Symmetry concepts in parametrized dynamical systems may reduce the number of external parameters by a suitable normalization prescription. If, under the action of a symmetry group G, parameter space A becomes a (locally) trivial principal bundle, A ~ A/G x G, then the normalized dynamics only depends on the quotient A/G. In this way, the dynamics of fractional variables in homogeneous epidemic SI(R)S models, with standard incidence, absence of R-susceptibility and compartment independent birth and death rates, turns out to be isomorphic to (a marginally extended version of) Hethcote's classic endemic model, first presented in 1973. The paper studies a 10-parameter master model with constant and I -linear vaccination rates, vertical transmission and a vaccination rate for susceptible newborns. As recently shown by the author, all demographic parameters are redundant. After adjusting time scale, the remaining 5-parameter model admits a 3-dimensional abelian scaling symmetry. By normalization we end up with Hethcote's extended 2-parameter model. Thus, in view of symmetry concepts, reproving theorems on endemic bifurcation and stability in such models becomes needless.

In this paper we define a continuous wavelet transform of a Schwartz tempered distribution $f \in S^{'}(\mathbb R^n)$ with wavelet kernel $\psi \in S(\mathbb R^n)$ and derive the corresponding wavelet inversion formula interpreting convergence in the weak topology of $S^{'}(\mathbb R^n)$. It turns out that the wavelet transform of a constant distribution is zero and our wavelet inversion formula is not true for constant distribution, but it is true for a non-constant distribution which is not equal to the sum of a non-constant distribution with a non-zero constant distribution.

A wealth of Full Waveform (FW) LiDAR data are available to the public from different sources, which is poised to boost the extensive application of FW LiDAR data. However, we lack a handy and open source tool that can be used by potential users for processing and analyzing FW LiDAR data. To this end, we introduce waveformlidar, an R package dedicated to FW LiDAR processing, analysis and visualization as a solution to the constraint. Specifically, this package provides several commonly used waveform processing methods such as Gaussian, adaptive Gaussian and Weibull decompositions, and deconvolution approaches (Gold and Richard-Lucy (RL)) with users’ customized settings. In addition, we also developed functions to derive commonly used waveform metrics for characterizing vegetation structure. Moreover, a new way to directly visualize FW LiDAR data is developed through converting waveforms into points to form the Hyper Point cloud (HPC), which can be easily adopted and subsequently analyzed with existing discrete-return LiDAR processing tools such as LAStools and FUSION. Basic explorations of the HPC such as 3D voxelization of the HPC and conversion from original waveforms to composite waveforms are also available in this package. All of these functions are developed based on small-footprint FW LiDAR data, but they can be easily transplanted to the large footprint FW LiDAR data such as Geoscience Laser Altimeter System (GLAS) and Global Ecosystem Dynamics Investigation (GEDI) data analysis. It is anticipated that these functions will facilitate the widespread use of FW LiDAR and be beneficial for better estimating biomass and characterizing vegetation structure at various scales. The package and code examples can be found at https://github.com/tankwin08/waveformlidar.

A significantly reduced stress concentration effect and a stable deformation behavior are exhibited by the arc-like S-shaped auxetic structure. Analytical works beyond the bar and hinge method to capture structural effects, such as bending, shearing, etc., in the S-structure are scarce in the literature. The deformation pattern of the S-structure is dominated by bending and shearing within the linear elastic region. In this work, Timoshenko beam theory is used to derive closed-form expressions for overall elastic modulus and Poisson’s ratio. This agrees well with the results of finite element simulations. An adjusted R-square value of over 0.99 and almost 0.82 is obtained for elastic modulus and Poisson’s ratio, respectively. From parametric studies, it’s established that under quasi-static transverse load, strut thickness and the angle `α’ are the most important parameters for controlling elastic modulus, specific energy absorption, negative Poisson’s ratio (NPR) effect, and relative density of the entire auxetic structure. Also, it’s found that energy absorption and elastic modulus increase together. Interestingly, the elastic modulus of the structure under transverse load lies in the range from 3 MPa to 250 MPa, which means this structure is compliant enough and can be used in cushioning, packaging, soft robotics applications, etc.

High resolution melting (HRM) analysis is a powerful detection method for fast, high-throughput post-PCR analysis. A two-step HRM marker system was developed for identification of the N-, S-, R- and T-cytoplasms of onion. In the first step for identification of N-, S-, and R-cytoplasms, one forward primer was designed to the identical sequences of both cox1 and orf725 genes and two reverse primers specific to the polymorphic sequences of cox1 and orf725 genes were used. For the second step breeding lines with N-cytoplasm were evaluated with primers developed from the orfA501 sequence to distinguish between N- and T-cytoplasms. An amplicon with primers to the mitocondrial atp9 gene was used as an internal control. The two-step HRM marker system was tested using 246 onion plants. HRM analysis showed that the most common source of CMS, often used by Russian breeders, is S-cytoplasm, the rarest type of CMS is R-cytoplasm, and the proportion of T-cytoplasm among the analyzed breeding lines was 20.5%.

With covid infection having a periodic occurrence and each wave affecting millions of people, there is an urgent need for healthcare providers to develop readily available biological markers to predict the severity and mortality of COVID-19 infection at an early stage of the disease to predict the most optimal management. The Neutrophil – lymphocyte Ratio (NLR) and Platelet-lymphocyte ratio (PLR), are novel inflammatory markers suggested to predict the severity of illness in COVID -19 patients. We evaluated a retrospective cohort of 224 patients with covid 19 illnesses from August 2020 to October 2020. We categorized the patients into 'mild' and 'moderate to severe as per the severity of their illnesses. The optimal cut-off values of the continuous NLR, PLR, and Age were calculated by applying the receiver operating characteristic (ROC) curve analysis. Sensitivity, specificity, and likelihood ratios were calculated from ROC analysis. The results showed that Age, Hb, and NLR are significant predictors of the severity of illness. So we quantified the predictive contribution of those variables by its Z- score and showed that NLR is the strongest predictor followed by Age.ROC curve analysis revealed NLR to be an excellent predictor of disease severity (sensitivity 88.30% and specificity 82.60%) at a cut-off of > 4.24. A cut-off of 165.63 was obtained for PLR, which showed good predictive value for the severity of illness. A NLR > 6 was used as a predictor for mortality due to covid illness with good sensitivity and specificity. Conclusion: NLR and PLR can be used as prognostic markers to identify the severity of covid illness and the probability of mortality in the future in low-resource settings. Given its low cost, easily available, accessible, and reproducible data, it can be used as a useful marker to assist the physician in early referral and treatment of covid 19 infected patients.

In this paper, we classify the function space of all real-valued functions on R denoted as F(R,R) into 28 distinct blocks. Each block contains elements that share common features in terms of the cardinality of their sets of continuity and differentiability. Alongside this classification, we introduce the concept of the Connection, which reveals a special relationship structure between four well-known real-valued functions in real analysis: the Cantor function, Dirichlet function, the Thomae function, and the Weierstrass function. Despite the significance of this field, several perspectives remain unexplored.

The polysaccharide-based chiral stationary phase (CSP) columns for high-performance liquid chromatography (HPLC) were applied in the separation of liquid crystalline racemic mixtures obtained based on (R,S)-2-octanol and were found to be highly effective in recognizing isomers of minor structural differences. The mobile phase (MP), which consists of acetonitrile (ACN)/water (H2O) at different volume ratios, was used. All measurements were made at room temperature. The order of the elution was also determined. The chromatographic parameters such as resolution - (Rs), selectivity - (α), and the number of theoretical plates, i.e., column efficiency - (N), were determined. The polysaccharide-based CSP columns have unique advantages in separation technology, and this study has shown the potential usefulness of the CSP columns in separating liquid crystalline racemic mixtures belonging to the same homologous series.

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.

The ecotoxic effect of glyphosate, a commonly used Parthenium control herbicide, was evaluated in laboratory on biological and fitness attributes of Zygogramma bicolorata. Bioassay of glyphosate was carried within a minimum range of field recommended dose. Indirect exposure experiment reveals that glyphosate caused maximum mortality of 3^rd larval instars, extends the development stages of larvae, pre pupation and pupation. Significant negative effect was observed on sex ratio, fecundity, egg viability and on other fitness attributes. The study demonstrated the non-compatibility of glyphosate and unsafe with Zygogramma bicolorata. The study concludes that owing to acute toxicity of glyphosate at recommended field dose may be used in combination with Z. bicolorata for successful control of Parthenium weed, but needs to be evaluated under natural field conditions.

Pulmonary infections with Mycobacterium avium occur in susceptible individuals following exposure to the bacterium in the environment, where it often persists in biofilms. Many methods have been used to generate biofilms of M. avium, and it is unknown whether different approaches generate similar structures and cell phenotypes. To make a parallel comparison of in vitro biofilm ultrastructure, extracellular matrix (ECM) composition, and drug susceptibility of biofilm resident bacteria, we used two published methods to generate M. avium biofilms: four week incubation in M63 medium or 24 hour exposure to dithiothreitol (DTT). Scanning electron microscopy revealed differences in biofilm ultrastructure between the two methods, including variation in appearance of ECM materials and morphology of resident cells, while light microscopy and staining with calcofluor white indicated that both biofilms contained polysaccharides characteristic of cellulose. Measuring susceptibility of biofilms to degradation by enzymes suggested differences in structurally important ECM molecules, with DTT biofilms having important protein and, to a lesser extent, cellulose components, and M63 biofilms having moderate protein, cellulose, and DNA components. Both biofilms conferred resistance to the bactericidal effects of amikacin and clarithromycin, with resident cells being killed at >10-fold lower rates than planktonic cells at almost all concentrations. Though these comparisons indicate differences in biofilm responses by M. avium under differing conditions, they also suggest common features of biofilm formation including cellulose production and antimicrobial resistance.

Significant challenges exist globally regarding literacy teaching and learning, particularly in poor socio-economic settings in countries of the Global South. In this paper we argue that to address these challenges, major features of how the brain works that are currently ignored in the educational literature should be taken into account. First, perception is an active process based in detection of errors in hierarchical predictions of sensory data and action outcomes. Reading is a particular case. Second, emotions play a key role in underlying cognitive functioning. Innate affective systems underlie and shape all brain functioning, including oral and written forms of language and sign. Third, there is not the fundamental difference between listening/speaking and reading/writing often alleged on the basis of evolutionary arguments. Both are socio-cultural practices driven and learnt by the communication imperative of the social brain. Fourth, like listening, reading is not a linear, bottom-up process. Both are non-linear contextually shaped psycho-social processes of understanding, shaped by current knowledge and cultural contexts and practices. Reductionist neuroscience studies which focus on decontextualized parts of reading cannot access all the relevant processes. An integrated view of brain function reflecting this non-linear nature implies that an ongoing focus on personal meaning and understanding provides positive conditions for all aspects of literacy learning. Assessment of literacy teaching at all its stages should include indicators that take into account these foundational features relating reading and writing to neuroscience.

Prime numbers are the atoms of mathematics and mathematics is needed to make sense of the real world. Finding the Prime number structure and eventually being able to crack their code is the ultimate goal in what is called Number Theory. From the evolution of species to cryptography, Nature finds help in Prime numbers. One of the most important advances in the study of Prime numbers was the paper by Bernhard Riemann in November 1859 called “Ueber die Anzahl der Primzahlen unter einer gegebenen Grösse” (On the number of primes less than a given quantity). In that paper, Riemann gave a formula for the number of primes less than x in terms the integral of 1/log(x) and the roots (zeros) of the zeta function defined by: Where ζ(z) is a function of a complex variable z that analytically continues the Dirichlet series. Riemann also formulated a conjecture about the location of the zeros of RZF, which fall into two classes: the "trivial zeros" -2, -4, -6, etc., and those whose real part lies between 0 and 1. Riemann's conjecture Riemann hypothesis [RH] was formulated as this: [RH] The real part of every nontrivial zero z* of the RZF is 1/2. Proving the RH is, as of today, one of the most important problems in mathematics. In this paper we will provide a proof of the RH. The proof of the RH will be built following these five parts: PART 1: Description of the RZF PART 2: The C-transformation PART 3: Application of the C-transformation to in Re(z) 0 to obtain ζ(z)=X(z)-Y(z) PART 4: Analysis of the values of z such that X(z)=Y(z), and |X(z)|=|Y(z)|, that equates to ζ(z)=0 Proof that |X(z)|=|Y(z)| only if Re(z)=1/2 Conclude that ζ(z)=0 only if Re(z)=1/2 for Re(z) 0 PART 5: We will also prove that all non-trivial zeros of ζ(z) in the critical line of the form are not distributed randomly. There is a relationship between the values of those zeros and the Harmonic function that leads to an algebraic relationship between any two zeros.

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.

Fatigue risk to commercial pilots operating under global pandemic conditions had not been in-vestigated prior to COVID-19. Examining how pilots slept during COVID-19 pandemic-specific flights can provide a precedent for estimating fatigue risk for future public health emergencies. Twenty (n=20) pilots flying across five COVID-19 humanitarian missions between Brazil and China wore a sleep-tracking device (the Zulu watch), which has been validated for the estimation of sleep timing (sleep onset and offset), duration, efficiency, and sleep depth (Wake, Interrupted, Light, or Deep Sleep) throughout the mission period. Pilots also reported sleep timing, duration and subjective quality of their in-flight rest periods using a sleep diary. To our knowledge, this is the first report of commercial pilot sleep behavior during ultra-long-range operations under COVID-19 pandemic conditions. Moreover, these analyses provide an estimate of sleep depth during in-flight sleep, which has not been reported previously in the literature.

Drought events are predicted to become more prevalent in the future. Evaluating the performance of herbicide-resistant and susceptible weed ecotypes to progressive drought can provide insights into whether resistance trait(s) increased or reduced the fitness of a resistant population. Two experiments were conducted in the greenhouse between January and May 2021 to evaluate drought tolerance differences between Palmer amaranth accessions resistant to S-metolachlor or glyphosate and their susceptible counterparts. The accessions used were: S-metolachlor-resistant (17TUN-A), a susceptible standard (09CRW-A), and glyphosate-resistant (22 to 165 EPSPS copies) and glyphosate-susceptible (3 to 10 EPSPS copies) plants from accession 16CRW-D. Daily transpiration of each plant was measured. The daily transpiration rate was converted to normalized transpiration ratio (NTR) using a double-normalization procedure. The daily soil water content was expressed as a fraction of transpirable soil water (FTSW). The threshold FTSW (FTSWcr), after which NTR decreases linearly, was estimated using a two-segment linear regression analysis. The data showed differences between S-metolachlor- resistant and -susceptible accessions (P ≤ 0.05). The FTSW remaining in the soil at the breakpoint for the S-metolachlor-susceptible accession (09CRW-A) was 0.17±0.007. The FTSW remaining in the soil at the breakpoint for the S-metolachlor-resistant accession (17TUN-A) was 0.23±0.004. Although the mechanism endowing resistance to S-metolachlor might have contributed to increased drought tolerance, follow-up experiments are needed to verify this finding. Increased EPSPS copy number did not improve drought tolerance of Palmer amaranth.

Data could be in many forms like text, image, audio, video and many others. Amongst these data, processing image is of important concern even with sophisticated technologies. Generally, images consume more storage space and processing time. This work aims in attaining a novel image encryption strategy that consumes very less computational time with maximum security. The idea is to split the image into blocks and rearrange the pixels in diagonal fashion to achieve confusion. Next, the blocks are combined to form sub images and one block of the sub image is subjected to Secure Hash Algorithm (SHA 512 bits). The SHA bits are XORed with the remaining blocks of the sub image. Finally, the entire image is encrypted using Advanced Encryption Standard (AES). Decryption process is the exact reverse of encryption process. The computational overhead is very low, and security is efficient. The results are compared with existing encryption techniques.

In the software development process, the decision-maker (DM) has a range of problems inherent to its function. Wrong choices during software planning can bring great risk to the project. Therefore, the planning of software releases to be delivered to the customer should be well done. This is not an easy task because releases are made up of many requirements that contain complex variables that must be considered, such as precedence, cost, requirement stability, among other features that make the requirements-selection process challenging. To make this process less exhaustive, DM can use tools that facilitate this work. In software engineering, we can find fields of research specialists in this context, such as Search-Based Software Engineering (SBSE). The SBSE makes use of advanced metaheuristics to search for optimal solutions or the closest to it. In this work, we try to use another field of research to solve this same problem type, the Verbal Decision Analysis (VDA). To do this, we elaborate a workflow that will use the same source data, execute two solutions using the two search fields (SBSE and VDA) and compare the results. In the end, we evaluated and commented on the results.

Direct reprogramming of fibroblasts into induced cardiomyocytes (iCMs) holds a great promise for regenerative medicine and has been studied in several major directions. However, cell-cycle regulation, a fundamental biological process, has not been investigated during iCM-reprogramming. Here, our time-lapse imaging on iCMs, reprogrammed by Gata4, Mef2c, and Tbx5 (GMT) monocistronic retroviruses, revealed that iCM-reprogramming was majorly initiated at late-G1- or S-phase and nearly half of GMT-reprogrammed iCMs divided soon after reprogramming. iCMs exited cell cycle along the process of reprogramming with decreased percentage of EdU⁺/αMHC-GFP⁺ cells. S-phase synchronization post-GMT-infection could enhance cell-cycle exit of reprogrammed iCMs and yield more GFP^high iCMs, which achieved an advanced reprogramming with more expression of cardiac genes than GFP^low cells; however, S-phase synchronization didn’t enhance the polycistronic-MGT reprogramming, in which cell-cycle exit had been accelerated. In conclusion, post-infection synchronization of S-phase facilitated the early progression of GMT-reprogramming through a mechanism of enhanced cell-cycle exit.

Topological indices have been used to modeling biological and chemical properties of molecules in quantitive structure property relationship studies and quantitive structure activity studies. All the degree based topological indices have been defined via classical degree concept. In this paper we define a novel degree concept for a vertex of a simple connected graph: S degree. And also we define S indices of a simple connected graph by using the S degree concept. We compute the S indices for well-known simple connected graphs such as paths, stars, complete graphs and cycles.

Analysis of telomere length is an important component of many studies aiming to characterize the role of telomere maintenance mechanisms in cellular lifespan, disease, or in general chromosome protection and DNA replication pathways. Several powerful methods to accurately measure telomere length from Southern blots have been developed, but their utility for large-scale genomic studies has not been previously evaluated. Here we performed comparative analysis of two recently developed programs, TeloTool and WALTER, for extracting mean telomere length values from Southern blots. Using both software packages, we measured telomere length in two extensive experimental datasets for the model plant Arabidopsis thaliana, consisting of 537 natural accessions and 65 T-DNA mutant lines in the Col-0 reference background. We report that TeloTool substantially overestimates telomere length in comparison to WALTER, especially for values over 4,500 bp. Importantly, TeloTool and WALTER-calculated telomere length values correlate the most in the 2,100-3,500 bp range, suggesting that telomeres in this size interval can be estimated by both programs equally well. We further show that genome-wide association studies using datasets from both telomere length analysis tools can detect the most significant SNP candidates equally well. However, GWAS analysis with the WALTER dataset consistently detects fewer significant SNPs than analysis with the TeloTool dataset, regardless of the GWAS method used. These results imply that telomere length data generated by WALTER may represent a more stringent approach to GWAS and SNP selection for downstream molecular screening of candidate genes. Overall, our work revealed the unanticipated impact of telomere length analysis method on the outcomes of large-scale genomic screens.

Uncovering hidden mixture correlation among variables have been investigating in the literature using mixture R-vine copula models. These models are hierarchical in nature. They provides a huge flexibility for modelling multivariate data. As the dimensions increases, the number of the model parameters that need to be estimated is increased dramatically, which becomes along with huge computational times and efforts. This situation becomes even much more harder and complicated in the mixture Regular vine models. Incorporating truncation method with mixture Regular vine models will reduce the computation difficulty for the mixture based models. In this paper, tree-by-tree estimation mixture model is joined with the truncation method, in order to reduce the computational time and the number of the parameters that need to be estimated in the mixture vine copula models. A simulation study and a real data applications illustrated the performance of the method. In addition, the real data applications show the affect of the mixture components on the truncation level.

The segmentation and de-noising are basic operations, required in every signal processing and classification system. The classical segmentation and de-noising approaches are time-invariant. Consequently, it results in the post processing of an unnecessary information and causes an increase in the system processing activity and power consumption. In this context, an efficient event-driven segmentation and de-noising technique is proposed. It is founded on the principles of level crossing and activity selection. Therefore, it can adapt its sampling frequency, segmentation window length and position along with the filter order by analyzing the input signal local characteristics. As a result, the computational complexity and the power consumption of the proposed system is reduced compared to the counter ones. The suggested system performance is compared with the classical one. It is done for the case of a multi-channel Electroencephalogram (EEG) signals. Results show a noticeable compression gain with an effective adaptation of the de-noising filters order. It aptitudes a significant computational gain, transmission data rate reduction and power consumption reduction of the proposed technique, compared to the counter ones. It shows that the proposed solution is an attractive candidate to embed in the new generation EEG wearables.

Radar transmit signal design is a critical factor for the radar performance. In this paper, we investigate the problem of radar signal waveform design under the small signal power conditions for detecting a doubly spread target, whose impulse response can be modeled as a random process, in a colored noise environment. The doubly spread target spans multiple range bins (range-spread) and its impulse response is time-varying due to fluctuation (hence also Doppler-spread), such that the target impulse response is both time-selective and frequency-selective. Instead of adopting the conventional assumption that the target is wide-sense stationary uncorrelated scattering,we assume that the target impulse response is both wide-sense stationary in range and in time to account for the possible correlation between the impulse responses corresponding to close range intervals. The locally most powerful detector, which is asymptotically optimal for small signal cases, is then derived for detecting such targets. The signal waveform is optimized to maximizing the detection performance of the detector or equivalently maximizing the Kullback-Leibler divergence. Numerical simulations validate the effectiveness of the proposed waveform design for the small signal power conditions and performance of optimum waveform design are shown in comparison to the frequency modulated waveform.

This research emphasizes a meta-heuristic Modified Ant Lion Optimizer (MALO) optimization approach for simultaneous utilization of DSTATCOM devices and distributed Photovoltaic (PV) sources with network reconfiguration in a radial power distribution scheme. In a radial power distribution network with network reconfiguration majority of the research is based on Constant Power model analysis. However, it is noticed that load models have a substantial impact on the distributed PV sources and the D-STATCOM device's optimal size and position. The effect of the Constant Power (CP) and Polynomial (ZIP) with load growth load models for the simultaneous insertion of distributed PV sources and DSTATCOM devices with network reconfiguration examined in this research work for power system planning. The penetration levels of distributed PV sources considered for the investigation are 25%, 50%, 75%, and 100%. The principal objective of this research is to reduce network total power losses, enhance the voltage magnitude profile at all buses, and reduce the overall operating cost while adhering to equality and inequality constraints. The proposed algorithm verified on 118-node test systems. The investigation is carried out for planning network upgradation to a High Voltage Distribution System(HVDS) on 317 nodes in the rural Bangalore Electricity Supply Company Limited(BESCOM) radial distribution scheme. Simulated results obtained by this method are validated with the BAT algorithm and available techniques in the literature.

Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. So, this paper proposes a two-level strategy involving feature extraction and selection methods before the classification step. The feature extraction step utilizes Short Term Fourier Transform (STFT), and the feature selection step employs Particle Swarm Optimization (PSO) and Harmonic Search (HS) metaheuristic methods. The classifiers employed are Non-Linear Regression, Gaussian Mixture Model, Softmax Discriminant, Naive Bayes, SVM (Linear), SVM (Polynomial), and SVM (RBF). The two-level extracted relevant features are compared with raw data classification results, including Convolutional Neural Network (CNN) Methodology. Among the methods, STFT with PSO feature selection and SVM (RBF) classifier produced the highest accuracy of 94.47%.

Untargeted and targeted approaches are the traditional metabolomics workflows acquired for a wider understanding of the metabolome under focus. Both approaches have their strengths and weaknesses. The untargeted, for example, is maximizing the detection and accurate identification of thousands of metabolites, while the targeted is maximizing the linear dynamic range and quantification sensitivity. These workflows, however, are acquired separately, so researchers compromise either a low-accuracy overview of total molecular changes (i.e., untargeted analysis) or a detailed yet blinkered snapshot of a selected group of metabolites (i.e., targeted analysis) by selecting one of the workflows over the other. In this review, we present a novel single injection simultaneous quantitation and discovery (SQUAD) metabolomics that combines targeted and untargeted workflows. It is used to identify and accurately quantify a targeted set of metabolites. It also allows data retro-mining to look for global metabolic changes that were not part of the original focus. This offers a way to strike the balance between targeted and untargeted approaches in one single experiment and address the two’s limitations. This simultaneous acquisition of hypothesis-led and discovery-led datasets allows scientists to gain more knowledge about biological systems in a single experiment.

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

This study was conducted to search for green technology that can extract metabolites from neem leaves for use in the development of botanical pesticide against Bactrocera dorsalis (Hendel) (Diptera:Tephritidae). Rice wine, rice wash, vinegar and distilled water were used as solvents and hot infusion, maceration, hot continuous reflux (Soxhlet), and fermentation were the methods employed. The different leaf extracts prepared by green technology were evaluated for their potentials as pesticide against B. dorsalis. Vinegar extract via Soxhlet extraction (V-S) for eight (8) h registered to have the highest mortality but not significantly different from vinegar - fermentation (V-F), rice wash - Soxhlet (RWa-S), vinegar - maceration (V-M), distilled water - fermentation (DW-F), and rice wash - fermentation (RWa-F) extracts. Phythochemicals present in the extracts are affected by the solvent-extraction interaction. Among the sixteen solvent-extraction interactions, the use of rice wash and fermentation is the most economical method in extracting the extracting the active components of neem leaves against B. dorsalis. Rice wash is a waste that can be utilized in the development of a biopesticide from neem leaves for pest management of B. dorsalis. This is the first report that rice wash is used as extracting solvent in green synthesis.

Dairy cattle predicted by genomic breeding values to be heat tolerant are known to have less milk production decline and lower core body temperature increases in response to elevated temperatures. In a study conducted at the University of Melbourne’s Dookie Robotic Dairy Farm during summer, we identified the most 20 heat-susceptible and 20 heat-tolerant cows in a herd of 150 Holstein Friesian lactating cows based on their phenotypic responses (changes in respiration rate, surface body temperature, panting score, and milk production). Hair samples were collected from the tip of the cows' tail following standard genotyping protocols. The results indicated variation in feed saved and HT genomic estimated breeding values (GEBVs) (P≤0.05) across age, indicating a potential for their selection. As expected, the thermotolerant group had higher GEBVs for HT and feed saved but lower for milk production. In general, younger cows had superior GEBVs for Balanced Performance Index (BPI), Type Weighted Index (TWI) and Australian Selection Index (ASI), whilst older cows were superior in fertility, feed saved (FS) and HT. The study demonstrated highly significant (P≤ 0.001) negative correlations (-0.28 to -0.74) between HT and GEBVs for current Australian Dairy cattle selection indices (BPI, TWI, ASI, HWI) and significant (P≤ 0.05) positive correlations between HT and GEBVs for traits like FS (0.45) and fertility (0.25). Genomic selection for HT will help improve cow efficiency and sustainability of dairy production under hot summer conditions. However, a more extensive study involving more lactating cows across multiple farms is recommended to confirm the associations between the phenotypic predictors of HT and GEBVs.

A New monogalactosyldiacylglycerol (MGDG), a known monogalactosylmonoacylglycerol (MGMG) and a known polyunsaturated fatty acid methyl ester (PUFAME) were isolated from the marine dinoflagellate Karenia mikimotoi. The planar structure of the glycolipids was elucidated using MS and NMR spectroscopic analyses and comparisons to the known glycolipid to confirm its structure. The isolation of PUFAME strongly supports the polyunsaturated fatty acid fragment of these glycolipids. The relative configuration of the sugar was deduced by comparisons of 3JHH values and proton chemical shifts with those of known glycolipids. All isolated compounds MGDG, MGMG and PUFAME (1-3) were evaluated for their antimicrobial and anti-inflammatory activity. All compounds modulated macrophage responses, with compound 3 exhibiting the greatest anti-inflammatory activity.

Despite well-documented health benefits of probiotics Saccharomyces, its application in oral health has not been comprehensively assessed. Dental caries is a transmissible disease initiated by acid production of cariogenic bacteria and yeast, such as Streptococcus mutans and Candida albicans, on tooth enamel and followed by subsequent enamel demineralization. Here, we investigated the effect of two Saccharomyces strains (Saccharomyces boulardii, Saccharomyces cerevisiae) on S. mutans-C. albicans cross-kingdom interactions using a cariogenic planktonic model. Viable cells, pH changes and gene expression were measured. S. cerevisiae and S. boulardii inhibited the growth of C. albicans either in dual-, or multi-species conditions. Saccharomyces also inhibited C. albicans hyphal formation. Furthermore, Saccharomyces reduced the acidity of the culture medium which usually plummeted below pH 5 when S. mutans and C. albicans were present in the model. The presence of Saccharomyces maintained the culture medium above 6 even after overnight incubation, demonstrating a protective potential against dental enamel demineralization. S. boulardii significantly downregulated S. mutans atpD and eno genes expression. Overall, our results shed light on a new promising candidate, Saccharomyces, for dental caries prevention due to its potential to create a less cariogenic environment marked by a neutral pH and reduced growth of C. albicans.

The oral administration of (R)-3-hydroxybutyl-(R)-3-hydroxybutyrate, allows inducing a beneficial level of blood ketone bodies without the adverse effects due to the adhesion to a ketogenic diet. Several studies documented the therapeutic effectiveness of the (R)-3-hydroxybutyl (R)-3-hydroxybutyrate in treating neurodegenerative diseases as well as its boosting activity of athletic and cognitive performances during prolonged physical exercises. Further studies considering this ketone body ester for therapy of other pathologies are also underway. In the present work, we describe the synthesis of (R)-3-hydroxybutyl-(R)-3-hydroxybutyrate through the enantioselective transesterification of racemic ethyl 3-hydroxybutyrate with (R)-1,3-butanediol catalyzed by immobilized Candida antarctica lipase B (CAL-B). The enantiopure (R)-1,3-butanediol was in turn obtained from the kinetic resolution of the racemate by CAL-B catalyzed acetylation with vinyl acetate. The economy of the synthetic procedure has been improved by recycling the unreacted (S) enantiomers of the ethyl 3-hydroxybutyrate and 1,3-buatnediol after stereochemical inversion achieved by tosylation and SN2 with ammonium acetate. The overall procedure allows to incorporate up to 70% of the starting racemic reagents into the final product.

The COVID-19 pandemic has posed a significant threat to society in recent times, endangering human health, life, and economic well-being. The disease spreads quickly due to the highly infectious SARS-CoV-2 virus, which has undergone numerous mutations. Despite intense research efforts by the scientific community since its emergence in 2019, no effective therapeutics have been discovered yet. While some repurposed drugs have been used to control the global outbreak and save lives, none have proven universally effective, particularly for severely infected patients. Although the spread of the disease is generally under control, anti-SARS-CoV-2 agents are still needed to combat current and future infections. This study reviews some of the most promising repurposed drugs containing indolyl heterocycle, which is an essential scaffold of many alkaloids with diverse bio-properties in various biological fields. The study also discusses natural and synthetic indole-containing compounds with anti-SARS-CoV-2 properties, as well as computer-aided drug design (in-silico studies) for optimizing anti-SARS-CoV-2 hits/leads.

Antimicrobial peptides (AMPs) are essential components of the innate immune system, present across a spectrum of organisms. Their versatility lies in their ability to effectively inhibit a wide range of pathogens including bacteria, fungi, parasites, and viruses. As the challenge of antibiotic resistance escalates and concerns surrounding antibiotic use grow, AMPs have emerged as promising alternatives. Their applications span diverse domains such as medicine, agriculture, food production, animal husbandry, and aquaculture, primarily due to their efficacy against resistant pathogens, signifying their crucial role in combating infections. Beyond their antimicrobial properties, research illuminates their intricate involvement in the immune response network. These peptides impact crucial processes including cytokine release, chemotaxis, wound healing, angiogenesis and the activation of the adaptive immune system. This comprehensive review delves into the multifaceted realm of AMPs, encompassing their classification, varied applications across industries and notably, their significance in diverse disease conditions like infections, skin diseases, cancer, oral diseases, lung diseases and cardiovascular ailments. Special attention is directed towards current advancements in clinical applications of peptide-based therapeutics, offering invaluable insights into their potential future integration within clinical settings.

Abstract: Agroforestry has a sustainable attributes with both tangible and nontangible benefits. In this study carbon mitigation and credits potential of traditional agroforestry systems at different elevations were evaluated. These traditional systems are: Agrihortisilviculture system (AHS), Agrihorticulture system (AH) and Agrisilviculture system (AS). Stand density, living biomass carbon and soil carbon were measured in each sample plot. The results were that stand density of woody perennials varied from 61 to 233 tree ha-1 across t elevations and systems, and , Grewia oppositifoila was the predominant tree species occupying most of the agroforestry land use system. Plant and soil organic carbon were significantly different (P ≤ 0.05) among systems and elevations. Total carbon including plant and soil was significantly higher in the AH system at upper elevations. Total carbon emmision mitigation varied with changing elevations and systems, being highest at lower elevation with AHS system. The total carbon credits was also recorded high at lower elevation, whereas the total value of C credits was higher at mid elevation due to the estimated agroforestry area. The total value of C credits from all agroforestry systems was observed (128977.59 €) of the study area.

Cross coupling reactions have changed the way complex molecules are synthesized. In particular, Suzuki-Miyaura and Buchwald-Hartwig amination reactions have given opportunities to elegantly make pharmaceutical ingredients. Indeed, these reactions are forefront at both the stages of drug development, medicinal chemistry, and process chemistry. On one hand, these reactions have given medicinal chemists a tool to derivatize the core molecule to arrive at scaffold rapidly. On the other hand, these cross couplings have offered the process chemists a smart tool to synthesize the development candidates safely, quickly, and efficiently. Generally, the application of cross coupling reactions is broad, and this review will specifically focus on their real (pharma) world applications in large scale synthesis those appeared in last two years.

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

Oral Squamous Cell Carcinoma is one among the most common cancer and early detection is the main key to avoid deaths. Automated diagnostic tools that process the histopathological images of a patient to detect abnormal oral lesions will be very much useful for the clinicians. A deep learning framework have been designed with an intermediate layer between feature extraction layers and classification layers for classifying the histopathological images into two categories, namely normal and oral squamous cell carcinoma. The intermediate layer is constructed using the proposed Swarm Intelligence technique called Modified Gorilla Troops Optimizer. Various optimization algorithms are implemented in literature for optimal parameter identification, weights updating and feature selection in deep learning models, but this work focuses on usage of optimization algorithm as intermediate layer that transforms the extracted features into the features that are more suitable for classification. Three datasets totally comprising 2784 normal and 3632 oral squamous cell carcinoma subjects are considered in this work. Three popular CNN architectures namely InceptionV2, MobileNetV3, and EfficientNetB3 are investigated as feature extraction layers. Two fully connected Neural Network layers along with batch normalization and dropout are used as classification layers. Among the investigated feature extraction models, MobileNetV3 performs well in all the three datasets with the highest accuracy of 0.89. Usage of the proposed Modified Gorilla Troops Optimizer as an intermediate layer boosts this accuracy to 0.95.

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.

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.

With widespread resistance to a limited number of insecticides available for medical and veterinary pests, new insecticides and insecticide synergists are desperately needed in this market space. We assessed the topical toxicity of carvone, menthone, and fenchone compared to permethrin and methomyl against the yellow fever mosquito, Aedes aegypti, and the house fly, Musca domestica. We also evaluated the synergistic potential of the monoterpenoids with permethrin and methomyl. Additionally, we assessed the acetylcholinesterase inhibitory potential of each monoterpenoid compared to methomyl. While all three monoterpenoids performed relatively poorly as topical insecticides (LD50 > 4000 ng/mg on M. domestica; > 6000 ng/mg on Ae. aegypti), they synergized both permethrin and methomyl as well as or better than piperonyl butoxide (PBO). Carvone and menthone yielded synergistic co-toxicity factors (23 and 29, respectively), which were each higher than PBO at 24 h. Acetylcholinesterase inhibition did not appear to explain the toxic or synergistic effects of the three monoterpenoids with IC50 values greater than 1 mM for all, compared to the 2.5 and 1.7 µM for methomyl on Aedes aegypti and Musca domestica, respectively. This study provides valuable monoterpenoid toxicity and synergism data on two pestiferous insects and highlights potential for these chemistries in future pest control formulations.

We show that low quality of all 427 Brazilian SARS-CoV-2 genomes recently published in Science (1) challenges their phylogenetic inference and may lead to incorrect typing of viral strains in clades with no statistical support. Absence of basecalling quality in genome assemblies and proper phylogeny parameter estimates preclude the assessment of signal-to-noise ratio in the data, downstream analysis and conclusions.

Acne vulgaris is a chronic skin disease, which occurs due to inflammation of the hair follicles and sebum producing (sebaceous) glands of the skin called pilosebaceous unit and the anaerobic propionic acne bacterium, P.acne. Human sebum is dominantly made up of 57.5% of triglycerides and fatty acids, 26%wax esters, 12% Squalene and 4.5% Cholesterol. The increased level Androgen hormone, sebum lipid composition, P.acne over growth which induces monocytes and pro inflammatory cytokines attracts neutrophils, basophils, and T cells to the pilosebaceous unit and drive epithelial hyper proliferation i.e., Acne vulgaris. The actual biomolecular changes due to acne vulgaris disease are present in the blood, in the sebum, and in the noninvasive sample of human scalp hair follicles. The main objectives of the present study are to analyze human scalp hair follicles samples using FTIR-ATR spectroscopy to compare and discriminate the spectral signatures of acne vulgaris and healthy scalp hair tissue samples through acne biomarkers Protein, Amide I, Amide II and Squalene (LDL), using the method of internal ratio parameters. This work represents a first step in the development of an analytical tool for future drug development.

Weed seedbank is an indication of future weed infestation potential of the species and is essential for making strategic planning for its sustainable management. Parthenium weed (Parthenium hysterophorus L.) is an invasive alien species threatening the biodiversity and the environment in Malaysia. A study was, therefore, conducted to estimate the soil seedbank of the weed at four soil depths of four villages of Kuala Muda, Kedah. The aim was to indicate the critical s of parthenium weed seedbank in Malaysia. Soil samples were collected from the sites using a soil core. The seeds were extracted from the soil samples with sieve shaker at the Universiti Malaysia Kelantan laboratory, Jeli Campus. The study indicates that the weed seedbank is in critical level at the area. The highest number of weed seeds (6915/m2) was found in Kg. Kongsi 6, followed by Kg. Sungai Tok Rawang (4481 seeds/m2). The top layer of soil, 0-5 cm, contained the maximum number of weed seeds (4878 seeds/m2) and a significant number of seeds (316 seeds/m2) were noticed at 10-15 cm soil depth. The study suggests the Malaysian government to take immediate action to control parthenium weed seedbank of the sites.

Molecular overtone transitions provide optical frequency transitions sensitive to variation in the proton-to-electron mass ratio (μ = m_p/m_e). However, robust molecular state preparation presents a challenge critical for achieving high precision. Here, we characterize infrared and optical-frequency broadband laser cooling schemes for TeH⁺, a species with multiple electronic transitions amenable to sustained laser control. Using rate equations to simulate laser cooling population dynamics, we estimate the fractional sensitivity to μ attainable using TeH⁺. We find that laser cooling of TeH⁺ can lead to significant improvements on current μ variation limits.

In this paper, we established the existence of PC-mild solutions for non local fractional impulsive functional integro-differential equations with finite delay. The proofs are obtained by using the techniques of fixed point theorems, semi-group theory and generalized Bellman inequality. In this paper, we have used the distributed characteristic operators to define the mild solution of the system. Results obtained here improve and extend some known results.

The future of the Colorado River water supply (WS) affects millions of people and the U.S. economy. A recent study suggested a cross-basin correlation between the Colorado River and its neighboring Great Salt Lake (GSL). Following that study, the feasibility of using the previously developed multi-year prediction of the GSL water level to forecast the Colorado River WS was tested. Time-series models were developed to predict the changes in WS out to 10 years. Regressive methods and the GSL water level data were used for the depiction of decadal variability of the Colorado River WS. Various time-series models suggest a decline in the 10-year-averaged WS since 2013 before starting to increase around 2020. Comparison between this WS prediction and the WS projection published in a 2012 government report (derived from climate models) reveals a widened imbalance between supply and demand by 2020. Further research to update similar multi-year prediction of the Colorado River WS is needed. Such information could aid in management decision making in the face of future water shortages.

Renal angiogram is a promising tool for diagnosing renal vasculature and structural alterations in renal diseases. In renal diseases, the vascular changes were observed earlier than the structural and other changes. However, the literature on angiograms in kidney diseases was limited. Six client-owned dogs with chronic kidney diseases with International Renal Interest Society (IRIS) stage II and III were selected for this study. Under general anesthesia, the femoral arterial catheterization was performed. With a Cobra (C2) catheter, Iohexol saline (50:50) was administered to evaluate the vascular changes of Renal failure, using selective and non-selective angiograms. The procedures were completed successfully with minimal complications. Serum biochemistry and urine protein creatinine ratio were estimated sequentially and quality of life was monitored. Due to contrast agent complications, a dog died within 14 days and necropsy was conducted. Though the renal angiogram has complications, it is a reliable tool for the diagnosis of vasculature changes associated with kidney diseases, in veterinary medicine.

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.

(R)-(+)-3,5-Dinitro-N-(1-phenylethyl)benzothioamide 1 is a potential chiral solvating agent (CSA) for the spectral resolution of enantiomers by 1H NMR spectroscopy. The single enantiomer of 1 was synthesized from commercially (R)-(+)-a-methylbenzylamine 2 in two-steps with 85% yield.

We study certain function algebras and their operator algebra completions on r-discrete abelian groupoids, the corresponding conditional expectations, maximal abelian subalgebras (masa) and eigen-functionals.

Products derived from Cannabis sativa have gained increased interest and popularity. As these products become common amongst the public, the heath and potential therapeutic values associated with hemp have become a premier focus of research. While the psychoactive and medicinal properties of Cannabis products have been extensively highlighted in literature, the antibacterial properties of CBD have not been explored in depth. This research serves to examine the antibacterial potential of CBD against Salmonella newington and Salmonella typhimurium. In this study we observed bacterial response to CBD exposure through biological assays, bacterial kinetics, and fluorescence microscopy. Additionally, comparative studies between CBD and ampicillin were conducted against Salmonella typhimurium and Salmonella newington to determine comparative efficacy. Furthermore, we observed potential resistance development of our Salmonella spp. against CBD treatment.

Coal combustion in thermal power plants releases ash. Ash is reported to cause different adverse health hazards in humans and other organisms. Owing to the presence of radionuclides, it is also considered as a potential radiation hazard. In this study, based on the surface radiation measurements and relevant ancillary data, expected radiation risk zones were identified with regard to the human population residing near the Thermal Power Plant. With population density as the risk determining criteria, about 20% of the study area was at ‘High’ risk and another 20% of the study area was at ‘Low’ risk zone. The remaining 60% was under medium risk zone. Based on the findings remedial measures which may be adopted have been suggested.

A study on the selection of hyperelastic constitutive model for polymeric materials is performed using a hybrid experimental-computational approach. Bis-GMA polymer is used as a case study of hyperelastic material to describe the polymer characteristics by determining its Poisson’s ratio and its valid range of the hyperelastic stress-strain curves. These two parameters are then used to determine the hyperelastic constitutive model by using the hybrid approach. Several uniaxial compression tests along with their finite element simulations are implemented in a systematic way, to identify the polymer behavior under the compressive loading conditions. Nano-indentation experiments are conducted to verify the hyperelastic behavior of the polymer. The experimental and computational evidences confirm that the Poisson’s ratio of Bis-GMA is 0.40 and the appropriate hyperelastic constitutive model for this polymer is of a second order polynomial. It is shown that, the results can be used to determine the true stress-strain curve of hyperelastic materials.

The present Feature Paper highlights the application of bacterial surface (S-) layer proteins as versatile components for the fabrication of biosensors. One technologically relevant feature of S‑layer proteins is their ability to self-assemble on many surfaces and interfaces to form a crystalline 2D protein lattice. The S-layer lattice on the surface of a biosensor becomes part of the interface architecture, linking the bioreceptor to the transducer interface, which may cause signal amplification. The S-layer lattice as ultrathin, highly porous structure with functional groups in a well-defined special distribution and orientation and an overall anti-fouling characteristics can significantly raise the limit in terms of variety and ease of bioreceptor immobilization, compactness of bioreceptor molecule arrangement, sensitivity, specificity, and detection limit for many types of biosensors. The present paper discusses and summarizes examples for the successful implementation of S-layer lattices on biosensor surfaces in order to give a comprehensive overview on the application potential of these bioinspired S-layer protein-based biosensors.

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.

This paper presents a script that classify spatial patterns of residential urban growth using a morpho-structural approach. The script performs a combination of variography analysis and morphological closings over buildings possessing a residential function in 2002 and 2017 within a region located in southern France named Centre-Var. The different bounding regions then allow classifying new residential buildings into different categories according to their degrees of clustering/scattering and to their locations regarding existing urban areas. Preliminary results show that this protocol is able to provide useful insights regarding the degree of contribution of each new residential building to different patterns of urban growth (clustered infill, scattered infill, clustered edge-expansion, scattered edge-expansion, clustered leapfrog and scattered leapfrog). Open-access to the script and to the test region data is provided.

In this paper we propose a computational framework that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large number of mechanistic models in SBML that are currently stored in public databases. With the proposed framework, existing SBML mechanistic models may be upgraded to hybrid systems through the incorporation of deep neural networks into the model core, using a freely available python tool. The so-formed hybrid mechanistic/neural network models are trained with a deep learning algorithm based on the adaptive moment estimation method (ADAM), stochastic regularization and semidirect sensitivity equations. The trained hybrid models are encoded in SBML and stored back in model databases, where they can be further analyzed as regular SBML models. The application of this approach is illustrated with three well-known case studies: the threonine synthesis model in Escherichia coli, the P58IPK signal transduction model, and the Yeast glycolytic oscillations model. The proposed framework is expected to greatly facilitate the widespread use of hybrid modeling techniques for systems biology applications.

Recent evidence suggests the existence of shared neural resources for rhythm processing in language and music. Such overlaps could be the basis of the facilitating effect of regular musical rhythm on spoken word processing previously reported for typical children and adults, as well as adults with Parkinson’s disease and children with developmental language disorders. The present study builds upon these previous findings by examining whether musical rhythmic priming also influences visual word processing, and the extent to which such cross-modal priming effect of rhythm is related to individual differences in musical aptitude and reading skills. EEG was recorded while participants listened to a rhythmic tone prime, followed by a visual target word with a stress pattern that either matched or mismatched the rhythmic structure of the auditory prime. Participants were also administered standardized assessments of musical aptitude and reading achievement. ERPs elicited by target words with a mismatching stress pattern showed an increased fronto-central negativity. Additionally, the size of the negative effect correlated with individual differences in musical rhythm aptitude and reading comprehension skills. Results support the existence of shared neurocognitive resources for linguistic and musical rhythm processing, and have important implications for the use of rhythm-based activities for reading interventions.

The article describes facile one-pot, hi-yielding reactions to synthesize substituted 3,4-dimethyl-1H-pyrrole-2-carboxamide (3a–m) and carbohydrazide analogues (5a–l) as potential antifungal and antimicrobial agents. The structural integrity and purity of the synthesized compounds were assigned based on appropriate spectroscopic techniques. Synthesized compounds were assessed in vitro for antifungal and antibacterial activity. The compound 5h, 5i and 5j were found to be the most potent against A. fumigatus, with MIC value of 0.031 mg/mL. The compound 5f bearing a 2,6-dichloro group on the phenyl ring was found to be the most active broad spectrum antibacterial agent with MIC value of 0.039 mg/mL. The mode of action of the most promising antifungal compounds (one representative from each series; 3j and 5h) was established by their molecular docking to the active site of sterol 14α-demethylase. Molecular docking studies revealed a highly spontaneous binding ability of the tested compounds in the access channel away from catalytic heme iron of the enzyme, which suggested that the tested compounds inhibit this enzyme and would avoid heme iron related deleterious side effects observed with existing antifungal compounds.

Now-a-days, the thrust area of materials’ research is to develop multifunctional materials, which have multiple properties in a single functional material. We are interested to develop multifunctional polysilanes having special functional properties such as optical activity and photoluminescence (PL) properties. In this investigation, poly(methyl phenyl silane) (PMPS) was integrated with a chiral unit and a photoactive unit by in situ photopolymerization of (R)-N-(1-phenyl ethyl) methacrylamide (R-NPEMAM) and disperse red 1 methacrylate (DR1MA) monomer in the presence of PMPS. PMPS acted as a macrophotoinitiator and by UV exposure it produced macroradicals which initiated polymerization of chiral and photoactive monomers. Thus a block copolymer of PMPS-b-(R-NPEMAM-ran-DR1MA) was synthesized.The synthesized multifunctional organic inorganic hybrid polymer samples were characterized by FTIR and NMR spectroscopy. The molecular weights of the samples were measured by GPC analysis. The optical, chiroptical and photoluminescence properties were studied. The narrow band at about 1638 cm^-1 is due to C=O stretching vibration of -CONH- of the chiral unit. A wide absorption peaks at 3444 cm^-1 is the characteristic of NH trans stretching vibration of secondary amide group. The asymmetric stretching of NO₂ group appeared at 1481 cm^-1 and the characteristic peak at 1427 cm^-1 was observed due to azo (-N=N-) group stretching of DR1MA unit. The Si-Si band of PMPS appeared at about 462 cm^-1 in FTIR spectra. The optical absorbance observed at 272 nm is due to π-π* transition of aromatic ring and at 330 nm corresponds to σ-σ* transition of Si-Si bond. The other electronic absorption observed in the visible region at 475 nm corresponds to the combined contribution of n-π* and π-π* transition of DR1MA unit. The photoluminescence properties of such polymers were studied for the variation of concentration of the polymer solution and variation with excitation energy such as 275 nm, 325 nm and 475 nm in THF solvent. Such synthesized multifunctional photoactive organic-inorganic polymers having unusual optical, chiroptical and photoluminescence property may find novel optoelectronic (friend foe identification and secretive code identification) applications.

Within the eastern part of the Black Sea and Sea of Azov, the vegetation of charophytes was studied using the Brown-Blanquet approach. For the first time, five communities are described, including three associations and two subassociations from the alliance Charion canescentis Krausch 1964, the order Charetalia intermediae Sauer 1937, and the class Charetea intermediae F. Fukarek 1961. Diagnoses of the described syntaxa are given. A comparison with the Baltic and Mediterranean communities of charophytes is made. It is shown that all the Azov-Black Sea communities with the dominance of charophytes, in contrast to Western European ones, include Lamprothamnium papulosum with high constancy. At the same time, the communities of the southern seas of Russia are characterized by a lower occurrence and abundance of higher aquatic plants (except for Nanozostera noltei) and a slightly higher occurrence of red and green algae. An indirect ordination analysis showed the ecological isolation of the described phytocenoses and revealed two main factors influencing the floristic composition of communities – the granulometric composition of bottom sediments and water eutrophication.

The recent legalization of Cannabis sativa L. in many regions has revealed a need for effective propagation and biotechnologies for the species. Micropropagation affords researchers and producers methods to rapidly propagate insect/disease/virus free clonal plants, store germplasm, and forms the basis for other biotechnologies. Despite this need, research in the area is limited due to the long history or prohibitions and restrictions. Existing literature has multiple limitation: many publications use hemp as a proxy for drug-type Cannabis when it is well established that there is significant genotype specificity, studies using drug-type cultivars are predominantly op-timized using a single cultivar, most protocols have not been replicated by independent groups, and some attempts demonstrate a lack of reproducibility across genotypes. Due to culture decline and other problems the multiplication phase of micropropagation (stage 2) has not been fully developed in many reports. This review will provide a brief background on the history and botany of Cannabis as well as a comprehensive and critical summary of Cannabis tissue culture. Special attention will be paid to current challenges faced by researchers, the limitations of existing Cannabis micropropagation studies, and recent developments and future directions of Cannabis tissue culture technologies.

Let R be a commutative graded ring with unity, S be a multiplicative subset of homogeneous elements of R and P be a graded ideal of R such that P\bigcap S=\emptyset In this article, we introduce several results concerning graded S-prime ideals. Then we introduce the concept of graded weakly S-prime ideals which is a generalization of graded weakly prime ideals. We say that P is a graded weakly S-prime ideal of R if there exists s\in S such that for all x, y\in h(R), if 0\neq xy\in P, then sx\in P or sy\in P. We show that graded weakly S-prime ideals have many acquaintance properties to these of graded weakly prime ideals.

Three soybean field trials were conducted in Indiana to evaluate the integration of seed treatment, cultivar selection, and seeding rate on sudden death syndrome (SDS) root infection, foliar symptoms, yield and net return. Two soybean cultivars, one moderately resistant and one susceptible to SDS were planted at three seeding rates (272,277 seeds/ha, 346,535 seeds/ha, and 420,792 seeds/ha). Fluopyram and pydiflumetofen seed treatments were applied to both cultivars and were compared to a control. Low foliar SDS disease pressure was observed in our study. Seed treatment of either fluopyram or pydiflumetofen, and use of a moderately resistant cultivar decreased root infection relative to the control and the use of a susceptible cultivar. Fluopyram significantly reduced root rot severity by 8.8% and increased yield by 105 kg/ha relative to the control, but was not different from pydiflumetofen. However, pydiflumetofen performed the same as the control with respect to root rot severity and yield. Findings from this study support the use of a seed treatment to protect roots from infection and the use of a moderately resistant cultivar planted at a seeding rate of 346,535 seeds/ha to protect yield and maximize on net returns when a field has low foliar SDS pressure.

Since the 1980s, a growing interest in goat milk was noticed due to the nutritional values and health benefits of this milk, which resulted in increasing goat populations and milk production worldwide. This comprehensive review elaborates on goat milk composition compared to other types of milk. It is also an overview of goat milk production, properties, nourishment-value, applications in dairy products, and potential health benefits. Goat milk composition and its characteristics are slightly different from other types of milk and can be utilized to manufacture many dairy products. Fresh goat milk and goat milk products (e.g., yogurt and kefir were found to provide various potential health benefits, such as anti-inflammatory, prevent cardiovascular disease, anti-diabetic and antihypertensive, strengthen bones, boost immunity, and improve metabolism.

An accurate outbreak prediction of COVID-19 can successfully help to get insight into the spread and consequences of infectious diseases. Recently, machine learning (ML) based prediction models have been successfully employed for the prediction of the disease outbreak. The present study aimed to engage an artificial neural network-integrated by grey wolf optimizer for COVID-19 outbreak predictions by employing the Global dataset. Training and testing processes have been performed by time-series data related to January 22 to September 15, 2020 and validation has been performed by time-series data related to September 16 to October 15, 2020. Results have been evaluated by employing mean absolute percentage error (MAPE) and correlation coefficient (r) values. ANN-GWO provided a MAPE of 6.23, 13.15 and 11.4% for training, testing and validating phases, respectively. According to the results, the developed model could successfully cope with the prediction task.

Gold nanoclusters (AuNCs) with fluorescence in the Near Infrared (NIR) by both one- and two-photon electronic excitation were incorporated in mesoporous silica nanoparticles (MSNs) using a novel one-pot synthesis procedure where the condensation polymerization of alkoxysilane monomers in the presence of the AuNCs and a surfactant produce hybrid MSNs of 49 nm diameter. This method was further developed to prepare 30 nm diameter nanocomposite particles with simultaneous NIR fluorescence and superparamagnetic properties, with a core composed of superparamagnetic manganese ferrite nanoparticles (MnFe2O4) coated with a thin silica layer, and a shell of mesoporous silica decorated with AuNCs. The nanocomposite particles feature NIR-photoluminescence with 0.6% quantum yield and large Stokes shift (290 nm), and superparamagnetic response at 300 K, with a saturation magnetization of 13.4 emu g-1. The conjugation of NIR photoluminescence and superparamagnetic properties in the biocompatible nanocomposite has high potential for application in multimodal bioimaging.

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.

Single image deraining (SID) has shown its importance in many advanced computer vision tasks. Though many CNN based image deraining methods have been proposed, how to effectively remove raindrops while maintaining background structure remains a challenge that needs to be overcome. Most of the deraining work focuses on removing rain streaks, but in heavy rain images, the dense accumulation of rainwater or the rain curtain effect significantly interferes with the effective removal of rain streaks, and often introduces some artifacts that make the scene more blurry. In this paper, we propose a new network structure R-PReNet for single image deraining with good background structure maintaining. This framework fully utilizes the cyclic recursive structure of PReNet. Moreover, we introduce residual channel prior (RCP) and feature fusion modules for better deraining performance by focusing on background feature information. Compared with the previous methods, our method has significantly improvement effect on the rainstorm image with the artifacts removing and good visual detail restoring.

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

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.

We explored the statistics of filtering of simple patterns on a number of deterministic and random graphs as a tractable simple example of information processing in complex systems. In this problem, multiple inputs map to the same output, and the statistics of filtering is represented by the distribution of this degeneracy. For a few simple filter patterns on a ring we obtained an exact solution of the problem and described numerically more difficult filter setups. For each of the filter patterns and networks we found a few numbers essentially describing the statistics of filtering and compared them for different networks. Our results for networks with diverse architectures appear to be essentially determined by two factors: whether the graphs structure is deterministic or random, and the vertex degree. We find that filtering in random graphs produces a much richer statistics than in deterministic graphs. This statistical richness is reduced by increasing the graph’s degree.

Rifampicin is one of the most important chemotherapeutic agents used in the treatment of tuberculosis. M. tuberculosis clinical strains resistant to rifampicin harbor mainly mutation in an 81-base pair region of rpoB. These mutations mainly consist of single amino acid substitutions. However insertions also can be related with rifampicin resistance strains. Herein, we described an insertion of 12 nucleotides in clinical isolates of M. tuberculosis resistant to rifampicin, all obtained from inmates. To evaluate the importance this insertion in surviving and drug resistance, it were carried out fitness experimental assays as well as in silico studies of 3D structural models, molecular docking simulations and virtual screening. The medical records of the seven patients showed all were previously treated to tuberculosis. Growth curves shown that the insertion determines a biological cost when compared to wild type rpoB and katG; or the double mutated rpoB S531L and katG S315T. From docking and molecular dynamics simulations it can be inferred that the insertion does not affect the process of synthesis of RNA transcripts. On the other hand, in the mutant RNAP-RIF complex rifampicin confirmed a low affinity interaction for the mutant form. Interesting, virtual screening for potential inhibitors for wtRNAP and mRNAP using a library of 1446 compounds approved by the FDA showed that the best ligands were mainly compounds with antibiotic activity, although the targets involved in the pharmacological action are other than RNAP. In conclusion, seven strains of M. tuberculosis RIF resistant that present an insertion of four amino acids in RNA polymerase showed by growth curve assays, a biological cost. Further, bioinformatics tools had characterized the putative drug resistance dynamic as well as the maintenance of RNA polymerase activity.

Castor oil may be differentiated from other non-edible vegetable oils because of its main composition of hydroxylated fatty acids. Ricinoleic acid comprises 80–90% wt. of fatty acids in castor oil (Ricinus communis). In this study, the thermo-oxidative stability and tribological behavior of bio-based lubricant samples synthesized from castor oil using isoamyl alcohol were evaluated. Initially, the compositional and physicochemical properties of the obtained samples were assessed using 1H NMR, FTIR, and ASTM methods. Oxidative stability of the samples was evaluated using Rancimat method at 110 °C under air flow. The final biolubricant sample (BL2), obtained after esterification, epoxidation, and oxirane rings opening reactions, presented an oxidation stability time (OST) of 14.3 h. The thermal stability was also evaluated by thermogravimetry (TG) from the mass variations under inert and oxidative atmosphere. BL2 showed higher thermal stability compared to the other samples, demonstrating higher decomposition temperatures in both inert (339.04 °C) and oxidative (338.47 °C) atmospheres, for a mass loss of 50%. The tribological properties of the samples were evaluated using a four-ball tribometer configuration. The BL1 and BL2 samples exhibited lower friction coefficients than the mineral oil sample (MOS) by 21.5% and 43.1%, respectively. Regarding wear, the observed wear scar diameter (WSD) was also lower in BL1 and BL2 compared to MOS by 5.2% and 40.4%, respectively. The results of the tribological evaluation suggest that both samples obtained in this study have promising potential for applications in lubricating machines and mechanical systems.

Vertically aligned Fe, S, and Fe-S doped anatase TiO₂ nanotube arrays are prepared by electrochemical anodization process using an organic electrolyte in which lactic acid is added as an additive. In the electrolyte, nanotube layers of greater length (12 μm) and high order with inner diameter of approx. 90 nm and outer diameter of approx. 170 nm are achieved. Doping of Fe, S, and Fe-S via simple wet impregnation method substituted Ti and O sites with Fe and S, which leads to enhance the rate performance at high discharge current densities. Discharge capacities of TiO₂ tubes increased from 82 mAh g-1 (bare) to 165 mAh g-1 for Fe-S doped TiO₂ at high current densities of 0.3 mAcm-2 after 100 cycles with exceptional capacity retention of 85% after 100 cycles. Owing to the enhancement of thermodynamic and kinetic properties by doping of Fe-S, Li-diffusion increas2ed resulting in remarkable discharge capacities of 143 mAh g-1 and 89 mAh g-1 at a current density of 7.4 mA cm-2 and 19 mA cm-2, respectively.

Planning and implementation of construction projects are difficult processes and are burdened with many risk elements. The budget spread over time, which is developed on the basis of the schedule, presents the expected distribution of costs throughout the duration of the works, which during the implementation of the project is subject to constant changes resulting from time, cost and organizational factors. Managing construction contracts requires managers to be able to analyze on an ongoing basis the variances of production costs - from the values calculated in the offer cost estimate and assumed in the Budgeted Cost of Work Scheduled. The article attempts to analyze the emerging time and cost variances using proprietary C-S and S-C monitoring, based on simple indicators of the EVM method. An example of construction of a multi-family housing development was used to study the variances of planned and incurred costs.

Mycobacterium tuberculosis is a leading cause of human mortality worldwide and the emergence of drug-resistantstrains, demands the discovery of new classes of antimycobacterials that can be employed in the therapeutic pipeline. Previously, a secondary metabolite Chrysomycin A, isolated from Streptomyces sp. OA161 was shown to have potent bactericidal activity against drug-resistant clinical isolates of M. tuberculosis and different species of mycobacteria. The antibiotic inhibits the mycobacterial topoisomerase I and DNA gyrase leading to bacterial death, but the mechanisms that could cause resistance are currently unknown. To further understand the resistance mechanism, spontaneous resistance mutants were isolated and subjected to whole-genome sequencing. Mutation in a Tet^R family transcriptional regulator MSMEG_1380 was identified in the resistant isolates and was close to an operon encoding membrane protein MSMEG_1381 and MSMEG_1382. Sequence analysis and modeling studies indicated that they are components of the Mmp family of efflux pumps and over-expression of either the operon or individual genes conferred resistance to chrysomycin A, isoniazid, and ethambutol that are in TB therapy. Our study highlights the role of membrane transporter proteins in conferring multiple drug resistance and the utility of recombinant strains overexpressing membrane transporters in the drug screening pipeline.

The current work addresses the control of two-input two-output (TITO) Wood and Berry model of a binary distillation column. The controller design problem is formulated in terms of multivariable H_∞ control synthesis. The controller structure takes the form of simplest static output feedback (SOF) control. The controller synthesis is performed using a hybrid approach of blending linear matrix inequalities (LMI) and genetic algorithm (GA). The performance of the static output feedback controller is compared with three other controllers designed for Wood and Berry model available in the literature. The first simulation study is performed for the case of tracking a unit step command in the presence of a step change in output disturbance. A second simulation study is performed for rejecting a change in sinusoidal output disturbance.

In this study, the pristine MgO, MgO/CNT and Ni-MgO/CNT nanocomposites were processed by the impregnation and chemical vapour deposition methods and analyzed for hydrogen evolution (HER) via electrochemical water splitting process. Furthermore, effect of nickel on the deposited carbon was systematically elaborated in this study. The highly conductive carbon nanotubes (CNTs) deposited on the metal surface of the Ni-MgO nanocomposite heterostructure provides the robust stability and superior electrocatalytic activity. The optimized Ni-MgO/CNT nanocomposite exhibited hierarchical helical-shaped carbon nanotubes adorned on the surface of the Ni-MgO flakes, forming a hybrid metal-carbon network structure. The HER catalytic reaction was carried out in 1M alkaline KOH electrolyte, and the optimized Ni-MgO/CNT nanocomposite achieves the low 117 mV overpotential value (ɳ) at the 10 mA cm-2 and needs low 116 mV/dec Tafel value denoted Volmer-Heyrovsky pathway. Also, high electrochemical active surface area (ECSA) value of Ni-MgO/CNT nanocomposite acquires 515 cm2, which is favorable for the generation of abundant electro-active species and the prepared electrocatalyst durability was also performed by chronoamperometry test for prolonged duration of 20 h at 10 mA cm-2 and exhibits the good stability with 72% retention. Hence, obtained results demonstrated that the optimized Ni-MgO/CNT nanocomposite is highly active and cost-effective electrocatalyst towards hydrogen energy production.

Aphelids are a holomycotan group, represented exclusively by parasitoids infecting algae. They form a sister lineage to Fungi in the phylogenetic tree and represent a key group for reconstruction of the evolution of Holomycota and for analysis of the origin of Fungi. The newly assembled genome of Aphelidium insullamus (Holomycota, Aphelida) with a total length of 18.9Mb, 7820 protein-coding genes and a GC percentage of 52.05% was obtained by a hybrid assembly based on Oxford Nanopore long reads and Illumina paired reads. In order to trace the origin and the evolution of fungal osmotrophy and its presence or absence in Aphelida, we analyzed the set of main fungal transmembrane transporters, which are proteins of the Major Facilitator superfamily (MFS), in the predicted aphelid proteomes. This search has shown an absence of a specific fungal protein family Drug:H+ antiporters-2 (DAH-2) and specific fungal orthologs of the sugar porters (SP) family, and the presence of common opisthokont's orthologs of the SP family in four aphelid genomes. The repertoire of SP orthologs in aphelids turned out to be less diverse than in free-living opisthokonts, and one of the most limited among opisthokonts. We argue that aphelids do not show signs of similarity with fungi in terms of their osmotrophic abilities, despite the sister relationships of these groups. Moreover, the osmotrophic abilities of aphelids appear to be reduced in comparison with free-living unicellular opisthokonts. Therefore, we assume that the evolution of fungi-specific traits began after the separation of fungal and aphelid lineages, and there are no essential reasons to consider aphelids as a prototype of the fungal ancestor.

Combustion parameters are the important aspects in the development and research of an internal combustion engines. Hence present work is an attempt to develop an artificial neural network (ANN) model for anticipating the combustion characteristics of computerized CI DI VCR, four strokes, single cylinder, and water cooled engine using mixture of two biodiesel and diesel blends as a fuel. The two biodiesel selected are Jatropha and Simarouba and mixed in the ratio of 75:25. Two biodiesel mixtures is used for the preparation of various blends with diesel. Experiments are carried out at different compression ratio, at different % load and blends B20, B40, B60and neat diesel (B00) fuel to accumulate the assorted combustion data. The input variables are % load, compression ratio, blends and crank angle. The outputs well thought-out are cylinder pressure (CP), net heat release rate (NHRR), cumulative heat release (CHR), rate of pressure rise (RPR), mass fraction burned (MFB) and maximum cylinder pressure. The assessment is focused on developing artificial neural network for the prediction and verifying the combustion characteristics of engine. MATLAB software is used for analysis of different combustion aspects of the engine. Multilayer neural network perceptions are used with Feed-Forward Back Propagation algorithm with performance function for mapping the input and output parameters. The experimental outcomes are compared with ANN estimated results for the analysis. The outcome from the study authenticate that experimental results are in match with ANN results. The accuracy of the ANN model shows the developed model can effectively predict the engine combustion characteristics with excellent regression coefficients ‘R’ and its values are close to unity and the mean square errors are extremely less. ANN model approach is competent towards predicting the combustion aspect of diesel engine with good accuracy

Nanoporous films of Eu-doped organosilicate glass (OSG) have been synthesized using sol-gel technology and spin-coating, employing evaporation-induced self-assembly (EISA), on silicon wafers. The Eu doping is achieved by dissolution of Eu(NO3)3·6H2O in the precursor solution. The deposited films are characterized by using Fourier transform infrared (FTIR) spectroscopy, ellipsometric porosimetry (EP), X-ray photoelectron spectroscopy (XPS) and photoluminescence spectroscopy. It is observed that Eu doping makes the films more hydrophilic and reduces the pore size and open porosity. The reduction Eu3+ → Eu2+ occurs in the pores of OSG films, which is confirmed by depth profiling XPS. However, Eu3+ still presents on the film’s top surface. Presence of Eu3+ and Eu2+ gives characteristic luminescence emission in the range of 600‒630 nm (Eu3+) and 290‒400 nm (Eu2+). The Eu2+/Eu3+ concentrations ratio depends on CH3 groups concentration in the films. Moreover, concentration of Eu2+ ions in the pores can be reduced by exposure in inductively coupled (ICP) oxygen plasma. The observed shift of the luminescence spectra towards the UV region, in comparison to previously reported Eu-doped organosilicate films, can be attributed to the energy transfer occurring between the host material and Eu2+ ions.

We report on the occurrence of natural Magnesium Alumina Silicate Hydrate (M-(A)-S-H) cement at Feragen and Leka in eastern and western Trøndelag Norway, respectively. Both occurrences are located in the sub-arctic climate zone and form in glacial till and moraine material deposited on ultramafic rock during the Weichselian glaciation. Weathering of serpentinized peridotite dissolve brucite and result in a relative high pH alkaline fluid that subsequently reacts with the felsic minerals of the till (quartz, plagioclase, K-feldspar) to form a cement consisting of an amorphous material or a mixture of nanocrystalline Mg-rich phyllosilicates, including illite. The presence of plagioclase in the till results in the enrichment of alumina in the cement, i.e., forms M-A-S-H instead of the M-S-H cement. Dissolution of quartz results in numerous etch-pits and negative quartz crystals filled with M-A-S-H cement. Where the quartz dissolution is faster that the cement precipitation, a honeycomb-like texture is formed. Compositionally the cemented till (tillite) contains more MgO and has a higher loss of ignition than the till, suggesting that the cement is formed by a MgO fluid that previously reacted with the peridotite. The M-(A)-S-H cemented till represent a new type of duricrust, coined magsilcrete. The study of natural Mg-cement provides information on peridotites as a Mg-source for Mg-cement and as a feedstock for CO2 sequestration.

Erythropoietin (EPO) protects cells by inhibiting apoptosis, oxidative stress and inflammation in several models of retinal degeneration. In this study, we demonstrate the effects of recombinant Adeno Associated Virus (AAV) vector-mediated delivery of a modified form of erythropoietin (EPO-R76E) in an established mouse model of dry-AMD in which retinal degeneration is induced by RPE oxidative stress. Experimental vector AAV-EPO-R76E and control vector AAV-GFP were packaged into serotype-1 (AAV1) to enable RPE selective expression. RPE oxidative stress-mediated retinal degeneration was induced by exon specific deletion of the protective enzyme MnSOD (encoded by Sod2) by cre/lox mechanism. Experimental mice received subretinal injection of AAV-EPO-R76E in the right eye and AAV-GFP in the left eye. Western blotting of RPE/Choroid protein samples from AAV-EPO-R76E injected eyes showed RPE specific exogenous protein expression. Retinal degeneration was monitored by electroretinography (ERG). EPO-R76E over-expression in RPE delayed the progressive retinal degeneration as measured by light microscopy in RPE specific Sod2 knockout mice. Delivery of EPO-R76E vector can be used as a tool to prevent retinal degeneration induced by RPE oxidative stress as seen in this mouse model.

Excess alcohol consumption is a top risk factor for death and disability. Fatty liver will likely develop and the risk of liver disease increases. We have previously demonstrated that an essential amino acid supplement (EAAS) improved protein synthesis and reduced intrahepatic lipid in the elderly. The purpose of this study was to further evaluate the influence of EAAS on intrahepatic lipid (IHL), body composition, and blood lipids in individuals with mild to moderate alcohol use disorder (AUD). Following consent, determination of eligibility, and medical screening, 25 participants (18 males at 38±15 years/age and 7 females at 34±18 years/age) were enrolled and randomly assigned to one of two dosages: a low dose (LD: 8 grams of EAAS twice/day (BID)) or high dose (HD: 13 grams of EAAS BID). Both groups consumed the supplement for 4 weeks. Pre- and post-EAAS administration, IHL was determined using magnetic resonance imaging/spectroscopy, body composition was analyzed using dual energy x-ray absorptiometry, and blood parameters were measured by LabCorp. T-tests were used for statistical analysis and considered significant at P<0.05. While there was no significant change in IHL in the LD group, there was a significant 23% reduction in IHL in the HD group (p=0.02). Fat mass, lean tissue mass, bone mineral content, and blood lipids were not altered. Post-EAAS phosphatidylethanol was elevated and remained unchanged in LD at 407±141 ng/ml and HD at 429±196 ng/ml, indicating chronic and excess alcohol consumption. Based on these results, we conclude that 13 grams of proprietary EAAS consumed BID lowers IHL in individuals with mild to moderate AUD.

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.

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.

We analyse recent contradictory results and conclusions about the spectrum of the screened Coulomb potential $V(r)=-r^{-1}e^{-C/r}$. The well known Hellmann-Feynman theorem shows that all the bound states of the Coulomb potential ($C=0$) remain bounded as $C$ increases. We derive a simple approximate analytical expression for the eigenvalues for sufficiently small values of the screening parameter $C$ and an approximate asymptotic expression for the asymptotic behaviour of the s-state eigenvalues when $C\rightarrow \infty $. Present results are expected to resolve the discrepancy about the spectrum of the quantum-mechanical model just mentioned.

A locally-rotationally-symmetric Bianchi-I model filled with strange quark matter (SQM) is explored in f(R, T) gravity. We take f(R, T) = R + 2 f(T) = R + 2λT, where R is the Ricci scalar, T is the trace of energy-momentum tensor and λ is an arbitrary constant. Exact solutions are obtained by assuming that the expansion scalar is proportional to the shear scalar. This yields a constant value for the deceleration parameter, q = 2, which corresponds to the decelerated phase of the universe. The model is found to be physically viable for λ < −1. SQM during early evolution mimics ultra-relativistic radiation whereas at late times, it behaves as dust, quintessence or even the cosmological constant depending on the value of λ. The effective matter acts as a stiff fluid irrespective of the matter content and of the f(R, T) terms. The model is shear free at late times but remains anisotropic throughout the evolution. In the absence of the f(R, T) terms, SQM accelerates the universe. In the specific case when SQM vanishes at late times, the effect of f(R, T) is to accelerate the universe. The model admits the possibility that SQM could be an alternative to dark energy.

Polyhedral oligomeric silsesquioxane (POSS) is a suitable nanoscale reinforcement for thermosetting polymers, such as epoxy resin systems in order to modify its mechanical, thermal, and chemical properties. The inclusion of POSS in the epoxy resin at higher loading (greater than 1 wt.%), however, introduces the ductility during the fracture behavior of these nanocomposites. Consequently, the J-integral is used to quantify the fracture behavior of these materials and characterize the crack growth resistance curve against stable crack growth. A range of nanocomposites is prepared by adding 0.5, 1, 3, 5, and 8 wt.% of glycidyl POSS into DGEBF epoxy resin cured with an amine-based curing agent. From the fracture toughness experiment the load-displacement result confirms that when the POSS reinforcement is greater than 1 wt.%, the fracture behavior of the nanocomposite changes from brittle to ductile. For both brittle and ductile nanocomposites, the addition of POSS molecules improves the crack initiation toughness. The development of POSS–POSS compliant domains are reported previously, is attributed for this change in the failure behavior. The fractured images of POSS–epoxy nanocomposites, obtained using scanning electron microscopy, show that the increase in fracture resistance at higher values of POSS loading occurs due to the extensive shear yielding. Meanwhile, the increased fracture toughness at lower values of POSS loading occurs due to crack pinning and crack deflection.

We obtain exact solutions to the field equations for 5 dimensional LRS Bianchi type-I spacetime in $f(R,T)$ theory of gravity where specifically the following three cases are considered: (i) $f(R,T)=\mu(R+T)$, (ii) $f(R,T)=R \mu + R T \mu^2$ and (iii) $f(R,T)=R+\mu R^2+\mu T$ where $R$ and $T$ respectively the Ricci scalar and trace of the energy-momentum tensor. It is found that the equation of state (EOS) parameter $w$ is governed by the parameter $\mu$ involved in the $f(R,T)$ expressions. We fine-tune the parameter $\mu$ to obtain effect of phantom energy in the model, however we also restrict this parameter to obtain a stable model of the universe. It is noted that the model isotropizes at finite cosmic time.

In this paper, we introduce a new generalization of the r-Stirling numbers of the second kind based on the q-numbers via an exponential generating function. We investigate their some properties and derive several relations among q-Bernoulli numbers and polynomials, and newly de…ned (q, r, w)-Stirling numbers of the second kind. We also obtain q-Bernstein polynomials as a linear combination of (q, r, w)-Stirling numbers of the second kind and q-Bernoulli polynomials in w.

This paper proposes a model to evaluate business projects to get into an incubator, allowing to rank them in order of selection priority. The model combines the Momentum method to build prospective scenarios and the Multiple Criteria Decision Making (MCDM) method TOPSIS-2N to rank the alternatives. Six business projects were evaluated to be incubated. The Momentum method made it possible for us to create an initial core of criteria for the evaluation of incubation projects. The TOPSIS-2N method supported the decision to choose the company to be incubated by ranking the alternatives in order of relevance. Our evaluation model has improved the existing models used by incubators. This model can be used and / or adapted by any incubator to evaluate the business projects to be incubated. The set of criteria for the evaluation of incubation projects is original and the use of prospective scenarios with a MCDM method to evaluate companies to be incubated does not exist in the literature.

Vitamin D, unlike the micronutrients, vitamins A, E and K, is largely obtained, not from food, but by the action of solar UV light on its precursor, 7-dehydrocholesterol, in skin. With the decline in UV light intensity in winter, most skin production of vitamin D occurs in summer. Because no defined storage organ or tissue has been found for vitamin D, it has been assumed that adequate vitamin D status in winter can only be maintained by oral supplementation. Skeletal muscle cells have now been shown to incorporate the vitamin D-binding protein (DBP) from blood into the cell cytoplasm where it binds to cytoplasmic actin. This intracellular DBP provides an array of specific binding sites for 25-hydroxyvitamin D (25(OH)D) which diffuses into the cell from the extracellular fluid. When intracellular DBP undergoes proteolytic breakdown, the bound 25(OH)D is then released and diffuses back into blood. This uptake and release of 25(OH)D by muscle, accounts for the very long half-life of this metabolite in the circulation. As 25(OH)D concentration in blood declines in winter, its cycling in and out of muscle cells appears to be upregulated. Parathyroid hormone is the most likely factor enhancing the repeated cycling of 25(OH)D between skeletal muscle and blood. This mechanism appears to have evolved to maintain adequate vitamin D status in winter.

Vitamin D, unlike the micronutrients, vitamins A, E and K, is largely obtained, not from food, but by the action of solar UV light on its precursor, 7-dehydrocholesterol, in skin. With the decline in UV light intensity in winter, most skin production of vitamin D occurs in summer. Because no defined storage organ or tissue has been found for vitamin D, it has been assumed that adequate vitamin D status in winter can only be maintained by oral supplementation. Skeletal muscle cells have now been shown to incorporate the vitamin D-binding protein (DBP) from blood into the cell cytoplasm where it binds to cytoplasmic actin. This intracellular DBP provides an array of specific binding sites for 25-hydroxyvitamin D (25(OH)D) which diffuses into the cell from the extracellular fluid. When intracellular DBP undergoes proteolytic breakdown, the bound 25(OH)D is then released and diffuses back into blood. This uptake and release of 25(OH)D by muscle, accounts for the very long half-life of this metabolite in the circulation. As 25(OH)D concentration in blood declines in winter, its cycling in and out of muscle cells appears to be upregulated. Parathyroid hormone is the most likely factor enhancing the repeated cycling of 25(OH)D between skeletal muscle and blood. This mechanism appears to have evolved to maintain adequate vitamin D status in winter.

A wideband antenna with excellent efficiency is the most important requirement of wireless communication. There are many ways to improve the antenna bandwidth, such as using a low permittivity substrate, increasing the substrate thickness, and using different shapes of radiating patches. However, this cannot achieve wideband. This problem can be solved by using a metamaterial-based microstrip antenna that can achieve wideband. The proposed patch antenna has a metamaterial unit cell loaded on the top patch and on the bottom ground plane. The top unit cell, which consists of a square loop with Complementary Split Ring Resonator (CSRR) and the bottom unit cell, which is a Square Shaped Cross-Slot (SSCS), is loaded on the patch and ground. The objective is to achieve a compact metamaterial-loaded antenna with enhanced radiation characteristics and to design a metamaterial antenna for wideband applications. The wideband and high gain features of the proposed antenna make it suitable for 5G NR FR1 and Wi-Fi 6E applications.

Design and advancement of the durable urban train infrastructures are of utmost importance for reliable mobility in the smart cities of the future. Given the importance of urban train lines, tunnels, and subway stations, these structures should be meticulously analyzed. In this research, two-dimensional modeling and analysis of the soil-structure mass of the Alan Dasht station of Mashhad Urban Train are studied. The two-dimensional modeling was conducted using Hashash’s method and displacement interaction. After calculating the free-field resonance and side distortion of the soil mass, this resonance was entered into PLAXIS finite element program, and finally, stress and displacement contours together with the bending moment, shear force and axial force curves of the structure were obtained.

Carbon supported nanoparticles of monometallic Ni catalyst and binary Ni-Transition Metal (Ni-TM/C) electrocatalytic composites were synthesized via chemical reduction method, where TM stands for the doping elements Fe, Co, and Cu. The chemical composition, structure and morphology of the Ni-TM/C materials were characterized by X-ray photoelectron spectroscopy (XPS), X-ray diffractometry (XRD), transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM) and energy-dispersive X-ray spectroscopy (EDS). The electrochemical properties towards hydrogen oxidation reaction in alkaline medium were studied using the rotating disc electrode and cycling voltammetry methods. A significant role of the TM dopant in the promotion of the hydrogen electrooxidation kinetics of the binary Ni-TM/C materials were revealed. A record-high in exchange current density value of 0.060 mA cm²_Ni was measured for Ni₃Fe₁/C, whereas the monometallic Ni/C counterpart has only shown 0.039 mA cm²_Ni. In order to predict the feasibility of the electrocatalysts for hydrogen chemisorption, density functional theory was applied to calculate the hydrogen binding energy and hydroxide binding energy values for bare Ni and Ni₃TM₁.