In the current work, in continuation of our recent research [1] we synthesized and studied new chimeric compounds comprising the ribosome-targeting antibiotic chloramphenicol (CHL) and the membrane-penetrating cation triphenylphosphonium (TPP) connected by alkyl linkers of different lengths. Using various biochemical assays, we showed that these CAM-Cn-TPP compounds bind to the bacterial ribosome, inhibit protein synthesis in vitro and in vivo in a way similar to that of the parent CHL, and significantly decrease membrane potential. Similar to CAM-C4-TPP, the mode of action of CAM-C10-TPP and CAM-C14-TPP on bacterial ribosomes differ from that of CHL. By simulating the dynamics of complexes of CAM-Cn-TPP with bacterial ribosomes, we have proposed a possible explanation for the specificity of the action of these analogs on the translation process. CAM-C10-TPP and CAM-C14-TPP stronger inhibit the growth of the Gram-positive bacteria in comparison to the CHL and suppress some strains of CHL-resistant bacteria. Thus, we have shown that TPP derivatives of CHL are dual-acting compounds that target the ribosomes and the cellular membranes of bacteria. The TPP fragment of CAM-Cn-TPP compounds contributes to the inhibitory effect on bacteria. Moreover, since the mitochondria of eukaryotic cells have qualities similar to those of their prokaryotic ancestors, we demonstrate the possibility of targeting chemoresistant cancer cells with these compounds.

Reliable species identification is critical for detection and monitoring of biological invasions. In this study, we propose four sets of primers for efficient amplification of several loci, including the mitochondrial cytochrome oxidase-c (COI) subunit I gene which is a basis for DNA barcoding. This set of primers gives a shorter product which can be used in high-throughput sequencing systems for metabarcoding purposes. Another mitochondrial locus encoding the large ribosomal subunit (16S) may be useful to study the population structure and as an additional source of information in the metabarcoding of communities. We propose to use a set of primers for the nuclear locus of the small ribosomal subunit (18S) as a positive control and to verify the results of the barcoding. Our proposed sets of primers demonstrate a high amplification efficiency and a high specificity both for freshwater alien and indigenous fishes. The proposed research design makes it possible to carry out extremely cheap studies on the assessment of biological diversity using genetic analysis without expensive equipment, and with the technique for conducting laboratory work and processing of the results available to any researcher. The paper also presents original data on the genetic polymorphism of all mass alien fish species in the Volga-Kama region. High efficiency of DNA identification based on our primers is shown as compared to traditional monitoring of biological invasions.

The aim of this articles is to investigate the entropy optimization in unsteady MHD flow Darcy-Forchheimer nanofluids towards a stretchable sheet. The surface we tend to think about is porous and stretchy under acceleration. Flow occurs due to the stretching of the surface. Four distinct types of aqueous nanostructures are taken in this examination where copper oxide ( ), copper ( ), titanium dioxide ( ) and aluminum oxide ( ) are the nanoparticles. Irreversibility analysis are discussed through second law of thermodynamics. The expression of energy is mathematically designed and discussed according to heat generation / absorption, dissipation, thermal radiation, and joule heating. The nonlinear PDE (partial differential conditions) is first changed to ODE (normal differential conditions) through appropriate similarity variables. Here we used the numerically embedded solution technique to develop a numerical result for the obtained nonlinear flow expression. Influence of various flow parameter velocity temperature distribution and entropy generation are discussed. Reduction occurs in velocity profile for larger porosity and magnetic parameters. An enhancement in entropy generation and temperature distribution is seen for Brinkman number. An opposite effect is noticed in velocity and temperature through solid volume friction.

Skin aging is one of the most common problems facing humanity. It occurs because of altering the balance between free radicals and antioxidants and increasing the amount of the reactive oxygen species (ROS) in skin cells, which leads to oxidative stress especially when exposed to UV radiation. Antioxidants can neutralize the harmful effects of ROS, and secondary plant metabolites can help protect against UV radiation. In this study, punicalagin was extracted from pomegranate and concentrations of total polyphenolics and flavonoids were determined and antioxidant activities measured. Punicalagin was loaded onto niosomes and its morphology and release were studied. An in vitro study was performed on human fibroblast cell line HFB4 cells with aging induced by H2O2 and UV radiation. Cell cycle arrest was studied and different genes (MMP3, Col1A1, Timp3, and TERT) involved in the skin aging process were selected to measure punicalagin's effect. Punicalagin succeeded in reducing the growth arrest of HFB4 cells, activated production of the Col1A1 and Timp3 genes, maintained collagen level, and lowered of MMP3. Punicalagin increased human TERT concentration in skin cells. Punicalagin is promising as a natural antioxidant to protect human skin from aging.

Colletotrichum lini is a flax fungal pathogen, comprising differently virulent strains. In this work, we sequenced the genomes of three C. lini strains of different virulence: high virulent #390-1, medium virulent #757, and low virulent #771. We obtained more than 100× genome coverage with Oxford Nanopore Technologies reads and more than 50× genome coverage with Illumina data. To construct high-quality genomes, several assembly strategies were tested. The final assemblies were obtained using the Canu – Racon ×2 – Medaka – Polca scheme and were 54.0-55.3 Mb in length, contained 26-32 contigs, had an N50 > 5 Mb and the BUSCO completeness > 96%. Comparative analysis of the constructed genomes showed high similarity between mitochondrial and nuclear genomes. However, a rearrangement event and the loss of a 0.9 Mb contig were revealed. The candidate effectors were predicted in sets of proteins received after genome annotation. The obtained genome sequences of C. lini strains extend the knowledge on the genetic diversity of Colletotrichum species and are the basis for establishing molecular mechanisms of pathogenicity of the flax pathogen and effective control of flax anthracnose.

This study aimed to optimize the bioelectricity production process using a vinasse solution through the application of Plackett-Burman and Box-Behnken designs. An electrochemical cell was constructed using Arduino to measure the potential difference between the anode and cathode immersed in the vinasse solution, a byproduct of wine production containing organic compounds and ions that undergo redox reactions. The Plackett-Burman design identified the most influential variables among eight previously selected, including vinasse concentration, agitation, and yeast, which positively affected millivolt production, while temperature showed a negative correlation. Based on these results, the Box-Behnken design was used for process optimization, varying parameters such as concentration, stirring, and sodium chloride. Response surface graphs demonstrated the relationship between these variables and millivolt production. The findings indicate that higher agitation levels, lower concentrations of vinasse, and the addition of sodium chloride can enhance bioelectricity generation. The study provides insights into the bioelectricity production process from vinasse, contributing to the understanding and potential for sustainable energy generation. The methodology involving Arduino-based measurement and the utilization of experimental designs offers a systematic approach to optimize bioelectricity production from vinasse.

Background: Intelligence quotient (IQ) is a measure of intellectual ability of performing, comprehension, and learning. Previous studies reported that intelligence measures predict various measures of job performance and income. Emotional awareness (EA) is the measure of emotional capacity to recognize and make sense of one’s emotions, as well as those of others. A high level of emotional awareness (EA) indicates one can learn from expressed emotions quickly. Both IQ and EA are important for personal and professional success.Objective: This study tests the hypothesis that the average national income rank is best predicted by the combined effect of the population's average intelligence quotient (one's ability to perform and learn) and emotional awareness (ability to recognize and make sense of emotions).Method: The population’s average intelligence quotient (IQ), emotional awareness (EA), and indices of good governance, which include corruption perception index and educational expenses for each country, were obtained from public data sources. The outcome variable was per capita gross national income. All the variables that are statistically significant in univariate analysis were included in the multivariate regression analyses but excluded from the final model if not statistically significant.Result: The total number of countries included in the final analysis was 81 because of missing values in different variables. Intelligence quotient (IQ) and emotional awareness (EA) were found to be highly correlated, at 0.77 and 0.32 respectively, with the per capita gross national income. The independent effects of intelligence quotient (IQ) and emotional awareness (EA) were found significant in the multivariate model after adjusting for measures of good governance. The R square value for the final multivariate model was 0.82. The corruption perception index (CPI) and educational expenses were strongly correlated with other measures of good governance such as democracy index, functioning of government, electoral process and pluralism, political participation, and civil liberty, but these variables were found not significant in the multivariate model. Conclusion: The study concludes the effect of intelligence quotient (IQ) and emotional awareness (EA) are complementary to each other but intelligence quotient (IQ) is a stronger predictor than emotional awareness (EA) for gross national income or wealth. We also find that indicators of good governance, including corruption perception index and educational expenses, have important associations with per capita gross national income. This study implies a nation may build more wealth if the educational system focuses on developing emotional awareness in addition to intelligence. The study concludes the effect of intelligence quotient (IQ) and emotional awareness (EA) are complementary to each other but intelligence quotient (IQ) is a stronger predictor than emotional awareness (EA) for gross national income or wealth. We also find that indicators of good governance, including corruption perception index and educational expenses, have important associations with per capita gross national income. This study implies a nation may build more wealth if the educational system focuses on developing emotional awareness in addition to intelligence.

New Schiff base ofN'-((E)-3,3-diphenyl-2,3-dihydro-1H-inden-1-ylidene)-2-((Z)-2-oxoindolin-3-ylidene)hydrazine-1-carbothiohydrazide (HL) and its Co(II),Ni(II), Fe(III), Cu(II), Cd(II), Zn(II) and Mn(II) complexes were created, isolated, and characterized by analytical analysis in good yields of 60 to 90%, UV–Vis, magnetic measurements, molar conductivity, and FT-IR. Additionally, mass spectrometry was used to examine the new ligand complexes' structural characteristics.1H NMR spectroscopy and elemental analysis. Depending on the electronic spectra and magnetic susceptibility measurements, these complexes are predicted to have octahedral molecular geometry. As an example, the quantum chemical properties, bond lengths, and bond angles were discussed. The structural formula for the examined ligand was improved using the Gaussian09 tool. The DFT/B3LYP method was used to calculate the energy gaps and other crucial theoretical features. The prepared hydrazine ligand complexes Co (II), Ni (II), Fe (III), Cu (II), Cd (II), Zn (II) and Mn (II) complexes were evaluated for its antimicrobial properties. As antimicrobial agents, it was found that the organic ligand was less biologically active than the targeted complexes. Gram positive bacteria (3ty7-Staphylococcus), Gram negative bacteria (3t88-Escherichia coli), and fungi (5k04-Candida albicans) all have crystal structures that interact well with the chemicals in the title, according to molecular docking.

Background: Glioblastoma remains a challenging brain tumor to treat due to its infiltrative nature. Accurately identifying tumor boundaries during surgery is crucial for successful tumor resection. This study introduces an innovative intraoperative visualization method utilizing a surgical fluorescence microscope to precisely locate tumor cells. The focus of the study is on IR-Glint, a novel preparation comprising Cy7.5-labeled aptamers Gli-233nt and Gli-55_3L specific to human glioblastoma. Methods: The aptamers were modified using molecular modeling and quantum chemical techniques. The effectiveness of the preparation was assessed using flow cytometry and microscopy on primary cultures of human glioblastoma. In vivo studies were conducted on mouse and rabbit models, employing orthotopic xenotransplantation of human brain glioblastoma with various imaging techniques, including PET/CT, in vivo fluorescence visualization, confocal laser scanning, and surgical microscopy. Results: The experiments validated the potential of IR-Glint for intraoperative visualization of glioblastoma using infrared imaging. Surface application of the aptamer-based formulation on the brain allowed clear visualization of the tumor, aiding surgeons in tumor resection. This approach also reduces the dosage required and mitigates potential toxic effects on the patient. Conclusions: This study demonstrates the promising potential of using in-frared dye-labeled aptamers for intraoperative visualization of glioblastoma. By improving surgical treatment outcomes in neurosurgery, this novel approach may pave the way for future advancements in the field.

The Vaal Dam catchment, which is the source of potable water for Gauteng province, holds various human activities including mining, urbanization, agricultural and industrial activities coupled with high fluxes of nutrients from different areas within the catchment. This situation led to an enhancement of Harmful Algal Blooms (HABs) in the dam reservoir. Phosphorus and Nitrogen are the limiting nutrients for HABs in many eutrophic aquatic systems when their concentrations are raised in such waters. In this study, multi-time-series plot types and scutter plots were analysed to reveal the relationship between HABs proxy chlorophyll-a (Chl-a) and the potential nutrients. Also (Chl-a) data extracted from landsat-8 satellite images were visualised to show the spatial distribution of HABs in the reservoir. The results showed that the Vaal Dam HABs productivity is a function of the total phosphorus (TP) and the organic nitrogen (KJEL_N) levels, which were positively correlated with chlorophyll-a (Chl-a) concentration. The long-term analysis of Chl-a in-situ data (1986 – 2022) measured at one point within the reservoir showed an average of 11.25μg/l but at some stochastic dates, the Chl-a concentration jumped to very high values reaching the maximum value of 452.8μg/l. Such high values are associated with high records of TP and KJEL_N concentrations at the same dates which clearly reveals their effect on the productivity levels. The decadal time series and its trend analysis showed that the average productivity level of Chl-a increased during the studded period from 4.75μg/l in the first decade (1990 – 2000) to 10.51μg/l in the second decade (2000 – 2010) reaching 16.7 during the last decade (2010 – 2020). The increasing averages of the decadal values are associated with the increasing decadal average of its driving factors, TP from 0.1043 to 0.1096 to 0.1119mg/l for the three decades, respectively and KJEL_N from 0.80mg/l in the first decade to 1.14mg/l in the last decade. The decadal average of temperature showed no significant increase, 17.9 °C in the first decade and 18 °C in the last decade which suggests that temperature is not the only enhancing factor of the HABs productivity in the Vaal Dam. The satellite data analysis during the last decade revealed that the HABs spatial dynamics is a function of the dam geometry and the levels of the discharges from its two feeding rivers. Higher concentrations were observed where the reservoir is meandering and within the areas of restricted water circulation.

Bottlebrush (BB) elastomers with water-soluble side chains and tissue-mimetic mechanical properties are promising for biomedical applications like tissue implants and drug depots. This work investigates the microstructure and phase transitions of BB elastomers with crystallizable polyethylene oxide (PEO) side chains by real-time synchrotron X-ray scattering. In the melt, the elastomers exhibit the characteristic BB peak corresponding to the backbone-to-backbone correlation. Upon crystallization of the side chains, the intensity of the peak decays linearly with crystallinity, and eventually vanishes due to BB packing disordering within intercrystalline amorphous gaps. This behavior of the bottlebrush peak differs from an earlier study of BBs with poly(ε-caprolactone) side chains, explained by stronger backbone confinement in the case of PEO, a high-crystallinity polymer. Microstructural models based on 1D SAXS correlation function analysis suggest crystalline lamellae of PEO side chains separated by amorphous gaps of monolayer-like BB backbones.

A magnetite (CDC@Fe3O4) heterogeneous photocatalyst was synthesized via treated and modified cotton in two steps. The designed nanocomposites were characterized by FTIR, TGA, XRD, SEM, and VSM analyses. The Fenton-photocatalytic decomposition efficiency of the synthesized magnetic catalyst was evaluated under visible sunlight using Methyl Orange (MO) as a model organic pollutant. The impacts of several degradation parameters, including the light source, catalyst load, irradiation temperature, oxidant dose, and pH of the dye aqueous solution and its corresponding concentration on the Fenton photodegradation performance, were methodically investigated. (CDC@Fe3O4) heterogeneous catalyst showed a remarkable MO removal rate of 97.9% at 10 min under visible-light irradiation. (CDC@Fe3O4) nanomaterials were also used in a heterogeneous catalytic optimized protocol for a multicomponent reaction procedure to obtain nine tetra-substituted imidazole derivatives. The green protocol afforded imidazole derivatives in 30 min with good yields (91-97%) at room temperature and under ultrasound irradiation. Generally, a synthesized recyclable heterogeneous nano-catalyst is a good example and is suitable for wastewater treatment and organic synthesis.

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly termed nonalcoholic fatty liver disease (NAFLD), is a widespread global health concern that affects around 25% of the global population. Its influence is expanding, and it is anticipated to overtake alcohol as the leading cause of liver failure and liver-related death worldwide. Unfortunately, there are no approved therapies for MASLD; as such, national and international regulatory health agencies undertook strategies and action plans designed to expedite the development of drugs for treatment of MASLD. A sedentary lifestyle and an unhealthy diet intake are important risk factors. Western countries have a greater estimated prevalence of MASLD partly due to lifestyle habits. Mitochondrial dysfunction is strongly linked to the development of MASLD. Further, it has been speculated that mitophagy, a type of mitochondrial quality control, may be impaired in MASLD. Thyroid hormone (TH) coordinates signals from the nuclear and mitochondrial genomes to control mitochondrial biogenesis and function in hepatocytes. Mitochondria are known TH targets and preclinical and clinical studies suggest that TH, thyroid receptor β (TR-β) analogs, and synthetic analogs specific to liver could be of therapeutic benefit in treating MASLD. In this review, we highlight how mitochondrial dysfunction contributes to development of MASLD, and how understanding the role of TH in improving mitochondrial function paved the way for innovative drug development programs of TH-based therapies targeting MASLD.

A form of dementia distinct from healthy cognitive aging, Alzheimer's disease (AD) is a complex multi-stage disease that currently afflicts over 50 million people worldwide. Unfortunately, previous therapeutic strategies developed from murine models emulating different aspects of AD pathogenesis have failed. Consequently, researchers are now developing models that express several aspects of pathogenesis that better reflect the clinical situation in humans. As such, this review seeks to provide insight regarding current applications of mammalian models in AD research by addressing recent developments and characterizations of prominent transgenic models and their contributions to pathogenesis as well as discuss the advantages, limitations, and application of emerging models (hAβ-KI) that better capture genetic heterogeneity and mixed pathologies observed in the clinical situation.

The need for multi-gene analysis in evolutionary and taxonomic studies is generally accepted. However, sequencing of multiple genes is not always possible. For various reasons, short mito-chondrial DNA barcodes are the only source of molecular information for some species in many genera, although multilocus data are available for other species of the same genera. In particular, such a situation exists in the species-rich butterfly subgenus Polyommatus (Agrodiaetus). Here, we analysed partitioning of this subgenus into species groups by using three data sets. The first data set was represented by short mitochondrial DNA barcodes for all analysed samples. The second and third data sets were represented by combination of short mitochondrial DNA barcodes for a part of the taxa with longer mitochondrial sequences COI+tRNA-Leu+COII (data set 2) and with longer mitochondrial COI+tRNA-Leu+COII and nuclear 5.8S rDNA+ITS2+28S rDNA sequences (data set 3) for the remaining species. We show that DNA barcoding approach (data set 1) failed to reveal the taxonomic structure resulting in numerous polytomies in the phylogenetic tree ob-tained. Combined analysis of the mitochondrial and nuclear sequences (data sets 2 and 3) re-vealed the species groups and position within these species groups even for the taxa for which only short DNA barcodes were available.

In this study, the microbiological quality of traditionally made yoghurt from Northern Uganda and Western Kenya were analysed. Six samples of typical traditionally fermented milk were randomly collected from traditional cattle keepers from Karamojong (UG 1) and Acholi (UG 2) in Northern Uganda), and Kalenjin in Western Kenya (KE). Analysis was carried out for microbial quality of the collected samples and was assessed using the conventional methods for total aerobic mesophilic bacteria, total coliform, lactic acid bacteria, Staphylococcus aureus, Listeria monocytogenes, yeasts, and mould counts. The results showed that the pH of the samples was low (2.9- 3.6). The mean aerobic mesophilic bacterial counts were 5.14 x 109 cfu/ml. The mean counts for mesophilic lactobacilli ranged from x 106 to x 108, cfu/ml. The mean thermophilic lactobacilli count ranged from x 107, to x 109, cfu/ml. However, the thermophilic lactococci counts ranged from x 106, to x 109, cfu/ml. On the other hand, the Streptococci counts were between x 106 to x 108 cfu/ml. The mean counts for the non-Sorbitol E. coli was 3.87 x 103 cfu/ml. The results suggest that although the pH of the yoghurt made in the Acholi and Karamojong (Northern Uganda) and in Kalenjin (Kenya) areas was low, the level of bacteria, yeast, and mould counts indicated poor microbiological quality control. This poses public health concerns. Therefore, attention of the appropriate government agencies is needed to ensure that environment of yogurt produced in a traditional setting in most appropriate condition to reduce contamination.

The substrate N1, N3, N5 -tris(2-hydroxyphenyl)benzene-1,3,5-tricarboxamide (Sensor A) was prepared in the reaction of 1,3,5-benzenetricarboxylic acid (trimesic acid) and o-aminophenol in ethanol. The prepared organic sensor fulfills the chemiluminescent requirements including luminophore, spacer, and suitable binding receptor that distress the probe's luminescent features, providing selective and sensitive detection of mercury and iron ions in aqueous solutions. The sensor selectively detects mercury and iron ions in a water matrix containing various metal ions including sodium, calcium, magnesium, zinc, and nickel. Strong and immediate binding was observed between mercury ions and the substrate at pH 7.0 with a binding affinity toward Hg (II) enhanced by nine folds higher than that observed for iron sensor binding affinity, which makes the substrate a distinctive luminescence sensor for mercury detection at ambient conditions. The sensor shows a linear response toward Hg (II) in the concentration range from 4.2 x 10-5 to 2.0 x 10-8 M with a limit of detection of 1.0 x 10-8 M. Further, Sensor A provides linear detection for iron ions in the range from 1.5 x 10-3 to 1.5 x 10-8 M. The measured adsorption capacity of Sensor A toward mercury ions ranged from 1.25 to 1.97 mg/g and the removal efficiency from water samples reached 98.8% at pH 7.0. The data demonstrate that Sensor A is an excellent probe for detecting and removing mercury ions from water bodies.

This present work explores the performance of a thermal-magnetic engine of Otto type, considering as a working substance an effective interacting spin model corresponding to the q− state clock model. We obtain all the thermodynamic quantities for the q = 2, 4, 6, 8 cases in a small lattice size (3×3 with free boundary conditions) by using the exact partition function calculated from the energies of all the accessible microstates of the system. The extension to bigger lattices was performed using the mean-field approximation. Our results indicate that the total work extraction of the cycle is highest for the q=4 case, while the performance for the Ising model (q=2) is the lowest of all cases studied. These results are strongly linked with the phase diagram of the working substance and the location of the cycle in the different magnetic phases present, where we find that the transition from a ferromagnetic to a paramagnetic phase extracts more work than one of the Berezinskii–Kosterlitz–Thouless to paramagnetic type. Additionally, as the size of the lattice increases, the extraction work is lower than smaller lattices for all values of q presented in this study.

Temperature-index modeling is used to determine the magnitude of temperature depression on the Blanca Massif, Colorado, required to maintain steady-state mass balances of nine reconstructed glaciers at their extent during the Last Glacial Maximum (LGM). The mean temperature depression thus determined is ~8.6 +0.7/–0.9 °C where the uncertainties account for those inherent in the glacier reconstructions, in model parameters (e.g. melt factors), and possible modest changes in LGM precipitation. Associated equilibrium-line altitudes (ELAs) exhibit a statistically significant directional dependency being lower toward the north and east. Under the assumption that regional temperature change was uniform, required changes in precipitation vary systematically – also exhibiting a directional dependency coinciding with that in ELAs – and indicate increases (over modern) occurred on the eastern side of the massif while decreases occurred on the western side. This disparity represents a strengthening of a precipitation asymmetry, particularly winter precipitation, that exists today. The modern precipitation asymmetry may be a consequence of snow being blown over to the eastern side of the massif (advective transport) by southwesterly flow. Intensification of this flow during the LGM would have enhanced advection, and augmented snow accumulation on glaciers, thus explaining the lower ELAs and increased precipitation on that side of the massif.

The present study assessed the effect of abscisic acid (ABA; 25 µM) and/or nitrogen (N; 10 mM) in minimization of salinity (NaCl; 100mM)-impact on growth, photosynthetic efficiency, Rubisco activity, nitrogen and sulfur assimilation, oxidative stress (H2O2), lipid peroxidation measured as thiobarbituric acid reactive substances, (TBARS), osmolyte (Proline) content, and the activity of antioxidant enzymes (superoxide dismutase, SOD glutathione reductase, GR; ascorbate peroxidase, APX) in cultivar RH0-749 of Brassica juncea L. NaCl stress caused significant elevations in H2O2 and TBARS, and differentially modulated proline content, the activity of antioxidant enzymes, and impaired growth and photosynthetic functions. Exogenously applied 25 µM ABA negatively affected plant growth and photosynthesis in B. juncea without NaCl. In contrast, exogenously applied 25 µM ABA and 10 mM N, alone or in combination minimized oxidative stress, and maintained a fine-tuning between proline content and the activity of antioxidant enzymes, and thereby improved plant growth and photosynthetic functions in NaCl exposed B. juncea.

The generalized dual-kinetic-balance approach for axially symmetric systems is employed to solve the two-center Dirac problem. The spectra of one-electron homonuclear quasimolecules are calculated and compared with the previous calculations. The analysis of the monopole approximation with two different choices of the origin is performed. Special attention is paid to the lead and xenon dimers, Pb82+–Pb82+–e− and Xe54+–Xe54+–e−, where the energies of the ground and several excited σ-states are presented in the wide range of internuclear distances. The developed method provides the quasicomplete finite basis set and allows for construction of the perturbation theory, including within the bound-state QED.

Zirconium based bulk metallic glasses are industrially valuable materials which commercial market grows rapidly. Surface modification of these metallic glasses by high-intensity lasers is relatively new and costly treatment promising great advantages over classical surface processing methods. In this work we perform the case study of surface modification of Zr$_{46}$Cu$_{36.8}$Ag$_{9.2}$Al$_8$ metallic glass by high-intensity millisecond laser beam. Our results suggest chemical deposition of atmospheric oxygen and nitrogen in the laser-melted surface area and its surroundings. Zirconium nitride layer was detected in the middle of laser-irradiated area. Nanocrystals embedded in the amorphous matrix were also formed on the surface. Overall, our findings suggest possibilities for improvement of mechanical characteristics of the studied metallic glass.

The main objective of the present study was to investigate arsenate [As (V)] resistance genes in rice cultivars grown in arsenic contaminated Egyptian soil in order to genetically induce resistance against arsenic in the local rice varieties as well as defining contaminated rice grains and/or soil. Three local rice cultivars; Sakha 102-104 were cultivated on modified Murashige and Skoog Basal Medium (MS medium) containing elevated concentrations of arsenate (0.1, 1 and 10 mg/l). The three varieties showed different resistant attitudes against arsenate with Sakha 104 being the most resistant. Extracted messenger RNA (mRNA) from treated and untreated Sakha 104 plantlets was scanned using differential display to demonstrate the arsenate resistant genes using three different arbitrary primers. About 100 different RNAs with (1500 bp - 50 bp) were obtained from which seven were up-regulated genes, subjected to DNA cloning using TOPO TA system and the selected clones were sequenced. The sequence analysis described four genes out of the seven namely disease resistance protein RPM1, Epstein-Barr virus EBNA-1-like, CwfJ family protein and outer membrane lipoprotein OmlA while the other three genes were hypothetical proteins. It is concluded the four induced genes in the resistant rice cultivar considered as a direct response to arsenic soil pollution. Genes detected in the present study can be used as geno-sensors for rice grains and soil contamination with As (V). Moreover, local rice cultivars may be genetically modified with such genes to induce high resistance and to overcome arsenic soil pollution.

Fourteen (14) rack-mounted polycrystalline modules installed on the concrete roof of the solar energy applications laboratory at the Kwame Nkrumah University of Science and Technology (KNUST) in Ghana, a hot humid environment were assessed after 19 years of continuous outdoor expodure. The physical state of the modules was documented using a visual inspection checklist. They were further assessed by current-voltage (I-V) characterization and thermal imaging. The modules were found to be in good physical state, except some bubbles on front side and minor discolouration/corrosion at edge of the cells. Compared with reference values, the performance decline of the modules observed over the exposure period was: nominal power (P_nom), 21% to 35%; short circuit current (I_sc), 5.8% to 11.7%; open circuit voltage (V_oc) 3.6% to 5.6% and 11.9% to 25.7% for fill factor (FF). It is hoped that this study will provide some helpful information to project developers, manufacturers and the research community on the long-term performance of PV modules in Ghana.

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a pleiotropic myelopoietic growth factor and proinflammatory cytokine, clinically used for multiple indications and serving as a promising target for treatment of many disorders, including cancer, multiple sclerosis, rheumatoid arthritis, psoriasis, asthma, COVID-19. We have previously shown that dimeric Ca2+-bound forms of S100A6 and S100P proteins, members of the multifunctional S100 protein family, are specific to GM-CSF. To probe selectivity of these interactions, the affinity of recombinant human GM-CSF to dimeric Ca2+-loaded forms of 18 recombinant human S100 proteins was studied by surface plasmon resonance spectroscopy. Of them, only S100A4 protein specifically binds to GM-CSF with equilibrium dissociation constant, Kd, values of 0.3-2 μM, as confirmed by intrinsic fluorescence and chemical crosslinking data. Calcium removal prevents S100A4 binding to GM-CSF, whereas monomerization of S100A4/A6/P proteins disrupts S100A4/A6 interaction with GM-CSF and induces a slight decrease in S100P affinity for GM-CSF. Structural modelling indicates the presence in the GM-CSF molecule of a conserved S100A4/A6/P-binding site, consisting of the residues from its termini, helices I and III, some of which are involved in the interaction with GM-CSF receptors. The predicted involvement of the ‘hinge’ region and F89 residue of S100P in GM-CSF recognition was confirmed by mutagenesis. Examination of S100A4/A6/P ability to affect GM-CSF signaling showed that S100A4/A6 inhibit GM-CSF/S100-induced suppression of viability of monocytic THP-1 cells. The ability of the S100 proteins to modulate GM-CSF activity is relevant to progression of various neoplasms and other diseases, according to bioinformatics analysis. The direct regulation of GM-CSF signaling by extracellular forms of the S100 proteins should be taken into account in the clinical use of GM-CSF and development of the therapeutic interventions targeting GM-CSF or its receptors.

Making sustainable business models, especially in manufacturing, is a key approach for organizations to adopt in order to create more sustainable processes. New technologies are needed to implement new policies that can minimize the economic, environmental, and social consequences of industrial activity. Sustainable maintenance is decisive to guarantee the availability, reliability, and safety of assets, surpassing traditional maintenance policies and embracing the principles of the circular economy. The main objective of Maintenance 4.0 is to increase the lifespan and availability of the equipment by preventing unplanned downtime, reducing planned shutdowns, and improving safety. This research focuses on the integration of advanced Industry 4.0 tools with conventional monitoring and control techniques in process industries. The article suggests that while complex neural networks might provide good predictions, simpler solutions can generalize well and have lower prediction errors because they can capture the underlying relationships between variables in a specific asset better. The combination of maintenance function, Industry 4.0 tools, and advanced statistical solutions to obtain sustainable processes can facilitate organizational change and aid decision-making in equipment management. These solutions seek to reduce interruptions and expenses through the unnecessary utilization of labor and spare parts. All these considerations improve communication and data processing, resulting in improved maintenance of a hydrogen compressor in the petrochemical industry.

Positively charged polyelectrolytes hold significant potential as materials for creating antibacterial coatings. Water-soluble macromolecules can be easily deposited onto a treated surface through various techniques, forming a film that provides antimicrobial properties to the surface through electrostatic interactions with bacterial membranes. The structural and molecular weight characteristics of the polymers play a crucial role in the physical and mechanical properties of the coatings. In this study, we investigated the properties of branched polyethyleneimine (PEI) and linear polydiallyldimethylammonium chloride (PDADMAC) coatings with different molecular weights of polymer samples to determine their suitability as stable coatings with antibacterial properties against foodborne bacteria. Using thermogravimetric analysis, dynamometry, and dynamic light scattering, we examined the physicochemical and mechanical properties of the macromolecules in water solutions and in coatings. Microbiological study was conducted to analyze the biocidal activity of the polycations in solutions and on the surface of coatings. Our findings showed that the moisture saturation of the polycationic coatings did not significantly depend on the chemical nature of charged groups or the molecular weight or architecture of macromolecules. Moreover, biocidal activity was not found to depend on the molecular weights of PEI and PDADMAC. However, the lowering of the molecular weight of polymers resulted in the loss of cohesive forces in the coatings and to dramatically loss of the stability towards wash-off with water. The diffusion coefficient (D0) of macromolecules was identified as a key parameter for the wash-off mechanism. Films formed by molecules with D0 below 1×10-7 cm2/s demonstrated high resistance to wash-off procedures. We demonstrated that PEI and PDADMAC samples with high molecular weights showed high antimicrobial activity towards L. monocytogenes. Our results highlight the importance of macromolecule characteristics in the development of new biocidal coatings based on polycations.

Herein, we demonstrate the synthesis of sandwiched composite nanomagnets, which consist of hard magnetic Cr-substituted hexaferrite cores and magnetite outer layers. The hexaferrite plate-like nanoparticles with average dimensions of 36.3 nm × 5.2 nm were prepared by glass crystallization method and were covered by spinel-type iron oxide via thermal decomposition of iron acetylacetonate in hexadecane solution. The hexaferrite nanoplates act as seeds for the epitaxial growth of the magnetite, which results in uniform continuous outer layers on both sides. The thickness of the layers can be adjusted by controlling the concentration of metal ions. In this way, layers with average thickness of 3.7 and 4.9 nm were obtained. Due to an atomically smooth interface the magnetic composites demonstrate the exchange coupling effect, acting as single phases during remagnetization. The developed approach can be applied to any spinel-type material with matching lattice parameters and opens the way to expand the performance of hexaferrite nanomagnets due to a combination of various functional properties.

In the present article, we study the possibilities of machine learning for estimation of seeing at the Maidanak Astronomical Observatory (38∘40′24′′N, 66∘53′47′′E) using only Era-5 re-analysis data. Seeing is usually associated with the integral of the turbulence strength Cn2(z) over the height z. Based on the seeing measurements accumulated over 13 years we created ensemble models of multi-layer neural networks under the machine learning framework, including training and validation. For the first time in the world, we have simulated optical turbulence (seeing variations) during night-time with deep neural networks trained on a 13-year database of astronomical seeing. A set of neural networks for simulations of night-time seeing variations have been obtained. For these neural networks the linear correlation coefficient ranges from 0.48 to 0.68. We show that modeled seeing with neural networks is well described through meteorological parameters, which include wind speed components, air temperature, humidity and turbulent surface stresses. One of the fundamental new results is that the structure of small-scale (optical) turbulence over the Maidanak Astronomical Observatory does not depend or depends negligibly on the vortex component of atmospheric flows.

Various iron oxides have been proven to be promising anode materials for metal-ion batteries due to their natural abundance, high theoretical capacity, ease of preparation, and environmental friendliness. However, the synthesis of iron oxide-based composites requires complex approaches, especially when it comes to composites with intrinsically conductive polymers. In this work we propose a one-step microplasma synthesis of a polyaniline-coated urchin-like FeOOH nanoparticles (FeOOH/PANI) for application as anode in lithium-ion batteries. The material shows excellent electrochemical characteristics, providing initial capacity of ca. 1600 mA∙h∙g−1 at 0.05 A∙g−1 and 900 mA∙g−1 at 1.2 A∙g−1. Further cycling lead to capacity decrease to 150 mA∙h∙g−1 by the 60th cycles, followed by a recovery that maintained the capacity at 767 mA∙h∙g−1 after 2000 cycles at 1.2 A∙g−1 and restored full initial capacity of 1600 mA∙h∙g−1 at low current density of 0.05 A∙g−1. Electrochemical milling of the material caused such interesting behavior of the material, and we confirmed this phenomenon by a combination of physico-chemical and electrochemical techniques. The anodes also exhibit high performance in a full cell with NMC532. NMC532//FeOOH/PANI full cell provided energy density of 224 Wh∙kg−1 which is comparable to the reference cell with graphite anode (264 Wh∙kg−1).

The evolutionary conserved STING-cGAS pathway represents one of the most important cytosolic DNA sensing systems that is activated in response to viral invasion and/or damaged integrity of the nuclear envelope. The key outcome of this pathway is the production of IFN, which subsequently stimulates hundreds of genes. In oncology, the situation is a complex one since this pathway may serve either anti- or pro-oncogenic roles in a context-dependent fashion. The prevailing understanding is that when the innate immune response is activated by sensing cytosolic DNA, such as from ruptured micronuclei, it results in the production of interferon which attracts cytotoxic cells to destroy tumors. However, in tumor cells that have adjusted to significant chromosomal instability, particularly in relapsed, treatment-resistant cancers, the cGAS–STING pathway often supports cancer progression. In these cells, the pathway initiates a non-canonical nuclear factor κB transcriptional response, fostering the epithelial-to-mesenchymal transition (EMT). Here, we review this intricate pathway in conjunction with cancer progression and development of new treatment modalities.

Porous ferroelectric lead zirconate-titanate (PZT) films are a promising material for various electronics applications. This study focuses on understanding how structure-directing agent (polyvinylpyrrolidone) can change structure and electrical properties of porous PZT films prepared by chemical solution deposition. The films with various porosity up to ~ 40 vol.% and pore connectivity changing from 3-0 to 3-3 were prepared and studied by capacitance-voltage, dielectric hysteresis, transient current, photocurrent, and local current techniques. We have found that the linear decrease in the material volume in a porous film is not the only factor governing film properties. The key role in changing electrical properties plays the creation of new internal grain boundaries. This research expands the understanding of physical phenomena in porous ferroelectric films and may enable the development of new materials and devices.

Osteoconductive granulated biopolymers (OGB) are used to restore the lost volume of the jaw bone. OGB is employed as a loose fraction and exhibits physical traits common to bulk mixtures. By removing air bubbles and industrial dust from the OGB fraction through special processing, more accessible spaces are left over for the adsorption of bone growth factors. The recipient site's biological environment alters the OGB fraction's physical characteristics. This is the cause of the OGB fraction's volume changing uncontrollably during the first three weeks following surgery. Predictive indicators for describing the physical processes of osteoconduction include the compaction coefficient and adsorption capacity. Taking into account the prognostic indicators of the dynamics of changes in the physical properties of the OGB fraction in the postoperative period, 3D planning of the bioengineered structure should be done. The OGB fraction's adsorption and drainage properties are optimized by raising the purity of OGB production and preparing the biopolymer for clinical studies.

Metabolomics is a powerful set of methods that uses analytical techniques to identify and quantify metabolites in biological samples, providing a snapshot of the metabolic state of a biological system. In medicine, metabolomics can help diagnose diseases, reveal molecular basis of a disease, and monitor treatment responses, while in agriculture, it can improve crop yields and plant breeding. However, animal metabolomics faces several challenges due to the complexity and diversity of animal metabolomes, the lack of standardized protocols, and the difficulty in interpreting metabolomic data. The current dataset includes quantitative metabolomic profiles of eye lens tissues from 26 bird species (111 specimens) that can aid researchers in developing new experiments, mathematical models, and integrations with other omics data. The dataset includes raw 1H NMR spectra, protocols for sample preparation, and data preprocessing with the final table containing information on 89 reliably identified and quantified metabolites. The dataset is quantitative, making it relevant for supplementing with new specimens or comparison groups, followed by data mining and expected new interpretations. It was obtained from bird specimens collected in compliance with ethical standards and reveals potential differences in metabolic pathways due to phylogenetic difference or environmental exposure.

In this article we investigate the generalized Kawahara-KdV system. A new topological approach is applied to prove the existence of at least one classical solution and at least two nonnegative classical solutions. The arguments are based upon recent theoretical results.

(1) Background: Recent studies provide some evidence for the contribution of antibody-mediated autoimmune mechanisms to the nature of fibromyalgia (FM) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Much attention was paid to the autoantibodies (AAb) targeting G protein-coupled receptors as natural components of the immune system. However, natural AAb network is much more extensive, and has not been previously investigated in these disorders; (2) Methods: The enzyme immunoassays ELI-Viscero-Test and ELI-Neuro-Test were used to determine changes in serum content of a 33 natural AAb to neural, organ-specific and non-tissue-specific autoantigens a) in 11 FM patients with comorbid ME/CFS; b) in 11 ME/CFS patients without FM; c) in 11 healthy controls. Individual autoantibody profiles and their correlation with some clinical symptoms were analyzed. (3) Results: both patients with ME/CFS and ME/CFS+FM were characterized by more frequent and pronounced deviations in the immunoreactivity to GABA-receptors than healthy controls. Although the level of other natural AAb did not differ between study groups, AAb correlation signatures were changing in patients compared to healthy controls. Both in patients and healthy controls the level of natural AAb to various neural and tissue-specific antigens correlated with the severity of fatigue, bodily pain, depression, anxiety, physical and mental-health related quality of life. Notably, that widely different correlation patterns were observed between study groups. (4) Conclusions: Findings from this pilot study provide some evidence that the homeostasis of autoimmune relationships, which are possibly a physiological part of our immune system, may break down in FM and ME/CFS. The correlation of disease-induced perturbations in individual AAb profiles with some clinical symptoms may arise from the immune system's ability to reflect qualitative and quantitative changes in antigenic composition of the body.

Ion channels serve many cellular functions including ion homeostasis, volume regulation, signaling, nutrient acquisition, and developmental progression. Although the complex lifecycles of malaria parasites necessitate ion and solute flux across membranes, whole genome sequencing of the human pathogen, Plasmodium falciparum, revealed remarkably few orthologs of known ion channel genes. Contrasting with this, biochemical studies have implicated channel-mediated flux of ions and nutritive solutes across several membranes in infected erythrocytes. Here, I review advances in the cellular and molecular biology of ion channels in malaria parasites. These studies have implicated novel parasite genes in the formation of at least two ion channels, with additional ion channels likely present at various membranes and parasite stages. Computational approaches that rely on homology to known channel genes from higher organisms will not be very helpful in identifying the molecular determinants of these activities. Given their unusual properties, novel molecular and structural features, and essential roles in pathogen survival and development, parasite channels should be promising targets for therapy development.

The current study characterizes the transient M/M/1 queue manifold info-geometrically, through devising Fisher Information matrix(FIM) and its inverse(IFIM). Additionally, the impact of stability on the existence of IFIM and explore the geodesic equations of motion has been revealed. More potentially, the paper discusses the relationship between stability and the Gaussian curvature, as well as the connections between queueing theory, information geometry, , Riemannian geometry, and the Theory of Relativity.

This paper provides a first-time ever unification of information theory, semi-group theory with the theory of uncertain reasoning, through functional perspective. Fundamentally, the threshold theorems for the inference functional were devised. Furthermore, numerical experiments are illustrated. The complex proofs in our paper are original results which emphasizes the credibility of the class of Rényi Generalized Entropies as measures of information, and that the field is open to extend an enhanced methodology regarding queuing networks with heavy tails.

The recent remarkable progress in Artificial Intelligence (AI) has renewed the discussion on the possibility of human-level AI. Despite the difficulty of the problem and the presence of many large gaps and challenges, most people working in the field think that human-level AI is achievable, but they disagree on the date. In this paper, I briefly discuss the possibility of human-level AI from the perspective of two traditions in the Islamic world, namely Kalam and Sufism, and despite their different mode of investigation, they converge to the same conclusion on this topic.

Information geometry (IG) seeks to characterize the structure of statistical geodesic models from a differential geometric point of view. By considering families of probability distributions as manifolds with coordinate charts determined by the parameters of each individual model, the tools of differential geometry, such as divergences and metric tensors, provide effective means of studying their characteristics. The research undertaken in this paper presents a novel approach to the modelling study of information geometrics of a queueing system. In this context, the manifold of a stable M/G/1queue is characterised from the viewpoint of IG. The Fisher Information matrix (FIM) as well as the inverse of (FIM), (IFIM) of stable M/G/1 queue manifold are devised. In addition to that, new results that uncovered the significant impact of stability of M/G/1 queue manifold on the existence of (IFIM) are obtained. The Kullback’s divergence (KD), and J-divergence (JD).New result has been devised on the significant impact of both server utilization and squared coefficient of variation of the underlying M/G/1 queue manifold on both (KD) and (KD) are devised. Also, it is revealed that stable M/G/1 QM is developable (i.e., has a zero Gaussian curvature) and has a non-zero Ricci Curvature Tensor (RCT). Novel stability dynamics of M/G/1 queue manifold is revealed by discovering the mutual dual impact between the behaviour of (RCT) and the stability and the instability phases of the underlying M/G/1 queue manifold. Furthermore, a new discovery that presents the significant impact of stability of M/G/1 queue manifold and the continuity of the unique representation between M/G/1 queue manifold and Ricci Curvature Tensor (RCT). The information matrix exponential (IME) is devised. It is also shown that the obtained (IME) is unstable. Also, it is shown that stability of the devised (IME) enforces the instability of M/G/1 queue manifold. Unifying IG with Queueing Theory enables the study of dynamics of queueing system from a novel Riemannian Geometric (RG) point of view, leading to the analysis of the stable M/G/1 queue, based on the Theory of Relativity (TR).Extending the study over two new additional divergence measures, namely and together with a complete illustrative numerical results for all these measures including KD, JD. This links Queueing theory, IG with deep machine learning and metric learning. Furthermore, this reveals the revolutionary approach of queue learning. Full analytic study of Gaussian curvatures subject to both Angular and Monge techniques together with the overall stability dynamics impact on these curvatures. Full analytic study of Einestein Tensor and Stress Energy Tensor together with the overall stability dynamics impact on these curvatures. The inclusion of the definitions of Gaussian and Ricci, Ricci scalar curvatures and Einstein Tensor together with their physical interpretations; The proposed novel approach for the pioneer visualization of queueing systems via computational information geometry. The determination of new important links between classical queueing theory and other mathematical disciplines, such as IG, matrix theory Riemannian geometry and the THEORY OF RELATIVITY by providing for first time i) The full detailed derivations of the Gaussian curvature ii) The Ricci curvature tensor and iii) The full physical as well as the geometric interpretation of these new results. The provision of a novel link between Ricci Curvature (RCT) and the stability analysis of the stable M/G/1 QM. The full investigation of the newly introduced QT-IG unifiers together with the impact of stability/ instability of the underlying M/G/1 QM on them. The full investigation of the newly introduced (QIGU) unifiers together with the impact of stability/ instability of the underlying M/G/1 QM on them.

Using the potent tools of information geometry (IG), the current research analyses the information geometrics of the five-dimensional HTBFC Manifold. By enabling a unique revolutionary analysis for the performance of Human-Trust Based Feedback Control (HTBFC), the integration of information geometry into HTBFC facilitates the relativistic analysis of the five-dimensional HTBFC manifold. Both the two- and three-dimensional manifold subcases are investigated. This work provides a ground-breaking approach to IG unification of Human- Machine Interactions (HMIs). Some potential applications of HTBFC to robotics are presented.Conclusions are provided, along with some emerging open problems and recommendations for future research.

The current study characterizes the transient M/M/1 queue manifold info-geometrically, through devising Fisher Information matrix(FIM) and its inverse(IFIM). Additionally, the impact of stability on the existence of IFIM and explore the geodesic equations of motion has been revealed. More potentially, the paper discusses some info-geometric applications to Machine Learning are highlighted. Closing remarks with some challenging open problems combined with the next phase of research are given.

Prostate cancer (PC) is the second most diagnosed cancer among men. It was observed that early diagnosis of disease is highly beneficial for survival of cancer patients. Therefore, extension and increasing quality of life of PC patients can be achieved by broadening the Cancer Screening programs that are aimed at the identification of cancer manifestation in patients at earlier stages before they demonstrate well-understood signs of the disease. Therefore, there is an urgent need in standard, sensitive, robust, and commonly available screening and diagnosis tools for identification of early signs of cancer pathologies. In this respect, “Holy Grail” of cancer researchers and bioengineers for decades have been molecular sensing probes that would allow diagnosis, prognosis, and monitoring of cancer diseases by their interaction with cell-secreted and cellassociated PC biomarkers, e.g. PSA and PSMA correspondinly. At present, most PSA tests are performed at centralized laboratories using high throughput Total PSA immune analyzers which are suitable for dedicated laboratories and are not readily available for the broad health screening. Therefore, the current trend in detection of PC is developments of the portable biosensors for mobile laboratories and individual use. Phage display since its conception by George Smith in 1985 has emerged as a premier tool in molecular biology with widespread applications. This review describes how the paradigm of molecular evolution and phage display revolutionized the methods of early diagnosis and monitoring of PC.

Non-coding RNAs, specifically microRNAs (miRNAs), exhibit altered expression and contribute significantly to the pathological processes observed in numerous diseases, encompassing various types of human cancers. Recent discoveries regarding miRNAs underscore their crucial roles in tumor pathogenesis and their responses to diverse therapeutic interventions. miRNAs are a subset of non-coding RNAs that regulate the expression of a multitude of genes post-transcriptionally and thus are potential diagnostic, prognostic, and predictive biomarkers and have also emerged as potential therapeutics. Because miRNAs are involved in the post-transcriptional regulation of their target mRNAs via repressing gene expression, defects in the miRNA biogenesis pathway and miRNA expression perturb the expression of a multitude of oncogenic or tumor-suppressive target genes that are involved in the pathogenesis of various cancers. As such, numerous miRNAs have been identified to be downregulated or upregulated in many types of cancers functioning as either oncomiRs or oncosuppressor miRs. Moreover, dysregulation of miRNA biogenesis pathways can also change miRNA expression and function in cancer. Profiling deregulated miRNAs in many cancer types has been shown to correlate with disease diagnosis, indicate optimal treatment options, and predict response to a specific therapy. Specific miRNA signatures can track all stages of disease including many cancer types and hold potential as biomarkers and therapeutic targets as well as therapeutics as miRNA mimics and inhibitors (antagomirs). As such, identifying specific miRNAs and mRNAs they regulate in many types of cancer along with downstream pathways can be used as potential therapeutic targets. Because a single miRNA can regulate a pool of targets involved in similar cellular processes and pathways, thereby amplifying the cellular response, this potentially makes miRNAs powerful therapeutics to restore cell functions that are altered as part of a disease phenotype. However, because a single miRNA regulates multiple gene expressions their cellular effects are numerous leading to potential off-target effects. Besides their intended targeting issues, there is a need to reduce the immunogenic reactions and determine the minimal dosing to achieve the desired effect while minimizing side effects. As such, a careful risk evaluation of miRNA therapeutics is needed to minimize off-target effects and to avoid overdosing of miRNA drugs. Furthermore, a limited understanding and validation of the specific roles of miRNAs limits their clinical application. In addition, there are many challenges concerning the delivery, sensitivity, specificity, toxicity, and applicability of the potential utility of miRNAs as therapeutic targets or therapeutics. Thus, future work will warrant if miRNAs can be used as cancer biomarkers as well as therapeutics for clinical application.

In this paper, we will use the maximum likelihood estimation (MLE) and the Bayes methods to perform estimation procedures for the reliability of stress-strength ℜ=P[X>Y] based on independent adaptive progressive censored samples that were taken from the Chen distributions. An approximate confidence interval of ℜ is constructed using a variety of classical techniques, such as the normal approximation of the MLE, the normal approximation of the log-transformed MLE, and the percentile bootstrap (Boot-p) procedure. The Bayesian estimation of ℜ is obtained based on the balanced loss function, which comes in two versions here, the symmetric balanced squared error (BSE) loss function and the asymmetric balanced linear exponential (BLINEX) loss function. When estimating ℜ using the Bayesian approach, all the unknown parameters of the Chen distributions are assumed to be independently distributed and to have informative gamma priors. Further, a mixture of Gibbs sampling algorithm and Metropolis-Hastings algorithm is used to compute the Bayes estimate of ℜ and the associated highest posterior density credible interval. In the end, simulation research are used to assess the general overall performance of the proposed estimators and a real data set is provided to exemplify the theoretical results.

Photophysics properties such as fluorescence quenching, and photoexcitation dynamics of bimolecular non-covalent systems consisting of cationic poly[(9,9-di(3,3’-N,N’-trimethyl-ammonium) propyl fluorenyl-2,7-diyl)-alt-co-(9,9-dioctyl-fluorenyl-2,7-diyl)] diiodide salt (PFN) and anionic graphene carboxylate (GC) have been discovered for the first time by the steady state and time-resolved femtosecond transient absorption (TA) spectroscopy with broadband capabilities. The steady-state fluorescence of PFN is quenched with high efficiency by GC acceptor. Fluorescence lifetime measurements revealed that the quenching mechanism of PFN by GC is static. Here, the quenching mechanisms are well proven by TA spectra of PFN/GC systems. For PFN/GC systems, the photo electron transfer (PET) and charge recombination (CR) processes are ultrafast (within few tens of ps) related to static interactions whereas for PFN/DCB systems the PET takes place in few hundreds ps (217.50 ps)1 suggesting diffusion-controlled PET process. In the latter case, the PFN+•-DCB-• radical ion pairs as the result of PET from the PFN to DCB are clearly resolved and they are long-lived. The slow CR process (in 30 ns time scales)1 suggest PFN+• and DCB-• may already form separated radical ion pairs through charge separation (CS) process, which recombined back to the initial state with a characteristic time constant of 30 ns. The advantage of the present positively charged polyfluorene used in this work is the control over the electrostatic interactions and electron transfers in non-covalent polyfluorene/quencher systems in DMSO solution.

A single type I RC (Fe-S type, ferredoxin reducing) is found in several of the phyla of anoxygenic phototrophic bacteria. They include the heliobacteria (HB), the green sulfur bacteria (GSB) and the chloroacidobacteria (CAB), for which high-resolution homodimeric RC-PS structures have recently appeared [1-4]. The 2.2-Å Xray structure of the RC-PS of Heliomicrobium modesticaldum [1] revealed that the core PshA apoprotein (PshA1 and PshA2 homodimeric pair) exhibits a structurally conserved PSI arrangement comprised of five C-terminal transmembrane helices (TMHs) forming the RC domain and six N-terminal TMHs coordinating the light-harvesting (LH) pigments. The Hm. modesticaldum structure lacked quinones, indicating that electrons were transferred directly from the A0 (81-OH-chlorophyl (Chl) a) primary acceptor to the FX [4Fe4S] component, serving as the terminal RC acceptor. A pair of additional TMHs designated as Psh X were found, that function as a low-energy antennae. The 2.5Å resolution cryo-electron microscopy (cryo-EM) structure for the RC-PS of the GSB Chlorobaculum tepidum [2] included two Fenna-Matthews-Olson protein (FMO) antennae, which transfer excitations from the chlorosomes to the RC-PS (PscA1 and PscA2) core. Two cytochromes c (PscC) molecules were revealed, which act in series as electron donors to the photooxidized RC BChl a’ special pair, as well as PscB, housing the [4Fe-4S] cluster FA and FB, and the associated PscD protein [3]. Although their FMO components were missing from the 2.6-Å cyro-EM structure of the Zn-BChl a’ special pair containing RC-PS of Chloroacidobacterium thermophilum [4], a unique architecture was revealed that consisted of seven additional subunits including PscZ in place of PscD, the PscX and PscY cytochrome c serial electron donors and four low mol. wt. subunits of unknown function. Overall, these diverse structures have revealed that: (i) the HB RC-PS is the simplest light-energy transducing complex yet isolated, and represents the closest known homolog to a common homodimeric RC-PS ancestor; (ii) the symmetrically localized Ca2+binding sites found in each of the Type I homodimeric RC-PSs likely gave rise to the analogously positioned Mn4CaO5 cluster of the PSII RC and the TyrZ RC donor site; (iii) a close relationship between the GSB RC-PS and Chl protein (CP)43 and CP47 of PSII was demonstrated by the strongly conserved locations of their LH-(B)Chls; (iv) LH-BChls of the GSB-RC-PS are also localized in the conserved RC-associated positions of the PSII ChlZ-D1 and ChlZ-D2 sites; (v) glycosylated carotenoids of the GSB RC-PS are located in the homologous carotenoid-containing positions of PSII, reflecting an O2-tolerance mechanism capable of sustaining early stages in the evolution of oxygenic photosynthesis. In addition to the close relationships found between the homodimeric RC-PS and PSII, duplication of the gene encoding the ancestral Type I RC apoprotein, followed by genetic divergence my well account for the appearance of the heterodimeric Type I and Type II RC found in extant oxygenic phototrophs. Accordingly, the long-held view that PSII arose from the anoxygenic Type II RC is now supplanted by the new evidence provided by Type I RC-PS homodimer structures, indicating that the evolutionary origins of anoxygenic Type II RCs along with their distinct antenna rings are likely to have occured later than the events which gave rise to their oxygenic counterparts.

The aim of this article is to identify the best available evidences analyzing liver samples, normall and pathological. In the study were used liver samples, collected during necropsy, from healthy patients and from patients diagnosed with cirrhosis .This mentioned, are known as routinally practice for hepatitis C diagnosis, which conduct to hepatic cirrhosis. In this study direction, chronic liver diseases stimulate a degree of hepatocyte injury. So previously mentioned modifications, alters thet affect the liver architecture and finally ends in cirrhosis are well analyse on microscopic preparates. Folowing morphological steps, it is possible to analyse normal and alterate liver structure, on colored preparates.

Approximately 6% of adults worldwide suffer from peripheral artery disease (PAD) primarily caused by atherosclerosis of lower limb arteries. Despite optimal medicine and revascularization, many PAD patients remain symptomatic and progress to critical limb ischemia (CLI) and risk major amputation. Delivery of pro-angiogenic factors as proteins or DNA, stem or progenitor cells confers vascular regeneration and functional recovery in animal models of CLI, but the effects are not well replicated in patients and no pro-angiogenic biopharmacological procedures are approved in the US. The reasons are unclear, but animal models that do not represent clinical PAD/CLI are implicated. Consequently, it is unclear whether the obstacles to clinical success lie in the toxic biochemical milieu of human CLI, or in procedures that were optimized by inappropriate models. The question is significant because the former case requires abandonment of current strategies, while the latter encourages continued optimization. These issues are discussed in the context of relevant preclinical and clinical data, and it is concluded that preclinical mouse models that include age and atherosclerosis as the only comorbidities that are consistently present and active in clinical trial patients are essential to predict clinical success. Of the reviewed materials, no biopharmacological procedure that failed in clinical trials had been tested in animal models that included advanced age and atherosclerosis relevant to PAD/CLI.

Ethical behaviour tends to lead to welfare consideration of animals, but much less so for invertebrates. Indigenous tradition often valued all animals having an important role in the life on the planet, a practical application of modern ecology. The Judaeo-Christian-Islamic tradition postulated ‘man’ as having dominion over all the earth, resulting in anthropocentrism and careless practices. In contrast, the Buddhist/Hindu beliefs in rebirth leads to ahisma or doing no harm. In the face of capitalist systems, practice does not necessarily follow these beliefs, especially in the ‘shepherding’ of domestic animals. Only the Jainist beliefs value the lives of all invertebrates. Philosophers are often divorced from the physiological reality of the animals they muse about and science’s traditions of objectivity and the simplest possible explanation of behaviour led to ignorance of invertebrates’ abilities. With the new information about sentience in some of these animals, moral standing and welfare consideration has sometimes been extended to invertebrates, but we have a long distance to go to consider recognition and care of all these 97% of the animals on the planet.

The signs and symptoms of Long COVID can be explained by a shortage of blood in the body and a resulting deficient blood flow through nearly all organs. This shortage arose during the acute phase of COVID19 by an increased breakdown of haematocytes, to which the liver responds by reducing the production of plasma, in order to prevent a too large decrease in haematocrit. In order to ensure the perfusion of organs that are directly necessary for survival, the body takes the emergency measure of diverting blood from other organs and tissues. The perfusion of the blood-producing organs is also affected by this distribution measure, which hinders the smooth recovery of the total blood volume. The body is stuck in this vicious circle: a shortage of circulating blood hinders the recovery of blood production. This explains the long duration of Long COVID. My proposed treatment of Long COVID focuses on the recovery of the correct volume of blood in the body of the right composition by the intravenous administration of donor blood products, starting with albumin concentrate. A trial treatment can be performed in any hospital without much additional preparations, and has a lower associated risk for the patient than analysing the total blood. A diagnosis ex juvantibus, by therapeutic response, is therefore preferable. I suspect that we will find a haematocrit value at the high extreme of the reference range, and an albumin value at the low extreme of the reference range in most Long COVID patients before the start of the treatment, because the liver can not keep up with the recovery of the red bone marrow.

The classical joint economic lot-sizing (JELS) policy in a single-vendor single-buyer system generates an equal production quantity in all cycles, where the input parameters remain static indefinitely. In this paper, a new two-echelon supply chain inventory model is developed involving a hybrid production system that simultaneously focuses on green and regular production methods with optimal allocation fraction of green and regular productions. Unlike the classical mathematical formulation, each cycle is independent from the previous one, and consequently, the input parameters can be adjusted to be responsive to the dynamic nature of demand rate and price fluctuation. A rigorous heuristic approach is used to derive a global optimal solution for a joint hybrid production system. The model accounts for carbon emissions from production and storage activities related to green and regular produced items along with transportation activity under a multi-level emission-taxing scheme. The results emphasize the significant impact of green production on emissions. That is, the higher the allocation fraction of green production the lower the total amount of emissions generated by the system, i.e., the system becoming more sustainable. Adopting a hybrid production method not only decreases the greenhouse gas (GHG) emissions dramatically, but also reduces the per unit time total cost when compared with regular production. One of the main findings is that the total system cost generated by the base closed-form formula of the proposed model is considerably lower than that of the existing literature i.e., 33.59% (16.13%) lower in the first cycle (subsequent cycles) when the regular production method is assumed. Moreover, the optimal production rate generated by the proposed model is the one that minimizes the emissions production function. Illustrative examples and special cases that reflect different realistic situations are compared to outline managerial insights.

Life on Earth evolved to accommodate the biochemical and biophysical boundary conditions of the planet millions of years ago. The former includes nutrients, water, and ability to synthesize other needed chemicals. The latter include the 1 g gravity of the planet, radiation, and the geomagnetic field (GMF)of the planet. How complex life forms have accommodated the GMF is not known in detail considering that Homo sapiens evolved a neuro system and a cardiovascular system that develops electromagnetic fields as part of their functioning. In addition, many proteins and physiologic processes utilize Fe ions, an ion that exhibits magnetic properties. Thus, complex organisms such as current humans generate magnetic fields, contain significant quantities of the Fe ion, and also respond to exogenous-supplied static and electromagnetic fields. Whether humans can store information in self-generated magnetic fields remains to be determined. Given the current body of literature, it remains somewhat unclear how Homo sapiens use exogenous magnetic fields to regulate function, and what can happen if the boundary condition of the GMF of Earth is no longer exerting an effect. Proposed deep space flights to destinations such as Mars will provide some insights as space flight could not have been anticipated by evolution. The results of such space flight “experiments” will provide new insights in the role of magnetic fields on human functioning. The outcomes may also have implications for those on Earth as magnetic field influences may play a role in developmental conditions such as autism and senescence-associated conditions such as dementia when integration of the biological and biophysical aspects of humans of humans are required for effective functioning. This review will discuss the involvement of magnetic fields on various normal and disturbed processes in humans while on Earth and then further discuss potential outcomes when the GMF is no longer available to impact host systems. Thus, the GMF of the Earth has been present throughout evolution but details of its role in human functions still remain to be elucidated.

The effects of wastewater step-feeding on the performance of Horizontal Subsurface Flow Constructed Wetlands (HSF CWs) are numerically investigated. The purpose is to check if this alternative feeding technique increases the ability of HSF CWs to remove pollutants. Two methodologies are used: Initially, the Tanks-In-series (TIS) methodology, based on Finite Volume Method (FVM), is analyzed by using the volumetric degradation coefficient λ. In this case the operation of CW is similar with a series of Continuous Stirred-Tank Reactors (CSTR), under steady conditions. Then, the Step-Feeding (SF) procedure is presented, when the CW is operated like a Plug Flow Reactor (PFR). The results show that the SF procedure does not improve the performance of HSF CWs on removing Biochemical Oxygen Demand (BOD), operating under Mediterranean conditions.

Matrix-variate Gaussian type or Wishart type distributions in the real domain are widely used in the literature. When the exponential trace has an arbitrary power and when a factor involving a determinant enters into the model or a matrix-variate gamma type or Wishart type model with exponential trace having an arbitrary power, is extremely difficult to handle. Evaluation of the normalizing constant in such a model is the most important part because when studying the properties of such a model, the method used in the evaluation of the normalizing constant will be the relevant steps in all the computations involved. One such model with a factor involving a trace and the exponential trace having an arbitrary power, in the real domain, is known in the literature as Kotz' model. No explicit evaluation of the normalizing constant in the model involving trace with an exponent and determinant with an exponent entering into the model and at the same time the exponential trace having an arbitrary exponent seems to be available in the literature. The normalizing constant widely used in the literature and interpreted as the normalizing constant in the general model and refers to as a Kotz' model does not seem to be correct. Corresponding model in the complex domain, with the correct normalizing constant, does not seem to be available in the literature. One of the main contributions in this paper is the matrix-variate distributions in the complex domain belonging to Gaussian type, gamma type, type-1 and type-2 beta type when the exponential trace has an arbitrary power. All these models are believed to be new. A second main contribution is the explicit evaluation of the the normalizing constants, in the real and complex domains especially in the complex domain, in a matrix-variate model involving a determinant and a trace as multiplicative factors and at the same time the exponential trace having an arbitrary power. Another main contribution is the introduction of matrix-variate models with exponential trace having an arbitrary exponent, in the categories of type-1 beta, type-2 beta and gamma distributions or in the family of Mathai's pathway models [1], both in the real and complex domains. Another new contribution is the logistic-based extensions of models in the real and complex domains with exponential trace having an arbitrary exponent and connecting to extended zeta functions introduced by this author recently. Some properties of such models are indicated but not derived in detail in order to limit the size of the paper. The techniques and steps used at various stages in this paper will be highly useful for people working in multivariate statistical analysis as well as people applying such models in engineering problems, communication theory, quantum physics and related areas, apart from statistical applications.

Attention Deficit Hyperactivity Disorder (ADHD) it is known as a neuropsychiatric disorder. Anatomicaly components with implications in this previously mentioned disorder, are the anterior cingulate gyrus and dorsolateral prefrontal cortex (DLFPC) that are are found having a role in appearing this disease. ADHD is associated with cognitive and functional deficits that relate to diffuse abnormalities in the brain. ADHD is a specific pathology in children but may persisit to youth and also not so hard to find to adults.Till now, hard to find the curative treatment knowing ADHD as a neuropsychiatric disorder with enlarge unknown scientific points. Genetic and environmental component play an important role in diagnosis. Patients life style, a relevant history of individual geneticsand environmental factors are important in diagnosisThe management of ADHD, is also an important part togeter with future trends.

Geothermal energy aims at harnessing the heat of the Earth to produce energy, from the near-surface to great depths. Emphasis is put on geothermal reservoirs in crystalline rocks, hence vol-canic islands and crystalline basements of sedimentary basins based on three examples world-wide. Hot brines circulate in those rocks and are responsible for their hydrothermal alteration because of fluid-rock interactions. This includes dissolution of preexisting minerals and crystal-lization of newly formed ones which provide many information of crucial importance for a better exploration of those reservoirs. For example, the crystallization of clay minerals results from the dissolution of preexisting minerals (feldspar and ferro-magnesian minerals in plutonic, volcanic or metamorphic rocks) or from the direct precipitation from geothermal brines, in specific condi-tions. Clay minerals are found in both the geothermal reservoirs and in the clay-cap found above them. Other newly formed minerals such as quartz, carbonates or sulfates have also recorded the conditions of temperature and salinity encountered by fossil reservoirs which can be evaluated thanks to the study of fluid inclusions trapped during their crystallization. This paper presents results from several geothermal deep sites and surface analogues to pinpoint the role played by newly-formed minerals in the characterization of geothermal reservoirs and their cap-rock.

Methicillin-resistant Staphylococcus aureus (MRSA) exerts a considerable concern in healthcare and the community. Globally MRSA strains cause numerous infections with high morbidity and mortality rates. The success of MRSA is a result of the extensive production of virulence factors. With the limited treatment options for the MRSA infection and growing resistance problem, an urgent call is needed to search for an alternative to antibiotics. One of the promising strategies is targeting the quorum sensing (QS) system, of the MRSA, by using a dendrimer loaded with kinase inhibitor peptide. This study formulates a poly-amidoamine dendrimers (PAMAM) G4 dendrimers loaded with Quorum Quencher (QQ), QQ3 peptide which is a Histidine Kinase inhibitor. The physicochemical properties of the formula were characterized using different in-vitro analysis method such as Zetasizer and transmission electron microscope (TEM). The antibacterial activity and anti-virulence effect of the formula was tested against MRSA and different mutant stains using growth assay, haemolysis assay and biofilm assay. Overall, QQ3-G4 complex showed antibacterial and anti-virulence activity and it can be a potential alternative treatment to overcome antimicrobial resistance and treat MRSA infection.

The falling cost of cameras, the advancement of AI based computer vision algorithms, and powerful hardware accelerators for deep learning have enabled wide-spread deployment of surveillance cameras with the ability to automatically analyze streaming video feeds to detect events of interest. While streaming video analytics is currently largely done in the cloud, edge computing has emerged as a pivotal component due to its advantages of low latency, reduced bandwidth, and enhanced privacy. However, a distinct gap persists between the state-of-the-art computer vision algorithms, and successful practical implementation of edge-based streaming video analytics systems. This paper presents a comprehensive review of more than 30 research papers published over the last 6 years on edge video analytics systems. The papers are analyzed across 17 distinct dimensions. Unlike prior reviews, we examine each system holistically, identifying their strengths and weaknesses in diverse implementations. Our findings suggest that certain critical topics necessary for the practical realization of edge video analytics systems are not sufficiently addressed in current research. Based on these observations, we propose research trajectories across short, medium, and long term horizons. Additionally, we explore trending topics in other computing areas that can significantly impact the field of edge video analytics.

A text obtained by a Large Language Model (LLM) such as GPT4 usually has issues in terms of incorrectness and hallucinations. We build a fact-checking system 'Truth-O-Meter' which identifies wrong facts, comparing the generation results with the web and other sources of information, and suggests corrections. Text mining and web mining techniques are leveraged to identify correct corresponding sentences; also, the syntactic and semantic generalization procedure adopted to the content improvement task. To handle inconsistent sources while fact-checking, we rely on an argumentation analysis in the form of defeasible logic programming. We compare our fact checking engine with competitive approach based on reinforcement learning on top of LLM or token-based hallucination detection. It is observed that LLM content can be substantially improved for factual correctness and meaningfulness.

Immunology is a branch of medicine that studies the immune system and its pathology. There are known scientific informations, that in medical immunology specific tests performed in the laboratory for diagnosis. In addition good to mention that allergies include medical diagnostic methods such as blood tests. Also there are used for detection the presence and the levels of IgE antibodies. These antibodies are produced by the human immune system in contact with certain allergens. Examples of allergens include for example pollen, house dust, some herbs or molds, some animals and certain foods. If a person has an allergy, their immune system overreacts to an allergen by producing antibodies, called Immunoglobulin E (IgE). Currently within the present describtion aim to discuss some aspects reffering to fungal allergen and mold allergy diagnosis, in a briefly following steps of our purposed shortly review.

Ptolemy’s Theorem in Euclidean geometry, named after the Greek astronomer and mathematician Claudius Ptolemy, is well known. We translate Ptolemy’s Theorem from analytic Euclidean geometry into the Poincar´e ball model of analytic hyperbolic geometry, which is based on M¨obius addition. The translation of Ptolemy’s Theorem from Euclidean geometry into hyperbolic geometry is achieved by means of the hyperbolic trigonometry, called gyrotrigonometry, to which the Poincar´e ball model gives rise, and by means of the duality of trigonometry and gyrotrigonometry.

Glioblastoma is considered the most aggressive primary brain tumor. Recurrence after treatment is a significant problem with a failed response to optimal therapies. The recurrence of GBM is linked to different cellular pathways and molecular pathways. Not only genetics are involved in gliomagenesis, but also epigenetics. Epigenetic mechanisms are highly involved in the pathogenesis of GBM. Histone modulation through acetylation, phosphorylation, ubiquitination, and methylation can regulate gene expression and may play a role in the pathogenesis of GBM. Preclinical and clinical studies currently target epigenetic enzymes in gliomas, including a new generation of histone deacetylase (HDAC) inhibitors. Herein, I tried to highlight the current research in glioma epigenetics, focusing on the culprit of histone modifications and the use of HDAC target therapies as a possible treatment line for glioblastoma.

Primary carcinomas of the lung are vastly represented by the conventional types of adenocarcinomas or squamous cell carcinomas. However, there are other types of non-small cell carcinomas that although uncommon represent a meaningful group that often pose a problem not only in diagnosis but also in classification. Spindle and giant cell carcinomas although uncommon primary lung carcinomas are well known to occur. Important to highlight is that current criteria are rather ambiguous and likely not up to date, which renders the classification of these tumors somewhat more obscure. In addition, with the daily use of immunohistochemical stains, the classification of these tumors may also pose a different problem in the proper allocation of these tumors. Proper classification is highly important in the selection process that takes place using such material for molecular analysis. Current molecular characteristics of these tumors is limited and lacks more in-depth studies and analysis that can provide specific targets for the treatment of patients with these tumors. The current review attempts to highlight the shortcomings in the current classification and definitions of these neoplasms as well as the more current view regarding these tumors when the use of immunohistochemical stains is employed.

We have revised the problem of the motion of a heavy symmetric top. When formulating equations of motion of the Lagrange top with the diagonal inertia tensor, the potential energy has more complicated form as compared with that assumed in the literature on dynamics of a rigid body. Using the Liouville's theorem, we solve the improved equations in quadratures and present the explicit expressions for the resulting elliptic integrals.

The mathematical modelling of reverse logistics inventory systems ignores that returned items may arrive out of sequence, i.e. with different number of remanufacturing times. Moreover, such modelling assumes that the retuned items may retain the same quality upon recovery regardless of how many times they have been previously remanufactured. This paper develops a new mathematical expression of the percentage of retuned items that can be remanufactured a finite number of times. The proposed expression is modelled as a function of the expected number of times an item can be remanufactured on its life cycle and the number of times an item can be technologically (or optimally) remanufactured based on its quality upon recovery. The model developed in this paper considers joint production and remanufacturing options. The return rate is a varying demand dependent rate, which is a decision variable with demand, product deterioration, manufacturing and remanufacturing rates being arbitrary functions of time. The model considers the initial inventory of returned items in the mathematical formulation, which enables decision makers to adjust all functions and input parameters for subsequent cycles. Illustrative examples indicate that dependent purchasing price of recovery items and the incorporation of remanufacturing investment cost significantly impact on the optimal remanufacturing policy.

Bronchial asthma (BA) is considered a chronic inflammatory disorder associated with airway hyperresponsiveness (AHR). Increased oxidative stress (OS) is a clinical feature of BA, which promotes the inflammatory responses in bronchial/airway epithelial cells. Smokers and nonsmokers with asthma have been shown to have increases in several OS and inflammatory biomarkers. A few studies suggest a relationship between antioxidant intake from diet/supplements and BA in smoking and nonsmoking asthmatics. Dietary carotenoids and vitamin C (VC) intake might reduce BA risk in smokers and/or non-smokers. Evidence is lacking on the protective role of antioxidant vitamin and/or mineral consumption against BA in smokers and nonsmokers with respect to inflammation and OS biomarkers. Therefore, the aim of this review is to highlight current knowledge regarding the relations between antioxidant intake, BA and its associated biomarkers in smokers and nonsmokers.

In this work, an analytical and numerical analysis of the transition to chaos in five nonlinear systems of ordinary and partial differential equations, which are models of the autocatalytic chemical processes and the numbers of interacting populations, is carried out. It is analytically and numerically shown that in all considered systems of equations, further complication of the dynamics of solutions and the transition to chemical and biological turbulence is carried out in full accordance with the universal Feigenbaum-Sharkovsky-Magnitskii bifurcation theory through subharmonic and homoclinic cascades of bifurcations of stable limit cycles. In this case, irregular (chaotic) attractors in all cases are exclusively singular attractors in the sense of the FShM theory.

The phenomenon of dissipative self-organization is studied on the example of time-crystal networks. Particular attention was given to transient processes, attractor topologies, phase transitions, and asymptotic stability. New concepts were introduced, including topological phases, spinorial states, and bond flavors. Concepts such as ground states, chemical potentials, elastic forces, temperature, and statistical distributions were endowed with a new meaning associated with asymptotic stability. Phenomena usually attributed exclusively to quantum physics have been shown to occur in this essentially classical environment. They coexist with, and in some cases, such as charge quantization, are related to the phenomenon of time dilation. The approach was applied to model vacuum self-organization. We have shown that under the ac-tion of competing forces, such as gravity and antigravity, a cascade of phase transitions can transform an unorganized vacuum into phases in which interactions, fields and waves resemble electromagnetic, weak, and strong, and their elements can be used as building blocks for prototype particles. In addition, some interrelation field parameters and probabilities of particle transmutations were calculated, which are not predicted by the standard model. The results are consistent with the experiment. The presented material and methodology may be of interest for studying self-organization in different environments.

The effect of elastic constants, cij, on the nature (easy or difficult) of a cleavage system in YBa2Cu3O7−δ is investigated, by employing a novel three-dimensional eigenfunction expansion technique, based in part on separation of the thickness-variable and partly a modified Frobenius type series expansion technique in conjunction with the Eshelby-Stroh formalism. Out of the available three complete sets of elastic constants, the first constitutes an estimate, while the second assumes tetragonal symmetry. This leaves only the experimental measurements by resonant ultrasound spectroscopy, despite reported values of c12 and to a lesser extent, c66, being excessively high. The present investigation considers six through-thickness crack systems weakening orthorhombic YBCO mon-crystalline plates. More important, the present approach predicts whether a crack would propagate in its original plane/direction or deflect to a different one. This fracture mechanics criterion is then employed for accurate determination of the full set of elastic constants of mono-crystalline YBCO. Finally, generally unavailable results, pertaining to the through-thickness variations of stress intensity factors and energy release rates for a crack corresponding to symmetric and skew-symmetric hyperbolic cosine loads that also satisfy the boundary conditions on the bounding surfaces of an orthorhombic monocrystalline plate bridge a longstanding gap in the field.

Vitamin K occupies a unique and often obscured place among its fellow fat-soluble vitamins. Evidence is mounting however, that vitamin K (VK) may play an important role in the visual system apart from the hepatic carboxylation of hemostatic related proteins. However, to our knowledge, no review covering the topic has appeared in the medical literature. Recent studies have confirmed that matrix Gla protein (MGP), a vitamin K-dependent protein (VKDP), is essential for the regulation of intraocular pressure in the mouse. The PREDIMED (Prevención con Dieta Mediterránea) study, a randomized trial involving 5860 adults at risk for cardiovascular disease, demonstrated a 29% reduction in the risk of cataract surgery in participants with the highest tertile of dietary vitamin K1 (PK) intake compared with the lowest tertile. However, the specific requirements of the eye and visual system (EVS) for VK, and what might constitute an optimized VK status, is currently unknown and largely unexplored. It is the intention therefore of this narrative review to provide an introduction concerning VK and the visual system, review ocular VK biology, and to provide some historical context to recent discoveries. Potential opportunities and gaps in current research efforts will be touched upon, in the hope of raising awareness, and encouraging continued VK related investigations in this important and highly specialized sensory system.

This paper presents a simple drone survey and image processing approach to identifying St. John's wort (Hypericum perforatum) on grazing land in the Hunter Valley NSW, Australia. St John’s wort is an invasive species (weed) that competes with pasture, poisons livestock, can downgrade wool with ‘vegetable fault’, and decreases property values. Identifying the locations of St John wort from the ground can be difficult due to topography, limited access, and/or larger land areas of mixed vegetation. In this study, a drone was used to survey a 174-ha grazing property in the Hunter Valley NSW (Australia). The images were stitched together using commercially available software. A unique Visual Atmospheric Resistance Index (VARI) attribute was identified and used to highlight the presence of St John’s wort in the survey area. These sub-areas were then digitised onto high resolution maps for future planning use by land managers.

In this review, several cost-effective thin-film coating methods which include dip-coating, spin-coating, spray-coating, blade-coating, and roll-coating are presented. Each method has its set of advantages and disadvantages depending on the type of application. Not all of them are appropriate for large-scale production due to their certain limitations. That is why the coating method should be selected based on the type and size of substrate including the resolution of the required thin-films. The sol-gel method offers several benefits, such as simplicity in fabrication, excellent film uniformity, the capacity to cover surfaces of any size and over vast areas, and a low processing temperature. Nevertheless, these coating methods are somewhat economical and well managed in low-budget laboratories. Moreover, the produced thin-films are homogeneous and have low-surface roughness. Furthermore, some other thin-film deposition methods such as physical vapor deposition (PVD) and chemical vapor deposition (CVD) are also discussed. Since CVD is not restricted to line-of-sight deposition, a characteristic shared by sputtering, evaporation, and other PVD processes, many manufacturing methods favor it. However, these techniques require sophisticated equipment and cleanroom facility. We aim to provide the pros and cons of thin-film coating methods and let the readers decide the suitable technique for their specific application.

We present a Quantum Space Model (QSM) of the evolution of the universe based on the theory that space consists of energy quanta from which it began. We used the Friedmann equations to trace its history and show that Dark Energy is the energy of space which caused its accelerating expansion.The universe started from a quanta of space which was triggered by quantum fluctuations that caused the Big Bang. It then expanded and cooled undergoing phase transitions to radiation, fundamental particles, and matter. Matter grew into galaxies, and was consolidated by gravity into Black Holes, ending in a Big Crunch and Deep Freeze inside a Black hole at 1.380 trillion years. Fluctuations caused a new Bang to start another cycle in its life. If the Law of Conservation of Energy is universal, then the cosmos is eternal. Our results support the theoretical predictions of a cyclic universe by Steinhardt and associates, as well as Penrose. Space and energy are equivalent as embodied in the Planck energy equation. They are the two most fundamental quantities that govern cosmic evolution. The two principal long range forces are the gravitational force and the space force,which maybe the fifth force in the universe. They provide the clockwork mechanism operating our cyclic universe.

Predation is a driving force of organismal ecology and evolution. Predator-prey interactions, constrained by other environmental factors and historical contingency, shape physical and behavioral phenotypes of organisms on both sides of the interaction arrow. Yet despite the universality of trophic interactions in biology, study of the ecology and evolution of anti-predator defense is challenging because these interactions tend to be brief and unpredictable, and thus gathering direct evidence requires patience and serendipity. The evolution of prey defenses can be studied by DNA sequencing followed by phylogenetic analysis, and the ecology can be studied by field observation and bringing tractable systems into the lab. However, animal models generally do not allow genetic manipulation, strict control of environmental variables, or detailed observation of evolution in real time, all of which are important for demonstrating evolutionary causes and consequences. Developing complementary microbial predator-prey systems can help overcome this hurdle. There is an extensive body of work on microbial experimental evolution, and many microbes come with well-characterized genomes and established methods for genetic manipulation. As understanding of microbial ecology and the mechanisms of their trophic interactions grows apace, these systems are poised to make valuable contributions to our understanding of how predator behaviors evolve, why certain anti-predator defenses evolve and not others, and how multiple defenses function together in a single defense portfolio. These systems will enable us to both test hypotheses formulated from the study of larger organisms and to propose new ones that can be tested in larger organisms with existing methods.

Three significant changes have occurred in the winter climate in Europe recently: increased UK flooding; Iberian drought; and warmer temperatures north of the Alps. The literature links all three to a persistent, significant increase in sea level pressure over Southern Europe, the Mediterranean, Iberia and the Eastern Atlantic (SEMIEA) which changes the atmospheric circulation system: forcing cold fronts to the north away from Iberia; and creating a south westerly flow around the northern perimeter of the high-pressure region bringing warmer, moist air from the subtropical Atlantic to the UK and Europe which increases precipitation in the UK and raises the temperature in Europe. I use the Last Millennium Ensemble, MERRA-2 and Terra-NCEP data to demonstrate that the extreme, anthropogenic, West African aerosol Plume (WAP) which only exists from December to April perturbs the northern, regional Hadley Circulation creating the high pressure in the SEMIEA. I also show that the anthropogenic WAP has only existed in its extreme form in recent decades as the two major sources of the WAP aerosols: biomass burning; and gas flaring have both increased significantly since 1950 due to: a four-fold increase in population; and gas flaring rising from zero to 7.4 billion m3/annum and note that this time span coincides with the changes in the three elements of the winter climate of Europe. I also suggest that it may be possible to eliminate the WAP and return the winter climate of Europe to its natural state after the crucial first step of recognising the cause of the changes is taken.

Applying a procedure similar to that of E.S. Bring, by using a 4^th degree Tschirnhaus transformation, it was possible to transform the Bring-Jerrard normal quintic (BJQ) equation into a De Moivre form (DMQ), so that it could be solved by radicals. The general solution by radicals of the De Moivre equations of any degree is presented. By the same procedure the BJSx (normal sextic) equation was taken to another one without the 2^nd, 4^th and 6^th terms which was transformed into a cubic (solvable) equation. By applying a 6^th degree Tschirnhaus transformation to the BJSp (normal septic) equation its binormal (without the 2^nd, 3^rd, 4^th and 5^th terms) form was obtained.

During cartilage development, the lineage commitment and condensation of stem cells into chondrocytes and their differentiation involves a ubiquitous signaling cascades and huge numbers of transcriptional factors. The kinetic requirements and the stoichiometry for the expression of key transcriptional factors are relevant and must be met to form proper and functionally competent cartilage tissue. More interestingly also, an exact and precise spatio-temporal distribution of these molecules are as necessary in the proper tissue morphogenesis and patterning as the relevant physical conditions and micro environmental forces playing at the background during embryogenesis. A milestone of experimental achievements has been obtained over the years on several signaling pathways involved in cartilage development. Several fate determining transcriptional factors has also been investigated and determined with regards to the transition of stem cells (pluripotent, embryonic, etc.) into chondrocytes. These transcriptional factors serve as master controllers in chondrocytes proliferation and hypertrophy. Concerns that variability in signaling and transcriptional factors have detrimental effect on cartilage formation and could potentiate most cartilage related diseases have led most scientists to investigate the role of signaling molecules and transcriptional factors implicated in osteoarthritis, rheumatoid arthritis, and other cartilage degenerative diseases. On bases of spatio-temporal distribution of transcriptional factors, there exist functional overlaps, hence, it is difficult to draw a hard line of demarcation of roles at each point of the cell’s life, nonetheless, it is also markedly established that some factors are skewed to the chondrocyte’ survival and proliferation, and others known for their master’s role in the cell’s apoptotic, necrotic and senescence. Here we review some published works on selected signaling pathways and transcriptional factors that are preferentially expressed in chondrogenic cells and their role as major players in cartilage formation, cartilage diseases, along with some highlights of unique signaling molecules that are indispensable in cartilage tissue regeneration and management.

Applying a procedure similar to that of E.S. Bring, by using a 4^th degree Tschirnhaus transformation, it was possible to transform the Bring-Jerrard normal quintic (BJQ) equation into a De Moivre form (DMQ), so that it could be solved by radicals. The general solution by radicals of the De Moivre equations of any degree is presented. By the same procedure the BJSx (normal sextic) equation was taken to another one without the 2^nd, 4^th and 6^th terms which was transformed into a cubic (solvable) equation. By applying a 6^th degree Tschirnhaus transformation to the BJSp (normal septic) equation its Bring-Jerrard binormal (without the 2^nd, 3^rd, 4^th and 5^th terms) form was obtained.

The deep neural network - BERT model (Bidirectional Encoder Representations from Transformers) and the stocks cumulative abnormal return is used in this article to analyze the sentiment of financial texts. The proposed approach, unlike those used so far, does not require the creation of dictionaries, takes into account the broad context of words and their meaning in financial texts, eliminates the problem of ambiguity of words in various contexts, does not require manual labelling of data and is free from the subjective assessment of the researcher. The sentiment of financial texts in the meaning presented in this paper is directly related to the market reaction to the information contained in these texts. For texts belonging to one of the two classes (positive or negative) with the highest probability the BERT model gives the results of predictions with a precision level of 62.38% for the positive class and 55% for the negative class. The results at this level can be used in event study, market efficiency research, investment strategy development or support of investment analysts using fundamental analysis.

We analyze the R + R2 model of quantum gravity where terms quadratic in the curvature tensor are added to the General Relativity action. This model was recently proved to be a self-consistent quantum theory of gravitation, being both renormalizable and unitary. The model can be made practically indistinguishable from General Relativity at astrophysical and cosmological scales by the proper choice of parameters.

The concentration of chlorophyll-a (chlor-a) is an important indicator of marine water quality, as it is considered an indicator of the phytoplankton density in a specific area. Remote sensing techniques have been developed to measure the near-surface concentration of chlor-a in water across the correlation between spectral bands and in situ data. This algorithm applies to sensors of varying spatial, temporal and spectral resolutions. However, in this study, chlor-a level 2 and 3 products of SNPP – VIIRS spectrometer (Equation OC3) of NASA OceanColor suite was relied upon to study the spatial and temporal distribution of chlor-a concentration in the Arabian Gulf (also known as the Persian Gulf) and the State of Kuwait’s water (located to the north-eastern part of the Arabian Gulf) from 2012 to 2019. Ground truthing points (n = 192) matched to the level 2 products have been used to build an empirical model and cross-validate it. The correlation was positive where was 0.79 and the validation RMSE was = ± 0.64 mg/m^-3. The derived algorithm was then applied to chlor-a level 3 seasonal products. Additionally, the chlor-a concentration values of Kuwaiti waters have been enhanced using the IDW algorithm to increase the spatial resolution, as it is considered as a small area compared to the spatial resolution of level 3 chlor-a products. The model derived from IDW was tested using the Mann Whitney test (Sig = 0.948 p > 0.01). However, the result showed that the chlor-a concentration is higher in Kuwait Bay compared to Kuwaiti water, and it is higher in Kuwaiti water compared to the Arabian Gulf. The coasts have higher concentrations too, when compared to the open water. Generally, the chlor-a increases in winter and makes a semi-regular cycle during the years of study; this cycle is more regular in the Gulf’s waters than in Kuwait’s.

Mucormycosis (previously called zygomycosis or phycomycosis), an aggressive, life-threatening infection is further aggravating the human health-impact of the devastating COVID-19 pandemic. Additionally, a great deal of mostly misleading discussion is focused also on the aggravation of the COVID-19 accrued impacts due to the white and yellow fungal diseases. In addition to the knowledge of important risk factors, modes of spread, pathogenesis and host defences, a critical discussion on the botanical insights into the main causative agents of mucormycosis in the current context is very imperative. Given above, in this paper: (i) general background of the mucormycosis and COVID-19 is briefly presented; (ii) overview of fungi is presented, the major beneficial and harmful fungi are highlighted; and also the major ways of fungal infections such as mycosis, mycotoxicosis, and mycetismus are enlightened; (iii) the major causative agents of mucormycosis are critically discussed; (iv) the systematic position, occurrence, structure, and the major modes of reproduction are summarized for Rhizopus sp. and Mucor sp., the major causative agents of mucormycosis; (v) the other causative agents of mucormycosis includes Cunninghamella bertholletiae, Apophysomyces elegans, Lichtheimia (Absidia), Saksenaea, and Rhizomucor pusillus are briefly introduced; (vi) facts related with the infection-misnomers based on fungi colour are also highlighted; and lastly, (vii) the major take-home message and clues for future research on the subject are listed.

We prove that it is necessary to introduce the non-zero gluon masses into the fundamental Lagrangian of Quantum Chromodynamics in order to describe the mass-gap in the reaction of electron-positron annihilation into hadrons. A new restriction on the gluon masses is obtained. The renormalized theory with non-zero Lagrangian gluon masses is constructed.

Tremendous progress has been witnessed in artificial intelligence within the domain of neural network backed deep learning systems and its applications. As we approach the post Moore’s Law era, the limit of semiconductor fabrication technology along with a rapid increase in data generation rates have lead to an impending growing challenge of tackling newer and more modern machine learning problems. In parallel, quantum computing has exhibited rapid development in recent years. Due to the potential of a quantum speedup, quantum based learning applications have become an area of significant interest, in hopes that we can leverage quantum systems to solve classical problems. In this work, we propose a quantum deep learning architecture; we demonstrate our quantum neural network architecture on tasks ranging from binary and multi-class classification to generative modelling. Powered by a modified quantum differentiation function along with a hybrid quantum-classic design, our architecture encodes the data with a reduced number of qubits and generates a quantum circuit, loading it onto a quantum platform where the model learns the optimal states iteratively. We conduct intensive experiments on both the local computing environment and IBM-Q quantum platform. The evaluation results demonstrate that our architecture is able to outperform Tensorflow-Quantum by up to 12.51% and 11.71% for a comparable classic deep neural network on the task of classification trained with the same network settings. Furthermore, our GAN architecture runs the discriminator and the generator purely on quantum hardware and utilizes the swap test on qubits to calculate the values of loss functions. In comparing our quantum GAN, we note our architecture is able to achieve similar performance with 98.5% reduction on the parameter set when compared to classical GANs. With the same number of parameters, additionally, QuGAN outperforms other quantum based GANs in the literature for up to 125.0% in terms of similarity between generated distributions and original data sets.

Research abounds in the literature on kinetic analyses using thermogravimetric (TG) runs. Many of these studies use approximations of integral or derivative forms of the kinetic law and all of them use programmed temperature, not the actual temperature measured by thermocouples close to the sample. In addition, it is common to conduct a single run in order to perform the calculation. Nevertheless, many authors consider that numerical methods should be used to analyse the kinetics of decomposition. In such cases, the actual temperature is used and, generally, several runs are fitted using the same kinetic parameters, giving robustness to the results. In the present work, a numerical integration procedure was discussed and applied to different examples. We focused on materials presenting a single decomposition curve as well as other materials with more complex processes. Different examples were explored, and the methodology was applied to a number of wastes such as coffee husks, polystyrene and polyethylene.

Despite the ongoing land administration reforms being implemented across sub-Saharan Africa (SSA), including Ghana as viable pathway to achieve tenure security and greater efficiency in land administration, the subject of land dispute resolution has received relatively less attention. Whereas customary tenure institutions play a central role in land administration (controlling ~80% of all land in Ghana), they remain at the fringes of the formal land dispute adjudicatory process. Recognizing the pivotal role traditional institutions as development agents and potential vehicles for promoting good land governance, recent discourse on land tenure have geared towards mainstreaming traditional land disputes institutions into the architecture of formal judicial process via alternative dispute resolution pathways. Yet little is known at least empirically as to the operations of traditional dispute resolution institutions in the contemporary context. This study therefore explores the importance of traditional dispute resolution institutions in the management of land-related disputes in southcentral and western Ghana. Drawing on data collated from 380 farming households operating 746 plots. The results show that contrary to the conventional thinking that traditional institutions are anachronistic and not fit for purpose, they remain strong and preferred forum for land dispute resolution (proving resilient and adaptable) given the changing socio-economic and tenurial conditions. Yet these forums have differing implications for different actors within the customary spheres accessing them. The results highlight practical ways for incorporating traditional dispute resolution in the overall land governance setup in Ghana and elsewhere in sub-Saharan Africa. This has implications for redesigning context-specific and appropriate land-use policy interventions that address local land dispute resolution.

The general coupling between particle transport and ionization-recombination processes in hot plasma is considered on the key concept of equilibrium charge state (CS) transport. A theoretical interpretation of particle and CS transport is gained in terms of a two-dimensional (2D) Markovian stochastic (random) processes, a discrete 2D Fokker-Plank-Kolmogorov equation (in charge and space variables) and generalized 2D coronal equilibrium between atomic processes and particle transport. The basic tool for analysis of CS equilibrium and transport is the equilibrium cell (EC) (two states on charge and two on space), which presents (i) a unit phase volume, (ii) the characteristic scale of local equilibrium, (iii) a comprehensive solution for the simplest nonlinear relations between transport and atomic processes. The approach opens up new perspectives on transport studies: (i) the direct modelling of equilibrium and transport of impurity using the atomic data base, (ii) recovery of the complete recombination rate profile based on knowledge of density profiles and ionization rate profiles, (iii) the local transport analysis, based on the reduction of the equilibrium set to the single EC (in particular, central or edge), (iv) analysis of the reduced transport coefficients (diffusion and convection) on the density profile measurements.

The paper describes an algorithm for semantic representation of behavioral contexts relative to a dichotomic decision alternative. The contexts are represented as quantum qubit states in two-dimensional Hilbert space visualized as points on the Bloch sphere. The azimuthal coordinate of this sphere functions as a one-dimensional semantic space in which the contexts are accommodated according to their subjective relevance to the considered uncertainty. The contexts are processed in triples defined by knowledge of a subject about a binary situational factor. The obtained triads of context representations function as stable cognitive structure at the same time allowing a subject to model probabilistically-variative behavior. The developed algorithm illustrates an approach for quantitative subjectively-semantic modeling of behavior based on conceptual and mathematical apparatus of quantum theory.

The structures of a number of dimers of sulphur dioxide and ozone have been optimized by means of a series of ab initio calculations. The dimer species have been classified as either genuine energy minima or transition states of first or higher order, and the most probable structures consistent with the experimental data have been confirmed. The molecular orbitals engaged in the interactions resulting in adduct formation have been identified and relations between the orbitals of the dimers of the valence isoelectronic monomer species examined. The vibrational spectra of the most probable structures have been computed, and compared with those reported in the literature, particularly with spectra observed in cryogenic matrices. The calculations have been extended to predict the properties of a number of possible heterodimers formed between sulphur dioxide and ozone.

Decades of research suggest that Mindfulness-Based Stress Reduction (MBSR) training supports a greater capacity to live with chronic medical conditions and contributes to lowering stress levels. This paper introduces a model for a Mindfulness-Based Recovery from Stroke (MBRfS) for promoting stroke recovery, informed by the lived experience of the author (a stroke survivor and certified MBSR instructor), the research literature regarding MBSR training, and the specific challenges of stroke recovery. Four themes emerged from the autoethnographic analysis that informed the proposed model: Readiness to accept the stroke event and the acquired brain injury; Navigating uncertainties of stroke recovery with awareness and self-responsibility for outcomes; Trusting the inherent wisdom of the body as a stroke recovery “teacher”; and Increased capacity to integrate complex emotions with self-compassion, and a sense of wholeness. A four component MBRfS model is offered, which consists of an integration amongst a modified MBSR framework, emergent attitudinal themes, and insights from the autoethnographic vignettes. The MBRfS model offers a path for providing participants with a supportive experience within stroke recovery. Recommendations and suggestions for future studies are offered to support the development of MBRfS for stroke survivors and their caregivers, as well as contributing to health care providers.

Publically available (own) transcriptomic data were re-analyzed to quantify the alteration of functional pathways in the thyroid cancer, establish the gene hierarchy, identify potential gene targets and predict the effects of their manipulation. The expression data were generated from one case of papillary thyroid carcinoma (PTC) and from genetically manipulated BCPAP (papillary) and 8505C (anaplastic) human thyroid cancer cell lines. The study used the genomic fabric perspective that considers the transcriptome as a multi-dimensional mathematical object based on the three independent characteristics that can be derived for each gene from the expression data. We found remarkable remodeling of the thyroid hormone synthesis, cell cycle, oxidative phosphorylation and apoptosis pathways. Serine peptidase inhibitor, Kunitz type, 2 (SPINT2) was identified as the Gene Master Regulator of the investigated PTC. The substantial increase of the expression synergism of SPINT2 with apoptosis genes in the cancer nodule with respect to the surrounding normal tissue (NOR) suggests that its experimental overexpression may force the PTC cells into apoptosis with negligible effect on the NOR cells. The predictive value of the expression coordination for the expression regulation was validated with data from 8505C and BCPAP cells before and after lentiviral transfection with DDX19B.

Many microbes live in habitats below their optimum temperature. Retention of metabolic heat by aggregation or insulation would boost growth. Generation of excess metabolic heat may also provide benefit. A cell that makes excess metabolic heat pays the cost of production, whereas the benefit may be shared by neighbors within a zone of local heat capture. Metabolic heat as a shareable public good raises interesting questions about conflict and cooperation of heat production and capture. Metabolic heat may also be deployed as a weapon. Species with greater thermotolerance gain by raising local temperature to outcompete less thermotolerant taxa. Metabolic heat may provide defense against bacteriophage attack, by analogy with fever in vertebrates. This article outlines the theory of metabolic heat in microbial conflict and cooperation, presenting several predictions for future study.

In [18], Kim et al. introduced the degenerate poly-Bernoulli polynomials by using polyexponential function. In this paper, we study the degenerate poly-Frobenius-Genocchi polynomials, which are called the type 2 degenerate poly-Frobenius-Genocchi polynomials, by means of polyexponential function. Then, we derive some useful relations and properties. We derive type 2 degenerate poly-Frobenius-Genocchi polynomials equal a linear combination of the degenerate Frobenius-Genocchi polynomials and Stirling numbers of the first kind. Furthermore, we introduce type 2 degenerate unipoly-Frobenius-Genocchi polynomials by means of unipoly function and derive explicit multifarious properties.

Purpose of this article is to project from the point of view of the scientific data concerning PAF and as a new approach by involving PAF, in order to contribute to clarification and proposal a possible mechanism of action of the coronavirus SARS-CoV-2 and to give a possible explanation for its observed side effects-complications of Covid-19 disease. The article is not intended to suggest any specific drugs, but clarifying the mechanism is the first step in illuminating the direction of prescribing the targets of medication that may be appropriate for the prevention, treatment, and cure of Covid-19 disease. More specifically, the purpose of this article is to provide unequivocal evidence indicating that: 1 It would not be unexpected for PAFR to participate in the entry of coronavirus SARS-CoV-2 into the cell. 2 There is interdependence and relationship of the receptors ACER and PAFR, which means the involvement of PAF in the processes related to coronavirus SARS-CoV-2 as well as to its effects exercised by the coronavirus SARS-CoV-2. 3 The receptors ACER, PAFR and TLRs are also involved in inflammation as well as in virus binding to stabilize and enter into the cell, and so they are "communicating vessels" with PAF being " a missing link" 4 Consequently there is a correlations of COVID-19 disease manifestations and biological characteristics with those caused by PAF, which shows the involvement of PAF in COVID-19 disease.

This preprint is focused in the presence of plastics and microplastics in food. We will discuss how many we eat, and how they arrive to the food, and why. We will treat many other things, such as the waste treatment in Europe and in Spain, with updated data; how much plastic waste is generated; what are microplastics and how they are analyzed, I will tell about the experience we have at the University of Alicante (UA); how they can be removed and we will estimate how many we eat over the course of a year.

Based on detection of elliptic particle tracks, $\simeq 137^2 n^2$ bigger than Bohr-Sommerfeld electron orbits, indicating the possible detection of superluminal electrons masquerading as magnetic monopoles, a new structure emerges leading to: (i) a new set of seven elementary lengths; (ii) replacement of the usual motion (Lorentz) transformations by scale transformations between $v^2<c^2$ and $v^2>c^2$ frames; (iii) equivalence of charge between $v^2<c^2$ and $v^2>c^2$ frames based on the Dirac-Schwinger quantization condition; (iv) a relativistic foundation for the Dirac-Schwinger quantization condition; (v) a possible cause of charge quantization; and (vi) the prospect of symmetry in Maxwell's equations. If the elliptic particle tracks are viewed as a magnification of electron orbits, the effect is suggestive of a spacetime distortion such as those predicted in general relativistic theories.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to cause 2019-coronavirus disease (COVID-19) pandemic is a zoonotic coronavirus and crosses species to infect human populations, where an efficient transmission of virus occurs human-to-human. Nationwide lockdown is being adopted to stop public transport, keep people at their homes and out of their work, and maintain social distancing. In turn, large geographic areas in the world (including China, Italy, Spain, and USA) has been almost halted. This temporary halt is significantly slashing down the air pollution (air pollutants and warming gases) in most cities across the world. This paper: (i) introduces both COVID-19 and air pollution; (ii) overviews the relation of air pollution with respiratory/lung diseases; (iii) compiles and highlights major data appeared in media and journals reporting lowering of air pollution in major cities those have been highly impacted by the COVID-19; and also (iv) lists the way forward in the present context. Because COVID-19 is an ongoing pandemic and currently far from over, strong conclusions could not be drawn with very limited data at present. The temporary slashed down global air pollution as a result of COVID-19 restrictions are expected to stimulate the researchers, policy makers and governments for the judicious use of resources; thereby minimise the global emissions, and maintain their economies once the pandemic eases. On the other, lifting of the nationwide lockdown and eventual normalisation of the temporarily halted sectors may also reverse the currently COVID-19 pandemic-led significantly slashed down global air pollution that could make the future respiratory health crisis grimmer.

The world is puzzling over the origin of the current outbreak of the coronavirus disease (COVID-19) that is caused by a novel coronavirus-2019 (2019-nCoV). As of 26^th March 2020, the World Health Organization has reported 46,2,684 confirmed cases and 20,834 confirmed deaths in total due to COVID-19. To this end, two unique mammals namely bats and pangolins are being investigated for their potential link to COVID-19. However, the evidence so far gathered in this context is far from clear. This paper aimed to: (i) enlighten the major aspects of life of bats and pangolins; (ii) briefly discusses their potential link to COVID-19; and also (iii) to highlight the way forward. The outcomes may contribute to future research on the subject.