the relationship between various socioeconomic variables and compliance level to these interventions. However, little attention has been paid to what constitutes people's response and whether people behave differently when faced with different interventions. Data collected from different sources show very significant regional differences across the United States. In this paper, we attempted to shed light on the fact that a response may be different depending on the health system capacity and each individuals’ social status. For that, we analyzed the correlation between different societal variables (i.e. education, income levels, population density, etc.) along with healthcare capacity related variables (i.e. hospital occupancy rates, percentage of essential workers, etc.) with regards to people's level of compliance with three main governmental mandates in the United States: mobility restrictions, mask adoption, and vaccine participation. Our aim was to isolate the most influential variables impacting behavior in response to these policies. We found that there was a strong relationship between individuals' educational levels and political preferences with respect to compliance with each of these mandates.

Research found that those who believe sexual orientation is inborn have generally positive attitudes towards gay men and lesbians. However, other studies have also found that these beliefs could include negative eugenic ideas. This study aims to investigate the role of people’s beliefs about the aetiology of sexual orientation on attitudes towards adoption for both gay and lesbian couples. We hypothesized that this relationship would be mediated by sexual prejudice. To test the predictions, 256 Italian heterosexual participants were asked to answer to a scale about their beliefs regarding the aetiology of sexual orientation, sexual prejudice, and attitudes towards adoption by same-sex couples. Results confirmed that the relationship between aetiology beliefs and adoption support was fully mediated by sexual prejudice. These investigation results suggest that the belief that sexual orientation is controllable may serve to justify one’s prejudice and, in turn, result in a lower support for same-sex couples’ adoption.

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

In this study, we aimed to determine the trend of antimicrobial resistance pattern of pathogens isolated in samples collected from patients hospitalized in the intensive care unit (ICU), in selected periods before and after COVID-19. A retrospective study of bacterial pathogens was performed on 1267 patients. The resistance patterns were analyzed using Vitek 2 Compact system. Positive-bacterial culture data of 1695 samples from pre-COVID-19 period and 1562 from post-COVID-19 period were obtained. The most frequently isolated in both periods were Staphylococcus aureus and Klebsiella spp. Klebsiella spp. had a statistically significant increase in resistance rates in the post COVID-19 period, against colistin, gentamicin and aztreonam. For E. coli strains, it was registered a significant increase against colistin and a significant decrease against levofloxacin and imipenem. For Acinetobacter spp. strains it was observed a significant increase against colistin. More than 50% from the Staphylococcus aureus strains were MRSA with statistically significant increases in antimicrobial resistance rate in the post-COVID-19 period against doxycycline, linezolid, rifampicin and teicoplanin. The study revealed a significantly increasing trend of the antimicrobial resistance rate of Gram-negative pathogens (Klebsiella spp., Acinetobacter spp.) against certain antibiotics, including those used only in cases where there are no other therapeutic options.

Eastern boundary upwelling systems feature strong zonal gradients of physical and biological ocean properties between cool, productive coastal oceans and warm, oligotrophic subtropical gyres. Zonal currents and jets (striations) are therefore likely to contribute to the transport of water properties between coastal and open oceanic regions. Multi-sensor satellite data are used to characterize the signatures of striations in sea surface temperature (SST), salinity (SSS), and chlorophyll-a (Chl-a) in subtropical eastern North/South Pacific (ENP/ESP) upwelling systems. In the ENP, tracers exhibit striated patterns extending up to ~2500 km offshore. Striations in SST and SSS are highly correlated with quasi-zonal jets, suggesting that these jets contribute to SST/SSS mesoscale patterns via zonal advection. Chl-a striations are collocated with sea surface height (SSH) bands, a possible result of mesoscale eddy trains trapping nutrients and forming striated signals. In the ESP, striations are only found in SST and coincide with SSH bands, consistently with quasi-zonal jets located outside major zonal tracer gradients. An interplay between large-scale SST/SSS advection by the quasi-zonal jets, mesoscale SST/SSS advection by the large-scale meridional flow and eddy advection may explain the persistent ENP hydrographic striations. These results underline the importance of quasi-zonal jets for surface tracer structuring at the mesoscale.

Background: Obesity remains a widely debated issue, often criticized for the limitations in its identification and classification. This study aims to compare two distinct systems for classifying obesity: Body Mass Index (BMI) and body fat percentage (BFP) as assessed by bioelectrical impedance analysis (BIA). By examining these measures, the study seeks to clarify how different metrics of body composition influence the identification of obesity-related risk factors. Methods: The study enrolled 1255 adults, comprising 471 males and 784 females, with a mean age of 36 ± 11.90 years. Participants exhibited varying degrees of weight status, including optimal weight, overweight, and obesity. Body composition analysis was conducted using the TANITA Body Composition Analyzer BC-418 MA III device (T5896, Tokyo, Japan), evaluating the following parameters: current weight, basal metabolic rate (BMR), adipose tissue (%), muscle mass (%), and hydration status (%). Results: Age and psychological factors like cravings, fatigue, stress, and compulsive eating were significant predictors of obesity in the BMI model but not in the BFP model. Additionally, having a family history of diabetes was protective in the BMI model (OR: 0.33) but increased risk in the BFP model (OR: 1.66). The BMI model demonstrates exceptional predictive ability (AUC=0.998). In contrast, the BFP model, while still performing well, exhibits a lower AUC (0.975), indicating slightly reduced discriminative power compared to the BMI model. Conclusions:BMI classification demonstrates superior predictive accuracy, specificity, and sensitivity. This suggests that BMI remains a more reliable measure for identifying obesity-related risk factors compared to the BFP model.

Major cardiovascular events (MACE) are a cause of major mortality worldwide. The narrowing and blockage of coronary arteries with atherosclerotic plaques is diagnosed and treated with percutaneous coronary intervention (PCI). During this procedure, coronary angiography (CAG) remains the most widely used guidance modality for the evaluation the affected blood vessel diameter in order to decide if intervention with stent colocation is suitable, where small blood vessels (&lt; 2.75 mm) are majorly left untreated; however, small vessel coronary artery disease (SvCAD) is a significant risk factor for recurrence of MACE, and there are some limitations to the use of CAG that could be improved with the use of newer techniques such as intravascular ultrasound (IVUS), although at higher costs, which might explain their underuse. To address this discrepancy and identify specific cases for its use, we conducted a retrospective study in patients who underwent PCI for MACE with at least one small blood vessel affected. The affected small blood vessels’ diameter was obtained with both CAG and IVUS, additionally we underwent a multivariate analysis to identify risk factors associated with a change in diameter. We included information from 48 patients with mean + SD age of 69.1 + 11.9 years and 34% were masculine gender. We found a significant positive low correlation in diameter measurements of small blood vessels (r=0.1242 p=0.014). Mean diameter with CAG and IVUS was 2.1 mm (95% CI 1.9-2.2), and 2.8 (2.8-3.0) the estimated difference was of 0.8 mm (95 % CI 0.7-0.9). In total 37 (77%) of patients had a reclassification of their blood vessels from a small to medium (2.75-3.00 mm) in 21 cases, or even large (&lt;3.00 mm) in 15 cases, after IVUS; this was important for the decision of intervention and stent collocation. The only variable associated with reclassification of blood vessels after adjusted in a multivariate analysis was DT2 (p=0 0.035). Our findings corroborate that blood vessels might appear smaller with CAG, especially in the diabetes population, therefore at least in these cases the use of IVUS is recommended over CAG.

Although Cucurbita pepo is one of the most variable species of the plant kingdom, Zucchini morphotype has undergone intensive breeding that has led to a narrow genetic base making the crop vulnerable to pest and diseases. This vulnerability makes the knowledge of resistance genes of utmost importance. In this study, a data mining search of Zucchini summer squash genome database was conducted to identify and annotate members of the NBS-encoding gene family. In order to characterize the retrieved genes in detail, they have been studied in the bases of phylogenetic relationships, structural diversity, conserved protein motifs, gene duplications and promoter region analysis. Our study shows that the NBS-encoding gene family is relatively small in Zucchini (34 members, which are separated into non-TIR- and TIR-NBS-LRR subfamilies) with a significantly lower number of R-genes than in other species. Duplications have not played a major role in the expansion of this type of genes in C. pepo. Among the cis-regulatory elements presented in these sequences, six motifs are over-represented. These elements were reported to be involved in pathogens or plant stress induced responses. These results will contribute to the identification, isolation and characterization of candidate R-genes, thereby providing insight into NBS gene family evolution in the species.

For a given set of plasma parameters, along a single series (Lyman, Balmer etc) the lines with higher principal quantum number(n) lines get progressively wider, closer to each other, and start merging for a certain critical n. In the present work four different codes(with further options) are used to calculate the entire Balmer series for moderate and high electron densities. Particular attention is paid to the relevant physics, such as the cutoff criteria, strong and penetrating electron collisions.

Successful translation of biofortified orange maize (BOM) to a household staple food is dependent on farmers’ ability to cultivate the maize and it subsequent utilization. In this study, we assessed farmers ‘allocation of their land to cultivation of BOM and con-ventional white maize (CWM) varieties in districts where AFI-KEPO Nutrition Program is implemented in Malawi. Results show farmers were skeptical of allocating more land to cultivation of BOM. CWM was allocated significantly more land (1.75 ± 0.51 acres) than BOM (1.12 ± 0.32 acres) (p

The classification of tumors in subtypes, characterized by phenotypes determined by specific differentiation pathways, aids diagnosis and directs therapy towards targeted approaches. However, with the advent and explosion of next-generation sequencing, cancer phenotypes are turning out to be far more heterogenous than initially thought, and the classification is continually being updated to include more subtypes. Tumors are indeed highly dynamic and they can evolve and undergo various changes in their characteristics during disease progression. The picture becomes even more complex when tumor responds to a therapy. In all these cases, cancer cells acquire the ability to trans-differentiate, changing subtype, and adapt to changing microenvironments. These modifications affect the tumor's growth rate, invasiveness, response to treatment, and overall clinical behavior. Studying tumor subtype transitions is crucial for understanding tumor evolution, predicting disease outcomes, and developing personalized treatment strategies. We discuss this emerging hallmark of cancer and the molecular mechanisms involved at the crossroads between tumor cells and their microenvironment, focusing on four different human cancers in which tissue plasticity causes a subtype switch: breast cancer, prostate cancer, glioblastoma and pancreatic adenocarcinoma.

Magnetic ceramic nanoparticles system xTm2O3-(1-x)alpha-Fe2O3 (x=0.1 and 0.5) was synthesized by mechanochemical activation starting from hematite and thulium oxide precursors and characterized by transmission Mӧssbauer spectroscopy. The Mӧssbauer spectra were typically analyzed considering 1-3 sextets, corresponding to hematite (with and without thulium doping) and a doublet, representing thulium iron perovskite (thulium orthoferrite). The magnetic hyperfine fields (BHF) and doublet abundance were studied as function of the ball milling time (BMT) for both molar concentrations employed. The results are consistent with the formation of solid solutions in the investigated system. The mixed-oxide nanoparticle system synthesized may have important applications in displays, sensors and photovoltaics, and is paving the way for emerging utilizations related to mechanically flexible electronics.

Public transport systems are considered to be a crucial aspect of a sustainable urban development, as they allow more passengers to efficiently travel across an urban area at low environmental and economic costs. Multiple factors can influence the public transport level of service. All take roots in the network structure and the operating regime, i.e. how bus lines are arranged atop the street network and how the service frequency is adjusted to meet urban mobility patterns. This is known as the bus network design problem and has been the subject of several studies. The problem is so challenging that most studies until now resort to strong assumptions such as a static description of the peak hour demand, homogeneous user behavior, and equal trip lengths. Potential effects of different types of user behavior and trip lengths patterns on the user and/or operator cost function have not been investigated whatsoever. Moreover, the existing studies have not considered the effects of the bus network structure on private car users, the level of interactions between the two modes, and the passenger mode choice that depends on the traffic conditions. This paper aims to close this gap and provide a general framework considering multiple trip length patterns, two types of user behavior, and the effects that the bus network structure might have on the traffic performance and passenger mode choice. For modeling different trip length patterns, the proposed approach combines all origin-destination pairs with the same trip length and uses the trip length distribution as an intermediate level of abstraction. As such, it allows to solve the optimal bus network design problem in an analytical way, while considering a more realistic setting including network congestion, mixed traffic, and different mode choice decisions depending on trip lengths and walking preferences. Numerical analysis reveals that both, the user behavior and the trip length patterns, have significant effects on the operator and user cost function. Results show that the probability of choosing any given mode is not constant across the user trip lengths, but follows certain distribution. This distribution is not unique, but varies across the trip length patterns, indicating the importance of modeling the mode choice at the trip length level. Finally, the analysis demonstrates the significance of addressing simplifications made in previous studies.

Over the last 20 years, begomoviruses have emerged as devastating pathogens, limiting the production of different crops worldwide. Weather conditions increase vector populations, with negative effects on crop production. In this work we evaluated the relationship between the in-cidence of begomovirus and climatic conditions before and during the crop cycle. Soybean and bean fields from the northwest (NW) of Argentina were monitored for 14 years and classified as moderate (≤50%) and severe (> 50%) according to the relative incidence. Two hundred bio-meteorological variables were constructed, summarizing meteorological data in 10-day peri-ods from June to March of each crop year. The studied variables included temperature, precipi-tation, relative humidity, wind (speed and direction), pressure, cloudiness and visibility. For bean, high maximum winter temperatures, low spring humidity and precipitation 10 days before planting correlated with severe incidence. In soybeans, high late winter and pre-planting tem-peratures, and low spring precipitations were found to be good predictors of high incidence of begomovirus presence. The results suggest that temperature and pre-sowing precipitations can be used to predict incidence status [predictive accuracy: 82% (bean) and 75% (soybean)]. Thus, these variables can be incorporated in early warning systems for crop management deci-sion-making to reduce the virus impact on bean and soybean crops.

The 2022-2023 influenza season in Romania was characterized by high pediatric hospitalization rates, predominated by influenza A subtypes H1N1 and H3N2. Lowered population immunity to influenza after the SARS-CoV-2 pandemic and subsequent stoppage of influenza circulation, particularly in children who had limited pre-pandemic exposures, influenced hospitalization among children immunosuppressed, and patients with concurrent medical conditions who are at increased risk for developing severe forms of influenza. This study focused on the characteristics of influenza issues among paediatric patients, as well as the relationship between different influenza virus types and viral and bacterial coinfections and illness severity in the 2022-2023 season after the SARS-CoV-2 pandemic. We conducted a retrospective clinical analysis on 301 cases of influenza in pediatric inpatients (age ≤ 18 years), hospitalized at the National Institute of Infectious Diseases "Prof. Dr. Matei Balș" IX Pediatric Infectious Diseases Clinical Section between October 2022 and February 2023. The most significant age group was 57.8% representing children between one to four years old and female. The average clinical forms were found in 61.7%, whereas severe versions represented 18.2% of cases. Most of the complications were respiratory (acute interstitial pneumonia, 76.1%), hematological (72.1%), represented by intra-infectious and deficiency anemia, leukopenia, thrombocytopenia), 33.6% were digestive, such as diarrheal disease, liver cytolysis syndrome, and the acute dehydration syndrome associated with electrolyte imbalance (71.4%). Severe complications were associated with a risk of unfavorable evolution: acute respiratory failure and neurological complications (convulsions, encephalitis). No deaths were reported. We noticed that the flu season 2022-2023 was characterized by the association of co-infections (viral, bacterial, fungal and parasitic) more frequent than in previous years (26.2% vs. 16%), which evolved more severely, with prolonged hospitalization and more complications (p<0.05), and time of use of oxygen therapy was statistically significant (p > 0.05); influenza vaccination in this group was zero. In conclusion, coinfections with respiratory viruses increase the severity of the pediatric population's immunity to influenza, especially among young children who are more vulnerable to developing a serious illness. All people above the age of six months should get vaccinated against influenza to prevent the illness and its severe complications.

Background: Risk of metastatic recurrence of breast cancer after initial diagnosis and treatment depends on the presence of a number of risk factors. Although most univariate risk factors have been identified using classical methods, machine-learning methods are also being conducted to tease out non-obvious contributors to a patient’s individual risk of developing late distant metastasis. Bayesian-network algorithms may predict not only risk factors but also interactions among these risks, which consequently lead to metastatic breast cancer. We proposed to apply a previously developed machine-learning method to predict risk factors of 5-, 10- and 15-year metastasis. Methods: We applied a previously validated algorithm named the Markov Blanket and Interactive risk factor Learner (MBIL) on the electronic health record (EHR)-based Lynn Sage database (LSDB) from the Lynn Sage Comprehensive Breast Cancer at Northwestern Memorial Hospital. This algorithm provided an output of both single and interactive risk factors of 5-, 10-, and 15-year metastasis from LSDB. We individually examined and interpreted the clinical relevance of these interactions based on years to metastasis and the reliance on interactivity between risk factors. Results: We found that with lower alpha values (low interactivity score), the prevalence of variables with an independent influence on long term metastasis was higher (i.e., HER2, TNEG). As the value of alpha increased to 480, stronger interactions were needed to define clusters of factors that increased the risk of metastasis (i.e., ER, smoking, race, alcohol usage). Conclusion: MBIL identified single and interacting risk factors of metastatic breast cancer, many of which were supported by clinical evidence. These results strongly recommend the development of further large data studies with different databases to validate the degree to which some of these variables impact metastatic breast cancer in the long term.

We show how the excitonic features of biaxial MoS₂ flakes are very sensitive to biaxial strain. We find a lower bound for the gauge factors of the A exciton and B exciton of (-41 ± 2) meV/% and (-45 ± 2) meV/% respectively, which are larger than those found for single-layer MoS₂. Interestingly, the interlayer exciton feature also shifts upon biaxial strain but with a gauge factor that is systematically larger than that found for the A exciton, (-48 ± 4) meV/%. We attribute this larger gauge factor for the interlayer exciton to the strain tunable van der Waals interaction due to the Poisson effect (the interlayer distance changes upon biaxial strain).

Developments in technology have enabled envisioning the derivation of materials and products from renewable biomass, as an alternative to finite fossil-based resource consumption. Therefore, bioeconomy is regarded as an opportunity for sustainable economic growth. Countries are formulating strategies in accordance with their goals to attain from bioeconomy. Proper measurement, monitoring and reporting of the outcomes of these strategies is crucial for long-term success. This study aims to critically evaluate the national methods used for the measurement, monitoring and reporting of bioeconomy contribution to the total economy. For this purpose, research and surveys have been conducted on selected countries (Argentina, Germany, Malaysia, the Netherlands, South Africa and the United States). The results reveal that the bioeconomy targets set up in the strategies often reflect country’s priorities and comparative advantages. However, comprehensive approaches to measure and monitor bioeconomy progress are frequently lacking. Most countries only measure the contribution to gross domestic product (GDP), turnover and employment of the sectors included in their bioeconomy definition, which may provide an incomplete picture. In addition, this study identifies the mismatch between the targets and measurement methods, as the environmental and social impacts of bioeconomy are often foreseen, but not measured. It is concluded that existing global efforts towards a sustainable bioeconomy monitoring can be strengthened and leveraged to measure progress towards sustainable goals.

Atomic structure of N-electron atoms is often determined using the Hartree-Fock method, which is an integro-differential equation. The exchange term of the Hartree-Fock equations is usually treated as an inhomogeneous term of a differential equation, or with a local density approximation. This work uses matrix methods to solve for the Hartree-Fock equations, rather than the more commonly-used shooting method to integrate an inhomogeneous differential equation. It is well known that a derivative operator can be expressed as a matrix made of finite-difference coefficients; energy eigenvalues and eigenvectors can be obtained by using computer linear-algebra packages. We extend the same technique to integro-differential equations, where a discretized integral can be written as a sum in matrix form. This method is compared against experiment and standard atomic structure calculations. We also can use this method for free-electron wavefunctions. This technique is important for spectral line broadening in two ways: improving the atomic structure calculations, and improving the motion of the plasma electrons that collide with the atom.

Yogyakarta City is one of the big city which is located in Java Island, Indonesia. Yogyakarta City, including study area (Pleret Sub District), are very prone to earthquake hazards, because close to several active earthquake sources. For example, Sunda Megathrust which often generates a big earthquake which can affect the study area. The Sunda Megathrust extends from north to south and west to east along the Sumatra and Java Islands. Furthermore, an active normal fault called as Opak Fault pass through right in the middle of Study area and divides the study area into east and west zone. Recently, after the devastating earthquake in 2006, the population of the study area increases significantly. As a result, the housing demand is also increasing. However, due to the absence of earthquake building code in the study area, locals tend to build improper new houses. Furthermore, in some part of the mountainous area in the study area, there are some building found in unstable slopes area. Due to this condition, the multi-hazard and risk study needs to be done in Pleret. The increasing of population and improper houses in Pleret Sub-District can lead to amplify the impact. Thus, the main objective of this study is to assess the multi-hazards and risk of earthquake and other related secondary hazards such as ground amplification, liquefaction, and coseismic landslide. The method mainly utilised the geographic information system, remote sensing and was fit up by the outcrop study. The results show that the middle part of the study area has a complex geological structure. It was indicated by a lot of unchartered faults was found in the outcrops. Furthermore, the relatively prone areas to earthquake can be determined. In term of the coseismic landslide, the prone area to the coseismic landslide is located in the east part of the study area in the middle slope of Baturagung Escarpment. The highly potential area of liquefaction is dominated in the central part of the study area. In term of building collapsed probability, the result shows that the safest house based on statistical analysis is the residential house with the building attribute of wood structure, roof cast material, distance more than 15 km from the earthquake source, and located above the Nglanggran Formation. Finally, the multi-hazard and risk analysis show that the middle part of the study area is more vulnerable than the other part of Pleret Sub-District.

Background: The clinical outcomes of antiretroviral drugs may be modified by drug interactions; thus, it is important to update the drug interactions in people living with HIV. Aim: To update clinically relevant drug interactions in people living with HIV on antiretroviral therapy. Methods: A systematic review in Medline/PubMed database from July 2017 to December 2022, using the Mesh terms: Anti-retroviral agents and drug interactions or herb-drug interactions or food-drug interactions. Publications with drug interactions in humans, in English or Spanish, and with full text were retrieved. The clinical relevance of drug interaction was grouped into 5 levels according to gravity and probability of occurrence. Results: 361 articles were identified and 148 were included, which allowed the identification of 894 drug interaction pairs. Among these 894 drug pairs, 355 have not been identified previously; and 89 (25.1%) and 72 (20.2%) were of levels 1 and 2, respectively. In addition, for 197 (55.5%) pairs the mechanism was pharmacokinetic. The non-nucleoside reverse transcriptase inhibitors (NNRTIs) and the protease inhibitors (PIs) with 91 (25.6%) and 76 (21.4%) pairs, respectively were more frequent. Conclusions: In people living with HIV on antiretroviral therapy, we identify 355 new drug interaction pairs, of them 161 (45.3%) are assessed as levels 1 and 2 and thus, clinically relevant; a figure that is lower compared to 2014-2107 update. The pharmacokinetic mechanism is the most frequently identified. The non-nucleoside reverse transcriptase inhibitors (NNRTIs) and the protease inhibitors (PIs) are the antiretroviral groups with the highest number of clinically relevant drug interactions.

The quality of life (QOL) is an important indicator of human satisfaction and wellbeing. QOL is significantly and persistently affected for patients after a cancer diagnosis. Despite some evidence suggesting that psycho-oncologic interventions can provide lasting benefits, the inclusion of such interventions in cancer therapy is not universal. This article overviews known approaches to the evaluation of QOL in cancer patients and various interventions for improving patients’ outcomes with a focus on the Eastern European regional and specific Romanian context. With a mortality rate above and cancer care performance below the EU average and unequally distributed, Roma-nia urgently needs a national coordination program which is discussed in our review highlighting the main psychological tools needed for the assessment and its challenges towards implementing the program. In the end, we suggest some directions for future development of the psycho-oncologic approach in the context of social, policy and unexpected financial challenges the nation provides

Demographic and socio-economic developments couple with other requirements to satisfy human needs result in rapid urban expansion sometimes with increasing rate of surface extent greater than the rate of growth of population, that result in continuous sealing of ground surface thereby affecting ecosystem services. This study applied remote sensing toward achieving the progress of SDGs and stage to determine the ratio of the rate of land consumption to the rate of population growth of Gombe metropolis. QGIS 2.18 was used for the image processing and classification analysis for the key Landsat ETM+ (Enhanced Thematic Mapper), Impervious Surface Indices and population data to inform on the urban trend and LCR/PGR for the periods 2000-2005, 2005-2010, and 2010-2015. The result appears that the LCR/PGR for the periods of study show split trends. During 2000-2005 the result shows that the study area expanded outward with LCR/PGR of 1.2. The result also indicate that during 2005-2010, the study area densified with little expansion with the LCR/PGR of 0.8. The result further reveals that during 2010-2015 the LCR/PGR reached 1.8. Pointing that the study area expanded outward with the rate of ground sealing getting high.

Diatom microalgae are the most outstanding natural source of porous silica. Diatom cell is enclosed in 3-D ordered nanopatterned silica cell wall, called frustule. The unique properties of diatoms frustule, including high specific surface area, thermal stability, biocompatibility, tailorable surface chemistry, make them really promising for biomedical applications. Moreover, diatoms are easy to cultivate in artificial environment and there is a huge availability of diatom frustules as fossil material (diatomite) in several areas of the world. For all these reasons, diatoms are an intriguing alternative to synthetic materials for the development of low-cost drug delivery systems. This review article focuses on the possible use of diatoms derived silica as drug carrier systems. The functionalization strategies of diatom micro-/nanoparticles for improving their biophysical properties, such as cellular internalization and drug loading/release kinetics, are described. In addition, the realization of hybrid diatom-based devices with advanced properties for theranostics and targeted or augmented drug delivery applications, are also discussed.

This study focuses on predicting PM2.5 levels at the University of Petroșani by employing advanced machine learning techniques to analyze a dataset that encapsulates a wide array of air pollutants and meteorological factors. Utilizing data from IoT sensors and established environmental monitoring stations, the research leverages Random Forest, Gradient Boosting Machines, and Support Vector Regression models to forecast air quality, emphasizing the complex interplay between various pollutants. The models demonstrate varying degrees of accuracy, with the Random Forest model achieving the highest predictive power, indicated by an R2 score of 0.82764. Our findings highlight the significant impact of specific pollutants such as NO, NO2, and CO on PM2.5 levels, suggesting targeted mitigation strategies could enhance local air quality. Additionally, the study explores the role of temporal dynamics in pollution trends, employing time-series analysis to further refine the predictive accuracy. This research contributes to the field of environmental science by providing a nuanced understanding of air quality fluctuations in a university setting and offering a replicable model for similar environments seeking to reduce airborne pollutants and protect public health.

Seed viability is routinely measured on seeds that fail to germinate at the end of an experiment. Together with the number of germinants, this is used to estimate viability of the seeds at start of the experiment (i.e., initial viability) and provides the comparative basis on which germination success is determined. We used this standard procedure on 40 Leucadendron species subjected to oscillating temperatures, heat and/or smoke pre-treatments to examine the extent to which they raised germination levels above that of the untreated controls. 16 species showed significantly different levels of estimated initial seed viability between treatments when they should have been unaffected. Loss of viability during the trial was an order of magnitude greater than annual loss during cold storage, which was usually negligible. Lowest levels of estimated initial viability occurred among the poorly germinating controls and confirmed that the heat and smoke treatments had little effect on viability. Species with soil-stored seeds were more vulnerable to this artefact than those with plant-stored seeds. We caution against the routine use of end-of-trial germination and viability of ungerminated seeds as an estimate of initial viability in determining germination success of various treatments. The preference is for estimates of initial viability to be undertaken on a separate sample of seeds in association with the trial.

Arthrospira platensis, commercially known as Spirulina, is a fresh-water cyanobacterium that is gaining even more attention in the last years due to its high biological and nutritional value. For this reason, it has been employed in several food applications, to obtain or enhance functional and technological properties of cheese, yogurt, bread, cookies or pasta. The aim of this work was to evaluate the potential boosting effect of two different concentrations (0.25% and 0.50%) of Arthrospira platensis on the fermentation capability of several starter LAB strains, 1 probiotic and 4 commercial mix culture. These strains were used to ferment three different substrates and their fermentation behaviors were evaluated by impedance analyses together with rheological and color measurements. It was demonstrated that the booster effect took place, but it was variable and dependent not only on the strain or mix culture used, but also on the substrate and Arthrospira platensis concentration. Also, rheological and color modifications were found to be dependent of these factors.

The link between the world of communication and the world of racing is provided by telemetry systems in electric racing cars. These systems send real-time data about the vehicle’s behavior and systems to enable informed decisions during the race. The aim of this research was to integrate telemetry into the battery bank of a racing electric vehicle to find the optimal values of current and voltage that optimize the charging process, thus improving the vehicle’s performance in competition using Response Surface Analysis. Particularly, the telemetry system consisted of an Arduino Mega, a digital wattmeter, and temperature sensors, all installed in the vehicle. Once the telemetry data was obtained, a response surface design was adapted with current, voltage, and temperature as factors, varying from low to high values, with the objective function being to minimize the battery’s charging time. Applying the response surface methodology and the steepest descent algorithm, it was found that all factors significantly affect the charging time, with the minimum charge time being 6961 seconds, obtained with a current of 2.4 amps and voltages of 50.5 volts and 43.6 volts.

Since the beginning of the 21st century, Romanian migrants have become one of the most significant national groups doing agricultural work in Spain, initially coming via a temporary migration program and later under several different modalities. However, despite their critical importance for the functioning of Europe’s largest agro-industry, the study of this long-term circular mobility is still underdeveloped in migration and agriculture literature. Thanks to extensive fieldwork carried out in the provinces of Huelva and Lleida in Spain and in the counties of Teleorman and Buzău in Romania, this paper has two main objectives: first, to identify some of the most common forms of mobility of these migrants and second, to discuss whether this industrial agriculture, hugely dependent on migrant work, is socially sustainable. The case of Romanian migrants in Spanish agriculture will serve to show how a critical sector for the EU and for the 2030 Agenda for Sustainable Development of the United Nations, operates on an unsustainable model based on precariousness and exploitation.

Speleothem oxygen isotope records from the Caribbean, Central, and North America reveal climatic controls that include orbital variation, deglacial forcing related to ocean circulation and ice sheet retreat, and the influence of local and remote sea surface temperature variations. Here, we review these records and the global climate teleconnections they suggest following the recent publication of the Speleothem Isotopes Synthesis and Analysis (SISAL) database. We find that low-latitude records generally reflect changes in precipitation, whereas higher latitude records are sensitive to temperature and moisture source variability. Tropical records suggest precipitation variability is forced by orbital precession and North Atlantic Ocean circulation driven changes in atmospheric convection on long timescales, and tropical sea surface temperature variations on short timescales. On millennial timescales, precipitation seasonality in southwestern North America is related to North Atlantic climate variability. Great Basin speleothem records are closely linked with changes in Northern Hemisphere summer insolation. Although speleothems have revealed these critical global climate teleconnections, the paucity of continuous records precludes our ability to investigate climate drivers from the whole of Central and North America for the Pleistocene through modern. This underscores the need to improve spatial and temporal coverage of speleothem records across this climatically variable region.

Abstract: Canine ehrlichiosis is a zoonotic disease transmitted by ticks, posing a formidable challenge to both veterinary and public health sectors worldwide. Across continents and regions, the prevalence rates of Ehrlichia canis exhibit significant variation, underlining the necessity for a nuanced and globally informed approach to understanding and combating this disease. The review navigates through this complexity, shedding light on the intricate pathogenesis of the illness. Central to this understanding is the bacterium's adept manipulation of the host's immune response, contributing to the diverse clinical manifestations observed in infected animals. Diagnostic methodologies, crucial for timely intervention and management, are subjected to critical assessment. From traditional microscopy to modern molecular techniques and serology, each approach is scrutinized for its strengths and limitations. By acknowledging these nuances, the review aims to equip practitioners with the knowledge necessary to make informed diagnostic decisions. A central tenet of this review is the advocacy for an integrated "One Health" approach. By leveraging advancements in genomics, proteomics, and artificial intelligence, there is a potential to enhance diagnostic accuracy and develop innovative therapeutic and preventive strategies globally. This collaborative approach recognizes the interconnectedness of human, animal, and environmental health, offering a holistic framework for tackling complex zoonotic diseases like canine ehrlichiosis. In conclusion, this review serves as a beacon of knowledge, illuminating the multifaceted landscape of canine ehrlichiosis. Through its synthesis of scientific literature and emphasis on methodological rigor, it provides a foundation upon which future research and interventions can be built. With a unified commitment to "One Health" principles and the integration of cutting-edge technologies, there exists the potential to mitigate the impact of this disease and safeguard both animal and human well-being worldwide

Background: Chronic kidney disease (CKD) is a significant cardiovascular (CV) risk factor, with dialysis-dependent CKD (DD-CKD) patients facing high mortality rates. Hypercholesterolemia is another crucial CV risk factor, typically managed with lipid-lowering therapy, though its efficacy in DD-CKD remains uncertain. Evidence shows mixed results regarding the benefits of statins in these patients. Citrate-based dialysates are known to reduce inflammatory biomarkers compared to acetate-based ones, potentially impacting lipid profiles and immune responses. This study aimed to determine the effects of citrate versus acetate dialysate on lipid profiles and immunophenotypes in DD-CKD patients. Methods: This unicentric, cross-over, prospective study included 21 hemodialysis patients (10 males, 11 females, average age 62.25 years). Each patient underwent 24 dialysis sessions (12 with each dialysate) and acted as their own control. Lipid profiles, immunological parameters, and nutritional and inflammatory markers were measured before the last session with each dialysate. Results: Compared to acetate dialysate (AD), citrate dialysate (CD) resulted in significantly higher LDL (75.71 vs. 67.05 mg/dL, p=0.042) and HDL (51.19 vs. 47.14 mg/dL, p=0.013), and lower TG (97.86 vs. 110.38 mg/dL, p=0.046). CD also led to higher NK cells (19.24 vs. 16.95%, p=0.035), higher complement C3 levels (115.14 vs. 107.81 mg/dL, p=0.009) and lower CD3+ CD8+ and CD16+56+ lymphocytes. Finally, total lymphocytes were lower with AD than with CD. We found no difference in predialysis nutritional nor inflammatory parameters (IL-6 and hs-CRP) except for ESR, which was higher when subjects used CD than AD. Conclusion: There are significant differences in lipid and immunophenotypic profiles that should increase the CV risk of patients who use CD. However, numerous studies have shown no differences, or even a benefit in mortality in certain HD subpopulations that use CD. Further studies are needed to understand if the observed changes may be counterbalanced by other mechanisms potentially provided by citrate (e.g., reducing vascular calcification).

Nasal high-frequency oscillatory ventilation (nHFOV) has emerged as an effective initial and rescue noninvasive respiratory support mode for preterm infants with respiratory distress syndrome (RDS). Multiple noninvasive respiratory support modes are currently available in Romania, but little is known about nHFOV use in Romanian neonatal intensive care units (NICUs). We aimed to identify the usage extent and clinical application of nHFOV in Romania. A structured web-based questionnaire was designed to find the rate of nHFOV use and knowledge of this new method of noninvasive respiratory support in Romanian level III NICUs. The questionnaire was addressed to the leaders of all level III Romanian NICUs. Using multiple-choice, open-ended, and yes/no questions, we collected information on the NICU’s size, noninvasive respiratory support modes used, nHFOV use, indications, settings, nasal interfaces, secondary effects, and equipment used. Descriptive statistics and comparisons were performed using IBM SPSS Statistics 26.0. A total of 21/23 (91.3%) leaders from level III NICUs (median [IQR] number of beds of 10 [10-17.5]) responded to the survey. The most frequently used noninvasive ventilation modes were CPAP mode on mechanical ventilators (76.2%), followed by NIPPV (76.2%), heated, humidified high flow nasal cannula (HHHFNC) (61.9%), and nHFOV (11/21 units; 52.4%); 5/11 units reported frequent nHFOV use (in 2 or more newborns/month) in both term and preterm infants. The main indications reported for nHFOV use were CPAP failure (90.9%), hypercapnia (81.8%), and bronchopulmonary dysplasia (72.7%). 10/11 units reported setting a mean airway pressure (MAP) equal to the CPAP level plus 1-2 cmH₂O on rescue nHFOV after CPAP failure. Both dedicated equipment (45.5%) and hybrid ventilators (63.6%) were used for nHFOV delivery, with face/nasal masks and short binasal prongs being the most commonly used nasal interfaces (90.9% and 72.7%, respectively). Air leaks at the interface level (90.9%), thick secretions (81.8%), and airway obstruction (63.6%) were the most frequently mentioned adverse effects of nHFOV; none of the units mentioned pneumothorax as an adverse effect. Only 3 of the NICUs had a written protocol for nHFOV use. Initial, minimum, and maximum amplitude and initial and minimum MAP settings used were significantly higher with hybrid ventilators as compared to dedicated equipment (p<0.05). Most units not yet using nHFOV cited lack of equipment, experience, training, or insufficient information and evidence for the clinical use and outcome of nHFOV use in neonates as the main reasons for not implementing this noninvasive respiratory mode. Our survey showed that nHFOV is already used in more than half of the Romanian level III NICUs to support term and preterm infants with respiratory distress despite a lack of consensus regarding indications and settings during nHFOV. A need for training for nHFOV use was identified, and efforts are needed at the national level to develop courses and training sessions, including using simulation workshops, to offer more information on optimal nHFOV use in clinical practice.

Being overweight or obese is a public health problem. This work evaluated a food and nutrition education (EAN) intervention against overweight schoolchildren in four schools in the West Panama Province. A quasi-experimental before-and-after study that implemented a 34-week EAN intervention through workshops with didactic material to 403 children between 8 and 13 years old. The knowledge and attitude survey was used as an evaluation tool before and after the educational intervention. The prevalence of excess weight (40%) did not report differences after the intervention. No differences were reported in the median level of attitude, although higher levels of knowledge were reported in students of both sexes. EAN in schoolchildren can be effective in acquiring knowledge and maintaining a positive attitude towards food.

Coronaviruses are an extensive family of viruses that can cause disease in both animals and humans. The current classification of coronaviruses recognizes 39 species in 27 subgenera that belong to the family Coronaviridae. From those, at least seven coronaviruses are known to cause respiratory infections in humans. Four of these viruses can cause common cold-like symptoms, while others that infect animals can evolve and become infectious to humans. Three recent examples of this viral jumps include SARS CoV, MERS-CoV and SARS CoV-2 virus. They are responsible for causing severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and the most recently discovered coronavirus disease during 2019 (COVID-19).COVID-19, a respiratory disease caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organization (WHO) on 11 March 2020. The rapid spread of the disease has taken the scientific and medical community by surprise. Latest figures from 14 April 2020 show more than 2 million people had been infected with the virus, causing more than 120,000 deaths in over 210 countries worldwide. The large amount of information we receive every day concerning this new disease is so abundant and dynamic that medical staff, health authorities, academics and the media are not able to keep up with this new pandemic. In order to offer a clear insight of the extensive literature available, we have conducted a comprehensive literature review of the SARS CoV-2 Virus and the Coronavirus Diseases 2019 (COVID-19).

The building sector is the largest consumer of energy and there are still major scientific challenges in this field. The façade, being the interface between the exterior and interior space, plays a key role in the energy efficiency of a building. In this context, this paper focuses on a ventilated bioclimatic wall for NZEB zero energy buildings. The objective of this study is to investigate an experimental set-up based on a Hot Box allowing characterizing the thermal performances of the ventilated wall. A specific ventilated prototype and an original thermal metrology has been developed. This paper presents the ventilated prototype, the experimental set-up and experimental results on the thermal performances of the ventilated wall. The influence of the air space thickness and the air flow rate on the thermal performances of the ventilated wall is studied.

HD-Zip proteins are unique to plants, and contain a homeodomain closely linked to a leucine zipper motif, which are involved in dimerization and DNA binding. Based on homology in the HD-Zip domain, gene structure and the presence of additional motifs, HD-Zips are divided into four families, HD-Zip I–IV. Phylogenetic and bioinformatics analysis of HD-Zip genes using transcriptomic and genomic datasets from a wide range of plant species indicate that the HD-Zip protein class was already present in green algae. Later, HD-Zips experienced multiple duplication events that promoted neo- and sub-functionalizations. HD-Zip proteins are known to control key developmental and environmental responses, and a growing body of evidence indicates a strict link between members of the HD-Zip II and III families and the auxin machineries. Interactions of HD-Zip proteins with other hormones such as brassinolide and cytokinin have also been described. However, it is striking that among the genes regulated by REV, a HD-Zip III protein playing a key role in apical development, are genes that mediate ABA signaling. Furthermore, HAT1 and HAT3, two HD-Zip II proteins involved in key developmental processes, repress ABA biosynthesis and signaling, indicating an essential role of these factors in adjusting development to changing environment.