In the NCBI database, as on June 6, 2020, total number of available complete genome sequences of SARS-CoV2 across the world is 3617. The envelope protein of SARS-CoV2 possesses several non-synonymous mutations over the transmembrane domain and (C)-terminus in 0.414\% of these 3617 genomes. The C-terminus motif DLLV has been changed to DFLV and YLLV in the proteins QJR88103 (Australia: Victoria) and QKI36831 (China: Guangzhou) respectively, which might affect the binding of this motif with the host protein PALS1.

This work describes a new transducer prototype for continuous monitoring both in the structural and geotechnical fields. The transducer is synthetically constituted by a wire of optical fiber embedded between two fiber tapes (fiberglass or carbon fiber) and glued by a matrix of polyester resin. The fiber optical wire ends have been connected to a control unit whose detection system is based on Brillouin optical time-domain frequency analysis. Three laboratory tests were carried out to evaluate the sensor's reliability and accuracy. In each experiment, the transducer was applied to a sample of inclinometer casing sets in different configurations and with different constraint conditions. The experimental data collected were compared with theoretical models and with data obtained from the use of different measuring instruments to perform validation and calibration of the transducer at the same time. Several diagrams allow comparing the transducer and highlighting its suitability for monitoring and maintenance of structures. The characteristic of the transducer suggests its use as a mixed system for reinforcing and monitoring, especially in lifetime maintenance of critical infrastructures such as transportation and service networks, and historical heritage.

Fungi critically impact the health and function of global ecosystems and economies. In Canada, fungal researchers often work within silos defined by sub-discipline and institutional type, complicating the collaborations necessary to understand the impacts fungi have on the environment, economy, and plant and animal health. Here, we announce the establishment of the Canadian Fungal Research Network (CanFunNet, https://fungalresearch.ca) whose mission is to strengthen and promote fungal research in Canada by facilitating dialogue among scientists. We summarize the challenges and opportunities for Canadian fungal research that were discussed at CanFunNet’s inaugural meeting in 2019, and identify four priorities for our community: 1) increasing collaboration among scientists; 2) studying diversity in the context of ecological disturbance; 3) preserving culture collections in the absence of sustained funding; and 4) leveraging diverse expertise to attract trainees. We have gathered additional information to support our recommendations, including a survey identifying underrepresentation of fungal-related courses at Canadian universities, a list of Canadian fungaria and culture collections, and a case study of a human fungal pathogen outbreak. We anticipate that these discussions will help prioritize fungal research in Canada, and we welcome all researchers to join this nationwide effort to enhance knowledge dissemination and funding advocacy.

To reduce the risk factors for mortality, the paper has focused on the assessment of the socioeconomic, clinical, physical, biophysiological, and biochemical characteristics of Down's syndrome which can be affected by the type of nutrition system, toxicity, and ecological footprint. Patients were males with trisomy 21 diagnosed by karyotype test and assessed by clinical examinations. Samples were collected from different biofluids. The physicochemical analyses of the biomatrix samples were performed and these properties had compared to findings of healthy males and age-matched controls. Duraphat application was proved effective for their oral treatment and saliva was the optimum biomarker for detecting malnutrition. Patients were hypersensitive to Cu while the Mn content in blood and hair was considered an expression to the degree of epileptic condition and chronic seizure development. The ecological footprint was 5.6 gha and carbon footprint was recognised in food poverty habits. These can be reduced by eating more plant-based proteins and fibre-rich foods with low saturated fats and sodium. The findings provide an up-to-date reference for expected developmental outcomes in children with DS in terms of biophysicochemistry. The genetically sensitive intervention is affected by heredity factor and sensitivity to toxics. Down's syndrome is encouraged to live green-hipster life.

The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral genome is an RNA virus consisting of approximately 30,000 bases. As part of testing efforts, whole genome sequencing of human isolates has resulted in over 1,600 complete genomes publicly available from GenBank. We have performed a comparative phylogenetic analysis of the sequences, in order to detect common mutations within the population. Analysis of variants occurring within the assembled genomes yields 417 variants occurring in at least 1% of the completed genomes, including 229 within the 5’ untranslated region (UTR), 152 within the 3’UTR, 2 within intergenic regions and 34 within coding sequences.

Purpose: Perceptual learning and production practice are basic mechanisms that children depend on to acquire adult levels of speech accuracy. In this study, we examined perceptual learning and production practice as they contributed to changes in speech accuracy in three- and four-year-old children. Our primary focus was manipulating the order of perceptual learning and baseline production practice to better understand when and how these learning mechanisms interact. Method: Sixty-five typically-developing children between the ages of three and four were included in the study. Children were asked to produce CVCCVC nonwords like /bozjəm/ and /tʌvtʃəp/ that were described as the names of make-believe animals. All children completed two separate experimental blocks: a baseline block in which participants heard each nonword once and repeated it, and a test block in which the perceptual input frequency of each nonword varied between 1 and 10. Half of the participants completed a baseline-test order; half completed a test-baseline order. Results: Greater accuracy was observed for nonwords produced in the second experimental block, reflecting a production practice effect. Perceptual learning resulted in greater accuracy during the test for nonwords that participants heard 3 or more times. However, perceptual learning did not carry over to baseline productions in the test-baseline design, suggesting that it reflects a kind of temporary priming. Finally, a post hoc analysis suggested that the size of the production practice effect depended on the age of acquisition of the consonants that comprised the nonwords. Conclusions: The study provides new details about how perceptual learning and production practice interact with each other and with phonological aspects of the nonwords, resulting in complex effects on speech accuracy and learning of form-referent pairs. These findings may ultimately help speech-language pathologists maximize their clients’ improvement in therapy.

Satellite communication (Satcom) is an artificial geostationary satellite that facilitates a wide range of telecommunications. Considering its quality of service (QoS) and security is crucial in government/military applications. The most challenging situation for efficient Satcom is radio frequency interference (RFI) environment. Thus, it is necessary to ensure that transmissions are incorruptible or at least sense the quality of its spectrum. This paper presents a new method to recognize received signal characteristics using a hierarchical classification in a multi-layer perceptron neural network. We consider signal modulation and the type of RFI as the characteristics of a real-time video stream transmitted in the direct broadcast satellite. Four different modulation types are investigated in this study. Moreover, the combination of the communication signal with various kinds of interference and their effects on the classification method widely have been analyzed. Besides, two robust feature selection techniques have been developed to reduce the data-set dimensional, which leads to optimizing the classification process. The results show that the Genetic Algorithm (GA) slightly outperforms Principal Component Analysis (PCA) for feature selection. Furthermore, the robustness of the proposed techniques is assessed to detect unknown signals at different signal to noise ratios.

Epithelial-mesenchymal transition (EMT) is a cellular biological process involved in migration of primary cancer cells to secondary sites facilitating metastasis. Besides, EMT also confers properties such as stemness, drug resistance and immune evasion which can aid a successful colonization at the distant site. EMT is not a binary process; recent evidence suggests that cells in partial EMT or hybrid E/M phenotype(s) can have enhanced stemness and drug resistance as compared to those undergoing a complete EMT. Moreover, partial EMT enables collective migration of cells as clusters of circulating tumor cells or emboli, further endorsing that cells in hybrid E/M phenotypes may be the ‘fittest’ for metastasis. Here, we review mechanisms and implications of hybrid E/M phenotypes, including their reported association with hypoxia. Hypoxia-driven activation of HIF-1α can drive EMT. In addition, cyclic hypoxia, as compared to acute or chronic hypoxia, shows the highest levels of active HIF-1α and can augment cancer aggressiveness to a greater extent, including enriching for a partial EMT phenotype. We also discuss how metastasis is influenced by hypoxia, partial EMT and collective cell migration, and call for a better understanding of interconnections among these mechanisms. We discuss the known regulators of hypoxia, hybrid EMT and collective cell migration and highlight the gaps which needs to be filled for connecting these three axes which will increase our understanding of dynamics of metastasis and help control it more effectively.

During the period of health emergency linked to the current COVID-19 pandemic, the management of children's oral health presents specific problems related to the infectious spread of the disease. These problems must be faced on the one hand by acting on the oral health prevention methods, and on the other by implementing specific protocols relating both to the conditions of oral pathologies that normally do not represent an emergency, and to those clinical situations that fall into the category of pediatric dental emergencies. In this perspective, in addition to defining rigorous and highly effective infection control protocols in the dental settings, it is of fundamental importance to work on remote communication and education aimed at maintaining the oral health of the children. This article, after an analysis of the risk factors from COVID-19 associated with pediatric dental treatment, presents a series of considerations on potential oral prevention strategies and on the management of emergency and non-emergency dental procedures in a context of disease transmission control, proposing new approaches and models of treatment based also on remote interaction techniques which will then retain their usefulness even at the end of the current emergency period.

This article aims to reflect upon the relevance of Decolonization methodologies with the Theses on Feuerbach. Somehow, all the Indigenous scholars started from new Marxist like Paulo Freire, Frantz Fanon, but not from classic Marx. To us, the German Ideology of young Marx only resembles the pioneering sources of Indigenous methodology. This discussion is thus a reflection of our studies and a philosophic endeavor to talk about the marginal people of the world, and the scholars who engaged in and with the oppressed. However, we are not prepared to turn our attention away from all the vastness of Marx to a collection of potentially equally relevant to Indigenous methodology. This article concludes that the Theses on Feuerbach is the core of Marxist archaeology of knowledge or philosophy as a whole and has been wading in the Indigenous paradigm.

In 1975, Fuller and Tabor have shown that roughness can destroy macroscopic adhesion. This means that in spite of the presence of adhesion at the microscopic scale, the macrosopic force of adhesion vanishes. The mechanism of vanishing macroscopic adhesion is very simple: during approach of elastic bodies, asperities are elastically deformed so strongly that after unloading they destroy the microscopic adhesive junctions. However, both in the moment of formation of microscopic adhesive junctions in the loading phase and their destruction during unloading, mechanical energy disappears. This means that the microscopic adhesion makes the contact dissipative even if there is no macroscopic force of adhesion. In particular, the force-distance dependency during indentation and pull-off do not coincide with each other showing some "adhesive hysteresis". When a ball rolls on such rough surface, there will be a final energy dissipation due to formation of a new contact at the frontline of the contact and its destruction at the rear part. Thus, microscopic adhesion will lead to appearance of rolling friction in an apparently non-adhesive contact. In the present paper, we calculate the approach and pull-off dependencies of force on distance, the dissipated energy in one loading-unloading cycle and estimate the force of rolling friction due to microscopic adhesion.

Objective: The aim of study is to find key genes and enriched pathways associated with lung cancer. Participants and Methods: Differentially expressed genes (DEGs) data of 54674 genes based on stage, tumor and status of lung cancer was taken from 66 patients of African American (AAs) origin. 2392 DEGs were found based on stage, 13502 DEGs were found based on tumor, 2927 DEGs were found based on status having p value (p<0.05). Results: Total 33 common DEGs were found from stage, tumor and status of lung cancer. Gene ontology (GO) and KEGG pathway enrichment analysis was performed and 49 significant pathways were obtained, out of which 10 pathways were found to be exclusively involved in lung cancer development. Protein-protein interaction (PPI) network analysis found 69 nodes and 324 edges and identified 10 hub genes based on their highest degrees. Module analysis of PPI found that ‘Viral carcinogenesis’, ‘pathways in cancer’, ‘notch signaling pathway’, ‘AMPK signaling pathways’ had a close association with lung cancer. Conclusion: These identified DEGs regulate other genes which play important role in growth of lung cancer. The key genes and enriched pathways identified can thus help in better identification and prediction of lung cancer.

Maximum entropy production principle (MEPP) has been formulated in the mid-twentieth century, and today it has acquired the status of an important principle of science, which is extremely effective in considering various non-equilibrium problems. In this study, for the first time, definition of life is based on an easily measurable physical quantity that is entropy production. Life and evolution are discussed from the point of view of MEPP and the Universe, but not a human

Graph theory plays significant role in every field of science as well as technology. Every situation can be articulated in terms of suitable graphs by using various approaches of graph theory. Considering the recent pandemic in the world and the precautions taken for prevention of the COVID 19, it is the most appropriate way to exercise the graph models with theoretical as well as practical aspects to control this epidemic. This paper defines the variable set, variable graphs and their types with respect to variable vertex sets and variable edge sets. Depending upon the nature of the pandemic, there are four types of Virus graphs. Virus graph I and III are not so perilous for all living beings. Although, Virus graphs II and IV are extremely hazardous for the harmony of the world. In view of different aspects for expand of pandemic, growth types of virus graphs are divided in 1-1, 1-P and 1-all growth types. The COVID19 initially was in Virus graph-I type, but presently it is in Virus graph-II types. We present the table involving the number of infected people after n days with respect to different values of P and growth rates with I0 = 100. Moreover, the country wise starting dates of stages of the virus graph-I and II are specified. The concept of cut sets is applicable for prevention of COVID19 and the whole world is using the same analogy.

The severity of the ongoing COVID-19 outbreak demand from countries to adopt extreme measurements of social isolation to stop the spread and flatten the curve of contamination. Although social isolation measures may have negative impacts on economy, historically it has been showed to be more effective in saving lives and less damaging to economy than not adopting these measurements during a viral pandemic. In Brazil, despite the positioning of the president against social isolation due to the consequent economic recession, the rapid spread of the virus has worried the governors of the Brazilian states, which are thus managing stringent social isolation measurements to avoid the advance of the virus. Since one of the main strategies to guarantee progress and economic growth in Brazil has been the exploitation of natural resources from the Amazonia biome, here we discuss the importance of this biome to Brazilian economy during the post-pandemic recession and highlights potential strategies to burst the economy without promoting Amazonia destruction. We show that, together with the REDD+ and the Amazon Fund, the Forest bonds represents good strategies to burst Brazilian economy in a sustainable way, showing that it is possible to improve the commodities without increasing Amazonia deforestation or the greenhouse gases emissions. Amazonia is a biome of global importance for the avoidance of another global crisis, which will occur if we reach the climatic tipping point of 1.5°C. Thus, governmental actions should go towards its preservation, not exploitation and depletion. The commitment of the government with environmental conservation is paramount so that these economic strategies have positive results, especially in a post-pandemic scenario, where the economy will be extremely weakened. The COVID-19 brings us a lesson regarding how our attitudes can impact the world, and what we can expect from a global crisis. Perhaps we can apply these lessons and focus on change our economy towards a sustainable direction to avoid another global crisis in the years to come.

The technology-driven world of the 21^st century is currently confronted with a major threat to humankind in the form of the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). As of April 22, 2020, COVID-19 has claimed 169, 006 human lives and had spread to over 200 countries with more than 2,471,136 confirmed cases. The perpetually increasing figures associated with COVID-19 are disrupting the social and economic systems globally. The losses are unmatched and significantly higher compared to those from previously encountered pathogenic infections. Previously, two CoVs (SARS-CoV and Middle East respiratory syndrome-CoV) affected the human population in 2002 and 2012 in China and Saudi Arabia, respectively. Based on genomic similarities, animal-origin CoVs, primarily those infecting bats, civet cats, and pangolins, were presumed to be the source of emerging human CoVs, including the SARS-CoV-2. The cohesive approach amongst virologists, bioinformaticians, big data analysts, epidemiologists, and public health researchers across the globe has delivered high-end viral diagnostics. Similarly, vaccines and therapeutics against COVID-19 are currently in the pipeline for clinical trials. The rapidly evolving and popular technology of artificial intelligence played a major role in confirming and countering the COVID-19 pandemic using digital technologies and mathematical algorithms. In this review, we discuss the noteworthy advancements in the mitigation of the COVID-19 pandemic, focusing on the etiological viral agent, comparative genomic analysis, population susceptibility, disease epidemiology, animal reservoirs, laboratory animal models, disease transmission, diagnosis using artificial intelligence interventions, therapeutics and vaccines, and disease mitigation measures to combat disease dissemination.

Polydimethylsiloxane (PDMS) is one of the most popular elastomers and has been used in different fields, especially in biomechanics research. Among the many interesting features of this material, its hyperelastic behaviour stands out, which allows the use of PDMS in various applications, like the ones that mimic soft tissues. However, the hyperelastic behaviour is not linear and needs detailed analysis, especially the characterization of shear strain. In this work, two approaches, numerical and experimental, were proposed to characterize the effect of shear strain on PDMS. The experimental method was implemented as a simple shear testing associated with 3D digital image correlation and was made using two specimens with two thicknesses of PDMS (2 and 4 mm). A finite element software was used to implement the numerical simulations, in which four different simulations using the Mooney-Rivlin, Yeoh, Gent, and Polynomial hyperelastic constitutive models were performed. These approaches showed that the maximum value of shear strain occurred in the central region of the PDMS, and higher values emerged for the 2 mm PDMS thickness. Qualitatively, in the central area of the specimen, the numerical and experimental results have similar behaviours and the values of shear strain are close. For higher values of displacement and thicknesses, the numerical simulation results move further away from experimental values.

The Coronavirus disease due to SARS-CoV-2 emerged in Wuhan city, China in December 2019 and rapidly spread more than 200 countries as a global health pandemic. There are more 3 million confirmed cases and around 207,000 fatalities. The primary manifestation is respiratory and cardiac but neurological manifestations are being reported in the literature as case reports and case series. The most common reported symptoms to include headache and dizziness followed by encephalopathy and delirium. Among the complications noted are Cerebrovascular accident, Guillian barre syndrome, acute transverse myelitis, and acute encephalitis. The most common peripheral manifestation was hyposmia. It is further noted that sometimes the neurological manifestations can precede the typical features like fever and cough and later on typical manifestations develop in these patients. Hence a high index of suspicion is required for timely diagnosis and isolation of cases to prevent the spread in neurology wards. We present a narrative review of the neurological manifestations and complications of COVID-19. Our aim is to update the neurologists and physicians working with suspected cases of COVID-19 about the possible neurological presentations and the probable neurological complications resulting from this novel virus infection.

Simulated crime scene investigation is an essential component of forensic science education, but its implementation poses challenges relating to cost, accessibility and breadth of experience. Virtual reality (VR) is an emerging technology which offers exciting prospects for teaching and learning, especially for imparting practical skills. We document here a multidisciplinary experimental study in which a bespoke VR crime scene app was designed and implemented, after which it was tested by both undergraduate student and staff/postgraduate student cohorts. Through both qualitative and quantitative analyses, we demonstrate that VR applications support learning of practical crime scene processing skills. VR-based practical sessions have the potential to add value to forensic science courses through offering cost-effective practical experience and the ability to work in isolation, in a variety of different scenarios. Both user groups reported high levels of satisfaction with the process and reports of adverse effects (motion sickness) were minimal. With reference to user feedback, we proceed to evaluate the scalability and development challenges associated with large-scale implementation of VR as an adjunct to forensic science education.

I localize gravity to match its measurements with the local inertial frame of special relativity. I find a geometric interpretation of the speed of light and mass. I find also a relation between every mass measured and the black hole entropy which introduces information-matter equation from gravity. Through localization of gravity, a timeless state of the universe emerges and the uncertainty principle does not hold since the velocity concept is replaced by distance in this timeless state. This would resolve the problem of time because timeless state of the universe emerges naturally and mathematically consistent. This would suggest that gravity form the hidden one variable of quantum mechanics which would complete the relation between quantum mechanics and gravity. The experimental evidence of timeless state of the universe is the quantum entanglement. Since the spin measurement is the manifestation of quantum entanglement. Therefore, the spin of quantum particle can be originated from geometrical or gravitational red-shift. We introduce also a principle of least computation which is achieved when the ratio equal to the difference in the process of local gravitational measurements.

Rapidly spreading disease, COVID-19 is classified as the human-to-human transmission-able disease and currently is a pandemic in the Globe. In this paper, we propose conceptual mathematical models for COVID-19 outbreak and it's control measurement; quarantine, hospitalization and the effect of panic and anxiety. In this situation, mathematical models are a important tool to employ an effective strategy in order to fight against this pandemic. We establish the positivity and boundedness of solutions, local and global stability analysis of equilibria to examine its epidemiological relevance. To validate the model and estimating the important model parameters and prediction about the disease, we consider the real cases of Italy from $15^{th}$ Feb to $13^{th} $ April 2020. In a series of graphical map, we have presented the comparative study to estimate the current scenarios and to predict the control measurement time boundary of the outbreak.

Abnormalities in male fertility constitute about 50% of all infertility causes. According to some data, the quality of human semen has deteriorated by 50-60 % over the last 40 years. A high-fat diet and obesity, the development of which is encouraged by the western lifestyle, affects the structure of spermatozoa, but also the development of the offspring and their health in later stages of life. In obese individuals, disorders on the hypothalamic-pituitary-gonadal axis are observed, as well as elevated oestrogen levels with simultaneous decrease of testosterone, LH and FSH hormone levels. Healthy dietary models clearly correlate with better sperm quality and a smaller risk of abnormalities in parameters, such as sperm count, sperm concentration and motility, as well as lower sperm DNA fragmentation. Apart from mineral components such as zinc and selenium, the role of omega-3 fatty acids and antioxidant vitamins should be emphasized, since their action will be based primarily on the minimization of oxidative stress and inflammation process. Additionally, the incorporation of carnitine supplements and coenzyme Q10 in therapeutic intervention seems also promising. Therefore, it is advisable to have a varied and balanced diet based on vegetables and fruit, fish and seafood, nuts, seeds, whole-grain products, poultry and low-fat dairy products.

Globally, there is massive uptake and explosion of data and challenge is to address issues like scale, pace, velocity, variety, volume and complexity of the data. Considering the recent epidemic in China, modeling of COVID-19 epidemic for cumulative number of infected cases using data available in early phase was big challenge. Being COVID-19 pandemic during very short time span, it is very important to analyze the trend of these spread and infected cases. This predictive analytics can be empowered using Information, Communication and Technologies (ICT) services, tools and applications. This paper presents medical perspective of COVID-19 towards epidemiological triad and the study of state-of-the-art. The main aim this paper is to present different predictive analytics techniques available for trend analysis, different models and algorithms and their comparison. Finally, this paper concludes with prediction of COVID-19 using Prophet algorithm indicating more faster spread in short term. These predictions will be useful to government and healthcare communities to initiate appropriate measures to control this outbreak in time.

The symptoms most commonly reported by patients affected by coronavirus disease 2019 (COVID-19) include cough, fever, and shortness of breath. However, other major events usually observed in COVID-19 patients (e.g. high blood pressure, thrombosis, pulmonary embolism) seem to suggest that the virus is targeting the endothelium, one of the largest organs in the human body. Herein, we report both clinical and preclinical evidence supporting the hypothesis that the endothelium is a key target organ of COVID-19.

This article investigates whether the weather has any role in terms of spread and vulnerability of COVID-19 and how that knowledge can be used to arrest this fast spreading disease. It highlights that temperature and humidity both are important for transmitting the virus- temperature being the stronger factor. A dry, cool environment is the most favourable state for the spread of the virus. In fact, high temperature environment significantly reduces the risk from the virus. Warm places and countries are likely to be less vulnerable. Only regulating temperature level can provide drastic results to stop and arrest the outbreak. Some urgent solutions are proposed based on that knowledge. The novelty of such approach is- it can be applied overnight and implemented immediately across the globe. It is very cost effective and practically without side effects. No vast amount of funding is required to adopt these solutions. Apart from existing guidelines, these additional measures are likely to reduce the spread of the disease dramatically. Following the scientific discussion, such solutions may be thought of implementing worldwide, especially to vulnerable countries, as an emergency basis.

There exists a great potential for application in soil mechanics with the use of mechanistic models such as the finite element model, and other non-local models, such as the peridynamic model, since the soil mass can be modelled as a group of particles that interact with each other. In this work, we determine the bearing capacity of deep foundations where stresses are transmitted to deep deposits, which generally present better characteristics in terms of compressibility and shear strength. One of the main elements are driven piles, which must be previously designed, made and tested before their final use. In this work, a comparison with different methods is presented. The finite element method and the peridynamic model are used. Because the effect of consolidation was not taken into account, in these examples, the assumption is made that the structures are cemented in inert soil. Likewise, it is assumed that the water table has no influence on the simulations. Failure envelopes were observed where bonds between particles present high gradients of deformation and fracture. Bearing capacities were estimated and compared with those obtained from the Terzaghi and Meyerhof methods.

The reliability analysis allows to estimate the system's probability of detecting and identifying outlier. Failure to identify an outlier can jeopardise the reliability level of a system. Due to its importance, outliers must be appropriately treated to ensure the normal operation of a system. The system models are usually developed from certain constraints. Constraints play a central role in model precision and validity. In this work, we present a detailed optical investigation of the effects of the hard and soft constraints on the reliability of a measurement system model. Hard constraints represent a case in which there exist known functional relations between the unknown model parameters, whereas the soft constraints are employed for the case where such functional relations can slightly be violated depending on their uncertainty. The results highlighted that the success rate of identifying an outlier for the case of hard constraints is larger than soft constraints. This suggested that hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. After identifying and removing possible outliers, one should set up the soft constraints to propagate the uncertainties of the constraints during the data processing. This recommendation is valid for outlier detection and identification purpose.

Most striking observations in COVID-19 patients are the hints on pulmonary edema (also seen on CT scans as ground glass opacities), dry cough, fluid restrictions to prevent more severe hypoxia, the huge PEEP that is needed while lungs are compliant, and the fact that anti-inflammatory therapies are not powerful enough to counter the severity of the disease. We propose that the severity of the disease and many deaths are due to a local vascular problem due to activation of B1 receptors on endothelial cells in the lungs. SARS-CoV-2 enters the cell via ACE2, a cell membrane bound molecule with enzymatic activity that next to its role in RAS is needed to inactivate des-Arg⁹ bradykinin, the potent ligand of the bradykinin receptor type 1 (B1). In contrast to bradykinin receptor 2 (B2), the B1 receptor on endothelial cells is upregulated by proinflammatory cytokines. Without ACE2 acting as a guardian to inactivate the ligands of B1, the lung environment is prone for local vascular leakage leading to angioedema. Angioedema is likely a feature already early in disease, and might explain the typical CT scans and the feeling of people that they drown. In some patients, this is followed by a clinical worsening of disease around day 9 due to the formation antibodies directed against the spike (S)-antigen of the corona-virus that binds to ACE2 that could contribute to disease by enhancement of local immune cell influx and proinflammatory cytokines leading to damage. In parallel, inflammation induces more B1 expression, and possibly via antibody-dependent enhancement of viral infection leading to continued ACE2 dysfunction in the lung because of persistence of the virus. In this viewpoint we propose that a bradykinin-dependent local lung angioedema via B1 and B2 receptors is an important feature of COVID-19, resulting in a very high number of ICU admissions. We propose that blocking the B1 and B2 receptors might have an ameliorating effect on disease caused by COVID-19. This kinin-dependent pulmonary edema is resistant to corticosteroids or adrenaline and should be targeted as long as the virus is present. In addition, this pathway might indirectly be responsive to anti-inflammatory agents or neutralizing strategies for the anti-S-antibody induced effects, but by itself is likely to be insufficient to reverse all the pulmonary edema. Moreover, we provide a suggestion of how to ventilate in the ICU in the context of this hypothesis.

The coronavirus pandemic will deeply affect the tourism and travel sector. It is already clear now that its economic impact would be more severe that in the case of the Severe Acute Respiratory Syndrome (SARS) in 2002-2003. Although not as deadly as SARS, coronavirus infection has a longer incubation period and leaves about 85% of the infected without any (or with just mild) symptoms which makes it more difficult to track and to contain. Moreover, it appears to be much more contagious than its predecessor. The goods news is that most people recover from the disease and develop antibodies that can protect them from getting infected again (natural vaccination). Those cured might become the key element for the post-virus recovery strategies of tourism organisations. People with the acquired immunity to the virus would be capable of travelling freely without spreading the disease. Airlines, hotels and gastronomy should aim at this group offering them discounts and special offers. However, the problem is how to effectively ensure that everyone who claims to be cured from COVID-19 is telling the truth. Health tracking bracelets, apps, and other advanced technological solutions should be put in place. Recent best practices from Hong Kong, mainland China, or India might be applied.

The Stochastic Optimisation Software (SOS) is a Java platform facilitating the algorithmic design process and the evaluation of metaheuristic optimisation algorithms. It reduces the burden of coding miscellaneous methods for dealing with several bothersome and time-demanding tasks such as parameter tuning, implementation of comparison algorithms and testbed problems, collecting and processing data to display results, measuring algorithmic overhead, etc. SOS provides numerous off-the-shelf methods including 1) customised implementations of statistical tests, such as the Wilcoxon Rank-Sum test and the Holm-Bonferroni procedure, for comparing performances of optimisation algorithms and automatically generate result tables in PDF and LaTeX formats; 2) the implementation of an original advanced statistical routine for accurately comparing couples of stochastic optimisation algorithms; 3) the implementation of a novel testbed suite for continuous optimisation, derived from the IEEE CEC 2014 benchmark, allowing for controlled activation of the rotation operator. each testbed function. Moreover, this article comments on the current state of the literature in stochastic optimisation and highlights similarities shared by modern metaheuristics inspired by nature. It is argued that the vast majority of these algorithms are simply a reformulation of the same methods and that metaheuristics for optimisation should be simply treated as stochastic processes with less emphasis on the inspiring metaphor behind them.

Previous studies had shown that mRNA, miRNA and lncRNA were associated with cardiovascular diseases. The study was aimed to explore the differential expressions of mRNA, lncRNA and miRNA between coronary artery disease (CAD) and healthy control, and their interaction in CAD. We investigated the differential expression of ceRNA between CAD and healthy control through data collected from Gene Expression Omnibus (GEO) microarrays. Furthermore, we investigated the biological function of these differential expressions of ceRNAs by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Protein-protein interaction (PPI) network was created to identify the hub genes. Biosystems and literature search were performed for signaling pathways and their function of the included differential expression ceRNAs. A total of 456 miRNA expression profiles, 16,325 mRNA expression profiles, and 2,869 lncRNA expression profiles were obtained. Eleven Go and KEGG pathways (count ≥9), top 15 of PPI network node connectivity rank, and top 15 of ceRNA network node degree centrality rank were achieved at the statistical significance level (P<0.05). We further identified that several differential expressions of ceRNAs and their signaling pathways were associated with CAD through biosystems and literature search. Based on eleven Go and KEGG pathways, top 15 of PPI network node connectivity rank, and top 15 of ceRNA network node degree centrality rank in CAD population, our findings would contribute to further exploration for the molecular mechanism of CAD.

The damage caused by global warming is rapidly increasing, and its adverse effects become more evident with each passing day. Although it is known that the use of alternative binder materials in concrete would decrease this negative effect, reluctance to new composites continues. Waste use plays a vital role in sustainability studies. In this study, pure cement paste was prepared and enriched with carbon fiber. This study investigated the wide range of volume fraction of carbon fiber in cement-based composites. Two different industrial wastes, marble dust, and bottom ash were chosen and mixed with cement and four different (0.3%, 0.75%, 1.5%, and 2.5%) carbon fiber volume fractions. Based on physical, mechanical, and durability tests at 7, 28, and 56-days of curing, the composites were resistant to sulfate and seawater attack. The 0.75% carbon fiber addition seems to be an optimum volume percentage beyond which both physical and mechanical properties were adversely affected. The composites with 0.75% carbon fiber have reached 48.4 MPa and 47.2 MPa at 56-days of curing for marble dust and bottom ash mixture groups, respectively.

Available water resources in the Middle East, as one of the most water-scarce regions of the world, have undergone extra pressure due to climatic change, population growth, and economic development during the past decades. The objective of this study is to detect the trends and quantify the changes in aridity with respect to precipitation and potential evapotranspiration in 20 countries of the Middle East and the adjacent area. A Pixel-wised trend analysis was conducted on precipitation, potential evapotranspiration, and aridity index for 71 years from 1948 to 2018. A nonparametric Mann-Kendall test was used over 14106 points in the study area to detect the trends at monthly and annual time scales. Results showed statistically significant (|Z| >1.96) upward trends in aridity (a downward trend in aridity index) up to 96 percent from December through September in most parts of the region. Aridity in October and November had a downward tendency in most parts of the study area. At the annual time scale, 62.5 percent of the statistically significant trends in aridity were found to be upward (up to 96 percent increase in aridity) due to the combined effects of the decrease in precipitation and the increase in potential evapotranspiration and 37.5 percent of the detected trends were downward (up to 61 percent decrease in aridity). The highest and the lowest trends in aridity were found in the north of Sudan (96 percent increase in aridity) and Eastern Arabia (61 percent decrease in aridity), respectively.

Purpose of this article is to introduce a modification of Phillips operators on the interval $\left[ \frac{1}{2},\infty \right) $ via Dunkl generalization. This type of modification enables a better error estimation on the interval $\left[ \frac{1}{2},\infty \right) $ rather than the classical Dunkl Phillips operators on $\left[ 0,\infty \right) $. We discuss the convergence results and obtain the degrees of approximations. Furthermore, we calculate the rate of convergence by means of modulus of continuity, Lipschitz type maximal functions, Peetre's $K$-functional and second order modulus of continuity.

The intermediate filament protein vimentin constitutes a critical sensor for electrophilic and oxidative stress. We previously showed that vimentin interacts with zinc, which affects its assembly and redox sensing. Here we have used vimentin wt and C328S, an oxidation-resistant mutant showing improved NaCl-induced polymerization, to assess the impact of zinc on soluble and polymerized vimentin by light scattering and electron microscopy. Zinc acts as a switch, reversibly inducing the formation of vimentin oligomeric species. High zinc concentrations elicit optically-detectable vimentin structures with a characteristic morphology depending on the support. These effects also occur in vimentin C328S, but are not mimicked by magnesium. Treatment of vimentin with micromolar zinc induces fibril-like particles that do not assemble into filaments, but form aggregates upon subsequent addition of NaCl. In contrast, when added to NaCl-polymerized vimentin, zinc increases the diameter or induces lateral association of vimentin wt filaments. Remarkably, these effects are absent or attenuated in vimentin C328S filaments. Therefore, the zinc-vimentin interaction depends on the chemical environment and on the assembly state of the protein, leading to atypical polymerization of soluble vimentin, likely through electrostatic interactions, or to broadening and lateral association of preformed filaments through mechanisms requiring the cysteine residue. Thus, impact of zinc on vimentin assembly and redox regulation is envisaged.

Future, flexible thermal energy conversion systems require new, demand-optimized high-performance materials. The High performance Ferritic (HiperFer) stainless steels, under development at the Institute of Microstructure and Properties of Materials (IEK-2) at Forschungszentrum Jülich GmbH in Germany, provide a balanced combination of fatigue, creep and corrosion resistance at reasonable price. This paper outlines the scientific background of alloy performance development, which resulted in an age-hardening ferritic, stainless steel grade. Furthermore, technological properties are addressed and the potential concerning application is estimated by benchmarking versus conventional state of the art materials.

Hematopoietic stem cells (HSCs) are responsible for the production of blood cells throughout the human life span. Single HSCs can give rise to at least eight distinct blood cell lineages. Together, hematopoiesis, erythropoiesis and angiogenesis coordinate several biological processes, such as cellular interactions in development and proliferation, guided migration, lineage programming and reprogramming by transcription factors. Any dysregulation of these processes may result in hematological disorders and/or malignancies. Several studies of the molecular mechanisms governing HSC maintenance have demonstrated that protein regulation by the ubiquitin proteasomal pathway is crucial for normal HSC function. Recent studies have shown that the reversal of ubiquitination by deubiquitinating enzymes (DUBs) plays an equally important role in hematopoiesis; however, there is only limited additional information regarding the biological function of DUBs. In this review, we focus on recent discoveries that have led to a better understanding of the physiological roles of DUBs in hematopoiesis, erythropoiesis and angiogenesis. In addition, we discuss the DUBs associated with common hematological disorders and malignancies, which may potentially be therapeutic drug targets.

Unmanned Aerial Vehicle (UAV) based remote sensing (RS) studies in glaciology are mainly focusing on obtaining accurate high-resolution data from UAV images. Studies for identifying and minimising the challenges faced during the UAV-based RS data acquisition survey on inaccessible and harsh terrains of mountain glaciers is limited. This study aims to examine the practical challenges faced during UAV surveys of glaciers and derive strategies to minimize them. To the authors' knowledge, this is the first study that addresses such problems over the Himalayan region. Here, the UAV surveys were conducted using a fixed-wing commercial-grade off-the-shelf UAV (eBee plus, SenseFly) on three glacier sites (East Rathong, Hamtah and Panchinala-A) located in different zones and climate regimes lying within the Indian part of Himalayas. From UAV collected photos, the study was able to generate ultra-high-resolution ortho-mosaicked images and Digital Elevation Models (DEMs) at 0.1m GSD. UAV-derived DEMs was able to achieve vertical (horizontal) accuracy of 0.45 and 0.21 m (0.15 and 0.1 m) with 3 and 6 ground control points (GCPs) for an area of 0.75 km2 and 1.38 km2. Accuracy assessment of UAV DEMs generated with and without GCPs indicate that GCPs are must to obtain decimetre level accurate DEM especially on glaciers with steep-valleyed terrains. The utility of the obtained ultra-high-resolution ortho-mosaicked images was demonstrated by generating glacier surface feature maps. Based on the challenges observed during UAV surveys, the study identifies and recommends best-suited locations on a glacier and its adjacent regions for conducting UAV surveys efficiently in the glaciated terrain of Himalayas and possibly beyond. Recommendations reported in this article shall minimise the challenges faced and involved risks for data acquisition and thus enable UAVs to cover more glaciated area successfully.

The high environmental impact of conventional methods of cooling and heating has increased the need for renewable energy deployment for covering thermal loads. Towards that direction, the proposed system aims at offering an efficient solar powered alternative, coupling a zeolite-water adsorption chiller with a conventional vapor compression cycle. The system is designed to operate under intermittent heat supply of low-temperature solar thermal energy (<90 °C) provided by evacuated tube collectors. A prototype was developed and tested in cooling mode operation. The results of separate components testing showed that the adsorption chiller was operating efficiently, achieving a maximum coefficient of performance (COP) of 0.65. With respect to the combined performance of the system, evaluated on a typical week of summer in Athens, the maximum reported COP was approximately 0.575, mainly due to the lower driving temperatures at a range of 75 °C. The corresponding mean energy efficiency ratio (EER) obtained was 5.8.

Rough volatility models are popularized by \cite{gatheral2018volatility}, where they have shown that the empirical volatility in the financial market is extremely consistent with rough volatility. Fractional Riccati equation as a part of computation for the characteristic function of rough Heston model is not known in explicit form as of now and therefore, we must rely on numerical methods to obtain a solution. In this paper, we give a short introduction to option pricing theory and an overview of the current advancements on the rough Heston model.

In this review, we summarize the current state-of-the-art in the utilization of close-range sensing in forest monitoring. We include technologies, such as terrestrial and mobile laser scanning as well as unmanned aerial vehicles, which are mainly used for collecting detailed information from single trees, forest patches or small forested landscapes. Based on the current published scientific literature, the capacity to characterize changes in forest ecosystems using close-range sensing has clearly been recognized. Forest growth has been the most investigated cause for changes and terrestrial laser scanner the most applied sensor for capturing forest structural changes. Unmanned aerial vehicles, on the other hand, have been used to acquire aerial imagery for detecting tree height growth and monitoring forest health. Mobile laser scanning has not yet been used in forest change monitoring except for a few early investigations. Considering the length of the forest growth process, investigated time spans have been rather short, less than 10 years. In addition, data from only two time points have been used in many of the studies, which has further been limiting the capability of understanding dynamics related to forest growth. In general, method development and quantification of changes have been the main interests so far regardless of the driver of change. This shows that the close-range remote sensing community has just started to explore the time dimension and its possibilities for forest characterization.

Rodents are known to be reservoir hosts for at least 60 zoonotic diseases and are known to play an important role in their transmission and spreading in different ways. We sampled different rodent communities within and around human settlements in Northern Senegal, an area subjected to major environmental transformations associated with global changes. Herein, we conducted an epidemiological study on their bacterial communities.One hundred and seventy-one (171) invasive and native rodents were captured, 50 from outdoors trapping sites and 121 rodents from indoors habitats, consisting on 5 species. DNA of thirteen pathogens have been successfully screened on the rodent’s spleens. We found: 2.3% of positive spleens to Piroplasmida and amplified one which gives a potentially new species Candidatus “Theileria senegalensis”; 9.35% of Bartonella spp. and amplified 10, giving three genotypes. 3.5% of filariasis species; 18.12% of Anaplasmataceae species and amplified only 5, giving a new potential species Candidatus “Ehrlichia senegalensis”; 2.33 % of Hepatozoon spp.; 3.5% of Kinetoplastidae spp; and 15.2% of Borrelia spp. and amplified 8 belonging all to Borrelia crocidurae.Some of the species of pathogens carried by the rodents of our studied area may be unknown because most of those we have identified are new species. In one bacterial taxon, Anaplasma, a positive correlation between host body mass and infection was found. Overall, male and invasive rodents appeared less infected than female and native ones, respectively.

We introduce an information theoretic framework for a quantitative measure of originality to model the impact of various classes of biases, errors and error corrections on scientific research. Some of the open problems are also outlined.

Precipitation is a crucial driver for many environmental processes and weather radars are capable of providing precipitation information with high spatial and temporal resolution. However, radar-based quantitative precipitation estimates (QPE) are also subject to various potential uncertainties. This study explores the development, uncertainties and potentials of the hourly operational German radar-based and gauge-adjusted QPE called RADOLAN and its reanalysed radar climatology dataset named RADKLIM in comparison to ground-truth rain gauge data. The precipitation datasets are statistically analysed across various time scales ranging from annual and seasonal aggregations to hourly rainfall intensities in regard to their capability to map long-term precipitation distribution, to detect low intensity rainfall and to capture heavy rainfall. Moreover, the impacts of season, orography and distance from the radar on long-term precipitation sums are examined in order to evaluate dataset performance and to describe inherent biases. Results revealed that both radar products tend to underestimate total precipitation sums and particularly high intensity rainfall. But our analyses also showed significant improvements throughout the RADOLAN time series as well as major advances through the climatologic reanalysis regarding the correction of typical radar artefacts, orographic and winter precipitation as well as range-dependent attenuation.

There is a current worldwide outbreak of a new type of coronavirus (2019-nCoV), which originated from China and has now spread to 17 other countries. Governments are under increase pressure to stop the outbreak spiraling into a global health emergency. At this stage, preparedness, transparency and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak sites, and from laboratories supporting the investigation. This paper aggregates and consolidates the virology, epidemiology, clinical management strategies from both English and Chinese literature, official news channels and other official government documents. In addition, by fitting the number of infections with a single-term exponential model, we report that the infection is spreading at an exponential rate, with a doubling period of 1.8 days.

Modern life implies a constant exposure of living organisms to electromagnetic fields generated by human made technology. The question of whether or not electromagnetic fields in the non-ionizing frequency range can affect cellular functions, increasing the risk of cancer or another pathologies is currently a subject of interest for scientific community of several disciplines of physics, biology, chemistry and medicine. The first part of this short review presents briefly the possible mechanism of interaction of electromagnetic fields in cellular level based in theoretical models and experimental results. The second part refers to experimental observations published by several authors about the potential cytotoxic and genotoxic effects of electromagnetic fields. Results of researches are no yet conclusive enough to accept or reject the genotoxic, carcinogenic or cytotoxic potential of these fields. Up to date the International Agency for Research on Cancer (IARC) has classified the X, gamma and ultraviolet radiation as carcinogenic and the fields generated by radio frequencies as possibly carcinogenic.

Structural displacement is an important metric for assessing structural conditions because it has a direct relationship with the structural stiffness. Many bridge displacement measurement techniques have been developed, but most methods require fixed reference points in the vicinity of the target structure which limits field implementations. A promising alternative is to use reference-free measurement techniques that indirectly estimate the displacement by using measurements such as acceleration, and strain. This paper proposes novel reference-free bridge displacement estimation by the fusion of single acceleration with pseudo-static displacement derived from co-located strain measurements. First, we propose a conversion of the strain at the center of a beam into displacement based on the geometric relationship between strain and deflection curves with reference-free calibration. Second, an adaptive Kalman filter is proposed to fuse the displacement generated by strain with acceleration by recursively estimate the noise covariance of displacement from strain measurements which is vulnerable to measurement condition. Both numerical and experimental validations are presented to demonstrate the efficiency and robustness of the proposed approach.

Current therapeutic strategies targeting cancer cells within solid tumors have displayed limited success owing to the presence of non-cancer components referred to as the tumor stroma within the tumor microenvironment (TM). These stromal cells, extracellular matrix and blood vessels influence cancer cell response to therapy and play key roles in tumor relapse and resistance. Of the stromal cells present in the TM, a lot of attention has been given to cancer-associated fibroblasts (CAFs) as they are the most abundant and are important in cancer initiation, progression and therapy resistance. In this updated review I emphasize the role of CAFs in the regulation of tumor cell behaviour and reveal how CAF-derived factors and signaling influence tumor cell heterogeneity and development of novel strategies to combat cancer. To investigate the expression of CAF markers in tumor tissues versus normal tissues, transcriptomic data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) databases was used. Bioinformatic analysis reveals differential expression of CAF markers in several cancer types, underscoring the need for further multiomics and biochemical studies on CAFs, CAF subsets and markers. Differences in CAF markers’ expression could be due to different cellular origins as well as the effect of cancer-specific tumor microenvironmental effect on CAFs. Lastly, I present recent advances in therapeutic targeting of CAFs and the success of such endeavours or its lack thereof. It is recommended that for patients’ outcomes to improve, cancer treatment be combinatorial in nature, targeting both cancer cells and stromal cells and interactions.

This paper presents a review of the electrical heating method for heavy oil recovery based on past, current, and future prospects of electrical heating. Heavy oil is one of the potential crude oil used as a link to reduce the crisis of light oil used today. The obstacle of heavy oil is a high viscosity and density in which thermal injection is a method for heavy oil recovery, but it results in economic and environmental issues. Electrical heating is one of the thermal methods by transferring heat into the reservoir. The basic process of electrical heating is to increase the mobility of the oil. Because the temperature rises, it can reduce oil viscosity and makes it easier for heavy oil to flow. The past and current developments have been carried out to fill up the gap of electrical heating projects. The future prospects must meet energy efficiency, and the excessive heat will damage formation that must be tackled in the future prospect. the works adopt several electrical heating projects and applications in the world where the works give a brief future prospect of electrical heating.

The World Health Organization(WHO) in 2016 considered mHealth as: “the use of mobile wireless technologies including smart devices such as smartphones and smartwatches for public health” as an important resource for health services delivery and public health given their ease of use, broad reach and acceptance. WHO emphasizes the potential of this technology to increase access to health information, services and skills as well as promoting positive changes in health behaviors and management of diseases. In this regard, the capability of smartphones and smartwatches for m-health monitoring as well as verification of the patient the signal has become an important component of mHealth system. Most of the smartwatches could extract more than one bioelectrical signal therefore, therefore they provide suitable platform for extracting health data for e-monitoring. The existing approaches have not considered the integrity of data obtained from these smart devices. Therefore, it is important that the integrity of the collected data be verified continuously through user authentication. This could be done using any of the bioelectrical signals extracted and transmitted for e-monitoring. In this article, a smartwatch is used for extracting bioelectrical signal before decomposing the signal into sub-bands of Detail and Approximation Coefficient for user authentication. To select suitable features using biorthogonal wavelet decomposition of signal from a non-intrusive extraction, a detailed experiment is conducted extracting suitable statistical features from the bioelectrical signal from 30 subjects using different biorthogonal wavelet family. Ten features are extracted using Biorthogonal wavelet to decompose the signal into three levels of sub-band Detail and Approximation Coefficient and features extracted from each level the decomposed Detail and Approximation Coefficients. Comparison analysis is done after the classification of the extracted features based on the Equal Error Rate (EER). Using Neural Network (NN) classifier, Biorthogonal Wavelet Detail Coefficient Sub-band level 3 of bior1.1 achieved the best result of EER 13.80% with the fusion of the best sub-band three levels of bior1.1 achieving a better result of 12.42% EER.

Many physiotherapy treatments begin with a diagnosis process. The patient describes symptoms, upon which the physiotherapist decides which tests to perform until a final diagnosis is reached. The relationships between the anatomical components are too complex to keep in mind and the possible actions are abundant. A trainee physiotherapist with little experience naively applies multiple tests to reach the root cause of the symptoms, which is a highly inefficient process. This work proposes to assist students in this challenge by presenting three main contributions: (1) A compilation of the neuromuscular system as components of a system in a Model-Based Diagnosis problem; (2) The PhysIt is an AI-based tool that enables an interactive visualization and diagnosis to assist trainee physiotherapists; and (3) An empirical evaluation that comprehends performance analysis and a user study. The performance analysis is based on evaluation of simulated cases and common scenarios taken from anatomy exams. The user study evaluates the efficacy of the system to assist students in the beginning of the clinical studies. The results show that our system significantly decreases the number of candidate diagnoses, without discarding the correct diagnosis, and that students in their clinical studies find PhysIt helpful in the diagnosis process.

In this short note, the described step-by-step derivations of the industrial energy demand function from the production function framework and provided researchers with two specifications. Then we applied these theoretical specifications to the time series data as empirical analysis. We concluded that theories should be considered at the beginning of the empirical analyses but the data also should be allowed to speak freely. Hence, the main suggestion of this short note is that it would be a better strategy to consider the combination of theory-driven and data-driven approaches in the empirical analyses.

This article aims to discuss, the stability and boundedness character of the solutions of the rational equation of the form \begin{equation}\label{eql21.1} y_{t+1}=\frac{\nu\epsilon^{-y_t}+\delta\epsilon^{-y_{t-1}}}{\mu+\nu y_t+\delta y_{t-1}},\quad t\in N(0). \end{equation} Here, $\epsilon>1, \nu,\delta,\mu\in (0,\infty)$ and $y_0, y_1$ are taken as arbitrary non-negative reals and $N(a)=\{a,a+1,a+2,\cdots \}$. Relevant examples are provided to validate our results. The exactness is tested using MATLAB.

Carcinus maenas (the “shore crab” or “European green crab”) is a very proficient invader (considered to be one of the world’s 100 worst invaders by the IUCN) due to its phenotypic plasticity, wide temperature and salinity tolerance, and an extensive omnivorous diet. Native to Atlantic Europe, it has established two well‐studied nonindigenous populations in the northwestern Atlantic and northeastern Pacific and less‐studied populations in Australia, Argentina and South Africa. Green crabs are eurythermal and euryhaline as adults, but they are limited to temperate coastlines due to more restrictive temperature requirements for breeding and larval development. They cannot tolerate wave‐swept open shores so are found in wave‐protected sheltered bays, estuaries and harbors. Carcinus maenas has been the subject of numerous papers, with over 1000 published in the past decade. This review provides an up‐to‐date account of the current published information on the life history and population dynamics of this very important species, including genetic differentiation, habitat preferences, physical parameter tolerances, reproduction and larval development, sizes of crabs, densities of populations, sex ratios, ecosystem dynamics and ecological impacts in the various established global populations of green crabs.

Integrated Model of Distributed Systems is used for modeling and verification. In formalism, the distributed system is modeled as a collection of server states and agent messages. The evolution of the system takes the form of actions that transform the global system configuration (states and messages) into a new configuration. Formalism is used in the Dedan verification environment for finding different kinds of deadlocks: communication deadlocks in the server view and resource deadlocks in the agent view. For other purposes, a conversion has been developed to equivalent models: to Petri nets for structural analysis and do Distributed Autonomous and Asynchronous Automata (DA3) for easy graphical modeling in terms of system components. In addition, it is possible to simulate a verified system on distributed components in DA3. The automata have two forms: Server-DA3 (S-DA3) for the server view and Agent-DA3 (A-DA3) for the agent view. DA3 formalism is compared to other concepts of distributed automata known from the literature.

Transient receptor potential canonical (TRPC) channels are ubiquitously expressed in excitable and non-excitable cardiac cells where they sense and respond to a wide variety of physical and chemical stimuli. As other TRP, TRPC may form homo or heterotetrameric ion channel, and they can associate with other membrane receptors and ion channels to regulate intracellular calcium concentration. Dysfunctions of TRPC channels are involved in many types of cardiovascular diseases. Significant increase of the expression of different TRPC isoforms has been observed in different animal model of heart infarcts, and in vitro experimental model of ischemia and reperfusion. TRPC-mediated increase of the intracellular Ca²⁺ concentration seems required for the activation of signaling pathway that plays minor roles in the healthy heart, but they are more relevant for cardiac responses to ischemia, such as the activation of different factors of transcription and cardiac hypertrophy, fibrosis, and angiogenesis. In this review, we will highlight the current knowledge regarding TRPC implication in different cellular processes related to ischemia and reperfusion, and to heart infarction.

The need to consider sustainability has substantially increased the complexity of implementing construction and infrastructure projects and new management practices have emerged during the past decade to tackle the global sustainability challenges, where the engagement and coordination of broader competences from stakeholders throughout the supply chain is required. This new project management paradigm has been accompanied by greater attention to the concept of collaborative business arrangements, often called partnering, that has emerged in construction and infrastructure projects to improve project deliveries. However, there are uncertainties about the optimal strategy to foster, integrate and maintain the required collaboration, particularly in sustainable management practices in infrastructure maintenance projects. This paper addresses these uncertainties, based on a single case study of an infrastructure maintenance contract involving an extensive collaborative business arrangement. The findings reveal that different collaborative practices affect diverse aspects of sustainable project management. Further, the extensive collaborative business arrangement has promoted sustainable deliveries based upon organizational learning and continuous improvements. Thus, this study offers an encouraging example of how extensive collaboration can be fostered and play a key role in sustainable project management practices.

An application of deep convolutional neural network and recurrence plot for financial market movement prediction is presented. Though it is challenging and subjective to interpret its information, the pattern formed by a recurrence plot provide a useful insight into the dy- namical system. We used a recurrence plot of seven financial time series to train a deep neural network for financial market movement predic- tion. Our approach is tested on our dataset and achieved an average of 53.25% classification accuracy. The result suggests that a well trained deep convolutional neural network can learn a recurrence plot and pre- dict a financial market direction.

In this paper we show how to efficiently implement parallel discrete simulations on Multi-Core and GPU architectures through a real example of application: a cellular automata model of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with48cores and also an NVIDIA Tesla6V100 GPU, both running on Amazon Web Server (AWS) Cloud, and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results are compared and analysed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current Multi-Core CPUs with large core numbers can bring a performance very near to that of GPUs, even similar in some cases.

Purpose of this article is to introduce a modification of Phillips operators on the interval $\left[ \frac{1}{2}% ,\infty \right) $ via Dunkl generalization. This type of modification enables a better error estimation on the interval $\left[ \frac{1}{2},\infty \right) $ rather than the classical Dunkl Phillips operators on $\left[ 0,\infty \right) $. We discuss the convergence results and obtain the degrees of approximations. Furthermore, we calculate the rate of convergence by means of modulus of continuity, Lipschitz type maximal functions, Peetre's $K$-functional and second order modulus of continuity.

Gifted students are usually known as students who have exceptional cognitive and learning abilities. This can be made clear through their learning performance or test scores. However, there are other students who have been identified as gifted and talented, yet have some learning and /or physical disabilities, and these are called twice-exceptional students. Identifying this population of gifted students is usually problematic because their disabilities and difficulties may mask their abilities and vice versa. It has been suggested that twice-exceptional students’ skills and abilities cannot be improved simply by working harder. Instead, these students need teachers to understand their strengths and weaknesses, use teaching strategies that fit their disabilities and serve their needs, and include their parents and educators in their learning process. Thus, this conceptual paper provides an extensive overview of the needs, challenges, and teaching strategies related to twice-exceptional students.

We investigate alternative candidates to dark energy that can explain the current state of the universe in the framework of the generalized teleparallel theory of gravity f(T ) where T denotes the torsion scalar. To achieve this, we carried out a series of reconstruction taking into account to the ordinary and entropy-corrected versions of the holographic and new agegraphic dark energy models. These models used as alternative to dark energy in the literature in order describe the current state of our universe. It is remarked that the models reconstructed indicates behaviors like phantom or quintessence models. Furthermore, we also generated the EoS parameters associated to entropy-corrected models and we observed a transition phase between quintessence state and phantom state as showed by recent observational data. We also investigated on the stability theses models and we created the {r − s}. The behavior of certains physical parameters as speed of sound and the Statefinder parameters are compatible with current observational data.

The largest impact of needle diseases in the recorded history of Pinus radiata and Pinus nigra plantations in the North of Spain, was from 2018 to 2019. The severity of the disease has led to a serious reconsideration of forest management in the area. The main pathogens involved in this historical outbreak were Lecanosticta acicola and Dothistroma septosporum. Three arboreta were established under the European project REINFFORCE in the Basque Country in recently harvested P. radiata plantations. The plants for the arboreta were produced in nurseries located in the Alps of Upper Provence (France). These arboreta were surrounded by plantations seriously damaged by L. acicola and D. septosporum. The Pinus species which were sampled in the arboreta included P. brutia (4 provenances), P. elliottii (2 provenances), P. nigra (8 or 9 provenances), P. pinaster (7 provenances), P. pinea (6 provenances), P. ponderosa (3 provenances), P. sylvestris (8 provenances) and P. taeda (3 provenances). Lecanosticta acicola is reported for the first time infecting Pinus brutia (Provenance: Alexandropolis, Greece and var. eldarica, Crimea), a new host species for this pathogen. Pinus elliottii (Provenance: Georgia, USA) and P. ponderosa (Provenance: Central California, USA) are new host reports of L. acicola for Spain. Dothistroma septosporum was found for the first time on P. brutia (Provenance: Marmaris, Turkey) and P. ponderosa (Provenance: Oregon, USA) in Spain and was also detected infecting P. nigra (Provenance: Slogne Vayrières, France).

This paper addresses the issues of how we can quantify structural information for nonparametric distributions and how we can detect its changes. Structural information refers to an index for a global understanding of a data distribution. When we consider the problem of clustering using a parametric model such as a Gaussian mixture model, the number of mixture components (clusters) can be thought of as structural information in the model. However, there does not exist any notion of structural information for nonparametric modeling of data. In this paper we introduce a novel notion of {\em kernel complexity} (KC) as structural information in the nonparametric setting. The key idea of KC is to combine the information bias inspired by the Gini index with the information quantity measured in terms of the normalized maximum likelihood (NML) code length. We empirically show that KC has a property similar to the number of clusters in a parametric model. We further propose a framework for structural change detection with KC in nonparametric distributions. With synthetic and real data sets we empirically demonstrate that our framework enables us to detect structural changes underlying the data and their early warning signals.

Over the past few years, we have experienced great technological advancements in the information and communication field, which has significantly contributed to reshaping the Intelligent Transportation System (ITS) concept. Evolving from the platform of a collection of sensors aiming to collect data, the data exchanged paradigm among vehicles is shifted from the local network to the cloud. With the introduction of cloud and edge computing along with ubiquitous 5G mobile network, it is expected to see the role of Artificial Intelligence (AI) in data processing and smart decision imminent. So as to fully understand the future automobile scenario in this verge of industrial revolution 4.0, it is necessary first of all to get a clear understanding of the cutting-edge technologies that going to take place in the automotive ecosystem so that the cyber-physical impact on transportation system can be measured. CIoV, which is abbreviated from Cognitive Internet of Vehicle, is one of the recently proposed architectures of the technological evolution in transportation, and it has amassed great attention. It introduces cloud-based artificial intelligence and machine learning into transportation system. What are the future expectations of CIoV? To fully contemplate this architecture’s future potentials, and milestones set to achieve, it is crucial to understand all the technologies that leaned into it. Also, the security issues to meet the security requirements of its practical implementation. Aiming to that, this paper presents the evolution of CIoV along with the layer abstractions to outline the distinctive functional parts of the proposed architecture. It also gives an investigation of the prime security and privacy issues associated with technological evolution to take measures.

In this review article, the occurrence of nor-lignans and their biological activities are explored and described. Nor-lignans have proven to be present in several different families also belonging to chemosystematically distant orders as well as to have many different beneficial pharmacological activities. This review article represents the first one on this argument and is thought to give a first overview on these compounds with the hope that their study may continue if not raise after this.

This study was undertaken to elucidate the role of trehalose (Tre) in mitigating oxidative stress under salinity and low P in maize. Eight-day-old maize seedlings of two maize varieties, BARI Hybrid Maize-7 and BARI Hybrid Maize-9 were subjected to salinity (150 mM NaCl), low P (5 µM KH2PO4) and their combined stress with or without 10 mM Tre for 15-d.Salinity and combined stress significantly inhibited the shoot length, root length, and root volume, whereas, low P increased the root length and volume in both genotypes. Exogenous Tre in the stress treatments increased all of the growth parameters as well as decreased the salinity, low P and combined stress-mediated Na+/K+, ROS, MDA, LOX activity and MG in both genotypes. Under salinity and low P stress, the SOD activity increased in both genotypes, but the activity decreased in combined stress. POD activity increased in all stress treatments. Interestingly, Tre application enhanced the SOD activity in all the stress treatments but inhibited the POD activity. Both CAT and GPX activity were increased by saline and low P stress while the activities inhibited in combined stress. Similar results were found for APX, GR, and DHAR activities in both genotypes. However, MDHAR activity was inhibited in all the stresses. Interestingly, Tre enhanced CAT APX, GPX, GR, MDHAR and DHAR activities suggesting the amelioration of ROS scavenging in maize under all the stresses. Increased GST activity in presence or absence of Tre might involve in detoxification of hydroperoxides as well as leaf senescence. On the other hand, increased glyoxalase activities in saline and low P stress in BHM-9 suggested better MG detoxification system because of down-regulation of Gly-I activity in BHM-7 in those stresses. Tre also increased the glyoxalase activities in both genotypes under all the stresses. Tre improved the growth in maize seedlings by decreasing Na+/K+, ROS, MDA, and MG through regulating antioxidant and glyoxalase systems.

Mapping short-term wetland vegetation and water storage changes is valuable for monitoring the biogeochemical processes of wetland systems. Old Woman Creek National Estuarine Research Reserve is a dynamic freshwater estuary that experiences intermittent changes in water level over the course of a year. Small unmanned aerial systems (sUAS) are useful tools in monitoring changes as they are rapidly deployed, repeatable, and high-resolution. In this study, commercial quadcopters were paired with a red/green/near-infrared MAPIR Survey 3W camera to produce normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) maps to observe short-term changes at OWC. Orthomosaics were produced for flights on 8 days throughout 2018 and early 2019. The orthomosaics were calibrated to bottom-of-atmosphere reflectance using the Empirical Line Correction method and NDVI and NDWI maps were created. The NDVI pixel values were used to generate maps of vegetation extent showing density changes over time. Identifying dominant vegetation in these maps allowed for the application of the National Estuarine Reserve System (NERRS) Classification Codes to zones of interest. NDWI provided water extent at different water levels and when paired with LiDAR and bathymetric data yielded water volume and residence time estimates. The produced maps contribute to the overall understanding of habitats affected by water inundation variations.

Zika virus (ZIKV) co-circulates with several closely related flaviviruses which exhibit similar clinical manifestations thus, clinicians rely on molecular and serological techniques for diagnosis. Cross-reactivity of patient specimens to flaviviruses is a significant impediment to serological diagnosis in areas where multiple flaviviruses co-circulate. Furthermore, patient exposure history to any of these viruses could complicate serological response patterns which could result in over and/or underdiagnosis of ZIKV infection. Three strains of ZIKV, dengue serotypes 1-4, West Nile virus, Japanese Encephalitis virus, and Yellow Fever virus were evaluated for neutralizing properties against 3 monoclonal antibodies, 4 ZIKV-naïve patients with flavivirus exposure history, 5 patients with verified ZIKV exposure and unknown flavivirus exposure history, and 5 flavivirus-naive patients with ZIKV-only exposure. Patients naïve for ZIKV exposure effectively neutralized multiple strains of ZIKV. Overall, the prototype ZIKV isolate MR-766 did not behave like the other ZIKV isolated used in this study. MR-766 was neutralized more completely by polyclonal patient serum than recent ZIKV isolates. MR-766 was neutralized better than dengue virus in ZIKV-naïve patients with prior dengue exposure. MR-766 was neutralized significantly less than recent ZIKV isolates when treated with monoclonal antibodies. The data herein show that without RT-PCR, serological diagnosis may not be possible in areas where multiple flaviviruses are endemic.

Pig genetic resources in Africa originate from different regions. Genetic analysis has shown a strong phylogeographic pattern with the pigs on the eastern parts showing a high frequency of alleles from the Far East while the ones on the western parts show a strong European influence. This highlights the influence of trade routes on the genetic legacy of African pigs. They have, however, since adapted to the local environments to produce unique populations with unique attributes. Most of the pigs are now reared in resource-constrained smallholdings under free-range conditions. They are largely owned by women who spread ownership of the resource through kinship networks. Very little work has been done to characterize, conserve and sustainably utilize pig genetic resources in Southern Africa. The risk status of the breeds together with population numbers, distribution and other attributes are largely unknown. This paper proposes several strategies for the sustainable utilization of the pig genetic resources: a market-driven in situ conservation program and two complementary ex situ strategies. In addition, the possibility of community-based breed improvement programs is discussed.

In this study, the author proposes to evaluate the effect of sales growth, Receivable Turnover and operating cash flow on the liquidity of PT. Unilever Indonesia Plc. The research method used is descriptive method with a quantitative approach. In this statement, the population used in this study is the financial statement data from PT. Unilever Indonesia Plc. from 2010 to 2018, the technique of determining the sampling uses Purposive Sampling. This research data uses secondary data from PT. Unilever Indonesia Plc financial statements from 2010 to 2018. All data sources were obtained from the website of the Indonesia Stock Exchange at https://www.idx.co.id, the company's website and Google search. Our analysis reveals that sales growth and accounts receivable turnover from PT. Unilever Indonesia Plc. has no influence on the liquidity of PT. Unilever Indonesia Plc, while operating cash flow has an influence on the Liquidity of PT Unilever Indonesia Plc. This means the ups and downs of the value of sales and accounts receivable turnover of a company has no influence on the liquidity of PT. Unilever Indonesia Plc, while operating cash flow has increased or decreased has an influence on the liquidity of PT Unilever Indonesia Plc. The value of sales growth, accounts receivable turnover and operating cash flow can explain the liquidity of PT Unilever Indonesia Plc. by 78%, while 22% is explained by other factors which are not included in this study.

Tryptanthrin has not been widely applied in clinical practice due to its poor solubility and low bioavailability in spite of possessing several biological and pharmacological activities. Here, to improve the solubility of tryptanthrin, two types of novel tryptanthrin-loaded micelles were prepared. One was tryptanthrin physically encapsulated by distearoyl phosphatidylethanolamine polyethylene glycol (DSPE-PEG) and the other was pegylated tryptanthrin synthesized by acid-sensitive hydrazone bond and further prepared as micelles. Molecular imprinting technology was used to separate pegylated tryptanthrin and free mPEG-COOH in the preparation of PEGylated tryptanthrin micelles with considerably high separation efficiency. The solubility of tryptanthrin-loaded DSPE-PEG micelles (TDMs) and PEGylated tryptanthrin micelles (PTMs) was increased by 300 and 1493 fold compared with that of tryptanthrin, respectively. The PTMs increased the solubility of tryptanthrin more effectively and 95% of tryptanthrin was released from PTMs at pH 5.5 in 12 h. The cytotoxicity of PTMs decreased under physiological conditions compared with that of tryptanthrin, whereas at pH 5.5, the PTMs showed comparable cytotoxicity with that of tryptanthrin, indicating successful drug release from the carrier in response to tumor cell pH. Overall, we elucidated an efficient method to improve water solubility of tryptanthrin and indicated pegylated tryptanthrin is a promising prodrug.

Recent works in mechanical fatigue consider that a threshold of entropy exists, the fracture fatigue entropy. The determination of this quantity is usually done considering empirical models for the mechanical power estimation. In this paper, we experimentally observe the existence of a threshold of entropy and exergy in low cycle fatigue for a flat Al-2024 specimen avoiding the use of a model, solely measuring the heat generated during a fatigue test. Results are then compared considering various hypotheses (1D heat dissipation with convection and radiation considered as heat sources, and, heat transfer from a fin with convection and radiation as boundary conditions) to an empirical mechanical model known in the literature and deviations between them are discussed.

In our recently proposed theory of quantum gravity, a black hole arises from the spontaneous localisation of an entangled state of a large number of atoms of space-time-matter [STM]. Prior to localisation, the non-commutative curvature of an STM atom is described by the spectral action of non-commutative geometry. By using the techniques of statistical thermodynamics from trace dynamics, we show that the gravitational entropy of a Schwarzschild black hole results from the microstates of the entangled STM atoms and is given (subject to certain assumptions) by the classical Euclidean gravitational action. This action, in turn, equals the Bekenstein-Hawking entropy (Area/$4{L_P}^2$) of the black hole. We argue that spontaneous localisation is related to black-hole evaporation through the fluctuation-dissipation theorem.

Immobilization of enzymes is a good field of study to expand the life of enzyme in and lowering the cost of the chemical processes such as separation processes. Urease is an important enzyme with medical and industrial applications. The aim of the present study is to prepare an immobilized urease on a strong cation exchange resin (Amberlite IR120 -Na) and study of its activity and stability. We monitored the liberation of Na ions in the collected fractions and searching for protein in the fractions as an indicators of immobilization by ion exchange phenomenon. Sodium is measured using atomic absorption spectroscopy techniques, while protein tested by Bradford’s method. Immobilized urease activity was evaluated by salicylate-hypochlorite method. The results indicated a complete immobilization of urease enzyme on the resin surface with reserving 92% of the activity of free enzyme. The immobilized urease enzyme on resin showed good stability and it has a 62% of its activity after 154 days of storage at room temperature. It is concluded that a new immobilized urease enzyme system is prepared with good enzyme activity and stability.

In this paper, we investigate the equilibrium points of following a system of difference equations x_n+1 = x_n 2y_n−1, y _n+1 = y_n 2x_n−1. We also study the asymptotic stability of related system of difference equations. Further we examine the periodic solutions of related system with period two. Additionally, we find out the invariant interval and periodic cycles of related system of difference equations.

The aim of this paper is the presentation of an analytical model of insulator flashover and its application for air at atmospheric pressure and pressurized SF6. After a review of the main existing models in air and compressed gases, we develop a relationship of flashover voltage on the basis of an electrical equivalent circuit and the thermal properties of the discharge. The model includes the discharge resistance, the insulator impedance, and the gas interface impedance. The application of this model to a cylindrical resin-epoxy insulators in air medium and SF6 gas with different pressures gives results close to the experimental measurements.

There is an important complementarity between experimental methods for the study of high-temperature viscoelasticity in the time and frequency domains, that has not always been fully exploited. Here we show that parallel processing of forced-oscillation data and microcreep records, involving consistent use of either Andrade or extended Burgers creep-function models, yields a robust composite modulus-dissipation dataset spanning a broader range of periods than either technique alone. In fitting this dataset, the alternative Andrade and extended Burgers models differ in their partitioning of strain between the anelastic and viscous contributions. The extended Burgers model is preferred because it involves a finite range of anelastic relaxation times, and accordingly a well-defined anelastic relaxation strength. The new strategy offers the prospect of better constraining the transition between transient and steady-state creep, or equivalently, between anelastic and viscous behaviour.

In an attempt to correct misunderstandings this article brings together the observations on Calcium, Myosin Binding Protein-C and Hypertrophic Cardiomyopathy in the basic function of cardiac muscle. A finding of many years ago is reiterated in a novel enzyme kinetic format with defined rate limiting step which makes CaATP the apparent substrate of the actomyosin cross-bridge. The relationship of these kinetics to recent observations on disruption of myosin binding protein-C is described along with how this bears on the understanding of the related cardiomyopathies.

Importance: Because of the high prevalence of myopia in Taiwan, understanding the risk factors for its development and progression is important to public health. Background: This study investigated the risk factors for myopia and their influence on the progression of myopia in schoolchildren in Taiwan. Design: Patients’ clinical records were obtained retrospectively from ophthalmologists. Questionnaires were given to collect demographic information, family background, hours spent on daily activities, myopia progression, and treatment methods. Participants: A total of 522 schoolchildren with myopia from a regional medical hospital in northern Taiwan participated the study. Written informed consent was obtained from the participants of legal age or the parents or legal guardians. Methods: Multivariable regression analyses were performed. Myopia measured in dioptres was analysed, controlling for patients’ family and demographic information as well as their daily behaviours. Main Outcome Results: Children with high myopic parents were more myopic. Earlier onset age of myopia was associated with a higher level of myopia and greater annual myopic progression. Children reporting more near work activities had higher levels of myopia and greater progression of myopia. Lower levels of myopia were associated with more exercise, longer periods of sleep, and better vision care knowledge in children and parents. Intake of food supplements had no effect on myopia. Conclusions and Relevance: In addition to genetics, education, environment, and near work activity can influence the development of myopia. Health policies for schoolchildren should promote protective activities and vision care knowledge in order to protect the eyesight of schoolchildren.

Polymeric particles made up of biodegradable and biocompatible polymers such as poly(lactic-co-glycolic acid) (PLGA) are promising tools for several biomedical applications including drug delivery. Particular emphasis is placed on the size and surface functionality of these systems as they are regarded as the main protagonists in dictating the particle behavior in vitro and in vivo. Current methods of manufacturing polymeric drug carriers offer a wide range of achievable particle sizes, however, they are unlikely to accurately control the size while maintaining the same production method and particle uniformity, as well as final production yield. Microfluidics technology has emerged as an efficient tool to manufacture particles in a highly controllable manner. Here, we report on tuning the size of PLGA particles at diameters ranging from sub-micron to microns using a single microfluidics device, and demonstrate how particle size influences the release characteristics, cellular uptake and in vivo clearance of these particles. Highly controlled production of PLGA particles with ~100 nm, ~200 nm and >1000 nm diameter is achieved through modification of flow and formulation parameters. Efficiency of particle uptake by dendritic cells and myeloid-derived suppressor cells isolated from mice is strongly correlated with particle size and is most efficient for ~100 nm particles. Particles systemically administered to mice mainly accumulate in liver and ~100 nm particles are cleared slower. Our study shows the direct relation between the particle size varied through microfluidics and the pharmacokinetics behavior of particles, which provides a further step towards the establishment of a customizable production process to generate tailor-made nanomedicines.

Understanding the physical properties of ultramafic rocks is important for evaluating awide variety of petrologic models of the oceanic lithosphere, particularly upper mantle and lower crust. Hydration of oceanic peridotites results in increasing serpentine content, which affects lithospheric physical properties and the global bio/geochemical cycles of various elements. In understanding tectonic, magmatic and metamorphic history of the oceanic crust, interpreting seismic velocities, rock composition and elastic moduli are of fundamental importance. In this study we show that as serpentine content increases, density decreases linearly with a slope of 7.85. We also correlate increase in serpentine content with a linear decline in shear, bulk and Young’s moduli with slopes of 0.48, 0.77, 0.45 respectively. Our results show that increase in serpentine content of lower crust and forearc mantle could decrease elasticity of lithospehere and result in break-offs. Therefore tectonic processes at peridotite rich slow spreading ridges may be strongly affected by serpentine content, particularly serpentinization may be responsible for discontinuities in thin crust, and formation of weak fault zones.

The study focused on two climatic variables i.e. precipitation and stream flow for analysing change in trend of rainfall for the River Ssezibwa Catchment area and stream flow of River Ssezibwa. This Catchment is found in the districts of Mukono and Buikwe in Uganda. In this area agriculture is majorly dependent on rainfall and irrigation on a small scale. However, rainfall occurrence has become unpredictable over the past few years as result of the changes in patterns of weather. This has caused severe effects on the agricultural cropping system as well as caused negative effects on the natural water resources. Stream flow data of 57 years (1960 – 2017) and rainfall data for 35 years (1982 – 2017) on a daily basis was analysed to find out the trend and detect change point. Trend analysis was done by using the non-parametric analysis while the change point detection was carried out by using the Pettit test (1979).Magnitude of trend for the time series data was carried out using Sen’s Slope estimator and Mann – Kendall test was done to determine the trend. Results from the statistical analysis highlighted that; for stream flow the trend was generally positive and change point detected to be in the year 2000 while for rainfall data analysis indicated that the trend was predominantly negative and change point was in the year 1998.

Viruses are the major causes of acute and chronic infectious diseases in the world. According to the World Health Organization, there is an urgent need for better control of viral diseases. Re-purposing existing antiviral agents from one viral disease to another could play a pivotal role in this process. Here we identified novel activities of obatoclax and emetine against herpes simplex virus type 2 (HSV-2), human immunodeficiency virus 1 (HIV-1), echovirus 1 (EV1), human metapneumovirus (HMPV) and Rift Valley fever virus (RVFV) in cell cultures. Moreover, we demonstrated novel activities of emetine against influenza A virus (FluAV), niclosamide against HSV-2, brequinar against HIV-1, and homoharringtonine against EV1. Our findings may expand the spectrum of indications of these safe-in-man agents and reinforce the arsenal of available antiviral therapeutics pending the results of further in vivo tests.

Poverty alleviation is a hallmark of post-revolution Chinese policymaking. Since 1978, the Communist Party of China (CPC) has implemented successive waves of poverty alleviation policies whose effects have become the focus of an ever-increasing body of academic literature. This paper reviews this diverse but limited literature that evaluates the impact of the CPC’s poverty reduction programs through four major channels, namely fiscal investment programs, social safety nets, rural governance on the village-, county- and provincial level, and the relocation of rural populations from destitute regions. This paper aims to synthesize results and evaluate whether and how the abovementioned poverty alleviation programs have had distinct positive or negative impacts on regional development outcomes. Furthermore, I highlight contradictions in empirical findings to motivate the discussion about contextual importance when designing and implementing future poverty alleviation programs. Finally, I suggest that an exhaustive and critical appraisal of the empirical strategies used in this literature would further the development and application of more accurate and informative methodologies.

Sorafenib is an oral kinase inhibitor that enhances survival in patients affected by advanced hepatocellular carcinoma (HCC). According to the results of two registrative trials, this drug represents a gold quality standard in the first line treatment of advanced HCC. Recently, lenvatinib showed similar results in terms of survival in a non-inferiority randomized trial study considering the same subset of patients. Unlike other targeted therapies, currently predictive and prognostic markers in HCC patients treated with sorafenib are lacking. Their identification could help clinicians in the daily management of these patients, mostly in light of the new therapeutic options available in the first.

Osteoimmunology was coined about twenty years ago to identify a strict cross talk between bone niche and immune system both in physiological and pathological activities, including cancer. Several molecules are involved in the complex interaction between bone niche, immune and cancer cells. The Receptor Activator ok NF-kB (RANK)/RANK Ligand (RANKL/Osteoprotegerin (OPG) pathway plays a crucial role in bone cells/cancer interactions with subsequently immune system control failure, bone destruction, inhibition of effect and metastasis outcome. The bidirectional cross talk between bone and immune system could became a potential target for anticancer drugs. Several studies evidenced a direct anticancer role with improved survival of bone-targeted therapies such as bisphosphonates and RANKL antagonist Denosumab. Conversely, initial data evidenced a possible anti-bone resorption effect of systemic anticancer drugs through and immunomodulation activity, i.e. new generation antiandrogens (Abiraterone) in prostate cancer. All data could open a future rationale of combined bone, immunologic and targeted therapies in cancer treatment.

Super-Resolution Microscopy enables non-invasive, molecule-specific imaging of the internal structure and dynamics of cells with sub-diffraction limit spatial resolution. One of its major limitations is the requirement for high-intensity illumination, generating considerable cellular phototoxicity. This factor considerably limits the capacity for live-cell observations, particularly for extended periods of time. Here, we overview new developments in hardware, software and probe chemistry aiming to reduce phototoxicity. Additionally, we discuss how the choice of biological model and sample environment impacts the capacity for live-cell observations.

The protection of electronics against environmental influences and mechanical loads is important for integration of conventional electronics in textile conductive tapes. For this purpose, the sensors on the tapes are molded with plastic locally. This process step is recognized in the injection molding process. The molding compound is then later selected depending on: The field of application, the parameters of the manufacturing process and the textile tape properties. We have designed a mould for liquid silicone (LSR) as well as for the textile and electronic insertions. The cavities are sealed by a local compression of the textile and the two inserts are positioned with position pins representing the main aspect of the mould design. The sampling tool and the process parameter optimization are mainly based on the material properties of the silicone and the mechanical sensitivity of the inserts. To reduce the deformation of the circuit boards by the melt front and ensuring the functionality of the electronics a low-pressure process is used.

This study aims to evaluate the patient’s dose exposure from Computed Tomography Pulmonary Angiography (CTPA) examination and to estimates the cancer risk induced from the examinations based on the patient’s size. One hundred patients were recruited, and data information was collected retrospectively. A multi-detector (MDCT) (Philips Brilliance 128, USA) scanner were utilized for the CTPA examination, and dose data were obtained from the system. The effective diameter of each subjects’ image was measured for the Size-specific dose estimates (SSDEs). All subjects divided into Group 1 (19 – 25 cm), Group 2 (25-28 cm) and Group 3 (28-38 cm), where the association between gender were analysed. Effective dose (E), SSDE, organ dose and cancer risk of each group were evaluated and compared statistically using independent t-test and one-way ANOVA. The range of mean CTDI_vol, DLP and E values were (6.44 – 17.42 mGy), (239 – 631 mGy), (5.19 – 13.90 mSv), respectively. In respective with the patient’s effective diameter, the mean SSDE value for Group 1, Group 2 and Group 3 were 9.93 ± 3.89 mGy, 13.70 ± 9.04 mGy and 22.29 ± 7.35 mGy. The organ dose and cancer risk attained for breast, lung and liver were 17.05 ± 10.40 mGy (194 per one million procedure), 17.55 ± 10.86 mGy (192 per one million procedure) and 15.04 ± 9.75 mGy (53 per one million procedure), respectively. Lung and breast with more massive patient’s effective diameter received the highest dose exposure which increases the probability of the cancer risk. CTDI_vol was found to be underestimated, and SSDE provides more accurate in describing the radiation dose and cancer risk. Body effective diameter found to be significant on the estimation except for gender. Therefore, it is essential to apply optimised protocols in order to reduce patient’s exposure during CTPA examination.

In this paper, we derive multifarious relationships among the two types of higher order q-Daehee polynomials and p-adic gamma function via Mahler theorem. Also, we compute some weighted p-adic q-integrals of the derivative of p-adic gamma function related to the Stirling numbers of the both kinds and the q-Bernoulli polynomials of order k.

The conventional machine learning (ML) algorithms are continuously advancing and evolving at a fast-paced by introducing the novel learning algorithms. ML models are continually improving using hybridization and ensemble techniques to empower computation, functionality, robustness, and accuracy aspects of modeling. Currently, numerous hybrid and ensemble ML models have been introduced. However, they have not been surveyed in a comprehensive manner. This paper presents the state of the art of novel ML models and their performance and application domains through a novel taxonomy.

Background: Peroxiredoxins (Prxs) comprise antioxidant factors that are widely found in prokaryotes and eukaryotes. Abnormal expression of Prxs is closely related to tumorigenesis. Methods: This study examined the prognostic value and expression of Prxs in lung cancer by Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, Kaplan-Meier Plotter, cBioPortal and Functional Enrichment Analysis Tool (FunRich) databases. Results: We found that Prx1/2/3/4/5 were overexpressed in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) relative to normal lung cells. However, the expression level of Prx6 was lower in LUAD and higher in LUSC than normal lung cells. The level of Prx3 and Prx6 were associated with pathological stage. Prognostic analysis showed that elevated Prx1 and Prx2 expression were correlated with low Overall Survival (OS), whereas high Prx5 and Prx6 expression level predicted high OS. Conclusions: Our results effectively revealed the level of Prxs in lung cancer and its influence on the prognosis of lung carcinoma, contributing to the study of the role of Prxs in tumorigenesis.

Concept Knowledge (C-K) theory has been used in engineering and science-based research for more than a decade. Design of an Information Technology (IT) artefact is mostly pragmatic in nature. Design Science Research (DSR) methodology applied and studied in many Information Systems (IS) research. Many sub design decisions involved through the design of an IT artefact from a concept (idea) to a working prototype. A DSR artefact is based on a combination of decisions made during several sub-design stages. Artefacts are built based on the selection of elements in each sub-design space. Recording the design decisions on each sub-design space would be beneficial for future researchers. By knowing the design decisions on each sub-design space, researchers would be able to try different combinations of the design. C-K theory provides the ability to capture the design processes’ several sub-design spaces. In this paper, we discuss the DSR research methodology by looking at the stages proposed in the literature, and the application of C-K theory in an IT-based DSR. This paper also proposed a C-K theory-based protocol called Concept Tree for tracking and reporting artefact design steps. The application of C-K theory in DSR is exhibited using the implementation of the Concept Tree for a prototype design IT artefact.

Skeletal metastases of unknown primary (SMUP) represent a clinical challenge dealing with patients diagnosed with bone metastases. The management have improved significantly in the past years, however fraught with lack of evidences, approach to these patients held out hope for more systematic and tailored treatment—and some patients can achieve impressive gains. Nevertheless, in real-life practice the outlook at the beginning of the take in charge of SMUP is decidedly more somber. An incomplete translational relevance of pathological and clinical data on the mortality and morbidity rate has had unsatisfactory consequences for SMUP patients and their physicians. We examined several approaches to confront the available evidences and highlighted three key points that emerge. The characterization of the SMUP biologic profile is essential to drive clinical decisions, integrating genetic and molecular profile into a multi-step diagnostic work-up. Nonetheless, pragmatic investigation plan and therapy of SMUP cannot follow a single template; it must be adapted to different pathophysiological dynamics and coordinated with efforts of a systematic algorithm and high-quality data derived from statistically powered clinical trials within. This review argues that greater efforts are required to face the unmet need dealing with SMUP patients in oncology. Finally, we provide an original functional network analysis, identifying novel therapeutic targets.

In this paper we propose a novel self-supervised approach of keywords and keyphrases retrieval and extraction by an end-to-end deep learning approach, which is trained by contextually self-labelled corpus. Our proposed approach is novel to use contextual and semantic features to extract the keywords and has outperformed the state of the art. Through the experiment the proposed approach has been proved to be better in both semantic meaning and quality than the existing popular algorithms of keyword extraction. In addition, we propose to use contextual features from bidirectional transformers to automatically label short-sentence corpus with keywords and keyphrases to build the ground truth. This process avoids the human time to label the keywords and do not need any prior knowledge. To the best of our knowledge, our published dataset in this paper is a fine domain-independent corpus of short sentences with labelled keywords and keyphrases in the NLP community.

The following study reports on the first thraustochytrid isolates identified from Iceland. They were collected from three different locations off the northern coast of the country (Location A, Skagaströnd; Location B, Hveravík; and Location C, Eyjafjörður). Using 18S rDNA sequence analysis, isolates from Locations A and B were identified within the Thraustochytrium kinnei species while other isolates within the Sicyoidochytrium minutum species when compared to other known strains. Cells isolated from Locations A (2.10 ± 0.70 g/L) and B (1.54 ± 0.17 g/L) produced more biomass than the ones isolated from Location C (0.43 ± 0.02 g/L). This study offers the first-time examination of the utility of byproducts from fisheries as a nitrogen source in media formulation for thraustochytrids. Experiments showed that isolates produced more biomass (per unit of substrate) when cultured on nitrogen of marine (2.55 ± 0.74 g/L) as compared to of commercial origin (1.06 ± 0.57 g/L). Glycerol (2.43 ± 0.56 g/L) was a better carbon source than glucose (1.84 ± 0.57 g/L) in growth studies. Fatty acid (FA) profiles showed that the isolates from Location C (S. minutum) had low ratios of monounsaturated (4.21 ± 2.96%) and omega-6 (0.68 ± 0.59%) FAs. However, the isolates also had high ratios of docosahexaenoic acid (DHA; 35.65 ± 1.73%) and total omega-3 FAs (40.39 ± 2.39%), indicating that they could serve as a source of marine oils for human consumption and in aquaculture feeds. The T. kinnei isolates from Location A could be used in biodiesel production due to their high ratios of monounsaturated (18.38 ± 6.27%) long chain (57.43 ± 8.27%) FAs.

South Africa is afflicted with the worst epidemic of HIV in the world a legacy of the system of oscillating migrant labour in the region and the consequent social disruption that was the legacy of Apartheid. The initial response from the national government was slow and ineffective but once the magnitude of the epidemic became apparent the government began to respond. The investment in HIV- and TB-related activities in 2013 was R22 Bn or (US$2.5; 2013 exchange rate) of which the South Africa government contributed 80% and the Presidents Emergency Plan for AIDS Relief (PEPFAR) 17%. South Africa now has the more people on anti-retroviral therapy than any other country and treatment is being started much sooner after infection. Much of the best biomedical, virological, immunological, mathematical and social science around the treatment and prevention of HIV and AIDS and the associated epidemic of TB has been done by South African’s and their international collaborators. If the efforts to control the epidemic are maintained South Africa is on track to meet the UNAIDS 90-90-90target by 2020 and to End AIDS by 2030 in spite of the magnitude of the problem. While individual, patient level data are increasingly available, especially in the Western Cape, much greater efforts need to be made to ensure that the information collected in this way is used to give feedback and support to clinic staff, to ensure that health clinics are providing the best possible service, and to individual patients and people living with HIV to ensure that they are receiving the best possible care and support. South Africa needs to make better use of the rich and detailed data that are being collected from individual clinics and their patients to identify problems or difficulties at the clinic level and to ensure that individual patients are retained on treatment, are virally suppressed and receive the best possible care and support.

The structure of turbulent flow over non-flat surfaces is a topic of major interest in practical applications in both engineering and geophysical settings. A lot of work has been done in the fully rough regime at high Reynolds numbers where the effect on the outer layer turbulence structure and the resulting friction drag is well documented. It turns out that surface topology plays a significant role on the flow drag especially in the transitional roughness regime and therefore, hard to characterize. Survey of literature shows that roughness function depends on the interaction of roughness height, flow Reynolds number and topology shape. In addition, if the surface topology contains large enough scales then it can impact the outer layer dynamics and in turn modulate the total frictional force. Therefore, it is important to understand the mechanisms underlying drag increase from systematically varied surface undulations in order to better interpret quantifications based on mean statistics such as roughness function. In this study, we explore the mechanisms that modulate the turbulence structure over a two-dimensional (2D) sinusoidal wavy surface with a fixed amplitude, but varying slope. To accomplish this, we model the turbulent flow between two infinitely wide 2D wavy plates at a friction Reynolds number, $Re_{\tau}=180$. We pursue two different but related flavors of analysis. The first one adopts a roughness characterization flavor of such wavy surfaces. The second one focuses on understanding the non-equilibrium near surface turbulence structure and their impact on roughness characterization. Analysis of the different statistical quantifications show strong dependence on wave slope for the roughness function indicating drag increase due to enhanced turbulent stresses resulting from increased production of vertical velocity variance from the surface undulations.

We report on the design and construction of a spin-flip Zeeman slower, quadrupole magnetic trap, and Feshbach fields for a new machine for ultra-cold Li-7. The small mass of the Li-7 atom, and the tight lattice spacing, will enable us to achieve a 100-fold increase in tuneling rates over comparable Rb-87 optical lattice emulator experiments. These improvements should enable to access new regimes in quantum magnetic phase transitions and spin dynamics.