Malaria remains a life-threatening disease in many tropical countries. Honduras has successfully reduced malaria transmission as different control methods have been applied focusing mainly on indoor mosquitoes. The selective pressure exerted by the use of insecticides inside the households could modify the feeding behavior of the mosquitoes forcing them to search for available animal hosts outside the houses. These animal hosts in the peridomicile could consequently become an important factor in maintaining vector populations in endemic areas. Herein, we investigated the blood meal sources and Plasmodium spp. infection on anophelines collected outdoors in endemic areas of Honduras. Individual PCR reactions with species-specific primers were used to detect five feeding sources on 181 visibly engorged mosquitoes. In addition, a subset of these mosquitoes where chosen for pathogen analysis by a nested PCR approach. Most mosquitoes fed on multiple hosts (2 to 4), and 24.9% of mosquitoes were fed on a single host, animal or human. Chicken and bovine were the most frequent blood meal sources (29.5% and 27.5% respectively). The average human blood index (HBI) was 22.1%. None of the mosquitoes was found to be infected with Plasmodium spp. Our results show the opportunistic and zoophilic behavior of Anopheles mosquitoes in Honduras.

This short paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of multi-asset financial derivatives. The multivariate models are built to ensure two conditions, first, marginals follow desirable processes, e.g. we choose the Geometric Brownian Motion (GBM), popular for stock prices. Second, the payoff of the derivative should follow a desired one dimensional process. These conditions lead to a specific choice of the dependence structure, in the form of a local-correlation model. Two popular multi-asset options are entertained, a spread option and a basket option.

In this work, optimal consumption and investment strategies are derived for risk-averse investors under the 4/2 stochastic volatility class of models. We work under an expected utility (EUT) framework and consider a Constant Relative Risk Aversion (CRRA) investor, who might also be ambiguity-averse. The corresponding Hamilton-Jacobi-Bellman (HJB) and HJB-Isaacs (HJBI) equations are solved in closed-form for a subset of the parametric space and under some restrictions on the portfolio setting, for complete markets. Conditions for proper changes of measure and well defined solutions are provided. These are the first analytical solutions for the 4/2 stochastic volatility model and the embedded 3/2 model for the type of excess returns established in .

We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

The state of knowledge of properties of the Andromeda Galaxy (also known as M31) is reviewed. The spatial structure of the Andromeda Galaxy, its main source populations and the properties of its gas and dust are discussed. To understand the formation history of the Andromeda Galaxy, the critical issues of its star formation history and the gas streams and dwarf galaxies in its surrounding environment are reviewed. Emphasis is on recent studies with important earlier work described in the references provided here. It is important to understand the Andromeda Galaxy because it is the nearest large external galaxy and is close enough for high resolution studies. This allows the Andromeda Galaxy to be used as a template to understand more distant and less resolved galaxies in the universe.

The purpose of this article is to analyze, in a three-stage research, the relationships between environmental expenses, the improvements achieved in 5 environmental variables analyzed and efficiency, from an economic and operational perspective. The stages of this research are analyzing the sustainability reports to determine the level of information, analyzing the economic and operational efficiency, and analyzing the alignment with the environmental priorities of the Eco Ports-ESPO (European Sea Ports Organization). The results reveal that (1) the type of traffic does not condition environmental actions; (2) environmental performance (improvements) depends on environmental expenditures; (3) environmental spending and efficiency in port operations are correlated; and (4) environmental spending and port economic efficiency are correlated.

This study presents an in-depth analysis of land use and land cover change on the Kerch Peninsula over a period spanning three decades. Utilizing convolutional neural networks alongside satellite imagery analysis, we have mapped and quantified the changes in land use and cover, revealing significant trends and transformations within the peninsula's landscape. The research aims to elucidate the interplay between anthropogenic activities, climatic variations, and policy interventions in shaping land cover dynamics, thereby providing insights into the environmental and socio-economic impacts of these changes. Our findings indicate a marked increase in urban expansion at the expense of natural ecosystems, including forests and wetlands, underscoring the urgent need for sustainable land management strategies. The study highlights the role of agricultural intensification and expansion in altering the peninsula's ecological balance and emphasizes the critical importance of integrating change analysis and prediction. By leveraging advanced remote sensing and GIS technologies, our analysis not only enhances the understanding of the complex dynamics driving land use and land cover change but also showcases the potential of predictive modeling in forecasting future land cover scenarios. The implications of this study extend beyond the Kerch Peninsula, offering valuable lessons for managing land use changes and conserving natural landscapes in similar regions globally.

Currently, companies and SMEs (small and medium enterprises) are looking to be more competitive. In order to achieve this, they are adopting new business models and strategies that allow them to move towards sustainability. Strategies such as CSR (Corporate social responsibility) and supply chain management have become essential for ensuring a company’s permanence and financial consolidation. The literature has stated that the theories of Stakeholders and Sustainability are fundamental pillars for the development and sustained growth of business. The purpose of this article is to examine the effects of CSR and the SC (supply chain) on innovation, image and reputation, and in turn, their influences on profitability in SMEs. This research is based on a sample of 143 companies in the city of Guaymas Sonora, in Mexico. For the analysis and validation of the results, we used the SEM (Structural Equation Modeling) statistical technique based on the variance, through PLS (Partial Least Squares) (using SmartPLS version 3.2.6 Professional). The findings show that SMEs that develop social and sustainable practices increase their level of innovation, and improve their image, their reputation, and their financial profitability. This work contributes mainly to the development of Stakeholders and Sustainability.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

This work addresses the problem of automatic head pose estimation and its application in 3D gaze estimation using low quality RGB--D sensors without any subject cooperation or manual intervention. The previous works on 3D head pose estimation using RGB--D sensors require either an offline step for supervised learning or 3D head model construction which may require manual intervention or subject cooperation for complete head model reconstruction. In this paper, we propose a 3D pose estimator based on low quality depth data, which is not limited by any of the aforementioned steps. Instead, the proposed technique relies on modeling the subject's face in 3--D rather than the complete head, which in turn, relaxes all of the constraints with the previous works. The proposed method is robust, highly accurate and fully automatic. Moreover, it does not need any offline step. Unlike some of the previous works, the method only uses depth data for pose estimation. The experimental results on the Biwi head pose database confirm the efficiency of our algorithm in handling large pose variations and partial occlusion. We also evaluate the performance of our algorithm on IDIAP database for 3D head pose and eye gaze estimation.

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.

This paper explores ballot split by type and introduces universal measures of democratic power flow and accountable local representation. These measures allow definitive comparison of electoral systems between countries, and choice of a new electoral system within a country based on existing data and with minimum assumptions.

The Covid-19 coronavirus, SARS-CoV-2, is inactivated much faster on paper (3h) than on plastic (7d). By classifying materials according to virus stability on their surface, the following list is obtained (from long to short stability): polypropylene (mask), plastic, glass, stainless steel, pig skin, cardboard, banknote, cotton, wood, paper, tissue, copper. These observations and other studies suggest that SARS-CoV-2 may be inactivated by dryness on water absorbent porous materials but sheltered by long-persisting micro-droplets of water on waterproof surfaces. If such physical phenomenons were confirmed by direct evidence, the persistence of the virus on any surface could be predicted, and new porous objects could be designed to eliminate the virus faster.

In recent years, different deep learning frameworks were introduced for hyperspectral image (HSI) classification. However, the proposed network models have a higher model complexity and do not provide high classification accuracy if few-shot learning is used. This paper pre-sents an HSI classification method that combines random patches network (RPNet) and re-cursive filtering (RF) to obtain informative deep features. The proposed method first convolves image bands with random patches to extract multi-level deep RPNet features. Thereafter, the RPNet feature set is subjected to dimension reduction through principal component analysis (PCA) and the extracted components are filtered using the RF procedure. Finally, HSI spectral features and the obtained RPNet-RF features are combined to classify the HSI using a support vector machine (SVM) classifier. In order to test the performance of the proposed RPNet-RF method, some experiments were performed on three widely known datasets using a few training samples for each class and classification results were compared with those obtained by other advanced HSI classification methods adopted for small training samples. The comparison showed that the RPNet-RF classification is characterized by higher values of such evaluation metrics as overall accuracy and Kappa coefficient (https://github.com/UchaevD/RPNet-RF).

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e. sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago the ratio between emitted and sequestered carbon has varied considerably with atmospheric CO₂ levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil and gas. Relatively low atmospheric CO₂ levels were the norm for the past 10 million years, and during the past million years they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO₂ levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with domestication of crops and livestock leading to urbanisation and development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO₂ emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance it is important to understand the roles of high-capacity carbon sequestration systems, such as natural forests and tropical croplands, and to devise strategies to facilitate net CO₂ uptake.

The X-ray emission from a supernova remnant (SNR) is a powerful diagnostic of the state of the shocked plasma, and, given a model, can be used to determine the energy of the explosion, the age of the SNR and the density of the surrounding medium. Observed properties are shock radius, electron temperature (kTe) and emission measure (EM) of the shocked-gas. The standard and XSPEC definitions have an important difference. The XSPEC definition is superior for SNRs, which have components with low hydrogen abundance. SNR model calculations are based on hydrodynamic solutions for fluid variables of density, pressure and velocity. The relations between fluid variables and kTe or EM depend on composition, ionization state and electron-ion temperature ratio (Te/TI). Here the effects of composition, ionization and Te/TI on standard and on XSPEC versions of kTe and EM are investigated.

The archival Rossi X-ray Timing Explorer (RXTE) Proportional Counter Array (PCA) observations of HZ Her/Her X-1 are analyzed here. The time periods for Anomalous Low States are refined. The 35-day X-ray lightcurve of Her X-1 is produced using 35-day phases determined with RXTE All-Sky Monitor (ASM) and Swift Burst Altert Telescope (BAT) data, with adjustments based on the RXTE/PCA data. The result is the highest sensitivity 35-day lightcurve of Her X-1. The RXTE/PCA data were separated into 8 differents states of the 35-day cycle: Main High (MH) turn-on, MH, MH decline, Low State (LS) 1, Short High (SH) turn-on, SH, SH decline, and LS2. Orbital lightcurves were created for each state, and the different states are compared. Eclipse data was extracted for each state to determine the changes of eclipse shape with 35-day phase. A scattering corona model was fit to the eclipses for the different 35-day states: this shows that the corona is present at all 35-day phases with similar intensity. We carried out a search for previously-reported dips with no absorption, but did not find any.

The tourism sector in general and the hotelier in particular face the challenge of managing appropriate measures to deal with the covid-19 pandemic. In this sense it is useful to know what the measures are most demanded by the clientele. This research, by analyzing the variance (ANOVA) of a factor concluded that women are more demanding than men in terms of the level of demand in relation to the measures to be taken in hotels. This, as a practical application, allows to know more accurately the expectations, demands and demands of the client segmented by sex, in order to satisfy and improve the tourist experiences.

Inverse problems of recovering surface fluxes on the boundary of a domain from pointwise observations are considered. Sharp conditions on the data ensuring existence and uniqueness of solutions in Sobolev classes are exposed. They are smoothness conditions on the data, geometric conditions on the location of measurement points, and the boundary of a domain. The proof relies on asymptotics of fundamental solutions to the corresponding elliptic problems and the Laplace transform. The problem is reduced to a linear algebraic system with a nondegerate matrix.

The tourism sector in general and the hotelier in particular face the challenge of managing appropriate measures to deal with the covid-19 pandemic. In this sense it is useful to know what the measures are most demanded by the clientele. This research, by analyzing the variance (ANOVA) of a factor concluded that women are more demanding than men in terms of the level of demand in relation to the measures to be taken in hotels. This, as a practical application, allows to know more accurately the expectations, demands and demands of the client segmented by sex, in order to satisfy and improve the tourist experiences.

The tourism sector in general and the hotelier in particular face the challenge of managing appropriate measures to deal with the covid-19 pandemic. In this sense it is useful to know what the measures are most demanded by the clientele. This research, by analyzing the variance (ANOVA) of a factor concluded that women are more demanding than men in terms of the level of demand in relation to the measures to be taken in hotels. This, as a practical application, allows to know more accurately the expectations, demands and demands of the client segmented by sex, in order to satisfy and improve the tourist experiences.

In this article, we delve into the intricate behavior of electronic mechanisms underlying NMR magnetic shieldings, σ, in molecules containing heavy atoms such as cadmium, platinum, and mercury. Specifically, we explore PtXn^{−2} (X = F, Cl, Br, I; n = 4, 6) and XCl2 Te2 Y2 H6 (X = Cd, Hg; Y = N, P) molecular systems. It is known that the leading electronic mechanisms responsible for the relativistic effects on σ are well characterized by the linear response with elimination of small components model (LRESC). In this study, we present results obtained from the innovative LRESC-Loc model, which offers the same outcomes as the LRESC model but employs localized molecular orbitals (LMOs) instead of canonical MOs. These LMOs provide a chemist’s representation of atomic core, lone pairs, and bonds. The whole set of electronic mechanisms responsible of the relativistic effects can be expressed in terms of both non-ligand-dependent and ligand-dependent contributions. We elucidate the electronic origins of trends and behaviors exhibited by these di- verse mechanisms in the aforementioned molecular systems. In PtX4^{−2} molecules, the predominant relativistic mechanism is the well-established one-body spin-orbit (σ^SO(1) ) mechanism, while the paramagnetic mass-velocity (σ^Mv ) and Darwin (σ^Dw ) contributing mechanisms also demand con- sideration. However, in PtX6−2 molecules, the σ Mv+ Dw contribution surpasses that of the SO(1) mechanism, thus influencing the overall ligand-dependent contributions. As for complexes con- taining Cd and Hg, the ligand-dependent contributions exhibit similar magnitudes when nitrogen is substituted with phosphorus. The only discrepancy arises from the σ^SO(1) contribution, which changes sign between the two molecules due to the contribution of bond orbitals between the metal and tellurium atoms.

In this paper, the authors consider the influence of the type of power supply and the internal parameters of the DC-DC converter on the stability of the system at constant power load. The stability of the system under consideration is important in the design and development of the power supply system for an autonomous consumer. Such a typical system can be a DC microgrid. In the work, when analyzing the stability of the system, the power source is not considered an ideal voltage source, but the active-inductive nature of the voltage source is taken into account, which is equivalent to using a synchronous machine with permanent magnets. The Rauss-Hurwitz algebraic criterion was used as a criterion for analyzing the stability of the system. This will make it possible to build and analyze the areas and boundaries of the system's stability. As a result, the areas and boundaries of the stability of the system were presented. The general trend towards the behavior of the zone of instability of the system was given. At the same time, dependences describing the boundaries of instability are presented, which are combinations of parameters of the DC-DC converter, beyond which the system becomes unstable. The presented definitions of the instability limits can be used as a corrective device of the control system to ensure the stability of the system in the upper limits of the power consumption.

At present, business strategies in SMEs (Small and medium enterprises) are crucial for consolidation in highly competitive markets, in achieving a better image and in business profitability. One of the strategies that have the most success and business success are sustainable practices and social responsibility such as: ISO 14001 and ISO 26001. The literature related to sustainable business is based mainly on the theory of resources and capabilities, and in theory based on Stakeholders. These currents state that companies should focus on profitable strategies to ensure significant and long-term results, in order to achieve organizational and financial results for stakeholders. In this work, the sample consists of 215 companies from the commerce, services and industry sectors, located in the southern region of the State of Sonora in Mexico. The objective of the work is to analyze the influence of ISO 14001 and 26001 standards on the image and profitability of SMEs. The statistical analysis of the data has been carried out through the linear regression technique by OLS (Ordinary Least Squares). The findings prove that the ISO 14001 standard is the one that most influences the improvement of the business image and the level of profitability of the SME. In addition, we discovered that ISO 26001 has a partial influence on the image and profitability of the SME.

Background Oil palm (OP), Elaeis guineensis , is by far the most important global oil crop, supplying about 40% of total traded vegetable oil. Palm oils are key dietary components consumed daily by over three billion people, mostly in Asia, and also have a wide range of important non-food uses including in cleansing and sanitising products. Main body Oil palm is a perennial crop with a >25-year life cycle and an exceptionally small land footprint compared to annual oilseed crops. Oil palm crops globally produce an annual 81 million tonnes (Mt) of oil from about 19 million hectares (Mha). In contrast, the second and third largest vegetable oil crops, soybean and rapeseed, yield a combined 84 Mt oil but occupy over 163 Mha of increasingly scarce arable land. Despite this advantage, oil palm has acquired a poor environmental reputation, especially in Europe and North America, although soybean planting is now responsible for more deforestation. Oil palm crops face other challenges in the 2020s. On the demand side, these include changing consumer purchasing habits, threats to global trade systems, and diminishing demand for liquid fuels as transport systems become increasingly electrified. On the supply side, major issues include stagnant yields in ageing plantations, sluggish replanting of improved varieties, labour shortages, diseases and climatic/ environmental threats. The latter include the increasing incidence of new and existing pests/diseases and a general lack of climatic resilience, especially relating to elevated temperatures and increasingly erratic rainfall patterns. This review surveys the oil palm sector in the 2020s and beyond, its major challenges and options for future progress. Conclusions Oil palm crops face many future challenges, including emerging threats from climate change and new pests and diseases, that require more effective international collaboration. Nevertheless, new breeding technologies are providing the promise of improvements, such as much higher yielding varieties, improved oil profiles, enhanced disease resistance and modified crop architecture to enable harvesting mechanisation. The industry also needs to redouble its efforts to engage with global consumers in a constructive dialogue aimed at addressing its image problem and explaining the many benefits of its products.

Multiagent technologies give a new way to study and control complex systems. Local interactions between agents often lead to group synchronization also known as clusterization, which usually is a more rapid process in comparison with relatively slow changes in external environment. Usually, the goal of system control is defined by the behaviour of a system on long time intervals. When these time intervals are much longer than the time of cluster formation, clusters may be considered as new variables in a ``slow'' time model. We call such variables ``mesoscopic'' to emphasize their scale laying between the level of the whole system (macroscopic scale) and the level of individual agents (microscopic scale). Thus, it allows us to reduce significantly the dimensionality of a system by omitting considerations of each separated agent, so that we may hope to reduce the required amount of control inputs. Thus, we are often able to consider a system as a collection of ``flowing'' (morphing) clusters emerged form behaviour of a huge amount of individual agents. In this paper, we contrast such approach to the one where a system is considered as a network of elementary agents. We develop a mathematical framework for analysis of cluster flows in multiagent networks and use it to analyze the Kuramoto model as an attracting example of a complex networked system. In this model, a clusterization leads to sparse representation of dynamic trajectories in the whole quantized state space. With that in mind, compressive sensing allows to restore the trajectories in a high-dimensional discrete state space based on significantly lower amount of randomized integral mesoscopic observations. We propose a corresponding algorithm of quantized dynamic trajectory compression. It could allow us to efficiently transmit the state space data to a data center for further control synthesis. The theoretical results are illustrated for a simulated multiagent network with multiple clusters.

The cultural and historical heritage of a city is a major resource to attract tourists. Therefore, reaching out to perceive and identify the characteristics of persons visiting a locality attracted by their property is relevant for the purpose of better meeting their expectations and needs. This research focuses on knowing the perceptions, motivations and satisfaction of women visiting Cordoba (Spain). Thus, on the basis of the questionnaire carried out on women visiting Cordoba during the months of June and November 2019, a statistical analysis has been made. Using various multivalent case-grouping techniques, tourist segments with similar perceptions of cultural heritage have been detected. Moreover, non-parametric statistical techniques have showed up significant differences between the valuations obtained in the various segments. This analysis has exposed a segment of women who, known as absorbent tourists, are characterized by the high cultural motivation to visit the city of Cordoba linked to the heritage they have visited. The conclusions obtained should be useful in adjusting the city's tourist supply to the specific demand of a population sector such as women visiting the city.

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

Autonomous driving navigation relies on diverse approaches, each with advantages and limitations depending on various factors. For HD maps, modular systems excel, while end-to-end methods dominate mapless scenarios. However, few leverage the strengths of both. This paper innovates by proposing a hybrid architecture that seamlessly integrates modular perception and control modules with data-driven path planning. This innovative design leverages the strengths of both approaches, enabling a clear understanding and debugging of individual components while simultaneously harnessing the learning power of end-to-end approaches. Our proposed architecture achieved 1st and 2nd place in the 2023 CARLA Autonomous Driving Challenge’s SENSORS and MAP tracks, respectively. These results demonstrate the architecture’s effectiveness in both map-based and mapless navigation.

The dual leucine zipper kinase (DLK) alias mitogen-activated protein 3 kinase 12 (MAP3K12) has gained much attention in recent years. DLK belongs to the mixed lineage kinases, characterized by homology to serine/threonine and tyrosine kinase but exerts serine/threonine kinase activity. DLK has been implicated in many diseases including several neurodegenerative diseases, glaucoma, and diabetes mellitus. As a MAP3K, it is generally assumed that DLK becomes phosphorylated and activated by upstream signals and phosphorylates and activates itself, the downstream serine/threonine MAP2K, and ultimately MAPK. In addition, other mechanisms such as protein-protein interactions, proteasomal degradation, dephosphorylation by various phosphatases, palmitoylation, and subcellular localization have been shown to be involved in the regulation of DLK activity or its fine-tuning. In the present review, the diverse mechanisms regulating DLK activity will be summarized to provide a better insight into DLK action and possibly new targets to modulate DLK function.

For tropical forests to survive anthropogenic climate change, the trees that comprise them will need to tolerate the newly emerging conditions through adaptation or acclimation, or they can avoid climate change through range shifts and “species migrations”. In this review, we show that the rapid pace and extreme severity of modern climate change makes it extremely unlikely that tropical tree species can adapt (with some possible exceptions). We also show that while many tropical tree species are shifting their distributions to higher, cooler elevations, the rate of these migrations are mostly insufficient to offset ongoing changes in temperatures, especially in lowland tropical rainforests where thermal gradients are shallow or nonexistent. We argue that the best hope for tropical tree species to avoid becoming “committed to extinction” is acclimation. While several new methods are being developed to test for acclimation, we unfortunately still do not know if tropical tree species can acclimate or what factors may prevent or facilitate acclimation. Until these questions are answered, our ability to predict the fate of tropical species and tropical forests – and the many services that they provide to humanity – remains critically impaired.

Observations of the X-ray binary system Her X-1 by the AstroSat Soft X-ray Telescope 1 (SXT) were carried out in 2020 through 2023 with the goals of measuring X-ray spectrum changes with the 35-day disk rotation phase and measuring eclipses at different 35-day phases. The four multi-day long observations were scheduled during: turn-on to Main High (MH) and MH rise; MH state; Short High (SH) state; and Low State (LS). 35-day phase was determined using monitoring observations with the Swift Burst Alert Telescope (BAT). Nine eclipses were observed at a range of 35-day phases, with at least one eclipse during each observation. Data with dips were separated from data without dips. The variation of X-ray spectral parameters vs. 35-day phase shows the following: eclipse parameters are nearly constant, showing that the scattering corona does not change with 35-day phase; dips show an increase in covering fraction but not column density compared to non-dip data; the 1 keV line normalization indicates an origin in a small region near the continuum emission region, likely the magnetospheric accretion flow from the inner disk onto the neutron star; and the change in blackbody normalization (area) shows that the emission region is much larger than the 1 keV emission region, and consistent with the inner edge of the accretion disk.

Tomato (Solanum lycopersicum L.) is one of the most commercially essential vegetable crops cultivated worldwide. In addition to the nutritional value, tomato is an excellent model for studying climacteric fruits' ripening process. Despite this, the available natural pool of genes that allows expanding phenotypic diversity is limited, and the difficulties of crossing using classical selection methods when stacking traits increase proportionally with each additional feature. Genetic engineering makes it possible to introduce changes in genes of interest without changing the allelic combinations characteristic of successful commercial varieties, to enhance the expression of existing genes, to create and transfer artificial and heterologous genes, and much more. However, this requires understanding the fundamental principles of the molecular interaction. Although the leading candidate genes for these components have been identified, a complete picture of their relationship has yet to be formed. The review summarizes the latest (2017-2023) achievements related to studying the ripening processes of tomato fruits. In this work, an attempt is made to systematize the results of various research and display the interaction pattern of genes regulating the process of tomato fruit ripening.

Given the documented wave-induced damage of elevated coastal decks during extreme natural hazards (e.g. hurricanes) in the last two decades, it is of utmost significance to decipher the wave-structure-interaction of complex deck geometries and quantify the associated loads. Therefore, this study focuses on the assessment of solitary wave impact on open-girder decks that allow the air to escape from the sides. To this end, an arbitrary Lagrangian-Eulerian (ALE) numerical method with a multi-phase compressible formulation is used for the development of three-dimensional hydrodynamic models, which are validated against a large-scale experimental dataset of a coastal deck. Using the validated model as a baseline, a parametric investigation of different deck geometries with a varying number of girders Ng and three different widths, was conducted. The results reveal that the Ng of a superstructure has a complex role and that for small wave heights the horizontal and uplift forces increase with the Ng, while for large waves the opposite happens. If the Ng is small the wave particles accelerate after the initial impact on the offshore girder leading to a more violent slamming on the onshore part of the deck and larger pressures and forces, however, if Ng is large then unsynchronized eddies are formed in each chamber, which dissipate energy and apply out-of-phase pressures that result in multiple but weaker impacts on the deck. The decomposition of the total loads into slamming and quasi-static components, reveals surprisingly consistent trends for all the simulated waves, which facilitates the development of predictive load equations. These new equations, which are a function of Ng and are limited by the ratio of the wavelength to the deck width, provide more accurate predictions than existing empirical methods, and are expected to be useful to both engineers and researchers working towards the development of resilient coastal infrastructure.

This paper is motivated by spatio-temporal pattern in the occurrence of Leishmaniasis in Afghanistan and the relatively high number of zero counts. We hold the view that correlations that arise from spatial and temporal sources are inherently distinct. Our method decouples these two sources of correlations, there are at least two advantages in taking this approach. First, it circumvents the need to inverting a large correlation matrix, which is a commonly encountered problem in spatio-temporal analyses. Second, it simplifies the modelling of complex relationships such as anisotropy, which would have been extremely difficult or impossible if spatio-temporal correlations were simultaneously considered. We identify three challenges in the modelling of a spatio-temporal process: (1) accommodation of covariances that arise from spatial and temporal sources; (2) choosing the correct covariance structure and (3) extending to situations where a covariance is not the natural measure of association. Moreover, because the data covers a period that overlaps with the US invasion of Afghanistan, the high number of zero counts may be the result of no disease incidence or lapse of data collection. To resolve this issue, a model truncated at zero built on a foundation of the generalized estimating equations was proposed.

Olive tree vegetal materials are considered a powerful source for isolation of bioactive compounds, mainly, phenols and triterpenic acids. However, the high humidity content of them reduces their preservation and extractability to a liquid solvent. Accordingly, a drying step is crucial to homogenize the material and to obtain an efficiency extraction. We studied the influence of the drying process on the extraction efficiency of bioactive compounds from olive vegetal material. For this purpose, we evaluated the effects of four drying processes on the solid–liquid extraction of bioactive compounds from two by-products, olive leaves and pomace, and olive fruits harvested from two cultivars, Alfafara and Koroneiki. Infrared-assisted drying (IAD) was the most suited approach to obtain extracts enriched in oleuropein from leaves. In the case of pomace, lyophilization and microwaves-assisted drying led to extracts concentrated in oleacein and oleuropein aglycone, whereas IAD and oven-drying led to extracts with enhanced content in hydroxytyrosol glucoside and hydroxytyrosol, respectively. The drying process affected considerably to the chemical composition of extracts obtained from fruits. Changes in the composition of extracts were explained essentially by the drying process conditions using auxiliary energies, temperature and time, which promoted chemical alterations and increased the extractability of compounds.

To protect power lines, distance relays are used which can rely on a modified distance resistance. But usually the operating range of these relays changes as the network conditions change (network topology, load value, output value, etc.) and leads to false trips, By using methods that can process information and recognize patterns, for example, the use of micro and intelligent processor algorithms can use the new relays with high precision and thus provide adequate protection. In this study, a distance relay was modeled using a neural network, and it was observed that the neural relay had higher accuracy than the conventional relay. In addition to detecting the fault and its location, type and phase of the fault, three-stage simultaneous protection can be performed. As a result, the number of linear relays can be reduced by using relays based on neural technologies. An MLP (multilayer perceptron) neural network is used to model a sequence of distances.

The nature of the sustainability crisis is characterized by high levels of complexity, thus it is not amenable to be approached from the linearity or reductionist paradigm. Emergence is a multilevel phenomenon that is characterized by qualitative novelty and is recognized as an important attribute of complex systems produced by self-organized processes, unveiled from a holistic stance. This conceptual-analytical article explores the emergence phenomenon and questions whether it can be a way of enhancing the solution process to meet the sustainability challenges. Emergent properties or behaviors emerge only when the system parts interact in a wider whole. Moreover, a systemic approach is proposed as an intermediary component in the process of emergence of creative and wise solutions to the wicked problems of unsustainability. This requires observation and entails analyzing open systems as a whole and recognizing the impact of traversing macro- and micro- scales on causal and creative emergence. The study also emphasizes synergies between emergence and creativity aimed at sustainability. Sustainable development requires leapfrogging past conventional practices, in an accelerated way, and the emergence phenomenon at play between systems levels, coupled with purposefully structured creative processes, holds the potential for catalyzing sustainable development efforts.

The global demand for rubber is on a steady rise, which is driven by the increasing production of automobiles and the growing need for industrial, medical, and household products. This surge in demand has led to a significant increase in rubber waste, posing a major global environmental challenge. End-of-life tire (ELT) is a primary source of rubber waste, which possesses significant environmental hazards due to its massive stockpiles. While landfilling is a low-cost and easy-to-implement solution, it is now largely prohibited due to environmental concerns. Recently, ELT rubber waste has garnered considerable attention for its potential applications in civil engineering and construction. These applications not only enhance sustainability but also foster a circular economy between ELT rubber waste and the civil engineering and construction sectors. This review article concentrates on the recent research progress and challenges in the civil engineering applications of ELT rubber waste. It also discusses commercially available recycled rubber-based construction materials, their properties, testing standards, and certification. To the best of the authors' knowledge, this is the first time such a discussion on commercial products has been presented.

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

Online education allows learners to develop knowledge and skills flexibly and conveniently—such observation among students whose characteristics involve student engagement, self-regulation, and self-efficacy. However, studies to characterize Filipino online learners seem lacking. Thus, this study aimed to characterize science education tertiary students in the Philippines concerning their online student engagement (OSE), self-regulated learning (SRL), and online learning self-efficacy (OLSE). The unprecedented events brought by COVID-19 pandemic also urged the implementation of online modalities while there is no available information on students’ online learning profiles. Hence, researchers used a survey research employed through ex post facto approach to determine the effects of the demographic profile on OSE, SRL, and OLSE. The survey was participated by N=373 respondents who answered the questionnaire with informed consent administered via Google Forms. Results revealed that OSE indicators moderately characterized students, while SRL and OLSE indicators are true of them, substantiated by the overall mean M=3.85(SD=0.90), M=3.86(SD=0.92), and M=3.14(SD=0.73), respectively. Also, multivariate tests showed no significant effect among the independent groups (p>0.05), except for gender and OLSE interaction (p<0.05) so, only in OLSE was a significant difference found in gender. In conclusion, Filipino online learners are moderate across aspects of student engagement, self-regulation, and self-efficacy.

The macro-litter (plastic) sea bottom pollution of 14 city harbors and marinas in North Africa and in the western Baltic Sea was investigated using a new simple mobile underwater camera system. The study was complemented by a harbor manager survey and 3D-hydrodynamic transport simulations. The average pollution in German marinas was 0.1 particles/m² sea floor (0.04–1.75). The pollution in North African marinas on average was 7 times higher (0.7 particles/m²) and exceeded 3 particles/m² in city center harbors. The resulting >100,000 litter particles per harbor indicate the existence of a problem. With 73%-74%, plastic particles are dominating. Existing legal and management frameworks explain the lack of plastic bottles and bags on sea floors in Germany and are one reason for the lower pollution levels. Items that indicate the role of untreated sewage water were not found. Harbor festivals seem not to be quantitatively relevant for open sea bottom pollution. Our method tends to underestimate the pollution level. Model simulations indicate that storms can cause litter reallocations and sediment cleanings. However, marina sea floor monitoring is recommendable, because it addresses pollution hot-spots, is cost-effective and takes place close to emission sources. Further, the effectiveness of land-based pollution reduction measures can easily be assessed.

In this work, a simple and environmentally friendly process combining low pressure (vacuum) and mechanical compression is proposed to convert recycled polypropylene (PP) foams (28 kg/m3) into low density foams (90-131 kg/m3) having negative tensile and compressive Poisson's ratios (NPR). The effect of processing conditions (vacuum time, temperature, and mechanical pressure) was studied. Based on the optimized conditions, the tensile Poisson’s ratio of the resulting auxetic foams reached −1.50, while the minimum compressive Poisson's ratios was −0.32 for the same sample. The foam structure was characterized via morphological analysis (SEM) to determine any changes related to the treatment applied. Finally, tensile and compressive properties (Young's modulus, strain energy, energy dissipation and damping capacity) are also presented and discussed. It was observed that the mechanical properties of the resulting auxetic foams were improved compared to the original PP foam (PP-O) for all tensile properties in terms of modulus (19.9 to 59.8 kPa), strength (0.298 to 1.43 kPa) elongation at break (28 to 77%), energy dissipation (14.4 to 56.3 mJ/cm3) and damping capacity (12 to 19%). Nevertheless, improvements were also observed under compression in terms of energy dissipation (1.6 to 3.6 mJ/cm3) and damping capacity (13 to 19%). These auxetic foams can find applications in sport and military protective equipment, as well as any energy mitigation system.

Global concerns of decreasing water availability and food security are being exacerbated by the increasing demand for food, water quality degradation, and climate change impacts. Rice is an essential crop for food security with paddy rice cultivation largely practiced using traditional flooding conditions. Water regimes and components of the soil water balance in paddy rice catchments affect uptake of water by rice roots. Paddy management, especially puddling, significantly affects soil hydrological properties, such as hydraulic conductivity, percolation, and seepage in the paddy rhizosphere. Improved knowledge of these interactions is vital for developing sustainable water management strategies in paddy fields. Alternate Wetting and Drying (AWD) practice contributes to sustainable water management, but little is known about effects of soil wetting and drying duration on gravitational soil water flow, moisture dynamics, and hydraulic conductivity in the rice paddy rhizosphere. These factors depend on soil type, rice variety, rooting conditions, and environmental factors, such as solar radiation and temperature. Here we examine the paddy cultivation environment and soil properties under traditional continuous flooding and AWD practice. Some studies indicate that the duration and frequency of wetting and soil drying under AWD practice in paddy fields affects soil hydraulic conductivity that alters the next cycle of water application. During droughts and short rainy seasons, rainfall, soil properties, and atmospheric conditions control soil moisture dynamics in paddy fields. Limitations and challenges of applying AWD in paddy soils, including the variation of hydrological properties and the need for frequent field manual monitoring of water level (WL) head, are discussed. Implications of AWD practice on yield, water use efficiency, soil hydrology, and reduction of methane emissions, are outlined along with opportunities to improve AWD integration within government policies, irrigation schemes, and adoption by farmers. Coupled crop models can provide important insights for sustainable agricultural water management.

The process of establishing secure communication between devices in the Internet of Things (IoT) can be approached by using a One-time-Pad (OTP) protocol. We propose using a known secure multiparty sum protocol for generating a One-time-Pad key using true (physical) random numbers in each device (party). We implemented the proposal using ZeroC-Ice, a middleware for distributed computing. The protocol security properties were analyzed under the assumptions of the Dolev-Yao threat model.

This paper proposes a method based on genetic algorithm (GA) for the security-constrained optimal dispatch of integrated natural gas and electricity networks, considering operating scenarios in both energy systems. The mathematical formulation of the optimization problem consists of a multi-objective function which aims to minimize both cost of thermal generation (diesel and natural gas) as well as the production and transportation of natural gas. The joint gas-electricity system is modeled by two separate groups of nonlinear equation, which are solved by the combination of Newton's method with the GA. The applicability of the proposed method is tested in the Belgian gas network integrated with the IEEE 14-bus test system and a 15-node natural gas network integrated with the IEEE 118-bus test system. The results demonstrate that the proposed method provides efficient and secure solutions for different operating scenarios in both energy systems.

Accurate transfer learning of clinical outcomes, e.g., of the effects and side effects of drugs or other interventions, from one cellular context to another (in-vitro versus ex-vivo versus in-vivo, or across tissues), between cell-types, developmental stages, omics modalities or species, is considered tremendously useful. Ultimately, it may avoid most drug development failing in translation, despite large investments in the preclinical stages, which includes animal experiments requiring careful justification. Thus, when transferring a prediction task from a source (model) domain to a target domain, what counts is the high quality of the predictions in the target domain, requiring molecular states or processes common to both source and target that can be learned by the predictor, reflected by latent variables. These latent variables may form a compendium of knowledge that is learned in the source, to enable predictions in the target; usually, there are few, if any, labeled target training samples to learn from. Transductive learning then refers to the learning of the predictor in the source domain, transferring its outcome label calculations to the target domain, considering the same task. Inductive learning considers cases where the target predictor is performing a different yet related task as compared to the source predictor, making some labeled target data necessary. Often, there is also a need to first map the variables in the input/feature spaces (e.g. of gene names to orthologs) and/or the variables in the output/outcome spaces (e.g. by matching of labels). Transfer across omics modalities also requires that the molecular information flow connecting these modalities is sufficiently conserved. Only one of the methods for transfer learning we reviewed offers an assessment of input data, suggesting that transfer learning is unreliable in certain cases. Moreover, source domains feature their very own particularities, and transfer learning should consider these, e.g., as differences in pharmacokinetics, drug clearance or the microenvironment. In light of these general considerations, we here discuss and juxtapose various recent transfer learning approaches, specifically designed (or at least adaptable) to predict clinical (human in-vivo) outcomes based on molecular data, towards finding the right tool for a given task, and paving the way for a comprehensive and systematic comparison of the suitability and accuracy of transfer learning of clinical outcomes.

Current smartphones incorporate different types of sensors that allow us to know our spatial position, they give us information about pressure, speed, acceleration, time, acoustic level, and other different physical magnitudes. These smartphones measure each component of the magnetic field, bearing in mind that any current perpendicular to a magnetic field produces a small potential difference, transversal to the said current, being this voltage easily measurable by Hall sensors. With the implementation of three Hall sensors, and an appropriate app, we can measure the three components of the magnetic field vector, and with this we can obtain information and deduce properties of the physical systems considered. In this paper we are exploring the use of smartphones in a physics laboratory for freshman students. To do this, we have measured, using Hall sensors, the magnetic field created by a linear quadrature, and we have obtained, first of all, its dependence on the distance between the quadrupole and the magnetic sensor. The second purpose of this work is to show that the laboratory is a powerful tool that increases the significant learning of freshman students through advanced technological tools.

We believe that a natural focus of the Physics Education Research community is on understanding and improving student learning in our physics courses. For this purpose, we are introducing smartphones in the physics laboratory. Current smartphones measure each component of the magnetic field, bearing in mind that any current perpendicular to a magnetic field produces a small potential difference, transversal to the said current, being this voltage easily measurable by Hall sensors. In this work, we have considered the magnetic field created by a linear quadrupole and we have studied its dependence on distance. Using an experimental procedure that is simple we have measured the magnetic field using the Hall sensor that most smartphones have, together with the corresponding app. The purpose of this work is to show that the laboratory is a powerful tool that increases significant learning under three conditions: 1) the practice must not be too sophisticated; 2) students must handle objects in the lab; and 3) the practice must be scientifically accurate, including the adjustments by minimum squares, and the following and necessary error calculation.

Dysregulation of the arsenal of cells, growth factors, cytokines, proteases, and proteins involved in wound healing (WH), could delay the healing process. Plants and plant-derived molecules (PDMs) have been used as medicines for skin wounds. This study aimed to select and evaluate the pro-healing capacity of PMDs. Thirty-three PDMs and 10 therapeutic targets (TTs) were chosen for molecular docking and PDMs: aristolochic acid (AA), α-copaene, selinenes, β-caryophyllene (BC), and BCoxide, and TTs: metalloproteinase (MMP) 3, MMP13, and tumor necrosis factor (TNF α) for molecular dynamics. The bests inhibitor was AA, but because of its toxicity, BC and BCoxide were chosen for evaluation in HaCat cells and BALB/c mice excisional model. Both compounds were not toxic, and higher percentages of lesion area closure (LAC) were induced by BC treatment (p<0.05). All mice healed; however, an initial delay of LAC was induced by 0.05, 0.1% BCoxide, 0.1% BC, and allantoin. At the end of treatment, lower numbers of mast cells, level of cellular infiltrates (except 1% BCoxide and 0.05, 0.5%BC), epidermal thickness tendency (except 0.1, 0.5% BCoxide), and higher values of SC-thickness, and collagen fibers only by 0.5% BC treatment compared with untreated control (p<0.05) were observed. Our results show that BC is a promising multitarget candidate for wound healing treatment and optimization campaigns.

Canistel (Pouteria campechiana (Kunth) Baehni) (yellow sapote, canistel). Originally from Mexico, the fruit is edible, and the tree is used as an ornamental and medicinal plant. Descriptive studies were carried out with the objective of morphologically characterizing the fruits and leaves of trees located in different regions of Mexico to select outstanding specimens and propose their massive reproduction. The trees were selected in three zones. In zone 2 from flower anthesis to harvest 11 months, fruits with 3 seeds, greater weight (180 to 330 g) and quantity of pulp (198.88 g), subglobose shape, total soluble solids 33 %. The fruits of zone 1 at harvest 8 months and zone 3 took 9 months to be harvested, in the rest of the characteristics evaluated were exceeded by the fruits of zone 2. To characterize the canistel (P. campechiana) leaf and identify accessions or cultivars, the three main variables, according to the principal component analysis were: leaf area, perimeter, and minor diameter. The three zones where canistel fruits and leaves were characterized are important and can be recommended for propagation in zones with favorable climatic conditions for fruiting in tropical and subtropical regions of Mexico.

Legume seed protein is an important source of nutrition, but it is less digestible than animal protein. Poor protein digestibility in legume seeds and seedlings may partly reflect defences against herbivores. Protein changes during germination typically increase proteolysis and digestibility, by lowering the levels of anti-nutrient protease inhibitors, activating proteases, and breaking down storage proteins (including allergens). Germinating legume sprouts also show striking increases in free amino acids (especially asparagine), but their roles in host defence or other processes are not known. While the net effect of germination is generally to increase the digestibility of legume seed proteins, the extent of improvement in digestibility is species and strain dependent. Further research is needed to highlight which changes contribute the most to improved digestibility of sprouted seeds. Such knowledge could guide the selection of varieties that are more digestible, and also guide the development of food preparations that are more digestible, potentially combining germination with other factors altering digestibility, such as heating and fermentation. Techniques to characterize the shifts in protein make-up, activity and degradation during germination need to draw on traditional analytical approaches, complemented by proteomic and peptidomic analysis of mass spectrometry identified peptide breakdown products.

We review a modern differential geometric description of the fluid isotropic motion and featuring it the diffeomorphism group structure, modelling the related dynamics, as well as its compatibility with the quasi-stationary thermodynamical constraints. There is analyzed the adiabatic liquid dynamics, within which, following the general approach, there is explained in detail, the nature of the related Poissonian structure on the fluid motion phase space, as a semidirect Banach groups product, and a natural reduction of the canonical symplectic structure on its cotangent space to the classical Lie-Poisson bracket on the adjoint space to the corresponding semidirect Lie algebras product. We also present a modification of the Hamiltonian analysis in case of the isotermal liquid dynamics. We study the differential-geometric structure of the adiabatic magneto-hydrodynamic superfluid phase space and its related motion within the Hamiltonian analysis and invariant theory. In particular, we construct an infinite hierarchies of different kinds of integral magneto-hydrodynamic invariants, generalizing those before constructed in the literature, and analyze their differential-geometric origins. A charged liquid dynamics on the phase space invariant with respect to an abelian gauge group transformation is also investigated, some generalization of the canonical Lie-Poisson type bracket is obtained.

Rapid industrialization, urbanization, and population explosion in sub-Saharan Africa escalate environmental Lead levels with subsequent elevation of blood Lead levels in children. Nutrition status, age, and genetics govern one’s susceptibility to Lead toxicity. This study expounded this susceptibility by relating blood Lead levels, d-aminolevulinic acid dehydratase enzyme activity (ALAD), and genetic variations of proteins that code for ALAD enzyme in urban children of Uganda. Spectrophotometric analysis for blood Lead (BL), hemoglobin levels, and determination d-levels aminolevulinic acid dehydratase enzyme activity of the blood samples from 198 children were performed prior to a polymerase chain reaction and restriction fragment length digestion for ALAD polymorphism was done. Up to 99.5% of samples coded for the ALAD1 allele whereas 0.05% coded for ALAD2. Genotypes ALAD2-2 members had elevated BLL (mean 14.1 µg/dL) and reduced ALAD enzyme activity compared to others. This, therefore, implies that the majority of children hoard BL which may affect them later in life.

As of the end of 2022, despite the disruptions caused by the COVID-19 pandemic, the global HIV epidemic persists, with 39 million individuals living with the virus and 1.3 million new infections reported in that year. Opportunistic infections associated with AIDS claimed the lives of over 630,000 people in 2022, contributing to a cumulative death toll exceeding 40.4 million since the disease's emergence in 1981. Although advances in HIV diagnosis and antiretroviral therapy have transformed the disease into a manageable chronic condition, issues like drug resistance, low compliance, and high treatment costs persist. Until a vaccine becomes available, a comprehensive approach involving prevention and therapy is essential, particularly for high-risk populations. Research shows that prevention strategies are more cost-effective than treatment. The development of antiretroviral drugs has also spurred the creation of antivirals for other infections. The emergence of COVID-19 vaccines has opened new avenues for HIV vaccine development, as lessons from vaccine platform technologies like mRNA, viral vectors, and protein subunits can be applied to HIV. This review explores the most promising prophylactic and therapeutic HIV vaccine trials, emphasizing the need for a multi-pronged approach combining vaccines with non-vaccine strategies. Though significant progress is anticipated, the road to a viable HIV vaccine remains long, especially for high-risk populations, such as medical workers, blood transfusion recipients, and drug users. The combinatorial approach, capitalizing on various aspects of immunity, may hold the key to defeating HIV in the future.

It is shown that the termination of the channeling of the fundamental radiation mode in the waveguide can be observed upon heating of an optical integrated circuit based on proton exchange channel waveguides formed in a lithium niobate single crystal. This process is reversible, but restoration of waveguide performance takes tens of minutes. The effect of the waveguide disappearance is observed upon rapid heating (5 °C/min) from a low temperature (minus 40 °C). This effect can lead to a temporary failure of navigation systems using fiber optic gyroscopes with modulators based on a lithium niobate crystal

Terrestrial LiDAR becomes more and more popular to estimate leaf and plant area density. Voxel-based approaches account for this vegetation heterogeneity and significant work has been done in this recent research field, but no general theoretical analysis is available. Although estimators have been proposed and several causes of biases have been identified, their consistency and efficiency have not been evaluated. Also, confidence intervals are almost never provided. In the present paper, we solve the transmittance equation and use the Maximum Likelihood Estimation (MLE), to derive unbiased estimators and confidence intervals for the attenuation coefficient, which is proportional to leaf area density. The new estimators and confidence intervals are defined at voxel scale, and account for the number of beams crossing the voxel, the inequality of path lengths in voxel, the size of vegetation elements, as well as for the variability of element positions between vegetation samples. They are completed by numerous numerical simulations for the evaluation of estimator consistency and efficiency, as well as the assessment of the coverage probabilities of confidence intervals. • Although commonly used when the beam number is low, the usual estimators are strongly biased and the 95% confidence intervals can be ≈±100% of the estimate. • Our unbiased estimators are consistent in a wider range of validity than the usual ones, especially for the unbiased MLE, which is consistent when the beam number is as low as 5. The unbiased MLE is efficient, meaning it reaches the lowest residual errors that can be expected (for an unbiased estimator). Also the unbiased MLE does not require any bias correction when path lengths are unequal. • When elements are small (or voxel is large), 103 beams entering the voxel leads to some confidence intervals ≈±10%, but when elements are larger (or voxel smaller), it can remain wider than ±50%, even for a large beam number. This is explained by the variability of element positions between vegetation samples. Such a result shows that a significant part of residual error can be explained by random effects. • Confidence intervals are much smaller (±5 to 10%) when LAD estimates are averaged over several small voxels, typically within a horizontal layer or in the crown of individual plants. In this context, our unbiased estimators show a reduction of 50% of the radius of confidence intervals, in comparison to usual estimators. Our study provides some new ready-to-use estimators and confidence intervals for attenuation coefficients, which are consistent and efficient within a fairly large range of parameter values. The consistency is achieved for a low beam number, which is promising for application to airborne LiDAR data. They entail to raise the level of understanding and confidence on LAD estimation. Among other applications, their usage should help determine the most suitable voxel size, for given vegetation types and scanning density, whereas existing guidelines are highly variable among studies, probably because of differences in vegetation, scanning design and estimators.

Introduction. Musculoskeletal disorders related to work might follow with a cumulative effect during working life. We aimed to develop a new model to allow to compare the accuracy of duration of work and intensity/frequency associations in application to severe knee pain. Methods. The CONSTANCES cohort is used with data from n=66553 subjects who were working at inclusion and coded. From a biomechanical job exposure matrix “JEM Constances”, intensity/frequency of heavy lifting and kneeling/squatting were used and applied to the work history in comparison to severe knee pain. An innovative model was developed and evaluated, allowing to compare the accuracy of duration of work and intensity/frequency associations. Results. The mean age is 49 years at inception with 46 percent of women. The G model developed was slightly better than regular models. In men, odds ratios of the highest quartile for the duration and low intensity were not significant for both exposures, whereas intensity/duration were for every duration. Results in women were less interpretable. Conclusion. Though increased duration increased strength of association with severe knee pain, intensity/frequency were important predictors among men. Exposure estimation along working history should have emphasis on such parameters, though other outcomes should be studied such as women.

Plants Microbial Fuel Cells (PMFC) is a new technology that generates electricity in a renewable, clean and sustainable way. In spite of these advantages, it still faces limitations in power generation and current density, reaching lower production values than other renewable technologies. Different studies maintain that the high resistivity of the cathode is the main limitation in the generation of energy; therefore, non-metallic materials to obtain a better performance are replacing the metallic electrodes. The implementation of these materials applied to PMFC requires a complex interdisciplinary work. Through three experimental tests using metallic electrodes for the extraction of electrons, this research study shows that the treatment of the substrate with natural materials, the volume plant roots, and substrate temperature and humidity control have a significant influence in the increase of the electric potential and the generated current.

Diclofenac is a non-steroidal anti-inflammatory drug (NSAID) from the group of phenylacetic acid derivatives, which has analgesic, anti-inflammatory and antipyretic properties. The interaction of non-steroidal anti-inflammatory drugs with cell membranes can affect their physicochemical properties, which, in turn, can cause a number of side effects in the use of these drugs. Electron paramagnetic resonance (EPR) spectroscopy could be used to study the interaction of diclofenac with the membrane, if its spin-labeled analogs existed. This paper describes the synthesis of spin-labeled diclofenac (diclofenac-SL), which consists of a simple sequence of transformations such as iodination, esterification, Sonogashira cross-coupling, oxidation and saponification. EPR spectra showed that diclofenac-SL binds to in a lipid membrane composed of palmito-yl-2-oleoyl-sn-glycero-3-phosphocholine (POPC). 2H electron spin echo spectroscopy (ESEEM) was used to determine the position of the diclofenac-SL relative to the membrane surface. It has been established that the average its depth of immersion corresponds to the 5th position of the carbon atom in the lipid chain.

Ultrafast pump-probe spectroscopic studies allow for deep insights into the mechanisms and timescales of photophysical and photochemical processes. Extracting valuable information from these studies, such as reactive intermediates' lifetimes and coherent oscillation frequencies, is an example of the inverse problems of chemical kinetics. This article describes a consistent approach for solving this inverse problem that avoids the common obstacles of simple least-squares fitting that can lead to unreliable results. The presented approach is based on the regularized Markov Chain Monte Carlo sampling for the strongly nonlinear parameters, allowing for a straightforward solution of the ill-posed nonlinear inverse problem. The software to implement the described fitting routine is introduced and the numerical examples of its application are given. We will also touch on critical experimental parameters, such as the temporal overlap of pulses and cross-correlation time and their connection to the minimal reachable time resolution.

Supernova remnants (SNRs) are an integral part in studying the properties of the Galaxy and its interstellar medium. For the current work, we explore the relation between the observed radio luminosities of SNRs and the physical properties of those SNRs. The physical properties of 54 SNRs are derived from their observed X-ray spectra. Then the observed radio emission is compared to predicted radio emission using the analytic model of . We find the model can be improved significantly by including an interstellar medium density dependence in the efficiency of particle acceleration and magnetic field amplification.

Since the emergence of the quantified self movement, users aim at health behavior change, but only those who are sufficiently motivated and competent with the tools will succeed. Our literature review shows that theoretical models for quantified self exist but they are too abstract to guide the design of effective user support systems. Here, we propose principles linking theory and implementation to arrive at a hierarchical model for an adaptable and personalized self-quantification system for physical activity support. We show that such a modeling approach should include a multi-factors user model (activity, context, personality, motivation), a hierarchy of multiple time scales (week, day, hour), and a multi-criteria decision analysis (user activity preference, user measured activity, external parameters). This theoretical groundwork, which should facilitate the design of more effective solutions, has now to be validated by further empirical research.

The necessary and sufficient conditions of existence of the nonlinear operator equations' branches of solutions in the neighbourhood of branching points are derived. The approach is based on reduction of the nonlinear operator equations to finite-dimensional problems. Methods of nonlinear functional analysis, integral equations, spectral theory based on index of Kronecker-Poincare, Morse-Conley index, power geometry and other methods are employed. Proposed methodology enables justification of the theorems on existence of bifurcation points and bifurcation sets in the nonstandard models. Formulated theorems are constructive. For a certain smoothness of the nonlinear operator, the asymptotic behaviour of the solutions is analysed in the neighbourhood of the branch points and uniformly converging iterative schemes with a choice of the uniformization parameter enables the comprehensive analysis of the problems details. General theorems are illustrated on the nonlinear integral equations.

We ascertain the in vitro Benznidazole (BZN) and Nifurtimox (NFX) susceptibility pattern of epimastigotes, trypomastigotes, and amastigotes of 21 T. cruzi strains, from patients, reservoir and triatomine bugs of various geographic origin. Using this panel of isolates, we compute the Epidemiological cut off value (CO_wt). Then, the frequency of the susceptible phenotype (Wild type) towards BZN and nifurtimox (NFX) within this set of strains belonging to 3 discrete typing units (DTUs), TcI, TcII, and TcV was deduced. We have observed that the susceptibility status of individual T. cruzi isolates toward BZN and NFX is related to the genetic background and to underlying factors probably related to the individual life trait history of each strain. Analyzing drug susceptibility in this conceptual framework would offers the possibility to evidence a link between isolates expressing a low susceptibility level (not wild-type) as define by the CO_wt value and none-curative treatment. It will also permit to tract drug-resistant parasites in T. cruzi population.

This study focuses on the modification of ion-exchange membranes by incorporating phosphorylated dendrimer into sulfonated polytetrafluoroethylene membranes to enhance specific selectivity between mono-/divalent ions, using the Ca2+/Na+ pair as an example. The research employs mechanical, physico-chemical, and electrochemical analyses to explore the effects of P-H20 incorporation on membrane properties. Bulk modification significantly increases membrane selectivity towards calcium ions (specific permselectivity coefficient rises from 1.5 to 7.2), while maintaining the same level of the limiting current density. Other findings indicate that bulk modification significantly changes the transport-channel structure of the membrane and alters the mechanism of over-limiting mass transfer. The over-limiting current for the pristine membrane is mainly due to non-equilibrium electroconvection, while modified membranes actively participate in the water-splitting reaction, leading to the suppression of the electroconvection. Despite this drawback, the decrease of the over-limiting potential drop results in a decrease in specific energy consumption from 0.11 to 0.07 kWh/mol. In the under-limiting current mode, the specific energy consumption for all studied membranes remains within the same limits of 0.02-0.03 kWh/mol.

The production and N-glycosylation of recombinant human butyrylcholinesterase (BChE), a model highly glycosylated therapeutic protein, in a transgenic rice cell suspension culture treated with kifunensine, a strong α-mannosidase I inhibitor, was studied in a 5 L bioreactor. A media exchange was performed at day 7 of cultivation by removing spent sugar rich media (NB+S) and adding fresh sugar free (NB-S) media to induce the rice α-amylase 3D (RAmy3D) promoter to produce rice recombinant human BChE (rrBChE). Using a 1.25X concentrated sugar-free medium together with an 80% reduced working volume during the media exchange lead to a total active rrBChE production level of 79 ± 2 µg (g FW)^-1 or 7.5 ± 0.4 mg L^-1 in the presence of kifunensine, which is 1.5-times higher than our previous bioreactor runs using normal sugar free medium with no kifunensine treatment. Importantly, the amount of secreted active rrBChE in culture medium was enhanced in the presence of kifunensine, comprising 44% of the total active rrBChE at day 5 post-induction. Coomassie stained SDS-PAGE gel and Western blot analyses reveal different electrophoretic migration of purified rrBChE bands with and without kifunensine treatment, which is attributed to different N-glycoforms. N-Glycosylation analysis shows substantial increase of oligomannose glycans (Man5/6/7/8) in rrBChE treated with kifunensine compared to controls. However, mass transfer limitation of kifunensine is likely the major reason for incomplete inhibition of α-mannosidase I in this bioreactor study.

The structural evolution and phase composition of multi-block thermoplastic polyurethanes, with different nature of the soft segments based on poly(butylene adipate) (PBA), were analyzed during in-situ thermal treatments. A combination of synchrotron small- and wide-angle X-ray scattering, differential scanning calorimetry, thermogravimetric analysis, and FTIR spectroscopy was used to determine the influence of macrodiol nature and crystallization conditions on the polymorphic behavior of PBA. Using a new synthesis scheme, a relatively high degree of crystallinity for urethane blocks was achieved, which depends on the diisocyanate type in the structure of the soft segment. The hard segment domains impose geometrical constraints on PBA, thereby altering its crystallization process compared to the neat oligomer. Thus, crystallization after annealing at a low temperature (80 °C) is fast, predominantly yielding a metastable β-phase. When heated to 180 °C, which is higher than the hard-segment melting temperature, a phase-separated structure is observed. Subsequent crystallization is slower, favoring the formation of the stable α-PBA modification. The phase separation can be observed even after the hard block melting. A notably slow crystallization from an isotropic melt was documented after the disruption of phase separation at 230 °C.

An aneurysm is a vascular malformation, it can be classified according to its location (cerebral, aortic); and according its shape (saccular, fusiform, and mycotic). The study of blood flow interaction with the aneurysms has gained attention from physicists an engineers in recent years. Shear stresses, oscillatory shear index (OSI), gradient oscillatory number (GON), and residence time had been used as potential variables to describe the hemodynamics as well as the origin and evolution of aneurysm. However, the causes of aneurysms and the hemodynamics conditions that promote the growth of these structures are still under debate. The present work presents numerical simulation on three aneurysms: 2 aortic and 1 cerebral. The results shows that the blood rheology is not relevant for aortic aneurysms, however, for cerebral aneurysm could play a relevant role in the hemodynamics. The turbulence models evaluated show equivalent results in both cases. Lastly, a simulation considering the fluid-structure interaction (FSI) shows that this phenomenon is the dominant factor for aneurysms simulation.

Human influenza A viruses (IAVs) cause global pandemics and epidemics, which remain serious threats to public health because of the shortage of effective means of control. To combat the surge of viral outbreaks, new treatments are urgently needed. Developing new virus control modalities requires better understanding of virus-host interactions. Here we describe how IAV infection triggers cellular apoptosis, and how this process can be exploited towards development of new therapeutics, which might be more effective than the currently available anti-influenza drugs.

Background: The use of antitussives is a crucial issue in pediatrics and can lead to respiratory complications that can affect the prognosis. Objectives: to determine the frequency of respiratory complications associated with the use of an-titussives in pediatrics in a remote city in the Democratic Republic of Congo. Method: This is a cross-sectional retrospective study conducted between January 1, 2017 and De-cember 2022. Patients under 12 years of age with an acute cough were eligible. The parameters studied were treatment with cough suppressants and associated respiratory complications. Results: A total of 218 children suffered from an acute cough. The average age was 11 months 10, the sex ratio (H/F) was 126/92. In 30% of cases, children were treated with cough suppressants for an average of 7 days prior to admission. Respiratory complications were observed in 11% (23/218) of cases. The majority of these complications, 61% (14 of 23), had received antitussive treatment prior to hospitalization. Respiratory complications were associated with cough medications (p-value = 0.0012, relative risk (RR) = 3.66, IC90 [1.696; 7,873]). Acute respiratory distress was reported in 87% (20/23) of cases and was associated with the use of cough suppressants (p-value = 0.0065, RR: 3.060, IC90: [1.433; 6,485]). Conclusion: The use of antitussives in pediatrics poses a risk of acute respiratory distress in a remote city that does not have sufficient human and material resources for management. Keywords: cough, cough suppressants, pediatrics, complications, Mbujimayi, Democratic Republic of Congo.

This study explores the potential of using a Siamese Network as a biomarker for assessing the effectiveness of Dolphin-Assisted Therapy (DAT) in children with Cerebral Palsy (CP). The problem statement revolves around the need for objective measures to evaluate the impact of DAT on patients with CP, considering the subjective nature of traditional assessment methods. The methodology involves training a Siamese network, a type of neural network designed to compare similarities between inputs, using data collected from CP patients undergoing DAT sessions. The network is trained to learn patterns and similarities between pre- and post-therapy evaluations, in order to identify biomarkers indicative of therapy effectiveness. Notably, the Siamese Network’s architecture ensures that comparisons are made within the same feature space, allowing for more accurate assessments. The results of the study demonstrate promising findings, indicating different patterns in the output of the Siamese Network that correlate with improvements in symptoms of CP post-DAT. These findings suggest the potential utility of the Siamese Network as a biomarker to monitor therapy outcomes in children with CP who undergo DAT, offering a more objective and quantifiable approach to assessing therapeutic interventions. Significant disparities in neuronal voltage perturbations, with a mean of 7.9825 dB in specific samples compared to 6.2838 dB in the data set, indicate a marked difference from resting activity. This suggests that dolphin-assisted therapy selectively activates specific brain regions uniquely during the intervention.

This article introduces a new physically based Lyapunov function difinition, which can be used as acoustic energy for finite amplitude pressure oscillations in reacting systems especially in combustion chambers. Reacting flow is seen as an open, non-equilibrium (parameters are distributed unevenly locally) thermodynamic system. This Lyapunov function is defined as the maximum mechanical work, which could be extracted by a heat engine from studied system, if this system would be disconnected from inlet and outlet and from any other surrounding environment, and the engine could transfer to the surrounding environment only mechanical work.

This study assessed bio-equivalence of high-quality, plant-based protein blends versus Whey Protein Isolate (WPI) in healthy, resistance-trained men. The primary endpoint was incremental area under the curve (iAUC) of blood essential Amino Acids (eAAs) 4 hours after consumption of each product. Cmax and Tmax of blood leucine were secondary outcomes. Subjects (n=18) consumed three plant-based protein blends and WPI (control). Analysis of Variance model was used to assess for bio-equivalence of total sum of blood eAA concentrations. The total blood eAA iAUC ratios of the three blends were: [90% CI]: #1: 0.66 [0.58-0.76]; #2: 0.71 [0.62-0.82]; #3: 0.60 [0.52-0.69], not completely within the pre-defined equivalence range [0.80-1.25], indicative of 30-40% lower iAUC versus WPI. Leucine Cmax of the three blends was not equivalent to WPI, #1: 0.70 [0.67-0.73]; #2: 0.72 [0.68-0.75]; #3: 0.65 [0.62 – 0.68], indicative of a 28-35% lower response. Leucine Tmax for two blends were similar to WPI (#1: 0.94 [0.73-1.18]; #2: 1.56 [1.28-1.92]; #3: 1.19 [0.95-1.48]). The plant-based protein blends were not bio-equivalent. However, blood leucine kinetic data across the blends approximately doubled from fasting concentrations whereas blood Tmax data across two blends was similar to WPI. This suggests evidence of rapid hyperleucinemia, which correlates with a protein’s anabolic potential.

Background and Objective: Type 2 diabetes mellitus (DM2) and breast cancer (BC) are diseases of high prevalence worldwide. Both alter lung function separately. So suffering both tables would increase this decrease in lung function. The objetive was to determine the effects of DM2 and BC on ventilation volumes and pressures in adult women. Material and Methods: Forty-two women patients were recruited, of whom 40 were accepted under the exclusion criteria. They were divided into four groups: control group (CG), DM2, BC and DM2+BC. Body plethysmography was used to measure forced vital capacity, lung volumes, airway resistance and muscle pressures. Finally the normality of the data was determined using Student's t test or the Mann-Whitney U test; the threshold of significance was p<0.05. Results: No significant differences were observed in the anthropometric variables between the control group and the other groups. The ventilation flows showed no significant differences, while the lung volumes presented significant differences in the inspiratory capacity (IC) variables (p<0,002). Maximum inspiratory and expiratory pressures (MIP-MEP) also presented significant diminution (p<0,001; p<0,041, respectively). Conclusions: From the results obtained we can conclude that the combination of type 2 diabetes mellitus with breast cancer caused a diminution in ventilation volumes and pressures, specifically in IC, MIP and MEP.

Biocides used in antifouling (AF) paints, such as 4,5-dichlorine-2-n-octyl-4-isothiazole-3-one (DCOIT), can gradually leach into the environment. Some AF compounds can persist in the marine environment and cause harmful effects on non-target organisms. Nanoengineered materials, such as mesoporous silica nanocapsules (SiNC) containing AF compounds, have been developed to control their release rate and reduce their toxicity to aquatic organisms. This study aimed to evaluate the acute toxicity of new nanoengineered materials, SiNC-DCOIT and a silver-coated form (SiNC-DCOIT-Ag), as well as the free form of DCOIT and empty nanocapsules (SiNC), on the sun coral Tubastraea coccinea. T. coccinea is an invasive species and can be an alternative test organism for evaluating the risks to native species, as most native corals are currently threatened. The colonies were collected from the Alcatrazes Archipelago, SP, Brazil, and acclimatized to laboratory conditions. They were exposed for 96h to different concentrations of the tested substances: 3.33, 10, 33, and 100 µg L-1 of free DCOIT; 500, 1000, 2000, and 4000 µg L-1 of SiNC; and 74.1, 222.2, 666.7, and 2000 µg L-1 of SiNC-DCOIT and SiNC-DCOIT-Ag. The test chambers consisted of 500 mL flasks containing the test solutions, and the tests were maintained under constant aeration, constant temperature of 23 ± 2°C, and photoperiod of 12h:12h (light/dark). At the end of the experiments, no lethal effect was observed; however, some sublethal effects were noticeable, such as the exposure of the skeleton in most of the concentrations and replicates, except for the controls, and embrittlement at higher concentrations. Adults of T. coccinea were considered little sensitive to the tested substances. This resistance may indicate a greater capacity for proliferation of the species, which is favored in substrates containing antifouling paints, to the detriment of the native species.

Phlebotomus (Paraphlebotomus) sergenti Parrot, 1917, the proven vector of Leishmania tropica Wright, 1903, the causative agent of anthroponotic cutaneous leishmaniasis, is widely distributed in Morocco. Previous works using molecular markers (ITS2 rDNA and Cyt b mtDNA) have hy-pothesized the existence of multiple closely related populations of sandfly species (cryptic species) that would exhibit distinct vectorial capacities. In this work, descriptive characteristics of wings (size and shape of the right and left wings) were measured in samples collected from fourteen sta-tions in central Morocco. These analyses support the existence of distinct P. sergenti populations, enlightening significant phenotypic variations of P. sergenti’s wings, regarding their size and shape, depending on geographic origin. In addition, geomorphometric analyses of wing’s length, centroid size, alpha, and beta distances allowed clear discrimination of P. sergenti sub-populations. These data pinpoint the adaptative ability of P. sergenti to local environmental conditions. Additional studies are now required to further shed light on the genetic structure of P. sergenti populations in Morocco.

The gut microbiota plays a crucial role in maintaining host health and has a significant impact on human health and disease. In this study, we investigated the alpha diversity of gut microbiota in COVID-19 patients and analyzed the impact of COVID-19 variants, antibiotic treatment, type 2 diabetes (T2D), and metformin therapy on gut microbiota composition and diversity. We used a culture-based method to analyze the gut microbiota and calculated alpha-diversity using the Shannon H' and Simpson 1/D indices. We collected clinical data, such as length of hospital stay (LoS), C-reactive protein (CRP) levels, and neutrophil-to-lymphocyte ratio (NLR). We found that patients with T2D had significantly lower alpha-diversity than those without T2D. Antibiotic use was associated with a reduction in alpha-diversity, while metformin therapy was associated with an increase. We did not find significant differences in alpha-diversity between the Delta and Omicron groups. Length of hospital stay, CRP levels, and NLR showed weak to moderate correlations with alpha diversity. Our findings suggest that maintaining a diverse gut microbiota may benefit COVID-19 patients with T2D. Interventions aimed at preserving or restoring gut microbiota diversity, such as avoiding unnecessary antibiotic use and promoting metformin therapy, may improve patient outcomes.

Melt mixing is a convenient method to prepare polymer nanocomposites, but the extent of the dispersion of the solid filler reached is often limited, and may compromise the anticipated performance of these materials during service. Since the efficiency of extensional flows on dispersion is now well recognized, several mixers were designed with the aim of inducing both shear and extensional flow components. This work combines experimental and numerical data to better understand the kinetics of the dispersion of graphite nanoplates in a polypropylene melt, using a mixing device that consists of a series of stacked rings with equal outer diameter and alternating larger and smaller inner diameters, thus creating a series of converging/diverging flows. Numerical simulation of the flow using the opensource OpenFOAM software assuming both inelastic and viscoelastic responses predicted the velocity, streamlines, flow type and shear and normal stress fields for the mixer. Experimental and computed data were combined to determine the trade-off between the local degree of dispersion of the PP/GnP nanocomposite, measured as Area ratio, and the absolute average value of the hydrodynamic stresses multiplied by the local cumulative residence time. From considerations based on a theoretical approach to dispersion, the cohesive strength of the GnP agglomerates studied was estimated to be in the range 3 - 10kPa.

The solid particle erosion at room and elevated temperatures of pure and filled hot-curing epoxy resin on anhydride hardener was experimentally tested using accelerated method on special bench. Micro-sized dispersed industrial wastes were used as fillers: fly-ash from a power plant and spent filling material from a copper mining and processing plant. The results showed that the unfilled resin wear significantly decreases with increasing temperature, while the dependence on the temperature of the wear intensity at an impingement angle of 45o is linear inversely proportional, and at an angle of 90o non-linear. The decrease in wear intensity is probably due to an increase in elasticity (an increase in the fracture strain limit) because of heating. Solid particle erosion of the examined filled epoxy compounds is considerably higher than that of unfilled compounds at impingement angles of 90o and 45o. Filled compounds showed ambiguous dependences of intensity of wear from temperature (especially at an angle of attack 45o), probably, character of dependence is defined by a filler share and the structural features of the samples caused by distribution of particles of the filler. Intensity of wear of the considered compounds at impingement angles 90o and 45o has high direct correlation with density and the modulus of elasticity (i.e., increases with their increase), and low correlation with bending strength of the considered materials. The data set for determining the correlation between mechanical properties and wear included characteristics due to both compound filling and test temperature.

Non-Linear Simulation by Harmonic Balance Techniques of Load Modulated Power Amplifier Driven by Random Modulated Signals. Comparison with measured results.

The paper presents a method for estimating the inertia tensor components of a spacecraft that has expired its active life using measurement data of the Earth's magnetic field induction vector components. The implementation of this estimation method is supposed to be carried out when cleaning up space debris in the form of a clapped-out spacecraft with the help of a space tug. It is assumed that a three-component magnetometer and a transmitting device are attached on space debris. With the help of this measuring system, the parameters for the rotational motion of space debris are estimated. Then the known controlled action from the space tug is transferred to the space debris. Next, measurements for the rotational motion parameters are carried out once again. Based on the available measurement data and parameters of the controlled action, the space debris inertia tensor components are estimated. It is assumed that the measurements of the Earth's magnetic field induction vector components are made in a coordinate system which axes are parallel to the corresponding axes of the main body axis system. Such an estimation makes it possible to effectively solve the problem of cleaning up space debris, to calculate the costs of the space tug working body and the parameters of the space debris removal orbit. Examples of numerical simulation using the measurement data of the Earth's magnetic field induction vector components on the Aist-2D small spacecraft are given. The results of the work can be used in the development and implementation of missions to clean up space debris in the form of clapped-out spacecraft.

In this paper, the characterization of 3D printed materials that are considered in the design of multirotor unmanned aerial vehicles (UAVs) for specialised purposes was carried out. The multirotor UAV system is briefly described, primarily from the aspect of system dynamics, considering that the airframe parts connect the UAV components, including the propulsion configuration, into a functional assembly. Three additive manufacturing (AM) technologies were discussed, and a brief overview was given of selective laser sintering (SLS), fused deposition modeling (FDM), and continuous fiber fabrication (CFF). Using hardware and related software, 12 series of specimens were produced which were experimentally tested utilizing a quasi-static uniaxial tensile test. The results of the experimental tests are given graphically with displacement-force characteristics. In this work, the focus is on CFF technology and the testing of materials that will be used in the production of mechanically loaded airframe parts of multirotor UAVs. Furthermore, an overview was given in such a way that the specimens were grouped, and the mean values of the maximum stress were presented, so that the tested materials could be more easily compared with conventional materials, such as aluminum alloys.

In this paper, a multirotor UAV platform based on the PX4 ecosystem was discussed, which in combination with the MATLAB Simulink programming environment enables utilization in various aspects of mechatronic engineering education. Extensive testing of the UAV platform control module was performed, in order to enable implementation in engineering education. In the design phase of the educational platform, take-off-the-shelf components were selected and tested, and airframe parts were manufactured using rapid prototyping technologies. The proposed educational platform with four rotors was presented and tested. The learning outcomes of the undergraduate mechatronics professional study program according to the Croatian Qualifications Framework and related to the considered platform are shown. A preliminary framework of laboratory exercises for the field of mechatronic systems control is investigated.

The Bayer process is the maim method of alumina production worldwide. The use of low-quality bauxites for alumina production results in the formation of a significant amount of technogenic waste - bauxite residue (BR). The Bayer reductive method is one possible way to eliminate BR stockpiling, but it requires high-pressure leaching at temperatures higher than 220 °C. In this research, the possibility of boehmitic bauxite atmospheric pressure leaching at both the first and second stages or high-pressure leaching at the second stage with the simultaneous reduction of hematite was investigated. Bauxite and solid residue after NaOH leaching were characterized using XRD, SEM-EDS, and Mössbauer spectroscopy methods. The first stage of leaching under atmospheric pressure with the addition of Fe(II) species in a strong alkali solution (330-400 g L–1 Na2O) results in a partial reduction of the iron minerals and an extraction of more than 60% of Si and 5-25% of Al (depending on caustic modulus of solution) after 1 h. The obtained desilicated bauxite was subjected to atmospheric leaching at 120 °C in a strong alkali solution (350 g L-1) or high-pressure leaching at 160-220 °C using the Bayer process mother liquor in order to obtain a concentrate with a magnetite content higher than 83 wt. %.

The phenomenon of coupling between light and surface plasmon polaritons requires specific momentum matching conditions. In the case of a single scattering object on a metallic surface, like a nanoparticle or a nanohole, the coupling between a broadband effect, i.e. scattering, and a discrete one such as surface plasmon excitation, leads to Fano-like resonance lineshapes. The necessary phase matching requirements can be used to engineer the light-plasmon coupling and to achieve a directional plasmonic excitation. Here we investigate this effect by using a chiral nanotip to excite surface plasmons with a strong spin-dependent azimuthal variation. This effect can be described by a Fano-like interference with a complex coupling factor that can be modified thanks to a symmetry breaking of a nanostructure.

Tolerogenic dendritic cells are crucial to control development of autoreactive T cell responses and prevention of autoimmunity. We have reported that NOD.CD11cStat5b-CA transgenic mice expressing a constitutively active form of Stat5b under the control of CD11c promoter are protected from diabetes and that Stat5b-CA-expressing DCs are tolerogenic and halt ongoing diabetes in NOD mice. However, the molecular mechanisms by which Stat5b-CA modulates DC tolerogenic function is not fully understood. Here, we used bone marrow-derived DCs from NOD.CD11cStat5b-CA transgenic mice (Stat5b-CA.BMDC) and found that Stat5b-CA.BMDC displayed high levels of MHC class II, CD80, CD86, PD-L1 and PD-L2 and produced elevated amounts of TGFβ but low amounts of TNF and IL-23. Stat5b-CA.BMDCs upregulated Irf4 and downregulated Irf8 genes and protein expression and promoted CD11c+CD11b+ DC2 subset differentiation. Interestingly, we found that the histone methyltransferase Ezh2 interacted with Stat5b-CA complex that bound GAS sequences in the Irf8 enhancer whereas Ezh2 did not interact with GAS sequences in the case of the Irf4 promoter. Injection of Stat5b-CA.BMDCs to prediabetic NOD mice halted progression of islet inflammation and protected against diabetes. Importantly, inhibition of Ezh2 in tolerogenic Stat5b-CA.BMDCs reduced their ability to prevent diabetes development in NOD recipient mice. Taken together, our data suggest that the active form of Stat5b induces tolerogenic DC function by modulating IRF4 and IRF8 expression through recruitment of Ezh2 and highlight the fundamental role of Ezh2 in Stat5b-mediated induction of tolerogenic DCs function.

Proper species identification from ancient DNA samples is a difficult task that sheds light on the evolutionary history of pathogenic microorganisms. The field of palaeomicrobiology has undoubtedly benefited from the advent of untargeted metagenomic approaches that use next-generation sequencing methodologies. Nevertheless, assigning ancient DNA at the species level is a challenging process. Recently, the gut microbiome analysis of three pre-Columbian Andean mummies [1](Santiago-Rodriguez et al. 2016) has called into question the identification of Leishmania in South America. Here, the metagenomic data filed in MG-RAST (Metagenomics RAST server) were used for a further attempt to identify members of the Trypanosomatidae family infecting these ancient remains. For this purpose, we used two metagenomic analysis tools. In the first step, data were analysed using the ultrafast metagenomic sequence classifier, based on exact alignment of k-mers (Kraken). In the second step, we used Bowtie2, an ultrafast and memory-efficient tool for aligning sequencing reads to long reference sequences. We then compared the output results. These approaches highlight some interesting findings on potential infections by human pathogenic trypanosomatids in these three pre-Columbian mummies.

: AlF3 has interesting electrophysical properties, due to which the material is promising for applications in supercapacitors, UV coatings with low refractive index, excimer laser mirrors, and photolithography. The formation of AlF3-based nano- and micro-wires can bring new functionalities to AlF3 material. AlF3 nanowires be used, for example, in functionally modified microprobes for scanning probe microscopy. In this work, we investigate the AlF3 samples obtained by the reaction of initial aluminum with aqueous hydrofluoric acid solution of different concentrations. All the samples were obtained under normal conditions. The morphology of the nanowire samples is studied by scanning electron microscopy. Quantitative energy-dispersive x-ray spectroscopy (EDS) spectra are obtained and analyzed with respect to the feedstock and each other.

: AlF3 has interesting electrophysical parameters, due to which the material is promising for applications in supercapacitors, UV coatings with low refractive index, excimer laser mirrors, and photolithography. The formation of AlF3-based nano- and micro-wires can bring new functionalities to AlF3 material. AlF3 nanowires be used, for example, in functionally modified microprobes for scanning probe microscopy. In this work, we investigate the AlF3 samples obtained by the reaction of initial aluminum with aqueous hydrofluoric acid solution of different concentrations. All the samples were obtained under normal conditions. The morphology of the nanowire samples is studied by scanning electron microscopy. Quantitative energy-dispersive x-ray spectroscopy (EDS) spectra are obtained and analyzed with respect to the feedstock and each other.

Oligo- and polyesters of polyglycerol and polyricinoleic acid are widely used as emulsifiers in various industries. Based on the condensation of glycerol and its oligomers with epoxidized derivatives of vegetable oils, new promising emulsifiers for oil-water systems were obtained. Complex structural and functional spectral analysis of synthesized substances showed that the main reactions leading to the formation of the desired products were the opening of epoxide cycles, the transesterification of esters and the condensation of fatty acid derivatives. The new combination of renewable raw materials is of undoubted interest for deeper vegetable oils chemical processing.

Pipeline integrity is an important area of concern for the oil and gas, refining, chemical, hydrogen, carbon sequestration, and electric-power industries, due to the safety risks associated with pipeline failures. Regular monitoring, inspection, and maintenance of these facilities is therefore required for safe operation. Large standoff magnetometry (LSM) is a non-intrusive, passive magnetometer-based mea- surement technology that has shown promise in detecting defects (anomalies) in regions of elevated mechanical stresses. However, analyzing the noisy multi-sensor LSM data to clearly identify regions of anomalies is a significant challenge. This is mainly due to the high frequency of the data collection, mis-alignment between consecutive inspections and sensors, as well as the number of sensor measurements recorded. In this paper we present LSM defect identification approach based on ma- chine learning (ML). We show that this ML approach is able to successfully detect anomalous readings using a series of methods with increasing model complexity and capacity. The methods start from unsupervised learning with "point" methods and eventually increase complexity to supervised learning with sequence methods and multi-output predictions. We observe data leakage issues for some methods with randomized train/test splitting and resolve them by specific non-randomized splitting of training and validation data. We also achieve a 200x acceleration of support-vector classifier (SVC) method by porting computations from CPU to GPU leveraging the cuML RAPIDS AI library. For sequence methods, we develop a customized Convolutional Neural Network (CNN) architecture based on 1D convolutional filters to identify and characterize multiple properties of these defects. In the end, we report the scalability of the best-performing methods and compare them, for viability in field trials.

One of the possible mechanisms causing significant emissions of methane into the atmosphere within the Arctic shelf may be the decomposition of gas hydrates. Their accumulations within the Arctic shelf formed during Ice Age almost simultaneously with the formation of permafrost, which contributed to the emergence of a zone of stable existence of gas hydrates. The subsequent flooding of the Arctic shelf led to the degradation of the permafrost and the violation of the conditions for the existence of hydrates. To assess the state of the stability zone, methods of mathematical numerical modeling are used. Standard seismic methods are widely used to localize gas hydrates, but monitoring their physical state requires the development of fundamentally new approaches based on solving multiparameter inverse seismic problems. In particular, the degree of attenuation of seismic energy is one of the objective parameters for assessing the consolidation of gas hydrates: the closer they are to the beginning of decomposition, the higher the attenuation, and hence the lower the quality factor. Thus, the methods of seismic monitoring of the state of gas hydrates in order to predict the possibility of developing dangerous scenarios should be based on solving a multi-parameter inverse seismic problem. This publication is devoted to the presentation of this approach.

Since smart cities aim at becoming self-monitoring and self-response systems, their deployment relies on close resource monitoring through large-scale urban sensing. The subsequent gathering of massive amounts of data makes essential the development of event filtering mechanisms that enable the selection of what is relevant and trustworthy. Due to the rise of mobile event producers, location information has become a valuable filtering criterion as it not only offers extra information on the event described but also enhances trust on the producer. Implementing mechanisms that validate the quality of location information becomes then imperative. The lack of such strategies in cloud architectures compels the adoption of new communication schemes for IoT-based urban services. To serve the demand for location verification in urban event-based systems (DEBS), we have designed three different fog architectures that combine proximity and cloud communication. Moreover, we have successfully assessed their performance using network simulations with realistic urban traces.

Lathyrane-type diterpenes have a wide range of biological activities. Among them, euphoboetirane A (1) exerts neurogenesis-promoting activity. In order to increase the structural diversity of this type of lathyranes to explore their potential use in neurodegenerative disorders, the biotransformation of 1 by Streptomyces puniceus BC-5GB.11 has been investigated. The strain BC-5GB.11, isolated from surface sediments collected from the intertidal zone of the inner Bay of Cadiz, was identified as Streptomyces puniceus, as determined by phylogenetic analysis using 16S rRNA gene sequence. Biotransformation of 1 by BC-5GB.11 afforded five products (3-7), all of them reported here for the first time. The main biotransformation pathways involved regioselective oxidation at non-activated carbons (3-5) and isomerization of the D^12,13 double bond (6). In addition, a cyclopropane-rearranged compound was found (7). The structures of all compounds were elucidated on the basis of extensive NMR and HRESIMS spectroscopic studies.

ZnO films with Ti atoms incorporated (TZO) in a wide range (0-18 at. %) have been grown by reactive co-sputtering on silicon and glass substrates. The influence of the titanium incorporation in the ZnO matrix on the structural and optical characteristics of the samples has been determined by Rutherford backscattering spectroscopy (RBS), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD). The results indicate that the samples with low Ti content (< 4 at. %) exhibit the wurtzite-like structure, with the Ti+4 ions substitutionally incorporated into the ZnO structure, forming Ti-doped ZnO films. In particular, very low concentration of Ti (<0.9 at. %) leads to a significant increase of the crystallinity of the TZO samples. Higher Ti contents give rise to a progressive amorphization of the wurtzite-like structure so samples with high Ti content (≥18at. %), displays an amorphous structure indicating the XPS analysis a predominance of Ti-O-Zn mixed oxides. The energy gap, obtained from absorption spectrophotometry, increases from 3.2 eV for pure ZnO films to 3.6 eV for those with the highest Ti content. Ti incorporation in the ZnO samples below 0.9 at. % rises both, the blue (380 nm) and green (550 nm) bands of the photoluminescence (PL) emission, thereby indicating a significant improvement of PL efficiency of the samples.

Abstract: Agarose is known to form a homogeneous thermoreversible gel in aqueous medium over a critical polymer concentration. The solid-liquid phase transitions are thermoreversible but depend on the molecular structure of the agarose sample tested. Then, in a first step, the structure was characterised by 1H and 13C NMR in D2O and in DMSO which is a solvent of agarose whatever the temperature. A low yield in methyl substituent on the D-galactose unit was determined. Then, evolution of the 1H NMR spectrum was followed as a function of temperature in increasing and decreasing temperature process from 25 to 80°C. A large thermal hysteresis is obtained and discussed. It helps to interpret rheological behaviour. In fact, NMR signals are related to proton relaxation and especially to proton involved in H-bonds between water and -OH agarose for tightly bound water and agarose/agarose in chain packing. In a second step, water was exchanged against ethanol which is a non solvent of agarose. A stable gel was demonstrated and characterised by rheology to be compared with aqueous behaviour. Bound water playing the role of plasticizer is probably removed and the gel is much stronger (and brittle) in ethanol with a larger thermal stability. It is the first time that such gel is characterised without phase transition when passing from a good-solvent to a non-solvent. This extends the domains of application of agarose.

This study presents the design and implementation of a PLC microprocessor adhering to the IEC-61131-3 standard, executed on a Cyclone-V FPGA using a DE10-NANO development board. Our microprocessor optimizes the central processing unit by streamlining the data path, achieving a remarkable simulated response time of approximately 60 ns, equivalent to three clock cycles at a 50MHz frequency for Boolean operations. To substantiate our approach, we conducted practical experiments utilizing a FESTO conveyor station, employing relays as actuators, and incorporating optical and inductive sensors. The results underscore the feasibility of our proposed approach and serve as practical validation of its efficacy. This work introduces a promising avenue for the development of cost-effective PLCs employing SoC FPGA variants. Additionally, a thorough comparison of execution times with other early reported architectures. Our microprocessor outperforms even well-established PLCs like the S7-312, with substantial reductions in execution times of 94.54% for floating-point operations, 71.42% to 93.33% for word operations, and up to 78.57% for bit operations.

Background and objective: Addressing the global morbidity associated with pulmonary disease is an important need for the respiratory community. However, there is also a growing momentum to show the efficacy of new tools of diagnosis. Despite this, there are few physiotherapeutic tools that help identify and categorize these conditions. The aim was to analyze the variables of physiotherapy index of the ventilatory workload (PIVW) in people with chronic obstructive pulmonary disease (COPD) during stability and exacerbation in an outpatient setting. Material and Methods: Analyzed retrospectively of 198 clinical records were reviewed. The PIVW was extracted in stability and exacerbation of these patients with COPD. After applying the exclusion and inclusion criteria; 54 patients were classified. Through the statistical analysis of chi-square, a significant association was reported for each of the variables and the total PIVW score. Results: when analyzing the baseline with the peak of PIVW, there was a significant increase in patients COPD exacerbation. Similarly, the variables that constitute the loads, translations and supports underwent a significant increase from baseline to exacerbation (p<0.0001), except for the additional oxygen contribution, where the frequency of patients was the same in basal and exacerbation as well. Conclusions: the PIVW, serves to determine ventilatory problemas in outpatients, characterizing the specific changes of loads, translators or assistance.

This paper addresses the problem of non-cooperative spectrum sensing in very low signal noise ratio (SNR) conditions. In our approach, detecting an unoccupied bandwidth consists to detect the presence or absence of a communication signal on this bandwidth. Major well known communication signals may contain hidden periodicities, we use the Recurrence Quantification Analysis (RQA) to reveal the hidden periodicities. RQA is very sensitive to a reliable estimation of the phase space dimension m or the time delay τ. In view of the limitations of algorithms proposed in the literature, we have proposed a new algorithm to estimate simultaneously the optimal values of m and τ. The new proposed optimal values allow the states reconstruction of the observed signal and then the estimation of the distance matrix. This distance matrix has particular properties which we have exploited to propose the Recurrence Analysis based Detector (RAD). RAD can detect a communication signal in a very low SNR condition. Using Receiver Operating Characteristic curves, our experimental results corroborate the robustness of our proposed algorithm comparing to classical widely used algorithms.