Polar Mesospheric Summer Echoes (PMSEs) are radar echoes that are observed in the mesosphere during the Arctic summer months in the polar regions. By studying PMSE, researchers can gain insights into physical and chemical processes that occur in the upper atmosphere specifically in the 80 to 90 km altitude range. In this paper, we employ fully convolutional networks such as UNET and UNET++ for the purposes of segmenting PMSE from the EISCAT VHF dataset. First, experiments are performed to find suitable weights and hyperparameters for UNET and UNET++. Second, different loss functions are tested to find one suitable for our task. Third, as the number of PMSE samples used is relatively small that can lead to poor generalization. To address this, image-level and object-level augmentation methods are employed. Four, we briefly explain our findings by employing layerwise relevance propagation.

In this paper, we present a framework to study the spatial structure of noctilucent clouds formed by ice particles in the upper atmosphere at mid and high latitude during summer. We study noctilucent cloud activity in optical images taken from three different locations and under different atmospheric conditions. In order to identify and distinguish noctilucent cloud activity from other objects in the scene, we employ linear discriminant analysis (LDA) with feature vectors ranging from simple metrics to higher-order local autocorrelation (HLAC), and histogram of oriented gradients (HOG). Finally, we propose a Convolutional Neural Networks (CNN) based method for the detection of noctilucent clouds. The results clearly indicate that the CNN based approach outperforms LDA based methods used in this article. Furthermore, we outline suggestions for future research directions to establish a framework that can be used for synchronizing the optical observations from ground based camera systems with echoes measured with radar systems like EISCAT in order to obtain independent additional information on the ice clouds.

One of the oldest problems in physics is that of calculating the motion of N particles under a specified mutual force: the N-body problem. Much is known about this problem if the specified force is non-relativistic gravity, and considerable progress has been made by considering the problem in one spatial dimension. Here I review what is known about the relativistic gravitational N-body problem. Reduction to one spatial dimension has the feature that gravitational radiation is absent, thereby allowing for a clear comparison between the physics of one-dimensional relativistic and non-relativistic self-gravitating systems. After describing how to obtain a relativistic theory of gravity coupled to N point particles, I discuss in turn the 2-body, 3-body, 4-body, and N-body problems. Quite general exact solutions can be obtained for the 2-body problem, unlike the situation in general relativity in 3 spatial dimensions for which only highly specified solutions exist. The 3-body problem exhibits mild forms of chaos, and provides one of the first theoretical settings in which relativistic chaos can be studied. For N4 other interesting features emerge. Relativistic self-gravitating systems have a number of interesting problems awaiting further investigation, providing us with a new frontier for exploring relativistic many-body systems.

The Mann-Whitney effect is a measure for comparing survival distributions between two groups. The Mann-Whitney effect is interpreted as the probability that a randomly selected subject in a group survives longer than a randomly selected subject in the other group. Under the independence assumption of two groups, the Mann-Whitney effect can be expressed as the traditional integral formula of survival functions. However, when the survival times in two groups are not independent each other, the traditional expression of the Mann-Whitney effect has to be modified. In this article, we propose a copula-based approach to compute the Mann-Witney effect with parametric survival models under dependence of two groups, which may arise in the potential outcome framework. In addition, we develop a Shiny web app that can implement the proposed method via simple commands (https://nkosuke.shinyapps.io/shiny_survival/). Through a simulation study, we show the correctness of the proposed calculator. We apply the proposed methods to two real datasets.

In this work, we extend the fundamental results of Schu to the class of monotone asymptotically nonexpansive mappings in modular function spaces. In particular, we study the behavior of the Fibonacci-Mann iteration process defined by $$x_{n+1} = t_n T^{\phi(n)}(x_n) + (1-t_n)x_n,$$ for $n \in \mathbb{N}$, when $T$ is a monotone asymptotically nonexpansive self-mapping.

Field electron emission, or electron tunneling through a potential barrier under the influence of a strong electrostatic field, is of broad interest to the accelerator physics community. For example, it is the source of undesirable dark currents in resonant cavities, providing a limit to high-field operation. The classical approach to field electron emission is the Fowler-Nordheim (FN) framework, which incorporates a simplified surface potential and various assumptions. Here we build a more realistic model using the potential and charge densities derived from a density-functional theory (DFT) calculation. We examine the correction factors associated with each model assumption. Compared to the FN framework, our results can be extended up to 80 GV/m, a limit that has been reached in laser-induced strong field emission scenarios.

Evidence shows that weightloss improves insulin sensitivity but few studies have examined the effect of macronutrient composition independently of weight loss on direct measures of insulin sensitivity. We randomised 89 overweight or obese women to either a standard diet (StdD) that was intended to be low in fat and relatively high in carbohydrate (n=42) or to a relatively high protein (up to 30% of energy), relatively high fibre (>30g/day) diet (HPHFib) (n=47) for 10 weeks. Advice regarding strict adherence to energy intake goals was not given. Insulin sensitivity and secretion was assessed by a novel method - the Dynamic Insulin Sensitivity and Secretion Test (DISST). Although there were significant improvements in body composition and most cardiometabolic risk factors on HPHFib, insulin sensitivity was reduced by 19.3% (95% CI: 31.8, 4.5%; p=0.013) in comparison with StdD. We conclude that the reduction in insulin sensitivity after a diet relatively high in both protein and fibre, despite cardiometabolic improvements, suggests insulin sensitivity may reflect metabolic adaptations to dietary composition for maintenance of glucose homeostasis, rather than impaired metabolism.

Virtual reality (VR) can play a key role in automotive marketing research, lowering costs and shortening the time it takes to bring a new product to market. However, there are still few VR applications that support automotive customers' experiences during the early stages of product development. Through a systematic review of literature and patents, this study aims to identify the challenges and opportunities for the application of virtual reality in car clinics, and to categorize them into attributes. We searched through the knowledge databases of PatentScout, ScienceDirect, Springer, and IEEEXplore. We found 72 patents with a high concentration in a few inventors. The United States of America presented the greatest number of records and the most common applications related to the apparatus for automatically reading respondents' reactions in a virtual environment. In terms of articles, we found 19 research papers that discussed sixteen categories identified as challenges and opportunities for automotive marketing research: 1) cost, 2) location to customers, 3) flexibility in interactions, 4) model transportation, 5) depth perception, 6) haptic perception, 7) motion, 8) movement perception/ physical collision, 9) color and texture, 10) sound feedback, 11) product interaction/manipulation, 12) visual-spatial, 13) graphic quality, 14) intuitiveness, 15) cybersecurity and 16) cybersickness. We conclude that the automotive industry can employ virtual reality for marketing research, but relevant elements such as hardware and software definition, stimulus quality, and research objectives, among others, must be considered.

This study investigates the trend in monthly and annual rainfall, minimum and maximum temperature (T_min and T_max) using the Mann–Kendall (MK) test and Sen’s slope (SS) method and evaluates the significance of their variability for maize, sorghum and millet yields in northern Togo employing multiple regression analysis. The historical data of Kara, Niamtougou, Mango and Dapaong weather stations from 1977 to 2012 were used. Four non-parametric methods—Alexandersson’s Standard Normal Homogeneity Test (SNHT), Buishand’s Range Test (BRT), Pettitt’s Test (PT) and Von Neumann’s Ratio Test (VNRT)—were applied to detect homogeneity in the data. For the data which were serially correlated, a modified version of the MK test (pre-whitening) was utilised. Results showed an increasing trend in the annual rainfall in all four locations. However, this trend was only significant at Dapaong (p < 0.1). There was an increasing trend in T_max at Kara, Mango and Niamtougou, unlike Dapaong where T_max revealed a significant decreasing trend (p < 0.01). Similarly, there was an increasing trend in T_min at Kara, Mango and Dapaong, unlike Niamtougou where T_min showed a non-significant decreasing trend (p > 0.05). Rainfall in Dapaong was found to have increased (7.79 mm/year) more than the other locations such as Kara (2.20 mm/year), Niamtougou (4.57 mm/year) and Mango (0.67 mm). T_max increased by 0.13, 0.13 and 0.32 °C per decade at Kara, Niamtougou and Mango, respectively, and decreased by 0.20 per decade in Dapaong. Likewise, T_min increased by 0.07, 0.20 and 0.02 °C per decade at Kara, Mango and Dapaong, respectively, and decreased by 0.01 °C per decade at Niamtougou. Results of multiple regression analysis revealed nonlinear yield responses to changes in rainfall and temperature. Rainfall and temperature variability affects rainfed cereal crops production, but the effects vary across crops. The temperature has a positive effect on maize yield in Kara, Niamtougou and Mango but a negative effect on sorghum in Niamtougou and millet in Dapaong, while rainfall has a negative effect on maize yield in Niamtougou and Dapaong and millet yield in Mango. In all locations, rainfall and temperature variability has a significant effect on the cereal crop yields. There is, therefore, a need to adopt some adaptation strategies for sustainable agricultural production in northern Togo.

This work presents the first evidence that dissolved globular proteins change the arrangement of hydrogen bonds in water, with different proteins showing quantitatively different effects. Using ATR-FTIR (Attenuated Total Reflection – Fourier Transform Infrared) spectroscopic analysis of OH-stretch bands, we obtain quantitative estimates of the relative amounts of the previously reported four subpopulations of water structures coexisting in a variety of aqueous solutions. Where solvatochromic dyes can measure the properties of solutions of non-ionic polymers, the results correlate well with ATR-FTIR measurements. In protein solutions to which solvatochromic dye probes cannot be applied, NMR (Nuclear Magnetic Resonance) spectroscopy was used for the first time to estimate the hydrogen bond donor acidity of water. We found strong correlations between the solvent acidity and arrangement of hydrogen bonds in aqueous solutions for several globular proteins. Even quite similar proteins are found to change water properties in dramatically different ways.

Maker spaces can contribute significantly to the circular economy of cities: they demonstrate not only the economic potential of inner loop circularity, but also provide tangible evidence of spatial and social integration of production into the urban context. This paper presents findings from a typological analysis of 326 maker spaces in seven European cities, with a focus on selected exemplar case studies to reveal design characteristics, principles and opportunities for circular city development. The research shows that circular economy principles of ‘reduce-reuse-recyle’ are aligned with maker spaces such as repair cafés, secondhand shops and fab labs. In the context of cities, circularity is revealed by a spatial tightening of resource cycles that close the loops of product life cycles. Furthermore, urban maker spaces demonstrate social engagement and a relationship to local production which inherently includes maintenance, repair, reuse, and redistribution. This paper defines five maker typologies, presents exemplars of each from different urban contexts and posits hybrid design strategies for the transition to circular maker cities. Through the adoption of these findings into urban planning policy it is possible accelerate circular urban production and close the sustainability gap between small scale local and large scale regional manufacturing.

The coordination of policy, makers and materials is critical to the success of circular city development. The network of maker activities in the city of Leuven is a flagship initiative that illustrates the mechanisms that support integrated circular urban production. This paper draws on the Pop-Machina project, funded by EC Horizon 2020, which identifies the links between the maker movement and the circular economy in seven European cities. The case study project in Leuven, confirmed as the most impactful amongst those studied in the Pop-Machina project, is examined to assess how local knowledge and policy measures, can provide a means of activating a circular maker ecology. Through desk research, spatial urban analysis and interviews with key stakeholders, this paper provides a critical narrative of the development, success factors and hurdles related to circular making processes in the city. It demonstrates how hybrid makers are supported by local, national, and international policy on the one hand, and by integration with the city’s community, educational and business groups on the other. It is this constellation of social, political, and spatial conditions that lies at the success of the project.

Humans are incapable of judging the temporal order of visual events at brief temporal separations with perfect accuracy. Their performance---which is of much interest in visual cognition and attention research---can be measured with the temporal-order judgment task, which typically produces S-shaped psychometric functions. Occasionally, researchers reported plateaus within these functions, and some theories predict such deviation from the basic S shape. However, the centers of the psychometric functions result from the weakest performance at the most difficult presentations and therefore fluctuate strongly, leaving existence and exact shapes of plateaus unclear. This study set out to investigate whether plateaus disappear if the data accuracy is enhanced, or if we are ``stuck on a plateau'', or rather with it. For this purpose, highly accurate data were assessed by model-based analysis. The existence of plateaus is confidently confirmed and two plausible mechanisms derived from very different models are presented. Neither model, however, performs well in the presence of a strong attention manipulation, and model comparison remains unclear on the question which of the models describes the data best. Nevertheless, the present study includes the highest accuracy in visual TOJ data and the most explicit models of plateaus in TOJ studied so far.

The efficacy of the product development process is measured by the ability to launch a project with product and production process specifications that could guarantee that the manufacturing can produce it with the least impact. If a problem is detected late, they bring consequences beyond the high cost of the solution, if related to physical ergonomics, which will influence the well-being of operators, productivity, and quality. Virtual Reality (VR) and Digital Human Modeling (DHM) are ones of the enabling technologies of Industry 4.0 and has already been applied on a large scale in industries such as automotive, construction, and aeronautics. However, even though the huge applications, these technologies are not yet applied by these industries for the analysis of physical ergonomics during product development phases. This study aims to characterize the state of the art and technology about the application of Virtual Reality and Digital Human Modeling for the physical ergonomics analysis in the during product development phases in the industry through a systematic review of the literature and patents. In patent documents recovery, we used Derwent Innovation database. The research is based on searching the selected terms in the title, summary, and claims of the documents through a search strategy containing IPC code and keywords. In articles recovery, we searched ScienceDirect, Springer, and IEEExplore databases for scientific publications. The search resulted in 311 patents documents and 16 articles in the scientific database. This study analyzed the patents to map out the technological progress in this area, where we found in the charts and data an increasing number of publications per year and a spread application with a considerable number of new technologies presented in these recent patents. The literature review indicated that Virtual Reality technology complements the Digital Human Modeling during physical ergonomics analysis for manufacturing process already designed. The majority of research on the use of VR and DHM technologies for physical ergonomics analysis focus on the automotive industry and the ergonomic assessment of workstations and current processes. Further research is needed to investigate how Virtual Reality and Digital Human Modeling might assist in the understanding of physical ergonomics in certain tasks throughout the product development process, such as the simulation of worker posture or effort when assembling parts.

The COVID-19 pandemic has struck educational experience systems around the globe. This paper investigates and evaluates the student participants’ perceptions who joined the international exchange seminar on global citizenship and peace held at a University in Hiroshima, Japan. Approximately seventy students and faculty members from nine to ten different universities from around the globe joined this summer program in August 2021 (online) and 2022 (face-to-face). This study is a mixed-method study. The first part consists of a quantitative analysis of BEVI data obtained from the students in the seminar before COVID-19 and after. The research concludes that there are no changes in the way students learn. The second part consists of qualitative data. This data shows the perceptions of students of online teaching versus hybrid teaching. It compares the differences in participants’ perceptions reported in students’ feedback on the programs during and post-COVID-19. Our results confirm prominent differences exist in the students’ perceptions of their learning experience during the pre-pandemic and post-pandemic periods. The findings of this study suggest that universities need to strive and define a meaning and purpose of international seminars, which enables students to experience a high level of intercultural social interaction face-to-face.

Respiratory Syncytial Virus (RSV) causes severe inflammation and airway pathology in children and the elderly by infecting the epithelial cells of the upper and lower respiratory tract. RSV replication is sensed by intracellular pattern recognition receptors upstream of the IRF and NF-B transcription factors. These proteins coordinate an innate inflammatory response via Bromodomain containing protein 4 (BRD4), a protein that functions as a scaffold for unknown transcriptional regulators. To better understand the pleiotropic regulatory function of BRD4, we examine the BRD4 interactome and identify how RSV infection dynamically alters it. To accomplish these goals, we leverage native immunoprecipitation and Parallel Accumulation – Serial Fragmentation (PASEF) mass spectrometry to examine BRD4 complexes isolated from human alveolar epithelial cells in the absence or presence of RSV infection. In addition, we explore the role of BRD4’s acetyl-lysine binding bromodomains in mediating these interactions by using a highly selective competitive bromodomain inhibitor. We identify 101 proteins that are significantly enriched in the BRD4 complex and are responsive to both RSV-infection and BRD4 inhibition. These proteins are highly enriched in transcription factors and transcriptional coactivators. Among them, we identify members of the AP1 transcription factor complex, a complex important in innate signaling and cell stress responses. We independently confirm the BRD4/AP1 interaction in primary human small airway epithelial cells. We conclude that BRD4 recruits multiple transcription factors during RSV infection in a manner dependent on acetyl-lysine binding domain interactions. This data suggests that BRD4 recruits transcription factors to target its RNA processing complex to regulate gene expression in innate immunity and inflammation.

Dampers provide safety by control of unwanted motion, due to conversion of mechanical work into another form of energy (e.g., heat). State of the art materials are elastomers including thermoplastic-elastomers. For polymer-appropriate replacement of multi-component shock absorbers comprising mounts, rods, hydraulic fluids, pneumatic devices, or electro-magnetic devices, among others, deep insights of the dynamic thermo-mechanical characteristics of damper materials have to be gained. The ultimate objective is to reduce complexity by utilizing inherent material damping rather than structural (multi-component) damping properties. The objective of this work was to compare the damping behavior of different elastomeric materials including thermoplastic poly(urethane) (TPU), and silicone rubber blends (mixtures of different poly(dimethylsiloxane) (PDMS)). Therefore, the materials were hyper- and viscoelastic characterized, a finite element calculation of a ball-drop test was performed, and for validation the rebound resilience was measured experimentally. In an attempt, the coil-over shock absorber of a model car was replaced by a damper made of the examined and modeled materials. The results revealed that the material parameter determination methodology is reliable, and the data applied for simulation lead to realistic predictions. Interestingly, the rebound resilience of the mixture of soft and hard PDMS (50:50)w% is the highest and the lowest values were measured for TPU.

Numerous approaches address over-fitting in neural networks: by imposing a penalty on the parameters of the network (L1, L2, etc); by changing the network stochastically (drop-out, Gaussian noise, etc.); or by transforming the input data (batch normalization, etc.). In contrast, we aim to ensure that a minimum amount of supporting evidence is present when fitting the model parameters to the training data. This, at the single neuron level, is equivalent to ensuring that both sides of the separating hyperplane (for a standard artificial neuron) have a minimum number of data points — noting that these points need not belong to the same class for the inner layers. We firstly benchmark the results of this approach on the standard Fashion-MINST dataset, comparing it to various regularization techniques. Interestingly, we note that by nudging each neuron to divide, at least in part, its input data, the resulting networks make use of each neuron, avoiding a hyperplane completely on one side of its input data (which is equivalent to a constant into the next layers). To illustrate this point, we study the prevalence of saturated nodes throughout training, showing that neurons are activated more frequently and earlier in training when using this regularization approach. A direct consequence of the improved neuron activation is that deep networks are now easier to train. This is crucially important when the network topology is not known a priori and fitting often remains stuck in a suboptimal local minima. We demonstrate this property by training a network of increasing depth (and constant width): most regularization approaches will result in increasingly frequent training failures (over different random seeds) whilst the proposed evidence-based regularization significantly outperforms in its ability to train deep networks.

Conditional Independence (CI) testing is fundamental in statistical analysis. For example, CI testing helps validate causal graphs or longitudinal data analysis with repeated measures in causal inference. CI testing is difficult, especially when testing involves categorical variables conditioned on a mixture of continuous and categorical variables. Current parametric and non-parametric testing methods designed for continuous variables and can quickly fall short in the categorical case. This paper presents a computational approach for CI testing for categorical data types, which we call computational conditional independence (CCI) testing. The test procedure is based on permutation and combines machine learning prediction algorithms and Monte Carlo Cross-Validation. We evaluated the approach through simulation studies and assessed the performance against alternative methods; the generalized covariance measure (GCM) test, the kernel conditional independence (KCI) test, and testing with multinomial regression. We find that the computational approach to testing has utility over the alternative methods, and we can achieve better control over type-I-error rates. We hope this work can expand the toolkit for CI testing for practitioners and researchers.

Background: Exercise is increasingly understood as an important resource for people with harmful substance use, including those in prison. Little is known about how inmates adopt various health behaviors during incarceration, without interventions. Methods: This study analyzed self-reports from 1468 inmates in Norwegian prisons, compared them according to harmful substance use pre-incarceration, and explored changes in exercise and nicotine use during incarceration. Results were presented in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results: Inmates with harmful substance use reported higher rates of smoking, smokeless tobacco, and physical inactivity pre-incarceration than inmates without harmful use. However, inmates with harmful use also exhibited more behavioral changes: they adopted exercise, ceased smoking, and adopted smokeless tobacco at higher rates during incarceration than the non-harmful group. Conclusions: Exercise is being taken up by a significant proportion of inmates, and may in particular be a replacement behavior for substance use. However, unhealthy behaviors are also begun or maintained. If prisons were used as an arena to facilitate healthy behaviors, the public health benefits to a marginalized group such as substance-using inmates could be substantial.

The interband transitions of urania (UO2) are validated independently through cathode luminescence of UO2. A picture emerges consistent with density functional theory. While theory is generally consistent with experiment, it is evident that the choice of functional can significantly alter the band gap and some details of the band structure, in particular at the conduction band minimum. Strictly ab initio predictions of the optical properties of the actinide compounds, based on density functional theory alone continues to be somewhat elusive.

This study introduces a novel computational approach for testing conditional independence (BB CI test) within causal Directed Acyclic Graphs (DAGs), leveraging Bayesian non-parametric bootstrap and machine learning techniques. Our method offers an alternative for validating the assumptions underpinning causal DAGs. Through simulation studies and an industrial case analysis, we demonstrate the test procedure in accurately assessing conditional independence, comparing it with the Generalized Covariance Measure (GCM) test. Our findings suggest that the BB CI test is advantageous in scenarios where existing methods may falter due to violations of model assumptions. This research contributes to the causal inference literature by providing a computational tool for researchers and practitioners to validate causal models.

Fe[C5H5N]2[N(CN)2]2 (1) was synthesized from a reaction of stoichiometric amounts of NaN(CN)2 and FeCl2·4 H2O in a methanol/pyridine solution. Single-crystal and powder diffraction show that 1 crystallizes in the monoclinic space group I2/m (no. 12), different from Mn[C5H5N]2[N(CN)2]2 (P21/c, no. 14) due to tilted pyridine rings, with a = 7.453(7) Å, b = 13.167(13) Å, c = 8.522(6) Å, β = 114.98(6)° and Z = 2. ATR-IR, AAS, and CHN measurements confirm the presence of dicyanamide and pyridine. Thermogravimetric analysis shows that π-stacking interactions of the pyridine rings play an important role in structural stabilization. Based on DFT-optimized structures, a chemical bonding analysis was performed using a local-orbital framework by projection from a plane-wave basis. The resulting bond orders and atomic charges are in good agreement with the expectations based on the structure analysis. SQUID magnetic susceptibility measurements show a high-spin state FeII compound with predominantly antiferromagnetic exchange interactions at lower temperatures.

The agro-biodiversity present in agro-ecosystems is fundamental in guaranteeing sustainability and resilience. However, there are very few proposals for evaluating it and, even less, ones that include indicators to analyze the influence of the structural and spatial configuration of a landscape in order to favor agro-biodiversity connectivity to productive systems, management and conservation practices, and the producer (farmer)’s perceptions, awareness and ability to favor it on his farm. The Main Agro-ecological Structure MAS is redefined as an environmental agro-biodiversity index. New indicators are established for a total of 10 criteria and 29 indicators of systems that describe the agro-biodiversity of agro-ecosystems. Methodologies for its evaluation are also described, and the possibility of adapting certain indicators according to the ecological and cultural contexts where the farms are located is discussed.

This work highlights that monitoring the microbiological quality of animal products, such as raw sheep’s milk and cheese, is necessary for food safety. Sheep’s milk and its derivatives are not legislated in Brazil. Thus, present study aimed to evaluate: (i) the hygienic-sanitary quality of raw sheep’s milk and cheese produced in southern Brazil; (ii) the presence of enterotoxins and Staphylococcus spp. in these products; and (iii) the antimicrobial susceptibility profile and resistance genes of the isolated Staphylococcus spp. Thirty-five raw sheep’s milk and cheese samples were evaluated. Microbiological quality and the presence of enterotoxins were determined by Petrifilm and VIDAS SET2 methods, respectively. Antimicrobial susceptibility tests were conducted using VITEK 2 equipment and the disc diffusion method. The presence of resistance genes tet(L), sul1, sul2, ermB, tetM, AAC(6)', tetW, and strA were evaluated by PCR. In total, 39 Staphylococcus spp. were isolated. The tetM, ermB, strA, tetL, sul1, AAC(6)’, and sul2 resistance genes were detected in 82%, 59%, 36%, 28%, 23%, 3%, and 3% of isolates, respectively. The results showed that both products contained Staphylococcus spp. and these strains were resistant to antimicrobials as well carriers of resistance genes. These results highlight Brazil's need for specific legislation regarding the pro-duction and marketing of these products.

A major challenge of augmented and mixed reality applications is identifying the context and semantics of the real environment. Studies on object and action recognition were developed based on the improvement of machine learning techniques, allowing them to be annotated and recognized. This study aims to characterize current knowledge on the use of machine learning for recognizing objects and actions in augmented and mixed reality environments, increasing context awareness. Therefore, a systematic literature review of works related to these topics was made, using the Scopus and Web of Science knowledge bases. We searched articles and conference reviews or papers published between 2018 and 2022 and selected fifteen studies to be reviewed. The results indicate that there is a great demand for using machine learning to immersive technologies in factories, engineering, entertainment, education, health, among other application domains. However, these real-time interactive systems still have challenges and limitations to be solved, involving network communication, prediction time and the creation of a model that recognize objects and actions in broad contexts. Furthermore, additional research is needed to investigate how object and action recognition can increase context awareness in augmented reality applications.

(1) Background: Preeclampsia (PE) prediction in the first trimester of pregnancy is a challenge for the clinicians. The aim of this study was to evaluate and compare the predictive performances of machine-learning based models for the prediction of preeclampsia, and its subtypes; (2) Methods: This prospective case-control study evaluated pregnancies that occurred in women who attended a tertiary maternity hospital in Romania between November 2019 and September 2022. The patients’ clinical and paraclinical characteristics were evaluated in the first trimester, and were included in 4 machine learning based models: decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF), and their predictive performance was assessed; (3) Results: early-onset PE was best predicted by DT (accuracy: 94.1%), and SVM (accuracy: 91.2%) models, while NB (accuracy: 98.6%), and RF (accuracy: 92.8%) models had the highest performance when used to predict all types of PE. The predictive performance of these models was modest for moderate and severe types of PE, with accuracies ranging from 70.6% and 82.4%; (4) The machine learning-based models could be useful tools for PE prediction in the first trimester of pregnancy.

The advances mobile communications has seen in recent years has rendered the radio spectrum a limited and, hence, an expensive resource. Therefore, technologies that support unlicensed access to spectrum are needed. Therefore, the adoption of novel modulation schemes becomes of utmost importance to obtain better spectral-localization and reduce the OOBE (\textit{Out of Band Emission}) inherent to OFDM (\textit{Orthogonal Frequency Division Multiplexing}) and, consequently, mitigating the interference between secondary (\textit{unlicensed}) and primary users. In this scenario, we assess the gain in the bit error probability using f-OFDM (\textit{filtered-OFDM}) in MIMO systems, both used in the 5G RANGE project.

Damage and fibre misalignment of woven fabrics during discontinuous polymer processing remain challenging. To overcome these, a promising switchable elastomeric adherence gripper is introduced here. The inherent surface tackiness is utilized for picking and placing large sheets. Due to the elastomer’s viscoelastic material behavior, the surface properties depend on loading speed and temperature. Different peeling speeds result in different adherence strength of an interface between the gripper and the substrate. This feature is mechanically characterized and the viscoelastic behavior of the stamp is examined. Based on this experimental characterization, an empirical model is proposed. Furthermore, a discussion of the applicability and limitation of the elastomeric gripper is given.

Canine infectious respiratory disease complex (CIRDC) is caused by different viruses and bacteria. Viruses associated with CIRDC include canine adenovirus-2 (CAV-2), canine distemper virus (CDV), canine influenza virus (CIV), canine herpesvirus (CHV), canine coronavirus (CCoV) and canine parainfluenza virus (CPIV). Bacteria associated with CIRDC include Bordetella bronchiseptica, Streptococcus equi subspecies zooepidemicus, and Mycoplasma spp. The present study examined the prevalence of pathogens associated with CIRDC in specimens received by a Veterinary Diagnostic Laboratory in Georgia from 2018 to 2022. Out of 459 cases, viral agents were detected in 34% cases and bacterial agents were detected in 58% cases. A single pathogen was detected in 31% cases, while two or more pathogens were identified in 24% cases. The percentages of viral agents identified were CAV-2 (4%), CDV (3%), CPIV (16%), CCoV (7%), and CIV (2%). The percentages of bacterial agents were Bordetella bronchiseptica (10%), Mycoplasma canis (24%), Mycoplasma cynos (21%), and S treptococcus zooepidemicus (2%). Positive viral cases ranged from 2-4% for CAV-2, 1-7% for CDV, 1-4% for CHV, 9-22% for CPIV, 4-13% for CCoV, and 1-4% for CIV. Overall, the study showed that the most prevalent pathogens associated with CIRDC during the study period were CPIV, M. canis, and M. cynos.

Virtual reality software might be challenging to utilize for beginners and unskilled professionals who do not have a programming or 3D modeling background. Concurrently, there is a knowledge gap in software project design for intuitive virtual reality authoring tools, which were supposed to be easier to use. These tools are frequently insufficient due to a lack of support and standard operating procedures. Adopting the Design Science Research paradigm, this study aims to evaluate the validity of fourteen design guidelines for the development of intuitive virtual reality authoring tools as an artifact. While a previous study completed the first steps of the Design Science Research, by identifying problems, defining solution objectives, and developing and demonstrating the design guidelines, this work seeks to qualitatively evaluate their application in a practical experiment. A group of engineering students with no prior experience in creating virtual worlds were tasked with examining the design guidelines while using the NVIDIA Omniverse Enterprise as an exemplary use case and responding to a questionnaire and a focus group interview about how they perceived these guidelines. A correlation analysis confirmed that most guidelines scores behaved as expected and were ranked according to the use-case functionality. The participants understood the guidelines' definition and could decide if they agreed or disagreed with their presence during the experiment. We conclude that, in accordance with the Design Science Research, the proposed artifact is useful, i.e., the design guidelines for virtual reality authoring tools perform what they are designed to do and are operationally reliable in accomplishing their goals.

This paper evaluates the feasibility of applying Massive MIMO to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), devised to exclusively consume data traffic from Machine Type Communications (MTC) devices, the capacity (i:e:, number of connected devices) of MTC networks and, in turn, that of the whole system, can be increased by clustering such devices and letting each cluster share the same time-frequency physical resource blocks. Following this research line, we study the possibility of employing sub-optimal linear detectors to the problem and present a simple and practical channel estimator that works without previous knowledge of the large-scale channel coefficients. Our simulation results suggest that the proposed channel estimator performs asymptotically as well as the MMSE estimator with respect to the number of antennas and the uplink transmission power. Furthermore, the results also indicate that, as the number of antennas is made progressively larger, the performance of sub-optimal linear detection methods approaches the perfect interference-cancellation bound. The findings presented in this paper shed light on and motivate for new and exciting research lines towards a better understanding of the use of massive MIMO in MTC networks.

The use of artificial intelligence algorithms (AI) has gained importance for dental applications in recent years. Analyzing using IA information from different sensor data such as images or X-ray radiographs can help to improve medical decisions and to achieve early diagnosis of different dental pathologies. In particular, the use of deep learning (DL) techniques based on convolutional neural networks (CNNs) has obtained promising results in dental applications based on images, in which approaches based on classification, detection, and segmentation are being studied with growing interest. However, there are still several challenges to be tackled, such as the data quality and quantity, the variability among categories, and the analysis of the possible bias and variance associated with each dataset distribution. In this work, we compare three different DL object detection models, which are Faster R-CNN, YOLO V2, and SSD. Each object detection architecture was trained, calibrated, validated, and tested with three different feature extraction CNNs which are ResNet-18, ResNet-50, and ResNet-101, which were the networks that best fit our dataset distribution. Based on such detection networks, we detect four different categories of angles in third molars using X-ray panoramic radiographs by using Winter's classification criterion. This criterion characterizes the third molar's position regarding the second molar's longitudinal axis. The detected categories for the third molars are distoangular, vertical, mesioangular, and horizontal. For training, we used a total of 644 panoramic X-ray images. The results obtained in the testing dataset reached up to 99% mean average accuracy performance, demonstrating the YOLOV2 obtained higher effectiveness in solving the third molar angle detection problem. These results demonstrate that the use of CNNs for object detection in panoramic X-rays represents a promising solution in dental applications.

Group B Streptococcus (GBS), a commensal in the body, causes a wide range of infectious diseases. The colonisation levels of GBS and its resistance profile to antibiotics provide important information useful for orienting prevention strategies. There is little data available on the subject with determination of resistance phenotypes in Cameroon. We therefore aimed to determine the prevalence of colonization, antibiotic resistance, including patterns of inducible resistance to clindamycin of GBS in Yaounde. To achieve this goal, a prospective cross-sectional study with an analytical component was carried out from the 28th June to the 29th August 2020 at the BIOSANTE laboratory and the Yaounde Gynaeco-Obstetrics and Paediatrics hospital. Vaginal swabs and urine were collected on 163 women. This samples were analysed using 5% defibrinated sheep blood agar and chocolate plus polyvitex agar. The isolates were identified using the morphology of the colony, Gram staining, haemolysis, catalase test and latex grouping test. Antibiotic susceptibility testing was done by disk diffusion method following the recommendations of the ACFSM 2019. The double disk diffusion method was used to identify isolates with clindamycin inducible resistance. Our data was analysed by the software SPSS version 2.1. The results obtained showed that the global prevalence of colonization by GBS was 37% (57/163), 40.35% in non-pregnant women and 59.65% in pregnant women. Pregnancy (P-value = 0.019) and gestational age (P-value = 0.025) constituted the risk factors of maternal colonization by GBS. In addition, the strains of GBS were resistant to all antibiotics tested. A D test showcased that 64.7% of GBS were resistant in a constitutive manner to clindamycin. We also note the presence of M phenotypes. As a whole, our results demonstrate that the rate of GBS colonization in this study was similar or higher than those in the previous report in Cameroon. All this indicates that attention should be paid to this bacterium in the monitoring of antimicrobial resistance and in the care of pregnant women and newborns.

Parasite control strategies such as blanket anthelmintic treatment of all horses in a herd or interval treatment regimen based on egg reappearance remain widely followed practices for the last several decades. These practices have resulted in the fast emergence of resistance in equine strongyles to all major classes of drugs on the market. In this regard, the guidelines set by the American Association of Equine Practitioners advocate evidence-based strongyle control in horses. It recommends targeted treatment of all heavy egg shedders [&gt; 500 eggs per gram (EPG) of feces] while the low shedders (0-200 EPG) are left untreated to maintain susceptible parasite refugia in a herd. As 50-75% of adult horses in a herd are low shedders, preventing them from unnecessary anthelmintic exposure is critical to tackling resistance. There are various fecal egg count (FEC) techniques with many modifications and variations in use, but none is identified as a gold standard and methods comparison studies are lacking. We hypothesized that the diagnostic performance of commonly used quantitation methodologies differs and the FEC methods must be evaluated to determine the gold standard. In this regard, we performed methods comparison studies using polystyrene beads with size and specific gravity comparable to strongyle eggs, as proxy. The linearity of 12 commonly used FEC methodologies (3 techniques with 4 different solutions) was studied using bead standards in the clinically applicable range (63 to 1,000) to determine their suitability for strongyle egg counts. Deming regression analysis identified Mini-FLOTAC with sugar (specific gravity 1.33) as the test with the greatest coefficient of determination. All tests underestimated the true bead count, and we determined a correction factor (CF) for each test to estimate the true count. CF negates the preference for a gold standard test. Finally, we analyzed the validity of CF for 5 tests with R2&gt;0.95 to accurately quantify strongyle eggs from 40 different horses. Overall, this study identified methodologies with the highest diagnostic performance and the limitations to standardizing routine FEC tests to promote uniformity in implementing AAEP parasite control guidelines.

This paper presents a methodology to calculate day-ahead wind speed predictions based on historical measurements done by weather stations. The methodology was tested for three locations: Colombia, Ecuador, and Spain. The data is input into the process in two ways: 1) as a single time series containing all measurements, and 2) as twenty-four separate parallel sequences, corresponding to the values of wind speed at each of the 24 hours in the day over several months. The methodology relies on the use of three non-parametric techniques: Least-Squares Support Vector Machines, Empirical Mode Decomposition, and the Wavelet Transform. Also, the traditional and simple Auto-Regressive model is applied. The combination of the aforementioned techniques results in nine methods for performing wind prediction. Experiments using a MATLAB implementation showed that the Least-squares Support Vector Machine using data as a single time series outperformed the other combinations, obtaining the least mean square error.

The required processes and steps for making bread include technological and innovative concepts. The current trend is the use of less toxic compounds and green processes. Besides lactic acid bacteria and yeast, other microorganisms with special properties, such as enzymes, new aroma and flavor, exopolysaccharides, and vitamins, among other compounds with beneficial properties, could be added to bread manufacture, improving bread quality and health effects for the consumers. Freeze drying, new encapsulation methods, cryoprotectants, spray drying, fluidized bed drying, and vacuum drying are used for probiotics and microorganism cultures that will be used as starters or biological additives in the fermentation. The same development is observed in the preservation methods, and studies with plant extracts and essential oils have been proposed and introduced, replacing chemical agents, such as propionate, within the clean-label bread formulations concept. Baking science is a growing research line incorporating innovative methods and biological additives.

In this paper, we identify issues and possible solutions in the key area of large-scale antenna systems, also know as Massive Multiple Input Multiple Output (MIMO) systems. Additionally, we propose the use of Massive MIMO technology as a means to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), the capacity of the MTC network and, in turn, that of the whole system, can be increased by grouping Machine-Type Communication (MTC) devices into clusters and letting each cluster share the same time-frequency physical resource blocks. We study the feasibility of applying sub-optimal linear detection to the problem of detecting a large number of MTC devices sharing the same time-frequency resources at the uplink of a base station (BS) equipped with a large number of antennas, M. In our study, we derive the achievable lower-bound rates for the studied sub-optimal linear detectors and show that the transmitted power of each MTC device can be reduced as M increases, which is a very important result for powerconstrained MTC devices running on batteries. Our simulation results suggest that, as M is made progressively larger, the performance of sub-optimal linear detection methods approach the matched filter bound, also known as perfect interference-cancellation bound.

During the second half of August 2022, a dust intrusion event occurred, when dust that originated from the dry regions of Kalmyk steppe and the Precaspian plain was transported over the eastern region of Romania. The dry soil in these regions was the result of the severe drought over a long period of time, accentuated by early heat waves in May and June 2022. The dust event was captured by MODIS images. Smoke trains originating from fires in the north of the Azov were also detected, but these did not reach Romania. Optical parametres from AERONET was used to confirm the dust event. To determine the trajectory of the particles, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used in this paper. The Ensemble median model was used to highlight the presence and concentration of dust in eastern part of Romania. Aerosols were detected between 0 and 4 km, according to radar and ceilometer data of the REXDAN cloud remote sensing facility in Galați, Romania. This dust intrusion event was the result of the dominant easterly cir-culation caused by the extension of East European High to the northeast of the continent, which transported the dust towards eastern part of Romania for more than 2 days. Moreover, the tor-rential rains between August 22nd and 24th did not clear the atmosphere of dust, since the intense easterly circulation kept carrying the dust into the Moldavian area.

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the actual one. This situation calls for novel ways to increase spectral efficiency. Therefore in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front-ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, $i.e.$, the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum-bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers.

The explosive emergence of wireless technologies and standards, covering licensed and unlicensed spectrum bands has triggered the appearance of a huge amount of wireless technologies, with many of them coexisting in the same band. Unfortunately, the wireless spectrum is a scarce resource, and the available frequency bands will not scale with the foreseen demand for new capacity. Certain parts of the spectrum, in particular the license-free ISM bands, are overcrowded, while other parts, mostly licensed bands, may be significantly underutilized. As such, there is a need to introduce more advanced techniques to access and share the wireless medium, either to improve the coordination within a given band, or to explore the possibilities of intelligently using unused spectrum in underutilized (e.g., licensed) bands. Therefore, in this paper, we present an open source SDR-based framework that can be employed to devise disruptive techniques to optimize the sub-optimal use of radio spectrum that exists today. Additionally, we describe three use cases where the proposed framework can be employed along with intelligent algorithms to achieve improved spectrum utilization.

Virtual reality experiences are frequently created using game engines, yet they are not simple for novices and unskilled professionals who don’t have programming and 3D modeling skills. Concurrently, there is a knowledge gap in software project design for intuitive virtual reality authoring tools, which were supposed to be easier to use. This work compiles design guidelines derived from a systematic literature review to contribute in the development of more intuitive virtual reality authoring tools. We searched the Scopus and Web of Science databases for works published between 2018 and 2021 and discovered 14 papers. We compiled 14 requirement and feature design guidelines, such as Visual Programming, Immersive Authoring, Reutilization, Sharing and Collaboration, Metaphors, and Movement Freedom, among others. The collected guidelines have the potential to either guide the development of new authoring tools or to evaluate the intuitiveness of existing tools. Furthermore, they can also support the development of the metaverse, since virtual content creation is one of its bases.

The calibration of three-dimensional (3D) coordinates in augmented reality (AR) systems is a complex activity. It involves the recognition of environmental characteristics and technology that models the 3D space of the device, determining its position and orientation. In the industrial environment, it is common for AR applications to cover large spaces, making it difficult to maintain attributes such as precision and accuracy. The set of sensors and mapping algorithms available in HoloLens stimulate the development of virtual reality (VR) applications, in particular localization techniques. This study proposes calibration models of the 3D coordinates of the HoloLens for indoor industrial environments. The performance of tests in a relevant environment provides data necessary to evaluate the performance of the proposed models in terms of precision and accuracy in determining point coordinates in the study environment. The results show improvements in determining the axes that define the 3D space, with a direct influence on the position of the points observed in the experiment

Objective: This study assessed hearing aid benefits for people with a normal audiogram but hearing-in-noise problems in everyday listening situations. Design: Exploratory double-blinded case control study whereby participants completed retrospective questionnaires, ecological momentary assessments, speech-in-noise testing, and mental effort testing with and without hearing aids. Twenty-seven adults reporting speech-in-noise problems but normal air-conduction pure-tone audiometry took part in the study. They were randomly separated into an experimental group who trialled mild-gain hearing aids with advanced directional processing and a control group fitted with hearing aids with no gain or directionality. Results: Self-reports showed mild-gain hearing aids reduce hearing-in-noise difficulties and provide a better hearing experience (i.e., improved understanding, participation, and mood). Despite the self-reported benefits, the laboratory tests did not reveal a benefit from the mild-gain hearing aids, with no group differences on speech-in-noise tests or mental effort measures. Further, participants found the elevated cost of hearing aids to be a barrier for their adoption. Conclusions: Hearing aids benefit the listening experience in some listening situations for people with normal audiogram who report hearing difficulties in noise. Decreasing the price of hearing aids may lead to greater accessibility to those seeking remediation for their communication needs.

We introduce the Transformation Flower Approach (TFA), a Theory of Change that attends to multiple value creation and institutional change as a dual design challenge. We highlight how the TFA integrates social scientific theories and models relevant for transformative change (in particular focusing on pathways, leverage points, governance, power, and values) and demonstrate its practical value by an application to the ongoing transformation of the Dutch food system. By providing a holistic, transdisciplinary and practically relevant approach that aims to support new social contract formation, the TFA goes beyond other transformative change approaches. Based on the notion of pathways, it offers a toolbox that aids in working towards desired futures, involving both incumbents and challengers in an effort to harness untapped yet proximal potentials in a forward-looking way. By embracing an innovation approach, it not only promises to circumvent resistance to change, but also serves as a step-by-step approach to identify options for multiple value creation and effective cooperation. We demonstrate the analytical and practical value of the TFA by discussing action perspectives at various levels and scales in the context of the Dutch food system transition, including (1) area-oriented approaches, (2) acceleration agendas for specific transformation pathways, and (3) actor-specific transformation flowers. In developing these, we emphasize the importance of interdependencies between leverage points. Our approach helps to identify opportunities to link transformative options (the what), actors (the who) and levers (the how) in dynamic interaction to embark on transformative pathways.

Background: Brain oxidative lipid damage and inflammation are common in neurodegenerative diseases such as Alzheimer’s disease (AD). Paraoxonase-1 and 3 (PON1 and PON3) protein expression have been described in tissues with no PON1 and PON3 gene expression. In the present study, we aimed to examine differences in PON1 and PON3 protein expression in the brain of a mouse model of AD. Methods: We used peroxidase-based and fluorescence-based immunohistochemistry in 5 brain regions (olfactory bulb, forebrain, posterior midbrain, hindbrain and cerebellum) of transgenic (Tg2576) mice with the Swedish mutation (KM670/671NL) responsible for a familial form of AD and corresponding wild-type mice. Results: We found intense PON1 and PON3 positive staining in star-shaped cells surrounding Aβ plaques in all Tg2576 mouse brain regions studied. Although we could not co-localize PON1 and PON3 with astrocytes, brain star-shaped cells, we found some co-localization of PON3 with microglia. Conclusions: These results suggest that 1) PON1 and PON3 cross the blood-brain barrier in discoidal HDLs and are transferred to specific brain cell types, and 2) PON1 and PON3 play an important role in preventing oxidative stress and lipid peroxidation in particular cell types, likely astrocytes and microglia, in AD pathology, and potentially in other neurodegenerative diseases

The explosive emergence of wireless technologies and standards, covering licensed and unlicensed spectrum bands has triggered the appearance of a huge amount of wireless technologies, with many of them coexisting in the same band. Unfortunately, the wireless spectrum is a scarce resource, and the available frequency bands will not scale with the foreseen demand for new capacity. Certain parts of the spectrum, in particular the license-free ISM bands, are overcrowded, while other parts, mostly licensed bands, may be significantly underutilized. As such, there is a need to introduce more advanced techniques to access and share the wireless medium, either to improve the coordination within a given band, or to explore the possibilities of intelligently using unused spectrum in underutilized (licensed) bands. Therefore, in this paper, we present a SDR based framework that can be employed to devise disruptive techniques to optimize the sub-optimal use of radio spectrum that exists today. Additionally, we describe two use cases for the proposed framework.

Sperm DNA integrity and chromatin status serve as pivotal indicators of sperm quality, given their in-tricate link to sperm function, embryo development, and overall fertility. Defects in chromatin com-paction, which are often associated with compromised protamine content, can lead to damaged DNA strands. In this study, chromatin status and possible correlation with DNA damage was assessed in males of three mouse species: Mus musculus, M. spretus and M. spicilegus. We employed various staining methods, including aniline blue, methylene blue (Diff-Quik), toluidine blue and chromomy-cin A3, to assess chromatin compaction in cauda epididymal sperm. Samples were also analyzed by the sperm chromatin structure assay (SCSA) to estimate DNA fragmentation (%tDFI, %HDS). Analyses were carried out on freshly collected sperm and cells incubated for 3 h in a Hepes-buffered modified Tyrode's medium simulating conditions of the female reproductive tract. Notably, the analysis of chromatin status yielded minimal abnormal values across all three species, employing diverse meth-odologies. SCSA analyses revealed distinct variations in %tDFI between species. Following sperm incubation, the percentages of sperm stained with methylene blue exhibited differences among the species and were significantly correlated to the DNA fragmentation index. HDS demonstrated correla-tions with the percentages of sperm stained by aniline blue, methylene blue and chromomycin A3. Overall, chromatin compaction was high across all species, with limited differences among them. The relationship between chromatin status and DNA integrity appeared to be related to levels of sperm competition among species.

Urban settings are increasingly faced with challenges across natural and engineered environmental systems, threatening the sustainability of urban centers where >50% of the world's population resides. The pressures of aging infrastructure, water and air pollution, and environmental justice exemplify the growing need for urban professionals to employ complex scientific reasoning across disciplines where they can effectively address the multi-faceted issues of urban sustainability. Here we present an innovative model for preparing the next generation of public, private, and academic leaders to address complex problems in urban sustainability. Specifically, we outline the design and implementation of an integrated, adaptable graduate training program, with the goals of science leadership, curriculum relevancy, community impact, broader applicability, recruitment into science, technology, engineering and mathematics (STEM) programs and careers, and program sustainability. This program addresses human-ecosystem challenges using a transdisciplinary approach to produce scientific products in partnership with local communities, businesses, industries, scientists, and policy makers, while providing a mechanism to understand and overcome contemporary societal challenges. Students receive rigorous training in their home disciplines, coupled with training across disciplinary lines and developmental experiences, to prepare them to communicate, collaborate, and innovate in a variety of contexts. Training success is evaluated across measurable competency domains including problem definition, research methods, communication, collaboration, and problem-solving. After three years the program expanded relationships across fields and professions, successfully established 18 internship opportunities with community partners, created a new dual-title PhD program open to students in 5 academic departments, and facilitated the co-production of knowledge with external partners. This model bridges the gaps between research, education, and application, providing an integrated, rigorous graduate training program that fosters collaborative problem-solving between STEM graduate students and the broader community of professionals conducting sustainability work in a post-industrial urban setting.

In the development of a digital twin (DT) for hydropower turbines, dynamic modeling of the system (e.g., penstock, turbine, speed control) is crucial, along with all the necessary data interface, virtualization, and dashboard designs. Since the DT must mimic the actual dynamics of the hydropower turbine accurately, adaptive learning is required to train these dynamic models online so that the models in the DT can effectively follow the representation of the actual hydropower turbine dynamics accurately and reliably. This study presents an adaptive learning method for obtaining the hydropower turbine models for DT development of hydropower systems using recursive least squares algorithm. To simplify the formulation, the hydropower turbine under consideration was assumed to operate near a fixed operating point, where the system dynamics can be well represented by a set of linear differential equations with constant parameters. In this context, the well-known six-coefficient model for the Francis turbine was formulated as the starting point to obtain input and output models for the turbine. Then, an adaptive learning mechanism was developed to learn model parameters using the real-time data from a hydropower turbine testing system. This led to a semi-physical modeling in which the first principles and data-driven modeling are integrated to produce dynamic models for the DT development. Applications to a pilot system at the Norwegian University of Science and Technology (NTNU) were made, and the models learned adaptively using the data collected from the university’s pilot system. Desired modeling and validation results were obtained.

Seed bank survival underpins plant population persistence but studies on seed bank trait-environment interactions are few. Changes in environmental conditions relevant to seed banks occur in desert ecosystems owing to solar energy development. We developed a conceptual model of seed bank survival to complement methodologies using in-situ seed bank packets. Using this framework, we quantified the seed bank survival of two closely related annual desert plant species, one rare (Eriophyllum mohavense) and one common (Eriophyllum wallacei) and the seed bank-environment interactions of these two species in the Mojave Desert within a system that emulates microhabitat variation associated with solar energy development. We tracked 4,860 seeds buried across 540 seed packets and found, averaged across both species, that seed bank survival was 21% and 6% for the first and second growing seasons, respectively. After two growing seasons, the rare annual had a significantly greater seed bank survival (10%) than the common annual (2%). Seed bank survival, across both species, was significantly greater in Shade (10%) microhabitats compared to Runoff (5%) microhabitats and Control microhabitats (3%). Our study confers insight into this early life-stage across rare and common congeners and their environmental interactions using a novel conceptual framework for seed bank survival.

Rapid advances in the screening, diagnosis, and treatment of genetic disorders has increased the number of conditions that could be detected through universal newborn screening (NBS). However, addition of conditions to the Recommended Uniform Screening Panel (RUSP) and implementation of nationwide screening has been a slow process taking several years to accomplish for individual conditions. Here we describe web-based tools and resources developed and implemented by the newborn screening translational research network (NBSTRN) to advance newborn screening research and support NBS stakeholders. NBSTRN’s tools include the Longitudinal Pediatric Data Resource (LPDR), the NBS Condition Resource (NBS-CR), the NBS Virtual Repository (NBS-VR), and the Ethical, Legal, and Social Issues (ELSI) Advantage. Research programs including the Inborn Errors of Metabolism Information System (IBEM-IS), BabySeq, EarlyCheck, and Family Narratives Use Cases have utilized NBSTRN’s tools, and in turn contributed research data to further expand and refine these this resource. Additionally, we discuss ongoing tool development to facilitate expansion of genetic disease screening in increasingly diverse populations. In conclusion, NBSTRN’s tools and resources provide a trusted platform to enable NBS stakeholders to advance NBS research and improve clinical care for patients and their families.

Cobalt, like other critical elements, is gaining in importance today. The great technological advances and the deep knowledge of the physical and chemical properties of this element have allowed to enhance its applications in various fields, such as: catalysts, paints, alloys for the mechanical and aerospace industries, as well as the medical sector and in recent times, its use within the rechargeable battery industry. The main exploitable deposits are in the Democratic Republic of the Congo, which have economic potential due to a strong influence on their mineralization processes. However, the growing demand for cobalt and the search for less dependence on African deposits leads to targeting other regions, so it is necessary to carry out exhaustive exploration to find out the potential of its reserves for a subsequent benefit of the mineral. Generally, cobalt comes as a by-product of the extraction of other metallic minerals, mainly from Cu-Co, Ni-Co, Ni-Cu-Co deposits. From the above, a first review is carried out on the differences that exist in the geochemical, mineralogical and forecast properties that exist within the different deposits that harbor cobalt. As a second review topic, it delves into efficient processing for cobalt recovery, which is generally carried out by flotation, acid leaching, in addition to its recovery from secondary sources, such as batteries and metallurgical waste. However, generally speaking there is still a vast lack of fundamental knowledge about the processability of cobalt. Said processing has been affected from the point of view of mineralogy, that is, understanding and knowing the cobalt-bearing minerals, as well as gangue mineralogy, these aspects exercise significant control during their processing and selection of the most appropriate route. suitable for cobalt extraction (leaching and/or flotation). In this context, the document concludes with a vision of the challenges that the mining industry must implement to enter circular economy models, mainly in the creation of sustainable processes from secondary sources.

Cyclodextrin (CD) is made up of 7 glucose molecules linked in a ring, creating a cone shape. Its interior can house hydrophobic molecules while the exterior is hydrophilic enough to interact with water molecules. Until now, this feature has been used for the development of active and intelligent packaging applied to food, interacting with the product or its environment to improve one or more aspects of its quality or safety. As well, it is used to provide information on monitoring the time in which food is optimal for consumption, an aspect considered very important for the consumer and for the merchant. A known problem with some of these types of packaging is that the bioactive compounds that are housed in the CD can interact with food and can modify its taste, smell, color and/or texture. Therefore, this review will focus on discerning which packaging is most appropriate for each situation.

It was the aim of this study to provide a more precise timeframe of development of the gonads and genital ducts in the equine fetus around the time of sexual differentiation. This included the identification and localisation of the primordial germ cell population. Equine fetuses between 45 and 60 days of gestation were evaluated using a combination of micro-computed tomography scanning, immunohistochemistry, and multiplex immunofluorescence. Fetal gonads increased in size by 23-fold from 45 to 60 days of gestation, paralleled by a greater increase in metanephros volume. Signs of mesonephros atrophy were detected during this time. Tubular structures of the fetal testes were present from day 50 onwards, whereas cell clusters dominated in the fetal ovary. The genital ducts were well-differentiated and presented a lumen in all samples. No sign of mesonephric or paramesonephric duct degeneration was detected. Expression of AMH was strong in the fetal testes but absent in ovaries. Irrespective of sex, primordial germ cells selectively expressed LIN28. Migration of primordial germ cells from the mesonephros to the gonad was detected at 45 days, but not at 60 days of development. Their number and distribution within the gonad were influenced (p&lt;0.05) by fetal sex. Most primordial germ cells (86.8 ± 3.2% in females and 84.6 ± 4.7% in males) were characterized as pluripotent according to co-localization with CD117. However, only a very small percentage of primordial germ cells was proliferating (7.5 ± 1.7% in females and 3.2 ± 1.2% in males) based on co-localization with Ki67. It can be concluded that gonadal sexual differentiation in the horse occurs asynchronously with regard to sex but already before 45 days of gestation.

Abstract: Background: Exposure to ETS (Environmental Tobacco Smoke) is one of the most toxic environmental exposures. Objective: To investigate the impact of ETS on physiological, biochemical, psychological indicators, on the urine antioxidant capacity (AC) and oxidative damage to lipids in a pilot sample of healthy pregnant women. Methods: The exposure to ETS was investigated by a validated questionnaire, urine cotinine and the marker of oxidative damage to lipids - 8-isoprostane concentrations using an ELISA kit. Urine AC was determined by the spectrophotometric TEAC method. From the sample of pregnant women (n=319, average age 30.84 ± 5.09 years) in 80 the levels of cotinine and oxidative stress markers were analyzed. Results: From our sample, 5 % individuals (7.4 % objectified by cotinine) were current smokers and 25 % reported passive smoking in the household (18.8 % objectified by cotinine). The Kappa was 0.78 for smokers and 0.22 for ETS exposed non-smokers. Smokers as well as non-smokers had significantly higher (p<0.05) urine AC than ETS exposed non-smokers. Non-smokers had significantly lower levels of 8-isoprostane than smokers (p<0.01) and ETS-exposed non-smokers (p<0.05). Correlations between urine levels of cotinine and AC were positive in ETS exposed non-smokers. Conclusion: The harmful effect of active and passive smoking on oxidative stress parameters has been indicated.

DARPA, the Defense Advanced Research Projects Agency from the United States, has started the Spectrum Collaboration Challenge with the aim to encourage research and development of coexistence and collaboration techniques of heterogeneous networks in the same wireless spectrum bands. Team SCATTER has been participating in the challenge since its beginning, back in 2016. SCATTER’s open-source software-defined physical layer (SCATTER PHY) has been developed as a standalone application, with the ability to communicate with higher layers of SCATTER’s system via ZeroMQ, and uses USRP X310 software-defined radio devices to send and receive wireless signals. SCATTER PHY relies on USRP’s ability to schedule timed commands, uses both physical interfaces of the radio devices, utilizes the radio’s internal FPGA board to implement custom high-performance filtering blocks in order to increase its spectral efficiency as well as enable reliable usage of neighboring spectrum bands. This paper describes the design and main features of SCATTER PHY and showcases the experiments performed to verify the achieved benefits.

Melanophryniscus admirabilis (admirable red-belly toad) is a microendemic and critically endangered species found exclusively along 700 meters of the Forqueta River, in a fragment of Atlantic Forest in southern Brazil. One of the greatest concerns regarding the conservation of this species is the extensive use of pesticides in areas near their natural habitat. In recent years, the adaptation and persistence of animal species in impacted environments have been associated with microbiota. Therefore, the current study aimed to characterize the oral bacterial community of wild M. admirabilis and to address the question of how this community might contribute to toad’s adaptation in the anthropogenic environment and its general metabolic capabilities. In the present study, 11 oral samples collected from wild M. admirabilis were characterized and analyzed via high-throughput sequencing. A total of 181,350 sequences were obtained, resulting in 16 phyla, 34 classes, 39 orders, and 77 families. Proteobacteria dominated (53%) the oral microbiota of toads followed by Firmicutes (18%), Bacteroidetes (17%), and Actinobacteria (5%). No significant differences in microbial community profile from among the samples were reported, suggesting that the dietary restriction may directly influence the bacterial composition. Functional inference of microbiome was performed using PICRUSt2 and important pathways, such as xenobiotic degradation pathways to pesticides and aromatic phenolic compounds were detected, suggesting that the bacterial communities may have important roles in M. admirabilis health and survival in the anthropogenic environment. Overall, our results have important implications for the conservation and management of this microendemic and critically endangered species.

Health care workers (HCWs), specifically dentists, are at the front line for acquiring blood-borne virus infections. The highest proportion of occupational transmission is through percutaneous injuries via hollow-bore needles. Several studies around the world have reported that hepatitis viruses and human immunodeficiency virus are the main pathogens for most cases of occupationally acquired blood-borne infection. We aim to investigate the prevalence of hepatitis B virus (HBV), hepatitis C virus (HCV), hepatitis E virus (HEV), and human immunodeficiency virus (HIV) among Mexican dentists. Methods. We included 159 dentists who attended the annual meeting at the Medica Sur Clinic & Foundation held in Mexico City in May 2016. A survey was applied in order to obtain data of occupational exposure to blood-borne viruses (BBV). Serum samples were screened serologically using enzyme-linked immunosorbent assays. Results. Two dentists (1.2%) were positive for antibodies against HCV antigen, one (0.6%) was positive for antibodies against HBV antigen and three (1.8%) were positive for the detection of IgG antibodies against HEV. Two cases (1.2%) were positive for antibodies against HIV. Conclusions. The infection by HEV was the most prevalent among dentists. However, the prevalence of BBV in dentists was similar to that in the general population.

The carbapenemase OXA-244 is a derivate of OXA-48, and its detection is very difficult in laboratories. Here we report the identification and genomic analysis of an Escherichia coli isolate (28Eco12) harbouring the bla_OXA-244 gene identified in Colombia, South America. The 28Eco12 isolate was identified during a retrospective study and it was recovered from a patient treated in Colombia. The complete nucleotide sequence was established using the PacBio platform. A comparative genomics analysis with other bla_OXA-244–harbouring Escherichia coli strains was performed. The 28Eco12 isolate belonged to sequence type (ST) 38 and its genome was composed of two molecules, a chromosome of 5,343,367 bp and a plasmid of 92,027 bp, which belonged to the incompatibility group IncY and did not harbour resistance genes. The bla_OXA-244 gene was chromosomally-encoded and mobilized by an ISR1-related Tn6237 composite transposon. Notably, this transposon was inserted and located within a new genomic island. For our knowledge this is the first report of a bla_OXA-244–harbouring Escherichia coli isolate in American continent.Our results suggest that the introduction of the OXA-244-producing E. coli isolate was through clonal expansion of the ST38 pandemic clone. Other isolates producing OXA-244 could be circulating silently on the American continent.

(1) Background: The RDW-CV has predictive value in many pregnancy-related conditions. Re-search question: Can the RDW-CV be utilized predictively in pregnant patients with thrombo-philia? Aim of the study: To carry out a detailed analysis of the RDW-CV in pregnant patients with treated thrombophilia as compared with pregnant patients without thrombophilia who de-livered via cesarean section at term. (2) Methods: We studied 160 pregnant patients, including 80 pregnant patients with treated thrombophilia in the study group, and another 80 patients of a similar age and parity. The patients were referred to our hospital for delivery at term by means of a cesarean section between 1/10/2017 and 1/12/2021. Every patient received a sonogram during the first 1–2 days after the cesarean section, and their uterine evaluation was interpreted using the PUUS (Postpartum Uterine Ultrasonographic Scale). (3) Results: Our PUUS≥1 pregnant and postpartum patients with treated thrombophilia were the only group with an RDW-CV value over 14. No deep vein thrombosis was observed during hospitalization, showing that the antico-agulant treatment was necessary and effective. An RDW-CV of 14.5 was the highest value in the Rh-negative group of pregnant patients with treated thrombophilia. An RDW-CV of 14.48 was the highest level in the Rh-negative postpartum patients with treated thrombophilia. (4) Conclu-sion: An RDW-CV of ≥14 can predict uterine hematometra (PUUS≥1). The RDW-CV values were higher in Rh-negative patients.

Abstract: The overuse of antibiotic prophylaxis during the COVID-19 pandemic would have led to the devel-opment of antibiotic-resistant bacterial strains, thereby increasing the epidemiological burden of antimicrobi-al resistance. The aim of this study was to determine the prevalence and antibiotic resistance pattern of bacte-ria isolated in 02 referral health facilities in Yaoundé before and during the COVID-19 pandemic era. We conducted a retrospective study over a period of 03 years (from 1 January 2019 to 31 December 2021) in the bacteriology units of the Central and General Hospitals of Yaoundé, Cameroon. The review of the services' registers was done to record bacterial isolates (Streptococcus, Staphylococcus, Neisseria meningitidis and Entero-bacteriaceae) as well as their susceptibility to selected, specific and highly potent antibiotics: Cefixime, Azythromycin and Erythromycin. The relationship between each group of resistant bacteria and the antibiotic of interest was determined by simple linear regression; the comparison of the prevalences of before (2019) and during 2 consecutive years of the COVID-19 pandemic onset (2020 and 2021) was done by the Chi2 test of in-dependence. In all, 426 bacterial strains were included. It appeared that the highest number of bacteria iso-lates and lowest rate of bacterial resistance were recorded during the pre-COVID 2019 period in 2019 (160 isolates vs. 58.8% resistance rate). Conversely, lower bacteria stains but greater resistance burden were rec-orded during the pandemic era (2020 and 2021) with the lowest bacteria amount and peak of bacteria re-sistance registered in 2020, the year of COVID-19 onset (120 isolates vs. 70% resistance in 2020 and 146 iso-lates vs.58.9% resistance in 2021). In contrast to almost all others groups of bacteria where the resistance burden was quite constant over years, the Enterobacteriaceae exhibited greater resistance rate during the pandemic period [60%(48/80) in 2019 to 86.9%(60/69) in 2020 and 64.5%(61/95) in 2021)]. Concerning antibiotics, unlike Erythromycin, Azythromycin related resitance increased during the pandemic period and the resistance to Cefixim tends to decrease the year of the pandemic onset (2020) and re-increase one year therafter. A significant association was found between resistant Enterobacteriaceae strains and Cefixime (R= 0.7; P-value= 0.0001) and also, between resistant Staphylococcus strains and Erythromycin (R= 0.8; P-value= 0.0001). It could be that the more frequent use of these antibiotics has increased resistance rate especially in Enterobacteriaceae. Anticromicrobial resistance should be closely monitor during and after COVID pandemic era.

Breast cancer (BC) affects millions of women; it is the leading cause of death by neoplasia in wom-en worldwide, with at least 500 thousand deaths each year, 70% of which occur in developing countries. Elastography evaluates tissue stiffness, making this a promising non-invasive real-time technique. BI-RADS is recognized as a standard and helpful technique for establishing BC risk. This study aimed to determine, by strain elastography (SE), the fat-to-lesion index (F/L index), sen-sitivity, specificity, and optimal cut-off to diagnose BC. This prospective study included 216 wom-en who underwent SE, ultrasound, mammography, and breast biopsy; according to mammogra-phy, we recruited BI-RADS category 2 (n= 5), category 3 (n=29), category 4 (n= 94), category 5 (n= 71) and category 6 (n=17); after biopsy, 108 women were classified as negative, and 108 were pos-itive for BC. Three expert BC radiologists performed all imaging interpretations and biopsies. Our results show mean values of the F/L index for negative biopsies of 3.70±2.57 and positive biopsies of 18.10±17.01; we developed two models for the prediction of BC, a logistic regression model with an AUC of 0.893 and a neural network with an AUC of 0.902. The Youden index yielded a F/L index cut-off >5.76, with a sensitivity and specificity of 84.26%. Positive Spearman's Rho cor-relation coefficient was observed between the F/L index and BI-RADS, r=.073 (p< 0.001). ANOVA test showed a difference between F/L index vs. molecular subtypes (p=0.002). SE is helpful as a di-agnostic complement to mammography, or in cases where the latter is contraindicated, elas-tography has an adequate predictive capacity and is a fast and minimally invasive procedure.

Tooth decay, also known as caries, is a significant medical problem that harms teeth. Treatment is based on the removal of the carious material and then filling the cavity left in the tooth, most commonly with amalgam or composite resin. The consequences of filling failure include repeating the filling, or performing another treatment, such as a root canal, or extraction. Dental amalgam contains mercury, and there is a global effort to reduce its use. However, no consensus has been reached using randomized clinical trials, regarding whether amalgam or composite resin materials are more durable, and which is the best restorative material. To determine which material is superior, we performed a retrospective cohort study using a large database where members of the 58 dental clinics with 440 dental units were treated. The number of failures of the amalgam compared to composite resin restorations between 2014 and 2021 were compared. Our data included information from over 650,000 patients. Between 2014 - 2021, 260,905 patients were treated. 19,692 out of 113,281 first amalgam restorations failed (17.49%), whereas significantly fewer composite restorations failed (11.98%) 65,943 out of 555,671. This study indicates that composite is superior to amalgam and therefore it is reasonable to cease using mercury containing amalgam.

The Covid-19 pandemic has rapidly evolved in December 2019 and to prevent its spread, effective vaccines has been produced and made available to the population. Despite their availability so far in Cameroon, the vaccination coverage remains low. This study aimed at describing the epidemiology of the acceptance of vaccines against Covid-19 in some urban and rural areas of Cameroon. A cross-sectional, descriptive and analytical survey was conducted from March 2021 to August 2021 targeting unvaccinated individuals from urban and rural area. After getting appropriate administrative authorizations and an ethical clearance from the Institutional Review Board (or Ethics Committee) of Douala University (N° 3070CEI-Udo/05/2022/M), a cluster sampling at many degrees was performed and a language adapted questionnaire was filled by each consenting participant. Data were analyzed using Epi info version 7.2.2.6 software and for P-values ˂ 0.05, the difference was considered as statistically significant. Out of 1053 individuals, 58.02% (611/1053) participants were residing in urban and 41.98% (442/1053) in rural areas. Good knowledge relative to Covid-19 was significantly higher in urban areas as compared to rural areas (97.55%vs.85.07, P<0.000). The proportion of respondents who intended to accept the anti Covid-19 vaccine was significantly higher in urban areas than rural areas (42.55%vs.33.26, p=0.0047). Conversely, the proportion of anti Covid-19 reluctant respondents thinking that the vaccine can induce a disease was significantly higher in rural areas than urban areas (54 (35.07 vs 8.84, P<0.0001). The significant determinants of anti-COVID-19 acceptance were the level of education (p=0.0001) and profession in the rural areas (p=<0.0001), and only the profession (p=0.0046) in the urban areas. This study globally shows that anti-COVID-19 vaccination remains a major challenge in urban as well as rural area in Cameroon. We should keep sensitizing and educate population about vaccine importance in preventing the COVID-19 spread.

(1) Background: Thrombophilia is a tendency towards hypercoagulability, and it is increased by pregnancy, peaking around delivery. Research question: does thrombophilia stimulate the in-flammatory state of the patient, already suppressed by pregnancy? (2) Methods: Eighty thrombo-philia patients admitted for delivery between 1/10/2017 and 1/12/2021 were prospectively stud-ied, together with eighty age- and para-matched control patients. Patients were admitted for de-livery at term by means of cesarean section. The inflammation indexes from the complete blood count values analysis during both the 24 hours before and after labor—extracted from the hospi-tal’s medical records—were calculated and then correlated with uterine involution. (3) Results: Except for the PLR, most of the numerous inflammation indexes studied were not significantly different in treated thrombophilia patients, before and after delivery, compared to non-thrombophilia patients. Only when we split the patients, based on the uterine haematometra in the first 24-48 hours postpartum, we found out that the few treated thrombophilia patients with haematometra (14 with haematometra out of 79 with treated thrombophilia) had elevated SII and AISI antepartum. In pregnant patients treated for thrombophilia, MLR is higher in pa-tients without the Rh factor than in those with the Rh factor. In non-thrombophilia patients, MCVL and NLPR increased with age and before labor, while SII and AISI increased with age postpartum. (4) Conclusions: Thrombophilia did not stimulate the inflammatory state of the pa-tient, already suppressed by pregnancy.

Background: COVID-19 remains a rapidly evolving and deadly pandemic worldwide. This necessitates the continuous assessment of existing diagnostic tools for robust, up-to-date and cost-effective pandemic response strategy. We sought to determine the infection rate (PCR-positivity) and degree of spread (IgM/IgG) of SARS-CoV-2 in three university settings in Cameroon Method: Study volunteers were recruited from November 2020 to July 2021 among COVID-19 non-vaccinated students in three Universities from two regions of Cameroon (West and Centre). Molecular testing was performed by RT-qPCR on nasopharyngeal swabs and IgM/IgG antibodies in plasma were detected using the Abbott Panbio IgM/IgG rapid diagnostic test (RDT) at the Virology Laboratory of CREMER/IMPM/MINRESI. The molecular and serological profiles were compared and, p<0.05 considered statistically significant. Results: Amongst the 291 participants enrolled (mean age 22.59±10.43 years), 19.59% (57/291) were symptomatic and 80.41 %(234/2691) asymptomatic. Overall COVID-19 PCR-positivity rate was 21.31% (62/291), distributed as follows: 25.25% from UdM-Bangangte; 27.27% from ISSBA-Yaounde and 5% from IUEs/INSAM-Yaounde. Women were more affected than men (28.76% [44/153] vs. 13.04% [18/138], p<0.0007) and they significantly expressed more IgM+/IgG+ (15.69% [24/153] vs. 7.25% [10/138], p<0.01). Participants from Bangangté, the nomadic, and the “non-contact cases” mainly presented an active infection compared to those from Yaoundé (p= 0.05; p=0.05 and p=0.01 respectively). Overall IgG seropositivity (IgM-/IgG+ and IgM+/IgG+) was 24.4% (71/291). A proportion of 26.92% (7/26) presenting COVID-19 IgM+/IgG- had negative PCR versus 73.08% (19/26) with positive PCR, p<0.0001. Furthermore, 17.65% (6/34) with COVID-19 IgM+/IgG+ had negative PCR as compared to 82.35% positive PCR (28/34), p<0.0001. Lastly, 7.22% (14/194) with IgM-/IgG- had a positive PCR. Conclusion: This study calls for a rapid preparedness and response strategy in higher institutes in case of any future pathogen with pandemic or epidemic potentials. The observed disparity between IgG/IgM and viral profile supports prioritizing assays targeting the virus (nucleic acid or antigen) for diagnosis and antibody screening for sero-surveys

In this paper, the technical aspects of a multi-lidar instrument, the long-range WindScanner system, will be presented accompanied by an overview of the results from several field campaigns. The long-range WindScanner system consists of three spatially separated coherent Doppler scanning lidars and a remote master computer that coordinates them. The lidars were carefully engineered to perform arbitrary and time controlled scanning trajectories. Their wireless coordination via the master computer allows achieving and maintaining lidars’ synchronization within ten milliseconds. As a whole, the long-range WindScanner system can measure an entire wind field by emitting and directing three laser beams to intersect, and then by moving the beam intersection over the points of interest. The long-range WindScanner system was developed to tackle the need for high-quality observations of wind fields from scales of modern wind turbine and wind farms. It has been in operation since 2013.

(1) Background: The prediction of cervical lesions evolution is a challenge for clinicians. The prospective study aimed to determine and compare the predictive accuracy of cytology, HPV genotyping, and p16/Ki67 dual staining alone or in combination with personal risk factors for the prediction of progression, regression or persistence of cervical lesions in human papillomavirus (HPV)-infected patients; (2) Methods: This prospective study included HPV-positive patients with or without cervical lesions that underwent follow-up. Descriptive statistics and sensitivity analysis for individual or combined index tests were used for data analysis; (3) Results: The highest predictive performance for the progression of cervical lesions was achieved by a model that comprised a Pap smear suggestive of high-grade squamous intraepithelial lesion (HSIL), the presence of 16/18 HPV strains, a positive p16/Ki67 dual staining result along with the presence of at least 3 clinical risk factors, which had a sensitivity (Se) of 74.42%, a specificity of 97.92%, an area under the receiver operating curve (AUC) of 0.961, and an accuracy of 90.65%. The prediction of cervical lesions regression or persistence was modest; (4) Conclusions: Multiple testing or new biomarkers should be used to improve HPV-positive patient surveillance, especially for cervical lesion regression or persistence prediction.

(1) Background: This study aimed to outline the antitumoral, antioxidant, and cytotoxic proprie-ties of various types of Perilla frutescens extracts obtained from the leaves of the species; (2) Methods: We determined total polyphenols, flavonoids and anthocyanins contents, as well as the in vitro antioxidant, antitumoral, and cytotoxic actions in 3 types of ethanolic extracts (E1, E2, E3) and in 3 types of ethanol: acetone extracts (A1, A2, A3) of Perilla frutescens according to standardized procedures; (3) Results: We found that Perilla frutescens ethanolic extracts had higher total phenol concentrations (p= 0.002). Flavonoids and anthocyanins concentrations were not statistically different between the two extracts. The iron chelating capacity, hydroxyl radical scavenging capacity, superoxide anion radical scavenging capacity, and lipoxygenase inhibition capacity showed a significant increase with higher concentrations of Perilla frutescens extracts, particularly the ethanolic extracts. Perillyl alcohol had greater cytotoxic capacity on MG-63 cell line and E1 extract showed similar significant cytotoxic effects on A431 cell line; (4) Conclusions: Both ethanolic and ethanol: acetone extracts from Perilla frutescens exhibited important antioxi-dant and antitumoral actions in vitro, which proportionally increased with concentration. The cytotoxic threshold determined in this study for various types of extracts could help determine the best dosage with the maximum antioxidant and antitumoral potential.

In the realm of smart transportation and mobility, delivery organizations are continuously refining their strategies, harnessing resources and advanced analytical techniques to streamline operations, aiming to achieve optimal solutions in terms of both efficiency and cost-effectiveness. However, a persistent challenge faced by these delivery companies revolves around the effective assignment of delivery personnel to customer orders, often grappling with suboptimal assignments that lead to inefficiencies and delays. To address this issue, we propose an architecture that uses the Munkres algorithm to optimize the task assignment problem for delivery personnel with pending orders, employing different cost functions obtained with deterministic and machine learning techniques. We compared the performance of linear and polynomial regression methods to construct different cost functions represented by matrices with orders and delivery people information. Subsequently, we applied the Munkres optimization algorithm to solve the assignment problem, which optimally assigns delivery people and orders. The results demonstrate that linear regression, used to estimate distance information, can reduce estimation errors by up to 568.52 km (1.51%) for our dataset compared to other methods. Conversely, polynomial regression proves effective in constructing a superior cost function based on time information, reducing estimation errors by up to 17,143.41 minutes (11.59%) compared to alternative methods. The proposed approach aims to enhance delivery personnel allocation within the delivery sector, optimizing the efficiency of this process.

Conservation of wildlife depends on precise and unbiased knowledge on the abundance and distribution of species. It is challenging to choose appropriate methods to obtain a sufficiently high detectability and spatial coverage matching the species characteristics and spatiotemporal use of the landscape. In remote regions, such as in the Arctic, monitoring efforts are often resource-intensive and there is a need for cheap and precise alternative methods. Here, we compare an uncrewed aerial vehicle (UAV; quadcopter) pilot-survey of the non-gregarious Svalbard reindeer to traditional population abundance surveys from ground and helicopter to investigate whether UAVs can be an efficient alternative technology. We found that the UAV survey underestimated reindeer abundance compared to the traditional abundance surveys when used at management relevant spatial scales. Observer variation in reindeer detection on UAV imagery was influenced by the RGB greenness index and mean blue channel. In future studies, we suggest to test long-range fixed-wing UAVs to increase the sample size of reindeer and area coverage and incorporate detection probability in animal density models from UAV imagery. In addition, we encourage focus on more efficient post-processing techniques, including automatic animal object identification with machine learning and analytical methods that account for uncertainties.

Prophylactic vaccines are important in the control of visceral leishmaniasis (VL) and as economic measures for public health. Despite the efforts to develop a vaccine against human VL caused by Leishmania infantum, none is available, and the focus has shifted to developing vaccines against canine visceral leishmaniasis (CVL). Currently, commercially available vaccines are targeted at CVL but are not effective. Different strategies have been applied in developing and improving vaccines, such as using chimeric proteins to expand vaccine coverage. The search for patents can be a way of tracking vaccines that have the potential to be marketed. In this context, the present work presents a summary of immunological aspects relevant to VL vaccine development with a focus on the composition of chimeric protein vaccines for CVL deposited in patent banks as an important approach for biotechnological development. The resulting data could facilitate the screening and selection of antigens to compose vaccine candidates with high performance against VL.

Bioenergy with carbon capture and sequestration (BECCS) is one strategy to remove CO2 from the atmosphere. To assess the potential scale and cost of CO2 sequestration from BECCS in the US, this analysis models carbon efficiencies and costs of biomass production, delivery, power generation, and CO2 capture and sequestration in saline formations. The analysis includes two biomass supply scenarios (near-term and long-term), two biomass logistics scenarios (conventional and pelletized), two generation technologies (pulverized combustion and integrated gasification combined cycle), and three cost accounting scenarios (gross cost, net cost after electricity revenues, and net cost after electricity revenues with avoided emissions from conventional power generation). Results show cost Mg-1 CO2 as a function of CO2 sequestered (simulating capture up to 90% of total CO2 sequestration potential) and associated spatial distribution of resources and generation locations for the array of scenario options. Under a near-term scenario using 222 million Mg yr-1 of biomass, up to 196 million Mg CO2 can be sequestered at scenario-average costs ranging from $60 to $158 Mg 1 CO2; under a long-term scenario using 823 million Mg yr-1 of biomass, up to 727 million Mg CO2 yr 1 can be sequestered at scenario-average costs ranging from $32 to $242 Mg-1 CO2. These costs are largely influenced by cost accounting scenario, and the CO2 sequestration potential may be reduced if future competing demand reduces resource availability. Results suggest there are multiple feedstock-logistics-generation pathways toward CO2 drawdown that could be incrementally trialed and monitored for environmental sustainability effects. Interactive visualization of results is available at [final link to be determined].

This survey reports on the DNA identification and occurrence of Culex torrentium and Cx. pipiens s.s. in Belgium. These native disease vector mosquito species are morphologically difficult to separate and the biotypes of Cx. pipiens s.s. are morphologically indistinguishable. Culex torrentium and Cx. pipiens s.s. were identified using the COI and ACE2 loci. We recorded 1,248 Cx. pipiens s.s. and 401 Cx. torrentium specimens from 24 locations in Belgium (collected between 2017 and 2019). Culex pipiens biotypes pipiens and molestus, and their hybrids, were differentiated by fragment size analysis of the CQ11 locus (956 pipiens and 227 molestus biotype specimens, 29 hybrids). Hybrids were observed at 13 out of 16 sympatric sites. These results confirm that both species are widespread in Belgium, but while Cx. torrentium revealed many COI haplotypes, Cx. pipiens s.s. showed only one abundant haplotype. This latter observation may either reflect a recent population-wide demographic or range expansion, or a recent bottleneck, possibly linked to a Wolbachia infection. Finally, new evidence is provided for the asymmetric but limited introgression of the molestus biotype into the pipiens biotype.

Carbapenems have long been considered as treatment of choice for Gram-Negative Bacteria (GNB) infections, and today the clinical utility of this class is threatened by the emergence and spread of resistance favored by its increasing use. According to the WHO, Acinetobacter baumannii, nosocomial infection agent, tops the list of priority antibiotic-resistant pathogens, considered to be the most risky for humans. This study sought to determine the prevalence of Acinetobacter baumannii strains producing carbapenemases in four health facilities in the Center and Littoral regions of Cameroon and the associated risk factors. An analytical cross-sectional study was conducted over a six-month period from January to June 2022. All Acinetobacter baumanii or suspected strains isolated from pathological samples at the bacteriology laboratory of different health facilities were systematically collected and underwent a re-identification. After successfully subculturing and growing on nutrient agar, re-identification and antimicrobial susceptibility Testing (AST) were performed using the VITEK 2 System and the Kirby-Bauer method according to the guidelines of the Clinical and Laboratory Standards Institute (CLSI). Detection and phenotypic characterization of carbapenemases was performed according to adequate standard procedures. A total of 168/226 clinical isolates of Acinetobacter baumannii were confirmed after re-identification of which 52.69% came from male patients, and 55.09% from participants aged between 10-39 years old and 46.71% from pus samples. A very high resistance rates to all families of antibiotics was noted except to colistin (10.2%). About 40.12% of these strains produced carbapenemases with 62.69% of class B and 37.31% of class A. In addition, frequent hospitalisation was significantly associated to the production of carbapenemase among Acinetobacter baumanii (Ajusted-OR=16.53, P-value<0.0001). This study highlighted the emergence of carbapenemase-producing Acinetobacter baumannii which is increasingly growing. Continuous drug-resistant monitoring and preventive measures could help to prevent and curb the dissemination of A.baumanii resistance genes, especially in hospital settings.

Visceral leishmaniasis (VL) is a chronic systemic disease. In Brazil this infection is caused by Leishmania (Leishmania) infantum. Extracellular vesicles (EVs) released by Leishmania species have different functions like modulation of host immune system, inflammatory response, among others. This study evaluated the participation of EVs from L. (L.) infantum (Leish-EVs) in stimulation of the humoral and cellular immune responses of hosts with VL. Promastigotes were cultivated in 199 medium and, in the log phase of growth, they were centrifuged, washed, resuspended in RPMI medium and incubated for 2 to 24h, at 25ºC or 37°C to release Leish-EVs. This dynamic was evaluated by transmission (TEM) and scanning (SEM) electron microscopies, as well as nanoparticle tracking analysis (NTA). The results suggested that parasite penetration in mammal macrophages requires more Leish-EVs than those living in insect vectors, since promastigotes incubated at 37°C released more Leish-EVs than those incubated at 25ºC. In comparison to the control group, infected THP-1 cells produced a significantly higher concentration of EVs (THP-1 cells-EVs). Similar results were obtained when THP-1 cells were treated with Leish-EVs or a crude Leishmania antigen. These data suggest that the concentration of host-EVs-Can distinguish between infected and uninfected cells. THP-1 cells treated with Leish-EVs expressed more IL-12 than control THP-1 cells, but were unable to produce IFN-γ. These same cells produced IL-10, which inhibited TNF and IL-6. Equally, THP-1 cells treated with Leish-EVs up-expressed miR-21-5p and miR-146a-5p. These findings indicate that the increased levels of miR-21-5p and miR-146a-5p observed in Leish-EVs-treated-THP-1 cells lead to immunosuppression and the secretion of pro-inflammatory cytokines.

(1) Background: Neonatal early-onset sepsis (EOS) is associated with important mortality and morbidity. The aims of this study were to evaluate the association between serum biomarkers with early onset neonatal sepsis in a cohort of patients with prolonged rupture of membranes (PROM), and to calculate their diagnostic accuracy. (2) Methods: A retrospective cohort study was conducted on 1355 newborns with PROM admitted between January 2017 and March 2020, who were divided in two groups: group A, with PROM ≥ 18 hours and group B, with PROM < 18 hours. Both groups were further split into subgroups: proven sepsis, probable sepsis and no sepsis. Descriptive statistics, ANOVA analysis, and a Random Effects Generalized Least Squares (GLS) regression were used to evaluate the data. (3) Results: The statistically significant predictors of neonatal sepsis were the high white blood cells count from the first (p = 0.005) and third day (p = 0.028), and high CRP values from the first day (p = 0.004). Procalcitonin (area under the curve - AUC = 0.78) and CRP (AUC = 0.76) measured on the first day had the best predictive performance for early onset neonatal sepsis. (4) Conclusions: Further studies are needed to explore other bi-omarkers of sepsis in both pregnant women and newborns to better predict EOS.

(1) Background: Thrombophilia is a tendency towards hypercoagulability, and it is increased by pregnancy, and peaking around delivery.; (2) Methods: 80 Eighty thrombophilia patients admitted for delivery between 1/10/2017 and 1/12/2021 were prospectively studied, together with 80 eighty age- and para-matched control patients. Patients were admitted for delivery at term by means of cesarean section. The inflammation indexes from the complete blood count values analysis, in during both the 24 hours before and the 24 hours after labor—, extracted from the hospital’s medical records—, were calculated, and then correlated with uterine involution.; (3) Results: In pregnant patients treated for thrombophilia patients, the patients who did not manage to have close their uterine cavity closed with in the first 24-48 hours had significantly higher SII and AISI inflammation indexes SII and AISI , than the onesthose who did manage to have their uterine cavity closed their uterine cavity. In pregnant patients treated for thrombophilia patients, MLR is higher in patients without the Rh factor than in those with the Rh factor. In non-thrombophilia patients, PLR was significantly higher as compared to treated thrombophilia patients. In non-thrombophilia patients, MCVL increased with age and, before labor, while SII and AISI increased with age, postpartum. ; (4) Conclusions: There may be an underlying inflammation state that persisted despite treatment in some pregnant thrombophilia pregnant patients.

1) Background: The screening of preeclampsia (PE) and intrauterine growth restriction (IUGR) represents a constant challenge for obstetricians. The aim of this study was to determine and compare the predictive performance of 4 machine learning-based algorithms for the prediction of PE, IUGR, and their association in a cohort of singleton pregnancies; (2) Methods This prospective study was conducted at a tertiary maternity hospital in Romania, and included 210 pregnancies that underwent first trimester screening. We included clinical and paraclinical data into 4 machine learning-based algorithms decision tree (DT), naïve Bayes (NB), support vector machine (SVM), and random forest (RF), and calculated their predictive performance; (3) Results: RF performed the best when used to predict PE, IUGR, and its subtypes, as well as the association between PE and IUGR. The overall predictive performance of DT for all these disorders was inferior to RF, NB, and SVM. Both SVM and NB had similar accuracy for the prediction of PE, while NB performed better than SVM for the prediction of IUGR; (4) Conclusions: Machine-learning-based algorithms could be useful for the prediction of ischemic placental disease and need to be validated on large cohorts of patients.

The plants Agave sisalana (sisal) and Punica granatum (pomegranate) are rich in saponins, which are secondary metabolites known for their therapeutic properties, including anti-inflammatory effects. Although, Brazil is the world's leading sisal producer, approximately 95% of the leaves are discarded after fiber extraction. Similarly, pomegranate peel waste is abundant in Brazil. To address the need for safe and effective anti-inflammatory treatments. This study aimed to create a topical mucoadhesive gel containing a combination of sisal (RS) and pomegranate residue ex-tracts (PR). In vitro experiments examined isolated and combined extracts, as well as the result-ing formulation, focusing on: 1) phytochemical analysis (total saponin content); 2) cytotoxicity (MTT assay); and 3) pharmacological assessment of anti-inflammatory activity (phagocytosis, macrophage spreading, and membrane stability).Results revealed saponin concentrations in grams per 100 grams of dry extract as follows: SR - 29.91 ± 0.33, PR - 15.83 ± 0.93, Association (A) - 22.99 ± 0.01, Gel Base (G1) - 0.00 ± 0.00, and Association Gel (G2) - 0.52 ± 0.05. In MTT tests for isolated extracts, cytotoxicity values (µg/mL) were 3757.00 for SR and 2064.91 for PR. Converse-ly, A and G2 exhibited no cytotoxicity, with increased cell viability over time. All three anti-inflammatory tests confirmed the presence of this activity in SR, PR, and A. Notably, G2 demon-strated an anti-inflammatory effect comparable to dexamethasone.In conclusion, the gel contain-ing SR and PR holds promise as a novel herbal anti-inflammatory treatment. Its development could yield economic, social, and environmental benefits by utilizing discarded materials in Brazil.

Control of canine infections with Leishmania infantum (L. infantum), a major zoonotic disease in Brazil and southern Europe is becoming increasingly important due to their close proximity to humans, the increasing import of dogs from endemic regions and impact of climate change on vector spreading. Simple, rapid and reliable diagnostic tests are therefore needed to detect infected dogs. Here, we re-evaluated different serological methods for the diagnosis of canine leishmaniosis (CanL) in Croatia and Brazil. The diagnostic performance of the indirect fluorescent antibody test (IFAT) and the VetLine® Leishmania ELISA was compared with three rKLi8.3 based diagnostic test systems, the rKLi8.3 ELISA, the INgezim® Leishma CROM lateral flow test (LFT) and the VetBlot® Leishmania LineBlot. CanL symptomatic dogs were efficiently diagnosed by all tests, except the VetLine® Leishmania ELISA, which is based on whole Leishmania antigens. The advantage of rKLi8.3 was also observed in oligo-and asymptomatic dogs from Brazil and Croatia, although with reduced diagnostic efficiency compared to symptomatic dogs. Similar to IFAT and rKLi8.3 ELISA, the LFT did not cross-react with other common canine pathogens, showed a very high specificity for healthy dogs from endemic regions of both countries and did not react with healthy, vaccinated dogs in Brazil. In conclusion, sero-diagnostic tests based on the rKLi8.3 antigens are superior to whole parasite antigens and the LFT has the advantage of providing a laboratory independent, rapid and specific diagnosis of CanL.

Excess energy from photosynthesis can be collected through biophotovoltaic platforms to generate green electrical power. This research evaluated the in-situ performance of different CAM (Crassulaceae acid metabolism) plants from Calama city located in the Atacama Desert for energy recovery as biophotovoltaic cell (BPV) using AISI 316L and Cu as electrodes. The species evaluated were Aloe perfoliata, Cereus jamacaru, Austrocylindropuntia subulata, Agave potatorum, Malephora crocea, and Kalanchoe daigremontiana. The results indicate that K. daigremontiana can be used as in-situ BFV because it has a maximum cell potential of 0.248 V and a minimum of 0.139 V with a recurrence close to 89% in the ranges [0.2 - 0.25] V. This is one of the few investigations that evaluate the potential of native CAM plants as BFV energy sources, providing new knowledge for the development of sustainable alternatives for horticultural crop production systems.

Epithelioid hemangioendothelioma (EHE) is an extremely rare vascular sarcoma with variable aggressive clinical behavior. In this retrospective study we aimed to investigate prognostic factors based on clinicopathologic findings in a molecular/immunohistochemical confirmed nationwide multicenter cohort of 57 EHE. Patients had unifocal disease (n=29), multifocal disease (n=5), lymph node metastasis (n=8) and/or distant metastasis (n=15) at the time of diagnosis. The overall survival rate was 69.6% at 1 year and 50.5% at 5 years. Survival did not correlate with sex, age or histo-pathological parameters. No survival differences were observed between multifocal and metastatic disease suggesting that multifocality represents early metastases and treatment options are limited in comparison to unifocal disease. In unifocal tumors, survival could be predicted using the risk stratification model of Shibayama et al. dividing the cases into low (n=4), intermediate (n=15) and high (n=3) risk-groups. Larger tumor size (>3cm) and higher mitotic count (>1/10HPF) was asso-ciated with progressive unifocal disease course. Lymph node metastases at time of diagnosis oc-curred in 14.0% of the cases and was mainly associated with tumor localization in the head and neck area proposing lymph node dissection. In conclusion, our results demonstrate the aggressive behavior of EHE, emphasize the prognostic value of a previous described risk stratification model and may provide new insights regarding tumor focality, therapeutic strategies and prognosis.

(1) Background: Urinary tract infections (UTIs) are an important cause of perinatal and maternal morbidity and mortality. The aim of this study was to describe and compare the main pregnancy outcomes among pregnant patients with complicated and uncomplicated UTIs; (2) Methods: This retrospective study included 183 pregnant patients who were evaluated for uncomplicated UTIs and urosepsis in the Urology Department of ‘C.I. Parhon’ University Hospital, and who were followed up at a tertiary maternity hospital- ‘Cuza-voda’ from Romania between January 2014 and October 2023. The control group (183 patients) was randomly selected from the patient’s cohort who gave birth in the same time frame at the maternity hospital without urinary pathology. Clinical and paraclinical data was examined. Descriptive statistics and a conditional logistic regression model were used to analyze our data. (3) Results: Our results indicated that patients with urosepsis had increased risk of premature rupture of membranes (aOR: 5.59, 95%CI: 2.02- 15.40, p&lt; 0.001) and preterm birth (aOR: 2.47, 95%CI: 1.15- 5.33, p= 0.02). We could not demonstrate a statistically significant association between intrauterine growth restriction and preeclampsia with the studied urological pathologies. (4) Conclusions: Careful UTIs screening during pregnancy is needed for preventing maternal-fetal complications.

To understand the biological relevance and mode of action of artificial protein ligands, crystal structures with their protein targets are essential. Here, we describe and investigate all known crystal structures that contain a so-called “molecular tweezer” or one of its derivatives with an attached natural ligand on the respective target protein. The aromatic ring system of these compounds is able to include lysine and arginine side chains, supported by one or two phosphate groups that are attached to the half-moon shaped molecule. We analyse the corresponding crystal structures with 14-3-3 proteins in complex with mono- and diphosphate tweezers. Furthermore, we solved crystal structures of two different tweezer variants in complex with the enzyme 1-Pyrroline-5-carboxyl-dehydrogenase (P5CDH), and found that the tweezers are bound to a lysine and methionine side chain, respectively. The different binding modes and their implications for affinity and specificity are discussed, as well as the general problems in crystallizing protein complexes with artificial ligands.

Doxorubicin (DOX) is a frequently used chemotherapeutic drug for breast cancer, but its site specificity and local internalization into tumor cells is rather low. In this paper we conjugated magnetic nanoparticles (MNPs) with DOX and/or a pseudopeptide NucAnt (N6L) as modality to enhance DOX-induced antitumor effects in breast cancer cells (BT474). In this context, we determined cellular uptake of MNP formulations, analyzed cell viability and expression of apoptotic and cell cycle proteins after magnetic hyperthermia (43°C, 1 h) in vivo and in vitro. We have shown that i) the presence of N6L on the surface of DOX-functionalized MNPs increases their internalization into a target cells and potentiates the cytotoxic potential of the anticancer drug, ii) in combination with hyperthermia, DOX functionalized MNPs influence the expression of apoptotic and cell cycle proteins, and also favors tumor regression in vivo. Our data show that intratumoral application of DOX coupled MNPs is able to overcome biological barriers to chemotherapeutic drugs, enabling them to penetrate into the target cells. Combined with hyperthermia these MNPs can be an effective method in enhancing the localised delivery and penetration of DOX into breast cancer cells.

The microbiome is capable of modulating the bioavailability of chemotherapy drugs mainly due to metabolizing these agents. Multiple cytostatic bacterial metabolites were recently identified that have cytostatic properties on cancer cells. In this study we addressed the question whether the cytostatic bacterial metabolites (cadaverine, indolepropionic acid, indoxylsulfate) can interfere with the cytostatic effects of the chemotherapy agents used in the management of breast cancer (doxorubicin, gemcitabine, irinotecan, methotrexate, rucaparib, 5-fluorouracil, paclitaxel). The chemotherapy drugs were applied in a wide concentration range to which a bacterial metabolite was added in a concentration within its serum reference range and the effects on cell proliferation were assessed. There was no interference between doxorubicin, gemcitabine, irinotecan, methotrexate, rucaparib and the bacterial metabolites. Nevertheless, cadaverine increased the Hill coefficient of the inhibitory curve of 5-fluorouracil and indolepropionic acid increased the IC50 value of 5-fluorouracil that are either disadvantageous effects or effects of unknown significance. Nevertheless, indolepropionic acid decreased the IC50 value of paclitaxel that is a potentially advantageous combination.

In the last decades, technological advances related to RNA manipulation enabled and expanded its application in vaccine development. This approach comprises synthetic single-stranded mRNA molecules that direct the translation of the antigen responsible for activating the desired immune response. The success of RNA vaccines depends on the delivery vehicle employed. Among the systems, yeasts emerge as a new approach to a natural delivery platform. The presence of β-glucans and mannans in its wall is responsible for the adjuvant action of this system. Yeasts are already employed to deliver protein antigens, with success and efficacy demonstrated through pre-clinical and clinical trials. Yeast β-glucan capsules, microparticles, and nanoparticles are capable of modulating host immune responses and have a high capacity to carry RNA and small molecules, with bioavailability upon oral immunization and with targeting to receptors present in anti-gen-presenting cells (APCs). Besides, yeasts are interesting vehicles for the protection and specific delivery of therapeutic vaccines based on shRNA or dsRNA. In this review, we present an overview of the attributes of yeast or its derivatives for the delivery of RNA-based vaccines, discussing their current challenges and prospects for using this promising strategy.

There is a need for multimodal strategies to keep research participants informed about study results. Our aim was to characterize preferences of genomic research participants from two institutions along four dimensions of general research result updates: content, timing, mechanism, and frequency. Methods: We conducted a web-based cross-sectional survey that was administered from 6-25-2018 to 12-5-2018. Results: 397 participants completed the survey, most of whom (96%) expressed a desire to receive research updates. Preferences with high endorsement included: update content (brief descriptions of major findings, descriptions of purpose and goals, and educational material); update timing (when the research is completed, when findings are reviewed, when findings are published, and when the study status changes); update mechanism (email with updates, and email newsletter); and update frequency (every three months). Hierarchical cluster analyses based on the four update preferences identified four profiles of participants with similar preference patterns. Very few participants in the largest profile were comfortable with budgeting less money for research activities so that researchers have money to set up services to send research result updates to study participants. Conclusion: This work provides evidence of a need for funders to incentivize researchers to communicate results to participants.

In golden retriever dogs, a 1 bp deletion in the canine TTC8 gene has been shown to cause progressive retinal atrophy (PRA), the canine equivalent of retinitis pigmentosa. In humans, TTC8 is also implicated in Bardet-Biedl syndrome (BBS). To investigate if the affected dogs only exhibit a non-syndromic PRA or develop a syndromic ciliopathy similar to human BBS, we recruited ten affected dogs to the study. The progression of PRA for two of the dogs was followed for two years, and a rigorous clinical characterization allowed a careful comparison with primary and secondary characteristics of human BBS. In addition to PRA, the dogs showed a spectrum of clinical and morphological signs similar to primary and secondary characteristics of human BBS patients, such as obesity, renal anomalies, sperm defects, and anosmia. We used Oxford Nanopore long-read cDNA sequencing to characterize retinal full-length TTC8 transcripts in affected and non-affected dogs, the results of which suggest that three isoforms are transcribed in the retina, and the 1 bp deletion is a loss-of-function mutation, resulting in a canine form of Bardet-Biedl syndrome with heterogeneous clinical signs.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.