Discrete Variations Research Articles

Brightening and Fading in the Youngest Galactic Supernova Remnant G1.9+0.3: 13 Years of Monitoring with the Chandra X-Ray Observatory

We report 13 years of Chandra monitoring of the youngest Galactic supernova remnant G1.9+0.3, the only remnant known to be increasing in brightness. We confirm the spatially integrated rate of flux increase of (1.2 ± 0.2)% yr−1 (1–7 keV), but find large spatial variations, from −3% yr−1 to +7% yr−1, over length scales as small as 10″ or smaller. We observe relatively little change in spectral slope, though one region shows significant hardening as it brightens by 1% yr−1. Such rates of change can be accommodated by any of several explanations, including steady blast-wave evolution, expansion or compression of discrete plasma blobs, magnetic turbulence, or variations in magnetic-field aspect angle. Our results do not constrain the mean magnetic-field strength, but a self-consistent picture can be produced in which the maximum particle energies are limited by the remnant age (applying both to electrons and to ions) to about 20 TeV, and the remnant-averaged magnetic-field strength is about 30 μG. The deceleration parameter m (average shock radius varying as t m ) is about 0.7, consistent with estimates from overall expansion dynamics and confirming an explosion date of about 1900 CE. Shock-efficiency factors ϵ e and ϵ B (fractions of shock energy in relativistic electrons and magnetic field) are 0.003 and 0.0002 in this picture. However, the large range of rates of brightness change indicates that such a global model is oversimplified. Temporal variations of photon index, expected to be small but measurable with longer time baselines, can discriminate among possible models.

The transcriptomic and spatial organization of telencephalic GABAergic neuronal types.

The telencephalon of the mammalian brain comprises multiple regions and circuit pathways that play adaptive and integrative roles in a variety of brain functions. There is a wide array of GABAergic neurons in the telencephalon; they play a multitude of circuit functions, and dysfunction of these neurons has been implicated in diverse brain disorders. In this study, we conducted a systematic and in-depth analysis of the transcriptomic and spatial organization of GABAergic neuronal types in all regions of the mouse telencephalon and their developmental origins. This was accomplished by utilizing 611,423 single-cell transcriptomes from the comprehensive and high-resolution transcriptomic and spatial cell type atlas for the adult whole mouse brain we have generated, supplemented with an additional single-cell RNA-sequencing dataset containing 99,438 high-quality single-cell transcriptomes collected from the pre- and postnatal developing mouse brain. We present a hierarchically organized adult telencephalic GABAergic neuronal cell type taxonomy of 7 classes, 52 subclasses, 284 supertypes, and 1,051 clusters, as well as a corresponding developmental taxonomy of 450 clusters across different ages. Detailed charting efforts reveal extraordinary complexity where relationships among cell types reflect both spatial locations and developmental origins. Transcriptomically and developmentally related cell types can often be found in distant and diverse brain regions indicating that long-distance migration and dispersion is a common characteristic of nearly all classes of telencephalic GABAergic neurons. Additionally, we find various spatial dimensions of both discrete and continuous variations among related cell types that are correlated with gene expression gradients. Lastly, we find that cortical, striatal and some pallidal GABAergic neurons undergo extensive postnatal diversification, whereas septal and most pallidal GABAergic neuronal types emerge simultaneously during the embryonic stage with limited postnatal diversification. Overall, the telencephalic GABAergic cell type taxonomy can serve as a foundational reference for molecular, structural and functional studies of cell types and circuits by the entire community.

Single-cell transcriptomics reveals tumor microenvironment remodeling in hepatocellular carcinoma with varying tumor subclonal complexity.

The complexity of tumor cell subclonal structure has been extensively investigated in hepatocellular carcinoma. However, the role of subclonal complexity in reshaping the tumor microenvironment (TME) remains poorly understood. We integrated single-cell transcriptome sequencing data from four independent HCC cohorts, involving 30 samples, to decode the associations between tumor subclonal complexity and the TME. We proposed a robust metric to accurately quantify the degree of subclonal complexity for each sample based on discrete copy number variations (CNVs) profiles. We found that tumor cells in the high-complexity group originated from the cell lineage with FGB overexpression and exhibited high levels of transcription factors associated with poor survival. In contrast, tumor cells in low-complexity patients showed activation of more hallmark signaling pathways, more active cell-cell communications within the TME and a higher immune activation status. Additionally, cytokines signaling activity analysis suggested a link between HMGB1 expressed by a specific endothelial subtype and T cell proliferation. Our study sheds light on the intricate relationship between the complexity of subclonal structure and the TME, offering novel insights into potential therapeutic targets for HCC.

The Application of Fluorescence Anisotropy for Viscosity Measurements of Small Volume Biological Analytes.

Time-resolved fluorescence anisotropy has been extensively used to detect changes in bimolecular rotation associated with viscosity levels within cells and other solutions. Physiological alterations of the viscosity of biological fluids have been associated with numerous pathological causes. This current work serves as proof of concept for a method to measure viscosity changes in small analyte volumes representative of biological fluids. The fluorophores used in this study were fluorescein disodium salt and Enhanced Green Fluorescent Protein (EGFP). To assess the ability of the method to accurately detect viscosity values in small volume samples, we conducted measurements with 12 μL and 100 μL samples. No statistically significant changes in determined viscosities were recorded as a function of sample volume for either fluorescent probe. The anisotropy of both fluorescence probes was measured in low viscosity standards ranging from 1.02 to 1.31 cP, representative of physiological fluid values, and showed increasing rotational correlation times in response to increasing viscosity. We also showed that smaller fluid volumes can be diluted to accommodate available cuvette volume requirements without a loss in the accuracy of detecting discrete viscosity variations. Moreover, the ability of this technique to detect subtle viscosity changes in complex fluids similar to physiological ones was assessed by using fetal bovine serum (FBS) containing samples. The presence of FBS in the analytes did not alter the viscosity specific rotational correlation time of EGFP, indicating that this probe does not interact with the tested analyte components and is able to accurately reflect sample viscosity. We also showed that freeze-thaw cycles, reflective of the temperature-dependent processes that biological samples of interest could undergo from the time of collection to analyses, did not impact the viscosity measurements' accuracy. Overall, our data highlight the feasibility of using time-resolved fluorescence anisotropy for precise viscosity measurements in biological samples. This finding is relevant as it could potentially expand the use of this technique for in vitro diagnostic systems.

Day-Ahead Electricity Market Price Forecasting Considering the Components of the Electricity Market Price; Using Demand Decomposition, Fuel Cost, and the Kernel Density Estimation

This paper aims to improve the forecasting of electricity market prices by incorporating the characteristics of electricity market prices that are discretely affected by the fuel cost per unit, the unit generation cost of the large-scale generators, and the demand. In this paper, two new techniques are introduced. The first technique applies feature generation to the label and forecasts the transformed new variables, which are then post-processed by inverse transformation, considering the characteristic of the fuel types of marginal generators or prices through two variables: fuel cost per unit by the representative fuel type and argument of the maximum of Probability Density Function (PDF) calculated by Kernel Density Estimation (KDE) from the previous price. The second technique applies decomposition to the demand, followed by a feature selection process to apply the major decomposed feature. It is verified using gain or SHapley Additive exPlanations (SHAP) value in the feature selection process. In the case study, both showed improvement in all indicators. In the Korean Electricity Market, the unit generation cost for each generator is calculated monthly, resulting in a step-wise change in the electricity market price depending on the monthly fuel cost. Feature generation using the fuel cost per unit improved the forecasting by eliminating monthly volatility caused by the fuel costs and reducing the error that occurs at the beginning of the month. It improved the Mean Squared Percentage Error (MAPE) of 3.83[%]. Using the argument of the maximum PDF calculated by KDE improved the forecasting during the test period, where discrete monthly variations were not included. The resulting MAPE was 3.82[%]. Combining these two techniques resulted in the most accurate performance compared to the other techniques used, which had a MAPE of 3.49[%]. The MAPE of the forecasting with the decomposed data of the original price was 4.41[%].

Alteration of Community Metabolism by Prebiotics and Medicinal Herbs.

Several studies have examined the impact of prebiotics on gut microbiota and associated changes in host physiology. Here, we used the in vitro cultivation of human fecal samples stimulated with a series of chemically related prebiotics and medicinal herbs commonly used in Ayurvedic medicine, followed by 16S rRNA sequencing. We applied a genome-wide metabolic reconstruction of enumerated communities to compare and contrast the structural and functional impact of prebiotics and medicinal herbs. In doings so, we examined the relationships between discrete variations in sugar composition and sugar linkages associated with each prebiotic to drive changes in microbiota composition. The restructuring of microbial communities with glycan substrates alters community metabolism and its potential impact on host physiology. We analyzed sugar fermentation pathways and products predicted to be formed and prebiotic-induced changes in vitamin and amino acid biosynthesis and degradation. These results highlight the utility of combining a genome-wide metabolic reconstruction methodology with 16S rRNA sequence-based community profiles to provide insights pertaining to community metabolism. This process also provides a rational means for prioritizing in vivo analysis of prebiotics and medicinal herbs in vivo to test hypotheses related to therapeutic potential in specific diseases of interest.

Nonlocal Perimeters and Curvature Flows on Graphs with Applications in Image Processing and High-Dimensional Data Classification

In this paper, we revisit the notion of perimeter on graphs, introduced in El Chakik, Elmoataz, and Desquesnes [Signal Process., 105 (2014), pp. 449–463], and we extend it to so-called inner and outer perimeters. We will also extend the notion of total variation on graphs. Thanks to the co-area formula, we show that discrete total variations can be expressed through these perimeters. Then, we propose a novel class of curvature operators on graphs that unifies both local and nonlocal mean curvature on an Euclidean domain. This leads us to translate and adapt the notion of the mean curvature flow on graphs as well as the level set mean curvature, which can be seen as approximate schemes. Finally, we exemplify the usefulness of these methods in image processing, 3D point cloud processing, and high dimensional data classification.

Assessing the Bioenergy Potential of Novel Non-Edible Biomass Resources via Ultrastructural Analysis of Seed Sculpturing Using Microscopic Imaging Visualization

Recently, intensifying energy crises accompanying ecological crises due to the decline in fossil-fuel reserves and extensive greenhouse gas emissions have triggered the exploration of renewable substitutes for petro-diesel. In this scenario, biodiesel is the best alternative to non-renewable finite conventional fuels due to its cost-effectiveness, sustainability, renewability, biodegradability, and eco-friendly nature. Hence, the current research was designed to utilize scanning electron microscopy to investigate and identify the micro-morphological characteristics of selected seed-bearing crops. Light-microscopy (LM) indicated discrete variations in macro-morphological characters such as seed shape (ovoid, ovate, oblong, semi-spheroid, or discoid), seed size (3.5–14 mm in length and 2.25 to 6.5 mm in width), seed color (yellow to black), and number of seeds per kilogram (from 6000 to 260,000). Chemical extraction via Soxhlet apparatus resulted in the estimation of oil content within the range of 20.3–48.0% (wt./wt.), FFA content (0.63–6.91 mg KOH/g), and maximum product, i.e., 98% biodiesel yield was achieved. Multivariate analysis via principal component analysis (PCA) was done using PAST 3 software to investigate similarities and differences among factors/variables. SEM examination exhibited ultra-morphological characters and distinct variation in cell-wall ornamentation; hilum occurrence, position, and level; wall-sculpturing variations such as ruminate, verrucate, wrinkled, or striate; cell arrangement (anticlinal or periclinal); and cell shape and margins. To conclude, SEM could be an advanced technique to disclose the ultra-micromorphological characteristics of oil-bearing energy crops providing a convenient way for scientists to determine correct identification, authentication, and classification.

Effects of graphene oxide and reduced graphene oxide nanomaterials on porcine endothelial progenitor cells.

Graphene oxide (GO) and reduced graphene oxide (rGO) have been widely used in the field of tissue regeneration and various biomedical applications. In order to use these nanomaterials in organisms, it is imperative to possess an understanding of their impact on different cell types. Due to the potential of these nanomaterials to enter the bloodstream, interact with the endothelium and accumulate within diverse tissues, it is highly relevant to probe them when in contact with the cellular components of the vascular system. Endothelial progenitor cells (EPCs), involved in blood vessel formation, have great potential for tissue engineering and offer great advantages to study the possible angiogenic effects of biomaterials. Vascular endothelial growth factor (VEGF) induces angiogenesis and regulates vascular permeability, mainly activating VEGFR2 on endothelial cells. The effects of GO and two types of reduced GO, obtained after vacuum-assisted thermal treatment for 15 min (rGO15) and 30 min (rGO30), on porcine endothelial progenitor cells (EPCs) functionality were assessed by analyzing the nanomaterial intracellular uptake, reactive oxygen species (ROS) production and VEGFR2 expression by EPCs. The results evidence that short annealing (15 and 30 minutes) at 200 °C of GO resulted in the mitigation of both the increased ROS production and decline in VEGFR2 expression of EPCs upon GO exposure. Interestingly, after 72 hours of exposure to rGO30, VEGFR2 was higher than in the control culture, suggesting an early angiogenic potential of rGO30. The present work reveals that discrete variations in the reduction of GO may significantly affect the response of porcine endothelial progenitor cells.

High-resolution 3D mapping of cold-water coral reefs using machine learning

Structure-from-Motion (SfM) photogrammetry is a time and cost-effective method for high-resolution 3D mapping of cold-water corals (CWC) reefs and deep-water environments. The accurate classification and analysis of marine habitats in 3D provide valuable information for the development of management strategies for large areas at various spatial and temporal scales. Given the amount of data derived from SfM data sources such as Remotely-Operated Vehicles (ROV), there is an increasing need to advance towards automatic and semiautomatic classification approaches. However, the lack of training data, benchmark datasets for CWC environments and processing resources are a bottleneck for the development of classification frameworks. In this study, machine learning (ML) methods and SfM-derived 3D data were combined to develop a novel multiclass classification workflow for CWC reefs in deep-water environments. The Piddington Mound area, southwest of Ireland, was selected for 3D reconstruction from high-definition video data acquired with an ROV. Six ML algorithms, namely: Support Vector Machines, Random Forests, Gradient Boosting Trees, k-Nearest Neighbours, Logistic Regression and Multilayer Perceptron, were trained in two datasets of different sizes (1,000 samples and 10,000 samples) in order to evaluate accuracy variation between approaches in relation to the number of samples. The Piddington Mound was classified into four classes: live coral framework, dead coral framework, coral rubble and sediment and dropstones. Parameter optimisation was performed with grid search and cross-validation. Run times were measured to evaluate the trade-off between processing time and accuracy. In total, eighteen variations of ML algorithms were created and tested. The results show that four algorithms yielded f1-scores >90% and were able to discern between the four classes, especially those with usually similar characteristics, e.g., coral rubble and dead coral. The accuracy variation among them was 3.6% which suggests that they can be used interchangeably depending on the classification task. Furthermore, results on sample size variations show that certain algorithms benefit more from larger datasets whilst others showed discrete accuracy variations (<5%) when trained in datasets of different sizes.

Effect of the region of the CAD/CAM block on the flexural strength and structural reliability of restorative materials

The aim of the study was to evaluate whether the region (internal or external) of the CAD/CAM block influences the mechanical performance of restorative materials. Blocks of different CAD/CAM materials (Composites: KAV – Katana Avencia; LULT – LULT Ultimate; Ceramics: ENAM – Vita Enamic; NICE - N!CE; EMP – IPS Empress CAD; VMII – Vita Mark II; EMAX – IPS e.max CAD) were selected, and direct resin composite blocks (APX - Clearfil AP-X; FSUP - Filtek Supreme) were built using the incremental technique on a mold from one of the CAD/CAM blocks. All blocks were sectioned into bar-shaped specimens (1 × 1 × 14 mm), which were separated into two groups according to the region of the block (inside or outside). 3-point bending tests were performed following ISO 6872:2015 and flexural strength data were analyzed using one-way ANOVA and Bonferroni post-hoc tests (p < 0.05). Weibull module and characteristic strength were also calculated. In general, the mean flexural strength values were not statistically different (p > 0.05) between the inside and outside regions of each material, except for LULT (inside > outside) and EMAX (outside > inside). Comparing the materials, a similar strength (only discrete variations) was observed for inside, outside or merged (inside and outside data assembled together) regions: EMAX > KAV = LULT > NICE = APX > EMP = ENAM = VMII ≥ FSUP (merged condition). Characteristic strength at 63.2% failure probability and at 5% failure probability generally corroborates such observations. There were no statistical differences for Weibull module data (inside, outside, or merged), except for KAV and NICE (outside > inside). Thus, the region from where the restoration is milled within the CAD/CAM block generally does not influence the mechanical performance hereof (flexural strength, failure probability, risk of premature failures, and mechanical reliability) of the material, except for LULT and EMAX.

The Art of Mbira: Musical Inheritance and LegacyMbira's Restless Dance: An Archive of Improvisation, Vols. 1 &amp; 2

The Art of Mbira: Musical Inheritance and LegacyMbira's Restless Dance: An Archive of Improvisation, Vols. 1 &amp; 2

Soil fertility in slash and burn agricultural systems in central Mozambique

Slash and burn is a land use practice widespread all over the world, and nowadays it is formally recognized as the principal livelihood system in rural areas of South America, Asia, and Africa. The practice consists of a land rotation where users cut native or secondary forest to establish a new crop field and, in some cases, build charcoal kilns with the cut wood to produce charcoal. Due to several socio-economic changes in developing countries, some scientists and international organizations have questioned the sustainability of slash and burn since in some cases, crop yield does not justify the soil degradation caused. To estimate the soil quality in agricultural and forest soils at different ages of the forest-fallow period (25, 35, and 50 years), this survey investigated rural areas in three locations in Manica province, central Mozambique: Vanduzi, Sussundenga, and Macate. Soil profiles were trenched and sampled with a pedological approach under crop fields and forest-fallow. The chronosequence was selected to test the hypothesis that the increase in forest-fallow age causes an improvement of soil fertility. Results highlighted discrete variations among locations in mineralogy, Al- and Fe-oxyhydroxides, sand, silt, pH, total organic carbon, humic carbon, total nitrogen, available phosphorous, chloride, nitrate, fluoride, and ammonium. Few differences in mineralogy, Fe-oxyhydroxides, available P, chloride, and nitrate were detected between crop fields and forest-fallow within the same location. Such differences were mostly ascribed to intrinsic fertility inherited from the parent material rather than a longer forest-fallow period. However, physicochemical soil property improvement did not occur under a forest age of 50 years (the longest forest-fallow considered), indicating that harmonization of intrinsic fertility and agronomic practices may increase soil organic matter and nutrient contents more than a long forest-fallow period.

General relativity on the multiverse and nature’s hierarchies

We define ``third-derivative'' general relativity by promoting the integration measure in Einstein-Hilbert action to be an arbitrary 4-form field strength. We project out its local fluctuations by coupling it to another 4-form field strength. This ensures that the gravitational sector contains only the usual massless helicity-2 propagating modes. Adding the charges to these 4-forms allows for discrete variations of the coupling parameters of conventional general relativity: ${G}_{N},\mathrm{\ensuremath{\Lambda}},{H}_{0}$, and even $⟨\mathsf{Higgs}⟩$ are all variables which can change by jumps. Hence, de Sitter spacetime is unstable to membrane nucleation. Using this instability, we explain how the cosmological constant problem can be solved. The scenario utilizes the idea behind the irrational axion, but instead of an axion it requires one more 4-form field strength and corresponding charged membranes. When the membrane charges satisfy the constraint $\frac{2{\ensuremath{\kappa}}_{\mathsf{eff}}^{2}{\ensuremath{\kappa}}^{2}|{\mathcal{Q}}_{i}|}{3{\mathcal{T}}_{i}^{2}}&lt;1$, the theory which ensues exponentially favors a huge hierarchy $\mathrm{\ensuremath{\Lambda}}/{M}_{\mathrm{Pl}}^{4}\ensuremath{\ll}1$ instead of $\mathrm{\ensuremath{\Lambda}}/{M}_{\mathrm{Pl}}^{4}\ensuremath{\simeq}1$. The discharges produce the distribution of the values of $\mathrm{\ensuremath{\Lambda}}$ described by the saddle point approximation of the Euclidean path integral.

Effective Forchheimer Coefficient for Layered Porous Media

Inertial flow in porous media, governed by the Forchheimer equation, is affected by domain heterogeneity at the field scale. We propose a method to derive formulae of the effective Forchheimer coefficient with application to a perfectly stratified medium. Consider uniform flow under a constant pressure gradient Delta P/L in a layered permeability field with a given probability distribution. The local Forchheimer coefficient beta is related to the local permeability k via the relation beta =a/k^c, where a>0 being a constant and cin [0,2]. Under ergodicity, an effective value of beta is derived for flow (i) perpendicular and (ii) parallel to layers. Expressions for effective Forchheimer coefficient, beta _e, generalize previous formulations for discrete permeability variations. Closed-form beta _e expressions are derived for flow perpendicular to layers and under two limit cases, Fll 1 and Fgg 1, for flow parallel to layering, with F a Forchheimer number depending on the pressure gradient. For F of order unity, beta _e is obtained numerically: when realistic values of Delta P/L and a are adopted, beta _e approaches the results valid for the high Forchheimer approximation. Further, beta _{e} increases with heterogeneity, with values always larger than those it would take if the beta - k relationship was applied to the mean permeability; it increases (decreases) with increasing (decreasing) exponent c for flow perpendicular (parallel) to layers. beta _{e} is also moderately sensitive to the permeability distribution, and is larger for the gamma than for the lognormal distribution.

Dynamic Performances of Technological Vibrating Machines

Based on the research carried out within the Research Institute for Construction Equipment and Technology—ICECON S.A. Bucharest, consisting of the design and development of vibrating-action machines and of the technical analysis of optimization of the technological processes with vibrating equipment for highway construction works in Romania. Moreover, the physical and mathematical modeling of this mechanical system used the data obtained in the activity of the certification of the technical level of capability of the processing equipment in industry and construction, taking into account the provisions of procedures and regulations legally enforced by normative documents. These are based on a parametric analysis of the dynamics of the technological processing vibratory equipment and machines. Thus, both the evaluation method and the parametric optimization procedure were established. In this context, this paper presents a numerical analytical approach with discrete and continuous parametric variations, from where favorable areas of operation can be established. In this way, the optimization criteria in stabilized harmonic vibration regimes are approached based on the assessment of the vibration amplitude, of the force transmitted to the processed material and of the energy dissipated in the system. The presented dynamic model as well as the specific parameters were used in the design and/or numerical and experimental assessment for vibrating rammers with the amplitude of the perturbing force from 2 kN up to 100 kN, vibrating compactors with the amplitude of the perturbing force from 100 kN up to 200 kN and vibrating sieves for mineral aggregates with surface sieves of 6, 12 and 18 sqm. The symmetry/asymmetry properties are specific to the dynamic response in steady-state technological regime. Thus, the amplitude of vibrations in resonance presents asymmetry through a functional level necessary for the technological regime. The maximum force transmitted in the technological process is asymmetric in relation to the variation of the excitation pulsation; also, the dissipated energy has asymmetries in the postresonance. Hysteresis loops are symmetrical to the main axis. The originality of the research results comes from the establishment of dynamic parameters for the amplitude of technological vibration, the force transmitted to the working part, the energy dissipated on the cycle, hysteresis loops in a steady-state regime with digital display to identify the dynamic regime and the damping in the system. The calculation relations are specific to machines with a vibrating action and, on their basis, the vibrating equipment from Romania were designed, manufactured and tested, as mentioned in this paper.

General model for the kinetics of solute diffusion at solid-solid interfaces

Solute diffusion through solid-solid interfaces is paramount to many physical processes. From a modeling point of view, the discontinuities in the energy landscape at a sharp interface represent difficulties in predicting solute diffusion that, to date, have not been solved in a consistent manner across length scales. Using an explicit finite volume method, this work is the first to derive numerical solutions to the diffusion equations at a continuum level while including discrete variations in the energy landscape at a bicrystal interface. An atomic jump equation consistent with atomistic descriptions is derived and scaled up into a compendium of model interfaces: monolayer energy barriers, monolayer interfacial traps, multilayered traps, and heterogeneous interfaces. These can track solute segregation behavior and long-range diffusion effects. We perform simulations with data for hydrogen diffusion in structural metals, of relevance to the assessment of the hydrogen embrittlement phenomenon, and point defects in electronic devices. The approach developed represents an advancement in the mathematical treatment of solute diffusion through solid-solid interfaces and an important bridge between the atomistic and macroscopic modeling of diffusion, with potential applications in a variety of fields in materials science and physics.

Hemarthria compressa—Aspergillus niger—Trichoderma pseudokoningii Mediated Trilateral Perspective for Bioremediation and Detoxification of Industrial Paper Sludge

The present study was carried out to evaluate the effects of different fungal species on the metal uptake from paper sludge by Hemarthria compressa L. Paper sludge (PS) in various concentrations (0, 30% and 60%) were used with four treatments of two fungal species (F0 = Control, F1 = Aspergillus niger, F2 = Trichoderma pseudokoningii, F3 = A. niger + T. pseudokoningii). Paper sludge as rooting medium steadily influenced growth and physio-biochemical attributes of H. compressa in F0. Results revealed discrete variations in growth attributes with different PS concentrations and each fungal treatment. The maximum damages in ionic homeostasis (Na+, K+, Ca2+, Mg2+) due to PS toxicity were evident in parallel with declined chlorophyll concentration. The highest growth, total chlorophyll and biomass of the plants were observed when PS was treated with combined fungal strains (F3). Translocation factor decreased with F3 that is indicative of changes in Cd, Pb, and Cu movement to shoot from root. The plants with combined fungal treatment also showed greater catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD) activity. Ions, such as Ca, Mg, and Na, also increased gradually with combined fungal treatment. The correlation matrix displayed a close association among diverse fungal and PS levels with multiple plant attributes. PCA-Biplot confirmed the outcome of correlational analyses among different characters of H. compressa. The combined fungal mediate the extraction of heavy metals from the paper sludge by H. compressa recommends the high accumulation of heavy metal (HM) and possible reutilization of metal free sludge as a fertilizer, for application in cultivated fields. Furthermore, the effects of fungal species on HM attenuation in PS are linear and can be used in different habitats. Advancement in such research work will also be helpful in understanding the mechanisms and enhancing the ability of other native microbes to remediate metals.

Comparison of Hurst exponent estimation methods

Through recent years many researchers have developed methods to estimate the self-similarity and long memory parameter that is best known as the Hurst parameter. In this paper, we set a comparison between nine different methods. Most of them use the deviations slope to find an estimate for the Hurst parameter like Rescaled range (R/S), Aggregate Variance (AV), and Absolute moments (AM), and some depend on filtration technique like Discrete Variations (DV), Variance versus level using wavelets (VVL) and Second-order discrete derivative using wavelets (SODDW) were the comparison set by a simulation study to find the most efficient method through MASE. The results of simulation experiments were shown that the performance of the methods is relatively close, except for the SODDW method was the most efficient in MASE.&#x0D; Paper type Categorize your paper under one of these classifications: General review

Resonance-based detection of perilous sulphur dioxide using TiO2 nanoparticles and unit-cell ring resonator

SOx gases are the emissions from the industrial belt, ship exhausts, burning of fossil fuels and also a product for propellants and high-energy materials. Not only are these emissions hazardous to human health, but are toxic to the environment. Due to their ozone depletion and acid raineffects, these are extremely detrimental to the sensitive ecosystem. Detection of traces of such gaseous emissions is a challenge; which has sought various solutions; however, the answer is not satisfactory, especially in terms of selectivity and low-concentration detections. Titanium dioxide nanoparticles, which are conventionally known to exhibit gas sensing properties, due to their oxygen vacancies, have been used in ourstudies to demonstrate extremely sensitive, selective and rapid detection of SOx gaseous moieties, using a resonant frequency approach. TiO2 nanoparticles interact with entrapped SO2 molecules to form unique signatures of SO4− and shift in hydroxyl group (Ti−OH), thereby generating shifts in the resonant frequency signatures of the complementary split-ring resonator (CSRR) sensor designed for430 MHz. The duly simulated CSRR unit cell sensor is designed on copper clad with FR4 substrate. The electromagnetic waves passing through the waveguide are intercepted by the resonant structure, creating distinct resonant dips at the detector. These are manipulated by the changes in the dielectric constant of the various concentrations of SO2-entrapped-TiO2 nanoparticles subjected to the sensor surface. The sensor shows the sensitivity of ∼ 17.3 KHz/ppm with discrete and selective variations in the range of 0–300 ppm of SO2 gas moieties. The two-unit device is hence demonstrated, exhibiting a room-temperature, sensitive, selective, rapid and re-usable sensor. Using effective permittivity calculations of the SO2-entrapped-TiO2 nanoparticles, the sensor is duly calibrated for a probable device application.