Background. The main impetus behind the worldwide Covid-19 vaccination campaign in 2021 was to reduce the mortality attributed to SARS-CoV-2 infection in the preceding year. Nevertheless, rigorous analyses of the mortality benefits conferred by this massive vaccination effort have been lacking. Methods Statistics offers us an essential methodological approach for measuring the impacts of Covid-19 vaccination on public health. The mathematical relation between vaccinated-alive groups can be repeated between vaccinated-dead groups with relatively high statistical reliability because of the large population numbers involved. This method also confers greater statistical usefulness because it eliminates the Simpson effect. Results Calculations were performed for each of the following five(5) four-week intervals: weeks 35-38 (2021), weeks 39-42 (2021), weeks 43-46 (2021), weeks 47-50 (2021), and weeks 50(2021)-1(2022). The results obtained confirm that the mortality of the vaccinated coronavirus-infected groups was 14.5% higher on average than the mortality of non-vaccinated coronavirus-infected groups. Conclusions Vaccinated infected groups appear to have higher average mortality than their non-vaccinated infected counterparts. The findings suggest the legitimacy of extending the statistics between vaccinated living and vaccinated dead individuals for different age groups. Calculating the impact of Covid-19 vaccination on the mortality rate is a necessary step towards satisfying the first principle of medicine: “Primum non nocere”, “Do no harm”.

Exploring the biological significance of mutations in SARS-CoV-2 coronavirus, causing the COVID–19 pandemic, has recently become an area of paramount interest for many researchers, who are pouring their tremendous efforts, in cracking the COVID–19 pandemic code. One of many such mutations that have occurred in the viral genome is V483A mutation, which is a part of the receptor-binding motif (RBM), present in the S1 domain of the spike protein. V483A mutant virus is becoming popular in North America with 36 cases so far, due to its frequent occurrences in recent days. In this review, we have assembled all information, currently available on V483A mutation, and have made a critical analysis based on the perspectives of many researchers all around the world. Comparison is made between the wild type and the V483A mutants to analyze certain factors like the type of interaction between the virus and host cell interface, binding affinity, stability, partition energy, hydrophobicity, occurrence rate, and transmissibility. Insilico dynamic analysis shows minimal alteration in the receptor-binding domain (RBD) of V483A mutant protein in free-state and no significant change of mutant tertiary structure of RBM upon binding to the ACE2 receptor. Comprehensive details about infectivity and evasion of the immune system by the virus are discussed. This information can in turn be of monumental importance in the field of vaccine and drug development because the mutants are becoming resistant to the vaccines and monoclonal antibodies.

COVID-19 (2019-nCoV) is a pandemic disease with an estimated mortality rate of 3.4% (estimated by the WHO as of March 3, 2020). Until now there is no antiviral drug and vaccine for COVID-19. The current overwhelming situation by COVID-19 patients in hospitals is likely to increase in the next few months. About 15 percent of patients with serious disease in COVID-19 require immediate health services. Rather than waiting for new anti-viral drugs or vaccines that take a few months to years to develop and test, several researchers and public health agencies are attempting to repurpose medicines that are already approved for another similar disease and have proved to be fairly effective. This study aims to identify FDA approved drugs that can be used for drug repurposing and identify biomarkers among high- risk and asymptomatic groups. In this study gene-disease association related to COVID-19 reported mild, severe symptoms and clinical outcomes were determined. The high-risk group was studied related to SARS-CoV-2 viral entry and life cycle by using Disgenet and compared with curated COVID-19 gene data sets from the CTD database. The overlapped gene sets were enriched and the selected genes were constructed for protein-protein interaction networks. Through interactome, key genes were identified for COVID-19 and also for high risk and asymptomatic groups. The key hub genes involved in COVID-19 were VEGFA, TNF, IL-6, CXCL8, IL10, CCL2, IL1B, TLR4, ICAM1, MMP9. The identified key genes were used for drug-gene interaction for drug repurposing. The chloroquine, lenalidomide, pentoxifylline, thalidome, sorafenib, pacitaxel, rapamycin, cortisol, statins were proposed to be probable drug repurposing candidates for the treatment of COVID-19. However, these predicted drug candidates need to be validated through randomized clinical trials. Also, a key gene involved in high risk and the asymptomatic group were identified, which can be used as probable biomarkers for early identification.

Background: COVID-19 pandemic has pulled us all a few steps back, were we never shake hands or hug each other when we meet our friends and family after a gap, but instead we greet them by saying Namaste and joining our hands together. As we all know, COVID-19 spreads through air and the only way to shield ourselves is by maintaining a safe distance from one another. Methodology: In order to conduct a meta-analysis on the number of COVID-19 cases in Kerala and India, the data was retrieved from various sites hosted by the government bodies. The data for analysis was collected from May 2020 to July 2020. The average number of days required to reach every 5000 fresh cases were also calculated using this data. COVID-19 has affected all the economy holistically regardless of financial, behavioral, or societal aspects. Conclusion: Lifting of the lockdown in a step by step process keeping in mind the necessities for the nation was a thoughtful act, but the people who mistook this opportunity and did not remain in quarantine after coming from abroad was recognized as the reasons behind the sudden and uncontrolled rise in the number of COVID-19 cases in Kerala, India. The government authorities had no other option but to lift the restrictions to reduce the economic burdens that had already affected the daily wage worker and farmers prompting them to give up their lives.

Decisions affecting the COVID-19 pandemic, by the individual and those with highest authority, are being made on the basis of unreliable data. Data about cases and deaths are collected daily but represent only a sample of reality. Statistics convert sample data into more reliable estimates. However, statistics have no magical powers; reliability requires dependable data. It is futile to rail against this darkness; COVID-19 is not a scientific experiment. However, we must do better both with data collection and data analysis. In this review, I focus on one element of the data, the asymptomatic case of COVID-19. Without reliable information about this number, decision makers are significantly blinded. By its nature, the asymptomatic case is hidden but contaminating to understanding COVID-19. The true case rate and death rate per case are unknowable without knowing the fraction of cases that are asymptomatic. The best estimate of asymptomatic cases is in the CDC document: COVID-19 Pandemic Planning Scenarios. For four different scenarios the estimates range from 10% to 70%, with the best estimate of 40% for asymptomatic cases. However, even the definition of the asymptomatic case is problematic. In simplest terms, two elements are required: an infection and no symptoms. How is “no symptoms” to be usefully defined? It appears to be analogous to pontificating about black swans from studying only white swans. It implies infection, but how is infection defined? Is it presence of the virus, replication of the virus, or presence of antibodies? Is asymptomatic disease an oxymoron? Without extensive, purposeful screening for specifically defined, essential symptoms and appropriate virus and antibody testing over time, the class of asymptomatic cases remains unknown. Current estimates range from <20% to ˃80%. If low, it can be ignored; if high, it dramatically and proportionately lowers the case rate and the death rate per case. Consequentially, the asymptomatic rate dramatically affects our societal and political responses. In this focused review, we assess the limitations of the published estimates, bring attention to the importance of obtaining accurate data, and exhort that high priority be given in the scientific community to understanding the issue, asymptomatic COVID-19 cases.

Background: Since the previous study dealing with the case fatality ratio and infection fatality ratio caused by COVID-19, the author has received many comments that prompted the question: "Why did an optimistic prognosis fail?" To answer this question, a more detailed and expanded analysis was carried out in a new study. Objective: To evaluate the dynamics of monthly numbers of cases, deaths, tests and CFR worldwide during three phases of the COVID-19 pandemic. Material and Methods: Twenty three sets of databases, dated the 22nd of each month from January 2020 to November 2021, for 213 countries were collected from the Worldometer website. The number of cases, deaths, tests, CFR, IFR, etc. were counted for various periods of time for each of the 213 countries, then results related to different periods of time were compared. Results: The analysis of the main epidemiological parameters led to the division of three phases of the global pandemic evolution. The first phase (23.01.20-22.07.20), the second phase (23.07.20-22.01.21) and the third phase (23.01.21-22.07.21) were different in terms of the number of tests performed, new cases, and mortality due to COVID-19. By the end of the second phase, the worldwide statistics indicated the imminent end of the pandemic, but the third phase was characterized by a sudden rise in the number of new cases and deaths that could not be explained rationally. The most dramatic evolution of the epidemic curve occurred in the countries where doctors had successfully battled COVID-19 during the first two phases of the pandemic. Conclusions: Despite the decrease in overall death numbers during the latest months analyzed, additional study is necessary to identify the cause for the increase in the number of new cases and deaths during the third phase of the pandemic. Only complete information regarding the positive and negative impact of medical and non-medical methods of diagnostics and prophylaxis of COVID-19 can help to organize effective measures to end the current pandemic and prevent a similar one from occurring in the future. Presumably, there are several causes of the negative evolution of the current pandemic, including the overreliance on PCR tests, application of non-specialized premises for quarantine and treatment, decrease in herd and individual immunity, inadequate change of therapeutic protocols, and ignoring prophylactic treatment. It can be suggested that the use of immunemodulatory drugs, for example, thymus extract or thymic peptides, in groups of people with compromised immunity is necessary, and prophylactic and therapeutic protocols should be changed from the 'standard' types to 'personalized' ones.

This case study investigates the heart rate (HR) and heart rate variability (HRV) in a patient with coronavirus disease 2019 (COVID-19). We report the case of a 58-year old male who contracted COVID-19. During his disease, 24-hour Holter electrocardiography (ECG) was performed continuously. For comparison, his 24-hour Holter ECGs from the previous 10 years were available. In this patient, COVID-19 was associated with a decrease in HR and a paradoxical decline in HRV. An abrupt decline in HRV and a decrease in HR may signal the onset of COVID-19 before common symptoms such as dry cough or fever appear. In addition, HRV and HR measurements may help to evaluate the course of the disease.

Background: Covid-19 was first reported in Wuhan, China in Dec 2019. Since then, it has been transmitted rapidly in China and the rest of the world. While Covid-19 transmission rate has been declining in China, it is increasing exponentially in Europe and America. Although there are numerous studies examining Covid-19 infection, including an archived paper looking into the meteorological effect, the role of outdoor air pollution has yet to be explored rigorously. It has been shown that air pollution will weaken the immune system, and increase the rate of respiratory virus infection. We postulate that outdoor air pollution concentrations will have a negative effect on Covid-19 infections in China, whilst lockdowns, characterized by strong social distancing and home isolation measures, will help to moderate such negative effect. Methods: We will collect the number of daily confirmed Covid-19 cases in 31 provincial capital cities in China during the period of 1 Dec 2019 to 20 Mar 2020 (from a popular Chinese online platform which aggregates all cases reported by the Chinese national/provincial health authorities). We will also collect daily air pollution and meteorology data at the city-level (from the Chinese National Environmental Monitoring Center and the US National Climatic Data Center), daily inter-city migration flows and intra-city movements (from Baidu). City-level demographics including age distribution and gender, education, and median household income can be obtained from the statistical yearbooks. City-level co-morbidity indicators including rates of chronic disease and co-infection can be obtained from related research articles. A regression model is developed to model the relationship between the infection rate of Covid-19 (number of confirmed cases/population at the city level) and outdoor air pollution at the city level, after taking into account confounding factors such as meteorology, inter- and intra-city movements, demographics, and co-morbidity and co-infection rates. In particular, we shall study how air pollution affects infection rates across different cities, including Wuhan. Our model will also study air pollution would affect infection rates in Wuhan before and after the lockdown. Expected findings: We expect there be a correlation between Covid-19 infection rate and outdoor air pollution. We also expect that reduced intra-city movement after the lockdowns in Wuhan and the rest of China will play an important role in reducing the infection rate. Interpretation: Infection rate is growing exponentially in major cities worldwide. We expect Covid-19 infection rate is related to the air pollution concentration, and is strongly dependent on inter- and intra-city movements. To reduce the infection rate, the international community may deploy effective air pollution reduction plans and social distancing policies.

Background: World Health Organization (WHO) declared that COVID-19 as a pandemic on March 11, 2020. There is sudden need of statistical modeling due to onset of COVID-19 pandemic across the world. But health planning and policy requirements the estimates of disease problem form clinical data. Objective: To predict recovery rate, cases load rate on the basis of cumulative confirmed Novel Corona virus (NCV) cases, recovered cases and deaths form COVID-19 in India. Methods: The reported COVID-19 cases in the country were obtained from website (https://datahub.io/core/covid-19#resource-covid-19_zip/). The cumulative NCV confirmed cases; recovery cases and deaths were used for estimating recovery rate, cases load rate and death rate till date 24 April 2020. Results: A total of 24530 NCV confirmed cases were reported nationwide in India on 24 April 2020. It is found that the recovery rate increased 22% and case load rate decreased 74%. Death rate is found to be very low 3%. The difference of cases load rate and recovery rate (delta) coincide at 50 % then NCV cases expected would be declined. Conclusion: The epidemic in the country was mainly caused by the importation of India. Lockdown as restricting the migration of population and decided to quarantine of population may greatly reduce the risk of continued spread of the epidemic in India. This study predicts that by 20 May 2020, the cases load rate lesser than recovery rate there after COVID-19 patients would be started to reducing.

The rapidly increasing adoption of high-resolution accurate-mass methods in analytical laboratories has fueled demand for instruments that combine high performance and reliability with small size and greater ease-of-use. This paper presents the major design principles that are driving the evolution of the hybrid quadrupole-Orbitrap instrument architecture to enable a greater range of applications and users. These principles may be summarized as follows: better usage of physical space and better access for service by means of size reduction of pumping and ion optics; expanded use of technologies from electronics in ion-optical design; flexibility in performance via modularity of design of the hardware and software components; and, harmonization of interfaces with other instruments to facilitate sharing and transferability of analytical workflows. The design of a novel family of hybrid mass spectrometers is described in detail, and performance evaluation is carried out on a wide variety of samples for its three representatives: the Orbitrap Exploris 120, Orbitrap Exploris 240 and Orbitrap Exploris 480 mass spectrometers.The new instrument family is shown to offer compelling potential not only for high-end proteomics and biopharmaceutical applications, but also for screening, trace, targeted and clinical analysis by liquid chromatography/mass spectrometry methods.

There is much discussion among clinicians, epidemiologists, and public health experts about why case fatality rate from COVID-19 in Italy (at 13.3% as of April 20, 2020, versus a global case fatality rate of 6.9%) is considerably higher than estimates from other countries (especially China, South Korea, and Germany). In this article, we propose several potential explanations for these differences. We suggest that Italy’s overall and relative case fatality rate, as reported by public health authorities, is likely to be inflated by such factors as heterogeneous reporting of coronavirus-related fatalities across countries and the iceberg effect of under-testing, yielding a distorted view of the global severity of the COVID-19 pandemic. We also acknowledge that deaths from COVID-19 in Italy are still likely to be higher than in other equally affected nations due to its unique demographic and socio-economic profile. Lastly, we discuss the important role of the stress imparted by the epidemic on the Italian healthcare system, which weakened its capacity to adequately respond to the sudden influx of COVID-19 patients in the most affected areas of the country, especially in the Lombardy region.

With the existence of several programming languages such as C/C++, Java, C#, LISP, Prolog, Python, Simula, F#, Go, Haskell, Scala, Ruby, Dart, Swift, Groovy etc. and diverse paradigms like structured, object-oriented, list, aspect-oriented, service-oriented, web, mobile and logic programming, there is a need to perform an exhaustive comparative analysis of diverse compilers and environments before making a choice of implementation technology in software engineering. Optimization of compilers helps to reduce execution time by making use of high speed processor registers, thereby, eliminating redundant computation. This paper reports some series of performance analysis done with some popular programming languages including Java, C++, Python and PHP. Programs involving recursive and iterative functions like factorial of large numbers and binary search of large arrays were run on the various platforms with the execution time recorded in milliseconds and represented in a chart. This can aid in making a selection of the appropriate language to use for a given application domain.

Biological systems are highly regulated. They are also highly resistant to sudden perturbations enabling them to maintain the dynamic equilibrium essential for sustenance of life. This robustness is conferred by regulatory mechanisms that influence the activity of enzymes/proteins within their cellular context, to adapt to changing environmental conditions. However, the initial rules governing the study of enzyme kinetics were tested and implemented for mostly cytosolic enzyme systems that were easy to isolate and/or recombinantly express. Moreover, these enzymes lacked complex regulatory modalities. Now, with academic labs and pharmaceutical companies turning their attention to more complex systems (for instance, multi-protein complexes, oligomeric assemblies, membrane proteins and post-translationally modified proteins), the initial axioms defined by Michaelis-Menten (MM) kinetics are rendered inadequate and the development of a new kind of kinetic analysis to study these systems is required. The current review strives to present an overview of enzyme kinetic mechanisms that are atypical and, oftentimes, do not conform to the classical MM kinetics. Further, it presents initial ideas on the design and analysis of experiments in early drug-discovery for such systems, to enable effective screening and characterisation of small-molecule inhibitors with desirable physiological outcomes.

A new form of coronavirus called severe acute respiratory disease coronavirus type 2 (SARS-CoV-2) is currently causing a pandemic. A six-month evolutionary history of SARS-CoV-2 is witnessed by characterising the total genome of 821 samples using comparative phylogenomic approaches. Our analyses produced striking inclusive results that may guide scientists/professionals for the past/future of pandemic. Phylogenetic and time estimation analyses suggest the proximate origin of pandemic strain as Guangdong and the origin time as first half of September 2019, not Wuhan and December 2019, respectively. The viral genome experienced a substitution rate similar to other RNA viruses, but it is particularly high in some of the peptides encoding sequences such as leader protein, E gene, orf8, orf10, nsp10, N gene, S gene and M gene and nsp4, while low in nsp11, orf7a, 3C-like proteinase, nsp9, nsp8 and endoRNase. Most strikingly, the divergence rate of amino acid sequences is high proportional to nucleotide divergence. Additionally, specific non-synonymous mutations in nsp3 and nsp6 evolved under positive selection. The exponential growth rate (r), doubling time (Td) and R₀ were estimated to be 47.43 per year, 5.39 days and 2.72, respectively. Comparison of synapomorphies distinguishing the SARS-CoV-2 and the candidate ancestor bat coronavirus indicates that mutation pattern in nsp3 and S gene enabled the new strain to invade human and become a pandemic strain. We arrive at the following main conclusions: (i) six months evolution of viral genome is nearly neutral, (ii) origin of pandemic is not Wuhan and predates formal reports, (iii) although viral population is ongoing an exponential growth, the doubling time is evolving towards shortening, and (iv) divergence rate of total genome is similar to other RNA viruses, but it is prominently high in some genes while low in some others and evolution in these genes should be closely monitored as their protein products intervening to pathogenicity, virulence and immune response.

Abstract The COVID-19 pandemic is thought to began in Wuhan, China in December 2019. Mobility analysis identified East-Asia and Oceania countries to be highly-exposed to COVID-19 spread, consistent with the earliest spread occurring in these regions. However, here we show that while a strong positive correlation between case-numbers and exposure level could be seen early-on as expected, at later times the infection-level is found to be negatively correlated with exposure-level. Moreover, the infection level is positively correlated with the population size, which is puzzling since it has not reached the level necessary for population-size to affect infection-level through herd immunity. These issues are resolved if a low-virulence Corona-strain (LVS) began spreading earlier in China outside of Wuhan, and later globally, providing immunity from the later appearing high-virulence strain (HVS). Following its spread into Wuhan, cumulative mutations gave rise to the emergence of an HVS, known as SARS-CoV-2, starting the COVID-19 pandemic. We model the co-infection by an LVS and an HVS, and show that it can explain the evolution of the COVID-19 pandemic and the non-trivial dependence on the exposure level to China and the population-size in each country. We find that the LVS began its spread a few months before the onset of the HVS, and that its spread doubling-time is $\sim 1.59\pm 0.17$ times slower than the HVS. Although more slowly spreading, its earlier onset allowed the LVS to spread globally before the emergence of the HVS. In particular, in countries exposed earlier to the LVS and/or having smaller population-size, the LVS could achieve herd-immunity earlier, and quench the later-spread HVS at earlier stages. We find our two-parameter (the spread-rate and the initial onset time of the LVS) can accurately explain the current infection levels (R^2$\mathrm{=0.74}$; correlation p-value (p) of 5x10^-13$$). Furthermore, countries exposed early should have already achieved herd-immunity. We predict that in those countries cumulative infection levels could rise by no more than 2-3 times the current level through local-outbreaks, even in the absence of any containment measures. We suggest several tests and predictions to further verify the double-strain co-infection model and discuss the implications of identifying the LVS.

The choice associated with words is a fundamental property of natural languages. It lies at the heart of quantitative linguistics, computational linguistics, and language sciences more generally. Information-theory gives us tools at hand to measure precisely the average amount of choice associated with words—the word entropy. Here we use three parallel corpora—encompassing ca. 450 million words in 1916 texts and 1259 languages—to tackle some of the major conceptual and practical problems of word entropy estimation: dependence on text size, register, style and estimation method, as well as non-independence of words in co-text. We present three main results: 1) a text size of 50K tokens is sufficient for word entropies to stabilize throughout the text, 2) across languages of the world, word entropies display a unimodal distribution that is skewed to the right. This suggests that there is a trade-off between the learnability and expressivity of words across languages of the world. 3) There is a strong linear relationship between unigram entropies and entropy rates, suggesting that they are inherently linked. We discuss the implications of these results for studying the diversity and evolution of languages from an information-theoretic point of view.

The use of machine learning techniques in predictive health care is on the rise with minimal data used for training machine-learning models to derive high accuracy predictions. In this paper, we propose such a system, which utilizes Heart Rate Variability (HRV) as features for training machine learning models. This paper further benchmarks the usefulness of HRV as features calculated from basic heart-rate data using a window shifting method. The benchmarking has been conducted using different machine-learning classifiers such as artificial neural network, decision tree, k-nearest neighbour and naive bays classifier. Empirical results using MIT-BIH Arrhythmia database shows that the proposed system can be used for highly efficient predictability of abnormality in heartbeat data series.

The high radio frequency polarization imaging of non-thermal emission from active galactic nuclei (AGN) is a direct way to probe the magnetic field strength and structure in the immediate vicinity of supermassive black holes (SMBHs) and is crucial in testing the jet-launching scenario. To explore the the magnetic field configuration at the base of jets in blazars, we took advantage of the full polarization capabilities of the GMVA (Global Millimeter VLBI Array). With an angular resolution of ~50 micro-arcseconds at 86 GHz, one could reach scales down to ~900 Schwarzschild radii (for a 10^9 solar mass black hole). We present here the preliminary results of our study on the blazar BL Lac. Our results imply that on sub-mas scales the core and central jet of BL Lac is significantly polarized with two distinct regions of polarized intensity. We also noted a great morphological similarity between the 7mm/3mm VLBI images at very similar angular resolution.

In this study the impact of terrorist attacks on exchange rate is estimated. Particularly, the study focuses on Turkish terrorist attacks and its implication on Turkish lira versus pound sterling exchange rate. In order, to find the causal effect the study employed Autoregressive distributive lag (ARDL) bound testing approach as an estimation technique. Accordingly, the analysis reveals that terrorist attack has a negative impact on the exchange rate in both short and long-run. However, the negative effect of terrorism tends to be small in both the short-run and long-run. More precisely, terrorist attack depreciates the exchange rate between Turkish lira and pound sterling by approximately 0.00072 in the next trading day. The long-term effect also shows that terrorist attack depreciates the exchange rate on average by 0.00212.

In this paper, we first discuss the research status and application progress of the finite element method and the smoothed particle method. By analyzing the advantages of the smoothed particle method and the finite element method, a new coupling algorithm, namely FEM-SPH algorithm, is proposed. By the method of comparison, it shows that finite element method and SPH method in the simulation of large deformation problems each have advantages and disadvantages, the finite element method smoothed particle coupling algorithm is effective to achieve the performance of high computational efficiency and can naturally simulate large deformation problems across. In the process of calculation, the large deformation unit can be freely into an algorithm to facilitate the calculation accuracy and efficiency of three methods of numerical simulation. Through the study found, FEM-SPH algorithm not only overcome the defect of smooth particle tensile instability, but also overcomes the problem of low efficiency of finite element computation. To further test the FEM-SPH algorithm has advantages in the practical engineering, we have carried out the actual test to the example of the super high speed collision, concluded that, since the target of most of the computational domain is always finite element, smoothed particle focused only in contact with the projectile and target of local area, particle number is not much, the whole calculation process just ten minutes, computational efficiency has been greatly improved, at the same time in the simulation of large deformation, the advantage is very obvious .This provides a criterion for the actual project, depending on the specific material deformation mode and choose a more appropriate conversion algorithm.

Originally developed to image the shadow region of the central black hole in Sagittarius A* and in the nearby galaxy M87, the Event Horizon Telescope (EHT) provides deep, very high angular resolution data on other AGN sources too. The challenges of working with EHT data have spurred the development of new image reconstruction algorithms. This work briefly reviews the status of the EHT and its utility for observing AGN sources, with emphasis on novel imaging techniques that offer the promise of better reconstructions at 1.3 mm and other wavelengths.

A high intake of carbohydrates, associated with obesity, is one of the major causes of fatty liver disease in humans. This study investigated how high carbohydrate intake induces fatty liver disease in Blunt snout bream (Megalobrama amblycephala). Blunt snout bream were fed a high-carbohydrate diet (HCBD) for 60 days. Their growth indices were evaluated, and the transcriptomes, metabolites, biochemistry, and histology of their blood and livers were analyzed. The final weight, weight gain, specific growth rate, and feed conversion ratio were all higher in the HCBD group than in the control group, but not significantly so (P > 0.05). The hepatosomatic index (HSI) differed significantly in the two groups (P < 0.05), and the metabolomics results showed that a high carbohydrate intake induced significant increases in plasma α/β-glucose, succinate, and tyrosine, which could increase hepatic glycogen and triglyceride. Low levels of betaine were also found in the livers of the HCBD group. The histology and blood biochemistry results suggested abnormal liver, with excessive lipid accumulation and liver damage. A transcriptome analysis and quantitative reverse transcription–PCR (RT–qPCR) indicated that the expression of the factors INSR, IRS, PI3K, PDK, AKT, ACC, IL6, AP1, ChREBP-MLX, PEPCK, and FBP in the insulin signaling pathway was significantly upregulated and that of SOCS3, GSK3β, and AMPK significantly downregulated in the HCBD. This pattern is associated with the nonalcoholic fatty liver disease (NAFLD) pathway. This study extends our understanding of how high carbohydrate causes increased fat deposition in the liver, enhanced glycolysis (α/β-glucose) in the plasma, and reduced betaine in the liver. This leads to activation of hepatocyte insulin resistance and lipogenesis by regulating the expression of genes related to fatty liver disease.

The preparation of gold nanoparticles (AuNPs) involves a variety of chemical and physical methods. These methods use toxic and environmentally harmful chemicals. Consequently, the synthesis of AuNPs using green chemistry has been under investigation to develop eco-friendly nanoparticles. One method to achieve this is the use of plant-derived phytochemicals capable of reducing gold ions to produce AuNPs. The aim of this study was to implement a facile microtitre-plate method to screen a large number of aqueous plant extracts to determine the optimum concentration (OC) to bio-synthesize the AuNPs. Several AuNPs of different sizes and shapes were successfully synthesized and characterized from seventeen South African plants. The characterization was done using Ultra Violet-Visible Spectroscopy, Dynamic Light Scattering, High Resolution Transmission Electron Microscopy and Energy-Dispersive X-ray Spectroscopy. We also studied the effects of temperature on the synthesis of the nanoparticles and measured its effect on the particle size of the synthesized AuNPs and the data showed that changes in temperatures affect the size and dispersity of the generated AuNPs. Further, some of the synthesized AuNPs were stable upon incubation with different biological solutions in vitro.

Abstract: Hyperuricemia is commonly diagnosed in subjects with abnormal purine metabolism. Prolonged hyperuricemia often associated with gout, which is a vital risk factor for joint dysfunction. The current study was designed to determine the efficacy of vitamin C supplements for treatment of high serum uric acid (UA) among hyperuricemic and gouty patients, and finding-out the effect of supplementation on serum creatinine (Cr) level and glomerular filtration rate (GFR). This intervention study was started in April, 2013, till two months. A convenient sample of 30 adults aged between 24-75 years of both genders was assigned into two study groups: hyperuricemic (n=15) and gouty (n=15) groups. Each participant supplemented with 500 mg/day vitamin C chewable tablets for 2 months. Serum UA, Cr, and GFR were measured before and after treatment. At the end of this study, Cr and GFR enhanced insignificantly in both groups. UA increased insignificantly in gouty group after 2 months by about 0.31 mg/dl. On the other hand, hyperuricemic group showed significant (P ≤0.05) decrease in UA (-0.78 mg/dl) after 2 months duration. In conclusion, supplementation with 500 mg/day vitamin C for 2 months significantly attenuated serum UA for hyperuricemic patients and insignificantly affected serum UA in gouty patients. The uselessness of vitamin C supplements on gouty patients could be associated to a number of possible reasons.

An experimental study is carried out in a cavitation tunnel on a propeller operating downstream of a non-uniform wake. The goal of this work is to establish quantitative correlations between the near pressure field and the cavitation pattern that takes place on the propeller blades. The pressure field is measured at the walls of the test section and in the near wake of the propeller, and is combined with quantitative high-speed image recording of the cavitation pattern. Through simple harmonic analysis of the pressure data and image processing techniques that allow to retrieve the cavitation extension and volume, we discuss the potential sources that generate the pressure fluctuations. Time correlations are unambiguously established between pressure peak fluctuations and cavitation collapse events, based upon the Rayleigh collapse time. Finally, we design a model to predict the cavitation-induced pressure fluctuations from the derivation of the cavitation volume acceleration. This simple model demonstrates a remarkable agreement with the actual pressure field.

Warming of the climate system is unequivocal, and many of the observed changes are unprecedented over five decades to millennia. Globally the atmosphere and ocean is increasingly getting warmer, the amount of ice on the earth is decreasing over the oceans, and the sea level has risen. According to Intergovernmental Panel on Climate Change, the total increasing temperature globally averaged combined land and surface between the average of the 1850-1900 period and the 2003 to 2012 period is 0.78 °C (0.72 to 0.85). But should we prepare for such the relatively small change? The importance is not the mean of the warming but the considerable likelihood of climate change that could trigger extreme natural hazards. The impact and the risk of climate change associated with railway infrastructure have not been fully addressed in the literature due to the difference in local environmental parameters. On the other hand, the current railway network in Malaysia, over the last decade, has been significantly affected by severe weather conditions such as rainfall, lightning, wind and very high temperatures. Our research findings point out the extremes that can lead to asset system failure, degraded operation and ultimately, delays to train services. During the period of flood, the embankment of the track can be swept away and bridge can be demolished, while during drought, the embankment of the track can suffer from soil desiccation and embankment deterioration, high temperature increases the risk of track buckling and high winds can result in vegetation or foreign object incursion on to the infrastructure as well as additional quasi-static burden exerted. This review is of significant importance for planning and design of the newly proposed high speed rail link between Malaysia and Singapore.

The present work investigates primarily the morphology evolution of the body-centered-cubic (BCC)/B2 phases in AlxNiCoFeCr high-entropy alloys (HEAs) with increasing Al content, which has been neglected so far. There exist two types of microscopic morphologies of BCC and B2 phases in this HEA series: one is the weave-like morphology induced by the spinodal decomposition, and the other is the microstructure of a spherical disordered BCC precipitation on the ordered B2 matrix that appears in HEAs with a much higher Al content. The shape of coherent precipitates is found to be closely related to the lattice misfit between BCC and B2 phases, which is sensitive to Al. The mechanical properties, including the compressive yielding strength and microhardness of the AlxNiCoFeCr HEAs, are also discussed in light of the concept of the valence electron concentration (VEC).

A high step-up DC-to-DC converter that integrates an isolated transformer and a switched-clamp capacitor is presented in this study. The voltage stress of the main power switch should be clamped to 1/4 V by using the turn ratio and switched-clamp capacitor of an isolated transformer to achieve a high voltage gain. In addition, a passive clamp circuit is employed reduce voltage stress on the main power switch. The energy of the leakage inductor can be recycled by the clamp capacitor because of the passive clamp circuit, thereby improving the power converter efficiency. The converter consists of one isolated transformer, one main switch, three capacitors, and four diodes. Operating principle and steady-state analyses are also discussed. Finally, a 24-V-input voltage to 200-V-output voltage and a 150 W output power prototype converter are fabricated in the laboratory. The maximum efficiency of the converter is 95.1 at 60 W.

In this work commercial 18650 lithium-ion cells with LiMn₂O₄, LiFePO₄ and Li(Ni_0.33Mn_0.33Co_0.33)O₂ cathodes were exposed to external heating in an Accelerating Rate Calorimeter (es-ARC, THT Company) to investigate the thermal behavior under abuse conditions. New procedures for measuring external and internal pressure change of cells were developed. The external pressure was measured utilizing a gas-tight cylinder inside the calorimeter chamber in order to detect venting of the cells. For internal pressure measurements, a pressure line connected to a pressure transducer was directly inserted into the cell. During the thermal runaway experiments, three stages (low rate, medium rate and high rate reaction) have been observed. Both pressure and temperature change indicated different stages of exothermic reactions, which produced gases or/and heat. The onset temperature of thermal runaway was estimated according to temperature and pressure changes. Moreover, the different activation energies for the exothermic reactions could be derived from Arrhenius plots.

Aerial image classification has become popular and has attracted extensive research efforts in recent decades. The main challenge lies in its very high spatial resolution but relatively insufficient spectral information. To this end, spatial-spectral feature extraction is a popular strategy for classification. However, parameter determination for that feature extraction is usually time-consuming and depends excessively on experience. In this paper, an automatic spatial feature extraction approach based on image raster and segmental vector data cross-analysis is proposed for the classification of very high spatial resolution (VHSR) aerial imagery. First, multi-resolution segmentation is used to generate strongly homogeneous image objects and extract corresponding vectors. Then, to automatically explore the region of a ground target, two rules, which are derived from Tobler’s First Law of Geography (TFL) and a topological relationship of vector data, are integrated to constrain the extension of a region around a central object. Third, the shape and size of the extended region are described. A final classification map is achieved through a supervised classifier using shape, size, and spectral features. Experiments on three real aerial images of VHSR (0.1 to 0.32 m) are done to evaluate effectiveness and robustness of the proposed approach. Comparisons to state-of-the-art methods demonstrate the superiority of the proposed method in VHSR image classification.

This study evaluated batch fermentation modes, namely, separate hydrolysis and fermentation (SHF), Quasi-simultaneous saccharification and fermentation (Q-SSF), and simultaneous saccharification and fermentation (SSF), and fermentation conditions, i.e., enzyme and yeast loadings, nutrient supplementation and sterilization, on high titer bioethanol production from SPORL-pretreated Douglas-fir forest residue without detoxification. The result indicated Q-SSF and SSF were obviously superior to SHF operation in terms of ethanol yield. The enzyme loading showed a strong positive correlation between enzyme loading and the ethanol yield. The nutrient supplementation and sterility was not necessary for ethanol production from SPORL-pretreated Douglas-fir. The yeast loading showed no significant influence on the ethanol yield for typical SSF conditions. The terminal ethanol titer of 43.2 g/L, or 75.1% theoretical based on glucose, mannose, and xylose theoretical was achieved when SSF was conducted at the condition of following: whole slurry solids loading of 15%, enzyme loading of 20 FPU/g glucan, 1.8 g/kg (wet) yeast loading, without nutrition supplementation and sterilization, at 38°C, on shake flask at 150 rpm for 96h. It is believed that with mechanical mixing, enzyme loading can be substantially reduced with affect ethanol yield by using a long fermentation time.

One mechanism by which fructose could exert deleterious effect in metabolism and inflammation is via its potency vis-à-vis de Maillard reaction. We employed simulated stomach and duodenum digestion of ovalbumin to test the hypothesis that indeed AGEs are formed by fructose during simulated digestion of an ubiquitous food protein with intrinsic allergenic potential and under model physiological conditions. Methods: OVA was subjected to simulated gastric and intestinal digestion using standard models, in presence of fructose or glucose (0-100 mM). Peptide fractions were analyzed by fluorescence spectroscopy and intensity at Excitation: λ370 nm, Emission: λ 440nm. Results: AGE adducts form between fructose and OVA which can be found in peptide fractions (< 5 kDa) at times (30 min) and concentration ranges (10 mM) plausibly found in the intestines, whereas no reaction occurs with glucose. The reaction is inhibited by chlorogenic acid at concentrations compatible with those found in the gut. The reaction is inhibited by AG, a specific antiglycation agent. Conclusion: Our proof of principle study shows that fructose-AGE formation on an ubiquitous allergenic protein indeed occurs in one hour and thereby may pave the way for the study of yet another mechanism by which the excess fructose in our Western diets is contributing to disease: intestinal AGE formation, absorption and RAGE engagement.

The open source CFD code OpenFOAM has emerged as one of the most popular alternative to commercial CFD solvers. The recent version of OpenFOAM supports overlapping grids, so called Overset mesh. In this type of mesh, one or more sub-collection of control volumes (or cells) are allowed to overlap with other set of cells. This allows for great flexibility in modelling Fluid Structure Interaction (FSI) problems. Fluid mesh can be standard structured mesh of a rectangular/cuboidal/or cylindrical domain. The structure mesh can be generated separately by creating multiple layers around a given body. The overset mesh functionality allows for overlapping or immersing this structured mesh inside the fluid mesh and a relevant FSI or moving dynamics problems can be solved. The idea of overset mesh has been around since eighties but its support in OpenFOAM is very recent. Most CFD codes which support overset mesh have either been in-house or commercial CFD codes. OpenFOAM's support for overset is the first major open source code resource available for CFD problems. The aim of this research is to solve a classical benchmark airfoil problem using OpenFOAM overset mesh and compare the numerical results with experimental result. We report here flow simulations results around NACA 0018. The result obtained from overset mesh compares convincingly well with experimental results. Computations have been carried out for Reynolds numbers in the range of 10⁵ with angle of attack ranging from α= 5 degree to α= 30 degree with an interval of 5 degree. Turbulence is incorporated using k - ε turbulence model. This study helps developing confidence in using OpenFOAM overset support for more complicated flows and moving dynamics. This report is complemented with a brief description of finite volume discretization using overset mesh.

This paper investigates the impact of price and real exchange rate volatility on Foreign Direct Investment (FDI) inflows in a panel of 10 Latin American and Caribbean countries, observed between 1990 and 2012. Both price and exchange rate volatility series are estimated through the Generalized Autoregressive Conditional Heteroscedasticity model (GARCH). Our results, obtained employing the Fixed Effects estimator, confirm the theory of hysteresis and option value, in so far it is found a statistically significant negative effect of exchange rate volatility on FDI. Price volatility, instead, turns out to be positive but insignificant. Moreover, we show that human capital and trade openness are key for attracting foreign capital. From the policy perspective, our analysis suggests the importance of stabilization policies as well as the one of government credibility in promoting trade openness and human capital formation.

Outbreaks of the crown-of-thorns seastar (CoTS) represent a major cause of coral loss on the Great Barrier Reef. Outbreaks might be explained by enhanced larval survival supported by higher phytoplankton availability after flood events, yet little is known about CoTS larvae feeding behaviour, in particular their potential for selective feeding. Here, single- and mixed-species feeding experiments were conducted on CoTS bipinnaria larvae using five algae (Phaeodactylum tricornutum, Pavlova lutheri, Tisochrysis lutea , Dunaliella sp. and Chaetoceros sp.) and two algal concentrations (1000 and 2500 algae mL^-1). Cell counts using flow-cytometry at the beginning and end of each incubation experiment allowed us to calculate the filtration and ingestion rates of each species by CoTS larvae. In line with previous studies, CoTS larvae ingested more algae when initial algal concentration was higher. We found evidence for the selective ingestion of some species (Chaetoceros sp., Dunaliella sp.) over others (P. lutheri, P. tricornutum). The preferred algal species had the highest energy content, suggesting that CoTS selectively ingested the most energetic algae. Ultimately, combining these results with spatio-temporal patterns in phytoplankton communities will help elucidate the role of larval feeding behaviour in determining the frequency and magnitude of CoTS outbreaks.

Background: Studies employing next-generation sequencing (NGS) show that the oral fungal community (mycobiome) is far more complex than hitherto thought. However, the role of the oral mycobiome in health and disease, including oral carcinogenesis, has not been explored. Objective: To characterize the mycobiome associated with oral squamous cell carcinoma (OSCC). Methods: Tissue biopsies [cases: 25 OSCC; controls: 27 intra-oral fibro-epithelial polyp (FEP)] were collected from oral and maxillofacial units in Sri Lanka. Total DNA was extracted and subjected to sequencing of the fungal ITS2 region using Illumina’s 2x300 bp chemistry. High quality, non-chimeric merged reads were classified to species level using a BLASTN-algorithm with UNITE’s named species sequences as reference. Downstream analyses were performed using QIIME and LEfSe. Results: 364 species representing 160 genera and 2 phyla (Ascomycota and Basidiomycota) were identified, with Candida and Malassezia making up 48% and 11% of the average mycobiome, respectively. However, only 5 species and 4 genera were detected in ≥50% of the samples. The species richness and diversity were significantly lower in OSCC. At the genus level, Candida, Hannaella and Gibberella were overrepresented in OSCC while Alternaria and Trametes were more abundant in FEP. Species-wise, C. albicans, C. etchellsii and Hannaella luteola-like species were enriched in OSCC while Malassezia restricta, Aspergillus tamarii, Alternaria alternate, Cladosporium halotolerans, and Hanseniaspora uvarum-like species were the most significantly abundant in FEP. Conclusions: A dysbiotic mycobiome dominated by C. albicans was found in association with OSCC. Whether this dysbiosis plays a role in oral carcinogenesis warrants further investigation.

Age-related diseases (ARDs) are the leading cause of death worldwide, and contribute to 90% of mortality in developed countries. Interestingly, the mortality rates of individual ARDs increase exponentially with age. Processes described by the exponential growth function typically involve a branching chain reaction or, more generally, a positive feedback loop. Here I propose that each ARD is mediated by one or several positive feedback loops (vicious cycles). I then identify critical vicious cycles in five major ARDs: atherosclerosis, hypertension, diabetes, Alzheimer’s and Parkinson’s. I also propose that the progression of ARDs can be halted by selectively interrupting the vicious cycles and suggest the most promising targets. An evolutionary perspective is also offered.

It is unclear why European countries have been more severely affected by COVID-19 than East Asian countries. In this ecological study we compared the COVID-19 epidemics (cumulative incidence and mortality rates), host genetic susceptibility and national responses (testing intensity) in all European versus all Western Pacific/East Asian countries reporting cases in the first month of the epidemic. The host-genetic-susceptibility assessment was limited to the frequency of the D-allele of the angiotensin converting enzyme-1 (ACE-1) which has been found to be positively associated with COVID-19 incidence within European countries. Despite earlier epidemics, countries from the Western Pacific reported lower cumulative numbers of COVID-19 cases/100 000 inhabitants than European countries (P=0.0002). The Western Pacific countries also reported fewer cumulative COVID-19 deaths/100 000 (P=0.0024). Whilst there was little difference in the cumulative number of tests conducted/100 000, the percent of COVID-19 tests reported positive was higher in Europe than the Western Pacific (P=0.0076). The frequency of the ACE-1 D-allele was lower in the Western Pacific than European countries (P=0.0007). Our results suggest that a combination of different testing strategies and host genetic susceptibility contribute to difference in severity of the COVID-19 epidemics in the Western Pacific/East Asia and Europe.

Studies on the possible association between bacteria and oral squamous cell carcinoma (OSCC) remain inconclusive, largely due to methodological variations/limitations. The objective of this study was to characterize the species composition as well as functional attributes of the bacteriome associated with OSCC. DNA obtained from 20 fresh OSCC biopsies (cases) and 20 deep-epithelium swabs (matched control subjects) were sequenced for the V1-V3 region using Illumina’s 2x300 bp chemistry. High quality, non-chimeric merged reads were classified to species level using a prioritized BLASTN-algorithm. Downstream analyses were performed using QIIME, PICRUSt, and LEfSe. Fusobacterium nucleatum subsp. polymorphum was the most significantly overrepresented species in the tumors followed by Pseudomonas aeruginosa and Campylobacter sp. Oral taxon 44, while Streptococcus mitis, Rothia mucilaginosa and Haemophilus parainfluenzae were the most significantly abundant in the controls. Functionally, genes involved in bacterial mobility, flagellar assembly, bacterial chemotaxis and LPS synthesis were enriched in the tumors while those responsible for DNA repair and combination, purine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, ribosome biogenesis and glycolysis/gluconeogenesis were significantly associated with the controls. This is the first epidemiological evidence for association of F. nucleatum and P. aeruginosa with OSCC. Functionally, an “inflammatory bacteriome” is enriched in OSSC.

In this paper we introduce a computational model for the simulation of hypervelocity impact (HVI) phenomena which is based on the Discrete Element Method (DEM). Our paper constitutes the first application of DEM to the modeling and simulating of impact events for velocities beyond 5 kms⁻¹. We present here the results of a systematic numerical study on HVI of solids. For modeling the solids, we use discrete spherical particles that interact with each other via potentials. In our numerical investigations we are particularly interested in the dynamics of material fragmentation upon impact. We model a typical HVI experiment configuration where a sphere strikes a thin plate and investigate the properties of the resulting debris cloud. We provide a quantitative computational analysis of the resulting debris cloud caused by impact and a comprehensive parameter study by varying key parameters of our model. We compare our findings from the simulations with recent HVI experiments performed at our institute. Our findings are that the DEM method leads to very stable, energy–conserving simulations of HVI scenarios that map the experimental setup where a sphere strikes a thin plate at hypervelocity speed. Our chosen interaction model works particularly well in the velocity range where the local stresses caused by impact shock waves markedly exceed the ultimate material strength.

In the case of long-stator linear drive, unlike rotative drives for which speed or position sensors are a single unit attached to the shaft, these sensors extend along the guideway. The position signals transmitted from maglev vehicle can’t meet the need of the real-time propulsion control in the on-ground inverter power substations. In this paper the design of the propulsion inverter control system with a position estimator for driving long-stator synchronous motor in high speed maglev train is proposed. The experiments have been carried out at the 150m long guideway in O-song test track. To investigate the performance of the position estimator, the propulsion control system with and without the position estimator are compared. The result confirms that the proposed strategy can meet the dynamic property need of propulsion inverter control system for driving long-stator linear synchronous motors

The fetal heart rate (FHR) is a screening signal for preventing fetal hypoxia during labor. When experts analyze this signal, they have to position a baseline and identify decelerations and accelerations. These steps can potentially be automated and made more objective by data processing analysis, but training and evaluation datasets are required. Here, we describe a dataset of 155 FHR recordings in which a reference baseline, accelerations and decelerations have been annotated by expert consensus. 66 FHR recordings with a shared expert analysis have been included in a training dataset, and 90 other FHR recordings with a non-shared expert analysis have been included in an evaluation dataset. Researchers wishing to evaluate their automatic analysis method should submit their results for comparison with the expert consensus. The dataset also contains the results produced by 11 re-coded automatic analysis methods from the literature. All the data are available at http://utsb.univ-catholille.fr/fhr-review.

High pressure crystallization technique has been successfully used to prepare an elusive form II of a non-steroidal anti-inflammatory drug, Mefenamic acid. Single crystal of form II was grown at 0.3 GPa from an 4:1 methanol/ ethanol mixture as a solvent using Diamond Anvil Cell. Comparison of crystal structures show that the efficient packing of MA molecules in Form II results from the structural flexibility of MA acid molecules. Compression studies performed on the single crystal of form I resulted in 14 % decrease of unit cell volume up to 2.5 GPa. No phase transition was observed up to this pressure. A reconstructive phase transition is required to induce conformational changes in the structure, which is confirmed by crystallization at high pressure results.

Semantic image segmentation has recently witnessed considerable progress by training deep convolutional neural networks (CNNs). The core issue of this technique is the limited capacity of CNNs to depict visual objects. Existing approaches tend to utilize approximate inference in a discrete domain or additional aides and do not have a global optimum guarantee. We propose the use of the multi-label manifold ranking (MR) method in solving the linear objective energy function in a continuous domain to delineate visual objects and solve these problems. We present a novel embedded single stream optimization method based on the manifold ranking (MR) model to avoid approximations without sacrificing expressive power. In addition, we propose a novel network, which we refer to as dual multi-scale manifold ranking (\textbf{DMSMR}) network, that combines the dilated, multi-scale strategies with the single stream MR optimization method in the deep learning architecture to further improve the performance. Experiments on high resolution images, including close-range and remote sensing datasets, demonstrate that the proposed approach can achieve competitive accuracy without additional aides in an end-to-end manner.

Abstract: High step-up voltage gain nonisolated DC-DC converter have attracted much attention in photovoltaic, fuel cells and other renewable energy system applications. In this paper, by combining input current ripple-free boost cell with coupled-inductor voltage-doubler cell, an input current ripple-free high voltage gain nonisolated converter is proposed. In addition, passive lossless clamp circuit is adopted to recycle the leakage inductor energy and to reduce the voltage spike across the power switch. By utilizing voltage-doubler cell consisting of diode and capacitor, the voltage stress of switch is further reduced and the resonance between the leakage inductor and the stray capacitor of the output diode is eliminated. A low switch-on-resistance low-voltage-rated MOSFET can therefore be employed to reduce the conduction loss and cost. The reverse recovery loss of output diode is reduced, and the efficiency of converter can be improved. Furthermore, the proposed converter can achieve nearly zero input current-ripple and make the design of electromagnetic interference (EMI) filter easy. Steady state analysis and operation mode of the converter is performed. Finally, experimental results are presented to verify the analysis results of the proposed converter.

This study explored the effects of cryogenic treatment on the microstructure, hardness, and wear-resistance of diamond-like carbon (DLC) by cryogenically treating NAK 80 mold steel coated with DLC. Raman spectroscopy analyzed the structure of the DLC film. Nanoindenter analyzed the hardness and Young’s modulus of the film, and their relationship determined the wear resistance. Wear test assessed the wear rate and friction coefficient of the DLC film. The results showed that cryogenic treatment increased the rate of carbide precipitation and refined the grain structure. Raman spectroscopy indicated that the Raman intensity rate (I_D/I_G) of treated DLC films was smaller than those without cryogenic treatment. When the sp3 bond increased, the hardness and wear-resistance of the DLC film also increased.

The Foreign Exchange rate is very much crucial for determining the economic health level of the country. The foreign exchange rate provides financial stability, enhances purchasing power and allows global trades. This rate usually fluctuates due to the market forces which control the supply and demand of the currency. Nominal and relative inflation and income level have a substantial effect on determining the exchange rates. Government measures, international situations, natural disasters or any unexpected situation like Covid-19, Rohingya crisis etc. can affect the exchange rates. Besides this, the interaction between the factors can create different reasoning to affect the market. This study tries to identify some factors with relevant examples.

The critical hypoxia in COVID-19 patients during this pandemic, has taken away many lives all around the globe. The mechanism has been poorly understood and initially, word got around that it was a SARS (Severe Acute Respiratory Syndrome) pneumonia. The atypical images in lung computerized axial tomography (CAT) scans were alarming. This immediately alerted everyone including poor countries to purchase lacking sophisticated ventilator equipment. However, in some countries, even 88% of the patients on ventilators lost their lives. New observations and pathological findings are gradually clarifying the disease. What seems evident is that it is not only one disease but several, with different responses in different countries and different altitudes. The critical hypoxia and «gasping» present in some patients are not totally understood. It was mentioned that it could be like a High-Altitude Pulmonary Edema (HAPE). Hereby, as high-altitude medicine and hypoxia physiology specialists, we compare the pathophysiology with that of high-altitude exposure in order to understand the mechanisms involved. Some differences in lung radiological images along with transmission and viral attack mechanisms are discussed. The oxygen transport triad used at high-altitude can be applied on this pathology in order to propose even the use of erythropoietin (EPO) early in the treatment. The immune system is the most important long-term survival tool, so we suggest a short-term strategy: the use of special Earth open-circuit astronaut-resembling suits with effective outside air filtering re-breathing mechanisms in order to return to work and daily activities, without contamination risk. Thereby, the curve can be flattened without quarantine and the economy could recover.

BackgroundThe novel virus COVID-19, also known as SARS-CoV‑2, is currently rapidly spreading around the globe and pushing healthcare systems to the limits of their capacity. One of the functions of predictive models is to timely act for epidemic preparedness including hospital preparedness. In Egypt, like many other countries in the world, the epidemic situation and forecasting have not yet sufficiently studied. ObjectiveThe study was carried out to develop a short-term forecast scenario for the COVID-19 epidemic situation in Egypt and predict the hospital needs to accommodate the growing number of cases.MethodsSecondary data from the COVID-2019 daily reports and the report issued 8^th of April by the Egyptian Ministry of Health and Population were used. Due to the daily changing level of knowledge and data, the article reflects the status up to 18 April 2020. The prediction was based on the exponential growth rate model. For the depiction of the situation, the full length of the epidemic timeline was analyzed (from February 14^th till April 18^th). The growth rates and their rates of decline during the period from the 22^nd of March till the 18^th of April were calculated and extrapolated in the coming 7 weeks. The predicted hospital needs were assessed against the announced allocated resources.ResultsThe epidemic curve in Egypt is on the ascending arm as of April, 18. The active cases showed exponential growth from the start of the epidemic till April, 18. At the end of this period time, the recovery rate was 23.12% and the case fatality rate (CFR) was7.39. The case fatality rate median level during the last four weeks was 6.64. The active cases are expected to reach more than 20,000 by late May then starts to decline. The allocated regular hospital beds are predicted to show shortage by the time of the release of the paper. The intensive care units (ICU) beds and ventilators are predicted to show insufficiency on May 6.Conclusions: The COVID-19 epidemic in Egypt is expected to continue on the rise for the next few weeks and expected to start to decline late in May, 2020. Our estimates should be useful in preparedness planning. Serious actions should be taken to provide ICU beds and ventilators enough for the predicted number of cases that would need them, not later than the end of April. Mitigation actions have to continue for the coming 6 weeks or until the epidemic situation is more clearly seen.

A literature review was conducted to summarize the frequency of the D-allele of the angiotensin-converting enzyme-1 in all countries with available data. Using an ecological study design limited to high income countries, we found that the country-level frequency of the D-allele was associated with increased COVID-19 incidence and mortality.

For distances less 10 nm, a total energy transfer occurs from a quantum emitter to a nearby metallic surface, producing evanescent surface waves that are plasmonic in nature. When investigating a metallic nanohole supported on an optically dense substrate (such as diamond with NV-), the scattering occurred preferentially from the diamond substrate towards the air for dipole distances less 10 nm from the aperture. In addition, an enhancement to the dipole's radiative decay rate was observed when resonance of the aperture matched the emitters wavelength. The relationship between an emitter and a nearby resonant aperture is shown to be that of the resonance energy transfer where the emitter acts as a donor and the hole as an acceptor. In conjunction with the preferential scattering behavior, this has led to the proposed device that operates in transmission mode, eliminating the need for epi-illumination techniques and optically denser than air superstrates in the collection cycle, hence making the design simpler and more suitable for miniaturization. A design criterion for the surface grating is also proposed to improve the performance, where the period of the grating differs significantly from the wavelength of the surface plasmon polaritons. Response of the proposed device is further studied with respect to changes in NV's position and its dipolar orientation to identify the crystallographic planes of diamond over which the performance of the device is maximized.

The objective of this study is to evaluate the effect of constitutive equations on the prediction accuracy for springback in cold stamping with various deformation modes. In this study, two types of yield functions—Hill’48 and Yld2000-2d—were considered to describe yield behavior. Isotropic and kinematic hardening models based on the Yoshida–Uemori model were also adopted to describe hardening behavior. Various material tests (such as uniaxial tension, tension- compression, loading-unloading, and hydraulic bulging tests) were carried out to determine the material parameters of the models. The obtained parameters were implemented in the finite element (FE) simulation to predict springback, and the results were compared with experimental data. U-bending and T-shape drawing were employed to evaluate the springback prediction accuracy. Obviously, the springback prediction accuracy was greatly influenced by constitutive equations. Therefore, it is important to choose appropriate constitutive equations for accurate description of material behaviors in FE simulation.

This study describes all the properties of high T_c cuprates by introducing rotating holes that are created by angular momentum conservations on a 2D CuO₂ surface, and which have a different mass from that of a normal hole because of the magnetic field energy induced by the rotation. This new particle called a macroscopic Boson describes the doping dependences of pseudo-gap temperature and the transition temperature at which an anomaly metal phase appears and describes the origin of the pseudo-gap. Furthermore, this study introduces a new model to handle many-body interactions, which results in a new statistic equation. This statistic equation describing many-body interactions accurately explains why high T_c cuprates have significantly high critical temperatures. Moreover a partition function of macroscopic Bosons describes all the properties of anomaly metal phase, which sufficiently agree with experiments, using the result from our previous study [1] that analytically describes the doping dependence of T_c. By introducing a macroscopic Boson and the new statistical model for many-body interactions, this study uncovered the mystery of high T_c cuprates, which have been a challenge for many researchers. An important point is that, in this study, pure analytical calculations are consistently conducted, which agree with experimental data well (i.e., they do not use numerical calculations or fitting methods but use many actual physical constants).

The aim of this research work was to provide model for predicting stock volatility in Nigeria Stock market. To achieve this, monthly data for Nigerian stock exchange, Exchange rate, Share index and inflation rate was collected for a period of January 1990 to December 2016.The descriptive statistics revealed these variables to exhibit volatility as a characteristics of financial time –varying series. DCC Model was fitted, were the coefficients for all the parameters and that of the correlation-Targeting (rho_21) are both negative and positive and tend very close to 1 and -1, indicating that high persistence in the conditional variances. The Model DCC, satisfied the properties of a good model of conditional mean and variance of the confidential Interval (C.I) of 1 and -1, that is, the conditional variances are finites and their series are strictly stationary. This therefore implies that the Nigerian Stock Exchange, Exchange rate, share index and Inflation rate will experience a non-steady shock in the Stock market. However Each of these variables have different length of recovery (volatility half- life) ranging from 1.5month, 6.5months, 6months to 2,4months for stock exchange, exchange rate, share index and inflation rate respectively. By implication, the volatility of these variables had a long memory, persistence and mean-reverting.

Covid-19 fatality rates of 0.37% (Gangelt, Germany) and 0.17% (Santa Clara, USA) have been reported, estimated from serological studies. We show that the two confidence intervals strongly overlap when the uncertainty in the number of deaths is taken into account, so that the two investigations may be regarded as representative of the same population (tentatively: “Western society with no overload of the Health Care System during the pandemic”). Combining the results, the Covid-19 fatality rate is estimated to be found with 95% confidence in the range [0.1%; 0.3%].

In the end of December 2019, a new strain of coronavirus was identified in the Wuhan city of Hubei province in China. Within a shorter period of time, an unprecedented outbreak of this strain was witnessed over the entire Wuhan city. This novel coronavirus strain was later officially renamed as COVID-19 (Coronavirus disease 2019) by the World Health Organization. The mode of transmission had been found to be human-to-human contact and hence resulted in a rapid surge across the globe where more than 1,100,000 people have been infected with COVID-19. In the current scenario, finding potent drug candidates for the treatment of COVID-19 has emerged as the most challenging task for clinicians and researchers worldwide. Identification of new drugs and vaccine development may take from a few months to years based on the clinical trial processes. To overcome the several limitations involved in identifying and bringing out potent drug candidates for treating COVID-19, in the present study attempts were made to screen the FDA approved drugs using High Throughput Virtual Screening (HTVS). The COVID-19 main protease (COVID-19 Mpro) was chosen as the drug target for which the FDA approved drugs were initially screened with HTVS. The drug candidates that exhibited favorable docking score, energy and emodel calculations were further taken for performing Induced Fit Docking (IFD) using Schrodinger’s GLIDE. From the flexible docking results, the following four FDA approved drugs Sincalide, Pentagastrin, Ritonavir and Phytonadione were identified. In particular, Sincalide and Pentagastrin can be considered potential key players for the treatment of COVID-19 disease.

The article reveals distinctive features of the interaction between architectural and structural solutions for the design of tall buildings as well as spotlights the most distinctive cases of expression. In the contemporary world, interaction is turning into the antithesis of the formerly dominant utilitarian attitude and standardization of tall buildings architectural solutions. Meanwhile, the search for rational structural solutions leads to new possibilities of architectural expression. This necessitates the transformation of a structural solution and its adaptation to the need of a modern architect to be exceptional and noticed. Interaction covers the current as well as retrospective and perspective periods. SWOT analysis was used by the authors of the article to assess the interaction between architectural and structural solutions in tall buildings design, select the most important criteria that could be used searching for rational architectural and structural solutions in future by applying multi-criteria decision making methods.

Previous studies on the prognostic impact of survivin expression in gastrointestinal (GI) cancer have yielded inconsistent results. This study was initiated to assess the relationship between survivin expression and overall survival (OS) or disease free survival (DFS) in GI cancer patients. We applied system literature searches on EMBASE, PubMed, Web of science, and the Cochrane library to conduct this up-to-date meta-analysis. Thirty studies with totally 3622 GI cancer patients were collected. The prevalence of high survivin expression in GI cancer was 0.57 (95% CI: 0.51-0.63). High survivin expression was significantly associated with shorter OS (HR 1.57, 95% CI: 1.42-1.74) and DFS (HR 1.38, 95% CI: 1.21-1.58). Subgroup analysis also showed significant association between high survivin expression and poorer OS or DFS in gastric cancer or colorectal cancer. In summary, our study indicated that high survivin expression was related to poor prognosis in GI cancer. Well-designed studies with large sample and more convincing data are needed to confirm our conclusion.

Tarsal tunnel syndrome is a focal compressive neuropathy of the posterior tibial nerve or one of its associated branches. Brief mention is made in the literature of the use of corticosteroid injections for this condition. The basic technique of hydrodissection is used for other nerve entrapments and includes identifying the region of nerve compression, and the injection of a fluid medium to dissect between structures or fascial planes. We introduce our treatment protocol using a methylprednisolone/sterile water/ropivacaine hydrochloride injectate mix and peripheral nerve stimulation to a perform hydrodissection technique for tarsal tunnel syndrome.

Field experiments were carried out during 2011-2014 at the Research and Experimental Center to Combating Desertification located in the Elsen Tasarkhai station of central Mongolia. The study was aimed to identify the effects of oxidized brown coal humic acid fertilizer on the relative growth rate of several trees for forest rehabilitation. The trees used were Populus sibirica, Salix ledebouriana and Acer tataricum. The experiment was carried out with the concentrations of 2,000, 10,000 and 20,000 mg L-1 of humic acid fertilization treatments. The measurement of relative height growth rate (RHGR) was conducted for a period of 4 years. The treatments showed significant differences within humic fertilizer concentrations which differed depending on the species. Compared to the monthly RHGR over the study, the treatment of fertilizers were significantly better for tree growth. P. sibirica in the 10,000 and 20,000 mg L-1 humic acid fertilizers had significant height growth rates. In addition, when the humic acid treatments were compared to control, A. tataricum decreased over the years which were statistically significant for high growth rate and a positive effect of humic acid fertilization treatments was observed. Furthermore, results showed that oxidized brown coal humic acid fertilizers as organic fertilizer can have a positive effect for the growth of A. tataricum during the study years. The results showed that the soil chemical properties EC, CO2, NO3, and K2O were significant among all the treatments compared to the control. The effect on P2O5 statistically significantly increased among all the treatments. However, pH and Mg were not significant effect among all the treatments. Combining the results obtained from the oxidized brown coal humic acid fertilization with sustainable land management practices can help improve soil organics for environmental issues in degraded sandy soil regions.

This study examines the exchange rate rebound effects of the Central Bank intervention in the selected ECOWAS economies. An empirical understanding of these effects is very important to trade adjustment as well as the macroeconomic stability in these countries. Using the panel data modelling framework, the study finds that the impact of the Central Bank intervention on exchange rate is insignificant and it does not lead to the exchange rate rebound. In addition, money supply as well as monetary policy rate implemented by the monetary authorities significantly influences the level of exchange rate in a positive direction.

In networked driving simulation, two or more human drivers participate interactively within a shared virtual environment. Thereby, typical applications of driving simulation can be extended to consider multi-driver scenarios, where a much closer approximation of reality with its unpredictability is achieved. However, the utilized network is typically prone to a considerable amount of message traffic. In addition to restricted system scalability, the resulting degradation of network performance leads to invalid simulation outcomes or unacceptable system behavior. High-level architecture (HLA) is an IEEE standard for networked simulation. Data distribution management (DDM) is one of the service groups provided by HLA standard. The aim of the DDM service is to reduce network traffic and to save effort required to process unnecessary received data. However, different approaches for current DDM implementations show major drawbacks in terms of utilization complexity, inefficiency, and yet added network overhead. This paper presents a concept of an interest manager that takes over the DDM functionality and avoids these drawbacks. Simulation data is exchanged between the participating driving simulators only when it is necessary according to the driving situations. The concept is validated by analyzing the network load of two driving maneuvers with and without the interest manager.

Study Objective: This study examined office workstation types’ impact on objective health-related metrics including stress, physical activity (PA), and sleep quality. We propose a sensor-based sleep quality index (SB-SQI) to fill a needed gap for objective sleep quality measurement over short timescales. Methods: We monitored 231 office workers using chest-worn sensors for 72 hours, yielding 11,736 hours of usable data from 163 participants (mean age 43.4, 56% women). SB-SQI was based on a validated algorithm estimating sleep-onset latency, total sleep time, and sleep efficiency, using the scoring method from the Pittsburg Sleep Quality Index (PSQI). We examined the relationships between SB-SQI, office workstation type (open-bench seating, cubicle, and private office), work-hours stress (standard deviation of heart rate variability), and after-work PA (relative duration of moderate-to-vigorous activity). Results: The sensor-derived poor-sleep ratio of the private office workers was higher than with other office workstation types (81% vs. 66.1%, p = 0.023). PSQI revealed a similar but insignificant trend with a lower effect-size. Among good-sleepers, open-bench seating workers had 22% (p = 0.018) less stress during work hours than others. A significant association between work-hours stress and after-work hours PA (r = 0.331, p = 0.000) was observed irrespective of office workstation type, with the highest PA level observed for open-bench seating workers. Conclusions: Office workstation type had a significant impact on work-hours stress, affecting PA after work hours, which influenced sleep quality. SB-SQI could be more sensitive than PSQI in determining the impact of office workstation types on sleep quality.

_{Superconducting foams of YBa$_2$Cu$_3$O$_y$ (YBCO) are proposed as trapped field magnets or supermagnets. The foams with an open-porous structure are light-weight, mechanically strong and can be prepared in large sample sizes. The trapped field distributions were measured using a scanning Hall probe on various sides of an YBCO foam sample after field-cooling in a magnetic field of 0.5 T produced by a square Nd-Fe-B permanent magnet. The maximum trapped field (TF) measured is about 400 G (77 K) at the bottom of the sample. Several details of the TF distribution, the current flow and possible applicatons of such superconducting foam samples in space applications, e.g., as active elements in flux-pinning docking interfaces (FPDI) or as portable strong magnets to collect debris in space, are outlined.}

In the recent concrete industry, high fluidity concrete is being widely used for the pouring of dense reinforced concrete. Normally, in the case of high fluidity concrete, it includes high binder contents, so it is necessary to replace part of the cement through admixtures such as fly ash to procure economic feasibility and durability. This study shows the mechanical properties and field applicability of high fluidity concrete that using mass of fly ash as alternative materials of cement. The high fluidity concrete mixed with 50% fly ash was measured to manufacture concrete that applies low water/binder ratio to measure the mechanical characteristics as compressive strength and elastic modulus. Also, in order to evaluate the field applicability, high fluidity concrete containing high volume fly ash was evaluated that fluidity, compressive strength, heat of hydration and drying shrinkage of concrete.

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

There are two contrary opinions regarding the risk if mainland China (MC) moves away from its zero-COVID policy. Some experts think the risk shall be much lower than influenza as per MC’s own COVID-19 case fatality rate (CFR), while some other experts think the risk shall be much higher than influenza as per the COVID-19 CFRs of other regions. We elucidate here that this and multiple other striking differences in the CFR between various scenarios all support and substantially resulted from the view that good IDM is highly powerful to mitigate COVID-19, where IDM (isolation-disinfection-maintenance) means isolation of COVID-19 cases from other people, disinfection of their living environments, and health maintenance (e.g., rest, nutrition, breathing). The high effect of good IDM is also supported by the theoretic functions of IDM in minimizing co-infections and maintaining body functions, and the fact that all the 505 COVID-19 deaths reported in MC in 2022 before May 5 died directly of severe underlying diseases with COVID-19. Although it is tough for people in poverty to obtain good IDM, good IDM can be feasible at home for the most mild cases and in hospitals for the most severe cases. Therefore, good IDM can be crucial to mitigating COVID-19 worldwide. It also suggests that the risk for China to end its zero-COVID policy depends on China’s control policies or measures. Based on the effect of IDM, the cautious co-existence policy was proposed for COVID-19 control. This policy could reduce the whole death toll in MC because good IDM is non-specific and can reduce deaths of various other diseases. The cautious co-existence policy (non-specific) and the vaccination policy (specific) aid each other to mitigate COVID-19, and they cannot replace each other. Those who are qualified in health for vaccination should be vaccinated against COVID-19 timely.

The production of lithium-ion battery cells is characterized by a high degree of complexit due to numerous cause-effect relationships between process characteristics. Knowledge about the multi-stage production is spread among several experts, rendering tasks such as failure analysis challenging. In this paper, a method is presented, which includes expert knowledge acquisition in production ramp-up by combining Failure Mode and Effects Analysis (FMEA) with a Bayesian Network. We show the effectiveness of this holistic method by building up a large scale, cross-process Bayesian Failure Network in lithium-ion battery production. Using this model, we are able to conduct root cause analyses as well as analyses of failure propagation. The former support operators in identifying root causes once a cell possesses a specific failure by calculating most-probable explanations matched to the individual battery cell data. The latter enable us to analyze propagation of failures and deviations in the production chain and thus provide support for placement of quality gates, leading to a significant reduction in scrap rate. Moreover, it gives an insight into which process steps are key drivers for which final product characteristics.

A novel high-voltage powerline inspection system is investigated, which consists of the cooperated ground vehicle and drone. The ground vehicle acts as a mobile platform that can launch and recycle the drone, while the drone can fly over the powerline for inspection within limited endurance. This inspection system enables the drone to inspect powerline networks in a very large area. Both vehicle’ route in the road network and drone’s routes along the powerline network have to be optimized for improving the inspection efficiency, which generates a new two-layer point-arc routing problem. Two constructive heuristics are designed based on “Cluster First, Rank Second” and “Rank First, Split Second”. Then local search strategies are developed to further improve the quality of the solution. To test the performance of the proposed algorithms, practical cases with different-scale are designed based on the road network and powerline network of Ji’an, China. Sensitivity analysis on the parameters related with the drone’s inspection speed and battery capacity is conducted. Computational results indicate that technical improvement on the inspection sensor is more important for the cooperated ground vehicle and drone system.

This paper identifies a criterion for choosing the largest set of rejected hypotheses in high-dimensional data analysis where Multiple Hypothesis testing is used in exploratory research to identify significant associations among many variables. The method neither requires predetermined thresholds for level of significance, nor uses presumed thresholds for false discovery rate. The upper limit for number of rejected hypotheses is determined by finding maximum difference between expected true hypotheses and false hypotheses among all possible sets of rejected hypotheses. Methods of choosing a reasonable number of rejected hypotheses and application to non-parametric analysis of ordinal survey data are presented.

During the conceptual and preliminary design stage of a ship, designers need to ensure that the selected principal dimensions and parameters are good enough to deliver a stable ship (statically and dynamically) besides deadweight and speed. To support this, the initial intact stability of the proposed ship is required to be calculated, and in doing so, the lightship weight and its detailed breakdown are necessary to be known. After hull steel weight, machinery weight, mainly, marine propulsion and power generation machinery, play a vital role in the lightship weight estimate of a ship due to its robustness. The correct estimation of respective weights improves the accuracy of calculating a ship's initial stability typically to be designed and built. Hence, it would be advantageous for the designer to convince the ship owner. A total of 3006 marine propulsion (main marine diesel) engines and 348 power generation (auxiliary marine diesel) engines/generators of various power output (generators output for auxiliary engines), engine RPM and cylinder number of different engine makers are collected. These are analyzed and presented in both tabular and graphical forms to demonstrate the possible relationship between marine propulsion engine weight and power generation engine weight, and their respective power output, RPM, cylinder number, power-RPM ratio and power-RPM ratio per cylinder.In this article, the authors have attempted to investigate the behavior of marine propulsion engine weight and power generation engine/generator weight regarding engine power output, generator power output, engine RPM and cylinder number (independent variables). Further attempts have been made to identify those independent variables that influence the weight of the marine propulsion engine and power generation engine/generator (dependent variables), and their interrelationships. A mathematical model has thus been developed and proposed, as a guiding tool, for the designer to estimate the weight of main and auxiliary engines more accurately during the conceptual and preliminary design stage.

Long-term, high-accuracy mapping of built-up land dynamics is essential for understanding urbanization and its consequences for the environment. Despite advances in remote sensing and classification algorithms, built-up land mapping using early satellite imagery (e.g., from the 2000s and earlier) remains prone to uncertainty. We mapped the extent of built-up land in the North China Plain, one of China’s most important agricultural regions, from 1990 to 2019 at three-year intervals. Using dense time-stack Landsat data, we applied discrete Fourier transformation to create temporal predictors and reduce mapping uncertainties for early years. We improved overall accuracy by 8% compared to using spectral and indices predictors alone. We implemented a temporal correction algorithm to remove inconsistent pixel classifications, further improving accuracy to a consistently high level (>94%) across years. A cross-product comparison showed that our study achieved the highest levels of accuracy across years. Total built-up land in the North China Plain increased from 37,941 km² in 1990–1992 to 131,578 km² in 2017–2019. Consistent, high-accuracy built-up land mapping provides a reliable basis for policy planning in one of the most rapidly urbanizing regions of the planet.

The precise information regarding the date of sowing, seed rate and row spacing is critical for achieving yield targets and better economic returns of barley. Therefore here, we determined the information regarding the optimum date of sowing, seed rate, spacing and economic aspects for barley production. This study was conducted for three years, in north Indian plains. Early sowing date of barley (last week of October) recorded higher yield in comparison to late sown crop (3^rd week of November). Moreover, the higher barley production proved more remunerative when sown early in the last week of October to the first week of November as compared to late sown the late sown crop. Furthermore, the enhanced seed rate of 10% then recommended did not affect the grain yield of barley. But, the closer spacing of 20 cm (row to row) produced higher grain yield (5.45 Mg ha^-1 ) than the recommended spacing of 22.5 cm (5.30 Mg ha^-1). Likewise, the economical parameters (net returns) were higher with 20 cm row spacing. Overall, this study determines the optimum date of sowing, seed rate and spacing for scoring better returns of barley crop under north Indian conditions.

The dependence of the critical temperature $T_c$ of high-temperature superconductors of various families on their composition and structure is proposed. A clear dependence of the critical temperature of high-temperature superconductors (hydrides, Hg- and Y-based cuprates) on the serial number of the constituent elements, their valence and crystal lattice structure has been revealed. For cuprates, it is shown that it is possible to obtain even higher temperatures of superconducting transitions at normal pressure by implanting mercury atoms into the crystal lattice of cuprate.

The three-dimensional single fin configuration finds application in an intake geometry where the cowl-shock wave interacts with the side-wall boundary-layer. Accurate numerical simulation of such three-dimensional shock/turbulent boundary-layer interaction flows, which are characterized by the appearance of strong crossflow separation, is a challenging task. Reynolds-averaged Navier-Stokes computations using the shock-unsteadiness modified Spalart-Allmaras model is carried out at Mach of 5 at large fin angle of 23^◦. The computed results using the modified model are compared to the standard Spalart-Allmaras model and validated against the experimental data. The focus of work is to implement the modified model and to study the flow physics in detail in the complex region of swept-shock-wave turbulent boundary-layer interaction in terms of the shock structure, expansion fan, shear layer and the surface streamlines. The flow structure is correlated to the wall pressure and skin friction in detail. It is observed that the standard model predicts an initial pressure location downstream of the experiments. The modified model reduces the eddy viscosity at the shock and predicts close to the experiments. Overall, the surface pressure using modified model is predicted accurately at all the locations. The skin friction is under predicted by both the models in the reattachment region and is attributed to the poor performance of turbulence models due to flow laminarization.

In the ongoing Covid-19 pandemic, if a preventive restriction (PR), intended to arrest the transmission of the virus, is effective we expect a decrease in the rate of transmission. If an effective PR is lifted or relaxed, the rate may show some increase. We test this expectation in the history of PR imposition and relaxation in all countries based on available public database. We found marginal or no negative correlation between standing stringency index of PR and change in slope of the local curve. A change in stringency index was significantly negatively correlated with change in slope, but change in stringency of PRs could explain only 6.1 percent of the variance in rates of transmission. The distribution of slope changes after imposing versus after relaxing PRs was highly overlapping with only a tail consisting of 4.5 % PR impositions being clearly non-overlapping with PR relaxation. Non-parametrically, only 9.4% of PR impositions were associated with a reduction in the slope above the expectation of a null hypothesis. In brief, globally, preventive restrictions have played a very small role in the pandemic process over the one year period. This feedback needs to be considered in making policy for disease prevention in the further course of the pandemic as well as in any future threats of respiratory disease epidemics.

Recently, light traps using light-emitting diode (LED) lights have been applied to monitor or control insect pests. The oriental armyworm, Mythimna separata Walker, is an important insect pest that has caused damage to several cereal crops, including corn, wheat and rice. The present study aims to seek out a sensitive wavelength causing high phototactic response in M. separata. The study evaluated the phototactic responses of M. separata moths to several LED lights of different wavelengths and luminance intensities under laboratory condition. Results showed that green (520 nm) LED light resulted in significant phototactic response of M. separata moths compared to LED lights of other wavelengths. Additionally, the highest attraction rate of the moths to green LED light appeared in luminance intensity group of 200 lux compared to the other intensities groups. Experiments under optimum conditions based on the above experiments revealed that the green LED light exhibited the strongest attraction rate (64.44%) among all experimental groups. An experiment performed in a net cage also showed that green LED light resulted in the highest phototactic response of M. separata moths, 1.7 times more than a commercial black light used as control. These findings clearly demonstrate that M. separata moths have a high sensitivity to the green LED light. Therefore, a light trap equipped with green LED light could be useful for monitoring and controlling M. separata moths.

Based on a modified dice-and-fill technique, a PIN-PMN-PT single crystal 1-3 composite with the kerf of 12 μm and pitch of 50 μm was prepared. The as-made piezoelectric composite material behaved with high piezoelectric constant (d33 = 1500 pC/N), high electromechanical coefficient (kt = 0.81), and low acoustic impedance (16.2 Mrayls). Using lithography and flexible circuit method, a 48-element phased array was successfully fabricated from such a piezoelectric composite. The array element was measured to have a central frequency of 20 MHz and a fractional bandwidth of approximately 77% at −6 dB. Of particular significance was that this PIN-PMN-PT single crystal 1-3 composite-based phased array exhibits a superior insertion loss compared with PMN-PT single crystal and PZT-5H-based 20 MHz phased arrays. The focusing and steering capabilities of the obtained phased array were demonstrated theoretically and experimentally. These promising results indicate that the PIN-PMN-PT single crystal 1-3 composite-based high frequency phased array is a good candidate for ultrasound imaging applications.

Significant problems have arisen in the last years, such as climate change, global warming, and hunger. These complications are correlated with the depletion and exploitation of natural resources and environmental contamination. Due to overcrowding, the list of challenges for the next few years is growing. A comprehensive approach was made to the agro-industrial production of Avocado (Persea americana) and the management of all its biomass waste. So, bioprocesses and biorefinery can be used to produce high added-value products. A large number of residues are composed of lignin and cellulose. They have many potentials to be exploited sustainably for chemical and biological conversion; physical, chemical, and natural treatments improve the following operations. There are some applications to many fields such as pharmaceutical, medical, material engineering, and environmental remediation. Possible pathways are mentioned to take advantage of Avocado as biofuels, drugs, bioplastics, and even in the environmental part and emerging technologies such as nanotechnology using bioprocesses and biotech. In conclusion, Avocado and its waste could be transformed into high value-added products in industries above to mitigate global warming and save non-renewable energy.

High-Intensity Functional Training (HIFT) is a novel exercise intervention that may test body systems in a balanced and integrated fashion by challenging individuals’ abilities to complete mechanical work. However, research has not previously determined if physical work capacity is unique to traditional physiologic measures of fitness. Twenty-five healthy men and women completed a six-week HIFT intervention with physical work capacity and various physiologic measures of fitness assessed pre- and post-intervention. At baseline, these physiologic measures of fitness (e.g., aerobic capacity) were significantly associated with physical work capacity and this relationship was even stronger at post-intervention assessment. Further, there were significant improvements across these physiologic measures in response to the delivered intervention. However, the change in these physiologic measures failed to predict the change in physical work capacity induced via HIFT. These findings point to the potential utility of HIFT as a unique challenge to individuals’ physiology beyond traditional resistance or aerobic training. Elucidating the translational impact of increasing work capacity via HIFT may be of great interest to health and fitness practitioners ranging from strength/conditioning coaches to physical therapists.

The mantle mass flow interconnected with the process of Glacial Isostatic Adjustment (GIA) and the reformation of the Earth’s crust constantly perturbs the observed gravity field towards a hypothetic isostatic state. We analyse the temporal changes of the gravity field from the GRACE data, using different mathematical and/or statistical methods to detect the GIA amidst other gravity signals. A number of gravimetric post-glacial land uplift rate (LUR) modelling methods are investigated and compared with the data from a total number of 515 GPS stations and preferred GIA forward models in Fennoscandia and North America. We investigate three mathematical methods, namely regression, principal component, and independent component analysis (ICA) to extracting the GIA signal from the GRACE monthly geoid heights. We use some regularization techniques to exploit the GRACE monthly data to their maximum spatial resolution and to increase the Signal to Noise Ratio of their short wavelengths. Near the centres of the study areas the gravimetric LUR model using the fast-ICA algorithm of Hyvärinen and Oja (2000) is shown to be in a complete agreement with the GPS data and the predictions of the GIA forward models, and for the whole areas, subject to epeirogeny movement of the two regions, their discrepancies reach to the extrema at -1.8 and +3.3, and -4.5 and +7.5 mm/a, respectively. We show that the largest discrepancies between the gravimetric model using the ICA method and the GIA forward model, occur for the sub-regions likely collocated with strong ice mass change signals.

Several articles have reported that the low number of COVID-19 cases in Japan is attributed to the small number of diagnostic RT-PCR tests performed. The criticism is based on the low number of the tests performed, and they suspected there would be more potential cases in Japan. The use of pre-test probability among tested subjects is proposed in order to evaluate of the sufficiency of test availability instead of the number of the tests. The pre-test probability means the average probability, i.e., ‘suspicion level’, of having coronavirus among the tested subject in a country. The higher pre-test probability is regarded as less sufficient opportunity of the tests, and the test availability could be evaluated by the pre-test probability. Thus, potential problems of underestimation of COVID-19 cases by insufficient amount of the test would be clear by using pre-test probability. The comparison of the pre-test probability could be replaced with that of the positive rate of the test because of the linear relationship between them under the assumption of common sensitivity and specificity. Japan shows the third lowest rate (8.6%), and is considered that the considerably sufficient number of the tests have been performed. In conclusion, the positive rate of the test as a surrogate index of the pre-test probability is useful to evaluate the sufficiency of test amount instead of the number of the tests performed. In present, the potential problem of underestimation by insufficient test availability would be less serious in Japan.

Gabapentin (GBP), a GABA analogue, is primarily used as an anticonvulsant to treat partial seizures and neuropathic pain. While a majority of the side effects are associated with the nervous system, emerging evidence suggests a high risk for heart diseases in the patients taking GBP. In the present study, we used a preclinical model of rats to investigate (1) the acute cardiovascular responses to GBP (bolus i.v. injection, 50 mg/kg) and (2) the effects of chronic GBP treatment (i.p. 100 mg/kg/day x 7 days) on cardiovascular function and the myocardial proteome. Under isoflurane-anesthesia, rat blood pressure (BP), heart rate (HR), and left ventricular (LV) hemodynamics were measured using Millar pressure transducers. The LV myocardium and brain cortex were analyzed by proteomics, bioinformatics, and western blot to explore the molecular mechanisms underlying GBP-induced cardiac dysfunction. In experiment (1), we found that i.v. GBP significantly decreased BP, HR, maximal LV pressure, and maximal and minimal dP/dt, whereas it increased IRP-AdP/dt, Tau, systolic, diastolic, and cycle durations (*p < 0.05 and **p < 0.01 vs baseline; n = 4/group). In experiment (2), we found that chronic GBP treatment resulted in hypotension, bradycardia, and LV systolic dysfunction, with no change in plasma norepinephrine. In the myocardium, we identified 109 differentially expressed proteins involved in calcium pathways, cholesterol metabolism, and galactose metabolism. Particularly, we found that calmodulin, a key protein of intracellular calcium signaling, was significantly upregulated by GBP in the heart but not in the brain. In summary, we found that acute and chronic GBP treatments suppressed cardiovascular function in rats, which is attributed to abnormal calcium signaling in cardiomyocytes. These data reveal a novel side effect of GBP independent of the nervous system, providing important translational evidence to suggest that GBP can evoke adverse cardiovascular events by depression of myocardial function.

Renal artery thrombosis is a sporadic serious clinical condition which potentially cause renal infarction. Diagnosis of renal infarction can be delayed or missed due to non specific clinical presentation and overlapping appearance of medical and surgical phenomena. Early diagnosis supported by biochemical and radiological findings while appropriate management potentially improve morbidity and mortality. Persistent abdominal or flank pain with raised LDH and proteinuria on background of thromboembolism risk factors supports the diagnosis. Despite the rarity of the disease rapid identification with prompt medical or endovascular intervention could prevent irreversible renal parenchymal damage.

Integrated ultra-low-loss waveguides are highly desired for integrated photonics to enable applications that require long delay lines, high-Q resonators, narrow filters, etc. Here we present an ultra-low-loss silicon waveguide on 500 nm thick SOI platform. Meter-scale delay lines, million-Q resonators and tens of picometer bandwidth grating filters are experimentally demonstrated. We design a low-loss low-reflection taper to seamlessly integrate the ultra-low-loss waveguide with standard heterogeneous Si/III-V integrated photonics platform to allow realization of high-performance photonic devices such as ultra-low-noise lasers and optical gyroscopes.

Background: Some patients who have recovered from COVID-19 have experienced a range of persistent symptoms or the appearance of new ones after a SARS-CoV-2 infection. These symptoms can last from weeks to months, impacting everyday functioning to a significant number of patients. Methods: A cross-sectional analysis based on an online, self-reporting questionnaire was conducted in Ecuador from April to July 2022. Participants were invited by social media, radio, and TV to voluntarily participate in our study. A total of 2103 surveys were included in this study. We compared socio-demographic variables and long-term persisting symptoms at low (&lt; 2,500 m) and high altitude (&gt;2,500 m).Results: Overall, 1100 (52.3%) responders claimed to have long-term symptoms after SARS-CoV-2 infection. Most of these symptoms were reported by women (64.0%), the most affected group was young adults (68.5%), and the majority of long-haulers were mestizos (91.6%). We found that high altitude residents were more likely to report persisting symptoms (71.7%) versus those living at lower altitudes (29.3%). The most common symptoms were fatigue or tiredness (8.4%), hair loss (5.1%) and difficulty concentrating (5.0%). The highest proportion of persisting symptoms was observed among those who received an incomplete vaccine scheme.Conclusions: This is the first study describing post-COVID symptoms' persistence in low and high-altitude residents. Our findings demonstrate that women, especially those aging between 20-40, are more likely to describe sequalae associated with post-COVID. We also found that living at a high altitude was associated with earlier onset and longer symptom duration. Finally, we found a greater risk to report long lasting symptoms among women, those with previous comorbidities and those who had a severer acute SARS-CoV-2 infection.

Topology optimization is a pioneering design method that can provide various candidates with high mechanical properties. However, the high-resolution for the optimum structures is highly desired, normally in turn leading to computationally intractable puzzle, especially for the famous Solid Isotropic Material with Penalization (SIMP) method. In this paper, an efficient and high-resolution topology optimization method is proposed based on the Super-Resolution Convolutional Neural Network (SRCNN) technique in the framework of SIMP. The SRCNN includes four processes, i.e. refining, path extraction & representation, non-linear mapping, and reconstruction. The high computational efficiency is achieved by a pooling strategy, which can balance the number of finite element analysis (FEA) and the output mesh in optimization process. To further reduce the high computational cost of 3D topology optimization problems, a combined treatment method using 2D SRCNN is built as another speeding-up strategy. A number of typical examples justify that the high-resolution topology optimization method adopting SRCNN has excellent applicability and high efficiency for 2D and 3D problems with arbitrary boundary conditions, any design domain shape, and varied load.

Gender recognition is trivial for physiotherapist, but it is considered a challenge for computers. The electromyography (EMG) and heart rate variability (HRV) were utilized in this work for gender recognition during the stepping exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC) function in a combinatorial fusion approach (CFA) was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB), decision tree (J48), k-nearest neighbor (KNN) and support vector machine (SMO). Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Nazarloo's work (90.34%) and other classifiers.

I propose a dynamic evolution hypothesis regarding the evolution of organisms by incorporating both diminished fitness returns and mutation rate tuning during adaptation to a constant environment. Basically, accumulating evidence from life history studies conducted over the past 70 years suggests that the evolution of individual fitness is subject to ecological constraints, leading to the evolutionary existence of an upper limit of individual fitness (ULIF). Given the existence of the ULIF, organismal evolution, which might initially have relatively great fitness returns through primarily Darwinian evolution, will eventually be subject to diminished fitness returns towards zero. With the diminished fitness return, Darwinian selection strength may eventually become smaller than the power of random genetic drift, leading to the occurrence of neutral evolution at both phenotypic and molecular levels. Meanwhile, mutation rates may change from an initial increase, due to the relatively strong fitness return, to subsequent decreases, due to both the diminished fitness return of beneficial mutations and the cost of deleterious mutations. The diminished fitness returns with subsequently reduced mutation rates are two potential evolution barriers leading to eventual evolutionary stasis. These findings provide important insights for understanding the conditions for the occurrences of different evolutionary patterns. Darwinian evolution theory, neutral evolution theory and punctuated equilibrium theory can be unified in the context of the dynamic evolution hypothesis formulated in this study.

During middle age, women are less susceptible to nonalcoholic steatohepatitis (NASH) than men. Thus, we investigated the underlying molecular mechanisms behind these sexual differences using an established rat model of NASH. Mature female and male stroke-prone spontaneously hypertensive 5/Dmcr rats were fed control or high-fat-cholesterol (HFC) diets for 2, 8, and 14 weeks. Although HFC-induced hepatic fibrosis was markedly less severe in females than in males, only minor gender differences were observed in expression levels of cytochrome P450 enzymes (CYP)7A1, CYP8B1 CYP27A1, and CYP7B1, and multidrug resistance-associated protein 3, and bile salt export pump, which are involved in fibrosis-related bile acid (BA) kinetics. However, the BA detoxification-related enzymes UDP-glucuronosyltransferase (UGT) and sulfotransferase (SULT) 2A1, and the nuclear receptors constitutive androstene receptor (CAR) and pregnane X receptor (PXR), were strongly suppressed in HFC fed males, and were only slightly changed in HFC-diet fed females. Expression levels of the farnesoid X receptor and its small heterodimer partner were similarly regulated in a gender-dependent fashion following HFC feeding. Hence, the pronounced female resistance to HFC-induced liver damage likely reflects sustained expression of the nuclear receptors CAR and PXR and the BA detoxification enzymes UGT and SULT.

This study employed the Fully Modified Ordinary Least Squares (FMOLS) and the Error Correction Model (ECM) to investigate the long-run and short-run determinants of unemployment rate in Nigeria. To achieve this annual data on unemployment rate, inflation rate, interest rate, exchange rate and population growth from 1981 to 2016 was collected from Central Bank Statistical Bulletins and the World Bank website. The ADF test revealed that the macroeconomic variables are stationary at first difference while the Cointegration test revealed that the variables are cointegrated. Using unemployment rate as dependent variable, the FMOLS model revealed that exchange rate and population growth are positively significantly related to unemployment rate, interest rate and inflation rate were negatively related to unemployment rate but only interest rate was significant. The short run relationship revealed that the coefficient of the ecm(-1) is negative and statistically significant at 5% level indicating that the system corrects its previous period disequilibrium at the speed of 48.93% yearly. This study concludes that high exchange rate and population growth can lead to increase in unemployment rate in Nigeria while the government should develop the industrial sector and non-oil sector in order to generate employment and boost export in Nigeria.

Rural electrification rate (RER) in Africa is still low to date. Several countries in Sub-Saharan Africa have tried to address this problem using conventional single-phase two-wire or three-phase three-wire systems, however at large costs due to the nature of dispersed rural load centers, low load demand, and low population density. Another solution of off-grid generation creates associated health problems. Therefore, this paper undertakes a review of a single wire earth return (SWER) network as a RER improvement solution. The paper undertakes intensive literature review to elucidate challenges and solutions to the implementation of SWER technology. Advantages of SWER technology discussed make it the choice for RER improvement in Sub-Saharan African countries. After that, a case study is selected in rural Tanzania, and a preliminary SWER network design is undertaken.

Understanding of the decisive role of the interaction mechanism and kinetics in the combustion processes is highly relevant for the elaboration of optimal conditions for obtaining Mo-Cu composite powders. From this perspective, the efficient delivery of the reduction mechanism of copper and molybdenum oxides with combined Mg + C reducing agents at high heating rates is crucial to develop a valuable approach for the combustion synthesis of Mo-Cu composite powders. Herein, we shed light on the mechanism of the reactions in all the studied binary, ternary and quaternary systems contemporaneously demonstrating the effect of the heating rate on the conversion degree. The combination of two highly exothermic and speedy reactions (MoO3+3Mg and CuO+Mg vs MoO3+CuO+4Mg) led to a slow interaction with weak self-heating (dysynergistic effect) due to a change in the reaction mechanism. On the other hand, it has been shown that during the simultaneous utilization of the Mg and C reducing agents, the process begins exclusively with carbothermic reduction, and at relatively high temperatures it continues with magnesiothermic one. The effective activation energy values of the magnesiothermic stages of the studied reactions were determined by Kissinger isoconversional method.

This research focuses on the effect of trampling on vegetation in high-mountain ecosystems through the electromagnetic spectrum’s interaction with plant pigments, cell structure, water content and other substances that have a direct impact on leaf properties. The most heavily visited part of the High Tatras in Poland was divided into polygons and, after selecting the dominant species within alpine swards, a detailed analysis of trampled and reference patterns was performed. An ASD FieldSpec 3 was used to acquire high-resolution spectral properties of plants, their fluorescence and the leaf chlorophyll content with the ts-ta temperature index and fraction of accumulated radiation in the range of photosynthesis (fAPAR) used as reference data. The results show that, along tourist trails, vegetation adapts to trampling with the impact depending on the species. A lower chlorophyll value was confirmed by a decrease in fluorescence, and the state of cellular structures was degraded in trampled compared to reference species, with a lower leaf reflectance. Also, at the extreme, trampling can eliminate certain species such as Luzula alpino-pilosa.

Infiltration based stormwater best management practices bring considerable economic, social and ecological benefits. Controlling stormwater quantity and quality are primarily important to prevent urban flooding and minimizing loads of pollutants to the receiving waters. However, there have been growing concerns about how the traditional design approach contributes to the failure of infiltration based BMP’s that have caused flooding, ponding, prolonged movement of surface water, and frequent clogging, etc. Many of these problems were due to the fact that the current design approaches of stormwater BMP’s only focus on surface hydrology and give little or no attention to the underline subsoil permeability rate and other constraints during the design and sizing process. As a result, we are exhibiting many newly constructed infiltration based BMP’s are failing to function well. This paper presents and demonstrates a new paradigm shift in designing infiltration-based stormwater BMP’s by combining subsurface hydrology and undelaying native soil constraints to establish acceptable criteria for sizing infiltration based BMPs.

Thin films (100-400 nm) of Ba_xSr_1-xTiO₃ (0≤x≤1) deposited in RF-magnetron co-sputtering equipment are presented in this research work. The change of deposition rate, gap energy, and resistivity as a function of temperature- applied power change in the growth parameters was studied through the ISO colour-code lines constructed with MATLAB: By analysing the trend information and take into account the influence of the calculated "x" parameter with the Boltzmann profile fitting is proposed a method to allow a controlled set up of the RF-magnetron co-sputtering system and predict the E_g and resistivity values in the Ba_xSr_1-xTiO₃ solid solution with 0≤x≤1 for amorphous and crystalline phases. Also, a versatile tool to optimise the deposition process and material properties.

Lattice and code cryptography can replace existing schemes such as Elliptic Curve Cryptography because of their resistance to quantum computers. In support of public key infrastructures, the distribution, validation and storage of the cryptographic keys is then more complex to handle longer keys. This paper describes practical ways to generate keys from physical unclonable functions, for both lattice and code based cryptography. Handshakes between client devices containing the PUFs and a server are used to select sets of addressable positions in the PUFs, from which streams of bits called seeds are generated on demand. The public and private cryptographic key pairs are computed from these seeds together with additional streams of random numbers. The method allows the server to independently validate the public key generated by the PUF, and act as a certificate authority in the network. Technologies such as High performance computing, and graphic processing units can further enhance security by preventing attackers to make this independent validation when only equipped with less powerful computers.

Farmers and seed companies constantly require high-quality seeds with excellent agronomic performance. However, faced with environmental adversity, limited natural resources and increasing food demand around the globe, more attention has turned to improving crop plant production by implementing efficient strategies. Seed priming technology has shown promising biological improvements leading to suitable agronomic performance in crop plants under adverse environmental conditions. Seeds are subjected to controlled conditions that are conducive to complex physiological, biochemical, and molecular changes, conferring specific stress tolerance to subsequent germination and growth conditions. In this review paper, we aimed to study the recent approaches in the efficiency of hydropriming, osmopriming, chemopriming, hormopriming, nanopriming, matrix priming, biopriming, physical priming and hybrid priming procedures in the production of crop plants under environmental adversity, as well as their biological mechanism changes. All priming methods demonstrated relevant changes in the biological mechanism related to crop plant production by mitigating salinity effects, heavy metals, and flooding stress and enhancing chilling, heat, drought and phytopathogen tolerance. We strongly recommend that researchers combine multiple priming methods, known as hybrid priming, in their investigations to provide novel technologies and additional biological approaches to enhance the knowledge of crop plant science. Thus, the findings shed light on the use of seed priming technology as a key strategy to increase crop plant production under environmental adversity by acquiring stress tolerance and enhancing agronomic traits to meet the global food demand.

Populations with essential hypertension have a high risk of nonalcoholic steatohepatitis (NASH). In this study, we investigated the mechanism that underlies the progression of hypertension-associated NASH by comparing differences in the development of high fat and cholesterol (HFC) diet-induced NASH among three strains of rats, i.e., two hypertensive strains comprising spontaneously hypertensive rats and the stroke-prone spontaneously hypertensive 5/Dmcr, and the original Wistar Kyoto rats as the normotensive control. We investigated histopathological changes and molecular signals related to inflammation in the liver after feeding with the HFC diet for 8 weeks. The diet induced severe lobular inflammation and fibrosis in the livers of the hypertensive rats, whereas it only caused mild steatohepatitis in the normotensive rats. Increased activation of proinflammatory signaling (transforming growth factor-β1/mitogen-activated protein kinases pathway) was observed in the hypertensive strains fed with the HFC diet. In addition, the HFC diet suppressed the nuclear factor erythroid 2-related factor 2 pathway in the hypertensive rats and led to lower increases in the hepatic expression of heme oxygenase-1, which has anti-oxidative and anti-inflammatory activities. In conclusion, these signaling pathways might play crucial roles in the development of hypertension-associated NASH.

Sulfonated carbon was used as an efficient and reusable heterogeneous solid acid catalyst for the synthesis of biodiesel via esterification of oleic acid with methanol under high voltage conditions. Using an inexpensive and reusable catalyst, environmental benignity, excellent yields in short times, synthesis in atmospheric pressure and low temperature conditions are some of the important features of this protocol. In the final results were confirmed by GC.