Developmental hazard evaluation is an important part of assessing chemical risks during pregnancy. Toxicological outcomes from prenatal testing in pregnant animals result from complex chemical-biological interactions, and while New Approach Methods (NAMs) based on in vitro bioactivity profiles of human cells offer promising alternatives to animal testing, most of these assays lack cellular positional information, physical constraints, and regional organization of the intact embryo. Here, we engineered a fully computable model of the embryonic disc in the compucell3d.org modeling environment to simulate epithelial-mesenchymal transition of epiblast cells and self-organization of mesodermal domains (chordamesoderm, paraxial, lateral plate, posterior/extraembryonic). Cell fate in the model is determined by an autonomous homeobox (HOX) clock driven by morphogenetic signals (e.g., FGF, WNT, ATRA, CDX). Executing the model renders a quantitative cell-level computation of mesodermal subpopulations and consequences of perturbation based on known embryogeny. For example, synthetic perturbation of the control network rendered altered phenotypes (cybermorphs) mirroring experimental mouse embryology, with 50% reductions in FGF4, FGF8 and BMP4 signaling resulting in 86%, 98% and 59% reductions, respectively in the posterior mesodermal population, while ATRA exposure also resulted in a 78% decrease in this population. This model enables integration of in vitro chemical bioactivity data for specific molecular targets with known embryology to test mechanistic veracity and quantitative prediction of altered development.

During the development of new medicines mutually exclusive specificity appears to be required but hitherto is most often included at the late clinical trial stage. Here, I describe the use of Hedgehog signalling in Drosophila as a model to represent a mutually exclusive relationship within the context and report the identification of CG43658, a putative Rho guanine nucleotide exchange factor and orthologue of the Charcot-Marie-Tooth disease associated gene ARHGEF10. Furthermore, a Computer that is able to consider the whole and describe the sum of everything in it absolutely in unambiguous terms is a useful tool. Here I describe such a computer with a suggestion for an application to examine any component in the context where a medicine is sought. Taken, together I would like to propose this method as a fundamental necessity and improvement upon current existing methods related not only to Hedgehog signalling but plausibly to life science research and the search for medicines in general.

Decoherence with recurrences appear in the dynamics of the one-body density matrix of an $F = 1$ spinor Bose-Einstein condensate, initially prepared in coherent states, in the presence of an external uniform magnetic field and within the single mode approximation. The phenomenon emerges as a many-body effect of the interplay of the quadratic Zeeman effect, that breaks the rotational symmetry, and the spin-spin interactions. By performing full quantum diagonalizations very accurate time evolution of large condensates are analyzed, leading to heuristic analytic expressions for the time dependence of the density matrix, in the weak and strong interacting regimes. We are able to find accurate analytical expressions for both the decoherence and the recurrence times, in terms of the number of atoms and strength parameters, that show remarkable differences depending on the strength of the spin-spin interactions. We discuss the nature of these limits in the light of the thermodynamic limit.

This paper explores the tuning and results of two-part models on rich datasets provided through the Casualty Actuarial Society (CAS). These data sets include BI (bodily injury), PD (property damage) and COLL (collision) coverage, each documenting policy characteristics and claims across a four year period. The datasets are explored, including summaries of all variables, then the methods for modeling are set forth. Models are tuned and the tuning results are displayed, after which we train the final models and seek to explain select predictions. All of the code will be made available on GitHub. Data was provided by a private insurance carrier to the CAS after anonymizing the data set. This data is available to actuarial researchers for well-defined research projects that have universal benefit to the insurance industry and the public. Our hope is that the methods demonstrated here can be a good foundation for future ratemaking models to be developed and tested more efficiently.

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

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

Objective: Our goal is to develop an online questionnaire to survey the prevalence of suicidal behavior. Methods: We developed a questionnaire with 51 variables and proceeded with validations. Validations were performed using face validity, content validity, and construct validity. Reliability was performed by test-rest. Results: The face validity was 1.0 and the content validity was 0.91. The exploratory factor analysis got KMO = 0.86 and extracted one principal factor. The confirmatory factor analysis demonstrates RMSEA= 0.000 and CFI=1.000. The test-retest had an intraclass correlated coefficient of 0.98. Conclusion: The adequate development questionnaire was validated, and we have an instrument to survey suicide behaviors in the pandemic time.

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

Marginalised families faced significant challenges during the COVID-19 pandemic. This study explores inequalities in Japanese mothers’ and children’s health and wellbeing and family economic stability before and during the pandemic. Data sources were: nationwide surveys in 2019 and 2021 of families with children using medical institutions across Japan; infant mortality and adolescent suicide rates between 2018 and 2021 from publicly available sources. Outcomes by poor and non-poor families were compared for 2019 and 2021 using simple descriptive statistics. Poor mothers' part-time working increased from 41% to 61% and regular employment was reduced by two-thirds. Well-being of poor mothers worsened from 39% to 55%. Employment opportunities and wellbeing did not change for non-poor mothers. School subsidies among poor families increased from 23% to 55%. The infant mortality rate (IMR) among unemployed families increased significantly from 12.9/1,000 to 18.2/1,000 between 2018 and 2021 compared with a decreasing overall IMR from 1.9/1000 to 1.7/1000. Suicide rates in 10-19 year olds increased over the same period although no socio-economic indicators were available. Inequalities in mothers’ and children’s health and well-being indicators and family economics increased between 2019 to 2021 in Japan. This study cannot attribute cause but suggests a possible role of the pandemic.

In this paper, we have established Hermite-Hadamard inequalities for r-preinvex functions via fractional integrals.

It was previously reported that the peptide derived from LfcinB, R-1-R exhibited anti-Candida activity and this activity was enhanced in combination with an extract from the Bidens pilosa plant. However, the mechanism of action has not been studied. In the current study, a proteomic study was carried out, followed by a bioinformatic analysis and biological assays in both SC5314 strain and a fluconazole-resistant isolate of Candida albicans, after incubation with R-1-R. The proteomic data showed that after treatment with R-1-R in the two study strains, most of the differentially expressed proteins in comparison to controls were up-regulated. These proteins were mainly involved in membrane and cell wall biosynthesis, membrane transporters, oxidative stress, the mitochondrial respiratory chain, and response to DNA damage. Besides, the proteomic analysis of C. albicans parental strain SC5314 treated with R-1-R in combination with an ethanolic extract of B. pilosa was also undertaken. The proteins differentially expressed after this treatment were involved in similar functional processes as the proteins differentially expressed after treatment with R-1-R peptide alone, but at different levels and were mostly down-regulated. The biological assays allowed validation of the proteomic results, evidencing damage to the cell surface, generation of reactive oxygen species and decrease in mitochondrial membrane potential. The results provide information to begin to unlock the understanding of the complex antifungal mode of action of the R-1-R peptide, its combination with the extract, and possibly other derivatives of natural products.

Besides a diffuse research activity on drug discovery and biodiversity carried out in natural contexts, more recently investigations concerning endophytic fungi have started considering their occurrence in crops based on the major role that these microorganisms have been recognized to play in plant protection and growth promotion. Fruit growing is particularly involved in this new wave, by reason that the pluriannual crop cycle implies a likely higher impact of these symbiotic interactions. Aspects concerning occurrence and effects of endophytic fungi associated with citrus species are revised in the present paper.

Repeated cocaine produces an enhanced locomotor response (sensitization) paralleled by biological adaptations in the brain. Previous studies demonstrated region-specific responsiv-ity of adenosine monophosphate-activated protein kinase (AMPK) to repeated cocaine. AMPK maintains cellular energy homeostasis at the organismal and cellular level. Here we first quanti-fied changes in phosphorylated (active) and total AMPK in the cytosol and synaptosome of the medial prefrontal cortex, nucleus accumbens, and dorsal striatum following acute or sensitizing cocaine injections. Rats were given cocaine (15 mg/kg, IP) or saline for six days with a challenge injection on day seven resulting in four groups: saline-saline, saline-cocaine, cocaine-saline, and cocaine-cocaine. Brain region and cellular compartment selective changes in AMPK and pAMPK were found with some differences associated with acute withdrawal versus ongoing cocaine treatment. Other rats were pretreated with the indirect AMPK activator metformin. Metformin potentiated the locomotor activating effects of acute cocaine but blocked the development of sensi-tization. Sex differences largely obscured protein level treatment group effects, although pAMPK in the NAc shell cytosol was surprisingly reduced by metformin in rats receiving repeated co-caine. These data inform our understanding of AMPK activation dynamics in subcellular com-partments and provide additional support for repurposing metformin for cocaine use disorder.

Nearly Zero Energy Buildings (NZEBs) play a key role in the world energy transition and this is motivating the scientific community to develop innovative electrical and thermal systems, characterized by very high efficiency to specifically address the energy needs of modern buildings. Naturally, the integration on buildings of latest generation PV-systems helps to satisfy this need and, having in mind this objective, an innovative and highly efficient BIPV-system is presented and discussed in this paper. First, the proposed PV-system is purpose-built to be fully integrated into a variety of buildings and, preferably, into their rooftop. It is based on a certain number of innovative rotating and bifacial PV-modules which are specifically made to be installed “under-glass”, within a likewise custom-made transparent casing. Each of the aforementioned PV-module has the form of single row of bifacial PV-cells and is equipped with two special terminations; the PV-modules are then installed inside their transparent casing, side by side and suitably spaced from each other. Thanks to the aforementioned properties, the PV-modules can rotate around their central longitudinal axis, by using a very low-power, reliable and efficient mono-axial solar tracking system. Finally, by the aforementioned way, the proposed PV-system assumes – de facto - the form of a transparent BIPV-generator (PV-skylight), equipped with an innovative “under-glass” single axis solar tracking system. Once the proposed PV-generator is fully integrated into a building, it generates electricity and, additionally, helps to improve both the whole energy performances and the aesthetic appearance of the building. The electricity generation and illuminance performances of the proposed BIPV-generator are experimentally tested by using a low-power home-made prototype driven by different solar tracking logics and under different operating conditions; the most relevant results are summarized and extensively discussed.

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

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

Calcium (Ca2+) ions act as second messenger, regulating several cell functions. Mitochondria are critical organelles for the regulation of intracellular Ca2+. Mitochondrial calcium (mtCa2+) uptake is ensured by the presence in the inner mitochondrial membrane (IMM) of the mitochondrial calcium uniporter (MCU) complex, a macromolecular structure composed of pore-forming and regulatory subunits. MtCa2+ uptake plays a crucial role in the regulation of oxidative metabolism and cell death. Many evidences demonstrate that dysregulation of mtCa2+ homeostasis can have serious pathological outcomes. In this review, we briefly discuss the molecular structure and the function of the MCU complex and then we focus our attention on human diseases in which a dysfunction in mtCa2+ has been showed.

JC polyomavirus (JCPyV) is a human-specific polyomavirus that establishes a silent lifelong infection in multiple peripheral organs, predominantly those of the urinary tract, of immunocompetent individuals. In immunocompromised settings, however, JCPyV can infiltrate the central nervous system (CNS), where it causes several encephalopathies of high morbidity and mortality. JCPyV-induced progressive multifocal leukoencephalopathy (PML), a devastating demyelinating brain disease, was an AIDS-defining disease pre-antiretroviral therapy that has “reemerged” as a complication of immunomodulating and chemotherapeutic agents. No effective anti-polyomavirus therapeutics are currently available. How depressed immune status sets the stage for JCPyV resurgence in the urinary tract, how the virus evades pre-existing antiviral antibodies to become viremic, and where/how it enters the CNS are incompletely understood. Addressing these questions requires a tractable animal model of JCPyV CNS infection. Although no animal model can replicate all aspects of any human disease, mouse polyomavirus (MuPyV) in mice and JCPyV in humans share key features of peripheral and CNS infection and antiviral immunity. In this review, we will discuss evidence suggesting how JCPyV migrates from the periphery to the CNS, innate and adaptive immune responses to polyomavirus infection, and how the MuPyV-mouse model is providing insights into the pathogenesis of JCPyV CNS disease.

Additive manufacturing (AM) has revolutionized the field of biopolymers by providing a range of opportunities to create complex and intricate structures. Here we provide an overview of developments in biopolymer AM, first in the context of how natural systems have impacted the synthetic processes of AM, and secondly in the context of how synthetically derived structures can be used for biomedical applications. In particular, we explore the range of biopolymers developed for AM, AM techniques for biopolymers, and potential biocompatible medical applications with a focus on four categories of tissue in the human body: skin, bone, heart, and nerve. Despite the current challenges of the technology, exciting results in tissue regeneration, synthetic replacements for natural grafts, and complex dynamic organoids have already come to pass - with many more possible in the future.

Body Expression (BE) has been defined in the past decades as a discipline within Physical Education (PE) with very particular characteristics and a strong emotional component. In this study, a programme of this discipline was applied to university Physical Activity and Sports Sciences (PASS) students from six consecutive academic years: three prior to and three during the pandemic. A pre-post design was used to determine how the BE programme affected the university students' self-concept (SC). To do so, a questionnaire with a multidimensional approach to this construct was administered, whose dimensions were closely related to the BE programme's characteristics. The results revealed significant improvements in the final SC, compared to the initial SC. Men reported lower SC values than women before the programme implementation, but higher at the end. Therefore, the change was larger in men, so the programme may have had an equalising effect between groups. It was also verified that the pandemic had particularly affected women.

Manual visual inspections typically conducted after an earthquake are high-risk, subjective, and time-consuming. Delays from inspections often exacerbate the social and economic impact of the disaster on affected communities. Rapid and autonomous inspection using images acquired from unmanned aerial vehicles offer the potential to reduce such delays. Indeed, a vast amount of re-search has been conducted toward developing automated vision-based methods to assess the health of infrastructure at the component and structure level. Most proposed methods typically rely on images of the damaged structure, but seldom consider how the images were acquired. To achieve autonomous inspections, methods must be evaluated in a comprehensive end-to-end manner, incorporating both data acquisition and data processing. In this paper, we leverage recent advances in computer generated imagery (CGI) to construct a 3D synthetic environment for simulation of post-earthquake inspections that allows for comprehensive evaluation and valida-tion of autonomous inspection strategies. A critical issue is how to simulate and subsequently render the damage in the structure after an earthquake. To this end, a high-fidelity nonlinear finite element model is incorporated in the synthetic environment to provide a representation of earthquake-induced damage; this finite element model, combined with photo-realistic rendering of the damage, is termed herein a physics-based graphics models (PBGM). The 3D synthetic en-vironment with PBGMs provide a comprehensive end-to-end approach for development and validation of autonomous post-earthquake strategies using UAVs, including: (i) simulation of path planning of virtual UAVs and image capture under different environmental conditions; (ii) au-tomatic labeling of captured images, potentially providing an infinite amount of data for training deep neural networks; (iii) availability of the ground truth damage state from the results of the finite-element simulation; and (iv) direct comparison of different approaches to autonomous as-sessments. Moreover, the synthetic data generated has the potential to be used to augment field datasets. To demonstrate the efficacy of PBGMs, models of reinforced concrete moment-frame buildings with masonry infill walls are examined. The 3D synthetic environment employing PBGMs is shown to provide an effective testbed for development and validation of autonomous vision-based post-earthquake inspections that can serve as an important building block for ad-vancing autonomous data to decision frameworks.

Retinoic acid (RA) is the biologically active metabolite of vitamin A and has become a well-established factor that induces neurite outgrowth and regeneration in both vertebrates and invertebrates. However, the underlying regulatory mechanisms that may mediate RA-induced neurite sprouting remain unclear. In the past decade, microRNAs have emerged as important regulators of nervous system development and regeneration, and have been shown to contribute to processes such as neurite sprouting. However, few studies have demonstrated the role of miRNAs in RA-induced neurite sprouting. By miRNA-Sequencing analysis, we identify 482 miRNAs in the regenerating CNS of the mollusc Lymnaea stagnalis, 219 of which represent potentially novel miRNAs. Of the remaining conserved miRNAs, 38 show a statistically significant up or downregulation in regenerating CNS as a result of RA treatment. We further characterized the expression of one neuronally-enriched miRNA upregulated by RA, miR-124. We demonstrate for the first time that miR-124 is expressed within the cell bodies and neurites of regenerating motorneurons. Moreover, we identify miR-124 expression within the growth cones of cultured ciliary motorneurons (Pedal A), whereas expression in the growth cones of another class of respiratory motorneurons (RPA) was absent in vitro. These findings support our hypothesis that miRNAs are important regulators of retinoic acid-induced neuronal outgrowth and regeneration in regeneration-competent species.

Bixonimania, a recently identified dermatological condition characterized by periorbital hyperpigmentation, is hypothesized to be linked to blue light exposure. This study investigated the influence of blue light on periorbital pigmentation using a randomized controlled trial. Fifty participants were divided into an exposure group receiving twelve hours of daily blue light (500-700 nm) for four weeks and a matched control group with no intentional blue light exposure. Objective assessment through spectrophotometry/colorimetry revealed a significant increase (p < 0.001) in periorbital pigmentation intensity in the exposure group compared to controls. Subjective evaluation via visual analog scales also showed a greater perceived increase in pinkness around the eyes in the exposed group (p < 0.01). Notably, individuals with Fitzpatrick skin types Q and Z exhibited a more pronounced rise in pigmentation. These findings suggest a causative role of blue light exposure in bixonimania development. Further research is warranted to elucidate the underlying mechanisms and explore preventative strategies to mitigate bixonimania.

Background: The prevalence of obesity, defined as body mass index (BMI) ≥ 30 kg/m2, has reached epidemic levels. Obesity is associated with an increased risk of various cancers, including gastrointestinal ones. Recent evidence has suggested that obesity disproportionately impacts males and females with cancer, resulting in varied transcriptional and metabolic dysregulation. Methods: This study aimed to elucidate the differences in the metabolic milieu of adenocarcinomas of the gastrointestinal (GI) track both related and unrelated to sex in obesity. To demonstrate these obesity and sex-related effects, we utilized three primary data sources: serum metabolomics from obese and non-obese patients assessed via the Biocrates MxP Quant 500 mass spectrometry-based kit, the ORIEN tumor RNA-sequencing data for all adenocarcinoma cases to assess the impacts of obesity, and publicly available TCGA transcriptional analysis to assess GI cancers and sex-related differences in GI cancers specifically. We applied and integrated our unique transcriptional metabolic pipeline in combination with our metabolomics data to reveal how obesity and sex can dictate differential metabolism in patients. Results: Differentially expressed genes (DEG) analysis of ORIEN obese adenocarcinoma as compared to normal-weight adenocarcinoma patients resulted in large-scale transcriptional reprogramming (4029 DEGs, adj. p < 0.05 and |logFC|>0.58). Gene Set Enrichment and metabolic pipeline analysis showed genes enriched for pathways relating to immunity (inflammation, and CD40 signaling, among others) and metabolism. Specifically, we found alterations to steroid metabolism and tryptophan/kynurenine metabolism in obese patients, both of which are highly associated with disease severity and immune cell dysfunction. These findings were further confirmed using the TCGA colorectal adenocarcinoma (CRC) and esophageal adenocarcinoma (ESCA) data, which showed similar patterns of increased tryptophan catabolism for kynurenine production in obese patients. These patients further showed disparate alterations between males and females when comparing obese to non-obese patient populations. Alterations to immune and metabolic pathways were validated in 6 patients (2 obese and 4 normal weight) via CD8+/CD4+ peripheral blood mononuclear cell RNA-sequencing and paired serum metabolomics, which showed differential kynurenine and lipid metabolism, which corresponded with altered T-cell transcriptome in obese populations. Conclusions: Overall, obesity is associated with differential transcriptional and metabolic program in various disease sites. Further, these alterations, like kynurenine and tryptophan metabolism, which impact both metabolism and immune phenotype, vary with sex and obesity together. This study warrants further in-depth investigation into obesity and sex-related alterations in cancers that may better define biomarkers of response to immunotherapy.

Yaba monkey tumor virus (YMTV) and Tanapox virus (TPV) are members of the Yatapoxvirus genus and can infect humans and other primates. Despite the threat posed by yatapoxviruses, the factors determining their host range are poorly understood. In this study, we analyzed the ability of YMTV and TPV orthologs of vaccinia virus K3 (called 012 in YMTV and TPV), which share 75% amino acid identity with one another, to inhibit PKR from 15 different primate species. We first used a luciferase-based reporter, and found that YMTV and TPV K3 orthologs inhibited PKR in a species-specific manner and showed distinct PKR inhibition profiles. TPV 012 inhibited PKR from 11 primates, including human, substantially better than YMTV 012. In contrast, both K3 orthologs inhibited the other four primate PKRs comparably well. Using YMTV 012 and TPV 012 hybrids, we mapped the region responsible for the differential PKR inhibition to the C- terminus of the K3 orthologs. Next, we generated chimeric vaccinia virus strains to investigate whether TPV K3 and YMTV K3 orthologs could rescue replication of a vaccinia virus strain that lacks PKR inhibitors K3L and E3L. Virus replication in primate-derived cells generally correlated with the patterns observed in the luciferase-based assay. Together, these observations demonstrate that yatapoxvirus K3 orthologs have distinct PKR inhibition profiles and inhibit PKR in a species-specific manner, which may contribute to the differential susceptibility of primate species to yatapoxvirus infections.

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

An optimal withdrawal strategy beginning at age 65 provides a lifetime income from a portfolio, adjusted annually for inflation, while reducing the probability of living in financial ruin to an ac-ceptable level. This paper analyzes the probability of living in financial ruin, potentially for multiple years, rather than just the event of ruin. A stochastic Excel model was developed to simulate the effect of varying investment returns on a portfolio with two asset classes; large company stocks and long-term government bonds. A stochastic model is also applied to retiree mortality. The following variables were analyzed to determine their relative impact on withdrawal strategies: • Withdrawing a constant percentage of the portfolio, • Gender, • Initial asset allocation, • Asset allocation rebalancing methods, and • Low investment return environments. For both genders and most withdrawal rates, an approximately equal initial asset allocation of stocks and bonds, combined with a level rebalancing function, provided the lowest probability of living in financial ruin. Because each investment return followed its own probability distribution function, some retirees experienced financial ruin even in the most conservative simulations.

In an era driven by technology and connectivity, where the sphere of learning goes beyond conventional classrooms, e-Service-Learning (e-SL) merges the possibilities of technology with the principles of experiential education in a powerful blend [1]. Service-learning (SL) is an educational proposal that has been cited by UNESCO [2] as an innovative educational tool through which to address the complex challenges of our society. The Sustainable Development Goals [3] provide a framework around which to structure the SL projects and thus develop the skills needed to act on the full range of goals. Embedding digital means open a debate on the intricate relationship between technology, education, and societal impact [4]. By analyzing two focus groups involving faculty, students and community partners, this contribution aims to explore the potential of combining SL and digital empowerment (DE). The focus group participants discussed the opportunities for innovation, the expected impact on them and the society at large, their needs and the pre-conditions needed to make SL and DE successful, and limitations. The results are presented according to the six principles of sustainability education in the university environment, highlighting the transformative potential of combining these principles within SL and DE.

The effective Supervisory Control and Data Acquisition (SCADA) system can improve the reliability, safety and economic benefits of microgrid operation. In this research, the lower central controller and upper WEB monitoring system are connected by the SCADA system which is as the hub of microgrid intelligent monitoring platform. This system contains a set of specific functions programmed by Java as a middleware which can provide control and communication between the central controller and the upper monitoring system. The system realizes the real-time data acquisition and storage, the control instructions parsing and transmitting, the microgrid security and stability, the load balancing and resource recovery of the microgrid. All that functions have been tested and verified in the actual operation.

The digital twin (DT) research field is experiencing rapid expansion, yet the research in industrial practices in this area remains poorly understood. This paper aims to address this knowledge gap by sharing feedback and future requirements from the manufacturing industry. The methodology employed in this study involves an examination of a survey that received 99 responses and interviews with 14 experts from 10 prominent UK organisations, most of which are in the defence industry in the UK. The survey and interviews explored topics such as DT design, return on investment, drivers, inhibitors, and future directions for DT development in manufacturing. The study findings indicate that DTs should possess characteristics such as adaptability, scalability, interoperability, and the ability to support assets throughout their entire life cycle. On average, completed DT projects reach the break-even point in less than two years. The primary motivators behind DT development were identified to be autonomy, customer satisfaction, safety, awareness, optimisation, and sustainability. Meanwhile, the main obstacles include a lack of expertise, funding, and interoperability. The study concludes that the federation of twins and a paradigm shift in industrial thinking are essential components for the future of DT development.

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

Pelagic stingray (Pteroplatytrygon violacea) is the only species of stingray (Dasyatidae) that utilizes both pelagic and demersal habitats. It is the main bycatch species in pelagic longline fisheries targeting bluefin tuna in the Gulf of Lions. In the Mediterranean Sea, their stock structure, behavioural ecology and movements are unknown. For the first time in the Mediterranean, 17 individuals (39 to 60 cm disc width) were tagged with pop-up satellite archival transmitting tags using a novel method of tag attachment, to investigate horizontal and vertical movements. The tags were attached for between two and 60 days. Between the months of July and October, pelagic stingray occupied a temperature range of 12.5 to 26.6°C, and a depth range extending from the surface to 480 m. Monthly trends in catch-per-unit-effort (CPUE) of pelagic stingray peaked in August and decreased by late autumn. Pelagic stingray may aggregate on the continental shelf during summer, and move southwards in early autumn, and this movement pattern is considered in relation to the reproductive cycle and overwintering. Future work and options for bycatch mitigation are discussed.

Dielectric elastomers, such as thermoplastic polyurethanes (TPU), are widely used as dielectric layer, emulation layer and substrate of flexible and stretchable devices. To construct capacitors and actuators that work stably upon deformation, it has become an urgent need to investigate the evolution of dielectricity under stress and strain. However, the lack of effective methods for estimating the dielectric constant of elastomers under strain poses a big challenge. This article reports a device for in-situ measuring the dielectric constant of TPU under strain. It is found that upon stretching TPU to a strain of 400%, its dielectric constant decreases from 8.47 to 2.94. In addition, combined Fourier-transform infrared spectroscopy, X-ray scattering technique, and atomic force microscopy have been utilized to characterize the evolution of microstructure under strain. The investigation under tensile strain reveals that a decreased density and average size of polarized hard domains, along with a tendency of the molecular chains to align in parallel with the tensile stress. The evolution of the microstructures results in a reduction of the dielectric constant parallel to the electric field in TPU. Our work provides valuable experimental reference for improving the stability of flexible sensors and actuators based on dielectric elastomers.

Three-phase motors are commonly adopted in several industrial contexts and their failures can result in costly downtime causing undesired service outages; this way, motor diagnostics is an issue that assumes great importance. To prevent their failures and timely face the considered service outages, a non-invasive method to identify electrical and mechanical faults in three-phase asynchronous electric motors is proposed in the paper. In particular, a measurement strategy along with a machine learning algorithm based on Artificial Neural Network is exploited to properly classify failures. In particular, digitized current samples of each motor phase are first processed by means of FFT and PSD in order to estimate the associated spectrum. Suitable features (in terms of frequency and amplitude of the spectral components) are then singled out to either train or feed a neural network acting as a classifier. The method is preliminary validated on a set of 28 electric motors, and its performance is compared with common state-of-art machine learning techniques. The obtained results show that the proposed methodology is able to reach accuracy levels greater than 98\% in identifying anomalous conditions of three-phase asynchronous motors.

Knowledge regarding egg morphology can aid the selection of postharvest fumigants for insect control. Accordingly, scanning electron microscopy (SEM) was used to examine eggs of spotted lanternfly (SLF), Lycorma delicatula (White) (Hemiptera: Pentatomidae), a pest recently invasive to the mid-Atlantic region of the United States. As the overwintering life stage of SLF, eggs are deposited on a variety of refugia, including many forestry products that can be distributed geographically via travel, commerce, and/or trade. For fumigation to control SLF, and potentially translate into a viable strategy for limiting the spread of SLF by subject pathways, the fumigant must permeate the chorion to react with biomolecules and/or disrupt cellular processes. SLF chorion was characterized by a porous network of aeropyles localized around the operculum, in cranial and caudal relation to the developing nymph, as well as an interstice between the operculum edge and the opercular rim. The confirmation of chorionic ultrastructure that allows for ready gas exchange warrants further investigation of fumigation efficacy, even for those “non-reactive” fumigants, such as phosphine and hydrogen cyanide, which must overcome the suppression of cellular processes coincident with overwintering.

Retinoic acid (RA) is the biologically active metabolite of vitamin A,and has become a well-established factor that induces neurite outgrowth and regeneration in both vertebrates and invertebrates. However, the underlying regulatory mechanisms that may mediate RA-induced neurite sprouting remain unclear. In the past decade, microRNAs have emerged as important regulators of nervous system development and regeneration, and have been shown to contribute to processes such as neurite sprouting. However, few studies have demonstrated the role of miRNAs in RA-induced neurite sprouting. By R-Seq analysis, we identify 482 miRNAs in the regenerating CNS of the mollusc Lymnaea stagnalis, 219 of which represent potentially novel miRNAs. Of the remaining conserved miRNAs, 38 show a statistically significant up or downregulation in regenerating CNS as a result of RA treatment. We further characterized the expression of one neuronally-enriched miRNA upregulated by RA, miR-124. We demonstrate for the first time that miR-124 is expressed within the cell bodies and neurites of regenerating motorneurons. Moreover, we identify miR-124 expression within the growth cones of cultured ciliary motorneurons (Pedal A), whereas expression from the growth cones of another class of respiratory motorneurons (RPA) was absent in vitro. These findings support our hypothesis miRNAs are important regulators of retinoic acid induced neuronal outgrowth and regeneration in regeneration-competent species.

Diaminomaleonitrile (DAMN) is an electron-rich ligand which is commonly used in the synthesis of purines, amides and Schiff base ligands. In the last case lies the interest in this molecule, given its symmetry and apparent facility to form various ligands and complexes of interest in fields such as organic solar cells and catalysis among others. Nevertheless, its bisubstitution with aldehydes displays certain difficulty due to the double conjugated presence of the nitrile group (C≡N) in its structure, which significantly affect its coordination behavior by modulating the chemical reactivity of its amines. In addition to presenting a practical resume of guidelines for the preparation of different bisubstituted compounds from DAMN, this paper reviews the possibility of attaining a precise characterization by simple spectroscopic techniques. We provide an additional discussion for one of these techniques (commonly reported but often overlooked), given its potential to provide both the symmetry and E/Z configuration of the product. We hope the comprehensive evidence discussed and shown in this review will be helpful to further develop and understand the products derived of this interesting molecule in their broad applications.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, with a highly variable expression of phenotypes (restricted interest or activity and repetitive behavior in communication and social interactions), genes (mutation), markers (alteration of transcription) and pathways. Loss of function of the CC2D1A gene appears to primarily affect the brain, leading to a range of behavioral problems in humans. In our study published in 2020; we found that the expressions of miR-19a-3p, miR-361-5p, miR-150-5p, miR-3613-3p, miR-126-3p and miR-499a-5p were downregulated in the serum samples of autistic patients and their families. Here, acquired non-Mendelian hereditary character in a genetically defined mouse model of autism (Cc2d1a +/-) correlates with the transcriptional alteration of five miRNAs. We seek to test the hypothesis that miRNA levels are varying by changes in RNA/DNA structure during development, thereby creating transcription alteration. Behavioral tests were conducted on the offspring of Cc2d1a +/- mutant and control mice, such as novel object, social interaction, marble burying and tail suspension behavior. Two RNA fractions were isolated from mouse hippocampal tissues and sperm cells by standard TRIzol extraction: total RNA and fraction of RNA bound to DNA in the form of a DNA/RNA hybrid (R-loop). The expression levels of miR-19a-3p, miR-361-5p, miR-150-5p, miR-126-3p and miR-499a-5p were investigated by quantitative real-time RT-PCR. We report differences in the distribution of five miRNAs in the hippocampus between male and female mice in RNA fractions, particularly in colonies of Cc2d1a +/- mice. Furthermore, the number of miRNAs engaged in the DNA/RNA hybrid fraction is generally higher in the mutant pedigree than in the control group. On the other hand, in sperm both fractions are at lower levels than in controls. R-loops contribute to the physiology and pathology of organisms including human disease. Here we report a variation in five miRNA levels between gender and tissue. Our results suggest that the transcription levels of these five miRNAs are directly regulated by their RNA.

Peritoneal fluid is an ovarian exudate from the growing follicle or corpus luteum. Therefore, the free concentrations of estrogens and progesterone are always much higher than in plasma, especially after ovulation. The peritoneum is not vascularised, and peritoneal implants and the superficial portion of deep endometriosis are likely influenced mainly by peritoneal fluid. Follicular phase progesterone concentrations are as high as during the luteal phase in plasma. This explains that most peritoneal implants are rarely proliferative and out of phase with the endometrium. From some 5 mm of depth onwards, endometriosis is rather influenced by plasma hormone concentra-tions, and the deeper parts can be proliferative as the endometrium. Because of these progesterone concentrations, progesterone resistance has to be postulated, permitting endometriosis lesions to initiate and develop. This opens the discussion of whether endometriosis is similar to the basal endometrium. These peritoneal fluid concentrations are important to understand the natural history and medical therapy of endometriosis. Most medical therapies decrease ovarian function and affect peritoneal fluid steroid hormone concentrations. It is suggested that the efficacy of medical therapy for endometriosis-associated pain is a consequence of the decreased estrogen concentrations in the peritoneal cavity and that the local effect of progestins may not be determinant for pain relief. If this is true, a history of endometriosis should not be considered a contraindication for hormone re-placement therapy.

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

Mass transfer restrictions of scaffolds are currently hindering the development of three-dimensional (3D), clinically viable, and tissue engineered constructs. For this situation, a 3D poly(lactide-co-glycolide)/hydroxyapatite porous scaffold, which was much favorable for transfer of nutrients to and waste products from the cells in the pores, was developed in this study. The 3D scaffold had an innovative structure, including macropores with diameters of 300−450 μm for cell ingrowth and microchannels with diameters of 2−4 μm for nutrition and waste exchange. The mechanical strength in wet state was strong enough to offer the structural support. The typical structure was more beneficial for the attachment, proliferation, and differentiation of rabbit bone marrow mesenchymal stem cells (rBMSCs). The alkaline phosphatase (ALP) activity and calcium (Ca) deposition were evaluated on the differentiation of rBMSCs, and the results indicated that the microchannel structure was very favorable for differentiating rBMSCs into maturing osteoblasts. For repairing rabbit radius defects in vivo, there was rapid healing in the defects treated with the 3D porous scaffold with microchannels, where the bridging by a large bony callus was observed at 12 weeks post-surgery. Based on the results, the 3D porous scaffold with microchannels was a promising candidate for bone defect repair.

The oncological outcomes are improving in gastrointestinal cancer with advancement in systemic therapies, and there is notable potential in combining immunotherapy and radiation therapy (RT)to allow for further improvements in outcomes. Various preclinical and early phase II studies have shown promising synergy with immunotherapy and RT in gastrointestinal cancer. Consolidative nivolumab in esophageal cancer after neoadjuvant chemoradiation (CRT) and complete resection has recently been approved as standard treatment after improved disease free survival in phase III study. Immunotherapy has shown promising results in hepatocellular carcinoma and colorectal cancer as well. We have reviewed the published and ongoing studies of the combinations of immunotherapy and RT in gastrointestinal cancers.

Background: The aim of the present work is the elaboration of a systematic review of existing research on physical fitness, self-efficacy for physical exercise, and quality of life in adulthood. Method: Using the PRISMA statement guidelines, and based on the findings in 396 articles, the final sample was composed of 31 articles, which were reviewed to show whether self-efficacy has previously been studied as a mediator in the relationship between physical fitness and quality of life in adulthood. Results: The results indicate that little research exists in relation to healthy, populations with the majority being people with pathology. Physical fitness should be considered as a fundamental aspect in determining the functional capacity of the person. Conclusions: We discuss the need to investigate the mediation of self-efficacy in relation to the value of physical activity on quality of life and well-being in the healthy adult population in adult life.

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

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

A non-negligible fraction of quasars are red at optical wavelengths, indicating (in the vast majority of cases) that the accretion disc is obscured by a column of dust which extinguishes the shorter-wavelength blue emission. In this paper we summarise recent work by our group, where we find fundamental differences in the radio properties of SDSS optically selected red quasars. We also present new analyses, using a consistent colour-selected quasar parent sample matched to four radio surveys (FIRST, VLA Stripe 82, VLA COSMOS 3 GHz and LoTSS DR1) across a frequency range 150 MHz-3 GHz and four orders of magnitude in radio flux. We show this enhancement is driven by systems with small-scale radio emission (∼kpc) and peaks around the radio-quiet threshold (defined as the ratio of 1.4 GHz luminosity to 6μm luminosity) across the four radio samples. Exploring the potential mechanisms behind this enhancement, we rule out star-formation and propose either small-scale jets or dusty winds interacting with the interstellar medium; this will be tested in detail using new multi-band uGMRT data. Overall our results cannot be explained with a simple viewing angle hypothesis, and so may point towards red quasars representing a key phase in the evolution of galaxies.

Some peptide-based drugs including oxytocin, vasopressin, ziconotide, pramlintide, nesiritide, and octreotide, contain one intramolecular disulfide bonds. A novel and reusable monodispersed silica nanosphere-supported Pt(IV) complex (SiO2@TPEA@Pt(IV)) was synthesized via a four-step procedure and used for formation of intramolecular disulfide bonds in peptides. TEM and chemical mapping results for the Pt(II) intermediates and for SiO2@TPEA@Pt(IV) show that the silica nanospheres possess a monodisperse spherical structure and contain uniformly distributed Si, O, C, N, Cl, and Pt. The valence state of Pt on the silica nanospheres was characterized by XPS. The Pt(IV) loaded on SiO2@TPEA@Pt(IV) was 0.15 mmol/g, as determined by UV-vis spectrometry. Formation of intramolecular disulfides in six dithiol-containing peptides of variable lengths by use of SiO2@TPEA@Pt(IV) was investigated and the relative oxidation yields were determined by HPLC. In addition, peptide 1 (Ac-CPFC-NH2) was utilized to study the reusability of SiO2@TPEA@Pt(IV). No significant decrease in the relative oxidation yield was observed after ten reaction cycles. Moreover, the structure of SiO2@TPEA@Pt(IV) after being used ten cycles was determined to be similar to its initial one, demonstrating the cycling stability of the complex.

As renewed interest in human space-exploration intensifies, a coherent and modernized strategy for mission-design and planning has become increasingly crucial. Biotechnology has emerged as a promising approach to increase mission resilience, flexibility, and efficiency by virtue of its ability to efficiently utilize in situ resources and reclaim resources from waste streams. Since its infancy during the Apollo years, biotechnology, and specifically biomanufacturing, have witnessed significant expansions of scope and scale. Here we outline four primary mission classes, on Luna and Mars, that drive a staged and accretive biomanufacturing strategy. Each class requires a unique approach to integrate biomanufacturing into the existing mission architecture and so faces unique challenges in technology development.These challenges stem directly from the resources available in a given mission class – the degree to which feedstocks are derived from cargo and in situ resources – and the degree to which loop-closure is necessary. We see that as mission duration and distance from Earth increase, the benefits of specialized sustainable biomanufacturing processes increases. Here we present a strategic approach, guided by technoeconomics, to development, testing, and deployment of these technologies serves to nucleate the larger effort of supporting a sustained human presence in space. The processes needed for each scenario spans the technical breadth of synthetic biology to design engineering, from sophisticated genetic tailoring of chassis-organisms to building scalable, automated, easily operable bioreactors and processing systems. As space-related technology development often does, these advancements are likely to have profound implications for the creation of a stable, resilient bioeconomy on Earth.

The range of interactions between Cladosporium, an ubiquitous fungal genus, and insects, a class including about 60% of the animal species, is extremely diverse. The broad case history of antagonism and mutualism connecting Cladosporium and insects is reviewed in this paper based on the examination of the available literature. Certain strains establish direct interactions with pest or beneficial insects, or indirectly influence them through their endophytic development in plants. Entomopathogenicity is often connected to the production of toxic secondary metabolites, although there is a case where these compounds have been reported to favor pollinators attraction, suggesting an important role in angiosperm reproduction. Other relationships include mycophagy, which on the other hand may reflect an ecological advantage for these extremely adaptable fungi using insects as carriers for spreading in the environment. Several Cladosporium species colonize insect structures, such as galleries of ambrosia beetles, leaf-rolls of attelabid weevils and galls formed by cecidomyid midges, playing a still uncertain symbiotic role. Finally, the occurrence of Cladosporium in the gut of several insect species has intriguing implications in pest management, also considering that some strains have proven to be able to degrade insecticides. These interactions especially deserve further investigation to understand the impact of these fungi on pest control measures and strategies to preserve beneficial insects.

Bayesian model calibration techniques are commonly employed in the characterization of nonlinear dynamic systems, as they provide a conceptual and effective framework to deal with model uncertainties, experimental errors and procedure assumptions. This understanding has resulted in the need to introduce a model discrepancy term to account for the differences between model-based predictions and real observations. Indeed, the goal of this work is to enhance model-driven Structural Health Monitoring procedures by incorporating the posterior uncertainty linked to updated model discrepancy, and thus make relevant considerations for its use in the Structural Health Monitoring. Specifically, the Bayesian inference has been applied to the calibration of nonlinear hysteretic systems to both provide: (i) most probable values (MPV) of the parameters following the calibration, and; (ii) estimates of the model discrepancy posterior distribution. The effect of the model discrepancy in the calibration is first illustrated recurring to a single degree of freedom Bouc-Wen type oscillator, and then applied for calibrating a reference nonlinear Bouc-Wen model, deriving from real data acquired on a monitored masonry building.

Phytochemicals have a long and successful history in drug discovery. With recent advancements in analytical techniques and methodologies, discovering bioactive leads from natural compounds has become easier. Computational techniques like molecular docking, QSAR modelling and machine learning, and network pharmacology are among the most promising new tools that allow researchers to make predictions concerning natural products' potential targets, thereby guiding experimental validation efforts. Additionally, approaches like LC-MS or LC-NMR speed up compound identification by streamlining analytical processes. Integrating structural and computational biology aids in lead identification, thus providing invaluable information to understand how phytochemicals interact with potential targets in the body. Emerging computational approach is machine learning involving QSAR modelling and deep neural networks that interrelate phytochemical properties with diverse physiological activities such as antimicrobial or anticancer effects.

The normal growth and development of skeletal muscle is essential for the health of the body. The regulation of skeletal muscle by intestinal microorganisms and their metabolites has been continuously revealed. Acetate is the predominant short-chain fatty acid synthesized by gut microbiota through the fermentation of dietary fiber, however, the underlying molecular mechanisms governing the interaction between acetate and skeletal muscle during rapid growth stage remain to be further elucidated; Here, specific pathogen-free (SPF) mice, germ-free (GF) mice, and germ-free mice supplemented with sodium acetate (GS) were used to evaluate the effects of acetate on skeletal muscle growth and development of young mice with gut microbiota deficiency; We found the concentration of serum acetate, body mass gain, succinate dehydrogenase activity and expression of myogenesis maker gene of skeletal muscle in the GS group was higher than GF group following sodium acetate supplement. Furthermore, the transcriptome analysis revealed that acetate activated biological processes regulating skeletal muscle growth and development in GF group that are inhibited due to gut microbiota deficiency. In vitro experiment, we proved that acetate up-regulated Gm16062 to promote skeletal muscle cell differentiation; Overall, our findings proved that acetate promote skeletal muscle growth and development in young mice via increase Gm16062 expression.

Peanut (Arachis hypogaea) contains allergenic proteins, which make it harmful to the sensitised population. The presence of peanut in foods must be indicated on label, to prevent accidental consumption by allergic population. In this work, we use chloroplast markers for specifically detection of peanut by real-time PCR, in order to increase the assay sensitivity. Binary mixtures of raw and processed peanut flour in wheat were performed at concentrations ranging from 100000 to 0.1 mg/kg. DNA isolation from peanut, mixtures and other legumes was carried out following three protocols for obtaining genomic and chloroplast-enrich DNA. Quantity and quality of DNA was evaluated, obtaining better results for protocol 2. Specificity and sensitivity of the method has been assayed with specific primers for three chloroplast markers (mat k, rpl16 and trnH-psbA) and Ara h 6 peanut allergen-coding region was selected as nuclear low-copy target and TaqMan probes. Efficiency and linear correlation of calibration curves were within the adequate ranges. Mat k chloroplast marker yielded the most sensitive and efficient detection for peanut. Moreover, detection of mat K in binary mixtures of processed samples was possible up to 10 mg/kg even after boiling, and autoclave 121°C 15 min, with acceptable efficiency and linear correlation. Applicability of the method has been assayed in several commercial food products.

CAMx-LPiG (Comprehensive Air Quality Model with Extensions – Linear Plume in Grid) is an online hybrid model, based on the Chemistry and Transport Model (CTM) CAMx, that includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions, called LPiG. LPiG is a plume in grid module specifically developed by extending the capabilities of the Lagrangian puff sub-grid model available in CAMx. The online integration of the local scale model within the Eulerian CTM allows for a multiscale simulation of air quality from the regional scale to the urban scale, preserving a coherent description of the chemical state of the atmosphere at all spatial scales and avoiding any double counting of the emissions simulated by the sub-grid module. In this work the model is presented and evaluated against measured NO2 concentrations for the city of Milan for the month of January 2017. The model is able to introduce road traffic induced gradient in NO2 concentration at sub-grid resolution. Moreover, CAMx-LPiG is shown to reduce the bias compared to CAMx stand-alone simulations.

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

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

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

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

In a previous paper, the authors dealt with the current showstoppers for morphing systems and with the reasons that have inhibited their commercial applicability. In this work, the authors ex-press a critical vision of the current status of the proposed architectures and the needs that should be accomplished to make them viable for installation onboard of commercial aircraft. The distinc-tion is essential because military and civil issues and necessities are very different, and both the solutions and difficulties to be overcome are widely diverse. Yet, still remaining in the civil seg-ment, there can be other differences, depending on the size of the aircraft, from large jets to com-muters or general aviation, in turn classifiable in tourism, acrobatic, ultralight and so on, each with their own peculiarities. Therefore, the paper wants to try to trace a common technology de-nominator, if possible, and envisage a future perspective of actual applications.

The present work provides continuity with studies where currently the industrial market is characterized by a highly variable demand in terms of quantities and flexibility of manufacturing or mass customization, which translates into a more demanding production context in terms of the continuous changes required to the production systems, the effect of which results in an increase in the fatigue subjected to the machines that make up the production systems. On the other hand, current production systems tend to use highly communicative and sensorized cyber-physical systems; these characteristics can be used to integrate them into decision-assisted systems in order to improve the availability of the industrial plant. The assisted system developed focuses on collecting and taking advantage of historical knowledge of industrial plant failures and breakdowns. By ideally integrating the Reliability Centered Maintenance (RCM) methodology and Case-Based Reasoning (CBR) algorithms implemented in a Java application, it is possible to design maintenance plans adjusted to a real and changing operational context of any industrial plant. As a result, faster and more accurate decisions are made, as they are based on data. This article focuses on improving certain aspects of the developed assisted system by adding more value to it by incorporating Fuzzy Logic (FL) techniques. The aim is to improve the way of entering information about risk factors and their relative importance, by incorporating natural language, instead of a numerical score, resulting in increased precision in the calculation of the Risk Priority Number (RPN) of the new cases incorporated into the assisted system.

Angiotensin-converting enzyme 2 (ACE2) is an important player of the renin-angiotensin-aldosterone system (RAAS) in regulating the conversion of angiotensin II into angiotensin (1-7). While expressed on the surface of human cells, such as lung, heart, kidney, neurons, and endothelial cells (EC), ACE2 is the entry receptor for SARS-CoV-2. Here, we would like to highlight that ACE2 is predominant on the EC membrane. Many of coronavirus disease 2019 (COVID-19) symptoms have been associated with the large recruitment of immune cells, directly affecting EC. Additionally, cytokines, hypoxia, and complement activation can trigger the activation of EC leading to the coagulation cascade. The EC dysfunction plus the inflammation due to SARS-CoV-2 infection may lead to abnormal coagulation, actively participating in thrombo-inflammatory processes resulting in vasculopathy and indicating poor prognosis in patients with COVID-19. Considering the intrinsic relationship between EC and the pathophysiology of SARS-CoV-2, EC-associated therapies such as anticoagulants, fibrinolytic drugs, immunomodulators, and molecular therapies have been proposed. In this review, we will discuss the role of EC in the lung inflammation and edema, in the disseminate coagulation process, ACE2 positive cancer patients, and current and future EC-associated therapies to treat COVID-19.

Rice has become the second major food among rural people. It is one of the most nutrient and low-cost food available in Asia. Rice is composed of two major subspecies as Japonica and Indica and it belongs to the Poaceae family. The World Bank predicts that rice demand will grow 51% faster than population growth in 2025. It is high time to develop a model which predicts the type of infected paddy leaf and avoids the loss of grains. In this paper, the proposed hybrid CNN model, three CNN networks with different layer properties are trained parallel. The extracted feature from these CNN networks is combined to provide the classification of the type of infected leaf. Fieldwork was carried and about 340 samples are collected from five different types of classes. The proposed hybrid model was tested with both the fieldwork dataset and also with an available dataset on the internet. The experimental results show that the proposed model outperforms the other CNN network and yields an accuracy value of 98%, a precision value of 95%, and a misclassification rate of 4% respectively.

One of the current challenges in Higher Education is the development of students’ emotional competencies, and consequently, how these competencies can be trained. Moreover, this must be addressed within the UN framework of inclusive, equitable, quality education (United Nations Agenda 2030) (SDG 4). To address this challenge, the present study set the following objectives: (1) to analyze pre-service teachers’ level of interest in EI and their perceived level of general EI knowledge, (2) to examine their self-perception of certain variables of emotional knowledge, according to their degree program and year of studies, (3) to analyze the relationship between these emotional knowledge variables and perceived emotional intelligence (EI); and (4) to study the predictive capacity of the study variables on future teachers' emotional knowledge variables. The study sample contained a total of 434 university students from three degree programs at two universities in Spain, of which 82.70% were women, and the mean age was 20.91 years. Two instruments were used: an ad hoc questionnaire, which assessed perceived emotional knowledge according to three variables (General knowledge of EI, where level of training in EI is considered; Intrapersonal knowledge of EI; and Theoretical-practical knowledge related to teaching), and the Trait Meta-Mood Scale (TMMS-24), which assesses metaknowledge of emotional states across three variables (Attention, Clarity, and Repair). Results of the study suggest that there are differences in perceived EI knowledge according to students' year of studies and according to their degree, and indicate that students present high interest, while their perceived level of knowledge is low. In addition, emotional clarity is the EI variable that was identified as being important in the emotional knowledge of future teachers. This study shows evidence of the importance of social-emotional competencies in initial teacher training.

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

Previous studies demonstrate the critical importance of non-coding RNAs interfacing with chromatin-modifying machinery resulting in promoter-enhancer-based gene regulation and raise the possibility that many other enhancer-like RNAs may operate via similar mechanisms. Critically, more than 80% of the disease-linked variations identified in genome-wide studies are located in the non-coding regions of genomes, especially non-coding RNA, suggesting non-coding RNAs are relevant to disease. Thus, a critical path forward for understanding non-coding RNAs' role, especially long non-coding RNAs, is to understand the genomic regions' transcriptional regulation, especially non-coding regions. Here, we developed a user-friendly R package called SomaGene for studying and identifying enhancer-like non-coding RNAs with enriched somatic mutations in the cancer genome. SomaGene accepts different genomic variants (whole genome/exome somatic point mutations, structural variations, copy number variations) to identify those RNAs that significantly mutated in diseases (e.g., cancer). It then uses multiple publicly available genomics and epigenetics datasets including ENCODE epigenomics annotations, FANTOM5 tissue-specific expression profiles, disease-associated genome-wide association SNPs, and tissue-specific eQTL pairs to identify those RNAs with potentially enhancer function. SomaGene, as a powerful R package, can provide the opportunity to cancer scientists to study the roles of non-coding RNAs in different cancer genomes.

The authors previously found a model of universal quantum computation by making use of the coset structure of subgroups of a free group $G$ with relations. A valid subgroup $H$ of index $d$ in $G$ leads to a \lq magic' state $\left|\psi\right\rangle$ in $d$-dimensional Hilbert space that encodes a minimal informationally complete quantum measurement (or MIC), possibly carrying a finite \lq contextual' geometry. In the present work, we choose $G$ as the fundamental group $\pi_1(V)$ of an exotic $4$-manifold $V$, more precisely a \lq small exotic' (space-time) $R^4$ (that is homeomorphic and isometric, but not diffeomorphic to the Euclidean $\mathbb{R}^4$). Our selected example, due to to S. Akbulut and R.~E. Gompf, has two remarkable properties: (a) it shows the occurence of standard contextual geometries such as the Fano plane (at index $7$), Mermin's pentagram (at index $10$), the two-qubit commutation picture $GQ(2,2)$ (at index $15$) as well as the combinatorial Grassmannian Gr$(2,8)$ (at index $28$) , (b) it allows the interpretation of MICs measurements as arising from such exotic (space-time) $R^4$'s. Our new picture relating a topological quantum computing and exotic space-time is also intended to become an approach of \lq quantum gravity'.

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

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

Organic electrophoretic coatings have gained significant attention due to their ability to provide a uniform and controlled coating thickness, high coating adhesion, and excellent corrosion protection properties. In this work, to investigate the aging behaviors of an organic electrophoretic coating for magnesium alloys, water absorption kinetics curves of the coatings after immersion in 3.5 wt.% NaCl at 20℃ and 40℃ were measured, and parameters such as the saturated water absorption and saturation time of the free film coatings were fitted to determine the densification evolution of the organic coatings. A tensile test was used to test the tensile strength of the organic coating during service to determine the evolution of the strength and toughness of the organic coating. The evolution of wet adhesion of organic coatings with service time was tested by ASTM D4541-02. The impedance spectra of the organic coatings under the above conditions were detected by EIS, and finally, the failure behavior of the organic coatings under immersion was analyzed.

The steep decline in the price of wind and solar photovoltaics provides a possibility to decarbonize electricity deeply and affordably. This study uses HOMER Pro energy modeling tool to model an optimized grid-connected renewable energy system for a community in southern Alberta, Canada. The study's goal is to identify the best renewable energy technology combinations that can provide electricity at the lowest levelized cost of energy (LCOE) and has lesser greenhouse gas emission as compared to the electricity produced by traditional fossil fuel. Gleichen, is a small town in southern Alberta and is near to numerous commercial wind and solar projects given the region’s high quality renewable resources. “Tri-brid” systems consisting of wind turbines, solar photovoltaics, and battery energy storage systems (BESS) are considered and compared based on electricity prices, net present cost, and greenhouse gas emissions savings. This tri-brid system is connected to the grid to sell excess electricity generated or buying electricity when there is less or no availability of solar and wind. The tri-brid energy system has an estimated LCOE of 0.0705 CAD/kWh which is competitive with the price of electricity generated by natural gas and coal which is 0.127 CAD/kWh.

This study develops a hybrid machine learning (ML) algorithm integrated with IoT technology to improve the accuracy and efficiency of soil monitoring and tomato crop disease prediction in Anakapalle, a south Indian station. An IoT device collected one-minute and critical soil parameters—humidity, temperature, pH values, nitrogen (N), phosphorus (P), and potassium (K)—essential for assessing soil health and optimizing crop growth. Kendall's correlations were computed to rank these parameters for utilization in hybrid ML techniques. Various ML algorithms including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Tree (DT), Random Forest (RF), and Logistic Regression (LR) were evaluated. A novel hybrid algorithm, 'Bayesian Optimization with KNN', was introduced to combine multiple ML techniques and enhance predictive performance. The hybrid algorithm demonstrated superior results with 95% accuracy, precision, and recall, and an F1 score of 94%, while individual ML algorithms achieved varying results: KNN (80% accuracy), SVM (82%), DT (77%), RF (80%), and LR (81%) with differing precision, recall, and F1 scores. This hybrid ML approach proved highly effective in predicting tomato crop diseases in natural environments, underscoring the synergistic benefits of IoT and advanced ML techniques in optimizing agricultural practices.

It has been a long time since the world has experienced a pandemic with such a rapid devastating impact as the current COVID-19 pandemic. The causative agent, the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) is further unusual in that it appears capable of infecting many different mammal species. As a significant proportion of people worldwide are infected with SARS-CoV-2 and may spread the infection unknowingly before symptoms occur or without any symptoms ever occurring, there is a non-negligible risk of humans spreading SARS-CoV-2 to wildlife, in particular mammals. Because of SARS-CoV-2’s evolutionary origins in bats and reports of humans transmitting the virus to pets and zoo animals, regulations for prevention of human-to-animal transmission have so far focused mostly on these animal groups. Here, we summarize recent studies and reports that show that a wide range of distantly related mammals are likely susceptible to SARS-CoV-2 and that susceptibility or resistance to the virus is in general not predictable, or only to some extent, by phylogenetic proximity to known susceptible or resistant hosts. In the absence of solid evidence on the SARS-CoV-2 susceptibility/resistance for each of the >5,500 mammal species, we argue that sanitary precautions should be taken when interacting with any mammal species in the wild. Preventing human-to-wildlife SARS-CoV-2 transmission is important for protecting these (sometimes endangered) animals from disease, but also to avoid establishment of novel SARS-CoV-2 reservoirs in wild animals. The risk of repeated re-infection of humans from such a wildlife reservoir could severely hamper SARS-CoV-2 control efforts. For wildlife fieldworkers interacting directly or indirectly with mammals, we recommend sanitary precautions such as physical distancing, wearing face masks and gloves, and frequent decontamination, which are very similar to regulations currently imposed to prevent transmission among humans.

Telemedicine is the use of Information and Communication Technology (ICT) for clinical health care from a distance. The exchange of radiographic images and electronic patient health information/records (ePHI/R) for diagnostic purposes has the risk of confidentiality, ownership identity, and authenticity. In this paper, a data hiding technique for ePHI/R is proposed. The color information in the cover image is used for key generation, and stego-images are produced with ideal case. As a result, the whole stego-system is perfectly secure. This method includes the features of watermarking and steganography techniques. The method is applied to radiographic images. For the radiographic images, this method resembles watermarking, which is an ePHI/R data system. Experiments show promising results for the application of this method to radiographic images in ePHI/R for both transmission and storage purpose.

Tree nuts show nutritional properties and human health benefits. However, they contain allergenic proteins, which make them harmful to the sensitised population. The presence of tree nuts on food labelling is mandatory and, consequently, the development of suitable analytical methodologies to detect nuts in processed foods is advisable. Real-time PCR allowed a specific and accurate amplification of allergen sequences. Some food processing methods could induce structural and/or conformational changes in proteins by altering their allergenic capacity, as well as produce the fragmentation and/or degradation of genomic DNA. In this work, we analysed by means of Real-time PCR, the influence of pressure and thermal processing through Instant Controlled Pressure Drop (DIC) on the detectability of hazelnut,pistachio and cashew allergens have been tested. The detection of targets in hazelnut, pistachio and cashew (Cor a 9, Pis v 1 and Ana o 1, respectively) is affected by the treatment, in different extent depending on the tree nut. Results are compared to those previously obtained by our group in the analysis of different treatments on the amplificability of the same targets. Reduction in amplificability is similar to that reported for some autoclave conditions. Our assays might allow detecting up to 1000 mg/kg of hazelnut, pistachio and cashew flours after being submitted to DIC treatment in food matrices.

For the set of probability measures ${\sf I}(X)$, where $X$ is a compact Hausdorff space, we propose a new way to introduce the topology by using open subsets of the space $X$. Then, among other things, we give a new proof that for a compact Hausdorff space $X$ the space ${\sf I}(X)$ is also a compact Hausdorff space. For a Tychonoff space $X$, we consider the topological space ${\sf I_{\tau}}(X)$ of $\tau$-smooth idempotent probability measures on $X$,and show that the space ${\sf I_{\tau}}(X)$ is \v{C}ech-complete if and only if the given space $X$ is \v{C}ech-complete.

Peanut hulls (PH) are an edible food waste that is an underutilized food source for human consumption. While edible and palatable, they are mainly diverted to livestock feed or building materials. Here, we describe existing literature on human food valorization of PHs and propose methods to optimize recapturing nutrients (e.g. protein, fiber, polyphenols) lost by treating PHs as waste. Incorporated into common foods, PHs can be processed into functional ingredients to improve nutrient-density and the corresponding positive health outcomes associated with increases in plant foods. PH valorization can also address additional priorities of the UN Sustainable Development Goals using a Food Systems Approach (FSA) including food waste, increasing economic opportunities for farmers, and increasing the availability of healthy shelf-stable foodstuffs to address food security. Recent advances in sustainable food processing technologies can be utilized to safely incorporate peanut hulls into human food streams. We propose future applications that could make meaningful impacts to food availability and the nutritional composition of common foods. While the limited literature on this topic spans several decades, no global operations exist to incorporate peanut hulls and most publications precede the technological ‘green revolution’. The approaches outlined in this review may help bolster commercialization of this underutilized and nutritious food potentially improving opportunities for multiple global stakeholders.

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

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

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

The tradeoff between the design phase and the experimental setup is crucial to satisfy the accuracy requirement of Large Deployable Reflectors. Manufacturing errors and tolerances change the RMS of the reflecting surface and require careful calibration of the tie rod system to be able to fit into the initial design specifications. To give a possible solution to this problem, here two calibration methods, respectively for rigid and flexible ring truss support, are described. Starting from the acquired experimental data on the net nodal coordinates, the initial problem of satisfying the static equilibrium at the measured configuration is described. Then, two constrained optimization problems, for rigid and flexible ring truss support, are defined to meet RMS accuracy of the reflecting surface modifying the tie lengths. Finally, a case study to demonstrate the validity of the proposed methods is presented.

In recent years, increasing attention has been paid to individuals organizing themselves and managing food systems in an ‘alternative’ and more sustainable way. Such emerging food initiatives are most commonly known as ‘Alternative Food Networks’ (AFNs). However, there is an ongoing debate concerning the extent to which AFNs facilitate social, economic and environmental change. There are criticisms of the overall sustainability promise of AFNs related to sufficiency of impact, possible counter effects and relevance of impacts. Because often empirical studies only focus on specific sustainability issues or AFNs, it has been difficult to develop more robust theories about the relations between diverse AFNs arrangements and sustainability. Thus, the aim of this paper is to contribute towards reducing this knowledge gap through a systematic literature review on AFNs in relation to sustainability. We summarize main methodological approaches, types of AFNs studied and sustainability dimensions addressed in literature to date. Findings serve as reference to propose opportunities for future research regarding sustainability in AFNs.

Little is understood about the impact of nebulisation on the viability of SARS-CoV-2. In this study, a range of nebulisers with differing methods of aerosol generation were evaluated to determine SARS-CoV-2 viability following aerosolisation. The aerosol particle size distribution was assessed using an aerosol particle sizer (APS) and SARS-CoV-2 viability was determined after collection into liquid media using All-Glass Impingers (AGI). Viable particles of SARS-CoV-2 were further characterised using the Collison 6-jet nebuliser in conjunction with novel sample techniques in an Andersen size-fractioning sampler to predict lung deposition profiles. Results demonstrate that all the tested nebulisers can generate stable, polydisperse aerosols (Geometric standard deviation (GSD) circa 1.8) in the respirable range (1.2 to 2.2µm). Viable fractions (PFU/particle, the virus viability as a function of total particles produced) were circa 5x10^-3 and were not significantly affected by relative humidity. The novel Andersen sample collection methods successfully captured viable virus particles across all sizes; with most particle sizes below 3.3µm. MMADs (Mass Median Aerodynamic Diameters) were calculated from linear regression of log10-log10 transformed cumulative PFU data, and calculated MMADs accorded well with APS measurements and did not differ across collection method types. This data will be vital in informing animal aerosol challenge models, and infection prevention and control policies.

Study aimed to evaluate the impact of integrating family planning with maternal, newborn, and child health (FP-MNCH) on uptake of modern contraceptive methods and related health outcomes in two districts of the province of Sindh, Pakistan. Impact of intervention was evaluated using a quasi-experimental control before-after study design. Intervention included capacity building of healthcare providers and outreach workers, ensuring sustained supplies of family planning commodities, data-driven decision-making, and community engagement activities. Data was collected through household surveys at baseline (December2020) and endline (December 2022). The sample size was estimated as 880 married women of reproductive age (MWRA) in each district. The Difference and Difference(DiD) analytical method was used to estimate the impact of intervention adjusted for potential confounding factors. There was statistically significant increase of 11.3% in the current use of MCM in the intervention group compared to the control group (p value <0.001), with increases observed in the uptake of injection , implants, and condoms. Additionally, there was an increase in the proportion of women who had ANC visits (DiD 10.5% p value 0.003), FP counselling during ANC (DiD 15.6% p value < 0.001), LHW visits during pregnancy (DiD 15.1% p value 0.021), PNC check-ups for mother (DiD 25.2% p value <0.001), LHW visits after delivery (DiD 20.4% p value <0.001), and LHW advised for family planning at PNC visit n (DiD 14.5% p value 0.030). This study provides strong evidence for the scaling-up of integrated interventions through existing health care platforms utilizing human resources deployed by the government. This FP-MNCH model has the potential to be adopted in other provinces and at federally administered areas for both health and population planning. This model should be considered for replication in other districts of Sindh to accelerate current level of integration already existing.

RNA editing involves the insertion, deletion or substitution of single nucleotides within a RNA molecule, without altering the DNA sequence. Adenosine to inosine (A-to-I) editing consists of an RNA modification where single adenosines along the RNA sequence are converted into inosines. Such a biochemical transformation is catalyzed by enzymes belonging to the family of adenosine deaminases acting on RNA (ADARs) and occurs either co- or post-transcriptionally. Initially, the A-to-I RNA editing phenomenon was discovered and studied in messenger RNAs (mRNAs), where it can influence RNA splicing and cause the recoding of codon sequences. The employment of more powerful, high-throughput detection methods has recently revealed that A-to-I editing widely occurs in non-coding RNAs, including microRNAs (miRNAs). MiRNAs are a class of small regulatory non-coding RNAs (ncRNAs) acting as translation inhibitors, known to exert relevant roles in controlling cell cycle, proliferation, and cancer development. Indeed, a growing number of recent researches have evidenced the importance of miRNA editing in cancer biology by exploiting various detection and validation methods. Herein, we briefly overview early and currently available A-to-I miRNA editing detection and validation methods and discuss the significance of A-to-I miRNA editing in human cancer.

In this paper, we first define the concepts of r-fuzzy soft α-open (semi-open and δ-open) sets on fuzzy soft topological spaces based on the article Aygunoglu et al. (Hacet. J. Math. Stat., 43 (2014), 193-208), and the relations of these sets with each other are established. In addition, we introduce the concepts of fuzzy soft δ-closure (δ-interior) operators, and study some properties of them. Also, the concept of r-fuzzy soft δ-connected sets is introduced and studied with help of fuzzy soft δ-closure operators. Thereafter, we define the concepts of fuzzy soft α-continuous (β-continuous, semi-continuous, pre-continuous and δ-continuous) functions, which are weaker forms of fuzzy soft continuity, and some properties of these functions along with their mutual relationships are discussed. Moreover, a decomposition of fuzzy soft α-continuity and a decomposition of fuzzy soft semi-continuity is obtained. Finally, as a weaker form of a fuzzy soft continuity, the concepts of fuzzy soft almost (weakly) continuous functions are defined, and some properties are specified. Additionally, we explore the notion of continuity in a very general setting called, fuzzy soft (L, M, N, O)-continuous functions and a historical justification is introduced.

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

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

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

Quasi-solid composited electrolytes were produced by LiFSI initiated polymerized poly-(Dioxolane) (PDOL) with garnet-LLZO (Li7La2Zr3O12) nanofibers and used in lithium-metal batteries. Linear sweep voltammetry shows that the initial oxidation voltage of 4.6 V for Gel-10% (G10, 10% wt. LLZO in PDOL) vs Li/Li+. EIS test of stainless steel// stainless steel symmetric cells for Gel-1% (G1), Gel-5% (G5) and Gel-10% (G10) show ion conductivity (5*10-5 S/cm). Li/G10/Li symmetric cells have stable stripping-plating cycling performance over 1300 hours continuously with the current density of 0.1 mA/cm2 at 25 oC, indicating a good interface contact and stable lithium-ion transport pathway through the composite electrolytes. LFP/G10/Li batteries have stable charge-discharge plateau, low polarization voltage of 0.07-volt, energy efficiency of 95% and coulombic efficiency of ~99% at current density of 26.3 mA/g at 25 oC for over 100 cycles.

This paper constitutes a first advance in the paleoenvironmental study of a small group of peatland ecosystems, of reduced size, located in the interior of the Iberian Peninsula (Puebla de Don Rodrigo, Ciudad Real, Spain). It represents a singular enclave, because these ecosystems are home to the southern-most peatlands in Europe, located at the lowest altitude in Spain, and are unique to the region of Castilla-La Mancha. They form ecosystems similar to the peat bogs of northern Europe, but in a Mediterranean climate. The analysis is followed of sample collection and data collection from documentary, textual, and cartographic sources drawn up since the 16th century up until the present day. The scientific analyses that were performed and the documentation that was consulted point to the hypothesis that these peatlands are the result of a long process of historical modification of the landscape in which anthropogenic activity has played a leading role, triggering a series of processes on the hillslopes that are culminating in the exhumation of the waterlogged areas, thereby establishing a recent genesis of these ecosystems.

Objective: Infliximab (IFX) concentrations are a predictive factor (PF) of pharmacokinetic (PK) origin in the treatment of Crohn’s disease (CD). We evaluated clearance, another PF of PK origin, either alone or in combination with concentrations. Methods: PF of PK origin were evaluated from two cohorts, the first received standard dosing (n=37), and the second was designed to proactively target therapeutic IFX concentrations (n=108). Concentrations were measured using homogenous mobility shift assay. Clearance was estimated using nonlinear mixed effects methods with Bayesian priors. C-reactive protein based clinical remission (<3mg/L in the absence of symptoms) was used for the disease control outcome. Longitudinal changes in disease control due to factors including time, IFX concentration, and clearance were analyzed using repeated event analysis. Change in objective function value (∆OFV) was calculated to compare concentration and clearance. Results: Lower baseline clearance and proactive dosing associated with enhanced disease control during induction (p<0.01). Higher IFX concentrations and lower Clearance measured at the second, third and fourth infusion yielded improved disease control during maintenance (p<0.032). During maintenance, the association with disease control was better with clearance than with concentrations (∆OFV= -19.2; p<0.001), and the combination of both further minimized OFV (p<0.001) with markedly improved clinical yield in the presence of both PF of PK origin. Conclusion: PF of PK origin and lower clearance during induction and maintenance yielded enhanced disease control in pediatric CD treated with IFX. The combination of IFX concentration and clearance are better predictors of therapeutic outcome compared to either one alone.

Unlike plants which have special gravity-sensing cells, such special cells in animals are yet to be discovered. However, microgravity, the condition of apparent weightlessness, causes bone, muscular and immune system dysfunctions in astronauts following spaceflights. Decades of investigations show correlations between these organ and system-level dysfunctions with changes induced at the cellular level both by simulated microgravity as well as microgravity conditions in outer space. Changes in single bone, muscle and immune cells include morphological abnormalities, altered gene expression, protein expression, metabolic pathways and signaling pathways. These suggest that human cells mount some response to microgravity. However, the implications of such adjustments on many cellular functions and responses are not clear. Here, we addressed the question whether microgravity induces alterations to drug response in cancer cells. We used both adherent cancer cells (T98G) and cancer cells in suspension (K562) to confirm known effects of microgravity and then treated the K562 cells with common cancer drugs (hydroxyurea and paclitaxel) following 48 hours of exposure to microgravity via a NASA-developed rotary cell culture system. Fluorescence-guided morphometry revealed microgravity-induced loss of the significant reduction (p &lt; 0.0l) to the nuclear to cytoplasm ratio of cancer cells treated with hydroxyurea. Our results call for more studies on impact of microgravity on cellular drug-response, in view of the growing need for space medicine, as space exploration grows.

In recent years, there is a growing concern about the alarming spread of antimicrobial resistance (AMR) in different environments. Increasingly, many species of bacteria, fungi and viruses are becoming immune to the most commonly used pharmaceuticals. One of the causes of the development of the resistance is the persistence of these drugs, excreted by humans, in municipal and hospital wastewater (WW). Consequently, wastewater treatment plants (WWTPs) are a primary source of antimicrobial resistance genes as novel pollutants. This systematic review sought to examine the relevant literature on pharmaceutical residues (PRs) responsible for AMR in municipal and hospital WW in order to propose a classification of the PRs of greatest concern and provide an updated source for AMR management in WWTPs. Among 546 studies collected from four databases, 18 were included in the present review. The internal and external validity of each study was assessed, and the risk of bias was evaluated on a 20-parameter basis. Results were combined in a narrative synthesis discussing influents and effluents PR concentrations at 88 WWTPs, seasonal variations, differences between hospital and municipal WW, environmental risk assessment values of antimicrobial substances and treatment facilities removal efficiencies. Among the 45 PRs responsible for AMR evaluated in this study, the antibiotics ciprofloxacin, clarithromycin, erythromycin, metronidazole, ofloxacin, sulfamethoxazole and trimethoprim constitute a considerable risk in terms of ubiquitous distribution, worrying concentrations, risk quotients values, and resistance to removal treatments. Gaps in knowledge, data and information reported in this review provide a valuable source for managing AMR in WWTPs.

The recyclable paper based on photochromic materials not only reduces the pollution in the paper manufacture process, but also reduces the pollution caused by the use of ink, which receives wide attention. In this paper, a serial of PMoA-PWA/ZnO/PVP hybrid films which had different ratio of PMoA/PWA was prepared by the ultrasonic composite method. The results indicated that the hybrid film prepared when the ratio of PMoA to PWA was 3 had the best photochromic performance. In this system, ZnO was the photosensitizer while PMoA/PWA was the chromophore. The photochromic mechanism of PMoA-PWA/ZnO/PVP hybrid film was based on the photogenerated electron transfer mechanism. ZnO generated photoelectron under the excitation of visible light, then PMoA and PWA obtained the photoelectron and produced photoreduction reaction to generate heteropolyblue. The visible light photochromic paper was prepared by loaded PMoA-PWA/ZnO/PVP hybrid film (A3) on A4 paper. Application test showed that the prepared paper had extremely stable, excellent and reversible visible light photochromic properties, whether it was printing patterns or words and could replace the ordinary paper to realize the reuse of paper.

CO2 geological sequestration in coal seams can achieve the dual objectives of CO2 emission reduction and enhanced coalbed methane production, making it a highly promising carbon capture and storage technology. However, the injection of CO2 into coal reservoirs in the form of supercritical fluid (ScCO2) leads to complex physicochemical reactions with the coal seam, altering the properties of the coal reservoir and impacting the effectiveness of CO2 sequestration and methane production enhancement.In this paper, theoretical calculations based on ReaxFF-MD were conducted to study the interaction mechanism between ScCO2 and the macromolecular structure of both low-rank and high-rank coal, to address the limitations of experimental methods. The reaction of ScCO2 with low-rank coal and high-rank coal exhibits significant differences. At swelling stage, the low-rank coal experiences a decrease in aromatic structure and aliphatic structure, high-rank coal shows an increase in aromatic structure and a decrease in aliphatic structure, while swelling phenomenon is more pronounced in high-rank coal. At dissolution stage, low-rank coal is initially decomposed into two secondary molecular fragments, and then recombine to form new molecular structure, the aromatic structure increased and the aliphatic structure decreased. In contrast, high-rank coal occurs stretches-breakage-movement-reconnection, a reduction in aromatic structure and an increase in aliphatic structure.The primary reasons for these variations lie in distinct molecular structure compositions and the properties of ScCO2, leading to different reaction pathways of functional group and aromatic structure. The reaction pathways of functional groups and aromatic structures in coal can be summarized as follows: the breakage of the O-H bond in hydroxyl groups, the breakage of the C-OH bond in carboxyl groups, transformation of aliphatic structures into smaller hydrocarbon compounds or formation of long-chain alkenes, and various pathways involving broken, rearrangement, recombination of aromatic structures. In low-rank coal, there is a higher abundance of oxygen-containing functional groups and aliphatic structures. The breakage of O-H and C-OH chemical bonds results in the formation of free radical ions, while some aliphatic structures detach to produce hydrocarbons. Additionally, some of these aliphatic structures combine with carbonyl groups and free radical ions to generate new aromatic structures. Conversely, in high-rank coal, the lower content of oxygen-containing functional groups and aliphatic structures, along with stronger intramolecular forces, results in fewer chemical bond breakages and makes it less conducive to the formation of new aromatic structures.These results elucidate the specific deformations of different chemical groups, offering a molecular-level understanding of the interaction between CO2 and coal.

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

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

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

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

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