The correspondence between classical and quaternion quantum equations, permits considering the universe (vacuum) as an ideal elastic solid. Elementary particles would have to be standing or soliton-like waves. Tension induced by the compression and twisting of the elastic medium would increase the energy density, consequently generate a gravity forcing and affect the wave speed. Consequently the gravity could be described by an index of refraction. Theory was created by combining the Cauchy model of the elastic continuum with the Planck-Kleinert crystal hypothesis. The quaternion-imaginary Lagrange’an, the quaternion motion equation and the quaternionic oscillator allowed deriving: - The Schrödinger equation from the functional integral, which identifies the quaternion-imaginary quantum Hamiltonian. - The 2nd order wave equation system describing both the bosons and the gravity in terms of quaternionic Poisson equation. - The first order quaternionic wave equation system. - The family of the second order wave equation systems describing both the particles and the generated quaternionic force-fields (four-potentials). - The fundamental Planck and gravity constants. - The quaternionic continuity equation in an ideal elastic solid.

Tryptophan is an essential nutrient required to produce niacin (vitamin B3), which is needed for energy metabolism and DNA production. Alterations in tryptophan metabolism could have significant effects on aging and musculoskeletal health. The kynurenine pathway, the main catabolic route of tryptophan, is modulated by inflammatory factors, which are increased in older persons, a process known as inflammaging. Osteoporosis, sarcopenia, osteosarcopenia and frailty have also been linked with chronic increased levels of inflammatory factors. Due to the disruption of the kynurenine pathway by chronic inflammation and/or changes in the gut microbiota, serum levels of toxic kynurenines are increased and have been associated with osteoporosis, sarcopenia and frailty. In contrast, anabolic end products of this pathway, such as picolinic acid, have demonstrated a beneficial effect on bone and muscle. In addition, recent studies have shown that physical activity can modulate this pathway by promoting the secretion of anabolic kynurenines. According to the evidence collected, kynurenines could have a promising role as biomarkers for osteoporosis sarcopenia, osteosarcopenia and frailty in older persons. In addition, some of these metabolites could become important targets for developing new pharmacological treatments for these conditions.

Digital twins are the foundation of autonomous off-road vehicles. Dynamic reduction methods are one of several ways to develop digital twins for off-road vehicles. The article commences with a comprehensive overview of the most widely used dynamic reduction methods and then introduces performance metrics for assessing their efficacies in the context of digital twins. The paper additionally includes a detailed mathematical derivation of the state-space representation for reduced-order finite element models. The state-space representation of the reduced finite element models facilitates their export to problem-solving environments for dynamic analysis. The state-space models are eventually solved utilizing the built-in libraries of numerical solvers in textual and graphical programming platforms. In addition, the article identifies the set of solvers that best suit the simulation of virtual models for off-road vehicles. This article also includes an evaluation of the simulation results of digital models with modes ranging from 0 to 30 Hz. In addition, the article demonstrates the lower bound of the frequency range necessary and sufficient to be retained in off-road vehicle virtual models. Finally, the paper presents the simulation outcomes for digital models of commercial off-road vehicles with custom-built control, electrical, and control systems.

The presence of a non-structural protein 1 (NS1) in tick-borne encephalitis (TBE) vaccines and the possible induction of an NS1-specific immune response in vaccinated individuals remains a somewhat controversial topic. Previously, we detected the presence of NS1 in Encepur TBE vaccine by mass spectrometry and found the induction of NS1-specific IgG antibodies in mice vaccinated with FSME-Immun TBE vaccine. Here, in this follow-up study, we examined the dynamics and extent of the NS1-specific IgG response in mice vaccinated with these two vaccines in more detail and compared it with the IgG response to the whole virus (WV). Mice were vaccinated at two-week intervals with a total of six doses of each vaccine, and levels of IgG antibodies to TBE virus WV and NS1 were measured by ELISA after each dose. Both vaccines elicited a robust anti-WV IgG response after two doses. The Encepur vaccine did not elicit NS1-specific IgG even after all six doses. In contrast, FSME-Immun vaccine triggered production of NS1-specific IgG after four doses. The results indicate that FSME-Immun is the only vaccine that elicits an NS1-specific antibody response in mice. However, compared to WV-specific IgG, the NS1-specific response is weaker, and a higher number of doses is required to induce detectable levels of NS1-specific IgG antibodies.

One of the critical tools for early detection and subsequent evaluation of the incidence of lung diseases is chest radiography. This study presents a real-world implementation of a convolutional neural network (CNN) based Carebot Covid app to detect COVID-19 from chest X-ray (CXR) images. Our proposed model takes the form of a simple and intuitive application. Used CNN can be deployed as a STOW-RS prediction endpoint for direct implementation into DICOM viewers. The results of this study show that the deep learning model based on DenseNet and ResNet architecture can detect SARS-CoV-2 from CXR images with precision of 0.981, recall of 0.962 and AP of 0.993.

Abstract Purpose of review: RNA therapeutics are a new and rapidly expanding class of drugs to prevent or treat a wide spectrum of diseases. We discuss the defining characteristics of the diverse family of molecules under the RNA therapeutics umbrella. Recent findings:RNA therapeutics are designed to regulate gene expression in a transient manner. For example, depending upon the strategy employed, RNA therapies offer the versatility to replace, supplement, correct, suppress, or eliminate the expression of a targeted gene. RNA therapies include antisense nucleotides, microRNAs and small interfering RNAs, RNA aptamers, and messenger RNAs. Further, we discuss the mechanism(s) by which different RNA therapies either reduce or increase the expression of their targets. Summary: We review the RNA therapeutics approved (and those in trials) to treat cardiovascular indications. RNA-based therapeutics are a new, rapidly growing class of drugs that will offer new alternatives for an increasing array of cardiovascular conditions.

All over the world energy is used for different purposes and hence its continuous high demand which has brought about an increase in crisis and prices of energy. Ghana has faced a lot of supply and high electricity consumption challenges over a period of time. The Energy Commission of Ghana has developed regulations and guidelines to help reduce high consumption challenges among users, these included the replacement of incandescent bulbs with fluorescent bulbs, ban of importation of low energy efficient appliances. In spite of the effort to reduce electricity wastage, there is still a high increase in electricity consumption. The research investigated what contributed to electricity consumption in Kwame Nkrumah University of Science and Technology with the lecture halls as the main focus, the research also analyzed the current occupant behavior characterized by the electrical energy consumption practices. And investigated how the contemporary theories for reducing energy consumption was used in the lecture halls. A questionnaire survey was conducted to investigate occupants on their energy use practices in lecture halls that causes wastages, observation was made to establish relevant data on the use of contemporary theories for energy reduction in lecture halls. In a total of 110 occupants that responded to the questionnaire, 79 occupants almost always turn off electrical fitting and fixtures when not in use. From the responses, a majority of the occupants claimed to comply to best practices of energy use. The research concluded that some contemporary theories to reduce energy consumptions was not used and considered in the lecture halls.

With the onset of the COVID19 pandemic, information technology has played a critical role in healthcare. A broad spectrum of information technology tools and applications played an essential role to create awareness of the COVID19 vaccination drive and its health benefits. We use the COVID-19 Global Beliefs, Behaviors, and Norms Survey for analysis of prevalence and factors associated with vaccination drives among men and women aged 20-80 years in 60 countries worldwide. Our analysis of the global survey offers a unique perspective about the role of information technology associated with vaccination drives involving social norms and human behavior among 437,236 respondents. The international survey was organized using a pre-registered randomized experiment demonstrating the role of technology in reaching out to people based in diverse communities and evaluating their beliefs, behavior, and social norms. The study shows that vaccine acceptance can vary due to descriptive norms. Our analysis shows 65.06% of people all over the globe are willing to get vaccinated and a large proportion of the population thinks that the COVID19 pandemic is a viable threat to the community and preventive measures need to be taken including vaccination drives.

Knowledge on the function of Connexin-43 on macrophages is gradually increasing and recent studies show how macrophages utilise Connexin-43. Migration, antigen-presentation and some forms of intercellular communication in macrophages are Connexin-43-dependant. Delicate processes, such as electrochemical support in conduction of the heartbeat in the AV-node, immunomodulatory regulation in the lungs and macrophage-differentiation are performed using Connexin-43 in macrophages. The relevance on pathophysiology becomes evident in inflammatory bowel disease, tumour networks and HIV in which aberrant function of Connexin-43 has been observed. Although many physiological, as well as pathophysiological functions were found to be Connexin-43-dependant, some still remain debated: the involvement of Connexin-43 in phagocytosis and polarisation, as well as its involvement in the mortality in murine sepsis are still unclear. These functions as well as further involvement in increasingly complex functions of the macrophage pose possible fields of research.

The chicken embryo is a widely used experimental animal-model in many studies such as developmental biology and to study the physiological responses and adaptation to altered environments as well as for cancer and neurobiology research. Embryonic heart rate is an important physiological variable useful as an index reflecting the embryo's natural activity and is considered one of the most difficult parameters to measure. An acceptable measurement technique of embryonic heart rate should provide a reliable cardiac signal quality while maintaining adequate gas exchange through the eggshell along the incubation and embryonic developmental period. In this paper, we presented a detailed design and methodology for a non-invasive PPG-based prototype (Egg-PPG) for real-time and continuous monitoring of embryonic heart rate during incubation. An automatic embryonic cardiac wave detection algorithm, based on normalised spectral entropy, is described. The developed algorithm successfully estimated the embryonic heart rate with 98.7% accuracy. We believe that the developed overall system presented in this paper is showing a promising solution for non-invasion, real-time monitoring of embryonic cardiac signal, which can be used in both experimental studies (e.g., developmental embryology and cardiovascular research) and in industrial incubation applications.

The widely spread CoronaVirus Disease (COVID)- 19 is one of the worst infectious disease outbreaks in history and has become an emergency of primary international concern. As the pandemic evolves, academic communities have been actively involved in various capacities, including accurate epidemic estimation, fast clinical diagnosis, policy effectiveness evaluation and development of contract tracing technologies. There are more than 23,000 academic papers on the COVID-19 outbreak, and this number is doubling every 20 days while the pandemic is still on-going [1]. The literature, however, at its early stage, lacks a comprehensive survey from a data analytics perspective. In this paper, we review the latest models for analyzing COVID19 related data, conduct post-publication model evaluations and cross-model comparisons, and collect data sources from different projects.

The past years saw the rise of genomic biobanks and mega-scale meta-analysis of genomic data that promise to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limit the global understanding of disease risk and intervention efficacy, but also inhibit viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared, and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable, computable, operate without access to raw data due to privacy concerns. But they must be comparable, both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of commonly used genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks, locally and internationally, increase the accuracy of association analyses, and inform developmental efforts.

The Avian retina is far less known than that of mammals such as mouse and macaque, and detailed study is overdue. The chicken (Gallus gallus) has potential as a model, in part because research can build on developmental studies of the eye and nervous system. One can expect differences between bird and mammal retinas simply because whereas most mammals have three types of visual photoreceptor birds normally have six. Spectral pathways and colour vision are of particular interest, because filtering by oil droplets narrows cone spectral sensitivities and birds are probably tetrachromatic. The number of receptor inputs is reflected in the retinal circuitry. The chicken probably has four types of horizontal cell, there are at least 11 types of bipolar cell, often with bi- or tri-stratified axon terminals, and there is a high density of ganglion cells, which make complex connections in the inner plexiform layer. In addition, there is likely to be retinal specialisation, for example chicken photoreceptors and ganglion cells have separate peaks of cell density in the central and dorsal retina, which probably serve different types of behaviour.

Eight samples of limestones and marbles were studied by neutron diffraction to collect 2 Quantitative Texture (i.e., Crystallographic Preferred Orientations or CPO) of calcite deforming at 3 different depths in the crust. We studied the different Texture patterns developed in shear zones at 4 different depth and their influence on seismic anisotropies. Samples were collected in the French and 5 Italian Alps, Apennines, and Paleozoic Sardinian basement. They are characterized by isotropic to 6 highly anisotropic (e.g., mylonite shear zone) fabrics. Mylonite limestones occur as shear zone horizons 7 within the Cenozoic Southern Domain in Alpine thrust-and-fold belts (Italy), the Briançonnais domain 8 of the Western Alps (Italy-France border), the Sardinian Paleozoic back-thrusts or in the Austroalpine 9 intermediate units. The analyzed marbles were collected in the Carrara Marble, in the Austroalpine Units 10 in the Central (Mortirolo) and Western Alps (Valpelline). The temperature and depth of development of fabrics vary from < 100◦C, to 800◦C and depth from <10 km to about 30 km, corresponding from upper 12 to lower crust conditions. Quantitative Texture Analysis shows different types of patterns for calcite: 13 random to strongly textured. Textured types may be further separated in orthorhombic and monoclinic 14 (Types A and B), based on the angle defined with the mesoscopic fabrics. Seismic anisotropies were 15 calculated by homogenizing the single crystal elastic tensor, using the Orientation Distribution Function 16 calculated by the Quantitative Texture Analysis. The resulting P- and S-waves anisotropies show a wide 17 variability due to the textural types, temperature and pressure conditions, and dip of the shear planes.

This work is aimed at promoting a healthier means of livelihood by investigating insignificant areas of pollution. In this work, soy candles produced from soybeans were proven as healthier alternatives to paraffin candles. Soxhlet extraction method was used with hexane as solvent. The extracted oil were then solidified. The wax was moulded into candle and tests were carried out to prove its claims as a safer alternative to paraffin wax. The results supported this claims that soy candles is more economical and produced lesser soot than the paraffin candles.

The underlying molecular basis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is not well understood. Characterized by chronic, unexplained fatigue, a disabling payback following exertion (“post-exertional malaise”) and variably presenting, multi-system symptoms, ME/CFS is a complex disease which demands concerted biomedical investigation from disparate fields of expertise. ME/CFS research and patient treatment have been challenged by the lack of diagnostic biomarkers and finding these is a prominent direction of current work. Despite these challenges, modern research demonstrates a tangible biomedical basis for the disorder across many body systems. This evidence is largely comprised of disturbances to immunological and inflammatory pathways, autonomic and neurologic systems, abnormalities in muscle and mitochondrial function, shifts in metabolism, and gut physiology or gut microbiome disturbances. It is possible that these threads are together entangled as parts of an underlying molecular pathology reflecting a far-reaching homeostatic shift affecting each of these systems. Due to the variability of non-overlapping symptom presentation or precipitating events such as infection or other bodily stresses, the initiation of body-wide pathological cascades with similar outcomes stemming from different causes may be implicated in the condition. Patient stratification to account for this heterogeneity is therefore one important consideration during exploration of potential diagnostic developments.

Blackcurrant leaf chlorosis associated virus (BCLCaV) was detected recently by next-generation sequencing (NGS) and proposed as a new and distinct species in the genus Idaeovirus. Genomic components of BCLCaV that were detected and confirmed include: 1) RNA-1 that is monocistronic and encodes the replicase complex; 2) a bicistronic RNA-2 that encodes a movement protein (MP) and the coat protein (CP) of the virus, with open reading frames (ORF) that overlap by a single adenine (A) nucleotide (nt) representing the third position of an opal stop codon of the MP ORF2a and the first position of the start codon of the CP ORF2b; 3) a subgenomic form of RNA-2 (RNA-3) that contains ORF2b; and 4) a concatenated form of RNA-2 that consists of a complementary and inverted RNA-3 conjoined to the full-length RNA-2. Analysis of NGS-derived paired-end reads revealed the existence of bridge reads encompassing the 3’-terminus and 5’-terminus of RNA-2 or RNA-3 of BCLCaV. The full RNA-2 or RNA-3 could be amplified using outward facing or abutting primers; also RNA-2/RNA-3 could be detected even after three consecutive RNase R enzyme treatments with denaturation at 95 ^oC preceding each digestion. Evidence was obtained indicating that there are circular forms of BCLCaV RNA-2 and RNA-3.

The research develops and validates new decomposition models for DNI estimations from Southern African data. The results demonstrated improved DNI estimation accuracy compared to the baseline models across all testing and validation datasets. These outcomes suggest that utilising a localised model can significantly enhance DNI estimations for Southern Africa and potentially for developing similar models in diverse geographic regions worldwide. Furthermore, clustered models highlighted the potential advantages of grouping data based on shared geographical and climatic attributes. This clustering approach could enhance decomposition model performance, particularly when local data is limited or data is available from multiple nearby stations. The Southern African decomposition model, which encompasses a wide spectrum of climatic regions and geographic locations, exhibited notable improvements over the baseline models despite occasional overestimation or underestimation. The overall metrics affirm the substantial advancement achieved with the Southern African model. This study focused on validating the model for hourly DNI in Southern Africa within a range of clearness index-intervals from 0.175 to 0.875. Implementing accurate decomposition models in developing countries can accelerate the adoption of renewable energy sources, diminishing reliance on coal and fossil fuels.

In the context of global warming and increasing scarcity of fresh water resources, it becomes siginificant to evaluate the contribution and evolution of non-rainfall waters such as dew. This study therefore evaluates the relative dew and rain contributions in three sites in south-western of Madagascar (Ifaty, Toliara and Andremba), a semi-arid region which suffers of a strong water deficit. The studied period is 1991 – 2023, with extrapolation to 2033. Dew is calculated from meteo data using a well-established energy model. The extrapolation uses an artificial neural network approach. While the yearly dew/rain ratio remains modest (3-4%) dew forms regularly (2-3 days in average between events), in contrast to rain (10-15 days). The evolutions of dew and rain are similar, with an increase from 1991 to 2000, a decrease up to 2018 and a further increase till 2033. These oscillations follow the Indian Ocean dipole variations and should be influenced by the climate change. Dew contribution to the water balance is important during the dry season (Apr.-Oct.), up to 80%. Dew therefore appears to be a reliable and sustainable resource for plants, small animals and population, especially during droughts.

The construction industry is notable contributors to atmospheric dust particulate emissions. The particulate matter (PM) produced in construction processes contains a range of chemically hazardous substances, posing significant health risks (HR) to individuals. The occupational health hazards research in construction has become a focal point of interest internationally. Initiated in the early 2000s, there has been a growing demand within the construction research community for the creation of a unified PM database that encapsulates a wide array of construction activities. Previous studies have endeavored to establish a PM database for various construction contexts, yet they have fallen short in thoroughly addressing the diversity of construction materials and the levels of toxic substances (TS) within the PM. This study validates the proof of value that HR associated with construction processes can be measured using PM and TS datasets generated from various work processes using a variety of construction materials. This was accomplished through a semi-automated Building Information Modeling (BIM)-based plugin, which streamlines the assessment of occupational HR in construction projects alongside ongoing work processes. To validate the practicality of the Health Risk Index (HRI) determination via this BIM plugin, a case study on a real renovation project was executed. This system provides construction supervisors with a tool to visually assess the HR of daily operations, thereby facilitating the adoption of preemptive measures to protect the health of construction workers.

This article postulates that, in principle, it is possible (1) to develop linkages between the extractive sector and other economic sectors; (2) for such linkages to contribute to economic diversification; and (3) for economic diversification to potentially drive positive economic transformation. We argue that achieving this three-stepped pathway is impossible without also achieving some level of political and social transformation. Empirically, many resource-rich countries have failed to develop linkages. Or, if they have, the linkages built remain limited to the development of supply chains serving the extractive sector, contributing little to economic diversification. In this article, we refer to limited linkages and dependence on exporting unprocessed minerals as the centripetal force of the extractive sector. This implies that capital investments and economic activities are concentrated around the extractive sector. We propose an alternative theoretical model that strives to foster the centrifugal force of the extractive sector – a term we use to capture the three-stepped pathway. This model is underpinned by multiple factors and their interactions, which are within the purview of the complex state and market relationship (posing as a challenge) and the role of minerals in the global transformation towards a clean energy system (posing as an opportunity).

Climate change-induced temperature fluctuations pose a significant threat to crop production, particularly in the Southern Hemisphere. This study investigates the transcriptome and physiological responses of rapeseed to post-flowering temperature increases, providing valuable insights into the molecular mechanisms underlying rapeseed tolerance to heat stress. Two rapeseed genotypes, Lumen and Solar, were assessed under control and heat stress conditions in field experiments conducted in Valdivia, Chile. Results showed that seed yield and seed number were negatively affected by heat stress, with genotype-specific responses. Lumen exhibited a 9.3% average seed yield reduction, while Solar showed a 28.7% reduction. RNA-seq analysis of siliques and seeds revealed tissue-specific responses to heat stress, with siliques being more sensitive to temperature stress. Hierarchical clustering analysis identified distinct gene clusters reflecting different aspects of heat stress adaptation in siliques, with a role for protein folding in maintaining silique development and seed quality under high temperature conditions. In seeds, three distinct patterns of heat-responsive gene expression were observed, with genes involved in protein folding and response to heat showing genotype-specific expression. Gene coexpression network analysis revealed major modules for rapeseed yield and quality, as well as the trade-off between seed number and seed weight. Overall, this study contributes to understanding the molecular mechanisms underlying rapeseed tolerance to heat stress and can inform crop improvement strategies targeting yield optimization under changing environmental conditions.

We prove a version of Ekeland Variational Principle (EkVP) in a weighted graph $G$ and its equivalence to Caristi fixed point theorem and to Takahashi minimization principle. The usual completeness and topological notions are replaced with some weaker versions expressed in terms of the graph $G$. The main tool used in the proof is the OSC property for sequences in a graph. Converse results, meaning the completeness of graphs for which one of these principles holds is also considered.

Neural networks require a large quantity of training spectra and detector responses in order to learn to solve the inverse problem of neutron spectrum unfolding. In addition, due to the under-determined nature of unfolding, non-physical spectra which would not be encountered in usage should not be included in the training set. While physically realistic training spectra are commonly determined experimentally or generated through Monte Carlo simulation, this can become prohibitively expensive when considering the quantity of spectra needed to effectively train an unfolding network. In this paper, we present three algorithms for the generation of large quantities of realistic and physically motivated neutron energy spectra. Using an IAEA compendium of 251 spectra, we compare the unfolding performance of neural networks trained on spectra from these algorithms, when unfolding real-world spectra, to two baselines. We also investigate general methods for evaluating the performance of and optimizing feature engineering algorithms.

Human motion analysis using inertial measurement units (IMUs) has recently been shown to provide accuracy similar to the gold standard, marker-based optical motion capture, but at much lower costs and while being less restrictive and time-consuming. However, IMU-based motion analysis requires precise knowledge of the orientation in which the sensor is attached to the body segments. This knowledge is commonly obtained via an anatomical calibration procedure based on precisely defined poses or motions, which is time-consuming and error-prone. In the present work, we propose a self-calibrating approach for magnetometer-free joint angle tracking that is suitable for joints with two degrees of freedom (DoF), such as the elbow, ankle, and metacarpophalangeal finger joints. The proposed methods exploit kinematic constraints to simultaneously identify the joint axes and the heading offset. The experimental evaluation shows that the proposed methods are able to estimate plausible and consistent joint axes from just ten seconds of arbitrary elbow joint motion. Comparison with optical motion capture shows that the proposed methods yield joint angles with similar accuracy as a conventional IMU-based method while being much less restrictive. Therefore, the proposed methods improve the practical usability of IMU-based motion tracking in many clinical and biomedical applications.

In the context of global warming and reduction in fresh water availability is presented a study of the evolution of dew, rain and evapotranspiration in the NW of Africa. The time periods are concerned with the years 2005-2020, using existing data, and years 2020-2100, using the low and high emissions representative concentration pathway scenarios RCP 2.6/8.5 from the Cordex database. A continuous decrease in rain precipitation is observed, on order of -14 mm/decade for the more credible scenario RCP 8.5. The amplitude is maximum on the coast and on the foothills of Atlas. A clear decrease in dew yields is also observed along a NW/SE axis, strongly correlated with a corresponding decrease in relative humidity (up to 7%). Chemical dew and rain data in the representative site of Mirleft correspond to the major cations Na+ > Ca2+ > Mg2+ > K+, similar to a local spring water. Concentrations in rain are about two times less than in dew water. Ionic concentrations are compatible with WHO standards. The seasonal variations of the ionic concentrations in dew and rain follow a volume dilution dependence. The expected diminution in dew and rain volumes according to the RCPs 2.6 and 8.5 should increase the dew and rain ionic concentrations in the future.

Based on some geometrical properties of the Rabinovich system the closed-form solutions of the equations has been established. Moreover the Rabinovich system is reduced to a nonlinear differential equation depending on an auxiliary unknown function. The approximate analytical solutions are built using the Optimal Auxiliary Functions Method (OAFM). A good agreement between the analytical and corresponding numerical results has been performed. The accuracy of the obtained results emphasizes that this procedure could be successfully applied for more dynamical systems with these geometrical properties.

Snowpack loss in midlatitude mountains is ubiquitously projected by Earth system models, though the magnitudes, persistence and time horizons of decline vary. Using daily downscaled hydroclimate and snow projections we examine changes in snow seasonality across the U.S. Pacific Southwest region during a simulated severe 20-year dry spell in the 21st century (2051–2070) developed as part of the 4th California Climate Change Assessment to provide a "stress test" for water resources. Across California’s mountains, substantial declines (30–100% loss) in median peak annual snow water equivalent accompany changes in snow seasonality throughout the region compared to the historic period. We find 80% of historic seasonal snowpacks transition to ephemeral conditions. Subsetting empirical-statistical wildfire projections for California by snow seasonality transition regions indicates a two-to-four-fold increase in burned area, consistent with recent observations of high elevation wildfires following extended drought conditions. By analyzing six of the major California snow-fed river systems we demonstrate snowpack reductions and seasonality transitions result in concomitant declines in annual runoff (47-58% of historic values). The negative impacts to statewide water supply reliability by the projected dry spell will likely be magnified by changes in snowpack seasonality and increased wildfire activity.

Eccentric punching shear can occur in concrete slab-column connections when the connection is subjected to shear and unbalanced moments. Typically, this situation results in edge and corner columns and is thus a common practical case. However, most punching experiments in the literature are concentric punching shear. This paper presents a developed database of eighty-eight experiments of flat slabs under eccentric punching shear, including a summary of the testing procedure of each reference and a description of the slab specimens. Additionally, a linear finite element analysis of all the specimens is included to determine the relevant sectional shear forces and moments. Finally, the ultimate shear stresses from the database experiments are compared to the shear capacities determined with ACI 318-19, Eurocode 2 NEN-EN 1992-1-1:2005, and the Model Code 2010. The comparison shows that the Model Code 2010 is the most precise in the predictions with an average tested over predicted ratio of 0.96 and a coefficient of variation of 27.96%. It can be concluded that this study represents the inconsistencies of the currently used design methods and the lack of experimental information.

B lymphocyte development has two DNA recombination processes: V(D)J recombination of the immunoglobulin (Igh) gene variable region and class switching of the Igh constant regions from IgM to IgG, IgA, or IgE. V(D)J recombination is required for successful maturation of B cells from pro-B to pre-B to immature-B and then to mature B cells in the bone marrow. CSR occurs outside of the bone marrow when mature B cells migrate to peripheral lymphoid organs, such as spleen and lymph nodes. Both V(D)J recombination and CSR depend on an “open chromatin” state that makes DNA accessible to specific enzymes, recombination activating gene (RAG), and activation-induced cytidine deaminase (AID). Acetyltransferases GCN5 and PCAF possess redundant functions acetylating histone H3 lysine 9 (H3K9). Here, we generated a mouse model that lacks both GCN5 and PCAF in B cells. We found that double-deficient mice possess low levels of mature B cells in the bone marrow and peripheral organs, an accumulation of pro-B cells in bone marrow, and reduced CSR levels. We conclude that both GCN5 and PCAF are required for B cell development in vivo.

Music and language are hypothesized to share neural resources, particularly at the level of syntax processing. Recent reports suggest that attention modulates this sharing of neural resources, but the time-course of the effects of attention, and the degree to which attention operates similarly on music and language, are yet unclear. In this EEG study we manipulate the syntactic structure of simultaneously presented musical chord progressions and garden-path sentences in a modified rapid serial visual presentation paradigm, while varying top-down attentional demands to the two modalities. The Early Right Anterior Negativity (ERAN) was observed in response to both attended and unattended musical syntax violations. In contrast, an N400 was only observed in response to attended linguistic syntax violations, and a P3 only in response to attended musical syntax violations. Results show that top-down allocation of attention indeed affects the processing of syntax in both music and language, with different neural resources acting upon the two modalities particularly at later stages of cognitive processing. However, the processing of musical syntax at an earlier stage of the perceptual-cognitive pathway, as indexed by the ERAN, is partially automatic, and is strongly indicative of separate neural resources for music and language.

Dogs are considered property under UK law, while current discourses of pet ownership place canine companions as part of an extended family. This means sentences for those who steal dogs are not reflective of a dogs’ sentience and agency, rather reflecting the same charges for those who steal a laptop or wallet. This is particularly problematic as dog theft is currently on the rise in England and Wales and led to public calls to change the law. Recognizing that a more robust analysis of dog theft crime statistics is required, we gathered dog theft data for 2015, 2016 and 2017 from 37 of 44 police forces through FOI requests. This paper uses this data to examine how dog theft crime statistics are constructed; assesses the strengths and weaknesses of this data; and categorizes, maps and measures dog theft changes temporally per police force in England and Wales. Our findings reveal there has been an increase in dog theft crimes, 1,294 in 2015, 1,525 in 2016 (+17.85%), and 1,678 in 2017 (+10.03%); and a decrease in court charges related to dog theft crimes, 62 (4.7%) in 2015, 48 (3.14%) in 2016, 37 (2.2%) in 2017. There were police force inconsistencies in recording dog theft crime which meant some data was unusable or could not be accessed or analysed. There is a need for a qualitative study to understand dog theft crime in different areas, and standardised approach to recording the theft of a dog by all forces across England and Wales.

Background: The vegetative state (VS)/unresponsive wakefulness syndrome (UWS) denotes brain-injured, awake patients who are seemingly without awareness. Still, up to 15% of these patients show signs of covert consciousness when examined by functional magnetic resonance imaging (fMRI) or EEG, which is known as cognitive motor dissociation (CMD). Most experts prefer the term unresponsive wakefulness syndrome to avoid the negative connotations associated with vegetative state and to highlight the possibility for CMD. However, the perception of VS/UWS by the public has never been studied systematically. Methods: Using an online crowdsourcing platform, we recruited 1297 participants from 32 countries. We investigated if vegetative state and unresponsive wakefulness syndrome might have a different influence on attitudes towards VS/UWS and CMD. Results: Participants randomized to be inquired about the vegetative state believed that CMD was less common (mean estimated frequency in unresponsive patients 38.07% ± SD 25.15) than participants randomized to unresponsive wakefulness syndrome (42.29% ± SD 26.63; p=0.016). Attitudes towards treatment withdrawal were similar. Most participants preferred unresponsive wakefulness syndrome (60.05%), although a sizeable minority favored vegetative state (24.21%; difference 35.84%, 95% CI 29.36 to 41.87; p<0.0001). Searches on PubMed and Google Trends revealed that unresponsive wakefulness syndrome is increasingly used by academics but not lay people.Discussion: Simply replacing vegetative state with unresponsive wakefulness syndrome may not be fully appropriate given that 1 of 4 prefer the first term. We suggest that physicians take advantage of the controversy around the terminology to explain relatives the concept of CMD and its ethical implications.

In this paper, an offshore airborne wind energy (AWE) farm consisting of three non-reversing pumping mode AWE systems is modelled and simulated. The AWE systems employ permanent magnet synchronous generators (PMSG). A direct interconnection technique is developed and implemented for AWE systems. This method is a new approach invented for interconnecting offshore wind turbines with the least number of required offshore-based power electronic converters. The direct interconnection technique can be beneficial in improving the economy and reliability of marine airborne wind energy systems. The performance and interactions of the directly interconnected generators inside the energy farm internal power grid are investigated. The results of the study conducted in this paper, show the directly interconnected AWE systems can exhibit a poor load balance and significant reactive power exchange which must be addressed. Power control strategies for controlling the active and reactive power of the AWE farm are designed, implemented, and promising results are discussed in this paper.

In this work a research on pulsed electrochemical micromachining of Stainless Steel is presented. A suitable equipment to study the process is described as well as a fitting procedure to machine and measure the variables involved. A tool of Tungsten with a tip of about 5 mm diameter sunk in an electrolyte of NaNO₃ is used for the process. The pulse on-time must be maintained in the order of ns to achieve a good current confinement, since the tool is active. Some experiments were made to assess the most important variables of the process, as current confinement, surface roughness, material removal rate and efficiency. It is observed that the current confinement get worse when the pulse on-time increases, as well as surface roughness. The material removal rate and the efficiency increase with the voltage amplitude and the pulse on-time. The voltage amplitude must be higher than 12 V so that the phenomenon of passivation disappears. There is a compromise in the choice of the variables, so a suitable combination of parameters is determined so that a good material removal rate with an acceptable result is achieved.

The catalytic decomposition of methane (CDM) process produces hydrogen in a single stage and avoids the CO₂ emission thanks to the formation of high added value carbon nanofilaments as by-product. In this work, Ni monometallic and Ni-Co, Ni-Cu and Ni-Fe bimetallic catalysts are tested in the CDM reaction for the obtention of fishbone carbon nanofibers (CNF). Catalysts, in which Al₂O₃ is used as textural promoter in their formulation, are based on Ni as main active phase for the carbon formation and on Co, Cu or Fe as dopants in order to obtain alloys with an improved catalytic behaviour. Characterization of bimetallic catalysts showed the formation of particles of Ni alloys with a bimodal size distribution. For the doping content studied (5 mol. %), only Cu formed an alloy with a lattice constant high enough to be able to favor the carbon diffusion through the catalytic particle against surface diffusion, resulting in higher carbon formations, longer activity times and activity at 750 °C, where Ni, Ni-Co and Ni-Fe catalysts were inactive. On the other hand, Fe also improved the undoped catalyst performance presenting a higher carbon formation at 700 °C and the obtention of narrow carbon nanofilaments from active Ni₃Fe crystallites.

Percutaneous coronary intervention(PCI) with stenting for the treatment of acute coronary syndrome(ACS) is the contemporary standard of care. Such treatment is followed by Dual anti-platelet therapy(DAPT) comprising of aspirin and a P2Y12 inhibitor. The efficacy of this therapy has been well established but the optimal duration of DAPT remains elusive, and has thus far attracted a prodigious deal of scientific attention. Decision regarding DAPT duration can be challenging clinically in the modern era with the evolution of newer stents, more potent antiplatelet agents and novel anticoagulant drugs in addition to an older patient population with multiple comorbidities. Major societal guidelines have emphasized comprehensive assessment of ischemic and bleeding risk, in turn recommending individualization of DAPT duration, thus encouraging "shared decision making". The following review is aimed at critically evaluating the available evidence to help make these crucial clinical decisions regarding duration of DAPT and triple therapy.

In the human organism various carotenoids are present of which, some are retinoid precursors. The bioactive derivatives of these retinoids are the retinoic acids, which can potently activate nuclear hormone receptors like the retinoic acid receptor and the retinoid X receptor. In our study using an HPLC analytical approach we aimed to assess how plasma carotenoid and retinoid concentrations along with the ratio of their isomers are altered in atopic dermatitis (AD) patients (n=20) compared to healthy volunteers (HV, n=20). We found that plasma levels of the carotenoids lutein (HV 198 ± 68 ng/ml, AD 158 ± 57 ng/ml), zeaxanthin (HV 350 ± 142 ng/ml, AD 236 ± 85) as well as the retinoids retinol (HV 216 ± 89 ng/ml, AD 167 ± 76 ng/ml) and all-trans-retinoic acid (HV 1.1 ± 0.6 ng/ml, AD 0.7 ± 0.5 ng/ml) were significantly lower in AD-patients, while lycopene, α-carotene and β-carotene levels were comparable. In addition the ratios of 13-cis vs. all-trans lycopene as well as 13-cis vs. all-trans retinoic acid were increased in the plasma of AD-patients indicating an AD-specific 13C-isomerisation. A positive correlation with SCORRAD was calculated with 13-cis vs. all-trans lycopene ratio, while a negative correlation was observed with zeaxanthin plasma levels. Based on our results we conclude that in the plasma of AD-patients various carotenoids and retinoids are at lower levels, while the ratio of lycopene isomers was also altered. The higher rate of lycopene and retinoic acid isomerisation products might be a consequence of AD or might result in an altered activation of nuclear hormone receptor signaling pathways and thus maybe partly be responsible for the AD-phenotype and additionally may represent a good plasma marker for AD.

After decades of research, oncolytic virotherapy has recently advanced to clinical application, and currently a multitude of novel agents and combination treatments are being evaluated for cancer therapy. Oncolytic agents preferentially replicate in tumor cells, inducing tumor cell lysis and complex anti-tumor effects, such as innate and adaptive immune responses and the destruction of tumor vasculature. With the availability of different vector platforms and the potential of both genetic engineering and combination regimens to enhance particular aspects of safety and efficacy, the identification of optimal treatments for patient subpopulations or even individual patients becomes a top priority. Mathematical modeling can provide support in this arena by making use of experimental and clinical data to generate hypotheses about the mechanisms underlying complex biology and, ultimately, predict optimal treatment protocols. Increasingly complex models can be applied to account for therapeutically relevant parameters such as components of the immune system. In this review, we describe current developments in oncolytic virotherapy and mathematical modeling to discuss the benefit of integrating different modeling approaches into biological and clinical experimentation. Conclusively, we propose a mutual combination of these fields of research for more efficient development and effective treatments.

Incisional hernias have a particular dynamic related both to the repair method and to the absence or presence of a prosthetic material. The incidence of incisional hernias is estimated at 9.8% after 21 months and increases to 18.7% after ten years. This study presents a surgical method for the repair of recurrent incisional hernias, through open surgery and the use of existing mesh. The selection criteria regarding the use of this method are: the prosthesis is well integrated, without granulomas, suppurations, defect appearing on the same prosthetic abdominal area. The analyzed factors were the location of the incisional hernias, the duration of the operation, the duration of hospitalization, identified complications, the size of the parietal defect. The retrospective study carried out focused on recurrences of incisional hernias from a group of 631 patients operated on for incisional hernias in a general surgery department of Dr. Constantin Andreoiu County Emergency Hospital, Ploiești, Romania, during January 2018 - December 2022. Of the total of 18.22% relapses, 13.6% were relapsed eventrations after prosthetic procedures. Following the application of the selection criteria, several 8 patients with recurrent eventrations were operated by the open method using the existing mesh. In the case of recurrences after prosthetic procedures of incisional hernias, the recurrence can be solved by open surgery using the existing well-integrated prosthesis, without tension, absence of suppuration in the wound, and the peritoneal cavity. For the presented case, the return to daily activities occurred after 22 hours of hospitalization.

Introductions- Liveable housing environments face the menace of global climate change. In-frastructure (including buildings and houses) continuously experiences significant impacts ex-acerbated by natural variability in climate. The study addressed how climate change impacts the resilience of residential buildings, increased maintenance frequency, and the wellbeing and comfort of residents in UK residential buildings. Design/Methodology/Approach: This study used deductive reasoning and an empirical epis-temological methodology as a data-collecting basis to evaluate primary information obtained via a questionnaire. Regression analysis was ultimately employed to analyse the collected da-ta. Result/Discussions: The findings show a significant relationship between climate change and the wellbeing of the occupants of UK residential buildings. Also, the results show that social wellbeing is more important to the occupants than mental and physical wellbeing. It reveals that residential buildings in the UK suffer the cost of maintenance due to continuous reduc-tion in the building fabric's resilience to the impacts of climate change; for instance, a recent increase in rainfall/storms results in unprecedented flooding, which continues to damage the UK residential building fabrics.

Selection of the most suitable material is one of the key decisions to be taken at the design stage of a manufacturing process. Traditional approaches as Ashby maps based on material properties are widely used in the industry. However, in the production of multimaterial components, the criteria for the selection can include antagonistic approaches. The aim of this work is the implementation of a methodology based on the results of process simulations for several materials and classify them by applying an advanced data analytics method based on Machine Learning (ML), in this case the Support Vector Regression (SVR) and Multi-Criteria Decision Making (MCDM) methodolo-gies, in this case Multi-criteria Optimization and Compromise Solution (VIKOR) combined with Entropy weighting methods. In order to do this, a Finite Element Model (FEM) has been built to evaluate the extrusion force and the die wear in a multi-material co-extrusion process of bimetallic Ti6Al4V-AZ31B billets. After applying SVR and VIKOR combined with Entropy weighting methodologies, a comparison has been established based on the material selection and complexity of the methodology used, resulting that material chosen in both methodologies is very similar and MCDM method is easier to implement because there is no need of evaluate the error of the pre-diction model and the time for data preprocessing is less than the time needed in SVR.

In this brief review, the concepts of quantum tunneling and parity violation are introduced in the context of chiral molecules. A particle moving in a double well potential provides a good model to study the behavior of chiral molecules, where the left well and right well represent the L and R enantiomers, respectively. If the model considers the quantum behavior of matter, the concept of quantum tunneling emerges, giving place to a stereomutation dynamics between left- and right-handed chiral molecules. Parity-violating interactions, like the electroweak one, can be also considered, making possible the existence of an energy difference between the L and R enantiomers, the so-called parity-violating energy difference (PVED). Here we provide a brief account of some theoretical methods usually employed to calculate this PVED, also commenting on relevant experiments devoted to experimentally detect the aforementioned PVED in chiral molecules.

The construction of reinforced concrete (RC) structures inevitably consumes an excessive number of rebars, leading to significant cutting waste and carbon emissions. Extensive research has been conducted to minimize this issue and its consequences; however, these methods consistently consume a substantial number of rebars. This includes a previous study that utilizes the lap splice position optimization and special-length rebar concept without considering the lapping zone regulation. Moreover, conventional lap splices pose inherent drawbacks that could jeopardize the structural integrity of RC members. In contrast, mechanical couplers eliminate the need for rebar lapping, effectively reducing rebar consumption. This research aims to evaluate the impact of an integrated mechanical coupler and special-length-priority minimization algorithm on the reduction in rebar consumption and cutting waste in RC columns, achieving near-zero cutting waste. To validate the effectiveness of the proposed algorithm, it was applied to the column rebars of an RC building. The results revealed a significant reduction in ordered rebar consumption by 18.25%, accompanied by substantial reductions in cutting waste (8.93%), carbon emissions (12.99%), and total costs (10.81%) compared with a previous study. The outcomes provide the industry with insights into further reducing rebar consumption and its related consequences. Applying the proposed algorithm to various construction projects will further amplify the corresponding benefits.

The grinding process by friction at the micro-scale in a mill with stones is considered a variable combination of contacts: with two-body (the asperities of lower millstone in direct contact with the asperities of upper millstone) and the three-body (micro-particles of ground seeds trapped between the asperities of lower and the upper stones of the mill). Three elements are described: (1) the mechanic contact of the asperities of the lower and upper millstone, to predict pressures on asperities, by modeling; (2) tests on a millstone sample covered with grinding particles, and (3) tests on a wafer sample formed by the millstones with the grinding particles between them. The paper highlights the combined effects of the micro-scale friction by individual measurements and to sum these effects an analytical model was used, and to validate the model, several experiments were performed. A suitable grind by friction assumes the grain’s movement and the interaction between the seeds and solid surfaces and is highlighted through theoretical and experimental studies. Topography analysis of the surface of the millstones revealed the model of microscopic frictional force. Endpoint measurements (the traces of the surface topography evolution), enable model verification in the grinding process.

The compatibility between the de Sitter Swampland conjecture and Ho\v{r}ava-Lifshitz $F(\bar{R})$ theories with a flat FLRW metric is studied. We first study the standard $f(R)$ theories and show that the only way in which the dS conjecture can be made independent of $R$ is by considering a power law of the form $f(R)\sim R^{\gamma}$. The conjecture and the consistency of the theory puts restrictions on $\gamma$ to be greater but close to $1$. For the $F(\bar{R})$ theories described by its two parameters $\lambda$ and $\mu$ we use the equations of motion to construct the function starting with an ansatz for the scale factor in the Jordan frame of the power law form. By doing a conformal transformation on the three metric to the Einstein frame we can obtain an action of gravity plus a scalar filed by relating the parameters of the theory. The non-projectable and projectable cases are studied and the differences are outlined. The $F(\bar{R})$ function obtained consists of terms of the form $\bar{R}^{\gamma}$ with the possibility of having negative power terms. The dS conjecture leads to inequalities for the $\lambda$ parameter, in both versions it gets restricted to be greater but close to $1/3$. For the general case in which $\mu$ and $\lambda$ are considered as independent, the action contains an extra term but we propose that the conjecture is still applicable. Once again the non-projectable and projectable cases are studied. The $F$ function obtained has the same form as before, the consistency of the theory and the dS conjecture lead to a set of inequalities on both parameters that are studied numerically. In all cases $\lambda$ is restricted by $\mu$ around $1/3$ and we obtain $\lambda\to1/3$ if $\mu\to0$. Finally we consider the $f(R)$ limit $\mu,\lambda\to1$ and we obtain consistent results.

The capability of extracting information and analyze it into a common format is essential for performing predictions, comparing projects through cost benchmarking, and for having a deeper understanding of the project costs. However, the lack of standardization and the manual inclusion of the data makes this process very time-consuming, unreliable, and inefficient. To tackle this problem, a novel approach with a big impact is presented combining the benefits of data mining, statistics, and machine learning to extract and analyze the information related to railway costs infrastructure data. To validate the suggested approach, data from 23 real historical projects from the client network rail was extracted, allowing their costs to be comparable. Finally, some machine learning and data analytics methods were implemented to identify the most relevant factors allowing for costs benchmarking. The presented method proves the benefits of data extraction being able to gather, analyze and benchmark each project in an efficient manner, and deeply understand the relationships and the relevant factors that matter in infrastructure costs.

Context: Despite the effort put into developing standards for structuring construction cost, and the strong interest into the field. Most construction companies still perform the process of data gathering and processing manually. That provokes inconsistencies, different criteria when classifying, misclassifications, and the process becomes very time-consuming, particularly on big projects. Additionally, the lack of standardization makes very difficult the cost estimation and comparison tasks. Objective: To create a method to extract and organize construction cost and quantity data into a consistent format and structure, to enable rapid and reliable digital comparison of the content. Method: The approach consists of a two-step method: Firstly, the system implements data mining to review the input document and determine how it is structured based on the position, format, sequence, and content of descriptive and quantitative data. Secondly, the extracted data is processed and classified with a combination of data science and experts’ knowledge to fit a common format. Results: A big variety of information coming from real historical projects has been successfully extracted and processed into a common format with 97.5% of accuracy, using a subset of 5770 assets located on 18 different files, building a solid base for analysis and comparison. Conclusion: A robust and accurate method was developed for extracting hierarchical project cost data to a common machine-readable format to enable rapid and reliable comparison and benchmarking.

An area has been designated for demonstrating the utility of marine hydrokinetic turbines in Minas Passage, Bay of Fundy. Marine renewable energy may be useful for the transition from carbon-based energy sources but there is concern for the safety of fish that might encounter turbines. Acoustic receivers that detect signals from acoustically tagged fish that pass through the tidal demonstration area and detection efficiency of tag signals might be used to estimate the likelihood of fish encountering marine hydrokinetic turbines. The method requires that tagged fish passing through the development area will be reliably detected by a receiver array. The present research tests the reliability with which passing tags are detected by suspending tags beneath GPS-tracked drifters. Drifters carrying high residency Innovasea tags that transmitted every 2 seconds were usually detected by the receiver array even in fast currents during spring tides but pulse position modulation tags were inadequate. Sometimes very few high residency tag signals were detected when fast tidal currents swept a drifter through the receiver array, so increasing the transmission interval degrades performance at the tidal energy development area. High residency tags suspended close to the sea surface were slightly less likely to be detected if they passed by during calm conditions. Previously measured detection efficiencies were found to slightly overestimate the chances of a high residency tag carried by a drifter being detected as it passed by a receiver. This works elucidates the effectiveness with which acoustically tagged fish are detected in fast, highly turbulent tidal currents and informs the application of detection efficiency measurements to calculate the probability that fish encounter a marine hydrokinetic turbine.

In recent years, pedestrian re-identification has gained a lot of interest due to its importance for many purposes such as security and safety. Many types of solutions have been proposed to solve this problem, where the majority are based on a features extraction such Convolution Neural Networks (CNNs). These approaches assume that only the identities that are in the training data can be recognized. The pedestrians in the training data are called In distribution (ID). However, in real world scenarios, new pedestrians and objects can appear in the scene and the model should detect them as Out Of Distribution (OOD). In our previous study , we proposed a pedestrian re-identification based on von-Mises Fisher (vMF) distribution. Each identity is embedded in the unit sphere as a compact vMF distribution far from other identities distributions. The embedding is done through a base CNN. Recently, proposed a framework called Virtual Outlier Synthetic (VOS), that detects OOD based on synthesising virtual outlier in the embedding space in an online manner. Their approach assumes that the samples from the same object maps to a compact space. This assumption aligns with the vMF based approach. Therefore, in this paper, we revisited the vMF approach and merged with VOS in order to detect OOD data points. We present our approach to merge both frameworks. We conducted several experiments to evaluate our proposed framework. Results showed that our framework was able to detect new pedestrian that do not exist in the training data in the inference phase. It also slightly helped to improve the re-identification performance.

Education is one of the most important tools available to policymakers and non-governmental bodies to promote a change in the behavior of society and to address the climate crisis, in line with the 4^th and 13^th Sustainable Development Goals of the United Nations 2030 Agenda. Project-based learning (PBL) addresses real and global challenges and allows the academic and professional formation of students. As part of the reflection stage of the educational action research method using the Business Canvas Model (BMC), pedagogic deficiencies were identified in the PBL and a didactic proposal was elaborated to emulate the interaction of students with the ecosystems of society. A prototype for improving the management of organic manures as soil amendments was initially developed, to provide the students with a quick start on the first steps of the proposed project. In the 10 sessions designed for the PBL (Make it happen!), the students elaborate a more sophisticated artifact in response to the demands of potential clients, as per the outcomes of the primary market research (5^th session). Active teaching methods and tools, such as a modified template of the BMC with the Rumsfeld’s matrix, aid the metacognition of students and their competences development. In a double session of the PBL, the primary market research is organized with key stakeholders of the agroindustry to enquire about the feasibility of the implementation of the technological solution and the logistics at farm level. Finally, the evaluation relies on the suitability of the upgraded prototype to respond customers’ demands.

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. Despite extensive research efforts, the majority of trialed monotherapies to date have failed to demonstrate significant benefit. It has been suggested that this is due to the complex pathophysiology of TBI, which may possibly be addressed by a combination of therapeutic interventions. In this article, we have reviewed combinations of different pharmacologic treatments, combinations of non-pharmacologic interventions, and combined pharmacologic and non-pharmacologic interventions for TBI. Both preclinical and clinical studies have been included. While promising results have been found in animal models, clinical trials of combination therapies have not yet shown clear benefit. This may possibly be due to their application without consideration of the evolving pathophysiology of TBI. Improvements of this paradigm may come from novel interventions guided by multimodal neuromonitoring and multimodal imaging techniques, as well as the application of multi-targeted non-pharmacologic and endogenous therapies. There also needs to be a greater representation of female subjects in preclinical and clinical studies.

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include buildup of cerebral β amyloid (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. The paucity of early detection and disease progression biomarkers also seems to present a major obstacle to AD drug development. The current established readouts based on expression levels of amyloid beta, tau and phospho tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, CSF or other biofluids that can facilitate early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry, are now being increasingly applied to study AD disease mechanisms, identify drug targets and novel disease biomarkers. In this report, we describe applications of the quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD and discuss development and validation of new predictive and diagnostic disease biomarkers.

Phase transitions- both in the classical and in the quantum version- are the perfect playground for appreciating universality at work. Indeed, the fine details become unimportant and a classification in very few universality classes is possible. Very recently, a striking deviation from this picture has been discovered: some antiferromagnetic spin chains with competing interactions show a different set of phase transitions depending on the parity of number of spins in the chain. The aim of this article is to demonstrate that the same behavior also characterizes the most simple quantum spin chain: the Ising model in a transverse field. By means of an exact solution based on a Wigner-Jordan transformation, we show that a first order quantum phase transition appears at zero applied field in the odd spin case, while it is not present in the even case. A hint of a possible physical interpretation is given by the combination of two fact: at the point of the phase transition, the degeneracy of the ground state in the even and the odd case substantially differ, being respectively 2 and 2N, with N the number of spins; the spin of the most favorable kink states changes at that point.

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

Neuroblastoma is an extra-cranial solid cancer that primarily affects children. Aggressive neuroblastoma tumors typically demonstrate resistance to conventional chemotherapeutic and radiotherapeutic regimens. Interestingly, the use of dietary supplements in the control of cancers has gained ascendance in recent scientific investigations. Capsaicin and dihydrocapsaicin are bioactive components of Capsicum chinenses fruit. Qutenza (a high-dose capsaicin patch) is used in the management of neuropathic pain from postherpetic neuralgia and HIV-associated neuropathy. Research on the potency of capsaicin as an anticancer agent has been demonstrated on several cancer cell lines and in in vivo models. The possibility of conventional cancer therapies having long-term developmental and other side effects on pediatric patients invokes the need to search for other less toxic agents against neuroblastoma. In this study, we tested if Capsicum chinenses fruit extract has therapeutic potential against neuroblastoma. To carry out this study, capsaicin and dihydrocapsaicin extract were made from Capsicum chinenses red fruits via hexane extraction method. Then, a range of concentrations (1pg/mL–100 mg/mL) of the extract was administered to cultured SH-SY5Y neuroblastoma cells and their viabilities assessed. The potency of capsaicin in destroying neuroblastoma cells indicated that it might act via multiple routes, hence we screen for possible receptors in and on neuroblastoma cells that might interact with capsaicin using molecular docking techniques. Our findings showed that capsaicin and dihydrocapsaicin extracted from Capsicum chinenses reduced neuroblastoma cell viability in a concentration-dependent manner with an IC₅₀ of 69.75 µg/mL. Our in-silico analysis determined that capsaicin might potentially bind to other receptors on the surface of neuroblastoma cells. We demonstrated a stronger binding affinity of capsaicin to human D4 Dopamine receptor (DRD4) than to the known vanilloid receptor TRPV1 using molecular docking. In conclusion, these results illustrated that Capsicum chinenses extract containing capsaicin and dihydrocapsaicin is effective in reducing viability of neuroblastoma cells in vitro and may serve as a naturally derived treatment source for this pediatric cancer, secondly, capsaicin may have multiple targets, and its strong binding to human D4 Dopamine receptors may point to different pathways by which capsaicin exerts its cancer killing effects.

Patients with chronic obstructive pulmonary disease (COPD) often require frequent hospitalization due to worsening symptoms. Preventing prolonged hospital stay and readmission becomes a challenge for healthcare professionals treating patients with COPD. Although the integration of health and social care supports greater collaboration and enhanced patient care, organizational structure and poor leadership may hinder the implementation of patient-oriented goals. This paper presents a case of a 64-year-old chronic smoker with severe COPD who was to be discharged on long-term oxygen therapy (LTOT). It further highlights the healthcare decisions made to ensure the patient’s safety at home and further provides a long-lasting solution to the existing medical and social needs. The goal was accomplished through a discharge plan that reflects multidisciplinary working, efficient leadership, and change management using Havelock’s theory. While COPD is characterized by frequent exacerbation and hospital readmission, it was emphasized that most failed discharges could be attributed to bureaucratic organizational workflow which might not be in the patient’s best interest. It was further demonstrated that healthcare professionals are likely to miss the window of opportunity to apply innovative and long-lasting solutions to the patient’s health condition in an attempt to remedy the immediate symptoms of COPD

T cells follow a triphasic distinct pathway of activation, proliferation and differentiation before becoming functionally and phenotypically ‘exhausted’ in settings of chronic infection, autoimmunity and in cancer. Exhausted T cells progressively lose canonical effector functions, exhibit altered transcriptional networks and epigenetic signatures and gain constitutive expression of a broad coinhibitory receptor suite. This review outlines recent advances in our understanding of exhausted T cell biology and examines cellular and molecular mechanisms by which a state of dysfunction or exhaustion is established, and mechanisms by which exhausted T cells may still contribute to pathogen or tumour control. Further, this review describes our understanding of exhausted T cell heterogeneity and outlines the mechanisms by which checkpoint blockade differentially engages exhausted T cell subsets to overcome exhaustion and recover T cell function.

This work presents the results of a computational study of the chemical reactivity and bioactivity properties of the members of the Theopapuamides A-D family of marine peptides by making use of our own proposed methodology named Computational Peptidology (CP) that has been successfully considered in previous studies of this kind of molecular systems. CP allowed for the determination of the global and local descriptors that come from Conceptual Density Functional Theory (CDFT) that can give an idea of the chemical reactivity properties of the marine natural products under study which are already known to be related to their bioactivity. At the same time, the validity of the procedure based on the adoption of the KID (Koopmans in DFT) technique as well as the MN12SX/Def2TZVP/H2O model chemistry has been successfully verified. Together with several Chemoinformatic tools that can be used for the improvement of process of Virtual Screening, some additional properties of these marine peptides were identified related to their ability to behave as useful drugs. With the further object of analyzing their bioactivity some parameters of usefulness for future QSAR studies, their predicted biological targets and the the ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) parameters related to the Theopapuamides A-D pharmacokinetics are also reported.

A methodology based on the concepts that arise from Density Functional Theory named Conceptual Density Functional Theory (CDFT) was chosen for the calculation of some global and local reactivity descriptors of the Discodermins A-H family of marine peptides through the consideration of the KID (Koopmans in DFT) technique that was successfully used in previous studies of this kind of molecular systems. The determination of active sites of the studied molecules for different kind of reactivities was achieved by resorting to some CDFT-based descriptors like the Fukui functions as well as the Parr functions derived from Molecular Electron Density Theory (MEDT). A few properties identified with their ability to behave as a drug and the bioactivity of the peptides considered in this examination were acquired by depending on a homology model by studying the correlation with the known bioactivity of related molecules in their interaction with various biological receptors. With the further object of analyzing their bioactivity some parameters of usefulness for future QSAR studies, their predicted biological targets and the the ADME (Absorption, Distribution, Metabolism, and Excretion) parameters related to the Discodermins A-H pharmacokinetics are also reported.

The paper presents the influence of different curing conditions – wet, dry and protection against water evaporation on selected properties of concretes with different amount of recycled concrete aggregate previously subjected to atmospheric CO2 sequestration. Additionally, the eco-efficiency bi and ci indexes as well as eco-durability S-CO2 index were calculated. It was found that dry conditions deteriorate the properties of concrete, especially made of blast furnace slag cement, while protection against evaporation allows to achieve results comparable to wet conditions. Moreover, for series with the highest amount of coarse recycled aggregate and after longer period of curing, the difference between the effects of wet curing and protection against water evaporation disappears. The eco-efficiency and eco-durability indexes approach confirms the beneficial effect of blast-furnace slag cement used as a binder but on condition of proper way of curing.

In the last few decades, a lot has been written on the use of sustainable agriculture to improve ecosystem services for resilience to climate change. However, no tangible and systematic evidence exists on how this would participate in alleviating impacts on vulnerable rural communities. This paper provides a narrative systematic review (SR) integrated with a bibliometric analysis and a concept network analysis to understand how, in a changing climate, sustainable agriculture builds the resilience of agro-systems. The search was set from the date of the first relevant article until the end of 2018. Results generated have demonstrated that: a. Only single practices and methods have been studied to assess impacts on single ecosystem services. b. Soil quality and health are considered a key indicator of sustainable agriculture. c. Albeit the assessed practices and methods have shown to improve the biodiversity of agro-systems, which makes them more resilient to extreme climate events, we are still far from reaching interdisciplinary and multi-dimensional agriculture which integrates all management aspects and generates a full range of ecosystem services. In conclusion, the study addressed the following recommendations for the scientific community and for decision-makers to orient future research strategies and efforts: a. Integration of all agro-systems services into sustainable management using an ecosystem-based approach on a life-cycle basis using Life Cycle Assessment (LCA) method; b. Improving the scientific understanding of traditional knowledge for higher synergies and for further integration; c. Unification of assessment methods and indicators for the quantification of impacts; d. Creation of a platform to share, monitor, screen, and approve assessments and evaluations of sustainable agriculture by region.

Since the 1950s sugarcane production has grown rapidly from less than 0.5 billion tonnes in the late 50s to reach over 1.9 billion tonnes in 2012 on about 27 million hectares of agricultural land. This expansion has been boosted by the high demand for bioethanol promoted as a sustainable bioenergy source which accounted in 2010 for the biggest share of the global biofuel market. Despite its benefits, the scientific debate on sugar is growing especially that counterarguments are so many, including negative impacts on different interacting ecosystems and human well-being, e.g. bigger stress on land and water resources, environmental externalities on air, a harmful impact on the biodiversity and endemic species, negative environmental externalities, health, and socio-economic aspects. This paper provides a narrative systematic review (SR) of the impacts of sugarcane production on these different ecosystems employing the ecosystem services framework for its acceptance by policy-makers. The references included for the SR were 163 and results showed that the majority of the studies are from Brazil, Australia, South Africa and the USA (≈ 75% of the literature), most of them were from peer-reviewed journals (85%), and most of the case studies adopted a quantitative research approach (93%). The literature assessed showed that sugarcane, like all agro-systems, depends on the practices and techniques to transform negative impacts into positive externalities on ecosystems and human well-being. However, the literature studied failed to include the inter-linkage in sugarcane production impacts’ and therefore to evaluate the related ecosystem services with respect to the Millennium Ecosystem Assessment (MA) framework to account for existing trade-offs. Therefore, the findings are addressed to the scientific community and decision-maker for an intensification of interdisciplinary and integrated research based on the MA framework to cover all ecosystem services, for sustainable development of the sugarcane sector.

This study was conducted in a laboratory-controlled environment aiming at studying the physical properties and elemental composition of coal combustion particles in a brazier. Particles were sampled ~1 m above the stove using a partector, where particles were collected on gold Transmission Electron Microscopy (TEM) grids and polycarbonate filters for TEM and inductively coupled plasma mass spectrometry (ICP-MS) analysis, respectively. Particles for elemental analysis collected on a 37 µm polycarbonate filters whereby a Gillian pump was used to draw in air. During sampling, a 2.5 µm cyclone was attached to the sampling cassette to isolate larger particles. The results have shown that combustion particles emitted during the early stage of combustion where single spherical particles with a diameter of around 450 nm. As the combustion progresses, the particle diameter gradually decreases and the morphology changes to accretion chain and fluffy bead structure for the flaming and char-burning phase, respectively.

There are frequently interactions between active folds and major rivers (mean annual water discharges > 70 m³s^-1). The major river may incise across the fold, to produce a water gap across the fold, or a bevelling (or lateral planation) of the top of the fold. Alternatively, the major river may be defeated to produce a diversion of the river around the fold, with wind gaps forming across the fold in some cases, or ponding of the river behind the fold. Why a river incises or diverts is often unclear, though influential characteristics and processes have been identified. A new scheme for investigating fold-river interactions has been devised, involving a short description of the major river, climate, and structural geology, and 13 characteristics of river and fold geomorphology: 1) Channel width at location of fold axis, w, 2) Channel-belt width at location of fold axis, cbw, 3) Floodplain width at location of fold axis, fpw, 4) Channel sinuosity, Sc, 5) Braiding index, BI, 6) General river course direction, RCD, 7) Distance from fold core to location of river crossing, C-RC, 8) Distance from fold core to river basin margin, C-BM, 9) Width of geological structure at location of river crossing, Wgs, 10) Estimate of erosion resistance of surface sediments/rocks and deeper sediments/rocks in fold, ERs, ERd, 11) Channel water surface slope at location of fold axis, s, 12) Average channel migration rate, Rm, 13) Estimate of fold total uplift rate, TUR. The first 10 geomorphological characteristics should be readily determinable for nearly all major rivers using widely available satellite imagery and fine scale geological maps. The last 3 characteristics should be determinable for most major rivers where other data sources are available. This study demonstrates the methodology of this scheme, using the example of the major rivers Karun and Dez interacting with active folds in the foreland basin tectonic setting of lowland south-west Iran. For the rivers Karun and Dez (mean annual water discharges 575 m³s^-1 and 230 m³s^-1, respectively), it was found that geomorphological characteristics Nos. 2, 3 and 7 had statistically significant differences (p-value ≤ 0.05) between the categories of river incision across a fold and river diversion around a fold. For river incision, at the fold axis, channel-belt width was always < 2.7 km, and floodplain width was generally (80 % of cases) < 5.7 km; whereas for river diversion, at the projection of the fold axis, these two characteristics had a wide range of values. For river incision, the distance from the fold core to the location where the river channel crossed the fold axis, was generally (80 % of cases) ≤ 8.5 km; whereas for river diversion, this distance was always > 22 km. Since it is highly likely that different characteristics will be important for other major rivers interacting with other folds, it is recommended that this scheme is now used to investigate a variety of major rivers from across the globe. By comparing the same parameters for different major rivers, a better understanding of fold-river interactions should be achieved.

This paper discusses a MEMS switch that can be fabricated using low temperature (<100^oC) deposition and patterning techniques suitable for the back-end-of-the-line integration with CMOS. The resulting cross-bar switches can be used for electrostatic discharge protection, FPGA implementation, chip security assessment and lock-down, and circuit block power management. We discuss platinum and iron switch with turn-on voltages of ~ 1.8 V. In the case of the iron switches, we also show that they can be magnetized to have “memory” and stay on when turned on. Platinum switch cycling of up to 1000 times did not show any changes in their turn-on voltage and their contact resistance was unchanged. The 10-100 nm switch airgaps were formed using low temperature sputtered sacrificial polysilicon and XeF₂ etching. XeF₂ does not attack any of the metals used in CMOS enabling fabrication of cross-bar switches with any of these metals. Once activated, it takes ∿ 6 to mechanically turn on the switch that can be decreased to ~1 ns by optimizing the device structure. Interestingly, the nm-scale gaps can be used as spark gap as a fast plasma switch to discharge first followed by the activation of the MEMS switch.

Polycystic ovary syndrome (PCOS) is a common endocrinopathy of reproductive-aged women characterized by hyperandrogenism, oligo-anovulation and insulin resistance closely linked with preferential abdominal fat accumulation. As an ancestral primate trait, PCOS was likely further selected in humans when scarcity of food in hunter-gatherers of the late Pleistocene additionally programmed for enhanced fat storage to meet the metabolic demands of reproduction in later life. As an evolutional model for PCOS, healthy normal-weight women with hyperandrogenic PCOS have subcutaneous (SC) abdominal adipose stem cells that favor fat storage through exaggerated lipid accumulation during development to adipocytes in vitro. In turn, fat storage is counterbalanced by reduced insulin sensitivity and preferential accumulation of highly-lipolytic intra-abdominal fat in vivo. This metabolic adaptation in PCOS balances energy storage with glucose availability and fatty acid oxidation for optimal energy use during reproduction; its accompanying oligo-anovulation allowed PCOS women from antiquity sufficient time and strength for childrearing of fewer offspring with a greater likelihood of childhood survival. Heritable PCOS characteristics are now affected by today’s contemporary environment through epigenetic events that predispose to lipotoxicity with excess weight gain and pregnancy complications, calling for an emphasis on preventive healthcare to optimize the long-term, endocrine-metabolic health of PCOS women in today’s obesogenic environment.

Six mode shapes, including bending and torsion, were documented for five different basketball rims and backboards at the United States Military Academy, West Point, New York, USA. The frequency and damping ratio of each mode shape were also determined. The empirical process began with the time-domain excitation and response of each rim-backboard system. The impulse of excitation came from an impact hammer separately applied to sequentially, to each node. The sinusoidal response was gathered from an accelerometer at a fixed location, node 1. Each time-domain excitation-response was then converted to a frequency domain Bode plot for each node by a B&K 2034 Signal Analyzer, giving transfer functions of output/input versus frequency. Structural Measurements System (SMS) Software was used to fit mode shapes to the Bode plots. Each of the six mode shapes were fitted to the Bode plots of each node at a specific modal frequency. Each of the six mode shapes were a function of the locations of the nodes, and the Bode plot gathered at each node. The first and second modes were critical for showing that the Energy Rebound Testing Device statistically correlated with the energy transferred to the rim and backboard. A known perturbation mass was selectively attached to the rim, to help isolate the dynamic masses and spring rates for the rim and backboard, to ascertain the kinetic energy transferred to the rim had a 95.67% inverse correlation with rim stiffness.

The study of photonic crystals has emerged as an attractive area of research in nanoscience in the last years. In this work we study the properties of a two-dimensional photonic crystal composed of dielectric rods. The unit cell of the system is composed of six rods organized on the sites of a C6 triangular lattice. We induce a topological phase by introducing an angular perturbation ϕ in the pristine system. The topology of the system is then determined by using the so-called k.p perturbed model. Our results show that the system presents a topological and a trivial phases, depending on the sign of the angular perturbation ϕ. The topological character of the system is probed by evaluating the electromagnetic energy density and analyzing its distribution in the real space, in particular on the maximal Wyckoff points. We also find two edge modes at the interface between the trivial and topological photonic crystals, which present a pseudospin topological behavior. By applying the Bulk-Edge correspondence, we study the pseudospin edge modes and conclude that they are robust against defects, disorder and reflection. Moreover, the localization of the edge modes leads to the confinement of light and the interface behaves as a waveguide for the propagation of electromagnetic waves. Finally, we show that the two edge modes present energy flux propagating in opposite directions, which is the photonic analogue of the quantum spin Hall effect.

The number of published studies on curcuminoids in cancer research, including its lead molecule curcumin and synthetic analogs, has been increasing substantially during the past two decades. Insights on the diversity of inhibitory effects they produced on a multitude of pathways involved in carcinogenesis and tumor progression were provided. As this wealth of data was obtained in a setting of various experimental and clinical data, this review first aimed at presenting a chronology of discoveries and an update on their complex in vivo effects. Secondly, there are many interesting questions linked to their pleiotropic effects. One of them, which is a growing research topic, relates to their ability to modulate metabolic reprogramming. This review will also cover the use of curcuminoids as chemosensitizing molecules, that can be combined with several anticancer drugs for reversing the phenomenon of multidrug resistance. Finally, current investigations in these three complementary research fields raise several important questions that will be put in the prospects for the future research related to the importance of these molecules in cancer research.

Aquaporins (AQPs) are water channels widely distributed in living organisms and involved in many pathophysiologies as well as in cell volume regulations (CVR). In the present study, based on the structural homology existing between mineralocorticoids receptors (MR), glucocorticoids receptors (GR), cholesterol consensus motif (CCM) and the extra-cellular vestibules of AQPs, we investigated the binding of corticosteroids on AQP family through in silico molecular dynamics simulations of AQP2 interactions with cortisol. We propose for the first time a putative AQPs corticosteroids binding site (ACBS) and discussed its conservation through structural alignment. Corticosteroids can mediate non-genomic effects, nonetheless, the transduction pathways involved are still misunderstood. Moreover, a growing body of evidence is pointing out toward the existence of a novel membrane receptor mediating part of these rapid corticosteroids effects. Our results suggest that the naturally produced glucocorticoid cortisol inhibits channel water permeability. Based on these results, we propose a detailed description of a putative underlying molecular mechanism. In this process, we also bring new insights on the regulatory function of AQPs extra-cellular loops and on the role of ions in tuning the water permeability. Altogether, this work brings new insights into corticosteroids non-genomic effects through the proposition of AQPs as membrane receptor of this family of regulatory molecules. This original result is the starting point for future investigations to define more in depth and in vivo the validity of this functional model.

Power quality problem is a hot area in power systems and drives that has drawn the attention of many researchers. This is because of the threat it poses on the health of electrical systems and the cost incurred on utility bills. The problem arises as a result of the need for reactive power to be supplied alongside active power in power transmission and distribution. Unfortunately, reactive power is consumed by almost all components of the system, leading to a shortage. To solve this problem, there is a need to compensate for the lost reactive power. Several researchers have proposed various approaches to mitigate this problem such as thyristor switched capacitor bank, series compensator, series reactor, series var compensator (SVC), Static Synchronous Compensator (STATCOM), synchronous condenser and others. In order to further draw attention in this area, this work investigates a number of research papers on power compensation techniques and draw up challenges from each work that can be considered for further investigation. To this end, each research paper reviewed is evaluated in terms of problem solved, technique used, and results obtained. It therefore offers ample opportunities for researchers to explore in improving power quality and power system safety.

Influenza A viruses (IAV) are widespread viruses affecting avian and mammalian species worldwide. Outbreaks of IAV in poultry are usually associated with substantial morbidity and mortality, significantly affecting the poultry industry and food security. IAVs from avian species can be transmitted to mammals including humans and, thus, they are of inherent pandemic concern. Most of the efforts to understand the pathogenicity and transmission of avian origin IAVs have been focused on H5 and H7 subtypes due to their highly pathogenic phenotype in poultry. However, IAV of the H9 subtype that circulate endemically in poultry flocks in some regions of the world have also been associated with cases of zoonotic infections. As a result, the World Health Organization includes avian origin H9N2 IAV among the top in the list of IAVs of pandemic concern. In this review, we discuss the interspecies transmission of H9N2 between avian and mammalian species and the molecular factors that are thought relevant for this spillover. Additionally, we discuss factors that have been associated with the ability of these viruses to transmit through the respiratory route in mammalian species.

This study reports a general scenario for the out-of-equilibrium features of collapsing polymeric architectures. We use molecular dynamics simulations to characterize the coarsening kinetics, in bad solvent, for several macromolecular systems with an increasing degree of structural complexity. In particular, we focus on: flexible and semiflexible polymer chains, star polymers with 3 and 12 arms, and microgels with both ordered and disordered networks. Starting from a powerful analogy with critical phenomena, we construct a density field representation that removes fast fluctuations and provides a consistent characterization of the domain growth. Our results indicate that the coarsening kinetics presents a scaling behaviour that is independent of the solvent quality parameter, in analogy to time-temperature superposition principle. Interestingly, the domain growth in time follows a power-law behaviour that is approximately independent of the architecture for all the flexible systems; while it is steeper for the semiflexible chains. Nevertheless, the fractal nature of the dense regions emerging during the collapse exhibits the same scaling behaviour for all the macromolecules. This, suggests that the faster growing length scale in the semiflexible chains originates just from a faster mass diffusion along the chain contour, induced by the local stiffness. The decay of the dynamic correlations displays scaling behavior with the growing length scale of the system, which is a characteristic signature in coarsening phenomena.

Acrylamide (AA), a molecule which potentially increases the risk of developing cancer, is easily formed in food rich in carbohydrates, such as biscuits, wafers and breakfast cereals, at temperatures above 120 °C. Thus, it is eminent the need to detect and quantify the AA content in processed foodstuffs, in order to delineate the limits and mitigation strategies. This work reports the development and validation of a high-resolution mass spectrometry-based methodology for identification and quantification of AA in specific food matrices of biscuits, by using LC-MSⁿ with electrospray ionization and Orbitrap as mass analyser. The developed analytical method showed good repeatability (RSD_r 11.1%) and 3.55 μg kg^-1 and 11.8 μg kg^-1 as limit of detection (LOD) and limit of quantification (LOQ), respectively. The choice of multiplexed targeted-SIM mode (t-SIM) for AA and AA-d3 isolated ions provided enhanced detection sensitivity, as demonstrated in this work. Results for AA concentration obtained vary between 323.7 and 2056.1 μg kg^-1. During baking an increase in AA concentration was observed, as well as between samples taken from different areas of the baking oven. Statistical processing of data was performed in order to compare the AA levels with several production parameters, such as time/cooking temperature, placement on the cooking conveyor belt, color and moisture for different biscuits. The composition of the raw materials was statistically the most correlated factor with the AA content when all samples are considered. The statistical treatment presented herein enables an important prediction of factors influencing AA formation in biscuits contributing for putting in place effective mitigation strategies.

One of the key areas of the International Renewable Energy Agency’s (IRENA) programme of work is the analysis of renewable technology costs and performance and the dissemination of these results to as wide an audience as possible. In addition to analysis, IRENA seeks to engage a broad range of stakeholders in the context of this work through the Renewable Costing Alliance. The Costing Alliance brings together companies, industry association, governments and researchers to share, confidentially, data for real-world renewable energy project cost and performance, helping to build further on IRENA’s costing work to date. In this context the authors analyse the current cost differentials and cost reduction potentials for solar PV in Japan compared to best practice levels and identify the reasons for higher costs in Japan and how to reduce them. This study analyses the current installed cost differentials for utility-scale, commercial and residential rooftop solar PV systems. In addition to identifying the reasons for the cost differentials, potential policy recommendations to reduce the cost differential are identified.

Understanding influences of multiple stressors across the landscape on aquatic biota is important for conservation, as it allows for an understanding of spatial patterns and informs stakeholders of significant conservation value. Data exists for land use/landcover (LULC) and other physicochemical components of the landscape throughout the Appalachian region yet biological data is sparse. This dearth of biological data relative to LULC and physicochemical data creates difficulties in making informed management and conservation decisions across large landscapes. At the HUC12 watershed scale we sought to create a single score for both abiotic and biotic values throughout the central and southern Appalachian region. We used boosted regression trees (BRT) to model biological responses (fish and aquatic macroinvertebrate variables) to abiotic variables. Variance explained by BRT models ranged from 62-94%. We categorized both predictor and response variables into themes and targets respectively to better understand large scale patterns on the landscape that influence biological condition of streams. We combined predicted values for a suite of response variables from BRT models to create a single watershed score for aquatic macroinvertebrates and fish. Regional models were developed for fish but we were unable to develop regional models for aquatic macroinvertebrates due to the low number of sample sites. There was strong correlation between regional and global watershed scores for fish models but not between fish and aquatic macroinvertebrate models. Use of such multimetric scores can inform managers, NGOs, and private land owners regarding land use practices; thereby contributing to largescale landscape scale conservation efforts.

This paper presents a novel approach for indoor acoustic source localization using microphone arrays and based on a Convolutional Neural Network (CNN). The proposed solution is, to the best of our knowledge, the first published work in which the CNN is designed to directly estimate the three dimensional position of an acoustic source, using the raw audio signal as the input information avoiding the use of hand crafted audio features. Given the limited amount of available localization data, we propose in this paper a training strategy based on two steps. We first train our network using semi-synthetic data, generated from close talk speech recordings, and where we simulate the time delays and distortion suffered in the signal that propagates from the source to the array of microphones. We then fine tune this network using a small amount of real data. Our experimental results show that this strategy is able to produce networks that significantly improve existing localization methods based on SRP-PHAT strategies. In addition, our experiments show that our CNN method exhibits better resistance against varying gender of the speaker and different window sizes compared with the other methods.

Molecules sourced from marine environments hold immense promise for the development of novel therapeutic drugs, owing to their distinctive chemical compositions and valuable medicinal attributes. Notably, Talarolide A and Talaropeptides A-D have gained recent attention as potential candidates for pharmaceutical applications. This study aims to explore the chemical reactivity of Talarolide A and Talaropeptides A-D through the application of molecular modeling and computational chemistry techniques, specifically employing Conceptual Density Functional Theory (CDFT). By investigating their chemical behaviors, the study seeks to contribute to the understanding of the potential pharmacological uses of these marine-derived compounds. The investigation involves the utilization of molecular modeling and computational chemistry tools, with a specific focus on Conceptual DFT. These techniques are applied to examine the chemical reactivity of Talarolide A and Talaropeptides A-D, shedding light on their potential for interacting with various biological targets. The research reveals insights into the chemical reactivity of Talarolide A and Talaropeptides A-D, uncovering active reaction sites and potential biological targets. Talarolide A demonstrates robust anti-inflammatory properties and antitumor activity against diverse cancer cell lines, while Talaropeptide A displays antimicrobial efficacy against both bacteria and fungi. The study underscores the significance of comprehending the chemical reactivity of natural marine products for advancing pharmaceutical development. By employing computational tools such as Conceptual DFT, this research uncovers crucial information about the active sites and potential targets of Talarolide A and Talaropeptides A-D. The findings contribute to the broader understanding of marine-derived peptides and their prospects as pharmaceutical agents, though further investigations are necessary to fully elucidate their pharmacological attributes.

Stellatolides are natural compounds that have shown promising biological activities, including antitumor, antimicrobial, and anti-inflammatory properties, making them potential candidates for drug development. Chemical Reactivity Theory (CRT) is a branch of chemistry that explains and predicts the behavior of chemical reactions based on the electronic structure of molecules. Conceptual Density Functional Theory (CDFT) and Computational Peptidology (CP) are computational approaches used to study the behavior of atoms, molecules, and peptides. In this study, we present the results of our investigation of the chemical reactivity and ADMET properties of Stellatolides A-H using a novel computational approach called Conceptual DFT-based Computational Peptidology (CDFT-CP). Our study uses CDFT and CP to predict the reactivity and stability of molecules and to understand the behavior of peptides at the molecular level. We also predict the ADMET properties of the Stellatolides A-H to provide insight into their effectiveness, potential side effects, and optimal dosage and route of administration. This study sheds light on the potential of Stellatolides A-H as promising candidates for drug development and highlights the potential of CDFT-CP for the study of other natural compounds and peptides.

Tipping bucket rain gauges (TBRs) have been, and apparently will continue to be one of the most widely used pieces of equipment for rainfall monitoring, being frequently used for the calibration, validation and downscaling of radar and remote sensing data, due to their major advantages–low cost, simplicity, and low energy consumption. Thus, many works have focused and continue to focus on their main disadvantage–measurement biases (mainly in wind and mechanical underestimations). However, despite arduous scientific effort, calibration methodologies are not frequently implemented by monitoring networks operators or data users, propagating bias in databases and in the different applications of such data, causing uncertainty in the modeling, management, and forecasting in hydrological research, mainly due to a lack of knowledge. Within this context, this work presents a review of the scientific advances in TBR measurement uncertainties, calibration, and error reduction strategies from a hydrological point of view, by describing different rainfall monitoring techniques in Section 2, summarizing TBR measurement uncertainties in Section 3, focusing on calibration, and error reduction strategies in Section 4, a discussion and perspectives in Section 5, and conclusions in Section 6, providing an overview of the of the state of the art and future perspectives of the technology.

Soarinho Alkaline Intrusion, southeastern Brazil, makes part of the Serra do Mar Igneous Province, and it is composed of alkali feldspar syenite, alkali feldspar trachyte, quartz syenite, and mon-zonite. Geochemical and geochronological analysis of the Soarinho were compared with data from its neighbors Rio Bonito and Tanguá. Zircon U-Pb Laser Ablation ages show that Soarinho is youngest than Rio Bonito and Tanguá. Ages obtained from the monzonite (60 ± 2 Ma), alkali feldspar syenite (58 ± 2 Ma), and quartz syenite (58 ± 2 Ma) are indistinguishable within error. Petrographic and geochemical data show a clear contrast among Soarinho, Rio Bonito, Tanguá, and Lu-Hf isotopic data for the three alkaline intrusions (all negative), point to some similarities in their sources. The data suggest an enriched mantle source for Soarinho; however, an older con-tinental crust contribution cannot be discarded.

An emerging picture in cancer biology is that, paradoxically, chemotherapy can actively induce changes that favor cancer progression. These pro-cancer changes can be either inside (intrinsic) or outside (extrinsic) the cancer cells. In this review, we will discuss the extrinsic pro-cancer effect of chemotherapy; that is, the effect of chemotherapy on the non-cancer host cells to promote cancer progression. We will focus on metastasis, and will first discuss recent data from mouse models of breast cancer. Intriguingly, despite reducing the size of primary tumors, chemotherapy changes the tumor microenvironment, resulting in an increased escape of cancer cells into the blood stream. Furthermore, chemotherapry changes the tissue microenvironment at the distant sites, making it more hospitable to cancer cells upon their arrival. We will then discuss the idea and evidence that these devastating pro-metastatic effects of chemotherapy can be explained in the context of stress response. At the end, we will discuss the potential relevance of these mouse data to human breast cancer and their implication on chemotherapy in the clinic.

Primary varicella-zoster virus (VZV) infection causes varicella (chickenpox) and the establishment of a lifelong latent infection in ganglionic neurons. VZV reactivates in about one-third of infected individuals to cause herpes zoster, often accompanied by neurological complications. The restricted host range of VZV and, until recently, the lack of suitable in vitro models to study VZV latency have seriously hampered molecular studies of viral latency. Nevertheless, recent technological advances facilitated a series of exciting studies that resulted in the discovery of a VZV latency-associated transcript (VLT) and have redefined our understanding of VZV latency and factors that initiate reactivation. Together, these findings pave the way for a new era of research that may finally unravel the precise molecular mechanisms that govern latency. In this review, we will summarize the implications of recent discoveries in the VZV latency field from both a virus and host perspective and provide a roadmap for future studies.

Rabies is a viral zoonotic disease caused by the lyssavirus and endemic to most tropical and sub-tropical areas of the world. This study reports on the occurrence of rabies in humans and dogs and relates the results to the vaccination status of the dogs. A total of each of 25 brain and saliva samples of dogs were tested for Lyssavirus using RT-PCR and visualised using gel electrophoresis. Additionally, histopathological diagnosis of the Lyssavirus was made on the brain samples. A lyssavirus positivity of 34 % was realised. Sample specific positivity was 58 % and 10 % for brain and saliva samples respectively. Only one of the nine vaccinated dogs tested positive for lyssavirus. Five dogs that tested positive for the virus had bitten seven people prior to death. Results confirms the endemicity of the virus in Ghana and the danger it poses to humans. This study confirms vaccination as an effective tool for preventative of rabies. However, elimination of the disease is possible if there is an established and effective collaboration between veterinary and human medicine through one health.

The green biomass of horticultural plants contains valuable secondary metabolites (SM) which can potentially be extracted and sold. When exposed to stress, plants accumulate higher amounts of these SMs, making the extraction and commercialization even more attractive. We evaluated the potential for accumulating of the flavones cynaroside and graveobioside A in leaves of two bell pepper cultivars (Mavras and Stayer) when exposed to salt stress (100 mM NaCl), UVA/B excitation (UVA 4-5 W/m²; UVB 10-14 W/m² for 3 hours per day) or a combination of both stressors. HPLC analyses proved the enhanced accumulation of both metabolites under stress conditions. Cynaroside accumulation is effectively triggered by high-UV stress, whereas graveobioside A contents increase under salt stress. Highest contents were observed in plants exposed to combined stress. Effects of stress on overall plant performance differed significantly between treatments, with least negative impact on aboveground biomass found for high-UV stressed plants. The usage of two non-destructive instruments (Dualex and Multiplex) allowed us to gain insights in ontogenetical effects at the leaf level and temporal development of SM contents over time. Indices provided by those devices correlate fairly with amounts detected via HPLC (Cynaroside: R2 = 0.46 – 0.66; Graveobioside A: R2 = 0.51 – 0.71). The concentrations of both metabolites tend to decrease at leaf level during the ontogenetical development even under stress conditions. High-UV stress is a promising tool for enriching plant leaves with valuable SM without major effects on plant biomass. All data is available online [1].

Global pose refinement is a significant challenge within Simultaneous Localization and Mapping (SLAM) frameworks. For LIDAR-based SLAM systems, pose refinement is integral to correcting drift caused by the successive registration of 3D point clouds collected by the sensor. A divergence between the actual and calculated platform path characterizes this error. In response to this challenge, we propose a linear, parameter-free model, which uses a closed circuit for global trajectory corrections. Our model maps rotations to quaternions and uses Spherical Linear Interpolation (SLERP) for transitions between them. The intervals are established from the constraint set by the Least Squares (LS) method on rotation closure and are proportional to the circuit's size. Translations are globally adjusted in a distinct linear phase. Additionally, we suggest a coarse-to-fine pairwise registration method, integrating Fast Global Registration and Generalized ICP with multiscale sampling and filtering. The proposed approach is tested on three varied datasets of point clouds, including Mobile Laser Scanners and Terrestrial Laser Scanners. These diverse datasets affirm the model's effectiveness in 3D pose estimation with substantial pose differences and efficient pose optimization in larger circuits.

The identification and physical interpretation of quantum correlations, more recently explored beyond entanglement, is not always a simple task. Two assumptions that, at least in principle, should lead to a relatively large dispersion for the observables of a quantum bipartite formed by systems I and II are to assume that; (a) all the possible observables describing the composite are potentially equally probable as outcomes of measurements; and (b) there cannot be concurrence (positive reinforcement) between any of the observables within a given system, meaning all their corresponding operators do not commute. The so-called EPR states are known to observe (a). Here we demonstrate in general terms that they also verify (b). As examples, we discuss three-level systems. Given the character of (a) and (b), one may expect the CHSH correlation for qubits to naturally violate its associated Bell’s inequality (i.e., it would yield values greater than 2) when applied to EPR states. Surprisingly, we show the CHSH contradicts such prediction. This finding emphasizes the subtleties of correlations in quantum mechanics, where the conceivable dispersive interdependence of EPR states observables results counterintuitively in a more limited range of values for the CHSH correlation, not surpassing the nonlocality threshold of 2.

The forest transition – or forest-area transition – has been put forward as a land-use concept by A.S. Mather in 1992 (The forest transition. Area 24, 367-379), to describe the historical trend generally observed in the forest area of developed countries, embodied in a V-shaped curve of the forest area over time, and that may serve as a paradigm to understand and anticipate deforestation in the developing world. Well in line with a geographical approach to forests, forest transition has thus been defined as one-dimensional, forest area being the reference state variable. From a forestry perspective, the analysis appears to be reductive, as forests are described by many other state variables than area, including forest growing stock, composition in tree species, or stand structure. Whether the drivers of forest transition (population dynamics, economic modes of production and consciousness, as classified by Mather) also impact these other forest state variables in a general way thus comes forth as a logical issue.From a deductive analysis of forest transition drivers, and from forest trends brought to light in Europe, France, and at other places in the world, we here argue that the forest transition concept can be extended to a multi-dimensional space of forest attributes, characterized by typical ideal dynamics. Cumulative impacts onto forests and irreversible losses in forest biodiversity over a forest transition are hence highlighted. Global change, as a parallel consequence of countries’ developing process, further appears as one additional albeit less coupled dimension of forest transition, as it modifies forest productivity and vitality over time. Since forest ecosystem services and forest profitability primarily depend on such attributes, we argue that the extension of the forest transition concept has significance for land-use change and forest protection issues. A prospect on future changes in the forests of developed countries with the European space as a benchmark is finally proposed that leads to extend the temporal significance of forest transition. Though poorly described, returning forests on abandoned agricultural lands are significant, and deserve greater attention.

Model-based image reconstruction has brought improvements in terms of contrast and spatial resolution to imaging applications such as magnetic resonance imaging and emission computed tomography. However, their use for pulse-echo techniques like ultrasound imaging is limited by the fact that model-based algorithms assume a finite grid of possible locations of scatterers in a medium -- which does not reflect the continuous nature of real world objects and creates a problem known as off-grid deviation. To cope with this problem, we present a method of dictionary expansion and constrained reconstruction that approximates the continuous manifold of all possible scatterer locations within a region of interest. The expanded dictionary is created using a highly coherent sampling of the region of interest, followed by a rank reduction procedure based on a truncated singular value decomposition. We develop a greedy algorithm, based on the Orthogonal Matching Pursuit (OMP), that uses a correlation-based non-convex constraint set that allows for the division of the region of interest into cells of any size. To evaluate the performance of the method, we present results of 2-dimensional ultrasound image reconstructions with simulated data in a nondestructive testing application. Our method succeeds in the reconstructions of sparse images from noisy measurements, providing higher accuracy than previous approaches based on regular discrete models.

The medium-voltage DC (MVDC) technology has gained increasing interests in recent years. Power electronics devices dominate those grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system level control model of such a modern MVDC distribution grid. Aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/- 10 kV MVDC grid case study, including Solid State Transformer (SST) and Modular Multilevel Converter (MMC) based Active Front End (AFE). Additional aim of this paper is to supply an educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented.

This contribution deals with the assessment of air pollution caused by atmospheric aerosol particulate matter fraction PM10 and benzo[a]pyrene (BaP) in the urban agglomeration of Ostrava, located in the Czech Republic in Central Europe. The motivation for this research was the need to identify the sources of air pollution in the area, particularly in locations where the contribution of different sources to concentrations of pollutants of concern has not been elucidated yet. In this study, source apportionment in the vicinity of the industrial hot-spot was performed by statistically evaluating measured pollutant concentrations as a function of meteorological variables and using the Positive Matrix Factorization (PMF) receptor model. A significant methodological innovation and improvement over previous assessments was the higher monitoring resolution of benzo[a]pyrene, with samples collected at three-hour intervals instead of the standard 24-hour collection period. The key findings indicate that in the cold part of the year, secondary particles - specifically sulphates and ammonium nitrates - were responsible for the most significant portion of PM10 air pollution throughout the area of interest. The contribution of these particles ranged from one third to two fifths of the total concentration, except at the industrial site of Ostrava-Radvanice (TORE), where they accounted for approximately one fifth of the measured pollution concentration level. Emissions from individual household heating were identified as the main source of this type of pollution. With regards to benzo[a]pyrene air pollution, the study found that in the whole area of interest, except for the Ostrava-Radvanice site, it mainly originated from individual heating with coal (90%). In contrast, at the Ostrava-Radvanice site, two-thirds of the benzo[a]pyrene pollution came from the premises of Liberty Ostrava a.s., primarily from coke production, and less than one-third from local domestic heating. This study also determined the spatial extent of the occurrence of extremely high benzo[a]pyrene concentrations (above 5 ng/m3), which are estimated to affect nearly 10,000 inhabitants. The results confirm that the data from the TORE station are only representative of its immediate surroundings and are not applicable to the assessment of air quality and causes of air pollution in the whole city of Ostrava or the urban area of Ostrava-Radvanice as a whole. After years of research, these findings provide the Ministry of the Environment of the Czech Republic and the government with an accurate basis for implementing measures to address the identified pollution sources in the area of interest. The success of this study was made possible by the adoption of a more detailed sampling approach, which involved a resolution of 3 hours instead of 24 hours. This methodological improvement is a significant finding and will be useful for future source apportionment studies.

The cultivation of pea pods spans across various regions and climates with a global production of around 20 million tons. The pea peel wastes, which make up 30–40% of the total weight of the peas, are freely available in large quantities. The biomass used was characterized via ultimate, proximate, and structural analysis obtaining a 20,2 %w of cellulose and 17,4 %w of hemicellulose which via valorization processes can be transformed into platform chemicals. Hydrothermal valorization presents itself as a clean form of treatment of said wastes, ranging from 120 – 180 ºC (LHW) to 180 to 260 ºC (HTC). The use of LHW can lead to the production of sugars (up to 70%w yield) and levulinic acid (4 %w yield) while the use of HTC leads to Formic acid (40 %w) and levulinic acid (4 %w yield). The use of LHW for longer times favors the production of HMF and Furfural. The use of homogeneous catalysts (H2SO4, CH3COOH, KOH and NaHCO3) was implemented and their selectivity described. Solid fractions of LHW and HTC were characterized via FTIR and elemental analysis and the change in their structure described as they shift from biomass to biochar. Optimal conditions for each platform chemical were reported for best utilization of the peapod waste.

As humans age, aberrancies in several signaling pathways occur. In the aging population, some patients display abnormal bone morphogenetic protein (BMP) signaling. This can lead to osteoporosis (OP), a debilitating bone disorder caused by an imbalance between osteoblasts and osteoclasts. In 2002, the Food and Drug Administration (FDA) approved usage of recombinant human BMP-2 (rhBMP-2) during spinal fusion surgery as it is crucial for bone formation. However, complications have been reported with rhBMP-2 and primary osteoblasts isolated from OP patients are unresponsive to BMP-2. While patient samples are available, previous medical history may alter results. Therefore, C57BL/6 mice, an aging model that displays aberrant BMP-signaling, can be utilized to investigate OP and aging. We show that BMP receptor type Ia (BMPRIa) is upregulated in the bone marrow stromal cells (BMSCs) of 15-month mice similar to previous data. We show that a conjugation between BMP-2 and Quantum Dots (QDot®s) effectively binds to BMPRIa and can investigate BMP-2 activity. After incubating BMSCs with methyl-β-cyclodextrin (MβCD), BMP-signaling is restored in 15-month mice as shown by western blotting and the von Kossa assay. MβCD may be used to rescue BMPRIa and the BMP-signaling pathway can be utilized by future therapeutics to treat OP.

Tungsten carbide inserts (TCI) and polycrystalline diamond compact (PCD) cutters used in two types of drill bits for drilling oil and gas wells were evaluated by a pin-on-disc test. The morphology of the worn surface was characterized by scanning electron microscopy (SEM). The behavior of corrosion resistance was evaluated with the electrodynamic polarization technique. The polycrystalline diamond compact cutter has a higher hardness, better corrosion, and wear behavior compared to tungsten carbide.

The perceived poor performance of publicly traded companies on their sustainability commitments and the quality of sustainability reporting has prompted stakeholders to consider the economic, environmental, and social impacts of corporate activities. Economic activities have led to various threats in the form of climate change, pollution, greenhouse gas emissions, natural disasters, and other issues that have negatively impacted the environment and stakeholders. Companies are expected to report to stakeholders on their sustainability performance, but reality proves that present reporting falls below stakeholders’ expectations mainly due to its still voluntary nature. The present study aims to provide a literature review of the relationship between sustainability reporting and the role of companies governance, especially observing if climate change requirements and energy-needed changes are being accounted. Results highlight mixed evidence for the influence of board governance attributes, providing interesting insights for research advancement. The study has practical implications for businesses, regulators, governments, and other stakeholders in their policy deliberations and investment decisions. Further empirical studies are recommended to re-examine sustainability reporting using the variables identified as important factors and gaps in this study and other board characteristics to improve the generalizability of the results.

This paper explores the potential of using the SAM segmentator to enhance the segmentation capability of known methods. SAM is a promptable segmentation system that offers zero-shot generalization to unfamiliar objects and images, eliminating the need for additional training. The open-source nature of SAM on GitHub allows for easy access and implementation. In our experiments, we aim to improve the segmentation performance by providing SAM with checkpoints extracted from the masks produced by DeepLabv3+, then merging the segmentation masks provided by these two networks. Additionally, we examine the \enquote{oracle} method (as upper bound baseline performance), where segmentation masks are inferred only by SAM with checkpoints extracted from ground truth. In addition, we tested in the CAMO datasets an ensemble of PVTv2 transformers; combining the ensemble and SAM yields state-of-the-art performance in that dataset. The results of our study provide valuable insights into the potential of incorporating the SAM segmentator into existing segmentation techniques. We release with this paper the open-source implementation of our method.

Despite being under development for decades, RNA therapeutics have only recently emerged as viable platform technologies. The COVID-19 mRNA vaccines have demonstrated the promise and power of the platform technology. In response, novel RNA drugs are entering clinical trials at an accelerating rate. As the skin is the largest and most accessible organ, it has always been a preferred target for drug discovery. This holds true for RNA therapies as well, and multiple candidate RNA-based drugs are currently in development for an array of skin conditions. In this mini review, we catalog the RNA therapies currently in clinical trials for different dermatological diseases. We summarize the main types of RNA-related drugs and use examples of drugs currently in development to illustrate their key mechanism of action.

Introduction: Uganda has got the highest prevalence rate of malaria among the risk groups compared to other parts of the world. In addition, Uganda bears a particularly large burden from the disease which is limited by a lack of reliable data, but it is clear that the prevalence of malaria infection, incidence of disease, and mortality among pregnant women all remain very high. According to the Iganga DHIS2 Jan-May report, a higher number of pregnant women received Intermittent Preventive Treatment one (IPT1) and the numbers dropped for IPT2 and IPT3. The district is also referral point of the greater Busoga region and has got several challenges towards malaria control. The study aimed at assessing the uptake of Intermittent Preventive Treatment and the prevalence of malaria among pregnant women in Iganga district so as to generate evidence for scaling up appropriate interventions for IPT uptake among pregnant women. Methods: The research was a retrospective study using secondary data to assess the uptake of IPT and prevalence of malaria for financial year 2019/2020 in nine Public Health Centre IIIs and one Public Health Centre IV. In this study IPT was defined as the administration of a curative dose of an effective antimalarial drug to all pregnant women without testing for presence of malaria parasite and at least three doses as recommended. Secondary data from HMIS was obtained and analyzed to assess the uptake of IPT services and the prevalence of malaria among pregnant women was determined using proportions. Results: The study found that of 6,672 women who received the first dose of IPT-SP, 1671 (25%) of the women received less than 2 doses of IPT and 46% of pregnant women received more than 2 doses of IPT. The study showed that a total of 3,435 pregnant women tested positive for malaria which brings the prevalence to 50%, and being highest among pregnant women aged 20-24 years at 50%. Conclusions: The study showed that the uptake of IPT was relatively low among lower age groups with a relatively high prevalence of malaria among the same age group. This calls for all stakeholders (DHO, MOH, Iganga District, NGOs e.t.c) urgent attention thus to ensure mass sensitization about malaria and IPT importance with IEC and ITN distribution, early diagnosis and treatment, giving incentives to ANC attending mothers, control of the vector.

Introduction: Since its emergence COVID-19 has become a global health threat. In Uganda, a number of COVID-19 Standard Operating Procedures (SOPs) have been put in place by the Ministry of Health Uganda, to mitigate the outbreak of the deadly COVID-19 pandemic among the population. Despite the putting in place COVID-19 SOPs, the deadly COVID-19 pandemic is still ravaging the population of Iganga District. This study investigated the level of compliance to guidelines for prevention of COVID-19 in public places in Iganga District so as to guide decision makers in making recommendations towards the entire public in order to prevent community acquisition and spread of COVID-19. Methodology: To deliver answers to the research objectives, the study adopted a cross-sectional survey design to guide the study process. Quantitative method of data collection using observational checklist were adopted for this study. The same data abstraction form helped to collect data from 3 public places which included: 3 markets, 5 public transport stations and 8 financial banks. Compliance was measured were the YES scored 1 and NO scored 0 and the ten indicators measured included: temperature screening, wearing of face masks, hand washing or sanitizing, physical distancing of at least 2 meters, information display on COVID-19, regular cleaning of public service places, cleaning of communal places, adequate ventilation, adequate waste management facilities and cleanliness of the work area. Overall a 4 point Likert scale used was: 0-2 poor, 3-5 fair, 6-8 good, 9-10 excellent were each indicator was equally important. Data was entered, cleaned and analyzed using Microsoft Excel 2019 spread sheet packages to generate tables and bar graphs. Results: Out of 5 public transportation stations studied, 80% were observed to be poorly compliant to covid-19 SOPs. On the other hand, out of 8 Financial Banks included in this study, 75% were observed to have excellent compliance levels to COVID-19 SOPs. Meanwhile, out of 3 Market places studied, 66.7% were observed to be poorly compliant to covid-19 SOPs. Conclusion; The results of the study revealed that; public places in Iganga district generally have low level of compliance to COVID-19 SOPs in terms of temperature screening, wearing of face masks, hand washing or sanitizing, social distancing of at least 2 meters and information display on COVID-19 Dos and Don’ts. Our findings suggest that there is a need to mobilize the population in Iganga district to comply with COVID-19 SOPs in terms of temperature screening, wearing of face masks, hand washing or sanitizing, social distancing of at least 2 meters and information display on COVID-19 Dos and Don’ts.