The purpose of this study was to determine the income, costs and revenue of the Gontor Putri 3 bakery. Want to know the efficiency of the bakery business in Karangbanyu Regency. The method used in this research is analytical descriptive by conducting a survey. The data used in this research is primary data. Data collection techniques use observation, interviews and documentation, while the process of analysis is quantitative descriptive. Using the R/C ratio, a value of 1.72 per month is obtained. This value indicates that the bakery factory in Karangbanyu is efficient because the value is more than one.

Sickle cell disease (SCD) is an inherited disorder of major health challenge in Nigeria. Micronutrients deficiencies often associated with the disorder may cause inflammation and abnormal metabolisms in the body. The copper-to-zinc ratio is a more important assessment than the concentrations of either of the metals in clinical practice. This study seeks to evaluate serum levels of c-reactive protein (CRP), copper, zinc and copper-to-zinc ratio and to correlate copper-to-zinc ratio with CRP in adult subjects with SCD. Serum copper, zinc, CRP and plasma fibrinogen were assayed in 100 confirmed SCD patients in steady clinical state and 100 age and sex matched subjects with normal haemoglobin. Serum copper and zinc were assayed by colorimetric method using reagents supplied by Centronic, Germany while CRP and fibrinogen were assayed using reagents supplied by Sigma (St. Louis, MO, USA) and Anogen (Ontario, Canada), respectively. The copper to zinc ratio was calculated from serum levels of copper and zinc. The measured parameters were compared between the groups using Students t-test and Pearson correlation coefficient was used to relate CRP with the other parameters. Serum copper, CRP, fibrinogen and copper-to-zinc ratio were significantly higher (p < 0.001) while zinc level was lower in SCD patients than controls. Serum CRP concentration correlated with copper (r = 0.10; p < 0.02), zinc (r = −0.199; p < 0.05) and Copper-to-zinc ratio (r = 0.312; p < 0.002) but the correlation between CRP and fibrinogen was not significant. Inflammatory condition may modulate copper and zinc homeostasis and copper-to-zinc ratio may be used as marker of nutritional deficiency and inflammation in SCD patients.

The article presents comparative results from 5 categories of animals (4 samples originating from pigs, 2 from cows, 1 from chicken, 1 from ostriches, 1 from horses, samples quantified with A, B, C, D, E, F, G, H, I). These samples were collected from large, medium and small (family) farms. The results were validated by the biogas production generated by the respective samples, using the Automatic Methane Potential Test System (AMPTS II) bio-processor. The largest amounts of biogas (2,464.5 Nml, 2,262.0 Nml) were recorded for the samples from pig farms (Sample B and Sample D), whereas the lowest values were obtained in the case of Sample A (414.1 Nml) and Sample C (558.3 Nml). The heavy metals analyzed in the article are Zn, Cu, Fe, Mn, Ca, K, As. The results corroborate that the C/N ratio can also vary to values lower than 20-30, without affecting the biogas production process, and the heavy metal content must be known especially for the full management of the wastes. All final data presented in the article are based on repeated, triplicate experiments, with less as 2% deviation between data.

Ustekinumab, a new anti-interleukin-12/23 antibody, is an effective treatment for ulcerative colitis; however, data regarding predictive factors of its efficacy are limited. This study aimed to identify biomarkers that can predict the long-term outcome of ustekinumab treatment. We retrospectively reviewed the records of patients with active ulcerative colitis treated with ustekinumab at our hospital from June 2020 to January 2023. We divided patients into non-remission and remission groups, and examined whether baseline biomarkers, including C-reactive protein-to-lymphocyte ratio, and early treatment response could predict clinical remission at week 48 of ustekinumab treatment. Of the 33 patients included in the study, 21 (63.6%) were in clinical remission at week 48 of ustekinumab treatment. The baseline C-reactive protein-to-lymphocyte ratio value was identified as an independent prognostic factor for clinical remission at week 48 (odds ratio: 10, 95% confidence interval: 1.6–62.4, p=0.014), with the cutoff value of 3.353 showing excellent prognostic performance (sensitivity: 71.4%, specificity: 83.3%). Furthermore, the clinical response at week 4 (p=0.009) and that at week 8 (p=0.005) were significantly associated with clinical remission at week 48. The baseline C-reactive protein-to-lymphocyte ratio value and early treatment response are useful biomarkers to predict the long-term efficacy of ustekinumab treatment.

Type 2 diabetes mellitus may be complicated with chronic complications including diabetic neuropathy (DN). Timely diagnosis is crucial in treatment and maybe reversal of this complication. C reactive protein to albumin ratio (CAR) is considered as a marker of inflammation in various diseases that characterized with acute or chronic inflammation. Since diabetic neuropathy and type 2 diabetes mellitus are also associated with chronic, low grade inflammation, we aimed to study CAR levels of type 2 diabetic subjects with diabetic neuropathy and to compare to those in patients without diabetic neuropathy. Type 2 diabetic patients presented to our institutional outpatient clinics were divided into two according to the presence of DN. Subjects with DN were listed as DN group and others were as non-DN group. Characteristics and laboratory data, including CAR, in DN and non-DN groups were compared. Median CAR of the DN and non-DN groups were 2,19 (0,2-49)% and 0,56 (0,02-5,8)%, respectively (p&lt;0.001). CAR was significantly and positively correlated with age (r=0.15, p&lt;0.001), weight (r=0.19, p=0.01), BMI (r=0.11, p=0.03), waist circumference (r=0.10, p=0.046), fasting plasma glucose (r=0.14, p=0.004), serum creatinine (r=0.25, p&lt;0.001), triglyceride (r=0.17, p&lt;0.001), and LDL-cholesterol (r=0.13, p=0.001) levels. Moreover, CAR was inversely correlated with eGFR levels (r=-0.16, p&lt;0.001). The sensitivity and specificity of CAR (when higher than 1,02%) in predicting diabetic neuropathy were 78% and 73%, respectively (AUC: 0.84, p&lt;0.001, 95% CI: 0,82-0,87). Moreover, high CAR level was an independent risk factor of diabetic neuropathy (p&lt;0.001, OR: 1.34, 95% CI: 0.48-1.62). In conclusion, elevated CAR levels could be considered as a marker of diabetic neuropathy.

Emerging pollutants as pharmaceuticals have been focusing international attention for few decades. Ciprofloxacin (CIP) is a common drug widely found in effluents from hospitals, industrial and different wastewater treatment plants, as well as rivers. In this work, the lab-scale 3D-BER system was established, and more than 90% of the antibiotic CIP removal from the Low C/N wastewater. Best results were obtained with current intensity, and different C/N ratio significantly improve the removal of CIP and nitrates, when the ideal conditions were; C/N = 1.5-3.5, pH =7.0-7.5, and I = 60 mA. The highest removal efficiency of CIP = 94.20 %, NO3--N= 95.53 % and total nitrogen (TN) = 84.27 %, respectively. In this novel system, the autotrophic-heterotrophic denitrifying bacteria played vital role for the removal of CIP and enhanced denitrification process. Thus, autotrophic denitrifying bacteria uses CO2 and H2 as carbon sources to reduce nitrates to N2. This system has the assortment and prosperous community revealed at the current intensity of 60 mA, and the analysis of bacterial community structure in effluent samples fluctuates under different condition of C/N ratios. According to the results of LC-MS/MS analysis, the intermediate products were proposed after efficient biodegradation of CIP. Microbial community on biodegrading was mostly found at phylum, and class level was dominantly responsible for the NO3--N and biodegradation of CIP. This work can provide some new insights towards the biodegradation of CIP and the efficient removal of nitrates from low C/N wastewater treatment by the novel 3D-BER system.

Abstract: Bulgaria is famous for its oil-bearing rose. R. damascena Mill. and R. alba L. are mainly cultivated in the country, but a recent survey of industrial plantations in 2020 revealed that R. centifolia L. and hybrids of R. damascena Mill. x R. gallica L. are also common in the rose valley. Although their essential oil cannot be compared in quality with the classic, they are preferred by farmers with high yields of flowers and resistance to diseases and pests. All these roses are also used to produce rose water and extracts. The aim of this investigation was to compare the yield and chromatographic fingerprints of seven rose oils and hydrosols produced in Bulgaria. The quantitative composition of the main components of the oils was compared with the norms of the world standard. Our study showed that the yield of essential oil from these roses was in the range of 0.015 - 0.048%. The main group in the chemical composition is terpene alcohols, which vary in the range: geraniol (17.60 - 34.02 %), citronellol (8.38 - 28.7 %), and nerol (4.8 - 11.90 %), but with a different ratio. Hydrocarbons are represented by saturated aliphatic homologs with an odd number of carbon atoms, the main ones being: nonadecane (8.10 - 22.67 %), heneicosane (4.37 - 10.21 %), heptadecane (1.07 - 2.98 %) and triclosan (0.81 - 5.90 %). In contrast, the chemical profile of the hydrosols was performed by phenyl ethyl alcohol (27.45 - 69.88 %), geraniol (13.72 - 28.67 %), and citronelol+nerol (4.56 - 17.37 %). The results show that the presence of plantations with a genotype different from that of R. damascena implies differences in the quality of rose oils and hydrosols. This predetermines their properties of use.

C-reactive protein to lymphocyte ratio (CLR) has been shown to be associated with diseases characterized by chronic, low-grade inflammation. Since type 2 diabetes (T2DM) is also associated with inflammation, we aimed to study the association between CLR and T2DM. Patients with T2DM who presented to internal medicine outpatient clinics of our institution were divided into 2 groups according to their glycosylated hemoglobin (HbA1c) levels as well-controlled (HbA1c&lt;7%) and poorly controlled (HbA1c≥7%) T2DM groups. Subjects assigned as healthy in routine check-up were included as control group. CLR values of the well and poorly controlled diabetics and control cases were compared. CLR of T2DM group (3.51 (0.03-21.78)) was significantly higher than that of the controls (0.65 (0.02-2.92)) (p&lt;0.001). CLR was found to have a sensitivity of 63.2% and a specificity of 97.3% in predicting T2DM. The CLR value of patients with poor diabetic control was 4.76 (0.06-21.78), while the CLR value of patients with well controlled disease was 2.53 (0.03-12.07) (p&lt;0.001). The sensitivity and specificity of the CLR in demonstrating poor diabetic control was 41.2% and the 86.1%, respectively. In conclusion, elevated CLR in T2DM patients and even more increased levels in poorly controlled diabetics suggest that CLR could be a useful additional diagnostic tool in treatment follow-up of the T2DM population.

To ensure the safety in aircraft flying, we aim use of the deep learning methods of nondestructive examination with multiple defect detection paradigms for X-ray image detection posed. The use of the Fast Region-based Convolutional Neural Networks (Fast R-CNN) driven model seeks to augment and improve existing automated Non-Destructive Testing (NDT) diagnosis. Within the context of X-ray screening, limited numbers insufficient types of X-ray aeronautics engine defect data samples can thus pose another problem in training model tackling multiple detections perform accuracy. To overcome this issue, we employ a deep learning paradigm of transfer learning tackling both single and multiple detection. Overall the achieve result get more then 90% accuracy based on the AE-RTISNet retrained with 8 types of defect detection. Caffe structure software to make networks tracking detection over multiples Fast R-CNN. We consider the AE-RTISNet provide best results to the more traditional multiple Fast R-CNN approaches simpler translate to C++ code and installed in the Jetson™ TX2 embedded computer. With the use of LMDB format, all images using input images of size 640 × 480 pixel. The results scope achieves 0.9 mean average precision (mAP) on 8 types of material defect classifiers problem and requires approximately 100 microseconds.

In this paper, we present a new concept of the generalized core orthogonality (called the C-S orthogonality) for two generalized core invertible matrices $A$ and $B$. $A$ is said to be C-S orthogonal to $B$ if $A^{\tiny\textcircled{S}}B=0$ and $BA^{\tiny\textcircled{S}}=0$, where $A^{\tiny\textcircled{S}}$ is the generalized core inverse of $A$. The characterizations of C-S orthogonal matries and the C-S additivity are also provided. And the connection between the C-S orthogonality and C-S partial order has been given using their canonical form. Moreover, the concept of the strongly C-S orthogonality is defined and characterized.

The regulation of multiple bacterial phenotypes was found to depend on different cyclic di-nucleotides (CDNs) that constitute intracellular signalling second messenger systems. Most notably, c-di-GMP, along with proteins related to its synthesis, sensing and degradation, was identified as playing a central role in the switching from biofilm to planktonic modes of growth. Recently, this world has been under expansion, with the discoveries of other signalling CNDs in bacteria (c-di-AMP and cGAMP) and also in eukaryotes, novel protein and RNA receptors of CDNs, and the numerous functions related to these molecules. In this work, we comprehensively review and analyse the structural biology data about the systems that bacteria use to synthesise and recognise CDNs, detailing their interactions at molecular level with their products/ligands. Additional interesting observations were made, including that different receptor types can bind CDNs in similar conformations and that, based on genomic data, different CDN second messenger systems may coexist in many organisms. The large amount of sequence and structural data available allows a broad view of the importance of CDNs in bacteria, but how cells coordinate these molecules to ensure adaptation to changing environmental conditions is still open for much further exploration.

In this paper, we explore a new norm on L^p-space called r-norm, and hence producing a new normed space called r-normed space. Measure theoretic and functional analytic properties are covered such as the relation between r-norm and the classical p-norm. An application of r-normed space in probability theory and statsitics is also presented, notably, its role as a rigorous framework in describing the coefficient of determination.

Higher body weight is known to negatively impact plasma vitamin C status. However, despite this well-documented inverse association, recommendations on daily vitamin C intakes by health authorities worldwide do not include particular reference values for people of higher body weight. This suggests that people of higher body weight and people with obesity may be insufficient in vitamin C in spite of ingesting the amounts recommended by their health authorities. The current preliminary investigation sought to estimate how much additional vitamin C people with higher body weights need to consume in order to attain a comparable vitamin C status to that of a lower weight person consuming an average Western vitamin C intake. Data from two published vitamin C dose-concentration studies were used to generate the relationship: a detailed pharmacokinetic study with seven healthy non-smoking men and a multiple depletion-repletion study with 68 healthy non-smoking men of varying body weights. Our estimates suggest that an additional intake of 10 mg vitamin C/day is required for every 10 kg increase in body weight to attain a comparable plasma concentration to a 60 kg individual with a vitamin C intake of ~110 mg/day, which is the daily intake recommended by the European Food Safety Authority (EFSA). Thus, individuals weighing e.g. 80 and 90 kg will need to consume ~130 and 140 mg vitamin C/day, respectively. People with obesity will likely need even higher vitamin C intakes. As poor vitamin C status is associated with increased risk of several chronic diseases including cardiovascular disease, these findings may have important public health implications. As such, dose-finding studies are required to determine optimal vitamin C intakes for overweight and obese people.

This article presents a proposed system that enables energy transfer from the dc grid to a single-phase onboard grid, operating at an hi frequency. In addition to the energy transfer function, it additionally enables compensation of reactive power in the ac grid when the converter operates at less than rated power. To operate in compensator mode, it is necessary to decouple the current from the grid into active and reactive components and control them independently. To achieve good dynamics, synchronizers that operate in the dq system are used. In the case of a single-phase grid, it requires such a synchronizer to generate virtual quadrature signals. The used systems based on second-order generalized integrator are good, but to improve dynamics in the work a quadrature generator based on trigonometric calculations was proposed. The developed system was implemented in a proportional resonant current control system. Tests performed in steady state and in dynamic states related to typical grid disturbances showed better dynamic properties than the standard integrator-based system.Keywords: power transfer; compensator; P+R controller

In this article, we give a brief review of the origin of the neutrino mass in some interesting non-linear supersymmetric models with R-symmetry. These models are able to address and solve the most important problems of the particle physics and provide mechanisms for neutrino mass generation and their mixing parameters in agreement with the current experimental data. Their prediction could be experimentally tested in the near future by collider experiments.

Herein, a chemophenetic significance, based on phenolic metabolite profiling of three Senecio (S. hercynicus, S. ovatus and S. rupestris) and two Jacobaea species (J. pancicii and J. maritima) coupled to morphometric data, is presented. A set of twelve morphometric characters were recorded from each plant species and used as predictor variables in a Linear Discriminant Analysis (LDA) model. From a total 75 observations (15 from each of the five species), the model correctly assumed their species' membership, except 2 observations. Among the studied species, S. hercynicus and S. ovatus presented the greatest morphological similarity. A phytochemical profiling of phenolic specialized metabolites by UHPLC-Orbitrap-HRMS revealed 46 hydroxybenzoic, hydroxycinnamic, acylquinic acids and their derivatives, 1 coumarin, and 21 flavonoids. Hierarchical and PCA clustering applied to the phytochemical data corroborated the similarity of S. hercynicus and S. ovatus, observed in the morphometric analysis. This study contributes to the phylogenetic relationships between the tribe Senecioneae taxa and highlights the chemophenetic similarity/dissmilarity of the studied species belonging to Senecio and Jacobaea genera.

Neuroinflammation, defined as inflammatory reactions mediated by cytokines, chemokines, reactive oxygen species, and secondary messengers in the central nervous system (CNS) including the brain and spinal cord is the basis of many neurological disorders. Recently, erythropoietin (EPO) has been considered and studied as a modulator of neuroinflammation. On this article minireview of pathophysiology of neuroinflammation and the neuroprotective effects of EPO is discussed and a case of subacute huge subdural hematoma with double mydriasis operated urgently, treated with low daily dose (vs high dose once or twice a month in the literature) of EPO and recovered fully and discharged home with good consciousness is reported. In addition, the probable unfavorable outcome of erythropoietin administration in patients with neuroinflammation in COVID-19 is considered.

Recently, Shehata et al. [37] introduced the r+1Rs(B;C; z) matrix function and established some properties. The aim of this study established to devote and derive certain basic properties including analytic properties, recurrence matrix relations, dierential properties, new integral representations, k- Beta transform, Laplace transform, fractional k-Fourier transform, fractional integral properties, the k-Riemann{Liouville and k-Weyl fractional integral and derivative operators an extended version of r+1Rs;k matrix function. We establish its relationships with other well known special matrix functions which have some particular cases in the context of three parametric Mittag-Leer matrix function, k- Konhauser and k-Laguerre matrix polynomials. Finally, some special cases of the established formulas are also discussed.

IHepatitis C virus (HCV) has a high genetic diversity, with seven genotypes with 86 subtypes. This genetic variability confers persistence in the infection and escape of the immune system with evolution to cirrhosis and cancer. Environmental factors can contribute to different disease progression, being essential to assess the viral genotype in the infection and discuss the environmental particularities of Eastern Amazon, and the frequencies of Liver fibrosis between different HCV genotypes in patients living in a region of the Brazilian Eastern Brazilian Amazon. Consists in an observational cross-sectional study. Sociodemographic and clinical data of 76 individuals diagnosed with Hepatitis C between 2019 and 2020 in public health services were selected. Data collected was tabulated in Microsoft Excel 2010TM spreadsheets and analysed in GraphPad Prism 5.0TM. Liver fibrosis was associated with genetic subtypes. Subtype 1b was predominant (42.1%), followed by 1a (13%) and 3a (1.3%). 69.7% of participants had chronic hepatitis, with mild fibrosis (F1/F2) being the most prevalent (38.1%). Severe fibrosis was detected in 75% of individuals infected with the subtype 1b, that is associated with more severe disease. We suggest further studies, to assess other communities in the region, as well as the monitoring of these patients with Liver Elastography to determine the disease evolution and its better management.

This work demonstrates that a plasmid can function as an efficient biocatalyst in mediating the nitroaldol (Henry) reaction at high temperatures in ultrapure water. Compared with ssDNA, the plasmid displayed a remarkable catalytic efficiency (97% yield within 20 min). Aromatic aldehydes which bear strong or moderate electron-withdrawing groups reacted satisfactorily with nitromethane, which afforded the corresponding β-nitroalcohols in good yields within 2 h (up to 98%). By contrast, aliphatic and aromatic aldehydes with electron-donating groups did not react. Moreover, the yield significantly dropped when the size of the carbanion increased, and the yield was only 10% when nitropropane was used as the donor.

Pulmonary Embolism (PE) is the obstruction of blood arteries in the lungs by a blood clot. The mortality risk for PE is approximately 30%. Detecting pulmonary embolism in the segmental arteries of the lung is more challenging than in the main arteries and is very prone to being missed. A computer-based approach was created in this work to automatically identify pulmonary embolism in the segmental arteries using computed tomography images. The system's infrastructure includes an enhanced Mask R-CNN deep neural network that has been trained with images containing PE. The network accurately identifies the location of the pulmonary embolism on the computed tomography picture and successfully extracts its borders. The investigation was conducted by generating a local dataset. The study's performance was evaluated using pulmonary embolisms identified manually by the expert radiologist. The sensitivity, specificity, accuracy, dice coefficient, and Jaccard index values for 2130 pictures were 96.4%, 93.5%, 96.1%, 0.96, and 0.90, respectively. The improved Mask R-CNN model has demonstrated superior performance when compared to the traditional Mask R-CNN and U-Net models. This high-performance technology is designed to identify pulmonary embolism and will aid professionals in assessing the size of the embolism.

Introduction: EEGLAB is one of the most famous software for processing, analyzing, and researching experiments that have Electroencephalography (EEG) datasets. Due to the numerous and famous add-ins along with global, widespread communications and online free training, its popularity increased every year. Method: To address this phenomenon from a bibliographic perspective, we found 20,464 citations in Google Scholar for the main EEGLAB reference since 8/27/2023. Then, only the Web of Science (WOS) articles were 12,700 that they were extracted. The results were analyzed with Bibliometrix package from CRAN R software. Results: The time span of these articles is from 2004 to 2023 with 12,700 documents in 1,125 sources (journals, books, etc.), 29,125 authors, 19,062 author’s keywords, 13,707 keywords PLUS, 279,617 references. The annual growth rate is 28.12 %, international Co-authorship is 37.27 % and Co-authors per document is s 4.89 and the average citations per document is 22.51. The most relevant sources are Neuroimage, Frontiers in Human Neurosciences, Scientific Reports, Psychophysiology, and PLOS One with 780, 526, 446,425, and 371 articles, respectively. The most cited countries are the USA, Germany, and the United Kingdom with 93,093, 32,621, and 20,748 total citations, respectively. The ERPLAB, ADJUST, and ICLabel add-ins have the local to global citation ratios equal to 85.4%, 65.1%, and 78.2% respectively. Other bibliometric analyses such as co-occurrence networks and thematic maps of abstracts, titles, and keywords are estimated and presented. Conclusions: EEGLAB is among the most cited MATLAB toolboxes in computational neuroscience. Many developed and developing countries use it in their research publications.

This research aims to obtain empirical evidence of the influence of the masculinity of male CEOs on the of research & development, this research seeks to identify the influence of the face of mas-culinity of male CEO’s on the of research & development. The study used a quantitative approach with population and research samples using companies listed on the Indonesia Stock Exchange from 2016 to 2021. The study collected images of faces identified as male CEOs from data from the Indonesia Stock Exchange website and company as utilizing Google searches. The data analysis method in this study used Regression Ordinary Least Square (OLS) with Stata Software. Stata software is one of the regression completion procedures that has a high degree of flexibility in re-search that connects theories, concepts and data that can be done on variables in research. The findings empirically explain that the higher the face value of male CEO masculinity has an impact on reducing research & development costs, and vice versa the lower the face value of male CEO masculinity has an impact on increasing research & development. The practical implications of the research results can help the Indonesian Association of Accountants in developing Financial Accounting Standard No. 19 in Indonesia. The theoretical implications of the research results can explain the Theory of Agency and the Theory of Consistency of Behavior. The policy implications of the results of the study can provide empirical evidence that the higher the facial value of male CEO masculinity has an impact on reducing research & development, while also the lower the face value of male CEO masculinity has an impact on increasing research & development.

Potholes on roads pose a major threat to motorists and autonomous vehicles. Driving over a pothole has the potential to cause serious damage to a vehicle, which in turn may result in fatal accidents. Currently, many pothole detection methods exist. However, these methods do not utilize deep learning techniques to detect a pothole in real-time, determine the location thereof and display its location on a map. The success of determining an effective pothole detection method, which includes the aforementioned deep learning techniques, is dependent on acquiring a large amount of data, including images of potholes. Once adequate data had been gathered, the images were processed and annotated. The next step was to determine which deep learning algorithms could be utilized. Three different models, including Faster R-CNN, SSD and YOLOv3 were trained on the custom dataset containing images of potholes to determine which network produces the best results for real-time detection. It was revealed that YOLOv3 produced the most accurate results and performed the best in real-time, with an average detection time of only 0.836s per image. The final results revealed that a real-time pothole detection system, integrated with a cloud and maps service, can be created to allow drivers to avoid potholes.

In this work, we explore a the different forms of a new type of modified gravity, namely f(φ) gravity. We construct the Big Rip type for the energy density and the curvature of the universe. We show that dark energy is a result of the transformation of the field φ mass (dark matter) to energy. In addition, we provide that Ω_{m}≈0,050, Ω_{DM}≈0,2, Ω_{DE}≈0,746, is in excellent agreement with observation data. We explore a generalized formalism of braneworld modified gravity. We also construct a new field equations, which generalize the Einstein field equations. We provide a relation between the extra dimension in 3-brane with the vacuum energy density. We show that the energy density of matter depends directly on the number of dimensions. We manage to find the value of the Gauss-Bonnet coupling α=1/4 which is a good agreement with the results in the literature, this correspondence creates a passage between f(R) gravity and Gauss-Bonnet gravity, this comparison leads to a number of bulk dimensions equal to D=10¹²¹+4.

The study focuses on the application of R programming language towards marine geological research with a case study of Mariana Trench. Due to its logical and straightforward syntax, multi-functional standard libraries, R is especially attractive to the geologists for the scientific computing. Using R libraries, the unevenness of various factors affecting Mariana Trench geomorphic structure has been studied. These include sediment thickness, slope steepness, angle aspect, depth at the basement and magmatism of the nearby areas. Methods includes using following R libraries: {ggplot2} for regression analysis, Kernel density curves, compositional charts; {ggalt} for Dumbbell charts for data comparison by tectonic plates, ranking dot plots for correlation analysis; {vcd} for mosaic plots, silhouette plots for compositional similarities among the bathymetric profiles, association plots; {car} for ANOVA. Bathymetric GIS data processing was dome in QGIS and LaTeX. The innovativeness of the work consists in the multi-disciplinary approach combining GIS analysis and statistical methods of R which contributes towards studies of ocean trenches, aimed at geospatial analysis of big data.

Due to the widespread application of (hetero)arylazoles, the development of straightforward functional group-tolerant synthetic methods that enable selective heteroaromatic elaboration under mild conditions aroused considerable attention. Over the last years we were interested in studies aimed to broaden the substrate scope of the direct functionalization of azoles and, in particular, to develop efficient synthetic protocols for the carbon-carbon bond forming reaction by selective palladium-catalyzed Csp2-H bond activation of imidazole derivatives. During these studies, we discovered that the outcome of the Pd-catalyzed arylation of imidazoles with aryl bromides is deeply influenced by the nature of the reaction solvent. Specifically, it is well known that the Pd-catalyzed direct arylation of imidazoles with aromatic halides selectively leads to C-5 monoarylation products when polar aprotic solvents such as DMF (or DMA) are used as a reaction medium, but these solvents are coded as dangerous according to EHS (Environmental, Health, Safety) parameters. Instead, the use of aromatic solvents as the reaction medium for direct arylations, although some of them show good EHS values, is poorly reported, probably due to their low solvent power against reagents and their potential involvement in undesired side reactions. So, with the intention of filling this gap, in this paper, we have developed a selective C-5 arylation procedure in anisole as the solvent, discovering also the unprecedented role of benzoic acid as a promoter of the coupling.

The α(1,2)fucosyltransferase (Se enzyme) encoded by FUT2 is involved in the secretor status of ABH(O) blood group antigens. The sedel2 allele is one of the non-functional FUT2 (se) alleles in which 9.3 kb containing the entire coding region of FUT2 is deleted by Alu-mediated nonhomologous recombination. In addition to this allele, three SNPs of FUT2, c.375A>G, c.385A>T, and c.571C>T, appear to be prevalent in certain Oceanian populations such as Polynesians. Recently, we developed an endpoint genotyping assay to determine the sedel2 zygosity, using a FAM-labeled probe for detection of the sedel2 allele and a VIC-labeled probe for detection of FUT2. In this study, instead of the VIC probe, a HEX-labeled probe covering both c.375A>G and c.385A>T and a Cy5-labeled probe covering c.571C>T were added to the sedel2 allele assay mixture to allow simultaneous detection of these four variations by endpoint genotyping for the sedel2 zygosity and fluorescence melting curve analysis for c.375A>G, c.385A>T, and c.571C>T genotyping. The results obtained from 24 Samoan subjects with this method were identical to those obtained with previous methods. Therefore, it appears that present method can accurately determine these four variations simultaneously.

Vitamin C status is known to be associated with several demographic and lifestyle factors. These include gender, age, ethnicity, pregnancy/lactation, body weight, smoking status and dietary habits. In the present study, our aim was to interrogate the National Health and Nutrition Examination Survey (NHANES) 2017-2018 datasets to assess the impact of these factors on vitamin C dose-concentration relationships to establish if there are higher requirements for vitamin C in certain subpopulations and the possible extent of these additional requirements. The relevant data were extracted from the NHANES 2017-2018 datasets, the final cohort of which comprised 2828 non-supplementing adult males and females (aged 18 – 80+ years) with both vitamin C serum concentrations and dietary intake data available. The data was subsequently stratified by gender, age tertiles (≤36, 37-58, ≥59 years), ethnicity (non-Hispanic white, non-Hispanic black, and total Hispanic), socioeconomic tertiles (poverty income ratios: &gt;3.0, 1.36 – 3.0, ≤1.35), weight tertiles (≤72, 72-91, ≥91 kg), BMI tertiles (≤26, 26-32, ≥32 kg/m2) and smoking status. Sigmoidal (four parameter logistic) curves with asymmetrical 95% confidence intervals were fitted to the dose-concentration data. We found that males required vitamin C intakes ~1.2-fold higher than females to reach ‘adequate’ serum concentrations of 50 µmol/L. Males had both higher body weight and a higher prevalence of smoking than females. Smokers required vitamin C intakes ~2.0-fold higher than non-smokers to reach adequate vitamin C concentrations. Relative to adults in the lighter weight tertile, adults in the heaver weight tertile required ~2.0-fold higher dietary intakes of vitamin C to reach adequate serum concentrations. We did not observe any impact of ethnicity or socioeconomic status on the vitamin C dose-concentration relationship, and although no significant difference between younger and older adults was observed at vitamin C intakes &gt; 75 mg/day, at intakes &lt; 75 mg/day, older adults had an attenuated serum response to vitamin C intake. In conclusion, certain demographic and lifestyle factors, specifically gender, smoking and body weight, have a significant impact on vitamin C requirements. Overall, the data indicate that the general population must consume ~110 mg/day of vitamin C to attain adequate serum concentrations, smokers require ~165 mg/day relative to non-smokers, and heavier people (100+ kg) require ~155 mg/day to reach the same vitamin C concentrations. These findings have important implications for global vitamin C dietary recommendations.

Pneumonia is a severe lower respiratory tract infection that is a common complication and a major cause of mortality of the vitamin C-deficiency disease scurvy. This suggests an important link between vitamin C status and lower respiratory tract infections. Due to the paucity of information on the vitamin C status of patients with pneumonia, we assessed the vitamin C status of 50 patients with community-acquired pneumonia and compared these with 50 healthy community controls. The pneumonia cohort comprised 44 patients recruited through the Acute Medical Assessment Unit (AMAU) and 6 patients recruited through the intensive care unit (ICU); mean age 68 ± 17 years, 54% male. Clinical, microbiological and haematological parameters were recorded. Blood samples were tested for vitamin C status using HPLC with electrochemical detection and protein carbonyl concentrations, a marker of oxidative stress, using ELISA. Patients with pneumonia had depleted vitamin C status compared with healthy controls (23 ± 14 µmol/L vs 56 ± 24 µmol/L, P <0.001). The more severe patients in the ICU had significantly lower vitamin C status than those recruited through AMAU (11 ± 3 µmol/L vs 24 ± 14 µmol/L, P = 0.02). The total pneumonia cohort comprised 62% with hypovitaminosis C and 22% with deficiency, compared with only 8% hypovitaminosis C and no cases of deficiency in the healthy controls. The pneumonia cohort also exhibited significantly elevated protein carbonyl concentrations compared with the healthy controls (P < 0.001), indicating enhanced oxidative stress in the patients. We were able to collect subsequent samples form 28% of the cohort (mean 2.7 ± 1.7 days; range 1-7 days). These showed no significant differences in vitamin C status or protein carbonyl concentrations compared with baseline values (P = 0.6). Overall, the depleted vitamin C status and elevated oxidative stress observed in the patients with pneumonia indicates an enhanced requirement for the vitamin during their illness. Due to the important roles that vitamin C plays in the immune system, low vitamin C status is possibly both a cause and a consequence of the disease. Therefore, these patients would likely benefit from additional vitamin C supplementation to restore their blood and tissue levels to optimal. This may decrease oxidative stress and aid in their recovery.

Candida (C.) infections represent a serious health risk for people affected by inflammatory bowel disease. An important fungal virulence factor is the capacity to form biofilms on the colonized surface of the host. This research study aimed to determine the effect of C. tropicalis and C. albicans co-infection on dextran sodium sulfate (DSS)-induced colitis in mice. Colitis severity was evaluated using histology and colonoscopy. Mice were mono-inoculated with C. albicans, C. tropicalis or co-challenged with both species. Mice were administered 3% DSS to induce acute colitis. Biofilm activity was assessed using (2-methoxy-4-nitro-5-sulfophenyl)-5-[(phenylamino)carbonyl] 2H-tetrazoliumhydroxide (XTT) assay. Abundance of C. albicans in the colon tissues was assessed by immunohistochemistry. Co-challenged mice showed decreased colitis severity compared to mono-inoculated mice. The XTT assay demonstrated a marked decrease of C. albicans biofilm production in a C. albicans culture incubated with C. tropicalis supernatant. Immunohistochemical staining showed that C. albicans was more abundant in the mucosa of C. albicans mono-inoculated mice compared to the co-inoculated group. These data indicate an antagonistic microbial interaction between the two Candida species, where C. tropicalis may produce molecules capable of limiting the ability of C. albicans to adhere to the host intestinal surface leading to a reduction in biofilm formation.

Background and objectives: Since 2013, highly effective direct-acting (DAA) chronic hepatitis C (CHC) antiviral therapy became available, which has cure rates of over 95%. For choice of optimal CHC treatment, assessment of hepatitis C virus (HCV) genotype (GT) and liver fibrosis stage are necessary. Information about distribution of these parameters among CHC patients in Baltic states and especially in Ukraine is scarce. This study was performed to obtain epidemiological data regarding CHC GT and fibrosis stage distribution for better planning of resources and prioritization of patients for DAA drug treatment according to disease severity in high-income (Baltic states) and lower-middle income (Ukraine) countries. Materials and Methods: This was an epidemiological, retrospective, cross-sectional study that included 1451 CHC patients. Demographic and disease information from medical charts was collected for each patient during a single visit. Results: Most frequent suspected mode of viral transmission was blood transfusions (17.8%), followed by injection drug use (15.7%); however, in 50.9% of patients exact mode of transmission was not clarified. In Ukraine (18.4%) and Estonia (26%) transmission by the injection drug use was higher than in Lithuania (5%) and Latvia (5.3%). Distribution of HCV GT among patients with CHC was as follows: GT1 - 66.4%; GT3 - 28.1; and GT2 - 4.1%. The prevalence of GT1 was the highest in Latvia (84%), and the lowest in Ukraine (63%, p<0.001). Liver fibrosis stages were distributed as follows: F0 - 12.2%, F1 - 26.3%, F2 - 23.5%, F3 – 17.1% and F4 - 20.9%. Cirrhosis (F4) was more prevalent in Lithuanian patients (30.1%) than in Estonians (8.1%, p <0.001). Conclusions: This study contributes to the knowledge of epidemiological characteristics of HCV infection in the Baltic states and Ukraine. The data regarding the patterns of HCV GT and fibrosis stage distribution will be helpful for the development of national strategies to control HCV infection in the era of DAA therapy.

Background: Angelica gigas Nakai, Korean dang-gui, has long been widely used in traditional treatment methods. There have been a number of studies of the health effects of A. gigas and related compounds, but studies addressing effects on blood triglycerides (TG) are lacking. To investigate the effects of A. gigas Nakai extract (AGNE) on TG in Korean subjects, we carried out a 12-week, randomized, double-blind, placebo-controlled clinical trial. Methods: Subjects who met the inclusion criterion (130 mg/dL ≤ fasting blood TG ≤ 200 mg/dL) were recruited for this study. One hundred subjects were assigned to the AGNE group (n=50) or the placebo group (n=50), who were given 1g/day of AGNE (as a gigas Nakai extract 200mg/d) in capsules, and the control group for 12 weeks. Outcomes were efficacy TG, lipid profiles, atherogenic index, and safety parameters were assessed initially for a baseline measurement and after 12 weeks. Results: After 12 weeks of supplementation, TG and very low-density lipoprotein cholesterol (VLDL-C) concentration and TG/HDL-C ratio in the AGNE group were significantly reduced compared to the placebo group (p <0.05). No significant changes in any safety parameter were observed. Conclusions: These results suggest that ingestion of AGNE may improve TG and be useful to manage or prevent hypertriglyceridemia.

Copper-catalyzed and organocopper-involved reactions are of great significance in organic synthesis. To have a deep understanding of the reaction mechanisms, the structural characterizations of organocopper intermediates become indispensable. Meanwhile, the structure-function relationship of organocopper compounds would advance rational design and development of new Cu-based reactions and organocopper reagents. Compared to the mono-carbonic ligand, the C,N- and C,C-bidentate ligands better stabilize the unstable organocopper compounds. The bidentate ligands can chelate to the same copper atom via ?2-mode, forming a mono-cupra-cyclic compounds with at least one acute C-Cu-C angle. When the bidentate ligands bind to two copper atoms via ?1-mode at each coordinating site, the bimetallic macrocyclic compounds will form nearly linear C-Cu-C angles. The anionic coordinating sites of the bidentate ligand can also bridge two metals via ?2-mode, forming organocopper aggregates with Cu-Cu interactions and organocuprates with contact ion pair structures. The reaction chemistry of some selected organocopper compounds is highlighted, showing their unique structure-reactivity relationships.

A Friedmann-Lemaitre-Robertson-Walker space-time model with all curvatures k=0,±1 is explored in f(R,T) gravity. The solutions are obtained via the parametrization of the scale factor that leads to a model transiting from a decelerated universe to an accelerating one. The physical features of the model are discussed and analysed.

When applying deep learning methods to detect micro defects on low-contrast LCD surfaces, there are challenges related to the imbalance in samples dataset, as well as the complexity and laboriousness of annotating and acquiring target image masks. In order to solve these problems, a method based on sample and mask auto-generation for deep generative network models is proposed. We first generate an augmented dataset of negative samples using a generative adversarial network(GAN), and then highlight the defect regions in these samples using the training method constructed by the GAN to generate masks for the defect images automatically. Experimental results shows the effectiveness of our proposed method, as it allows for the simultaneous generation of LCD image samples and their corresponding image masks. Through a comparative experiment on the deep learning method Mask R-CNN, we demonstrate that the automatically obtained image masks have high detection accuracy.

Revenue-sharing (RS) contracts are a common approach to incentivize innovation of upstream suppliers by addressing the uneven profit distribution between upstream and downstream firms. Considering the possible overconfidence characterizing decision makers in the supply chain, we investigate the effect of the RS contract and the tendency of overconfidence of supply chain members on the investment in R&D of key components of products in the context of an upstream supplier that is the leader in the R&D and production of key components. We find that regardless of the bargaining power of either party, a RS contract can increase the R&D investment in key components. Regarding the effects of overconfidence of either downstream manufacturer or up-stream supplier, it can increase the R&D investment in key components. Supplier (manufacturer) overconfidence can harm their own profits but increase the profits of the manufacturer (supplier), and when the level of overconfidence is below a certain threshold, the damage to their own profits is less than the increase in each other's profits, thus benefiting the whole supply chain. In addition, we also find a joint effect of RS contracts and overconfidence: when the bargaining power of the supplier is low, the RS contract has a certain compensatory effect on the loss of their own profits caused by overconfidence.

The circular economy (CE) has emerged as a viable alternative for tackling the problems caused by rising consumption, including solid waste (SW). The present study conducted a meta-analysis of research published between 2012 and 2022 on CE and solid waste management (SWM). A bibliometric analysis was used from the Web of Science (WoS) and Scopus databases. By studying the articles, we briefly discussed the connections between them and how one contributes to the evolution of the other. Some findings point to greater collaboration between Italy and Bolivia, followed by China and Malaysia. However, they move away from the traditional axes as the United States and Canada. In addition, it was found that the adoption of reuse and selective collection, in fact, allow the reduction of the volume of discarded materials. In this way, it was possible to conclude that a greater connection between CE and GRS makes it possible to optimize the useful life of landfills through the treatment of organic waste and recycling, to encourage waste picker cooperatives and selective collection programs, and to reduce the financial costs of the system as a whole, making it more durable and sustainable.

Low-resource languages often face the problem of insufficient data, which leads to poor quality in machine translation. One approach to address this issue is data augmentation. Data augmentation involves creating new data by transforming existing data through methods such as flipping, cropping, rotating, and adding noise. Traditionally, pseudo-parallel corpora are generated by randomly replacing words in low-resource language machine translation. However, this method can introduce ambiguity as the same word may have different meanings in different contexts. This study proposes a new approach for low-resource language machine translation, which involves generating pseudo-parallel corpora by replacing phrases. The performance of this approach is compared with other data augmentation methods, and it is observed that combining it with other data augmentation methods further improves performance. To enhance the robustness of the model, R-Drop regularization is also used. R-Drop is an effective method for improving the quality of machine translation. The proposed method was tested on Chinese-Kazakh (Latin script) translation tasks, resulting in performance improvements of 4.99 and 7.7 for Chinese-to-Kazakh and Kazakh-to-Chinese translations, respectively.

The aim of this study, for determination of verteporfin in real samples (simulated body fluid, and simulated tears, 0.9% isotonic sodium chloride solution, Lactated Ringer IV solution for infusion, 5% dextrose IV solution for infusion, lemon juice and drinking water) was the method validation and to examined by HPLC-DAD-UV. Metod validation parameters such as specificity, linearity, precision, accuracy, robustness, limit of detection (LOD) and limit of quantitation (LOQ) for verteporfin were validated and developed according to the International Conference on Harmonization (ICH) Q2 R1 guidelines. The LOD and LOQ for verteporfin were found 0.06 µg/L and 0.2 µg/L, respectively. The recovery values of the optimization and validation for verteporfin were found in the range of 97.5-100.7%. The relative standard deviations (RSD) for vertepofin were <1%. The developed method was successfully applied to real samples with high accuracy and the recoveries (%) from real samples were 99.9, 100, 98.2, 99.2, 99.4, 98.8 and 99.4, respectively.

Crocodilepox virus (CRV) belongs to the Poxviridae family and mainly infects hatchling and juvenile Nile crocodiles. Most poxviruses encode inhibitors of the host antiviral protein kinase R (PKR), which is activated by viral double-stranded (ds) RNA formed during virus replication, resulting in the phosphorylation of eIF2 and subsequent shutdown of general mRNA translation. Because CRV lacks orthologs of known poxviral PKR inhibitors, we experimentally characterized one candidate (CRV157), which contains a predicted dsRNA-binding domain. Bioinformatic analyses indicated that CRV157 evolved independently from other poxvirus PKR inhibitors. CRV157 bound to dsRNA, co-localized with PKR in the cytosol, and inhibited PKR from various species. To analyze whether CRV157 could inhibit PKR in the context of a poxvirus infection, we constructed recombinant vaccinia virus strains that contain either CRV157 or a mutant CRV157 deficient in dsRNA binding in a strain that lacks PKR inhibitors. The presence of wild type CRV157 rescued vaccinia virus replication, while the CRV157 mutant did not. The ability of CRV157 to inhibit PKR correlated with virus replication and eIF2alpha phosphorylation. The independent evolution of CRV157 demonstrates that poxvirus PKR inhibitors evolved from a diverse set of ancestral genes in an example of convergent evolution.

In this article we have presented a new perception of herd immunity threshold (HIT) which considers that only a “band of population” are susceptible to any pathogenic infection. This is termed as the “effective herd immunity threshold” (EHIT) and the progression of the disease (caused by this pathogenic infection) is mainly determined by this EHIT value. We have argued here that this EHIT value (considering the immunity band picture in the population) will be substantially lower than the estimated canonical HIT values obtained from various existing models. We propose that the actual prediction of the disease progression should now be calculated using the EHIT values.

Inspired by the work of S. D. Odintsov and V. K. Oikonomou, Phys. Rev. D 92, 024016 (2015) [1], the present study reports a reconstruction scheme for f (R) gravity with the scale factor a(t) µ (t _* - t) _c²²describing the pre-bounce ekpyrotic contraction, where t is the big crunch time. The reconstructed f (R) is used to derive expressions for density and pressure contributions and the equation of state parameter resulting from this reconstruction is found to behave like "quintom". It has also been observed that the reconstructed f (R) has satisfied a sufficient condition for a realistic model. In the subsequent phase the reconstructed f (R) is applied to the model of chameleon scalar field and the scalar field f and the potential V(f) are tested for quasi-exponential ex pansion. It has been observed that although the reconstructed f (R) satisfies one of the sufficient conditions for realistic model, the quasi-exponential expansion is not available due to this reconstruction. Finally, the consequences pre-bounce ekpyrotic inflation i n f (R) gravity are compared to the background solution for f (R) matter bounce.

The crux of the paper is to present a detailed analysis of COVID-19 data which is available on global basis. This analysis is performed using some specific package of R software. It provides various insights from the data and help to understand the current status of this pandemic in India so that effective measures can be formulated by policymakers. These insights include global summary of this disease, growth rate of this pandemic and performance of SIR model for the given global data. The analysis has been presented in different tables and graphs to understand the outputs of the problem in a more detailed point of view.

Collisions of low energy electrons with molecules are important for understanding many aspects of the environment and technologies. Understanding the processes that occur in these types of collisions can give insights into plasma etching processes, edge effects in fusion plasmas, radiation damage to biological tissues and more. A radical update of the previous expert system for computing observables relevant to these processes, Quantemol-N, is presented. The new Quantemol Electron Collision (QEC) expert system simplifyies the user experience, improving reliability and implements new features. The QEC GUI interfaces the Molpro quantum chemistry package for molecular target setups and to the sophisticated UKRmol+ codes to generate accurate and reliable cross-sections. These include elastic cross-sections, super elastic cross-sections between excited states, electron impact dissociation, scattering reaction rates, dissociative electron attachment, differential cross-sections, momentum transfer cross-sections, ionization cross sections and high energy electron scattering cross-sections. With this new interface we will be implementing dissociative recombination estimations, vibrational excitations for neutrals and ions, and effective core potentials in the near future.

This paper introduces an application of R programming language for geostatistical data processing with a case study of the Mariana Trench, Pacific Ocean. The formation of the Mariana Trench, the deepest among all hadal oceanic depth trenches, is caused by complex and diverse geomorphic factors affecting its development. Mariana Trench crosses four tectonic plates: Mariana, Caroline, Pacific and Philippine. The impact of the geographic location and geological factors on its geomorphology has been studied by methods of statistical analysis and data visualization using R libraries. The methodology includes following steps. Firstly, vector thematic data were processed in QGIS: tectonics, bathymetry, geomorphology and geology. Secondly, 25 cross-section profiles were drawn across the trench. The length of each profile is 1000-km. The attribute information has been derived from each profile and stored in a table containing coordinates, depths and thematic information. Finally, this table was processed by methods of the statistical analysis on R. The programming codes and graphical results are presented. The results include geospatial comparative analysis and estimated effects of the data distribution by tectonic plates: slope angle, igneous volcanic areas and depths. The innovativeness of this paper consists in a cross-disciplinary approach combining GIS, statistical analysis and R programming.

We present a methodology to enable users to interact with statistical information owned by an institution and stored in a cloud infrastructure. Mainly based on R, this approach was developed following the open-data philosophy. Also, since we use R, the implementation is mainly based on open-source software. R gives several advantages from the point of view of data management and acquisition, as it becomes a common framework that can be used to structure the processes involved in any statistical operation. This simplifies the access to the data and enable to use all the power of R in the cloud information. This methodology was applied successfully to develop a tool to manage the data of the Centre d’Estudis d’Opinió, but it can be applied to other institutions to enable open access to its data. The infrastructure also was deployed to a cloud infrastructure, to assure the scalability and a 24/7 access.

The exceptional increase in molecular DNA sequence data in open repositories is mirrored by an ever-growing interest among evolutionary biologists to harvest and use those data for phylogenetic inference. Many quality issues, however, are known and the sheer amount and complexity of data available can pose considerable barriers to their usefulness. A key issue in this domain is the high frequency of sequence mislabelling encountered when searching for suitable sequences for phylogenetic analysis. These issues include the incorrect identification of sequenced species, non-standardised and ambiguous sequence annotation, and the inadvertent addition of paralogous sequences by users, among others. Taken together, these issues likely add considerable noise, error or bias to phylogenetic inference, a risk that is likely to increase with the size of phylogenies or the molecular datasets used to generate them. Here we present a software package, phylotaR, that bypasses the above issues by using instead an alignment search tool to identify orthologous sequences. Our package builds on the framework of its predecessor, PhyLoTa, by providing a modular pipeline for identifying overlapping sequence clusters using up-to-date GenBank data and providing new features, improvements and tools. We demonstrate our pipeline’s effectiveness by presenting trees generated from phylotaR clusters for two large taxonomic clades: palms and primates. Given the versatility of this package, we hope that it will become a standard tool for any research aiming to use GenBank data for phylogenetic analysis.

Radar altimetry provides valuable measurements to characterize the state and the evolution of the Antartica and Greenland ice sheet cover. Global Navigation Satellite System Reflectometry (GNSS-R) has the potential capacity of complementing the dedicated radar altimeters incrementing the temporal and spatial resolution of the surface height measurements. In this work we perform an study of the Greenland ice sheet using data obtained by the GNSS-R instrument aboard the British TechDemoSat-1 (TDS-1) satellite mission, designed primarily to provide sea state information, like sea surface roughness or wind, but not altimetric products. The data has been analyzed with altimetric methodologies, already proved in aircraft based experiments, to extract signal delay observables to be used to infer the topography of the Greenland cover. The penetration depth of the GNSS signals into ice has also considered. The topographic signal obtained is consistent with those obtained with other passive or active microwave sensors. The main conclusion derived from this work is that GNSS-R also provides valuable measurements of the ice sheet cover and, as taken at a variety of geometries and at least two frequency bands, they prospect different depths into the ice. They have thus potential to complement our understanding of the ice firn and its evolution.

We developed two human induced pluripotent stem cell (hiPSC)/human embryonic stem cell-specific glycan-recognizing mouse antibodies, R-10G and R-17F, using the Tic (JCRB1331) hiPSC line as an antigen. R-10G recognizes a low-sulfate keratan sulfate, and R-17F recognizes lacto-N-fucopentaose-1. To evaluate the general characteristics of stem cell glycans, we used the hiPSC line 201B7 (HPS0063), a prototype iPSC line. Using an R-10G affinity column, an R-10G-binding protein was isolated. The protein yielded a single but very broad band from 480 to 1,236 kDa by blue native gel electrophoresis. After trypsin digestion, the protein was identified as podocalyxin by liquid chromatography/mass spectrometry. According to Western blotting, the protein reacted with R-10G and R-17F. The R-10G positive band was resistant to digestion with glycan-degrading enzymes, including peptide N-glycanase, but the intensity of the band was decreased significantly by digestion with keratanase, keratanase II, and endo-β-galactosidase, suggesting the R-10G epitope to be a keratan sulfate. These results suggest that keratan sulfate-type epitopes are shared by hiPSCs. However, the keratan sulfate from 201B7 cells contained a polylactosamine disaccharide unit (Galβ1-4GlcNAc) at a significant frequency, whereas that from Tic cells consisted mostly of keratan sulfate disaccharide units (Galβ1-4GlcNAc(6S)). In addition, the abundance of the R-10G epitope was significantly lower in 201B7 cells than in Tic cells.

Preterm delivery can be precipitated by infection, and preterm infants are at heightened risk of postnatal infection. Little is known about the ontogeny of inflammatory biomarkers in extremely preterm infants. We hypothesized that suspected prenatal infection (chorioamnionitis or spontaneous preterm labor) and clinically diagnosed postnatal infection would be associated with unique biomarker signatures, and those patterns would be influenced by the degree of prematurity. Venous blood was collected daily for the first week and weekly for up to 14 additional weeks from 142 neonates born at 22-32 weeks gestation. A custom array was utilized to measure monocyte chemoattractant protein-1 (MCP-1) and interleukin-6 (IL-6). C-reactive protein (CRP) levels were obtained from the electronic medical record. 90 infants had suspected prenatal infection and 63 were diagnosed with postnatal infection. Independent of gestational age at delivery, MCP-1 was significantly increased (P &lt; 0.001) in association with maternal preeclampsia, but MCP-1 was decreased (P&lt;0.01) and CRP was increased (P&lt;0.05) in the presence of chorioamnionitis. IL-6 and CRP were both increased in infants diagnosed with postnatal infection with peak levels observed on days 2 and 3, respectively. In conclusion, suspected prenatal and postnatal infections and non-infectious complications of pregnancy are associated with unique biomarker profiles, independent of gestational age. In those clinically diagnosed with a postnatal infection in the absence of antenatal infection concerns, IL-6 increases before CRP, emphasizing a potential role for expanded biomarker screening if antibiotics are initially avoided in infants born exclusively for maternal indications.

Motivated from the theory of Hilbert-Schmidt morphisms between Hilbert C*-modules over commutative C*-algebras by Stern and van Suijlekom [J. Funct. Anal., 2021], we introduce the notion of p-absolutely summing morphisms between Hilbert C*-modules over commutative C*-algebras. We show that an adjointable morphism between Hilbert C*-modules over monotone closed commutative C*-algebra is 2-absolutely summing if and only if it is Hilbert-Schmidt. We formulate version of Pietsch factorization problem for p-absolutely summing morphisms and solve partially.

A series of MgAl-layered double hydroxide (MgAl-HT), the calcined form at 500^oC (MgAlO_x) and the re-hydrated one at 25^oC (MgAl-HT-RH) were synthesized. Physicochemical properties of the catalysts were characterized by x-ray diffraction (XRD), scanning electron microscopy (SEM). Surface area of the as-synthesized, calcined and re-hydrated catalysts was determined by N₂ physisorption at -196^oC. CO₂-teperature programmed desorption (CO₂-TPD) was applied to determine the basic sites of catalysts. The catalytic test reaction was carried out using benzaldehyde and their derivatives with nitromethane and their derivatives. The Henry products (1-15) were obtained in a very good yield using MgAl-HT-RH catalyst either by conventional method at 90^oC in liquid phase, or under microwave irradiation method. The mesoporous structure and basic nature of re-hydrated solid catalyst were responsible for their superior catalytic efficiency. The robust nature was determined by using the same catalyst for five times, where the product % yield was almost unchanged significantly.

Soil amendments with composted organic materials are recommended to increase soil organic matter (SOM), promote soil fertility, and the Circular Economy. Growing areas of hedged olive groves in southern Iberia peninsula generate huge amounts of olive leaves whose potential as soil organic amendment is not fully studied. An experimental field trial in a hedged olive grove (cv. “Cobrançosa”) was set up near Portalegre, Portugal, to test a compost of olive leaves plus sheep manure (2:1) applied in the row, at soil surface. Three nominal rates (0 or control, 2.5 and 5.0 kg m-2) were used, in a complete randomized block setup (3 treatments, 3 replicas, 9 plots) and soil chemical properties of layers 0-5, 5-15, and 15-30 cm deep were annually monitored. Results (mainly in layer 0-5 cm) showed increases in total N, carbon of the particulate organic matter (POM-C), permanganate oxidizable carbon (POX-C), extractable phosphorus, and zinc, after one year, and increases in soil organic carbon (SOC), C-stock, pHKCl, extractable phosphorus, and zinc, after two years. POX-C was the most sensitive SOM-related indicator, showing increases up to 30 cm deep after one year. This compost improved soil fertility, but should be monitored over longer periods of time, namely for SOC and extractable zinc content.

A recent review of global vitamin C status indicated a high prevalence of deficiency, particularly in low- and middle-income countries, as well as in specific subgroups within high-income countries. Here we provide a narrative of potential factors influencing vitamin C status. The in vivo status of vitamin C is primarily affected by dietary intake and supplement use. Dietary intake can be influenced by cultural aspects such as staple foods and traditional cooking practices. Environmental factors can also affect vitamin C intake and status; these include geographic region, season and climate, as well as pollution. Demographic factors such as sex, age, and race are known to affect vitamin C status, as do socioeconomic factors such as deprivation, education and social class, and institutionalization. Various health aspects affect vitamin C status; these include body weight, pregnancy and lactation, genetic variants, smoking, and disease states, including severe infections as well as various non-communicable diseases such as cardiovascular disease and cancer. Some of these factors have changed over time, therefore we also explore if vitamin C status has shown temporal changes. Overall, there are numerous factors that can affect vitamin C status to different extents in various regions of the world. Many of these factors are not taken into consideration during the setting of global recommended dietary intakes for vitamin C.

The existences of the N→C dative bonds in the complexes between N-containing molecules and fullerenes have been verified both theoretically and experimentally. However, finding stable N→C dative bonds is still a highly challenging task. In this work, we investigated computationally the N→C dative bonds in the complexes formed by fullerene C60 with 1,2,5-chalcogenadiazoles, 2,1,3-benzochalcogenadiazoles and 1,2,4,5-chalcogenatriazoles, respectively. It was found that the N→C dative bonds are formed along with the formation of the N–Ch···C (Ch = S, Se, Te) chalcogen bonds. In the gas phase, from S-containing complexes through Se-containing complexes to Te-containing complexes, the intrinsic interaction energies become more and more negative, which indicates that the N–Ch···C chalcogen bonds can facilitate the formation of the N→C dative bonds. The intrinsic interaction energies are compensated by the large deformation energy of fullerene C60. The total interaction energies of Te-containing complexes are negative, while both of the total interaction energies of S-containing complexes and Se-containing complexes are positive. This means that the N→C dative bonds in the Te-containing complexes are more easily observed in experiments in comparison with those in the S-containing complexes and Se-containing complexes. This study provides a new theoretical perspective on the experimental observation of the N→C dative bonds in the complexes involving fullerenes. Further, the formation of stable N→C dative bonds in the complexes involving fullerenes can significantly change the properties of fullerenes, which will greatly simulate and expand the application range of fullerenes.

A Brewer Spent Grain (BSG), the most abundant by-product of the brewing process, is mainly used in animal feed and biogas production. The aim of the present work is BSG valorization by yeast fermentation to produce carotenoids. R. mucilaginosa CBS316 was cultured on BSG syrups, supplemented or not with YE and PEP (s-Fsa and Fsa). The biomass and carotenoid production were optimized in flasks and then scaled-up in bioreactor. In flask tests, the maximum biomass concentration was 5.3 and 6.2 g/L for Fsa and s-Fsa cultures, respectively. The maximum carotenoid production was 833 μg/L in Fsa and 1159 μg/L in s-FSA. Considering that the highest specific productivity value (P 7.16 μg/g*h) was obtained with Fsa syrup, this medium was selected for the process scale-up. In bioreactor tests, the maximum concentrations of biomass (4.29 g/L) and carotenoid (396 ug/L) was reached at 72 hours of fer-mentation, 24 h later than in flask. The total carotenoid produced was 524 and 150 ug in bioreactor and flask cultures, respectively. The carotenoids production by R. mucilaginosa was obtained both in Fsa and s-Fsa syrups. The results confirm the possibility to use the syrup as it is, Fsa, thus limiting the process costs.

This study aims to analyse whether Chinese companies' R&amp;D investment affects management innovation performance. Also, this dissertation defines management innovation as diversification strategies such as technology and industry diversification and analyzes the impact of these diversification strategies. In particular, this paper analyzes whether R&amp;D investment leads to technology and industry diversification and whether technology diversification creates a mediating effect in the process of R&amp;D investment leading to industry diversification. The analysis results can be summarized as follows: First, R&amp;D investment showed a significant positive relationship with industry diversification. Second, R&amp;D investment shows a significantly positive relationship with technology diversification. Third, technology and industry diversification showed a positive relationship. Fourth, this study examined the mediating role of technology diversification, and it was confirmed that technology diversification plays a mediating role in the effect of R&amp;D investment on industry diversification. R&amp;D investment and business innovation play a key role in the sustainable development of enterprises, and the findings of this paper have important reference value for enterprises' R&amp;D investment decision-making. The results of this study provide the following implications that Chinese companies improve business innovation performance by increasing their R&amp;D investment, promoting innovative R&amp;D, and improving technology diversification and industry diversification strategies.

We investigate the impact of incoming nuclear data on the predictions of the neutron star (NS) stripping model for short gamma-ray bursts. The main area to which we pay attention is the NS crust. We show that the uncertain properties of the NS equation of state can significantly influence the stripping time tstr, the main dynamical parameter of the model. Based on the known time delay (tstr≈1.7s) between the peak of the gravitational wave signal GW170817 and the detection of gamma photons from GRB170817A, we obtain new restrictions on the nuclear matter parameters, in particular, the symmetry energy slope parameter: L&lt;114.5MeV. In addition, we study the process of nucleosynthesis in the outer and inner crusts of a low-mass NS. We show that the nucleosynthesis is strongly influenced by both the incoming nuclear data and the equation of state of the NS matter.

We analyze the behavior of relativistic spherical objects within the context of modified $f(R,T)$ gravity considering Tolman VI spacetime, where gravitational lagrangian is a function of Ricci scalar(R) and trace of energy momentum tensor(T) i.e,$ f(R,T)= R+ 2\beta T$, for some arbitrary constant $\beta$. For developing our model, we have chosen $\pounds_{m} = -p$, where $ \pounds_{m}$ represents matter lagrangian. For this investigation, we have chosen three compact stars namely PSR J1614-2230 [Mass=(1.97$\pm$ 0.4)M$_\odot$; Radius= 9.69$_{-0.02} ^{+0.02}$ Km] ,Vela X-1 [Mass=(1.77$\pm$ 0.08)M$_\odot$; Radius= 9.560$_{-0.08} ^{+0.08}$ Km] and 4U 1538-52 [Mass=(9.69)M$_\odot$; Radius= 1.97 Km]. In this theory the equation of pressure isotropy is identical to standard Einstein's theory. So all known metric potential solving Einstein's equations are also valid here. In this paper, we have investigated the effort of coupling parameter ($\beta$) on the local matter distribution. Sound of speed and adiabatic index are higher with grater values of $\beta$ while on contrary mass function and gravitational redshift are lower with higher values of $\beta$ . For supporting the theoretical results, graphical representation are also employed to analyze the physical viability of the compact stars.

Land degradation and climate change are among the main threats to the sustainability of ecosystems worldwide. Therefore, the restoration of degraded landscapes is essential to maintain the functionality of ecosystems, especially those with greater social, economic and environmental vulnerability. Nevertheless, policy-makers are frequently challenged by deciding on where to prioritize restoration actions, which usually includes to deal with multiple and complex needs under an always short budget. If these decisions are not taken based on proper data and processes, restoration implementation can easily fail. To help decision-makers taking informed decisions on where to implement restoration activities, we have developed a semiautomatic geospatial platform to prioritize areas for restoration activities based on ecological, social and economic variables. This platform takes advantage of the potential to integrate R coding, Google Earth Engine cloud computing and GIS visualization services to generate an interactive geospatial decision-maker tool for restoration. Here, we present a prototype version called "RePlant alpha" which was tested with data from the Central Zone of Chile. This exercise proved that integrating R and GEE was feasible, and that the analysis, with at least six indicators and for a specific region was also feasible to implement even from a personal computer. Therefore, the use of a virtual machine in the cloud with a large number of indicators over large areas is both possible and practical.

New setting is introduced to study the global powerful alliance. Global powerful alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global powerful alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs excluding empty, path, star, and wheel and containing complete, cycle and r-regular-strong are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is used in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-powerful-alliance number and minimal-global-powerful-alliance-neutrosophic number. Two different types of sets namely global-powerful alliance and minimal-global-powerful alliance are defined. Global-powerful alliance identifies the sets in general vision but minimal-global-powerful alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-powerful-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-powerful alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs has an open avenue, in the way that, the family only contains same classes of neutrosophic graphs. The results are about minimal-global-powerful alliance, minimal-global-powerful-alliance number and its corresponded sets, minimal-global-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-powerful alliances, minimal-t-powerful alliance, minimal-t-powerful-alliance number and its corresponded sets, minimal-t-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-t-powerful alliances. The connections amid t-powerful-alliances are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications and closing remarks. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global powerful alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set and reversely for non-members of set with less members in the way that the set is simultaneously t-offensive and(t-2)-defensive. A set is global if t=0. It leads us to the notion of global powerful alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

It is a common practice to detect outliers in a financial time series in order to avoid the adverse effect of additive outliers. This paper investigated the performance of GARCH family models (sGARCH; gjrGARCH; iGARCH; TGARCH and NGARCH) in the presence of different sizes of outliers (small, medium and large) for different time series lengths (250, 500, 750, 1000, 1250 and 1500) using root mean square error (RMSE) and mean absolute error (MAE) to adjudge the models. In a simulation iteration of 1000 times in R environment using rugarch package, results revealed that for small size of outliers, irrespective of the length of time series, iGARCH dominated, for medium size of outliers, it was sGARCH and gjrGARCH that dominated irrespective of time series length, while for large size of outliers, irrespective of time series length, gjrGARCH dominated. The study further leveled that in the presence of additive outliers on time series analysis, both RMSE and MAE increased as the time series length increased.

GNSS have been widely used in navigation, positioning and timing. Nowadays, the multipath errors previously considered detrimental may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), e.g. GPS- Multipath Reflectometry (GPS-MR). In this paper, a new element describing bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model linking the GPS observables (SNR, phase and pseudorange) with detailed vegetation parameters, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that wheat will decrease the amplitudes of GPS multipath observables, if we increase the vegetation moisture contents or the scatters sizes (stem or leaf), the amplitudes of GPS multipath observables (SNR, phase and code) decrease. Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with published results for environmental parameter detections with GPS-MR.

Nowadays, digitalization and automation in both industrial and research activities is a driving force for innovations. In recent years, Machine Learning (ML) techniques - the subset of Artificial Intelligence - have been widely applied as a key tool to automize and digitalize numerous in-dustrial processes. ML models can predict specific features, like materials' lifetime in a heating device, based on recently trained algorithms with applied input data. The results of ML algorithms are easy to interpret and can significantly decrease the time of research and decision-making, thus, substituting the trial-error approach. This work presents the state of the art in the application of Machine Learning in the investigation of MgO-C refractories for the steel industry. Also, the work presents an overview of the most commonly used ML algorithms in refractory engineering. So far published results confirm the high performance of ML, e.g., for prediction of oxidation behaviour, optimum graphite content and wear rate of MgO-C refractories, or for clustering materials based on various fused and sintered MgO sources into groups with similar corrosion resistance, thus, permitting to reduce expensive fused raw materials content. Most of the presented works were positively validated via experiment.

Nonalcoholic fatty liver disease (NAFLD) is a liver metabolism-associated steatohepatitis caused by non-alcoholic factors. NAFLD is currently the most prevalent liver disease in the world, affecting one-fourth of the world's population, and its prevalence increases with age. There are no approved drugs specifically for the treatment of NAFLD, and one important reason hindering drug development is the lack of effective biomarkers. C-reactive protein (CRP), a marker of inflammation, has been linked to NAFLD and aging in recent studies. Coincidentally, hepatocytes are responsible for the major CRP production, and the levels of CRP increase with age. Therefore, CRP is not only a potential marker, but also acts as a key factor driving liver aging and NAFLD. Herein, we reviewed the biological function and production mechanism of CRP and the relationship between CRP and NAFLD. We also comprehensively described the potential molecular mechanisms of CRP-mediated signaling in aging-associated NAFLD. Finally, we proposed possible therapeutic approaches based on the mechanism of CRP signaling in the pathogenesis of NAFLD. We hope this study can provide new insights into the development of aging associated NAFLD biomarkers and suggest that modulation of CRP signaling is a potential therapeutic target.

Consider a uniquely ergodic $C^*$-dynamical system ba\-sed on a unital $*$-endomorphism $\Phi$ of a $C^*$-algebra. We prove the uniform convergence of Cesaro averages $\frac1{n}\sum_{k=0}^{n-1}\lambda^{-n}\Phi(a)$ for all values $\lambda$ in the unit circle which are not eigenvalues corresponding to "measurable non continuous" eigenfunctions. This result generalises the analogous one in commutative ergodic theory presented in [19], which turns out to be a combination of the Wiener-Wintner Theorem (cf. [22]) and the uniformly convergent ergodic theorem of Krylov and Bogolioubov (cf. [15]).

We cultured Parmelina carporrhizans and P. quercina in Corn Meal Agar and 0.2% glucose Malt Yeast Agar for 160 days. Chemosyndrome of natural thalli and mycobiont cultures were analyzed by HPLC. Lecanoric acid, atranorin, chloratranorin and ergosterol were detected in P. carporrhizans thalli, while lecanoric acid, chloratranorin and aliphates were found in P. quercina thalli. The secondary methabolites pattern between thalli and mycobiont culture was completely different in both species. Both species secreted the phenalenone myeloconone C in culture media and was also detected in P. quercina mycobiont aggregates. Interestingly, the phenolic compounds produced by the mycobiont culture of P. carporrhizans are related to those produced by natural thallus by the same biosynthetic pathway, while the chemosyndrome of P. quercina mycobiont implies switch of biosynthetic pathway from acetate-polymalonate pathway to shikimic acid pathway, with pulvinic acid as major compound of mycobiont culture. The role of Myelochonone C, confluentic acid and pulvinic acid produced by mycobiont culture is discussed as possible adaptive vantage in field as photoprotective agent or as byproduct result of stressing artificial culture conditions.

Two series of novel [1,2,4]triazolo[4,3-c]- and [1,2,4]triazolo[1,5-c]quinazoline fluorophores with 4’-amino[1,1′]-biphenyl residue at position 5 have been prepared via Pd-catalyzed cross-coupling Suzuki-Miyaura reactions. The treatment of 2-(4-bromophenyl)-4-hydrazinoquinazoline with orthoesters in solvent-free conditions or in absolute ethanol leads to the formation of [4,3-c]-annulated triazoloquinazolines, whereas [1,5-c] isomers are formed in acidic media as a result of Dimroth rearrangement. 1D-NMR and 2D-NMR spectroscopy as well as single‐crystal X‐ray diffraction analysis unambiguously confirmed the annelation type and determined the molecular structure of p-bromophenyl intermediates and target products. Photophysical properties of the target compounds were investigated in two solvents and solid state and compared with those of related 3-aryl-substituted [1,2,4]triazolo[4,3-c]quinazolines. The excluding of aryl fragment from triazole ring has been revealed to improve fluorescence quantum yield in solution. Most of the synthesized structures show moderate to high quantum yields in solution. Additionally, the effect of solvent polarity on the absorption and emission spectra of fluorophores has been studied and considerable fluorosolvatochromism was stated. Moreover, electrochemical investigation and DFT calculations have been performed, their results are consistent with the experimental observation.

Bermudagrass (Cynodon spp.) is one of the drought-resistant warm-season turfgrasses adapted to the southern and transitional zones in the United States. Multiple hybrid varieties have been developed and released for use as a turfgrass and others are in pipeline. Increasing genetic di-versity of commercial varieties is vital to tackle stress tolerance. A DNA profiling study of 21 experimental selections from the Oklahoma State University (OSU) turfgrass breeding program and 11 cultivars was conducted using 51 simple sequence repeat (SSR) primer pairs that spread across the bermudagrass genome. Pairwise genetic relationship analysis among the genotypes using 352 polymorphic bands showed genetic similarity coefficients ranging from 0.59 to 0.89. Cluster analysis using the un-weighted paired group method with arithmetic average (UPGMA) method grouped the entries into six clusters. Correlation analysis identified different levels of pairwise genetic relationship among the entries that largely reflected parental relationship. Di-rectional breeding and selection for cold hardiness or drought resistance created progeny that had distinct genetic diversity in the tested bermudagrasses. It is evident that an increase in genetic diversity of the existing cultivar pool with the release of one or more of the experimental selec-tions for commercial use will strengthen and improve bermudagrass systems.

We recently formulated Modular Dvoretzky, Type-Cotype, Khinchin-Kahane and Grothendieck Inequality problems in the Appendix of \textit{[arXiv:2302.03718v1]}. For the sake of wide accessibility we give a separate treatment of them.

Vitamin C is an essential nutrient that must be obtained through the diet in adequate amounts to prevent hypovitaminosis C and the potentially fatal deficiency disease scurvy. Global vitamin C status and prevalence of deficiency has not previously been reported, despite vitamin C’s pleiotropic roles in both non-communicable and communicable disease. This review highlights the global literature on vitamin C status and the prevalence of hypovitaminosis C and deficiency. Related dietary intake is reported if assessed in the studies. We also explore if global vitamin C status has changed over time. Overall, the review illustrates the shortage of high quality epidemiological studies of vitamin C status in many countries, particularly low- and middle-income countries. The available evidence indicates that vitamin C deficiency is common in low- and middle-income countries and not uncommon in high income settings. Further high quality studies are required to confirm these findings, including in the countries not yet represented, and to fully understand associations with a range of disease processes. Our findings suggest a need for interventions to prevent deficiency in a range of at risk groups and regions of the world.

Since its initial development in the 1970’s by Phil Burke and his collaborators, the R-matrix theory and associated computer codes have become the de facto approach for the calculation of accurate data for general electron-atom/ion/molecule collision and photoionization processes. The use of a non-orthonormal set of orbitals based on B-splines, now called the B-spline R-matrix (BSR) approach, was pioneered by Zatsarinny. It has considerably extended the flexibility of the approach and improved particularly the treatment of complex many-electron atomic and ionic targets, for which accurate data are needed in many modelling applications for processes involving low-temperature plasmas. Both the original R-matrix approach and the BSR method have been extended to the interaction of short, intense electromagnetic (EM) radiation with atoms and molecules. Here we provide an overview of the theoretical tools that were required to facilitate the extension of the theory to the time domain. As an example of a practical application, we show results for two-photon ionization of argon by intense short-pulse extreme ultraviolet radiation

With the rise of long-read sequencers and long-range technologies, delivering high-quality plant genome assemblies is no longer reserved to large consortia. Indeed, sequencing techniques but also computer algorithms have reached a point where the reconstruction of assemblies at the chromosome-scale is now feasible at the laboratory scale. Current technologies, and especially long-range technologies, are numerous and selecting the most promising one for the genome of interest is crucial to obtain optimal results. In this study, we resequenced the genome of the yellow sarson, Brassica rapa cv. Z1, using the Oxford Nanopore PromethION sequencer and assembled the sequenced data using current assemblers. To reconstruct complete chromosomes, we used and compared three long-range techniques, optical mapping, Omni-C and Pore-C sequencing libraries commercialized by Bionano Genomics, Dovetail Genomics and Oxford Nanopore Technologies respectively, or a combination of the three, in order to evaluate the capability of each technology.

Identification and segmentation of rock particles is very important in geology, mining, engineering construction, and environmental monitoring. Traditional methods for recognizing the rock particle characteristics are time-consuming, labor-intensive, and limited by the geographical scope of the sampling sites, which makes it more difficult to represent the spatial distribution of the rock particles accurately. Recent advancements in deep learning techniques offer promising solutions to automate this process. This study aims at utilizing state-of-the-art (SOTA) Mask R-CNN deep learning algorithm from the Detectron2 framework, to capture global features of rocks that will enable the recognition of rock particles more efficiently, just from having the rock images. These images are subject to image processing techniques such as a Gaussian filter, to denoise and smoothen the image, and an Illumination Adaptive Transformer (IAT) framework, to adjust the lighting exposure; all of which add to improve the quality of the image dataset. Afterward, the Mask R-CNN and Detectron2 models are utilized in training the images using transfer learning. Experimental results from evaluating the performance of the proposed algorithms showcase the effectiveness of the approach, thereby highlighting its potential to revolutionize rock particle segmentation across various domains.

Objective: The study aimed to evaluate the effects of monoclonal antibodies (mAbs) acting on the calcitonin gene-related peptide (CGRP) or its receptor (anti-CGRP/R mAbs) on comorbid symptoms of depression, anxiety, and fatigue in migraine patients resistant to traditional prophylaxis. Methods: The study was an open-label prospective study assessing comorbidities in patients with high frequency (HFEM) and chronic migraine (CM), medication overuse headache (MOH), and resistance to traditional prophylaxis treated with anti-CGRP/R mAbs for 3 months. Results: 77 patients were enrolled with either HFEM (21%) or CM (79%) with or without MOH (56% and 44% respectively). We identified 21 non-responders (27%) and 56 responders (73%), defined on the reduction ≥ 50% of headache frequency. The two groups were highly homogeneous for investigated comorbidities. Disease severity in terms of headache frequency, migraine-related disability, and affective comorbid symptoms were reduced in both groups with different thresholds; allodynia and fatigue were ameliorated only in responders. Conclusion: anti-CGRP/R antibodies improve pain together with affection, fatigue, and sensory sensitization in migraine patients.

This article explores the relationship between convex functions defined on integers ($\mathbb{Z}$) and their extension to real numbers ($\mathbb{R}$). We introduce key definitions and investigate the hypothesis that there exists a unique convex curve within this family of functions, leading to a proof by contradiction. Our findings highlight the preservation of convexity as functions transition from integers to real numbers.

Disgust evolved as a way to protect one’s self from illness. DS-R measures disgust propensity of three kinds of disgust (Core, Animal Reminder and Contamination). Although the DS-R scale was refined mainly with young and largely female student population its impact on educational orientation has not been assessed. In the present study we examined the DS-R scoring and the choice of postgraduate studies in medical (n= 94) and psychology (n= 97) students. They responded to an anonymous web-based survey and completed the DS-R and a questionnaire on their demographics and plans for postgraduate studies. Female students outnumbered males (3:1) and scored higher in Total DS-R score (median: 59 vs. 50, p<0.05). Psychology students scored higher in all three kinds of disgust (p<0.05), indicating a higher level of disease avoidance. Medical students willing to follow Internal Medicine scored higher in Core Disgust (p<0.05) while psychology students willing to study Experimental Psychology scored lower in Animal Reminder subscale (p<0.001). Also, the higher the psychology students scored in Core Disgust scale the higher was the probability to choose Experimental Psychology. In conclusion, disgust propensity as rated by DS-R differentiates medical from psychology students and is also related to orientation preferences in postgraduate studies.

We propose an electrocardiogram (ECG) signal-based algorithm to estimate the respiratory rate is a significant informative indicator of physiological state of a patient. The consecutive ECG signals reflect the information about the respiration because inhalation and exhalation make transthoracic impedance vary. The proposed algorithm extracts the respiration-related signal by finding out the commonality between the frequency and amplitude features in the ECG pulse train. The respiration rate can be calculated from the principle components after the procedure of the singular spectrum analysis. We achieved 1.7569 breaths per min of root-mean-squared error and 1.7517 of standard deviation with a 32-seconds signal window of the Capnobase dataset, which gives notable improvement compared with the conventional Autoregressive model based estimation methods.

In chronic hepatitis C (CHC) patients, interferon-based treatments showed toxicity, limited efficacy, and psychiatric manifestations. Direct-acting antiviral (DAA) agents appeared safer, though it remains unclear if they may exacerbate or foster mood symptoms in drug-naïve CHC patients. We evaluated 62 CHC patients’ mental status, before and 12 weeks after DAA therapy, by assessment scales and psychometric instruments. We subdivided patients into two groups, CHC patients with (Group A) or without (Group B) a current and/or past psychiatric history. After DAA treatment, Group A patients showed low anxiety and improved depression, no variation in self-report distress, but worse general health perceptions. No significant difference emerged from coping strategies. Depression and anxiety improved in Group B, and no change emerged from total self-reported distress, except for somatization. Moreover, Group B increased problem-focused strategies for suppression of competing activities, and decreased strategies of instrumental social support. Contrarily, Group B reduced significantly emotion-focused strategies, such as acceptance and mental disengagement, and improved vitality, physical and social role functioning. DAA therapy is safe and free of hepatological and psychiatric side effects in CHC patients, regardless of current and/or past psychiatric history. In particular, patients without a psychiatric history also remarkably improved their quality of life.

Nanotechnology sparks discussions and concerns about the impacts of new nanomaterials on health and the environment. It holds importance in various domains due to its unique struc-tures. Carbon dots (C-dots) are versatile nanomaterials with applications in bioimaging, sensing, catalysis, polymers, solar cells, and more. They offer desirable characteristics such as stability, cost-effectiveness, biocompatibility, and high photoluminescent quantum yield. C-dots have the potential to replace expensive fluorophores in solar cells. They are catego-rized as carbon quantum dots, graphene quantum dots, and carbonized polymer dots. C-dots have outstanding optical and photoelectric properties with low toxicity. Bottom-up and top-down approaches are used for the synthesis of carbon dots (CDs), with each method im-pacting their physicochemical characteristics. The choice of synthesis method depends on de-sired properties and application requirements. Researchers combine these methods and ex-plore new approaches to enhance synthesis efficiency and tailor CD properties. CDs have di-verse chemical structures with modified oxygen, polymer-based, or amino groups on their surface. Various characterization methods such as HRTEM, XPS, and optical analysis (PL, UV) are used to determine CD structure. Carbon dots (CDs) are cutting-edge fluorescent nano-materials with remarkable qualities such as biocompatibility, low toxicity, environmental friendliness, high water solubility, and photo-stability. They are easily adjustable in terms of their optical properties, making them highly versatile in various fields. CDs find applications in bio-imaging, nanomedicine, drug delivery, solar cells, LEDs, photo-catalysis, elec-tro-catalysis, and other related areas.

The purpose of the study is to show the effect of the intake of vitamin C obtained from a diet rich in fruit and vegetables or vitamin C supplements on the level of vitamin C in the plasma. The level of vitamin C in plasma were determined before the study (T1), and after five months (T2). Moreover, a medical record was carried out and a questionnaire on the habits such as general eating and specific consumption of food rich in vitamin C. Both of them were completed before and after five months. In addition, related anthropometric analyses were carried out. The results of the first determination of vitamin C level in plasma were between 1.0 and 16.0 mg/L and the results of the second determination of vitamin C in plasma were between 4.9 and 14.1 mg/L. Furthermore, it was identified that 50% of the questioned people had a low fruit intake. Raw vegetables were consumed by fewer people, the intake being higher during the main meals. The correlation of plasma vitamin C with the eating habits of the subjects to the study points out an interdependence between the consumption of fruit and vegetables and the level of vitamin C in the plasma.

Adenoviruses are associated with respiratory tract, gastrointestinal or, less frequently, other involvement. Epidemics of adenovirus infections occur globally, in communities and in closed or crowded settings. In our institution, an outbreak of Adenovirus infection in infants and children was recently observed. Two main patterns of clinical presentation were observed: 68 patients had mainly respiratory symptoms (pharyngitis n=67, cough n=44; tonsillar exudate n=17; other respiratory signs n=4) while 26 patients showed prevalent gastrointestinal involvement (diarrhea n=26, vomiting n=8). Patients with respiratory symptoms had a significantly higher count of WBC, PMN and platelets, while CRP level approached statistical significance (p=0.07) for higher values in the patients with diarrhea. In order to explore the impact of selected presenting features, possible association between level of CRP and presence of pharyngeal exudate, cough, vomiting, diarrhea, duration of fever, number of neutrophils, and administration of antibiotics was analyzed. Patients falling in the tertile with more elevated CRP values had significantly more often tonsillar exudate and diarrhea, while those in the lower tertile had a 4.4 days duration of fever, vs. ≥5.0 days in the remaining patients. Antibiotic therapy was administered more frequently to patients with higher values of CRP (p=0.006). Duration of hospitalization was not associated with the CRP level. The median time from the receipt of positive adenovirus PCR test result to patient discharge was 1 day in 73% of cases. The number of copies of adenovirus detected by PCR ranged between 47 million and 15/L. Falling in the highest terzile of copy number was significantly associated with pharyngitis. The 24 patients with evidence of viral coinfection had no difference in the demographics or presenting features, with the only exception of a significantly higher leukocyte count. Rapid turn-around of results of molecular testing of adenovirus genome on pharyngeal swab allowed us to rapidly diagnose adenovirus infection, allowing stopping antibiotic therapy and immediate discharge, with reduced discomfort for the families and more appropriate use of hospital beds. A high copy number of adenovirus from pharyngeal swab should not be taken as an indicator of worse prognosis, thus allowing preferential use of qualitative rather than quantitaive assay.

Aging is a complex process associated with tissue degeneration and an increased risk of age-related diseases. This study aimed to evaluate the impact of Terasen®, a nutraceutical containing standardized extracts of Euterpe oleracea, Myrciaria dubia, and purified oil of Bixa orellana and Astrocaryum aculeatum on the lifespan of Caenorhabditis elegans, a widely used model organism for aging research. The findings demonstrated that Terasen® exhibited significant antioxidant activity and influenced the feeding behavior of C. elegans, leading to a reduced pharyngeal pumping rate and a decreased number of offspring produced by treated individuals. Notably, Terasen® also displayed a remarkable ability to extend the lifespan of C. elegans. These findings suggest that Terasen® may possess promising anti-aging effects in vivo, warranting further investigation.

The involvement of NK and other cytotoxic cells is considered the first defense' line against cancer. However, a significant lack of information prevails on the possible roles played by factors considered characteristic of primitive cells, such as c-kit and Sca-1, in activating these cells, particularly in melanoma models subjected to treatments with substances under investigation, such as the case of norcantharidin. In this study, B16F1 murine melanoma cells were used to induce tumors in DBA/2 mice, estimating the proportions of NK and iNKT cells, the presence of activation (CD107a+) and primitive/activation (c-kit+/Lya6A+) markers, some tumor parameters, such as the presence of mitotic bodies, nuclear factor area, NK and iNKT cell infiltration in the tumor, infiltrated tumor area, and infiltrating lymphocyte count at 10x and 40x in specimens treated with pentoxifylline, norcantharidin and the combination of both drugs. Possible correlations were estimated with Pearson's correlation analysis. Despite having demonstrated multiple correlations, it should be noted that immaturity/activation markers were related to these cells' activation. At the tumor site, iNKT cells are the ones that exert the cytotoxic potential on tumor cells, but they are confined to specific sites in the tumor. Due to the higher number of interactions of natural killer cells with tumor cells, it is concluded that the most effective treatment was PTX at 60 mg/kg + NCTD at 0.75 mg/kg.

Modified nucleobases are potentially useful building blocks when containing catalytically active functionalities and could be introduced in chiral tridimensional molecules such as nucleic acids, which creates the premises for the development of novel catalytic species. Herein we describe the synthesis of a novel β-C-nucleoside bearing a diol group at anomeric position, amenable as metal ligand or as organo-catalyst. The abasic ligand was successfully prepared and inserted into complementary DNA strand.

Hepatitis C virus (HCV) core protein is a multifunctional protein that is involved in proliferation, inflammation and apoptosis mechanism of hepatocytes. HCV core protein genetic variability has been implicated in various outcomes of HCV pathology and treatment. In the present study, we aimed to analyze the role of HCV core protein in tumor necrosis factor α (TNFα)-induced death under the viewpoint of HCV genetic variability. Immortalized hepatocytes (IHH), and not the Huh7.5 hepatoma cell line, stably expressing HCV subtype 4a and HCV subtype 4f core proteins showed that only HCV 4a core protein could increase sensitivity to TNFα-induced death. Development of two transgenic mice expressing the two different core proteins under the liver-specific promoter of transthyretin (TTR) allowed for the in vivo assessment of the role of core in TNFα-induced death. Using the TNFα-dependent model of lipopolysaccharide/D-galactosamine (LPS/Dgal) we were able to recapitulate the in vitro results in IHH cells in vivo. Transgenic mice expressing HCV 4a core protein were more susceptible to the LPS/Dgal model while mice expressing HCV 4f core protein had the same susceptibility as their littermate controls. Transcriptome analysis in liver biopsies from these transgenic mice gave insights into HCV core molecular pathogenesis, while linking HCV core protein genetic variability to differential pathology in vivo.

Abstract: Carbohydrates form the major source of energy in Asian diets. A lower carbohydrate diet became the recommended golden standard for healthy lifestyle. However, the effects of low-carbohydrates diet on health in apparently healthy individuals have been poorly studied, especially in relation to insulin resistance syndrome (IRS). A total of 120 healthy weight participants with no previous history of a major medical condition and an average BMI of ≤ 25kg/m2 were recruited. Self-reported dietary intake and objective physical activity by accelerometry were tracked for seven days. Participants were divided into three categories according to their dietary intake of carbohydrates. Blood samples were collected for metabolic markers analysis. HOMA of insulin resistance (HOMA-IR), β-cell function (HOMA-B) and C-peptide were used to evaluate glucose homeostasis. The consumption of low carbohydrates (less than 45% of total energy) significantly correlated with higher HOMA-IR, Lower HOMA-β % compared to moderate carbohydrate intake (between 45% to 65%). However, only the HOMA-β % was significantly influenced by carbohydrates intake. Moreover, low carbohydrates intake was significantly associated with elevated C-peptide secretion. The substitution of carbohydrates with other macronutrients, such as fat and proteins in the Atkins/ketogenic diet, resulted in a pronounced induction of IRS-related inflammatory markers; FGF2, IP-10, IL-6, IL-17A, MDC and reduction of IL-13. Overall, the presented data highlight, for the first time, that low carbohydrate intake results in significant glucose homeostasis imbalance that may be driven by a heightened state of inflammatory response.

Vitamin C is important in preventing and slowing the progression of many diseases. There is significant evidence linking periodontal disease and vitamin C. We aimed to systematically review studies addressing the relationship between vitamin C and periodontal disease and the preventive ability of vitamin C against periodontal disease. Electric searches were performed using PubMed, EMBASE, Cochrane Library, and Web of Science. Studies addressing the relationships between periodontal disease and vitamin C in adults aged over 18 years were included. Quality assessment was done using Critical Appraisal Skills Program guideline and GRADE-CERQual. Seventy hundred and sixteen articles were retrieved and fifteen articles (7 cross-sectional studies, 2 case-control studies, 2 cohort studies, and 4 randomized controlled trial [RCT]) were selected by reviewing all articles. Vitamin C intake and blood level were negatively related to periodontal disease in all 7 cross-sectional studies. Subjects who suffer from periodontitis presented lower vitamin C intake and lower blood vitamin C level than subjects without periodontal disease in the two case-control studies. Patients with lower dietary intake or lower blood level of vitamin C showed greater progression of periodontal disease than did the controls. Intervention using vitamin C administration improved gingival bleeding in gingivitis but not in periodontitis. Alveolar bone absorption was also not improved. The present systematic review suggested that vitamin C contributes to reduced risk of periodontal disease.

Adenosine to inosine (A-to-I) RNA editing is a highly conserved regulatory process carried out by adenosine-deaminases (ADARs) on dsRNAs. Although a considerable fraction of the transcriptome is edited, the function of most editing sites is unknown. Previous studies indicate changes in A-to-I RNA editing frequencies following exposure to several stress types. However, the overall effect of stress on the expression of ADAR targets is not fully understood. Here, we performed high-throughput RNA sequencing of wild-type and ADAR mutant C. elegans worms after heat-shock to analyze the effect of heat-shock stress on the expression pattern of genes. We found that ADAR regulation following heat-shock does not directly involve heat-shock related genes. Our analysis also revealed that lncRNAs and pseudogenes, which have a tendency for secondary RNA structures, are enriched among upregulated genes following heat-shock in ADAR mutant worms. The same group of genes is downregulated in ADAR mutant worms under permissive conditions, which is likely, considering that A-to-I editing protects endogenous dsRNA from RNA-interference (RNAi). Therefore, temperature increases may destabilize dsRNA structures and protect them from RNAi degradation, despite the lack of ADAR function. These findings shed new light on the dynamics of gene expression under heat-shock in relation to ADAR function.

It has been proven that in standard Einstein gravity, exotic matter (i.e. matter violating the point-wise and averaged weak and null energy conditions) is required to stabilize traversable wormholes. Quantum field theory permits these violations due to the quantum coherent effects found in any quantum field . Even reasonable classical scalar fields violate the energy conditions. In the case of the Casimir effect and squeezed vacuum states, these violations have been experimentally proven. It is advantageous to investigate methods of minimizing the use of exotic matter. One such area of interest is extended theories of Einstein gravity. It has been claimed that in some extended theories, stable traversable wormholes solutions can be found without the use of exotic matter. There are many extended theories of gravity and in this review paper we first explore f(R) theories and then explore some wormhole solutions in f(R) theories including Lovelock gravity.

Partial negative allosteric modulators (NAM) of the mGlu5 receptor are an excellent alternative to full antagonists and NAMs because they retain some therapeutic effects and, at the same time, have a much broader therapeutic window. Here, we investigated whether partial mGlu5 NAM, M-5MPEP induced a fast and sustained antidepressant-like effect, characteristic of rapid-acting antidepressant drugs (RAADs) like ketamine, in C57BL/6J mice. M-5MPEP caused a rapid, dose-dependent antidepressant-like action in the tail suspension test (TST) 60 min after injection. This effect was antagonized by an AMPA receptor antagonist (NBQX) and a TrkB receptor antagonist (ANA-12) but not by 5HT1A and 5HT2A/2C receptor antagonists. Furthermore, M-5MPEP (30 mg/kg) induced sustained antidepressant-like effects 24 h after the last of four administrations. These effects were revealed in the splash test, designed to measure apathy-like state, and in the TST. Western blot and ELISA analyses indicated the involvement of the TrkB/BDNF pathway in the sustained M-5MPEP effects. Additionally, prolonged effects of M-5MPEP were entirely reversed by the TrkB receptor antagonist ANA-12 in both the splash test and the TST, confirming the critical role of TrkB receptor activation in the sustained antidepressant-like effect of M-5MPEP. Importantly, M-5MPEP enhanced the subthreshold dose of (R)-ketamine in the TST, indicating both substances' convergent mechanisms of action and the possibility of their practical use in treating depression.

Infant electrocardiograms (ECG) and heart rates (HR) are very useful biosignals for psychological research and clinical work, but can be hard to analyze properly, particularly long form (≥5 minutes) recordings taken in naturalistic environments. Infant HRs are typically much faster than adult HRs, and so some of the underlying frequency assumptions made about adult ECGs may not hold for infants. However, the bulk of publicly available ECG approaches focus on adult data. Here, existing open-source ECG approaches are tested on infant datasets. The best performing open-source method is then modified to maximize its performance on infant data (e.g., including a 15Hz high pass filter, adding local peak correction). The HR signal is then subsequently analyzed, developing an approach for cleaning data with separate sets of parameters for the analysis of cleaner and noisier HR. A Signal Quality Index (SQI) for HR is also developed, providing insight into where a signal is recoverable and where it is not, allowing for more confidence in analysis performed on naturalistic recordings. The tools developed and reported in this paper provide a base for future analysis of infant ECG and related biophysical characteristics. Of particular importance, the proposed solutions outlined here can be efficiently applied to real-world large datasets.

We introduce a special vector field ω on a Riemannian manifold (N^m, g), such that the Lie derivative of the metric g with respect to ω is equal to ρRic, where Ric is the Ricci curvature of (N^m, g) and ρ is a smooth function on N^{m} and call this vector field a ρ-Ricci vector field. We use ρ-Ricci vector field on a Riemannian manifold (N^m, g) and find two characterizations of m-sphere S^m(α). In first result, we show that an m-dimensional compact and connected Riemannian manifold (N^m, g) with nonzero scalar curvature admits a ρ-Ricci vector field ω such that ρ is nonconstant function and the integral of Ric(ω,ω) has a suitable lower bound is necessary and sufficient for (N^m, g) to be isometric to m-sphere S^m(α). In second result, we show that an m-dimensional complete and simply connected Riemannian manifold (N^m, g) of positive scalar curvature admits a ρ-Ricci vector field ω such that ρ is a nontrivial solution of Fischer-Marsden equation and the squared length of the covariant derivative of ω has an appropriate upper bound, if and only if, (N^m, g) to be isometric to m-sphere S^m(α).

Bone Scan Index (BSI) is an image biomarker for quantification on bone metastasis of cancers. To compute BSI, not only the hotspots (metastasis) but also the bones have to be segmented. Most related researches focus on binary classification on bone scintigraphy: having metastasis or none. Rare studies focus on pixelwise segmentation. In this study we compare three advanced convolutional neural network (CNN) based models to explore the bone segmentation on dataset in house. The best model is Mask R-CNN, which reaches the precision, sensitivity and F1-score: 0.93, 0.87, 0.90 for prostate cancer patients and 0.92, 0.86, 0.88 for breast cancer patients, respectively. The results are the average of 10-fold cross-validation, which reveals the reliability for clinical use on bone segmentation.

In the first part of this article, we discuss and generalize the complete convergence introduced by Hsu and Robbins (1947) to the r-complete convergence introduced by Tartakovsky (1998). We also establish its relation to the r-quick convergence first introduced by Strassen (1967) and extensively studied by Lai (1976). Our work is motivated by various statistical problems, mostly in sequential analysis. As we show in the second part, generalizing and studying these convergence modes is important not only in probability theory but also to solve challenging statistical problems in hypothesis testing and changepoint detection for general stochastic non-i.i.d. models.

In this paper, we investigated the trajectory of the massive particle in the vicinity of a general spherical symmetric black hole. Also, in the framework of general sphericalily symmetric black hole, Pseudo-Newtonian potential (PNP) and effective potentials has been investigated. As an example, static spherically symmetric black hole in f(R) gravity is considered and presented the brief discussion on the structure of spacetime and horizons. We calculated energy and angular momentum in the framework of general relativity as well as in Pseudo-Newtonian theory. A graphical comparison of angular momentum in this both framework has been studied.

Early detection of wildfires has been limited using the sun-synchronous orbit satellites due to their low temporal resolution and wildfires’ fast spread in the early stage. NOAA’s geostationary weather satellites GOES-R can acquire images every 15 minutes at 2km spatial resolution, and have been used for early fire detection. However, advanced processing algorithms are needed to provide timely and reliable detection of wildfires. In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R dense time series data. GRU model maintains good performance on temporal modelling while keep a simple architecture, makes it suitable to efficiently process time-series data. 36 different wildfires in North and South America under the coverage of GOES-R satellites are selected to assess the effectiveness of the GRU method. The detection times based on GOES-R are compared with VIIRS active fire products at 375m resolution in NASA’s Fire Information for Resource Management System (FIRMS). The results show that GRU-based GOES-R detections of the wildfires are earlier than that of the VIIRS active fire products in most of the study areas. Also, results from proposed method offer more precise location on the active fire at early stage than GOES-R Active Fire Product in mid-latitude and low-latitude regions.

Background: Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) affects human respiratory function causing COVID-19 disease. Safe natural products with potential antiviral phytochemicals with benefits to control high-altitude sickness could be adopted as adjunct therapy for COVID-19. The red petals of Rhododendron arboreum, commonly available and consumed in the Himalayan region may have phytochemicals with potential antiviral properties against COVID-19 targets.Purpose: This study was aimed to profile the secondary metabolites of R. arboreum petals, to assess their absorption, distribution, metabolism and elimination (ADME) properties and evaluate their antiviral potential by docking against COVID-19 targets such as SARS-CoV-2 main protease (M^pro PDB ID: 6LU7) and Human Angiotensin Converting Enzyme 2 (ACE2) receptor (PDB ID: 1R4L) that mediates the viral replication and entry into the host respectively.Methods: The phytochemicals of R. arboreum petals were mainly profiled using Gas Chromatography-Mass Spectroscopy (GC-MS) and ¹H-NMR. In addition, the phytochemicals reported from the literature were tabulated. The ADME properties of the phytochemicals were predicted using SwissADME tool. Molecular docking simulation of the phytochemicals against SARS-CoV-2 main protease (M^pro PDB ID: 6LU7) and Human Angiotensin converting enzyme 2 (ACE2) receptor (PDB ID: 1R4L) were carried out using PyRx.Results: R. arboreum petals were found to be rich in appreciable proportions of secondary metabolites such as Quinic acid, 3-Caffeoyl-quinic acid, 5-O-Coumaroyl-D-quinic acid, 5-O-Feruloylquinic acid, 2,4-Quinolinediamine, Coumaric acid, Caffeic acid, Epicatechin, Catechin, 3-Hydroxybenzoic acid, Shikimic acid, Protocatechuic acid, Epicatechin gallate, Quercetin, Quercetin-O-pentoside, Quercetin-O-rhamnoside, Kaempferol-O-pentoside and Kaempferol. Several of these phytochemicals were reported to exhibit inhibitory activities against a range of viruses. From the molecular docking studies, 5-O-Feruloylquinic acid, 3-Caffeoyl-quinic acid, 5-O-Coumaroyl-D-quinic acid, Epicatechin and Catechin showed strong binding affinity with SARS-CoV-2 M^pro and human ACE2 receptor.Conclusion: This report showed that R. arboreum petals are rich in several antiviral phytochemicals that also docked against SARS-CoV-2 M^Pro and Human ACE2 receptor. This is the first report highlighting R. arboreum petals as a reservoir of antiviral phytochemicals with potential for synergetic activities. The outcomes merit further in vitro, in vivo and clinical studies on R. arboreum phytochemicals to develop natural formulations against COVID-19 disease for therapeutic benefits.

Infectious as well as most non-infectious diseases share certain common molecular mechanisms. Among them, oxidative stress and the subsequent inflammatory reaction are of particular note. Metabolic disorders induced by external agents, be they bacterial or viral pathogens, excessive calorie intake, poor-quality nutrients, or environmental factors, produce an imbalance between the production of free radicals and endogenous antioxidant systems; the consequence being the oxidation of lipids, proteins and nucleic acids. Oxidation and inflammation are closely related, and whether oxidative stress and inflammation represent the causes or consequences of cellular pathology, they produce metabolic alterations that influence the pathogenesis of the disease. In this review we highlight two key molecules in the regulation of these processes: Paraoxonase-1 (PON1) and chemokine (C-C motif) ligand 2 (CCL2). PON1 is an enzyme bound to high-density lipoproteins. It breaks down lipid peroxides in lipoproteins and cells, participates in the protection conferred by HDL against different infectious agents, and is considered part of the innate immune system. With PON1 deficiency, CCL2 production increases, which induces migration and infiltration of immune cells in target tissues, and is involved in disturbing normal metabolic function. This disruption involves pathways controlling cellular homeostasis as well as metabolically-driven chronic inflammatory states. Hence, an understanding of these relationships would help improve treatments and, as well, identify new therapeutic targets.