During the past few years unexpected developments have driven studies in the field of clinical immunology. One driver of immense impact was the outbreak of a pandemic caused by the novel virus SARS-CoV-2. Excellent recent reviews address diverse aspects of immunological re-search into cardiovascular diseases. Here, we specifically focus on selected studies taking ad-vantage of advanced state-of-the-art molecular genetic methods ranging from genome-wide epi/transcriptome mapping and variant scanning to optogenetics and chemogenetics. First, we discuss emerging clinical relevance of advanced diagnostics for cardiovascular diseases - includ-ing those associated with COVID-19 - with a focus on the role of inflammation in cardiomyopa-thies and arrhythmias. Second, we consider newly identified immunological interactions at or-gan and systems level which affect cardiovascular pathogenesis. Thus, studies into immune in-fluences arising from the intestinal system are moving towards therapeutic exploitation. Fur-ther, powerful new research tools have enabled novel insight into brain – immune system inter-actions at unprecedented resolution. This latter line of investigation emphasizes the strength of influence of emotional stress - acting through defined brain regions - upon viral and cardiovas-cular disorders. Several challenges need to be overcome before the full impact of these far-reaching new findings will hit the clinical arena.

At the end of 2019, while the world was being hit by the COVID-19 virus and, consequently, was living a global health crisis, many other pandemics were putting humankind in danger. The role of social media is of paramount importance in these kinds of contexts since they help health systems to cope with emergencies by contributing to conducting some activities such as the identification of public concerns, the detection of infections’ symptoms, and the traceability of the virus diffusion. In this paper, we have analyzed comments on events related to cholera, ebola, HIV/AIDS, influenza, malaria, Spanish influenza, swine flu, tuberculosis, typhus, yellow fever, and zika, collecting 369,472 tweets from the 3rd of March to the 15th of September, 2022. Our analysis has started with the collection of comments composed of unstructured texts on which we have applied natural language processing solutions. Afterward, we have employed topic modelling and sentiment analysis techniques to obtain a collection of people’s concerns and attitudes toward these pandemics. According to our findings, people's discussions were mostly about malaria, influenza, and tuberculosis and the focus was on the diseases themselves. As regards emotions, the most popular were fear, trust, and disgust where trust is mainly regarding HIV/AIDS tweets.

This study evaluated the using of machine vision in combination with deep learning to identify weeds in real-time for wheat production system. PMAS-Arid Agriculture university research farm were selected for collection of images (6000 total images) of weeds and wheat crops under different weather condition. During growing season, the database was constructed to identify the weeds. For this study two framework were used TensorFlow and PyTorch under CNNs and Deep learning. Deep learning perfromed better with in PyTourch value as compared to another model in Tensorflow. comparing with other networks such as YOLOv4, we concluded that our network reaches a better result between speed and accuracy. Specifically, the maximum precision of weed and wheat plants were 0.89 and 0.91 respectively with 9.43 ms and 12.38 ms inference time per image (640 × 640) NVIDIA RTX2070 GPU.

This research investigates a model for the COVID-19 outbreak in Indonesia by analyzing comorbid diseases, self-quarantine, government-provided quarantine, and immunization regimens. Some model parameters are derived from academic journals, others are extrapolated from data collected by the Indonesian Ministry of Health in 2020, and others are assumed. Evaluation of the model reveals non-endemic equilibrium points, endemic equilibrium points, and the basic reproduction number (BRN). The contact rate and infected probability factors impact the increase in the number of COVID-19-infected individuals with comorbid disease within a group. According to the sensitivity analysis of the BRN, the key parameters impacting the spread of COVID-19 are the rate of susceptible recruitment, the rate of contact, the COVID-19 infection death rate, and the likelihood of infection. In addition, sensitivity analyses are provided to examine the effect of parameter changes on subpopulations. We discovered that the natural death rate is the most sensitive parameter based on the sensitivity index after reaching equilibrium. Symmetry aspects appear in some of the visualization of the model’s solution and the BRN and parameters’ sensitivity.

COVID-19 is a well-known respiratory disease spreading worldwide since January 2020, causing many deaths and massive pressure on health systems. This pandemic’s appearance compromised the health services’ sustainability and quality as many procedures were postponed or even canceled out, with an expected increase of adverse events like nosocomial infections, in-hospital deaths, and the worsening of the patients’ clinical status. Therefore, assessing whether the healthcare providers’ performance has changed is paramount. In this case, we evaluated the public hospitals in Portugal as the leading secondary health care providers in the country, which in turn has been highly affected by the pandemic. To this end, we developed a network Data Envelopment Analysis model serially relating efficiency and effectiveness. Using 2,795 observations from public hospitals and 18 variables, we observed consistent drops in efficiency when the pandemic started, followed by a recovery to levels above the pre-pandemic ones. Regarding effectiveness, we observed a positive trend during the evaluated period. In short, these results allow us to conclude that, apart from the great resilience of public healthcare providers, the Portuguese State was not prepared for a pandemic like COVID-19, but still the actions taken (including massive vaccination) were beneficial.

Abstract Aim of the study: Presentation of ophthalmic symptoms of Cerebral Autosomal Dominant Arteriopathy with Subcortical Infracts and Leucoencephalopathy (CADASIL). Material and methods: Clinical presentation of female patient with diagnosed CADASIL, manifested by transient loss of vision, migraine, convergence insufficiency, diplopia, increased deep tendon reflexes of upper left limb, subcortical infarcts, mood disturbances and dementia. Results: Confirmed NOTCH3 gene mutation (p.Cys212Gly), and presence of granular osmiophilic material (GOM) in cutaneous small vessel wall in immunohistochemistry laboratory test (IHC). Magnetic resonance imaging (MRI) revealed bilateral focal vasogenic lesions in white matter of cerebral hemisphere with single micro-focal infarct in the left external capsule. Furthermore, a left eye exophoria, a bilateral peripheral visual field loss of 20 degrees and a loss of nasolabial fold was confirmed during ophthalmic tests. An eye fundus examination as well as a fluorescein angiography (FA) revealed vessel constriction of retinal arteries and a peripheral retinal pigment epithelium (RPE) atrophy with focal drusen in the left eye. The doppler ultrasonography (USG) confirmed a decreased blood flow and an increased vascular resistance of the extraocular vessels. The pattern electroretinogram (PERG) revealed a reduced P50 wave amplitude in the patient’s left eye. Conclusions: intermittent blindness, migraine, convergence failure, diplopia with specific MRI signs, NOTCH3 mutation, and the presence of GOM in the skin of small blood vessels in a young or middle-aged patient suggests CADASIL. New observations include: atrophic changes in the RPE, hemodynamic disturbances in blood flow in the short posterior ciliary arteries and in the central retinal artery, single drusen in the retina, and a reduced amplitude of the P50 wave in PERG.

Magnesium and Aluminum alloys continue to be important in the context of modern and lightweight technologies. With the advancement of additive manufacturing (AM), components can be produced directly in a net shape, widen up the usage of magnesium and aluminum alloys as well as holding new ideas for the application of unique physical structures made feasible by 3D printing. Laser-based approach, one of the metal additive manufacturing (AM) methods, enables the formation of arbitrary 3D structures. With promising findings, research in this area is advancing quickly, bringing up a variety of potential applications in both the scientific and industrial sectors. Complex structures can now be manufactured easily utilizing AM technologies to meet the pre-requisite objectives like reduced part numbers, greater functionality, and lightweight, among others. AM has the ability to meet demands by lowering costs and speeding up the manufacturing process. Due to their popularity in numerous high-value applications, aluminum, and magnesium alloys are one of the key material systems being researched in the laser-based additive manufacturing approaches. The review here aims to comprehensively examine the additive manufacturing of magnesium and aluminum alloys, highlighting the influence of the laser-based additive manufacturing approach on the mechanical characteristics, microstructure, and tribological performance of magnesium and aluminum alloys.

In this work we present a new algorithm that achieves the perfect Shannon secret by means of the XOR function and a method that we call multiple key reuse. The algorithm has two execution modes: message authentication and data encryption. The XOR encryption scheme allows for batch encryption and exhibits Perfect Forward Secrecy (PFS). Furthermore, based on our fundamental algorithm, we have developed a new strategy for blockchain implementation that does not require Proof of Work (PoW), but defines a fair mechanism for miner selection and secure addition of blocks to the chain. Since our method is mainly based on the Boolean XOR function, the strength of the cryptosystem can be directly established thanks to its mathematical properties. Due to the risk that quantum computers represent for current cryptosystems based on prime factorization or discrete logarithm, we postulate that our method represents a promising alternative in the quantum era for the security of communications between Internet of Things devices as well as Blockchain technology.

Recent deep learning frameworks draw a strong research interest in the application of ego-motion estimation as they demonstrate a superior result compared to geometric approaches. However, due to the lack of multimodal datasets, most of these studies primarily focused on a single sensor-based estimation. To overcome this challenge, we collect a unique multimodal dataset named LboroAV2, using multiple sensors including camera, Light Detecting And Ranging (LiDAR), ultrasound, e-compass and rotary encoder. We also propose an end-to-end deep learning architecture for fusion of RGB images and LiDAR laser scan data for odometry application. The proposed method contains a convolutional encoder, a compressed representation and a recurrent neural network. Besides feature extraction and outlier rejection, the convolutional encoder produces a compressed representation which is used to visualise the network's learning process and to pass useful sequential information. The recurrent neural network uses this compressed sequential data to learn the relation between consecutive time steps. We use the LboroAV2 and KITTI VO datasets to experiment and evaluate our results. In addition to visualising the network's learning process, our approach gives superior results compared to other similar methods. The code for the proposed architecture is released in GitHub and accessible publicly.

In Los Angeles, at one point, the Covid-19 testing positivity rate was 6.25%, or one in sixteen. This translates to, on average, one in sixteen specimens testing positive and the vast majority testing negative. Usually, we run sixteen tests on sixteen specimens to identify the positive one(s). This process can be time consuming and expensive. Since a group of negative specimens pooled together for testing will produce a negative result, one single test could potentially eliminate many specimens. Only when the pooled specimen tests positive do we need further testing to identify the positive one(s). Based on this concept, we designed a strategy that will identify the positive specimen(s) efficiently. Assuming one in sixteen specimens is positive, we find that only four tests are needed. Furthermore, we can run them simultaneously, saving both resources and time. Although, in the real world, we cannot make the assumption of only one positive specimen, the same strategy works with slight modification and proves to be much more efficient than the conventional testing. Our strategy returns an answer 48% of the time in four tests and one time cycle. Overall, the average number of tests is seven or eight depending on the follow-up testing, and the average time cycle is about one and a half.

Skin cancer is an uncommon but serious malignancy. Dermoscopic images examination and biopsy are required for cancer detection. Deep learning (DL) is extremely effective in learning characteristics and predicting malignancies. However, DL requires a large number of images to train. Image augmentation and transferring learning were employed to overcome the lack of images issue. In this study we divided images into two categories: benign and malignant. To train and test our models, we used the public ISIC 2020 database. Melanoma is classified as malignant in the ISIC 2020 dataset. Along with categorization, the dataset was studied to demonstrate variation. The performance of three top pretrained models was then benchmarked in terms of training and validation accuracy. Three optimizers were employed to optimize the loss: RMSProp, SGD, and ADAM. Using ResNet, VGG16, and MobileNetV2, we obtained training accuracy of 98.73%, 99.12%, and 99.76%, respectively. Using these three pretrained models, we attained a validation accuracy of 98.39%.

This study identified and mapped worldwide surveillance actions and initiatives of drinking water quality implemented by government agencies or public health services. The scoping review was conducted between July 2021 and August 2022 based on the Joanna Briggs Institute. The search was performed in relevant databases and grey literature; 49 studies were obtained. Quantitative variables were presented as absolute and relative frequencies, while qualitative variables were analyzed using the IRaMuTeQ software. The actions developed worldwide and their impacts and results provided four thematic classes: (1) assessment of coverage, accessibility, quantity, and drinking water quality in routine and emergency situations; (2) analysis of physical-chemical and microbiological parameters in public supply networks or alternative water supply solutions; (3) identification of household water contamination, communication, and education with the community; (4) and investigation of water-borne disease outbreaks. Preliminary results were shared with stakeholders to favor early knowledge dissemination.

The G protein-coupled receptor (GPCR) Smoothened (Smo) is a central signal transducer of the Hedgehog (Hh) pathway which has been linked to diverse forms of tumours. Stimulated by advancements in structural and functional characterisation, the Smo receptor has been recognised as an important therapeutic target in Hh-driven cancers, and several Smo inhibitors have now been approved for cancer therapy. This receptor is also known to be an oncoprotein itself and its gain-of-function variants have been associated with skin, brain, and liver cancers. According to the COSMIC database, oncogenic mutations of Smo have been identified in various other tumours, although their oncogenic effect remains unknown in these tissues. Drug resistance is a common challenge in cancer therapies targeting Smo, and data analysis shows that healthy individuals also harbour resistance mutations. Based on the importance of Smo in cancer progression and the high incidence of resistance towards Smo inhibitors, this review suggests that detection of Smo variants through tumour profiling could lead to increased precision and improved outcomes of anti-cancer treatments.

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. 3D pharmacophore models are powerful computational tools in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning will be highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

A synoptic review of plant disease epidemics and outbreaks was made using two complementary approaches. The first approach involved reviewing scientific literature published in 2021, in which quantitative data related to new plant disease epidemics or outbreaks were obtained via surveys or similar methodologies. The second approach involved retrieving new records added in 2021 to the CABI Distribution Database, which contains over a million global geographic records of organisms from over 50,000 species. The literature review retrieved 186 articles, describing studies in 62 categories (pathogen species/species complexes) across >40 host species on 6 continents. Pathogen species with >5 articles were: Bursaphelenchus xylophilus, Candidatus Liberibacter asiaticus, cassava mosaic viruses, citrus tristeza virus, Erwinia amylovora, Fusarium spp. complexes, Fusarium oxysporum f. sp. cubense, Magnaporthe oryzae, maize lethal necrosis co-infecting viruses, Meloidogyne spp. complexes, Pseudomonas syringae pvs, Puccinia striiformis f. sp. tritici, Xylella fastidiosa, and Zymoseptoria tritici. Automated searches of the CABI Distribution Database identified 617 distribution records new in 2021 of 283 plant pathogens. A further manual review of these records confirmed 15 pathogens reported in new locations: apple hammerhead viroid, apple rubbery wood viruses, Aphelenchoides besseyi, Biscogniauxia mediterranea, Ca. Liberibacter asiaticus, citrus tristeza virus, Colletotrichum siamense, cucurbit chlorotic yellows virus, Erwinia rhapontici, Erysiphe corylacearum, Fusarium oxysporum f. sp. cubense Tropical Race 4, Globodera rostochiensis, Nothophoma quercina, potato spindle tuber viroid, and tomato brown rugose fruit virus. Of these, 4 pathogens had at least 25% of all records reported in 2021. We assessed two of these pathogens – tomato brown rugose fruit virus and cucurbit chlorotic yellows virus – to be actively emerging in/spreading to new locations. Although three important pathogens – Ca. Liberibacter asiaticus, citrus tristeza virus and Fusarium oxysporum f. sp. cubense – were represented in the results of both our literature review and our interrogation of the CABI Distribution Database, in general our dual approaches revealed distinct sets of plant disease outbreaks and new records, with little overlap.

Artificial membrane systems can serve as models to investigate molecular mechanisms of different cellular processes, including transport, pore formation, and viral fusion. However, the current simulacrums such as SUVs, GUVs, and the supported lipid bilayers suffer from issues, namely high curvature, heterogeneity, and surface artefacts, respectively. Freestanding membranes provide a facile solution to these issues, but current systems developed by various groups use silicon or aluminium oxide wafers for fabrication that involves access to a dedicated nanolithography facility and high cost while conferring poor membrane stability. Here, we report the development, characterization and applications of an easy-to-fabricate suspended lipid bilayer (SULB) membrane platform leveraging commercial track-etched porous filters (PCTE) with defined microwell size. Our SULB system offers a platform to study the lipid composition-dependent structural and functional properties of membranes with exceptional stability in a high throughput fashion. With dye entrapped in PCTE microwells by SULB, we show that sphingomyelin significantly augments the activity of pore-forming toxin, Cytolysin A (ClyA) and the pore formation induces lipid exchange between the bilayer leaflets. Further, we demonstrate high efficiency and rapid kinetics of membrane fusion by dengue virus in our SULB platform. Our suspended bilayer membrane mimetic offers a novel platform to investigate a large class of biomembrane interactions and processes.

Entrepreneurship has been viewed as an opportunity for economic development and changing economic scenarios in global markets. Women are viewed as a reservoir of entrepreneurial talent, so they can be growth engines in novel markets. Previous studies have considered entrepreneurship as the most effective way towards the economic empowerment of women. Female students engaged in entrepreneurial education have been addressed persistently, while what transforms them in an education process is still unclear. Considering the transforming global economy and its influence on higher education, this study aims to detect female students transforming entrepreneurial competency, mindset, and intention into sustainable entrepreneurship. Using a self-compiled survey, we targeted 752 female students to investigate their entrepreneurial competency, mindset, and intention. SPSS and AMOS were used to transform the data for interpretation. We assumed that the impact of female students’ entrepreneurial competency could be modified by an entrepreneurial mindset and result in entrepreneurial intention. To detect this causal relationship, this study employed reliability, factor, structural equation modeling (SEM), and bootstrap-ping analyses to verify the evidence. The result of the SEM confirms that female students’ entrepreneurial competency will, through their entrepreneurial mindset, impact entrepreneurial intention. With bootstrapping, 5000 samples were collected, and it was demonstrated that the measure constructs were still reliable in the model. This study found that there is a mediation effect between entrepreneurial competency and entrepreneurial intention. The entrepreneurial mindset plays a crucial role in the transformation process. Without an entrepreneurial mindset, entrepreneurial competency cannot exert a significant effect on entrepreneurial intention. The findings can help reinvent related entrepreneurial education in higher education.

In the recent decade, metal-based conductive nano-inks comprising of nanometer-sized metallic particles of high electrical conductivity (mainly Ag and Cu) suspended in a polymer have revolutionized the field of printed electronics. The present review aims to provide an overview of the current state of research in synthesis and characterization techniques for metallic nano-inks and associated challenges. Moreover, the end of the review will discuss future perspectives in this field (from industrial and academic viewpoints).

Epithelial surfaces in humans are home to symbiotic microbes (i.e., microbiota) that influence the defensive function against pathogens depending on the health of the microbiota. Healthy microbiota contribute to the well-being of their host in general (e.g., via the gut-brain-axis), and their respective anatomical site in particular (e.g., oral, urogenital, skin or respiratory microbiota). Despite efforts towards a more responsible use of antibiotics, they are often prescribed for uncomplicated, self-limiting infections and can have a substantial negative impact on the gut microbiota. Treatment alternatives such as non-steroidal anti-inflammatory drugs may also influence the microbiota and thus can have lasting adverse effects. Herbal drugs offer a generally safe treatment option for uncomplicated infections of the urinary or respiratory tract. Additionally, their microbiota preserving properties allow for a more appropriate therapy of uncomplicated infections without contributing to an increase in antibiotic resistance or disturbing the gut microbiota. Here, herbal treatments may be a more appropriate therapy with a generally favorable safety profile.

Genome-scale metabolic model (GEM) is a powerful tool for interpreting and predicting cellular phenotypes under various environmental and genetic perturbations. However, GEM only consid-ers stoichiometric constraints, and the simulated growth and product yield values will show a monotonic linear increase with increasing substrate uptake rate, which deviates from the experi-mentally measured values. Recently, the integration of enzymatic constraints into stoichiometry-based GEMs was proven to be effective in making novel discoveries and predicting new engineer-ing targets. Here we present the first genome-scale enzyme-constrained model (eciCW773) for Corynebacterium glutamicum reconstructed by integrating enzyme kinetic data from various sources using ECMpy workflow based on the high-quality GEM of C. glutamicum (obtained by modifying the iCW773 model). The enzyme-constrained model improved the prediction of pheno-types and simulated overflow metabolism, while also recapitulating the trade-off between biomass yield and enzyme usage efficiency. Finally, we used eciCW773 to identify several gene modifica-tion targets for L-lysine production, most of which agree with previously reported genes. This study shows that incorporating enzyme kinetic information into the GEM enhances the cellular phenotypes prediction of C. glutamicum, which can help identify key enzymes and thus provide reliable guidance for metabolic engineering.

Excessive online behaviors refer to harmful or disproportionate use of digital network applications. Such behaviors are likely to be associated with escapist motives. Our aim was to analyze whether escapism predicts excessive gambling, excessive gaming, and excessive internet use over time. A longitudinal sample of Finnish residents aged 18–75 years (N = 1,022, 51.27% male) was surveyed at three time points in 6-month intervals: April 2021 (Time 1), October–November 2021 (Time 2), April–May 2022 (Time 3). Of the original Time 1 respondents, 66.80% took part in the surveys at both Time 2 and Time 3. All surveys included measures for excessive gambling (Problem Gambling Severity Index), excessive gaming (Internet Gaming Disorder Test), and excessive internet use (Compulsive Internet Use Scale). Three escapism-specific questions were used to construct a dedicated escapism variable. Socio-demographic variables, alcohol consumption, and psychological distress were used as controls. The study was conducted with multilevel regression analyses using hybrid models. Our research showed that escapism had strong within-person effects on excessive gambling, B = 0.18, p = .003; excessive gaming, B = 0.50, p < .001; and excessive internet use, B = 0.77, p < .001 over time. The between-person effect of escapism was demonstrated on excessive gaming B = 0.91, p <.001; and excessive internet use B = 0.61, p = .036. Adverse societal events and uncertain times can manifest in excessive online behaviors motivated by escapism, highlighting a need to focus prevention efforts on healthy coping methods.

We conduct a thematic analysis of a U.S. adult sample’s self-reported motives and perception of environmental activists’ motives to engage in pro-environmental behavior via a qualitative online survey. We identified themes using a two-stage coding procedure, whereby the research team first helped to code all content into one or more of 17 inductive content categories, then the lead investigator examined themes in each of the categories and created 5 themes based on both inductive and theoretical (e.g., moral foundations theory) considerations: a) harm and care, b) purity, c) waste and efficiency, d) spreading awareness, and e) self-interest (mostly non-financial). Endorsement of themes were qualitatively similar across individuals’ own self-described motives and perceptions of environmental activists’ motives.

The recent COVID-19 pandemic has caused tremendous damage to social economy and people’s health. Some major issues fighting COVID-19 include early and accurate diagnosis and the shortage of ventilator machines for critical patients. In this work, we propose a closed-loop solution to deal with COVID-19: portable biosensing and wearable photoacoustic imaging for early and accurate diagnosis of infection and magnetically neuromodulation or minimally invasive electrical stimulation to replace the traditional ventilation. Proposed technique can guarantee ubiquitous and onsite detection, and electrical hypoglossal stimulator can be more effective in helping severe patients as well as reducing complications caused by ventilators.

The cyclic universe theory is a model of cosmic evolution according to which the universe undergoes endless cycles of expansion and cooling, each beginning with a big bang and ending in a big crunch. In this paper, the researcher finds a unique property of Space-time, this particular and marvelous nature of space shows us that space can shrink, expand, and stretch. This property of space is caused the size of the Universe changing over time: growing or shrinking. The observed accelerated expansion, which relates the stretching of Shrunk space for the new theory, is derived. This model is based on three underlying notions: First, the Big Bang was not the beginning of Space-time, but rather at the very beginning fraction of a second there was an infinite force of infinite Shrunk space in the cosmic singularity, that force gave rise to the big bang and caused the rapidly growing of space-time, and all other forms of energy are transformed into matter and radiation and a new period of expansion and cooling begins. Second, there was a previous phase leading up to it, with multiple cycles of contraction and expansion that repeat indefinitely. Third, the two principal long-range forces are the gravitational force and the repulsive force generated by shrunk space. They are the two most fundamental quantities in the universe that govern cosmic evolution. They may provide the clockwork mechanism that operates our eternal cyclic universe. The space will not continue to expand forever, no need however, for dark energy and dark matter. This model of Space-time and its unique properties enables us to describe a sequence of events from the Big Bang to the Big Crunch.

Using digital media has become the most popular leisure activity for children and adolescents. The effects of digital media use on the developing brain and cognitive processes of children are subject to debate. Here, we examine the effect of digital media use on attention subdomains in children aged 6 to 10 years. In total, 77 children participated in the study. Selective and divided attention as well as switching between attentional demands were quantified by the SwAD task. Parents were asked to assess the screen time of their children (TV, smartphone, laptop/PC, game console, tablet). Results show no main or interaction effects of screen time on any of the attention conditions investigated. Based on the present findings, as well as previous studies, we suggest a possible non-linear relationship between the amount of screen time and attention function. Furthermore, we emphasize the relevance of considering the socio-economic background of children and a need for longitudinal studies.

A total $m$-labelling $\alpha$ on graph $\Gamma$ is called an edge irregular total $m$-labelling if for any two different edges of $\Gamma$, their weights respect to $\alpha$ are distinct, where the weight of any edge is defined as the sum of its label and the labels of its end vertices. We determine the minimum $m$ such that $\Gamma$ can be labelled by an edge irregular total $m$-labelling whenever $\Gamma$ is an odd staircase graph or an even staircase graph.

This research was carried out with the objective of analyzing the principles of social and solidarity economy in the community funds of the rural sector of Pichincha, Ecuador. Small organizations promote microcredits for local, social and economic development, representing an alternative to those managed by traditional banks. The research was descriptive, non-experimental field research. The population analyzed consisted of 220 community funds, and the size of the representative sample was 49 community organizations that practice solidarity finance. The data were collected through online questionnaires using a Likert scale, and the validity of this approach was judged by experts; the reliability of the instrument obtained was 0.95 using the Cronbach’s alpha method. The results highlight that in these organizations, the following traits prevail: associativity, self-management and organization. However, autonomy and solidarity have a negative valuation, which shows that strategies must be rethought to achieve the empowerment of the financial service. This will allow them to be sustainable and to expand with more benefits that promulgate financial activity and promote structures in rural community networks that promote local development and strengthen deficient principles as a basis for generating a greater benefit to the partners.

Disasters such as the 2015-2018 drought in South Africa usually negatively impact agricultural water, especially in smallholder farming systems. This study assessed the availability of irrigation water, performance of irrigation infrastructure, and water governance systems in Genadendal, Western Cape, with a focus on smallholder farmers. Data for streamflow, dam levels, and rainfall were acquired from water institutions and analysed using Microsoft Excel. The performance of the infrastructure and water governance were assessed based on the perceptions of smallholder farmers and key informants. A questionnaire was administered to eight smallholder farmers, followed by a focus group discussion with 15 smallholder farmers. Interviews were conducted with eight key informants who worked in water-related institutions. Qualitative data from the interviews were analysed using thematic content analysis. The study showed adequate agricultural water resources during the 2015-2018 drought period for the smallholder farmers who relied on water from dams. However, smallholder farmers who relied on the Riviersonderend River experienced severe water shortages during the same period. The findings also showed that there was poor performance of irrigation water infrastructure due to inadequate maintenance. Lack of coordination among institutions, insufficient funding, political interference, fragmentation of roles and responsibilities, lack of human resources, and farmers’ lack of participation and commitment in water resources management contributed to the dysfunctionality of irrigation water governance systems, leading to water insecurity. This study recommends adequate funding for the operation and maintenance of infrastructure. Furthermore, water institutions need to support smallholder farmers with training skills in agricultural water management and infrastructure maintenance. Further studies are recommended to quantify the water lost due to the poor performance of water infrastructure and to develop effective water governance in Genadendal.

(1) Background: The subject of athlete burnout is often discussed among sports psychologists. Interventions to reduce this phenomenon are still under investigation with follow-up. Thus, the purpose of the current meta-analysis was to examine psychological interventions that have already been carried out to decrease or eliminate burnout syndrome in young athletes. (2) Methods: Scientific electronic databases were searched and five published studies published between January 2002 and June 2022, which met the criteria, were selected. This systematic review and meta-analyses followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Cochrane Collaboration's tool for assessing the risk of bias was used to assess the studies' quality. The metafor a package of the R statistical program was used to perform the analysis. (3) Results: Cognitive-behavioral therapy as well as mindfulness-based interventions effectively reduced most dimensions of burnout. Moreover, online interventions were significantly more beneficial in this reduction (4) Conclusions: There should be more high-quality studies on the effectiveness of psychological interventions in reducing burnout. Mainly because it leads to tremendous physical and psychological problems for athletes and their coaches and therefore requires particular interventions and prevention strategies.

Normal function of placental extravillous trophoblasts (EVTs), which are responsible for uteroplacental vascular remodeling, is critical for adequate delivery of oxygen and nutrients to the developing fetus and normal fetal programming. Proliferation and invasion of spiral arteries by EVTs depends upon adequate levels of folate. Multidrug resistance-associated protein 1 (MRP1), which is an efflux transporter, is known to remove folate from these cells. We hypothesized that palmitic acid increases MRP1-mediated folate removal from EVTs, thereby interfering with EVTs’ role in early placental vascular remodeling. HTR-8/SVneo and Swan-71 cells, first trimester human EVTs, were grown in the absence or presence of 0.5 mM and 0.7 mM palmitic acid, respectively, for 72 h. Palmitic acid increased ABCC1 gene expression and MRP1 protein expression in both cell lines. The rate of folate efflux from the cells into the media increased with a decrease in migration and invasion functions in the cultured cells. Treatment with N-acetyl cysteine (NAC) prevented the palmitic acid mediated upregulation of MRP1 and restored invasion and migration in the EVTs. Finally, in an ABCC1 knockout subline of Swan-71 cells, there was a significant increase in invasion and migration functions. The novel finding in this study that palmitic acid increases MRP1-mediated folate efflux provides a missing link that helps to explain how maternal consumption of saturated fatty acids compromises the in-utero environment.

The objective of this study was to compare the mental well-being of French women who were and were not pregnant during the first COVID-19 pandemic lockdown. We performed a nationwide online quantitative survey including all women between 18 and 45 years of age during the second and third weeks of global lockdown (March 25–April 07, 2020). The main outcome measures was the mental well-being measured by the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). This study analysed 275 responses from pregnant women and compared them with those from a propensity score–matched sample of 825 non-pregnant women. The median WEMWBS score was 49.0 and did not differ by pregnancy status. Women living in urban areas reported better well-being, while those with sleep disorders or who spent more than an hour a day watching the news reported poorer well-being. During the first lockdown in France, women had relatively low mental well-being scores, with no significant difference between pregnant and non-pregnant women. More than ever, health-care workers need to find a way to maintain their support for women’s well-being. Minor daily annoyances of pregnancy, such as insomnia, should not be trivialised because they are a potential sign of poor well-being.

A low-cost medium power carbon dioxide (CO₂) laser system is designed, constructed, and characterized to produce coherent, monochromatic laser radiation in the Infrared region. The laser cavity is simulated and designed by using ZEMAX optic studio. A switch-mode high tension pump source is designed and constructed using a flyback transformer and simulated using NI Multisim to study the voltage behavior at different node points. A prototype cooling system/chiller is designed and built using the Thermo-Electric Coolers (TEC) to remove the excess heat produced during laser action. Various parameters, like pumping mechanism, chiller stability, efficiency, output power, and current at different applied voltages, are studied. The chiller efficiency at different output powers of the laser is analyzed, which clearly shows that the chiller's cooling rate is good enough to compensate for the heat generated by the laser system. The center wavelength of the carbon dioxide laser is 10.6μm with FWHM of 1.2nm simulated in the ZEMAX optic studio. The output beam penetration through salt rock (NaCl), wood, and acrylic sheet at various output powers is analyzed to measure the penetration depth rate of the CO₂ laser.

According to the risk investigations of being involved in an accident, alcohol-impaired driving is one of the major causes of motor-vehicles accidents. Preventing highly intoxicated persons from driving would potentially save many lives. This paper proposes a lightweight in-vehicle alcohol detection that processes the data generated from 6-alcohol sensors (MQ-3 Alcohol Sensors) using an optimizable shallow neural network (O-SNN). The experimental evaluation results exhibit a high-performance detection system scoring a 99.8% of detection accuracy with a very short inferencing delay of 2.22 µ seconds. Hence, the proposed model can be efficiently deployed and used to discover in-vehicle alcohol with high accuracy and low inference overhead as a part of the driver alcohol detection system for safety (DADSS) system aiming at massive deployment of alcohol sensing systems that could potentially save thousands of lives annually.

The COVID-19 is an exponentially growing disease that has intentioned nations to use technologies to detect the coronavirus infection. Several nations are working greatly to fight against COVID-19. Many nations have been using a range of devices to combat the pandemic, seeking information about growth, monitoring as well as the leaking the confidential information of the residents. This research aims to assist infected people online using the Internet of Things (IoT) and Blockchain technologies through smart devices. IoT-based healthcare devices gather useful information, provide additional insight through symptoms and behaviors, allow remote monitoring, and simply give people better self - determination and healthcare. Blockchain allows the secure transfer of patient health information, regulates the medical distribution network. A four-layer architecture is proposed using IoT and Blockchain to detect and prevent individuals to be COVID 19. This research provides a framework for patients with COVID-19 infectious disease and recognizes health issues and diagnoses online. Smart devices such as smartphones can install any mobile apps such as Aarogya Setu, Tawakkalna, and so on. These applications can track COVID-19 patients properly. The installation of mobile apps on smart devices focuses to reduce the time and cost and increase the performance of the infectious patient's condition. A four-layer architecture is proposed using IoT and Blockchain technologies. Many research works focus on investigating, analyzing, and highlighting the affected individuals through guiding the COVID-19 infection. Eventually, various mobile apps are recognized and addressed in this paper.

The oil produced in the oil fields of the Republic of Kazakhstan contains a high percentage of sulfur. Synthesis and improvement of the properties of catalytic systems for the production of fuels with high octane number and low sulfur content is currently an urgent task for Kazakhstan. In this study, catalytic systems with a new composition based on zeolites with the addition of rare-earth metals (E) and phosphorus (P) have been prepared and tested in the process of the catalytic hydrotreating of straight-run gasoline and gasoline of catalytic cracking. In case of NiO-MoO3-E-P-HZSM-HY-Al2O3 catalyst, the octane rating of the gasoline after hydro-processing was increased to 88-90, which is much higher than for other catalysts. The octane number of straight-run gasoline up to 400°C is a maximum of 90 (Research Method) and 83.7 (Motor Method). At the same time, the sulfur content in the resulting gasoline decreases from 0.0088% to 0.0011%. In the case of catalytic cracking gasoline, the sulfur content is reduced from 0.0134% to 0.0012%. The smallest residual sulfur content in the final product, 0.0005% is revealed in case of catalyst CoO-WO3-E-P-HZSM-HY-Al2O3, and it is 2-4 times lower than for catalysts CoO-MoO3-E-P-HZSM-HY-Al2O3 and NiO-MoO3-E-P-HZSM-HY-Al2O3. These amounts of sulfur residue in raw materials is lower than that required by the Euro-5 Standard. The surface of the prepared catalysts was 211.0-274.0 m2/g, diameter of pores d ≈ 1.5-2.5 nm and d ≈ 7.0 nm. The total pore volume of the catalysts was not higher than 0.28-0.41 ml/g. The catalysts developed in this study can be used for hydrotreating raw materials and producing high-octane gasoline with a low sulfur content, corresponding in its characteristics to the Euro-5 Standard.

Providing patient-centered care to manage chronic pain and opioid use disorder (OUD) is associated with improved health outcomes. However, adopting a holistic approach to providing care is often challenging in rural communities. This study aims to identify and contrast challenges to providing patient-centered care from the perspective of patients and providers. A participatory design approach was adopted to elicit the perceptions of providers and patients with lived experiences of chronic pain and OUD in Jefferson County, Wisconsin. Two focus groups were conducted with each stakeholder group to identify problems that participants face with respect to chronic pain management and OUD and possible solutions. Four interviews were conducted with providers experienced in chronic pain management. Analysis of focus group sessions and interviews show consensus among patients and providers that lack of behavioral health and recovery resources create barriers to effectively manage OUD and chronic pain. However, there was discordance among the two groups about other barriers such as patient and provider attitudes, tapering approach, and access to medications for OUD. This tension among patients and providers can influence patients’ retention in therapy. More efforts are needed to mitigate stigma among providers in rural communities and support psychosocial needs of patients.

Introduction: The proliferation of literature regarding COVID-19 pandemic has served to highlight a wide spectrum of disease manifestations and complications like thrombotic microangiopathies. Our review with a brief case presentation highlights the increasing recognition of TTP in COVID-19 and describes its salient characteristics. Methods: We screened the available literature in Pubmed, EMBASE and Cochrane database from inception till April 2022 of articles mentioning COVID-19 associated TTP in English Language. Results: From 404 records, we included 8 articles mentioning data of 11 patients in our review. TTP was predominantly reported in females (72%) with a mean age of 48.2 years (SD 15.1). Dyspnea was the most common symptom in 1/3rd of patients (36.6%). Neurological symptoms were reported in 27.3% of cases. The time to diagnosis of TTP was 10 days (SD: 5.8) from onset of Covid-19. All 11 cases underwent plasma exchange (PLEX), with a mean of 12 sessions per patient, whereas six cases received Rituximab (54.5%), and three received Caplacizumab (27.3%). One patient died from the illness. Conclusion: This review of available literature highlights the atypical and refractory nature of COVID-19 associated TTP. It required longer sessions of PLEX with half of the patients receiving at least one immunosuppressant.

Research focused on succinate dehydrogenase (SDH) and its substrate, succinate, culminated in the 50’s accompanying the rapid development of research dedicated to bioenergetics and intermediary metabolism. This allowed to uncover the implication of the SDH in both the mitochondrial respiratory chain and the Krebs cycle. Nowadays this theme is experiencing a real revival following the discovery of the role of SDH and succinate in a subset of tumors and cancers in human. The aim of this review is to enlighten the many questions yet unanswered, ranging from fundamental to clinically oriented aspects, up to the danger of the current use of SDH as a target for a sub class of pesticides.

Globally, inequalities in educational provision are prevalent between genders, various geographical regions, and among different socio-economic backgrounds. Consequently, this study set-out to assess the level of disparity among the Federal Regional States of Ethiopia using Gini-coefficient and Lorenz curve from the statistical data of MoE. Moreover, data were collected from 656 respondents found in the sample regions. The result of the Gini-coefficient indicated that disparity in educational provision has been reduced over the past couple of decades both at primary (0.145 to 0.032) and secondary levels (0.277 to 0.126). Emerging regions are by far lagging behind the central and established regions. The sources of variation were mainly the demand-side variables, especially the economic and contextual related issues like drought and conflicts. Therefore, educational policies designed at the central level are advised to consider the strategies to bridge the existing inequalities through equitable provision of the education system to its citizen.

Matrix metalloproteinases (MMPs) are critical enzymes involved in a variety of cellular processes. MMPs are well known for their ability to degrade the extracellular matrix (ECM) and their extracellular role in cell migration. Recently, more research has been conducted on investigating novel subcellular localizations of MMPs and their intracellular roles at the respective locations. In this review article, we focus on the subcellular localization and novel intracellular roles of two MMPs closely related: membrane-type-1 matrix metalloproteinase (MT1-MMP) and matrix metalloproteinase-2 (MMP-2). Although MT1-MMP is commonly known to localize on the cell surface, the protease also localizes to the cytoplasm, caveolae, Golgi, cytoskeleton, centrosome, and nucleus. At these subcellular locations, MT1-MMP functions in cell migration, macrophage metabolism, invadopodia development, spindle formation and genes expression, respectively. Similar to MT1-MMP, MMP-2 localizes to the caveolae, mitochondria, cytoskeleton, nucleus and nucleolus, and functions in calcium regulation, contractile dysfunction, genes expression and ribosomal RNA transcription. Our particular interest lies in the role MMP-2 and MT1-MMP serve within the nucleus, as it may provide critical insights into cancer epigenetics and tumor migration and invasion. We suggest that targeting nuclear MT1-MMP or MMP-2 to reduce or halt cell proliferation and migration may lead to the development of new therapies in cancer and other diseases.

Lipoproteins are important cardiovascular (CV) risk biomarkers. This study aimed to investigate the associations of lipoprotein subclasses with micro- and macrovascular biomarkers to better understand how these subclasses relate to atherosclerotic CV diseases. One hundred fifty-eight serum samples from the EXAMIN AGE study, consisting of healthy individuals and CV risk patients, were analyzed by nuclear magnetic resonance (NMR) spectroscopy to quantify lipoprotein subclasses. Microvascular health was quantified by measuring retinal arteriolar and venular diameters. Macrovascular health was quantified by measuring carotid-to-femoral pulse wave velocity (PWV). Nineteen lipoprotein subclasses showed statistically significant associations with retinal vessel diameters and nine with PWV. These lipoprotein subclasses together explained up to 26% of variation (R²=0.26, F(29,121)=2.80, p<0.001) in micro- and 12% (R²=0.12, F(29,124)=1.70, p=0.025) of variation in macrovascular health. High-density (HDL-C) and low-density lipoprotein cholesterol (LDL-C) as well as triglycerides together explained up to 13% (R²=0.13, F(3,143)=8.42, p<0.001) of micro and 8% (R²=0.08, F(3,145)=5.46, p=0.001) of macrovascular variation. Lipoprotein subclasses seem to reflect micro- and macrovascular end organ damage more precisely as compared to only measuring HDL-C, LDL-C and triglycerides. Further studies are needed to analyse how the additional quantification of lipoprotein subclasses can improve CV risk stratification and CV disease prediction.

We describe an efficient and cost effective data access mechanism for Sentinel-1 TOPS 1 mode bursts. Our data access mechanism enables burst-based data access and processing, thereby 2 eliminating ESA’s Sentinel-1 SLC data packaging conventions as a bottleneck to large scale processing. 3 Pipeline throughput is now determined by available compute resources and efficiency of the analysis 4 algorithms. For targeted infrastructure monitoring studies, we are able to generate coregistered, 5 geocoded stacks of SLCs for any AOI in the world in a few minutes. In addition, we describe our 6 global scale radar backscatter and interferometric products and associated pipeline design decisions 7 that ensure geolocation consistency across the suite of derived products from Sentinel-1 data. Finally, 8 we discuss the benefits and limitations of working with geocoded SAR SLC data.

Background: Emergency medical services (EMS) are the first health care contact for the majority of stroke patients. However, there is a lack of data on the current paramedics’ hospital-directed feedback and training needs across different health care settings. We aimed to evaluate paramedics’ prehospital stroke care knowledge, training needs, and current status of feedback on suspected stroke patients. Methods: We surveyed paramedics from the Vilnius region from September to November 2019, and compared the answers between the city and the district agencies. The questionnaire content included questions on paramedics’ demographic characteristics, prehospital stroke care self-assessment, knowledge on stroke mimics, stroke training needs, and the importance of hospital-directed feedback on suspected stroke patients. Results: A total number of 161 paramedics were surveyed, with more district paramedics rating their prehospital stroke care knowledge as inadequate (44.8% (95% confidence interval (CI) 32.8–57.6) vs 28.1% (95% CI 20.1–27.8), p = 0.028). In addition, more district paramedics indicated a need for additional stroke training (83.1% (95% CI 71.5–90.5) vs 69.8% (60.0–78.1), p = 0.043). However, respondents reported being the most confident while dealing with stroke (71.3%, 95% CI 63.8–77.7) compared to other time-critical conditions (p < 0.001). Vertigo (60.8%, 95% CI 53.0–68.0), brain tumours (56.3%, 95% CI 48.5–63.8), and seizures (54.4%, 95% CI 46.7–62.0) were indicated as the most common stroke mimics. Only 6.2% (95% CI 3.4–11.1) of respondents received formal feedback on the outcome of suspected stroke patients brought to the emergency department. Conclusion: A high proportion of paramedics self-perceive having inadequate stroke knowledge and an urgent need for further stroke training. The EMS staff indicate receiving an insufficient amount of feedback on suspected stroke patients, even though the usefulness is perceived to be paramount.

Lemonomycin (1) was first isolated from the fermentation broth of Streptomyces candidus in 1964. The complete chemical structure was not elucidated until 2000 with extensive spectroscopic analysis. Lemonomycin is currently known as the only glycosylated tetrahydroisoquinoline antibiotic. Its potent antibacterial activity against Staphylococcus aureus and Bacillus subtilis and complex architecture make it an ideal target for total synthesis. In this short review, we summarize the research status of lemonomycin for biological activity, biosynthesis and chemical synthesis. The unique deoxy aminosugar-lemonose was proposed to play a crucial role in biological activity, as shown in other antibiotics, such as arimetamycin A, nocathiacin I, glycothiohexide α, and thiazamycins. Given the self-resistance of the original bacterial host, the integration of biosynthesis and chemical synthesis to pursue efficient synthesis and further derivatization is in high demand for the development of novel antibiotics to combat antibiotic-resistant infections.

Renewable energy technologies (RET) are critical to the sustainable development of modern societies. Hong Kong has set up a RET theme park so as to fulfill the needs of and impart knowledge on RET through entertainment and educational activities. Such understanding aids in formulating appropriate future park designs and neuromarketing strategies to maximize the attractiveness of the park. Therefore, this study attempts to investigate potential visitors’ preferences with regard to cartoon characters in the RET theme park, especially for student groups to meet the “edutainment” theme of the park. A total of 400 people have participated in this study. Findings indicate that Snoopy, Mickey Mouse, and Donald Duck show a high degree of likeness of presence in the RET theme park.

The potential of social networks for the circulation of disinformation as a strategy of diplomacy has been of great interest to the academic community, but the way in which it is propagated and modelled is still in its beginnings. This article aimed to simulate the propagation of disinformation in social networks derived from the diplomacy strategy, based on the elements of the system. For the design of the simulation model, system dynamics was used as the main technique in the research methodology in conjunction with statistical analysis. Five computational simulations were run for the adoption methods of susceptible and uninformed population, misinformation techniques and echo chamber. The developed model found that the diplomacy disinformation agent is able to spread its message efficiently through the bot outreach mechanism and only a part of the susceptible population unsubscribes to the disinformation agent's account. Significant differences were identified in the absence of paid outreach, bots and trolls in the propagation of information, and in the variation in the timing of disinformation propagation. Consequently, the developed model allows the understanding of the problem of disinformation as a strategy of diplomacy from international rather than local dynamics, as well as the effects of the use of each element in the system.

The purpose of this study was to investigate trends in undergraduate enrollment, graduation, and employment in Ethiopia. It looked at data from the past 20 years of enrollment and graduation, as well as the 15 years of unemployment trends. For enrollment, we used the ARIMA(0,1,0) model, for graduation, the Holt-Winter model, and unemployment, the Simple model. Results showed that enrollment rates increased dramatically, but graduation rates remained constant. Besides, enrollment is expected to continue rising, while graduation rates are expected to fall. On the other hand, between 1999 and 2018, the overall unemployment trend declined. Yet, between 2009 and 2018 the unemployment trends stayed stable. According to the findings, for the next ten years, higher education enrollment and graduation will continue. Nevertheless, it is shown the diminishing demand for jobs in the labor market. As part of improving the existing realities of higher education, the study suggests reconsidering job-driven policy formulation, strengthening higher education-labor market alignment, controlling higher education expansion, and sustaining the development qualification systems.

Cynomorium songaricum is an important endangered plant with significant medicinal and edible values. However, the lack of resources and quality variation have limited the comprehensive developments and sustainable utilization of C. songaricum. Here, we evaluated chemical and genetic traits of C. songaricum from the highly suitable habitat regions simulated with species distribution models. The PCA and NJ tree analyses displayed intraspecific variation in C. songaricum, that could be divided into two ecotypes: ecotype I and ecotype II. Furthermore, the LC-MS/MS-based metabolomic was used to identify and analyze the metabolites of two ecotypes. The results indicated that a total of 589 compounds were detected, 236 of which were significantly different between the two ecotypes. Specifically, the relative content and the kind of flavonoids were more abundant in ecotype I, which were closely associated with the medicinal activities. In contrast, amino acids and organic acids were more enriched in ecotype II, which may provide better nutritional quality and unique flavor. In summary, our findings demonstrate the ecotype division and chemical diversity of C. songaricum in China from different geographical regions and provide a reference for the development of germplasm and directed plant breeding of endangered medicinal plants.

The C/N ratio is an extremely important parameter in the composting process, which is directly responsible for the growth of microorganisms. A low C/N ratio contributes to higher emissions of greenhouse gases and odorous substances, such as ammonia (NH3), which is formed by nitrogen mineralization. Due to the highly toxic effects of ammonia, it is a particularly unwanted by-product that can disrupt the composting process because it poisons microorganisms and cause environmental issues. The activity of anammox bacteria, so far analyzed only in wastewater treatment processes, is a particularly efficient method of nitrogen removal, having an advantage over the conventional methods used previously. Our study proofs the presence of anammox bacteria during composting, what gives an opportunity to improve the process and reduce its impact on atmospheric pollution. Despite the aerobic nature of this process, the composted mass of waste presents conditions conducive to the development of these ammonia oxidizing bacteria, as well as other strains of microorganisms cooperating with them. This makes it possible to compost at a low C/N ratio; in addition, there is no need for additional energy supply through aeration, as the processes carried out by anammox bacteria do not require oxygen.

Cigarette smoking and air pollution (particulate matter) are recognized as two major etiological factors for lung cancer. Of all the risk factors, cigarette smoking is significantly associated with lung carcinogenesis. The main mechanism lies in the metabolically activated carcinogens (majorly polycyclic aromatic hydrocarbons and nitrosamines), which could covalently bind with DNA molecules and lead to irreversible mutations in pivotal cancer genes, such as TP53 and KRAS. Another major etiological factor for lung cancer is air pollution, which is with complex compositions and ubiquitous in daily life, especially in developing countries as China and India. The latest literatures on lung cancer epidemiology and etiology have been briefly summarized and reviewed in this work.

The analysis of data produced by the MV20/20 sensor, tagged with quality outcomes, is presented with the aim of developing a predictor model for real-time anomaly detection and classification. Three types of inclusions, undesired particles that deteriorate the quality of production, are used to tag the quality data using results from the lab. We explore both unsupervised and supervised learning, which both offer advantages in monitoring and controlling the quality of production. It is discovered that the dataset can be clustered using techniques like K-Means and DBSCAN. Bounding the data within a 95% confidence interval ellipse ensures we can detect anomalous events in real time. For supervised learning, a two-stage classifier is explored, which classifies the outcome of a cast and secondly the inclusion responsible for the negative outcome. We explore models from logistic regression and support vector machines, to two neural networks, namely the multi-layer perceptron and the radial basis function network. While the cast outcome is adequately predicted by all the models, the multi-layer perceptron provides a boundary performance for the inclusion type. A more advanced technique for model optimisation, namely grid search, is applied in order to improve on the results. The outcome for the grid search is not much better, which indicates a global maximum in the learning capacity of the model. Recommendations include the addition of sensor systems and an audit of data collection variation.

Scientific theories on the functioning and dysfunction of the human brain require a good understanding of both its development — before and after birth, and through maturation to adulthood — and its evolution from the ancestral primate brain. Adopting a complex-systems approach, here we propose that the apparent uniqueness of humans’ cognitive capacities might best be understood as emerging from multiple nested “virtuous cycles.” In particular, we propose that the intimate link that exists between oxygen metabolic loops, cortical expansion, and ultimately cognitive and social demands is a key driver of genetic developmental programs for the human brain. Overall, our proposed evolutionary model makes explicit mechanistic links between metabolism, molecular and cellular brain heterogeneity, and behaviour that may in time provide a clearer understanding of brain developmental trajectories and their disorders.

African swine fever (ASF) is a notifiable viral disease of domestic and wild suids. Despite intensive re-search efforts, the pathogenesis of the disease is still far from being understood. Analysis of biomarkers in different body fluids may supplement traditional pathogenesis studies. As reliable protocols are often es-tablished in laboratories with lower biosafety, reliable inactivation of samples is crucial. The objective of this study was to find a procedure that inactivates the virus while preserving the biomarkers for down-stream analyses. To this means, three different inactivation protocols were employed, namely Tergitol-type NP-40 (NP-40) and polyoxyethylene-p-t-octylphenol (Triton X-100), respectively, and one with 95 °C heating. It could be demonstrated that all samples treated with 0.5% (v/v) concentration of both deter-gents showed absence of virus infectivity. The same was true for heated samples. However, heated serum was not suitable for analyses. Next, the treatment impact on biomarker readouts was assessed. While all protocols had an impact on the detection of biomarkers, correlation was retained. Especially NP-40 could be the desired detergent for more accurate measurements while achieving efficient virus inactivation. Based on these studies, samples can be reliably inactivated for most biomarker analyses and thus broader interdisciplinary cooperation is possible.

The study of a flexible body immersed in a flowing medium is one of best way to find its aerodynamic shape. This Letter revisited the problem first studied by Alben, Shelley and Zhang (Nature 420, 479-481, 2002). The aerodynamic shape of the fibre is found by simpler approach and universal drag scaling laws of the flexible fibre in flowing medium are proposed by using dimensional analysis. The Alben scaling laws is being generalized and confirmed to be universal. Our study show that the Alben number is a measurement of maximum curvature of the fibre forced by dynamic pressure. A complete Maple code is provided for finding aerodynamic shape of the fibre in the flowing medium.

The manufacturing parameters influence the properties of thermo-mechanically processed met-als such as Mg alloys. This paper presents how the mechanical properties, the microstructure and the degradation rate of extruded Mn-containing Mg-Gd-alloys can be modified. Gd as repre-sented REE-element is particularly interesting due to the influence on the texture development in Mg and therefore studied as a base alloy system. The contents of Gd were investigated be-tween 2 to 9 wt.% with Mn-addition of 0.5 and 1.0 wt.%. The grain sizes and the corresponding textures were modified by the extrusion parameters and the alloy content. It was shown that modification by Mn can decrease the grain size, but increase the degree of recrystallization and decrease the degradation rate in the biological medium compared to the binary Mg-Gd system from previous studies. The results suggest that the binary Mg-Gd system can be produced more efficiently by adding Mn and that the resulting properties are more robust.

Background: In long-term care facilities, there are many residents who do not have the ability to seek shelter by themselves in the case of an emergency. Thus, it is extremely important that the staff of nursing homes are equipped with correct disaster prevention concepts, emergency survival responses, and hazard mitigation measures. Purpose: Discuss the intervention effectiveness of different fire prevention and emergency response trainings at nursing homes and the relationship and predictivity of awareness to self-efficacy. Method: Recruit staff from two nursing homes through purposive sampling, using a two-team pre-and post-test design to collect results from 41 individuals in the experiment group and 40 individuals in the control group. The research tool is the “Nursing Home Fire Prevention and Emergency Response Awareness and Self-Efficacy Scale,” to compare the effectiveness of advanced and general fire safety trainings. Result: After receiving improved advanced fire safety training, the total score and the result of the experiment group on fire prevention and emergency response awareness and self-efficacy had both performed better than the control group who received general fire safety training (p < .001); fire prevention and emergency response awareness has significant and positive correlation with self-efficacy (r=.601, p < .001), and awareness is a significant predictor variable to self-efficacy (p < .001). Conclusion/Practical Application: This study finds that the key to improving learning effectiveness includes adding fire science concept chapter when creating fire safety training material in order to strengthen basic awareness; fire safety training should comprehensively introduce all related duty responsibilities of staff fire defense formation, in turn enabling mutual responsive support for the needs of the site; also, to become familiarized with the knowledge requires appropriate frequency of training and enhancing the staff’s awareness to fire prevention and emergency response, which is the most important key of learning effectiveness.

Pandemic scenario has significantly changed several factors of life, including teaching, and learning at university. The development of suitable teaching materials to support university studies is mandatory to overcome distance learning difficulties and improve traditional teaching methodologies. This work explains a novel method for the preparation of teaching materials for medical sciences, but also plausible for other learning fields. An encephalon was extracted and prepared by using this methodology for teaching purposes. More than 200 students evaluated several factors of the material prepared this way, indicating a better understanding (up to 80%) of theoretical contents related to this human section, together with a high usability and good physical appearance

We explore the importance of curvature in carbonaceaous species transformation and stability, using laser-induced vaporisation to evaporate and ionise a source of curved polyaromatic hydrocarbons: carbon nanobelts. Collision impacts between species cause mass loss and the resultant ions are catalogued via mass-spectrometry. To interpret the mass spectra, we perform a series of “in-silico” simulated systematic hydrogen-loss studies using density functional theory (DFT) modelling, sequentially removing hydrogen atoms using thermodynamic stability as a selection for subsequent dehydrogenation. In an initial sequence of H2 removal, the rings are maintained through stable carbyne chain and pentagon-chain formation, giving rise to circular strained dehydrobenzoannulene species. The chains subsequently break, releasing CH and C2. While theoretical closed-cage routes are identified, they are not observed experimentally. The results can serve as a useful guide to high-energy impact conditions observed in some astrochemical environments.

Introduction: Established predictors for COVID-19 related mortalities are diverse, with cytokine release syndrome (CRS), a key intermediator to the case fatalities being dominant and multi-faceted. The impact of these several risk factors on coronavirus mortality have been previously reported in several meta‐analyses limited by small sample sizes and premature data, and CRS not fully being accounted for. The objective of this systematic review and meta-analysis was to evaluate the evidence on the risk of COVID-19 related CRS and mortality with HIV serostatus using published data, and a meta-regression to account for possible covariates. Method: Electronic databases including Google Scholar, Cochrane Library, Web of Sciences (WOS), EMBASE, Medline/PubMed, COVID-19 Research Database, and Scopus, were systematically searched till 30th February, 2022. All human studies were included irrespective of publication date or region. Twenty-two studies with a total of 19,783,097 patients detailing COVID-related mortality and eleven with a total of 2,005,274 were included. To pool the estimate, a random-effects model with risk ration as the effect measure was used. Moreover, publication bias and sensitivity analysis were evaluated followed by meta-regression. The trial was registered (CRD42021264761) on the PROSPERO register. Results: The findings were consistent in stating the contribution of HIV infection for COVID-19 related CRS and mortality. The cumulative COVID-19 related mortality and CRS was 110270 (0.6%) and 48863 (2.4%) with total events of 2010 (3.6%), 108260 (0.5%) and 837(4.6%), 48026 (2.4%) among HIV-positive and negative persons respectively. HIV infection showed an increased risk of COVID-19 related CRS and mortality [RR= 1.48, 95% CI (1.16, 1.88) (P=0.002)] and [RR =1.19, 95% CI (1.02 -1.39) (P=0.00001)] respectively, both with substantial heterogeneity (I² > 80%). The true effects size in 95% of all the comparable populations fell between 0.64 to 2.22 and 0.67 to 3.29 for mortality and CRS respectively. MC studies and COVID-19 mortality with HIV infection showed a significant association [RR = 1.305, 95% CI (1.092 -1.559) (P = 0.003)], similar to studies conducted in America (RR = 1.422, 95% CI 1.233–1.639) and South Africa (RR = 1.123, 95% CI 1.052–1.198). HIV infection showed a risk for ICU admission [(P=0.00001) (I² = 0%)] and mechanical ventilation [(P=0.04) (I² = 0%)] as parameters of CRS. Furthermore, risk of COVID-19 related CRS is influenced by the year a study was conducted (R² = 0.55) and the region (R² = 0.11) same for mortality (R² = 0.60). The variance proportion explained by covariates was significant for CRS (I² = 86.5%, Q = 73.99, df = 10, P = 0.0000) (R² = 0.78) and mortality (I² = 87.5%, Q = 168.02, df = 21, p = 0.0000) (R² = 0.67). Conclusion: Our updated meta-analysis indicated that HIV infection was significantly associated with an increased risk for both COVID-19 – CRS and mortality, which might be modulated by regions, study setting and year. Risk for ICU admission and mechanical ventilation are the key indicators of CRS. We believe the updated data further anchoring CRS will contribute to more substantiation of the findings reported by similar earlier studies (Dong et al., 2021; K. W. Lee et al., 2021; Massarvva, 2021; Mellor et al., 2021; Ssentongo et al., 2021)

Hippocampus plays a crucial role in spatial and episodic memory. The acquisition of new memories is impossible without participation of the hippocampus. There are two main functional states or “modes” of the hippocampal activity, theta and non-theta state. They have different behavioral correlates and clearly different spectral content of the LFPs and neuronal spiking. Hippocampal theta state is present under active exploratory behavior, locomotion, cognitive situations requiring attention and REM sleep. Slow-wave sleep and quiet wakefulness (immobility, eating, grooming) represent the non-theta hippocampal state. The nodal point for the regulation of hippocampal activity is the MS. The activation or suppression of different types of MS cells appears to be responsible for controlling hippocampal theta and non-theta states. Functional coupling between MS neurons and hippocampal interneurons varies in a state-dependent manner.

The service conditions of underground coal mine equipment are poor, and it is difficult to accurately extract the fault characteristics of rolling bearings. In order to better improve the accuracy of fault identification of rolling bearings, a fault detection method based on multiscale permutation entropy and SOA-SVM is proposed. First, the whale optimization algorithm is used to select the modal analysis number K and the penalty factor α of the variational mode decomposition algorithm. Then, the vibration signal of rolling bearings is dissolved according to the optimized variational mode decomposition algorithm, and the multi-scale permutation entropy of the main intrinsic mode function is calculated. Finally, the feature values of the matrix are entered into the SVM algorithm optimized by the seagull optimization algorithm to obtain the classification result. The experimental results based on the published rolling bearing datasets of Western Reserve University show that the identification success rate of the proposed method can reach 98.75%. The fault detection of the rolling bearings can be completed accurately and efficiently.

The choice of holiday destinations is highly depended on climate considerations. Nowadays, since the effects of climate crisis are being increasingly felt, the need of accurate weather and climate services for hotels is crucial. Such a service could be beneficial for both the future planning of tourists’ activities and destinations and for hotel managers as it could help in decision making about the planning and expansion of the touristic season, due to a prediction of higher temperatures for a longer time span, thus causing increased revenue for companies in the local touristic sector. The aim of this work is to calculate predictions on climatic variables using statistical techniques as well as Artificial Intelligence (AI) for a specific area of interest utilising data from in situ meteorological station, and produce valuable and reliable localised predictions with the most cost-effective method possible. This investigation will answer the question of the most suitable prediction method for time series data from a single meteorological station that is deployed in a specific location. As a result, an accurate representation of the microclimate in a specific are is achieved. To achieve this high accuracy in situ measurements and prediction techniques are used. As prediction techniques, Seasonal Auto Regressive Integrated Moving Average (SARIMA), AI techniques like the Long-Short-Term-Memory (LSTM) Neural Network and hybrid combinations of the two are used. Variables of interest are divided in the easier to predict temperature and humidity that are more periodic and less chaotic, and the wind speed as an example of a more stochastic variable with no known seasonality and patterns. Our results show that the examined Hybrid methodology performs the best at temperature and wind speed forecasts, closely followed by the SARIMA whereas LSTM perform better overall at the humidity forecast, even after the correction of the Hybrid to the SARIMA model.

Objective: To investigate postacute laryngeal injuries and dysfunctions (PLID) in coronavirus disease 2019 (COVID-19) patients. Methods: Three independent investigators performed a systematic review of the current literature studying PLID in patients with a history of COVID-19. The review was performed according to PRISMA Statement. Epidemiological, clinical, hospitalization features, laryngeal diseases and voice outcomes were extracted from the included papers. Results: Eight papers met our inclusion criteria (393 patients) corresponding to 5 uncontrolled prospective and 3 retrospective studies. The most prevalent PLID were vocal fold dysmotility (65%), vocal fold edema (35%), laryngopharyngeal reflux (21%), and muscle tension dysphonia (21%). Posterior glottic stenosis (12%), granuloma (14%), and posterior glottic diastasis (12%) were the most common injuries. Most patients with PLID were obese and had a history of intensive care unit hospitalization, and orotracheal intubation. The delay between the discharge and the laryngology office consultation ranged from 51 to 122 days. The mean duration of intubation ranged from 10 to 34 days. Seventy-eight (49%) intubated patients were in prone position. The proportion of patients requiring surgical treatment ranged from 39% to 70% (mean=48%). There was an important heterogeneity between studies about inclusion, exclusion criteria and outcomes. Conclusion: COVID-19 appeared to be associated with PLID, especially in patients with a history of intubation. However, future controlled studies are needed to evaluate if intubated COVID-19 patients reported more frequently PLID than patients who were intubated for other conditions.

Objectives: As institutions modified medical practices to mitigate the spread of the SARS-CoV-2 virus, providers were forced to modify care through the implementation of telemedicine. The objective of this article is to review the current practices of otolaryngology during the COVID-19 pandemic and the limitations of telemedicine in current practice. Methods: A thorough review of the PubMed and MEDLINE databases was performed for publications between 2020 and 2021. Studies discussing telemedicine in otolaryngology during COVID-19 pandemic were selected. Results: As worldwide cases of COVID-19 continue to oscillate, we must continue to be vigilant in our clinical practice, implementing safe techniques to mitigate the spread of the SARS-CoV-2 virus through the continual use of telemedicine in all specialties of otolaryngology. Trends of increased patient acceptance of the use of telemedicine have been seen across subspecialities, including otolaryngology. Conclusion: Currently there are challenges associated with the implementation of telemedicine in the field of otolaryngology that rely heavily on adjunct physical examination, imaging studies, and specialty procedures. However, telemedicine has tremendous potential and can be adapted to include in the otolaryngologist’s toolbelt during public health emergencies such as the COVID-19 pandemic.

Burrowing crabs are considered to be the ecosystem engineers in mangrove ecosystems because they have impact on the ecosystem functioning through bio-geochemical transformations. This process depends on the size and shape of burrows. The present study analysed architecture of burrows, constructed by crabs in a restored mangrove habitat. Fourteen crab species were found to construct the burrows of 13 different shapes with predominance of ‘I’,’J’,’L’. The burrow shape was diverse in Metopograpsus messor, followed by Austruca occidentalis, Gelasimus vocans, and A. annulipes. The burrow structural complexity was higher during summer in Avicennia or open zone. Sesarmids were larger in size than fiddlers, making the burrows of wider opening. Fiddlers were relatively smaller in size and they constructed complex burrows at vertical position, making longer and deeper burrows, in contrast to sesarmids, which formed simple burrows at horizontal position, digging shorter and shallower burrows. The sesarmids have smaller burrows without branching in mangrove zones, whereas the fiddler crabs (except Austruca variegata) have larger burrows with or without branching in open and Avicennia zones. The fiddler crabs especially Austruca occidentalis and A.annulipes have separate openings and passage for exit and entry as an adaptation against predators. The present work identified Austruca occidentalis and A. annulipes as the most potent bio-turbating crab species for restored mangrove habitats due to their efficiency in soil excavation and large sized burrows.

The purpose of this study was to investigate the changes in anterior knee laxity (AKL), stiffness, general joint laxity (GJL), and genu recurvatum (GR) during the menstrual cycle in female non-athletes and female athletes with normal and irregular menstrual cycles. Participants were 19 female non-athletes (eumenorrhea, n=11; oligomenorrhea, n=8) and 15 female athletes (eumenorrhea, n=8; oligomenorrhea, n=7). AKL was measured as the amount of anterior tibial displacement at 67 N - 133 N. Stiffness was calculated as change in (Δ)force/Δ anterior displacement. The Beighton method was used to evaluate the GJL. The GR was measured as the maximum angle of passive knee joint extension. AKL, stiffness, GJL, and GR were measured twice in four phases during the menstrual cycle. Stiffness was significantly higher in oligomenorrhea groups than in eumenorrhea groups, although no significant differences between menstrual cycle phases were evident in female non-athletes. GR was significantly higher in the late follicular, ovulation, and luteal phases than in the early follicular phase, although no significant differences between groups were seen in female athletes. Estradiol may affect the stiffness of the periarticular muscles in the knee, suggesting that GR in female athletes may change during the menstrual cycle.

This article presents new PEM fuel cell models with hexagonal and pentagonal designs. After observing cell performance improvement in these models, we optimized them. Inlet pressure and temperature were used as input parameters, and consumption and output power were the target parameters of the multi-objective optimization algorithm. Then we used artificial intelligence techniques, including deep neural networks and polynomial regression, to model the data. Next, we employed the RSM (Response Surface Method) method to derive the target functions. Furthermore, we applied the NSGA-II multi-objective genetic algorithm to optimize the targets. Compared to the base model (Cubic), the optimized Pentagonal and Hexagonal models averagely increase the output current density by 21.819\% and 39.931\%, respectively.

Memristors were proposed in the early ’70s of the XXth century by Leon Chua as a new electrical element linking the charge and the flux. Since that first introduction, these devices have positioned themselves to be considered as possibly fundamental for the new generations of electronic devices. It has to be mentioned that actual memristors have only been recognized to exist as physical elements. In this paper, we apply a modeling framework to generate a model describing experimental measurements performed on a ReRAM. We show how to apply the Dynamic Route Map technique in the general case to obtain an approximation to the differential equation that determines the behaviour of the device.

This article aims to create the nexus between sustainable development and the quality of the political regime. The current social and political context is characterized by a series of crises generated by COVID-19 pandemic, economic imbalances and regional conflicts. In this context, sustainable development is affected by the economic dynamics and the “democratic recession”. The study aims to respond to the following research questions: “how could influence the quality of the democracy the dynamics of the Sustainable Development Goals (SDGs 17)?” and “what are the premises for sustainable development in the new political context, characterized by democratic recession?” The purpose of the study is to underline the fact that democratic regimes are inclined to create both participative and deliberative frames for achieving the SDGs in accordance with UN 2030 Agenda. The research methodology used in this study is based on descriptive and inferential statistics. The research data are collected from secondary sources in the years between 2015 and 2021, from 193 countries covering all the geographical areas. The empirical results suggest two models of development: the Asian model of sustainable development characterized by economic growth and the Western democratic model based on democratic institutions, fair justice and mechanisms for preserving peace. We noticed that the key-variables for explaining the dynamics of sustainability in correlation with democratic index are represented by the functioning of the governments and the political participation. Through civic engagement and political ac-countability, democracy could be seen as a pre-requisite for achieving an optimal level of the SDGs. All these empirical results could prove valuable for the scholars interested in the relation between democracy and sustainability and for the political decision makers involved in shaping strategies for social, economic and environmental development.

Fever and rash as manifestations of infection by microorganisms are collectively known as febrile exanthem. Viruses are more frequently associated with febrile exanthema, and often these symptoms are thus impetuously termed viral exanthem. However, bacteria represent a frequently overlooked infectious etiology causing rash in humans. In addition, certain microbes may exhibit pathognomonic features that erupt during illness and facilitate clinical diagnosis. Conversely, coinfections often obscure the clinical characteristics of the primary disease and further challenge clinicians attempting to reach a diagnosis. We retrospectively looked at de-identified clinical data of a patient who presented to the Hospital for Tropical Diseases in Bangkok in July 2019 with complaints of fever and rash. The case involved a 35-year-old who presented with a 3-day history of fever, respiratory symptoms, myalgia, conjunctivitis, diarrhea, and a generalized maculopapular rash. On examination, the patient was febrile, tachycardic, and tachypneic, with a mean arterial pressure of 95 mmHg. A differential white blood cell count showed: leukocytes, 5800/µL; neutrophils, 4408/µL; lymphocytes, 406/µL; and platelets, 155,000/µL. Striking findings involving the integumentary system included Koplik’s spots and generalized maculopapular rash. Further serology revealed positive immunoglobulin (Ig)M and IgG for both measles and rubella virus, including reactive serology for Treponema pallidum. Here we describe the clinical course and management of this patient.

This review summarises the main numerical models of fuel droplet heating and evaporation (DHE) in combustion engines across the different scales by accessing the nano/micro, meso and macroscopic fluid elements. The phenomena of multi-physics, multi-scale and multi-phase fluid flow and heat transfer are fully investigated when the fuel droplet (dodecane) is heating and evaporated into a background gas (nitrogen) crossing the liquid-vapour (LV) interface, kinetic region (i.e., Knudsen layer) and the bulk regions of liquid and gas in terms of molecular dynamics (MD) simulations, kinetic theory modelling (i.e., direct numerical solutions of Boltzmann equations) and convectional fluid dynamics approach, respectively. The evaporation coefficient of fuel evaporating molecules and their velocity distributions at the LV interface derived from MD simulations formulate a new kinetic boundary condition (KBC). Moreover, a novel kinetic model considering the inelastic collision between fuel molecules alongside the new KBC enables us to describe the non-equilibrium gas dynamics of fuel vapour and gas mixture in Knudsen layer (KL). Heat and mass flux analysis of the fuel droplet under combustion engine conditions can be accurately assessed by implementing the inelastic collision between fuel molecules in KL and a temperature-dependent evaporation coefficient at the LV interface into DHE. The surface temperature of fuel droplet and its evaporation time, which play a significant role in resolving the ignition delay and hence the combustion phasing in engines, can also be well estimated. The multi-scale modelling of fuel DHE will make significantly potential input into the cleaner engine targeting the low-carbon emissions and enhance the capability of the existing computational fluid dynamics (CFD) solvers.

In this paper, we present a framework that automatically labels Latent Dirichlet Allocation (LDA) generated topics using sentiment and aspect terms from COVID-19 tweets to help the end-users by minimizing the cognitive overhead of identifying key topics labels. Social media platforms especially Twitter are considered as one of the most influential sources of information for providing public opinion related to a critical situation like the COVID-19 pandemic. LDA is a popular topic modelling algorithm that extracts hidden themes of documents without assigning a specific label. Thus automatic labelling of LDA-generated topics from COVID-19 tweets is a great challenge instead of following the manual labelling approach to get an overview of wider public opinion. To overcome this problem, in this paper, we propose a framework named \texttt{SATLabel} that effectively identifies significant topic labels using \textit{top unigrams features of sentiment terms and aspect terms clusters from LDA generated topics} of COVID-19 related tweets to uncover various issues related to the COVID-19 pandemic. The experimental results show that our methodology is more effective, simpler, and traces better topic labels compare to the manual topic labelling approach.

During the 90 days following hospitalization for acute heart failure, ejection fraction and type of discharge medications have been shown in clinical trials to have little effect on mortality. We examined the recent literature addressing brain-related etiologies of sudden death following heart failure. Two mechanisms of sudden unexpected death have been suggested to possibly result from 4 significant influences on pathophysiology in the brain. The two causes of death are severe cardiac arrhythmia, and neurogenic pulmonary edema. They are both mediated through the brainstem autonomic nuclei generally, and executed specifically through the dorsal motor nucleus of the vagus nerve. The four significant influences on pathophysiology in the brainstem autonomic nuclei are: 1) Hyper-stimulation of neurons in the solitary tract nucleus, increasing their metabolic requirements; 2) Inadequate blood flow at a vascular watershed terminus; 3) Additionally decreased blood flow following vasoconstriction related to relative hyperventilation and decreased pCO2 levels; 4) Gravitational ischemia in the brain—caused by the weight of the brain mass sitting above the brainstem. Changes in head tilt release gravitational ischemia in the brain. There is no specific head position (relative to gravity) that is considered favorable or unfavorable for an extended period of time (i.e. more than 24 hours). Even a small degree of head elevation, used in managing pulmonary congestion, may increase gravitational ischemia in the posterior fossa and brainstem. In this paper we suggest a new and important research avenue for intervening in cardiac arrhythmias, and preventing their occurrence, through the non-invasive use of head-tilting, and other head repositioning maneuvers. This could potentially help many geriatric patients with heart failure, who have decreased mobility in bed, and who tend to stay in one position longer, thereby increasing gravitational ischemia in the brain.

We examine a family of nonlinear q-difference-differential Cauchy problems obtained as a coupling of linear Cauchy problems containing dilation q-difference operators, recently investigated by the author, and quasi-linear Kowalevski type problems that involve contraction q-difference operators. We build up local holomorphic solutions to these problems. Two aspects of these solutions are explored. One facet deals with asymptotic expansions in the complex time variable for which a mixed type Gevrey and q-Gevrey structure is exhibited. The other feature concerns the problem of confluence of these solutions as q tends to 1.

The history of saline nasal irrigation (SNI) is indeed a long one, beginning from the ancient Ayurvedic practices and starting to gain a foothold in the west at the beginning of 20th century. Today, there is a growing number of papers covering effects of SNI from in vitro studies to randomized clinical trials and literature overviews. Based on the recommendations of most of the European and American professional associations, seawater, alone or in combination with other preparations, has its place in treatment of numerous conditions of the upper respiratory tract (URT), primarily in chronic (rhino)sinusitis, allergic rhinitis, acute URT infections and postoperative recovery. Additionally, taking into account its multiple mechanisms of action and mounting evidence from recent studies, locally applied seawater preparations may have an important role in prevention of viral and bacterial infections of the URT. Therefore, in this review we discuss results published in the past years focused on the seawater preparations and their use in clinical and everyday conditions, since such products are superior to saline, have an excellent safety profile and are recommended by most professional associations in the field of otorhinolaryngology.

Shell-like, double curved and thus above-average performance structures, are usually produced monolithically on site. For industrial advancement, however, they must be divided into transportable modules which can be assembled on the construction site (design for assembly). Models are lattice shells made of steel and glass, in which predominantly flat sub-surfaces (modules) are used. Therefore, the main question is: Which modularizations are suitable for flow production with mineral building materials? In this paper designed free-form surface is going to be discretized as PQ circular mesh system, suitable modules for 3D concrete printing. Moreover, the multi-criteria optimization is done with Response Surface Methodology (RSM) in order to get optimal final shape. The goal is to start from the arbitrary shape, that can be generated from two curves, with possible two-way division into modules and compare it with the resulted discretized PQ circular mesh system, realized with new algorithm. The comparison can be defined through two main criteria: geometrical and structural.

The cytosolic PNGase (peptide:N-glycanase; Png1 in yeast; NGLY1/Ngly1 in human/mice), also known as peptide-N4-(N-acetyl-beta-glucosaminyl)-asparagine ami-dase, is a well-conserved deglycosylation enzyme (EC 3.5.1.52) which catalyzes the non-lysosomal hydrolysis of an N(4)-(acetyl-β-D-glucosaminyl) asparagine residue into N-acetyl-β-D-glucosaminylamine and a peptide containing an aspartate residue. This enzyme (NGLY1) plays essential roles in clearance of misfolded or unassembled gly-coproteins through a process named ER-associated degradation (ERAD). Accumulating evidence also points out that NGLY1 deficiency can cause an autosomal recessive hu-man genetic disorder associated with abnormal development and congenital disorder of deglycosylation. In addition, the loss of NGLY1 can affect multiple cellular pathways, including but not limited to NFE2L1 pathway, Creb1/Atf1-AQP pathway, BMP path-way, AMPK pathway, and SLC12A2 ion transporter, which might be the underlying reasons for a constellation of clinical phenotypes of NGLY1 deficiency. The current comprehensive review indeed uncovers the detailed NGLY1’s structure and its im-portant roles for participation in ERAD, involvement in CDDG and potential treatment for NGLY1 deficiency.

Therapeutic patient education (TPE) aims to empower the patients and their caregivers to effectively care for and manage their conditions. Such educational programs have been shown to improve health behaviors, disease outcomes and quality of life among different patient populations. The field of TPE has evolved extensively over decades, owing to interdisciplinary research. No study so far has been done to map this field, to identify the stakeholders and gaps requiring future research. By leveraging the theory of co-citation, Citespace was used to visualize the bibliographic data pertaining to TPE research. A total of 54,533 articles published in English language were analyzed to identify influential funders, regions and institutes contributing to this field. Besides these, important theoretical and empirical work that has shaped this field has also been mapped. Our analysis revealed several important insights. Most of the important theories which helped shape TPE were inspired from the social sciences. Five important themes of research were identified including disorders, study designs utilized in TPE research, scope of the TPE literature, and outcomes, and populations. The research focused on improving perceptions, behaviors, and attitudes for health promotion, reducing stigma as well as self-management and medication adherence. Most of the research was developed in the context of high income countries. The future research should more involve patients and use digital technology. Meta-analytical studies need to be done to identify the specificities of TPE interventions across different disorders. More research should involve low and middle income countries (LMIC) to ensure knowledge and technology transfer.

Alzheimer’s disease is the most common neurodegenerative disease and affects persons of all races, ethnic groups, and sexes. The disease is characterized by neuronal loss leading to cognitive decline and memory loss. There is no cure and the effectiveness of existing treatments is limited and depends on the time of diagnosis. The long prodromal period, during which patients’ ability to live a normal life is not affected despite neuronal loss, often leads to a delayed diagnosis because it can be mistaken for normal aging of the brain. In order to make a substantial impact on AD patients, early diagnosis may provide a greater therapeutic window for future therapies to slow AD-associated neurodegeneration. Current gold standards for disease detection include magnetic resonance imaging and positron emission tomography scans, which visualize amyloid β and phosphorylated tau depositions and aggregates. Liquid biopsies, already an active field of research in precision oncology, are hypothesized to provide early disease detection through minimally or non-invasive sample collection techniques. Liquid biopsies in Alzheimer’s disease have been studied in cerebrospinal fluid, blood, ocular, oral, and olfactory fluids. However, most of the focus has been on blood and cerebrospinal fluid due to biomarker specificity and sensitivity attributed to the effects of the blood-brain barrier and inter-laboratory variation during sample collection. Many studies have identified amyloid β and phosphorylated tau levels as putative biomarkers, however, advances in next-generation sequencing-based liquid biopsy methods have led to significant interest in identifying nucleic acids species associated with Alzheimer’s disease from liquid tissues. Differences in cell-free RNAs and DNAs have been described as potential biomarkers for AD and hold the potential to affect disease diagnosis, treatment, and future research avenues.

Eating disorders (EDs) are serious, life-threatening psychiatric conditions associated with physical and psychosocial impairments, as well as high morbidity and mortality. Given the chronic refractory nature of EDs and the paucity of evidence-based treatments, there is a pressing need to identify novel approaches for this population. The noncompetitive N-methyl-D-aspartate receptor (NMDAr) antagonist, ketamine, has recently been approved for treatment-resistant depression, exerting rapid and robust antidepressant effects. It is now being investigated for several new indications, including obsessive-compulsive, post-traumatic, and substance use disorder; and shows transdiagnostic potential for EDs, particularly among clinical non-responders. As such, the aim of this review is to examine contemporary findings on the treatment of EDs with ketamine, whether used as a primary, adjunctive, or combination psychopharmacotherapy. Avenues for future research are also discussed. Overall, results are encouraging and point to therapeutic value, yet are limited to case series and reports on anorexia nervosa. Further empirical work is thus needed to explore ketamine efficacy across ED subgroups; establish safety profiles and optimize dosing; and develop theory-driven, targeted treatment strategies at the individual patient level.

The model organism Drosophila melanogaster has become a focal system for investigations of rapidly evolving genital morphology as well as the development and functions of insect reproductive structures. To follow up on a previous paper outlining unifying terminology for the structures of the male terminalia in this species, we offer here a detailed description of the female terminalia of D. melanogaster. Informative diagrams and micrographs are presented to provide a comprehensive overview of the external and internal reproductive structures of females. We propose a collection of terms and definitions to standardize the terminology associated with the female terminalia in D. melanogaster and we provide a correspondence table with the terms previously used. Unifying terminology for both males and females in this species will help to facilitate communication between various disciplines, as well as aid in synthesizing research across publications within a discipline that has historically focused principally on male features. Our efforts to refine and standardize the terminology should expand the utility of this important model system for addressing questions related to the development and evolution of animal genitalia, and morphology in general.

Current lines of research into mood disorders indicate that immune mediators participating in the pathophysiology of chronic somatic disorders have potent influences on brain functions, even when these mediators are produced in peripheral tissues. Elevated levels of circulating immune molecules have been consistently associated with depressive symptoms in a number of clinical populations and experimental models, to the extent that major depressive disorder (MDD) is now seen, at least in part, as a disorder of immunity. This paradigm has brought to the fore the use of anti-inflammatory therapies as adjunctive to standard antidepressant therapy with the hope to improve treatment efficacy, particularly in those cohorts that do not respond well to standard medication. Such new practice requires the availability of biomarkers to tailor these new therapies to those most likely to benefit but also clear mechanisms of action describing the interaction between peripheral immunity and brain function. These mechanisms are generally studied in preclinical models that try to recapitulate the human disease through peripherally induced sickness behaviour as the model for immune-induced MDD. After an appraisal of the data in rodent models and their adherence to the data in clinical cohorts, we propose a modified model of periphery-brain interaction that goes beyond the currently established view of interaction between peripheral cytokines and microglia cells as the driver of depression. Instead, we suggest that brain barriers are primary actors in the communication between body and brain and, as a consequence, in the pathophysiology of the disease. This model suggests novel biomarkers, novel targets for therapies as well as a novel mechanism for resistance to standard treatments.

Polymer adhesives have emerged as a promising dielectric passivation layer in hybrid bonding for 3D integration while they raise misalignment problems during curing. In this work, the synergistic effect of oxygen plasma surface activation and wetting is utilized to achieve bonding between completed cured polyimides. The optimized process achieves a void-less bonding with a maximum shear strength of 35.3 MPa at a low temperature of 250 °C in merely 2 min, significantly shortening the bonding period and decreasing thermal stress. It is found that the plasma activation generated hydrophilic groups on the polyimide surface, and the wetting process further introduced more -OH groups and water molecular on the activated polyimide surface. The synergistic process of plasma activation and wetting facilitate bridging polyimide interfaces to achieve bonding, providing an alternative path for adhesive bonding in 3D integration.

The goal of this paper is to review the relevant literature on autism questionnaires, models, analytic tools, and subgrouping, focusing on the opportunities and limitations. We examined how the size and nature of the database and the number and type of parameters measured determine the use of analytic tools and the expected type of results. To support our position about the examined aspects, we rely on various parts of the reviewed articles. We emphasize that the individual results in each article can only be interpreted in the light of the methods that brought about the conclusions. The reviewed literature suggests a heterogeneous palette in autism subtypes instead of distinct, well-characterized subgroups, or a single-dimensional continuous spectrum.

The temporal evolution of pandemics described by the susceptible-infectious-recovered (SIR)-compartment model is sensitively determined by the time dependence of the infection (a(t)) and recovery (u(t)) rates regulating the transitions from the susceptible to the infected and from the infected to the recovered compartment, respectively. Here approximated SIR-solutions for different time dependencies of the infection and recovery rates are derived which are based on the adiabatic approximation assuming time-dependent ratios k(t)=u(t)/a(t) varying slowly in comparison to the typical time characteristics of the pandemic wave. For such slow variations the available analytical approximations from the KSSIR-model, valid for a stationary value of the ratio k, are used to insert a-posteriori the adopted time-dependent ratio of the two rates. Instead of investigating endless different combinations of the time dependencies of the two rates a(t) and u(t) a suitably parameterized reduced time dependence of the ratio k(tau) is adopted. Together with the definition of the reduced time this parameterized ratio k(tau) allows us to cover a great variety of different time dependencies of the infection and recovery rates. The agreement between the solutions from the adiabatic approximation in its four different studied variants and the exact numerical solutions of the SIR-equations is remarkably good providing strong confidence in the accuracy of the proposed adiabatic approximation.

After the first weeks of vaccination against the SARS-CoV-2, several cases of acute thrombosis were reported. These news reports began to be shared frequently across social media platforms. The aim of this study was to conduct an analysis of Twitter data related to the overall discussion. Data was retrieved from 14th March to 14th April using the keyword ‘blood clots’. A dataset with n=266,677 tweets was retrieved, and a systematic random sample of 5% of tweets (n=13,334) were entered into NodeXL for further analysis. Social network analysis was used to analyse the data by drawing upon the Clauset-Newman-Moore algorithm. Influential users were identified by drawing upon the betweenness centrality metric. Text analysis was applied to identify the key hashtags and websites used at this time. More than half of the network was comprised of retweets and the largest groups within the network were broadcast clusters where a number of key users were retweeted. The most popular narratives were around highlighting the low risk of obtaining a blood clot from a vaccine and highlighting higher blood clot risks in medicines commonly consumed. A wide-variety of actors drove the discussion on Twitter ranging from writers, physicians, the general public academics, celebrities, and journalists. Twitter was used to highlight the low potential of obtaining a blood clot from a vaccine and encouraged vaccinations among the public.

Until recently, the classic approach to mineral exploration studies is to bring the field samples/drill cores collected during field studies to the laboratory followed by laborious analysis procedures to generate the analytical data. This is very expensive, time consuming and difficult for exploring vast areas. But rapid technological advances in field portable analytical instruments such as portable ultraviolet–visible and near-infrared spectrophotometers, gamma ray spectrometer, pXRF, pXRD, pLIBS, and µRaman spectrometer have changed this scenario completely and increased their on-site applications in mineral exploration studies. These instruments are currently providing direct, rapid, on-site, real-time, non-destructive, cost-effective identification, and determination of target elements, indicator minerals and pathfinder elements in rock, soil, and sediment samples. These portable analytical instruments are currently helping to obtain accurate chemical and mineralogical information directly in field with minimal or no sample preparation, and providing decision-making support during field work as well as during drilling operations in several successful mineral exploration programs. In this article, the developments in these portable devices, and their contributions in the platinum group elements (PGE), rare earth elements (REE), gold, base metals, and lithium exploration studies both on land and on ocean bed have been summarized with examples.

probiotics. However, these bacteria caused rare infections mostly in diabetic and immunocompromised subjects in presence of risk factors such as prosthetic hearth valves and dental procedures or caries. The scope of this survey was re-assessing the pathogenic potential of lactobacilli based on the infection case reports published in the last three years. In 2019, 2020 and 2021 17, 15 and 16 cases, respective-ly,.including endocarditis, bacteremia and other infections, were reported. These annual numbers are higher than observed previously. Lacticaseibacillus rhamnosus (13 cases), comprising strain GG (ATCC 53103) with established applications in healthcare, L. paracasei (7 cases), Lactobacillus acidophilus (5 cas-es), L. jensenii (5 cases), Lactiplantibacillus plantarum (3 cases), L. paraplantarum, L. delbrueckii subsp. del-brueckii, L. gasseri, L. paragasseri, Limosilactobacillus fermentum and L. reuteri (1 case each) were involved. Virulence characterization of two strains that caused infections, a derivative of L. rhamnosus GG and L.paracasei LP10266, indicated that increased biofilm forming capacity favors pathogenicity and it is determined by variable genetic traits. This survey highlighted that strains of lactobacilli able to cause infections were little characterized genet-ically. Instead, to avoid that these bacteria become a hazard, genetic stability should be periodically re-evaluated by whole genome sequencing (WGS) to ensure that only non-pathogenic variants are ad-ministered to vulnerable individuals.

A 3-month (June-August) regime of the year 2002 summer rainfall (JJA2002) was simulated with 30 physics combinations using the Weather Research and Forecasting (WRF) model at 12-km horizontal grid resolution. The objective is to examine summer rainfall sensitivity to parameterization of microphysical, convective, and boundary layer processes and identify the best possible combination of parameterization options that perform relatively better in simulating the spatial and temporal distribution of summer rains over Ethiopia. The WRF simulated rainfall was evaluated against station data and satellite rainfall products (CHIRPS and ENACTS) using mean absolute error, Pearson and Pattern correlation coefficients (PCC), pattern correlation, and error in a number of rainy days as evaluation metrics. Summer rainfall is found to be most sensitive to the choice of cumulus parameterization and least sensitive to cloud microphysics. All simulations captured the spatial distribution of mean seasonal precipitation with PCC ranging from 0.89-0.94. However, all simulations overestimated precipitation amount and number of rainy days. Out of the 30, the simulations that use a combination of Grell-3D cumulus scheme, ACM2 boundary layer, Lin Microphysics, Dudhai shortwave radiation, and RRTM longwave radiation scheme ranked the top and provided the most realistic simulation in terms of amount and spatio-temporal distribution of summer rainfall.

We consider the role information energy can play as a source of dark energy. Firstly, we note that, if stars and structure had not formed in the universe, elemental bits of information describing the attributes of particles would have exhibited properties similar to the cosmological constant. The Landauer equivalent energy of such elemental bits would be defined identical in form and value to the characteristic energy of the cosmological constant. But, with the formation of stars and structure, stellar heated gas and dust now provides the dominant contribution to information energy with the characteristics of a dynamic, transitional, dark energy. At low redshift, z<~1.35, this dark energy emulates the cosmological constant with a near constant energy density, w=−1.03±0.05, and an energy total similar to the mc² of the universe's ∼10⁵³ kg of baryons. At earlier times, z>~1.35, information energy was phantom, differing from the cosmological constant, Λ, by a CPL parameter difference of ∆w_o=−0.03±0.05 and ∆w_a=−0.79±0.08, values sufficient to account for the H₀ Tension. Information dark energy agrees with most phenomena as well as Λ, while exhibiting characteristics that resolve many tensions and problems of ΛCDM: the cosmological constant problem; the cosmological coincidence problem; the H₀ and σ₈ tensions. As this proposed dark energy source is not usually considered, we identify the expected signature in H(a) that will enable the role of information dark energy to be falsified by experimental observation.

The research presents the inter-comparison of atmospheric variables measured by 9 automatic meteorological stations. This set of data was compared with the measurements of other meteorological stations in order to standardize the values that must be adjusted when taken to different areas. The data of a set of a total of 9 GMX500, which measures conventional meteorological variables, and 10 WS100 sensors, which measures precipitation parameters. The automatic stations were set up at the Huancayo Observatory (Geophysical Institute of Peru) for a period of 5 months. The data set of GMX500 were evaluated comparing with the average of the 9 sensors and the WS100 was compared with a optical disdrometer Parsivel2. The temperature, pressure, relative humidity, wind speed, rainfall rate, and drop size distribution was evaluated. A pair of GMX500 sensors presented high data dispersion, it was found found that the errors came from a bad configuration; once this problem was solved, good agreement was archived, with low RMSE and high correlation. I was found that the WS100 sensors overestimate the precipitation with a percent bias close to 100% and the differences increase with the greater intensity of rain. The DSD retrieved by WS100 have unrealistic behavior with higher concentrations in diameters of 1 mm and 5 mm, in addition to a flattened curve.

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

Gut protozoan parasites are neglected and not targeted by specific control initiatives and this have led to a knowledge gap concerning their regional diversity and epidemiology. The present study aims to explore Giardia duodenalis genetic diversity and assess the epidemiologic scenario of subclinical infections in different Brazilian biogeographic regions. Cross-sectional surveys (n=1,334 subjects) were conducted in the Amazon, Cerrado, Semiarid and Atlantic Forest. Microscopy of non-diarrheal feces and nucleotide sequencing of a β-giardin gene fragment were performed. Twenty-seven (52.9%) β-giardin sequences were characterized as assemblage A and 24 (47.1%) as assemblage B. In Amazon, assemblage B was the most frequently detected with 2 novel sub-assemblages. Assemblage A predominated in the extra-Amazon region, with 5 novel sub-assemblages. Prevalence rates reached 17.8% in Amazon, 8.8% in Atlantic Forest, 7.4% in Cerrado and 2.3% in the Semiarid. People living in poverty and extreme poverty presented significantly higher positivity rates, reaching 11.9% and 14.5%, respectively. Giardiasis tended to be more frequent in stunted (21.6%) than in eutrophic children (12.9%). In conclusion, subclinical giardiasis in endemic in Brazilian communities in different biogeographic regions, presenting high genetic diversity and a heterogeneous genotypic distribution.

Gol'denveizer's problem of a torus has been analyzed by Audoly and Pomeau (2002) and Sun (2021). However, all of the investigations of Gol'denveizer's problem of an elastic torus have been linear. In this paper, the finite element method is used to more accurately address this problem. Furthermore, Sun (2021) cannot be solved by nonlinear analysis. We research the nonlinear mechanical properties of Gol'denveizer's problem of circular and elliptic tori, and relevant nephograms are given. We study the buckling of Gol'denveizer's problem of an elastic torus, and propose failure patterns and force-displacement curves of tori in the nonlinear range. Investigations reveal that circular tori have more rich buckling phenomena as the parameter a increases. Gol'denveizer's problem of the buckling of an elliptic torus is analyzed, and we find a new buckling phenomenon called a "skirt." As a/b increases, the collapse load of an elliptic torus of the Gol'denveizer problem is enhanced gradually.

Bayesian nonlinear mixed effects models for data in the form of continuous, repeated measurements from a population, also known as Bayesian hierarchical nonlinear models, are a popular platform for analysis when interest focuses on individual specific characteristics and relevant uncertainty quantification. Due to the limitation of computational power, this framework was relatively dormant until the late 1980s, but in recent years, the statistical research community saw vigorous development of new methodological and computational techniques for these models, the emergence of software, and wide application of the models in numerous industrial and academic fields. This article presents an overview of the formulation, interpretation, and implementation of Bayesian nonlinear mixed effects models and surveys recent advances and applications.

The combination of interstitial hyperthermia treatment (IHT) with high dose rate brachytherapy (HDR-BT) for prostate cancer treatment and has the potential to improve clinical outcome, since it highly enhances the efficiency of cell kill, especially when applied simultaneously. Therefore, we have developed the ThermoBrachy applicators. To effectively apply optimal targeted IHT, treatment planning is considered essential. However, treatment planning in IHT is rarely applied since it is regarded difficult to accurately calculate the deposited energy in the tissue in a short enough time for clinical practice. In this study, we investigated various time-efficient methods for fast computation of the electromagnetic (EM) energy deposition resulting from the ThermoBrachy applicators. Initially, we investigated the use of an electro-quasistatic solver. Next, we extended our investigation to the application of geometric simplifications. Furthermore, we investigated the validity of the superpositioning principle, which can enable adaptive treatment plan optimization without the need for continuous recomputation of the EM field. Finally, we evaluated the accuracy of the methods by comparing them to the golden standard Finite-Difference Time-Domain calculation method using gamma-index analysis. The simplifications considerably reduced the computation time needed, improving from &gt;12 h to a few seconds. All investigated methods showed excellent agreement with the golden standard by showing a &gt;99% passing rate with 1%/0.5 mm Dose Difference and Distance-to-Agreement criteria. These results allow the proposed electromagnetic simulation method to be used for fast and accurate adaptive treatment planning.

Among the thermophysical properties, the surface / interfacial tension, viscosity and density / molar volume of liquid alloys are the key properties for the modelling of microstructural evolution during solidification. Therefore, only reliable input data can yield accurate predictions preventing the error propagation in numerical simulations of solidification related processes. Due to experimental difficulties related to reactivity of metallic melts at high temperatures, the measured data are often unreliable or even lacking. The application of containerless processing techniques either leads to a significant improvement of the accuracy or makes the measurement possible at all. On the other side, accurate model predicted property values could be used to compensate the missing data; otherwise, the experimental data are useful for the validation of theoretical models. The choice of models is particularly important for the surface, transport and structural properties of liquid alloys representing the two limiting cases of mixing, i.e. ordered and phase separating alloy systems. To this aim, the thermophysical properties of the Fe-Si and Cu-Pb systems were analysed and the connections with the peculiarities of their mixing behaviours are highlighted.

This study examines the relation between ambient air pollution and emergency department (ED) visits due to certain infectious diseases in Toronto, Canada. The National Ambulatory Care Reporting System database was used to draw the corresponding health cases. Daily data on ED visits, ambient air pollution concentration levels, and weather conditions during the period from April 2004 to December 2015 (4,292 days in total) were linked together and used in statistical models. Six air pollutants (fine particulate matter PM2.5, CO, NO2, SO2, ozone O3 as a daily average, and ozone O3-8 hour ozone, as a maximum eight hour average) were investigated. In addition, the Air Quality Health Index (combining NO2, O3, and PM2.5) was also considered. The time-stratified case-crossover technique was applied in the study design. Conditional Poisson models were created using the daily counts of ED visit data. The considered factors, air pollutants and weather, were lagged by the same number of days, from 0 to 14. In the period of the study 339,644 ED visits were identified; 177,619 for females and 162,025 for males. For each air pollutant 270 models were realized (15 lags x 18 strata). Ambient air pollution concentrations lagged by 2, 3, and 5 days have the highest impact on ED visits, with 34, 32, and 35 positive associations, respectively. For all patients and an increase in a one interquartile range (IQR=1.2 ppb) of sulphur dioxide, the following values of the relative risks (RR) were estimated: RR=1.005 (95% confidence interval: 0.998, 1.013), 1.008 (1.001, 1.016), 1.009 (1.001, 1.016), 1.011 (1.004, 1.019), 1.007 (0.987, 1.028), and 1.009 (1.002, 1.016) for lags from 0 to 5, respectively. The results suggest that exposures for certain air pollutants (mainly CO, O3, and SO2) in urban environment affect the number of ED visits related to infectious diseases.

Salinity acts as a critical environmental filter on microbial communities in natural systems, negatively affecting microbial diversity. However, how salinity affects the community assembly remains unclear. This study used Wendeng multi-pond saltern as a model to evaluate the prokaryotic community composition and diversity and quantify the relative importance of ecological processes across salinity gradients. Results showed that low saline salterns (45-80 g/L) exhibited higher bacterial diversity than those in high saline salterns (175-265 g/L). The relative abundance of taxa assigned to Halanaerobiaceae, Haloferacaceae, Desulfohalobiaceae, Phormidiaceae, Rohodobacteraceae, and Nitrococcaceae was higher with increasing salinity. Salinity and pH were the primary environmental factors that directly or indirectly determined the composition and diversity of prokaryotic communities. Microbial co-occurrence network dynamics were more complex in the sediment than in water of salterns. An infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis (iCAMP) showed that microbial community assembly in sediment and water differed. Our findings provide more information about microbial community structure and the importance of various ecological processes in controlling microbial community diversity and succession along salinity gradients in water and sediment environments.

Malnutrition, unhealthy diets, and lifestyle changes have become major risk factors for non-communicable diseases while ad-versely impacting economic growth and sustainable development. Anthocyanins, a group of flavonoids that are rich in fruits and vegetables, contribute positively to human health. This review focuses on genetic variation harnessed through crossbreeding and biotechnology-led approaches for developing anthocyanins-rich fruit and vegetable crops. Significant progress has been made in identifying genes involved in anthocyanin biosynthesis in various crops. Thus, the use of genetics has led to the development and release of anthocyanin-rich crop cultivars in Europe and USA. Such a trend is emerging in the developing world. The purple pota-to “Kufri Neelkanth” has been released for cultivation in northern India, and a few colored grain wheat lines, developed through crossbreeding, are being tested for their productivity and adaptation. Although tomato is deficient in anthocyanins, some of its wild relatives are known to accumulate anthocyanins in their sub-epidermal fruit tissue. In Europe, anthocyanin-rich tomato cul-tivar ‘Sun Black’ developed via the introgression of Aft and atv genes has been released. The development of anthocyanin-rich food crops without any significant yield penalty has been due to the use of genetic engineering involving specific transcription factors or gene editing. The anthocyanin-rich food ingredients have the potential of being more nutritious than those devoid of anthocyanins. The inclusion of anthocyanins as a target characteristic in breeding programs can ensure the development of culti-vars to meet the nutritional needs for human consumption, particularly in the developing world.