It is expected that scholars will continue to strengthen the depth and breadth of theoretical research on RIS, so as to provide a higher theoretical upper bound for the engineering application of RIS. While making breakthroughs in academic research, great progress has been made in engineering application research and industrialization promotion. This article will provide an overview of RIS engineering applications, mainly including the typical features, typical classifications, and typical deployment scenarios of RIS. Then the challenges and candidate solutions of the RIS are systematically and deeply analyzed, involving the cascade channel decoupling for solving the RIS beamforming, the influences and solutions of RIS regulation constraints, RIS system architecture of network controlled mode, the integrated channel regulation and information modulation, TDD mechanism used for RIS. Future trends and challenges are also provided.

As a derivative of graphene, graphene oxide (GO) was initially developed by chemists to emulate some of the key properties of graphene, but it was soon recognized as a unique material in its own right, addressing an application space that is not accessible to chemical vapor deposition based materials. Over the past decade, GO has emerged as a new frontier material with tremendous advances in its material fabrication and quality control over its properties. These in turn have led to rapid progress in GO based photonics, electronics, and optoelectronics concepts and devices, evoking new science and paving the way for many technological breakthroughs with exceptional performance. Here, we review the unique fundamental characteristics of GO, its thin film fabrication methods, patterning techniques, and mechanisms for tuning its material properties. This latter capability in particular has enabled novel advanced functional photonic, electronic, and optoelectronic devices. Understanding these insights is essential for designing and tailoring GO properties for state-of-the-art applications including solar energy harvesting, energy storage, medical diagnosis, image displays, and optical communications. We conclude by discussing the open challenges and exciting opportunities of this field, together with future prospects for major technological advancements and breakthroughs.

With the rise of Blockchain technology, the cryptocurrency market has been gaining significant interest. In particular, the number of cryptocurrency traders and the market capitalization have grown tremendously. However, predicting cryptocurrency price is very challenging and difficult due to the high price volatility. In this paper, we propose a classification machine learning approach in order to predict the direction of the market (i.e., if the market is going up or down). We identify key features such as Relative Strength Index (RSI) and Moving Average Convergence Divergence (MACD) to feed the machine learning model. We illustrate our approach through the analysis of Bitcoin close price. We evaluate the proposed approach via different simulations. Particularly, we provide a backtesting strategy. The evaluation results show that the proposed machine learning approach provides buy and sell signals with more than 86% accuracy.

Sports traumatic brain injury (TBI) accounts for up to 20% of all sports injuries, and the number of cases is growing year by year due to an increase in the number of people involved in sports, the growing popularity of extreme and contact sports, as well as a high level of motivation to achieve record results. Mild TBI dominates, which can provoke the development of a very wide range of complications and negative consequences. In the programs for the prevention of complications and the rehabilitation of athletes after TBI, TBI features are not sufficiently considered, which significantly differ from household, road or criminal injuries. There are no instrumental methods for diagnosing the severity of the injury. Sports TBI is characterized by repeated frequent TBI, elevated body and brain temperature, peripheral redistribution of blood flow and hypocapnia, which significantly affect cerebral blood flow. Brain injury is an independent cause of the development of cerebral hyperthermia, which significantly worsens the consequences of TBI. To diagnose sports TBI, the method of microwave radiometry of the brain (MWR) can be used. For the prevention of complications, the technology of craniocerebral hypothermia (CCH), which allows for to reduce of physical general and cerebral hyperthermia, and increases the resistance of cerebral cortex neurons to hypoxia and trauma could be used However, these approaches in sports medicine are used sporadically, which, is due to the lack of awareness of coaches and doctors of sports teams. The purpose of the review is to present MWR and CCH in sports TBI.

What would compel a composer to set the same poem twice? Ludwig van Beethoven first set the text of Christoph Tiedge’s “An Die Hoffnung” (to Hope) between 1804 and 1805, and would later set the poem again, using even more of the text in 1815. While seeking context clues from what is known of his biography is crucial, another avenue of study lies within the pieces themselves. Through the study of key characteristics during Beethoven’s lifetime in addition to what biographical information we know, we can infer Beethoven’s intentions with each setting of the text and how this reflects his changing relationship to the text of “An Die Hoffnung”.

In sub-Saharan Africa, malaria is a leading cause of mortality and morbidity. As a result of the interplay between many factors, the control of this disease can be challenging. However, few studies have demonstrated malaria's complexity, control, and modeling although this perspective could lead to effective policy recommendations. This paper aims to be a didactic material providing the reader with an overview of malaria. More importantly, using a system approach lens, we intend to highlight the debated topics and the multifaceted thematic aspects of malaria transmission mechanisms, while showing the control approaches used as well as the model supporting the dynamics of malaria. As there is a large amount of information on each subject, we have attempted to provide a basic understanding of malaria that needs to be further developed. Nevertheless, this study illustrates the importance of using a multidisciplinary approach to designing next-generation malaria control policies.

In this article key results in general relativity are studied and the dynamics of quantum fields in curved spacetime is reviewed. It has been shown geometrically how dark energy breaks strong energy condition. We study tan-hyperbolic inflation for an open FRWL universe and show that over half and full period scalar field remains in it's initial state.

The thermocontextual interpretation (TCI) establishes a system’s exergy, entropic energy, and thermal entropy as thermocontextual properties of state, defined with respect to its positive temperature surroundings. This work extends previous applications of the TCI to irreversible and statistical transitions. The TCI defines statistical entropy as a transactional process of derandomization and transition to a negative-entropy state. Statistical measurements of a confined quantum particle’s position are detailed in terms of reversible processes of instantiation and actualization. The TCI then formalizes the MaxEnt as a fundamental physical principle. We apply MaxEnt and statistical entropy measurements to the double-slit experiment. Particles passing through parallel slits record a wave interference pattern, but a “which-slit” detector eliminates wave interference. Richard Feynman called the double-slit experiment the only mystery, at the heart of quantum mechanics. The TCI offers a simple explanation. The which-slit detector breaks the system’s symmetry, enabling particles to pass through one slit or the other, and MaxEnt selects the asymmetrical transition, which has no wave interference and a higher statistical entropy.

We present large eddy simulations of a mid-latitude open ocean front using a modified state of the art computational fluid dynamics code. We investigate the energy and information fluxes at the submesoscale/small-scale range in the absence of any atmospheric forcing. We find submesoscale conditions (Ro∼1, Ri∼1) near surface, within baroclinic structures related with partially imbalanced frontogenetic activity. Near surface, the simulations show a significant scale coupling on scales larger than ∼103(m). This is manifested as a strong direct energy cascade and intense mutual communication between scales, where the latter was evaluated using an estimator based on Mutual Information Theory. At scales smaller than ∼103(m) the results show near-zero energy flux, however, at this scale range, the estimator of mutual communication still shows values corresponding with a significant level of communication between them. This fact motivates to investigate the nature of the self-organized turbulent motion at this scale range with weak energetic coupling but where communication between scales is still significant and to inquire into the existence of synchronization or functional relationships between scales with emphasis on eventual underlying non-local processes.

The Action Control Theory (ACT) is an enactive theory of perception and mental imagery with six components: Schemata, Objects, Actions, Affect, Goals and Others’ Behavior. The evidence support-ing these six connected processes is reviewed in light of research on mental imagery vividness. The six processes and their interconnections receive empirical support from a wide range of studies. All six domains of perception and mental imagery are influenced by individual differences in vividness. Real-world applications of ACT show interesting potential to improve human well-being in both healthy people and patients. Mental imagery can be applied in creative ways to make new collective goals and actions for change that are necessary to maximize the future prospects of the planet.

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.

In the present paper, we introduce the phytoscreening and antiradical characteristics of conker extracts prepared from 2-, 1-year stored and just collected plants as well as the anti-inflammatory effect of oinment composition based on the extract.

Plant secondary metabolites are organic compounds (alkaloids, flavonoids, phenolics, tannins, anthraquinones, saponins, steroids, lignins, terpenes) produced by plant for self-defense during growth and development in order to protect them from harmful agents. As population is increasing and quality of life is reducing couple with outbreak of some diseases that are posing threat on the economy, a lot of medicinal plants have attracted interest of researchers because of the usefulness of these metabolites in pharmaceuticals, food and cosmetic industries. In this review, the pharmacological activities of some medicinal plants that are rich in secondary metabolites were studied, means of identifying and quantifying using spectrophotometry and chromatography techniques were also discussed. However, this will assist to reduce the uses and dependent on the synthetic drug and the onset of the age related diseases.

The international literature shows a polarised debate on the impacts of climate change on migration. Some studies find a positive linkage, whereas others find a negative one. It is, without a doubt, a complex process better considered case-specific. There is no available information on the relationship between climate change and migration in Colombia, despite past research exploring each of these subjects independently. This study intends explicitly to investigate this linkage gap. Consequently, this paper's essential contribution is that it builds a bridge between climate change scenarios and migratory science for the first time in Colombia. Despite their limitations, the theoretical and methodological framework suggested by IOM (2009b pp. 86, Section B, Chapter II) is demonstrated in this study to be very valid since it provides a methodology to predict where future flows will occur (based on past evidence). The methodological approaches of SLA and NELM explained in section A in the IV Chapter are also valuable for analysing and approaching this study's conclusions. The primary conclusions of this study indicate that the "Coffee Region," Valle, and Atlantic (or Caribbean Coast) provinces that mainly send emigrants to Spain and the US are the key internal regions responsible for most of the international migration from Colombians. The same areas are especially vulnerable to the impacts of upcoming climate change in the A1B scenario produced by the IDEAM (2010) for 2040 and 2100. Thus, future flows of migrants are expected from these regions (2040-2100). However, issues such as visa requirements or the costs associated with migration constitute international barriers to this flow. The sensitivity of these regions can also be associated with internal migration flows, more armed conflict, and forced displacement in a cyclical process. Theoretically, a resurgence of Colombia's armed conflict and displacement due to climate change can be expected. However, the need for empirical studies in Colombia to support this analysis is imperative and is the most crucial recommendation arising from this study.

Extracellular vesicles (EV), including exosomes and microvesicles, are released from various cells and alter recipient cell phenotypes and fates by their biomolecules. Here we review current knowledge about tumor EVs and how they prompt malignant cell communication with tumor-associated cells, such as cancer-associated fibroblasts, tumor endothelial cells, and immune cells. We delineate the major pathways and molecular players that influence each step of cancer initiation, progression, and resistance. Of note, cancer exosomes involve immunosuppression by tumor-associated macrophages, myeloid-derived suppressor cells, and regulatory T cells. Moreover, tumor exosomes can induce the apoptosis of killer T cells and immune checkpoint of dendritic cells and attenuate natural killer cells. An in-depth understanding of EV biology is essential to ensure the clinical development of exosome/EV-based therapeutic products, which will be of benefit to exosome manipulation in cancer management.

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

Good estimators are characterized as robust, unbiased, efficient, and consistent. However, the commonly used estimators are weak or lack one or more of these properties. In this article, eight (8) estimators for statistical and geometrical estimations of symmetry/asymmetry, similarity/dissimilarity, identity/unidentity, and feature transformation were proposed following Kabirian-based optinalysis and other operations. The proposed estimators are characterized as invariant (robust) under scaling, location shift, and rotation or reflection. A computing code was written in python language for each of the proposed estimators so that peers can have working codes for application and performance evaluation.

Tumorigenesis is a complex and dynamic process involving cell-cell and cell-extracellular matrix (ECM) interactions that allow tumor cell growth, drug resistance and metastasis. This review provides an updated summary of the role played by the tumor microenvironment (TME) components and hypoxia in tumorigenesis and highlight various ways through which tumor cells reprogram normal cells including into phenotypes that are pro-tumorigenic including cancer associated- fibroblasts, -macrophages and -endothelial cells. Tumor cells secrete numerous factors leading to transformation of a previously anti-tumorigenic environment into a pro-tumorigenic environment. Once formed, solid tumors continue to interact with various stromal cells including local and infiltrating fibroblasts, macrophages, mesenchymal stem cells, endothelial cells, pericytes, and secreted factors and the ECM within the tumor microenvironment (TME). The TME is key to tumorigenesis, drug response and treatment outcome. Importantly, stromal cells and secreted factors can initially be anti-tumorigenic but over time promote tumorigenesis and induce therapy resistance. To counter hypoxia, increased angiogenesis leads to formation of new vascular networks in order to actively promote and sustain tumor growth via supply of oxygen and nutrients whilst removing metabolic waste. Angiogenic vascular network formation aid in tumor cell metastatic dissemination. Successful tumor treatment and novel drug development require the identification and therapeutic targeting of pro-tumorigenic components of the TME including cancer-associated- fibroblasts (CAFs) and -macrophages (CAMs), hypoxia, blocking ECM-receptor interactions, in addition to targeting of tumor cells. Re-programming of stromal cells and the immune response to be anti-tumorigenic is key to therapeutic success. Lastly, this review highlights potential TME- and hypoxia-centred therapies under investigations.

Guessing effects frequently occur in testing data in educational or psychological applications. Different item response models have been proposed to handle guessing effects in dichotomous test items. However, it has been pointed out in the literature that the oftenemployed three-parameter logistic model poses implausible assumptions regarding the guessing process. The four-parameter guessing model has been proposed as an alternative to circumvent these conceptual issues. In this article, the four-parameter guessing model is compared with alternative item response models for handling guessing effects through a simulation study and an empirical example. It turned out that model selection for item response models should be rather based on the AIC than the BIC. However, the RMSD item fit statistic used with typical cutoff values was found to be ineffective in detecting misspecified item response models. Furthermore, sufficiently large sample sizes are required for sufficiently precise item parameter estimation. Moreover, it is argued that the criterion of statistical model fit should not be the sole criterion of model choice. The item response model used in operational practice should be valid with respect to the meaning of the ability variable and the underlying model assumptions. In this sense, the four-parameter guessing model could be the model of choice in educational large-scale assessment studies.

Aneuploidy describes the gain or loss of entire chromosomes or chromosome arms. Already more than 100 years ago, aneuploidy was described to be featured in cancer and it is known today to be present in 68-90 % of cancers, depending on tumour entity. Aneuploidy is implicated to affect cancer growth, therapy response and frequently affects prognosis. Chromosomal instability (CIN) is recognized as the main cause of aneuploidy and is characterised as the fluent process of gaining or losing chromosomes. Chromosomally instable cells need to be kept in check, or cleared, to prohibit the sampling of aneuploid karyotypes able to drive tumorigenesis. Of note, even aneuploid cancer cells often show CIN, a feature that promotes therapy related drug-resistance. Here, we review how CIN can be prevented or limited to spread by the induction of cell death and the relevance of different p53 responses triggered in response to mitotic perturbations to prohibit the formation of cancer driving aneuploidies.

Different hypotheses of carcinogenesis have been proposed based on local genetic factors and physiologic mechanisms. It is assumed that changes of the metric invariants of a biologic system (BS) determine general mechanisms of cancer development. Numerous data demonstrate an existence of three invariant feedback patterns of BS: negative feedback (NFB), positive feedback (PFB) and reciprocal links (RL). These base patterns represent basis elements of a Lie algebra and imaginary part of coquaternion. Considering coquaternion as a model of a functional core of a BS, conditions of the system can be identified with the points of three families of hypersurfaces in R⁴₂: hyperboloids of one sheet, hyperboloids of two sheets and double-cones. Corresponding quadratic form relates negative and positive entropy contributions of base elements to the energy level of the system, so that anabolic states of the system will correspond to the points of a hyperboloid of one sheet, while catabolic conditions to the points of a hyperboloid of two sheets. Equilibrium states will lie in a double cone. Hypothetically anabolic and catabolic states dominate intermittently oscillating around the equilibrium. Deterioration of base elements increases positive entropy and causes domination of catabolic states which is the main metabolic determinant of cancer. Corresponding trajectory of a malfunctioning system will have a tendency to remain inside the double cone.

: Emaravirus (Order Bunyavirales; Family Fimoviridae) is a genus comprising over 20 emerging plant viruses with a worldwide distribution and economic impact. Emaraviruses infect a variety of host plants and have especially become prevalent in important long-living woody plants. These viruses are enveloped, with a segmented, single-stranded, negative-sense RNA genome and are transmitted by eriophyid mites or mechanical transmission. Emaraviruses have four core genome segments encoding an RNA-dependent RNA polymerase, a glycoprotein precursor, a nucleocapsid protein, and a movement protein. They also have additional genome segments, whose number varies widely. We report here that the proteins encoded by these segments form three main homology groups: a homolog of the sadwavirus Glu2 Pro glutamic protease; a protein involved in pathogenicity, which we named “ABC”; and a protein of unknown function, which we named “P55”. The distribution of these proteins parallels the emaravirus phylogeny and suggests, with other analyses, that emaraviruses should be split into at least two genera. Reliable diagnosis systems are urgently needed to detect emaraviruses, assess their economic and ecological importance, and take appropriate measures to prevent their spread (such as routine testing, hygiene measures, and control of mite vectors). Additional research needs include understanding the function of emaravirus proteins, breeding resistant plants and clarifying transmission modes.

Both Stevens Johnson Syndrome (SJS) and toxic epidermal necrolysis (TEN) are main injurious cutaneous medication reactions that mostly affect the epidermis and mucus membranes. TEN and SJS affecting nearly 1 or 2/1,000,000 people per year, and can recognized as medical crises since they may be deadly. Mucocutaneous discomfort, hemorrhagic erosions, erythema, and more or less severe epidermal separation that appear as ulcer and patches of dermic loss are their defining characteristics. The sole difference between TEN and SJS at this time is the degree of skin detachment, making them two extremes of a spectrum of severe cutaneous adverse drug reactions (cADRs). In the majority of cases, drugs are considered as the principal reason of SJS/TEN, but herpes simplex virus and Mycoplasma pneumoniae infections are also recognized causes, along with lesser number of cases in which the cause is still unknown. Among the drugs with a "high" likelihood of producing TEN/SJS are carbamazepine (CBZ), trimethoprim-sulfamethoxazole, phenytoin, aminopenicillins, allopurinol, cephalosporins, other sulfonamide antibiotics, quinolones, phenobarbital, and NSAIDs of the oxicam variety. There is strong genetic evidence for SJS and TEN in Han Chinese due to the substantial association between the human leukocyte antigen (HLA-B*1502) and SJS brought on by CBZ. The diagnosis is made mostly based on clinical symptoms and the histological study of a dermal biopsy. Pemphigus vulgaris, bullous pemphigoid, linear IgA dermatosis, paraneoplastic pemphigus, disseminated fixed bullous drug eruption, acute generalized exanthematous pustulosis (AGEP), and staphylococcal scalded skin syndrome (SSSS) are among the differential diagnoses. The management of patients with SJS/TEN is complicated by the high risk of mortality, necessitating early diagnosis, estimation of the SCORTEN prognosis, identification and discontinuation of the causative drug, specialized supportive care, and high-dose injectable Ig therapeutic interventions. The reported fatality rates for SJS are 1-5% on average and 25-35% for TEN; it can be even higher in patients who are elderly or who have a significant amount of epidermal detachment on their skin. More than 50% of TEN patients who survive the disease experience long-term consequences.

An essential step in solving any topology optimization problem is determining the sensitivities of the objective function and optimization constraints. Unfortunately, these sensitivities are usually derived and implemented manually. Nontrivial objective functions and constraints, especially with the involvement of material and geometric nonlinearities, need strenuous mathematical derivation, leading to error-prone implementation. Another intriguing approach to finding sensitivities is automatic differentiation. This paper uses the automatic differentiation and adjoint method to find the sensitivities for two multiphysics topology optimization problems: 1) thermoelasticity and 2) piezoelectricity. This approach is not limited to these examples and can be easily extended to other single- or multi-physics topology optimization problems.

Background and objectives: The impact of prenatal exposure to polycyclicaromatic 17 hydrocarbons (PAHs) on birth outcomes as weight, length, head circumference, placenta 18 weight, and Apgar. Materials and Methods: Two cohorts of children born in the years 2013 and 19 2014 in Karvina (Northern Moravia, N=144) and Ceske Budejovice (Southern Bohemia, 20 N=198), were studied for the relationship between the prenatal exposure to PAHs and growth 21 parameters up to two years of age. PAHs exposure was evaluated according to the concentration 22 of benzo[a]pyrene (B[a]P) in polluted air and monohydroxylated PAH metabolites (OH-PAHs) 23 in urine of newborns as well as their mothers. Data of growth parameters were obtained from 24 pediatric questionnaires up to 24 months. 25 Results: Concentrations of B[a]P were significantly higher in Karvina (p<0.001). OH-26 PAH metabolites were significantly higher in the mothers´ as well as in the newborns´ urine in 27 Karvina. The length was shorter in newborns in Karvina at birth (p<0.001), but this difference 28 was straightened out during next 3 to 24 months. Birth weight at the delivery did not differ 29 between newborns in Karvina and Ceske Budejovice. Newborns in both locations significantly 30 decreased their weight gain between birth and 3 months after delivery. OH-PAHs metabolites 31 in mother’s or newborn’s urine did not affect birth weight. Top 25% values of concentrations 32 of 2-OH-FLUO, 1-OH-NAP, 2-OH-NAP, 1-OH-PHEN, 2-OH-PHEN, 3-OH-PHEN, 4-OH-33 PHEN, and the sum of all-OH-PAHs higher than median in the newborns´ urine decreased their 34 length. 2-OH-PHEN top 25% of concentrations in the newborns´ urine decreased their head 35 circumference, 2-OH-FLUO, 1-OH-NAP, 2-OH-NAP, 1-OH-PHEN, 2-OH-PHEN, 3-OH-36 PHEN, 4-OH-PHEN, 9-OH-PHEN, 1-OH-PYR, and all-OH-PAHs decreased placenta weight; 37 2-OH-FLUO, 1-OH-NAP, 2-OH-NAP, 1-OH-PHEN, 2-OH-PHEN, 3-OH-PHEN, 4-OH-38 PHEN, and all-OH-PAHs decreased Apgar 5´. Conclusions: We observed that higher 39 concentration of PAHs determined as OH-PAHs metabolites in newborns´ urine decreased their 40 length, head circumference, placenta weight, and Apgar 5´, but did not affect birth weight.

There has been a surge in the interest for (semi)transparent photovoltaics (sTPVs) in recent years, since the more traditional, opaque, devices are not ideally suited for a variety of innovative appli-cations spanning from smart and self-powered windows for buildings to those for vehicle inte-gration. Additional requirements for these photovoltaic applications are a high conversion effi-ciency (despite the necessary compromise to achieve a degree of transparency) and an aesthetical-ly pleasing design. One potential realm to explore in the attempt to meet such challenges is the bio-logical world, where evolution has led to highly efficient and fascinating light-management structures. In this mini-review, we explore some of the biomimetic approaches that can be used to improve both transparent and semitransparent photovoltaic cells, such as moth-eye inspired structures for improved performance and stability or tuneable, coloured, and semi-transparent devices inspired by beetles’ cuticles. Lastly, we will briefly discuss possible future developments for bio-inspired and potentially bio-compatible sTPVs.

Intratumor heterogeneity (ITH) is associated with therapeutic resistance and poor prognosis in cancer patients, and attributed to genetic, epigenetic, and microenvironmental factors. We developed a new computational platform, GATHER, for geostatistical modeling of single cell RNA-seq data to synthesize high-resolution and continuous gene expression landscapes of a given tumor sample. Such landscapes allow GATHER to map the enriched regions of pathways of interest in the tumor space and identify genes that have spatial differential expressions at locations representing specific phenotypic contexts using measures based on optimal transport. GATHER provides new applications of spatial entropy measures for quantification and objective characterization of ITH. It includes new tools for insightful visualization of spatial transcriptomic phenomena. We illustrate the capabilities of GATHER using real data from breast cancer tumor to study hallmarks of cancer in the phenotypic contexts defined by cancer associated fibroblasts.

ZnO was synthesized by Sol gel method using zinc nitrate as precursor at different calcination temperatures. Nucleation of ZnO crystallites and their growth with rise in temperature was observed. Exciton bands and lattice imperfections affected the absorption spectra. The decrease in band gap with temperature was due to the formation of defect energy levels. Phonon assisted non-radiative transitions caused broadening of the peaks. The possibility of tuning the band gap of ZnO by changing the temperature was explored. Simulation studies showed transition to single phase with rise in temperature.

Excessive production, consumption and indiscriminate disposal of plastic waste cause an increasing plastic pollution with detrimental impacts on environment and human health. This study aimed to assess the level of knowledge, attitude, and practices (KAP) towards plastic pollution among Malaysians and evaluate the variation of plastic pollution related KAP among various socio-demographics. An online survey was conducted, and 294 valid responses was obtained. Descriptive statistics, KAP scoring and cross tabulation of responses were estimated. One-way analysis of variance, paired t-test and binary logistic regressions were carried out. Results showed that respondents had poor knowledge (mean 7.41 ± 1.80) and practice score (3.81 ± 1.39) across all socio-demographics. Compared to younger (18-30 years) respondents, older ones (>46 years) had higher knowledge (odds ratio, OR 4.304; p<0.01). However, middle aged (31-45 years) respondents reported significantly (p<0.01) higher attitude (OR 4.019) and practice (OR 4.056; p <0.05). Respondents with environmental related university education had showed higher odds about plastic pollution related knowledge (OR 10.343; p<0.01). Suggestions are made to undertake interventions such as environmental awareness creation, incorporating plastic pollution topics in formal and informal education, and providing recycling facilities nearby the localities for encouraging good practices towards minimizing plastic uses and pollution.

This computational research study will compare the specific charge capacity (SCC) between lithium ions inserted into crystallize silicon (c-Si) nanowires versus sodium ions inserted into amorphous silicon (a-Si) nanowires. It will be demonstrated that the potential energy V(r) within the lithium-silicon nanowire supports a coherent energy state model with discrete electron particles while the sodium-silicon nanowire potential energy will be discovered to be essentially zero and thus the electron current that travels through the sodiated silicon nanowire will be modeled as free electron with wave-like characteristics. This is due to the vast differences in the electric fields of the lithiated and sodiated silicon nanowires where the electric fields are of the order of 1e10 V/m and 1e-15 V/m respectively. The main reason for the great disparity in electric fields are due to the present of optical amplification within lithium ions and the absence of this process within sodium ions. It will be shown that optical amplification develops coherent optical interactions which is the primary reason for the surge of specific charge capacity in the lithiated silicon nanowire. Conversely, the lack of optical amplification is the reason for the incoherent optical interactions within sodium ions which is the reason for the low presence of SCC in sodiated silicon nanowires.

The literature on contract farming and climate change in Zimbabwe has blind spots in relation to the study of contract farming as a climate change response. While the literature on contract farming and climate change abounds, such literature is lacking when it comes to the exploration of how contract farming can facilitate climate change coping and adaptation strategies by smallholder farmers. This paper fills this gap. It draws on in-depth interviews with 10 contracted and 10 non-contract farmers who were engaged through face-to-face in-depth interviews in the Chipinge South Constituency. It found that contract farming does not only boost productivity, but it also enables farmers to positively respond to the ravages of climate change, and therefore, it should be supported and encouraged. Future research should explore more viable and sustainable way through which the state, instead of private sector actors, should be at the centre of contract farming.

We present results on the spontaneous crystallization of freely-jointed polymers of hard spheres obtained in an unprecedentedly long Monte Carlo (MC) simulation on a system of 54 chains of 1000 monomers. Starting from a purely amorphous configuration and after a transitory dominance of the hexagonal closed packed (HCP) polymorph, the system crystallizes in a final, stable, face centered cubic (FCC) crystal of very high perfection. Through refined metrics we gauge the degree of ordering and identify the regions of the phase transition and the corresponding morphologies. An analysis of chain conformational characteristics, of the spatial distribution of monomers and of the volume accessible to them shows that the phase transition is caused by an increase in translational entropy that is larger than the loss of conformational entropy of the chains in the crystal compared to the amorphous state. Polymer chains in the crystal adopt ideal random walk statistics as their great length renders local conformational details, imposed by the geometry of the FCC crystal, irrelevant.

This paper develops feasible control strategies and associated system responses to bring an autonomous front-axle bicycle robot from specified initial conditions to final conditions such that a specific performance index is minimized. To solve the problem, the following approach is used: The feasible controls derived from the normal equations of optimality are substituted into the state and the costate systems and form a combined control-free state-costate system which is vectorized to enable and ease the application of a numerical method. A computer program written in Matlab computer programming language, codes a fourth-order Runge-Kutta numerical method and then solve the combined state-costate system of ordinary differential equations. The obtained results are the feasible bicycle robot trajectory, the feasible state functions, the feasible costate functions and the feasible control functions. Associated Computational Simulations are designed and provided to persuade on the effectiveness and the reliability of the approach.

Let $\mathbb{K}$ be a non-Archimedean (complete) valued field satisfying \begin{align*} \left|\sum_{j=1}^{n}\lambda_j^2\right|=\max_{1\leq j \leq n}|\lambda_j|^2, \quad \forall \lambda_j \in \mathbb{K}, 1\leq j \leq n, \forall n \in \mathbb{N}. \end{align*} For $d\in \mathbb{N}$, let $\mathbb{K}^d$ be the standard $d$-dimensional non-Archimedean Hilbert space. Let $m \in \mathbb{N}$ and $\text{Sym}^m(\mathbb{K}^d)$ be the non-Archimedean Hilbert space of symmetric m-tensors. We prove the following result. If $\{\tau_j\}_{j=1}^n$ is a collection in $\mathbb{K}^d$ satisfying $\langle \tau_j, \tau_j\rangle =1$ for all $1\leq j \leq n$ and the operator $\text{Sym}^m(\mathbb{K}^d)\ni x \mapsto \sum_{j=1}^n\langle x, \tau_j^{\otimes m}\rangle \tau_j^{\otimes m} \in \text{Sym}^m(\mathbb{K}^d)$ is diagonalizable, then \begin{align}\label{WELCHNONABSTRACT} \max_{1\leq j,k \leq n, j \neq k}\{|n|, |\langle \tau_j, \tau_k\rangle|^{2m} \}\geq \frac{|n|^2}{\left|{d+m-1 \choose m}\right| }. \end{align} We call Inequality (\ref{WELCHNONABSTRACT}) as the non-Archimedean version of Welch bounds obtained by Welch [\textit{IEEE Transactions on Information Theory, 1974}]. We formulate non-Archimedean Zauner conjecture.

new subsonic blower wind tunnel design has been studied both numerically and experimentally, it is also referred to as “blower” wind tunnel. This paper, is initially aimed to address each sequential stage of the wind tunnel design process. Rather than applying the standard method of modelling solely the flow in the test section, a large-scale CFD model of the whole wind tunnel was employed. The loss of every constituent element was calculated and then all the losses are added up to determine the power needed for the wind tunnel operation which is used as “intake fan” boundary conditions in the CFD model. Then, flow uniformity and turbulent intensity measurements in an empty test section using a Pitot-static tube and hot wire anemometer (HWA) were introduced to validate the CFD results. The results showed that flow quality was significantly affected by boundary layer controllers (honeycomb and mesh screens) in the settling chamber and wide-angle diffuser. Investigations were also conducted to evaluate the flow deficit in the wake area behind a convex hump model using HWA. This was additional experimental tests carried out to validate the suitability of the wind tunnel flow aerodynamic research.

Globally, zoonotic diseases have been on the rise in recent years. Predictive modelling approaches have been successfully used in the literature to identify the underlying causes of these zoonotic diseases. We examine the latest research in the field of predictive modeling that verifies the growth of zoonotic pathogens and assesses the factors associated with their spread. The results of our survey indicate that popular mathematical models can successfully be used in modeling the growth rate of these pathogens under varying storage temperatures. Additionally, some of them are used for the assessment of the inactivation of these pathogens based on various conditions. Based on the results of our study, machine learning models and deep learning are commonly used to detect pathogens within food items and to predict the factors associated with the presence of the pathogens.

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical space they encompass is far from being fully explored. Over history, NPs have represented a significant source of bioactive molecules and have served as a source of inspiration for developing many drugs on the market. On the other hand, computer-aided drug design (CADD) has contributed to drug discovery research, mitigating costs and time. In this sense, compound databases represent a fundamental element for the CADD. This work reviews the progress toward developing compound databases of natural origin, particularly databases developed in Latin America, and their practical applications in the drug discovery area. We also survey the computational methods, emphasizing chemoinformatic approaches to profile natural product databases.

Visualization of deep biological structures in human and animal bodies is not possible through the naked eye due to the scattering of visible light by tissues in tolerable intensities. Different types of imaging modalities based on electromagnetic and pressure waves have been developed that help us image deep biological tissues with varying resolution and contrast. Some of the most widely used modalities are X-ray imaging, ultrasound imaging, MRI imaging, fluorescence imaging, and photoacoustic imaging. Although these techniques have significantly helped the advancement of our understanding of deep biological tissues and functions, they often require the use of exogenous contrast agents to improve their image quality for better investigation. Nanoparticle-based contrast agents have captivated scientists because of multiple advantages associated with them such as their excellent photophysical and chemical properties, ability to be precisely delivered at the target, and superlative tunability. This article is aimed to give a brief outlook on the recent state of art advances in the usage of nanoparticles for preclinical and clinical bioimaging through fluorescence, photoacoustic, and MRI imaging modalities.

As the scarcity of potable water increases, recycling of treated wastewater is increasing. Small-scale, decentralized treatment can be implemented to serve local populations by keeping water within their boundaries and within reach for reuse, particularly in less dense, non-urban communities. Availability of cellular networks and high-speed internet connectivity, along with significant reduction in cost, allows ongoing monitoring of decentralized treatment systems at a central location. In this paper a decentralized treatment system using micro nanobubble aeration, moving media and membranes is able to produce reusable water with low energy consumption, thereby allowing the use of solar energy in places with unreliable electrical supply. The treatment system, which uses no external chemicals, is able to operate unattended and deliver clear, disinfected water with non-detect suspended solids, BOD5 less than 10 mg/L and nutrients below 5 mg/L.

We propose a novel interpretation of consciousness and an enlarged definition of locality, which provide a solution to the problem of the consistency of measurements in quantum mechanics: consciousness is a characteristics of the Universe as a whole. Besides its physical conse- quences, this interpretation has also moral implications: individuality comes out naturally to be just an accident functional to evolution which shaped past and present history through competition, and re- alizing this fact should enforce cooperation.

Enterovirus A71 (EV-A71) infection is a major cause of hand, foot and mouth disease (HFMD) which may be occasionally associated with severe neurological complications. There are currently a lack of treatment options for EV-A71 infection. The Raf-MEK-ERK signaling pathway, in addition to its critical importance in the regulation of cell growth, differentiation and survival, has been shown to be essential for virus replication. In this study, we investigated the anti-EV-A71 activity of vemurafenib, a clinically approved B-Raf inhibitor used in the treatment of late stage melanoma. Vemurafenib exhibits potent anti-EV-A71 effect in cytopathic effect inhibition and viral load reduction assays, with half maximal effective concentration (EC50) at nanomolar concentration. Mechanistically, vemurafenib interrupts both EV-A71 genome replication and assembly. These findings expand the list of potential antiviral candidates of anti-EV-A71 therapeutics.

Gestational diabetes mellitus (GDM) is a common complication of pregnancy that adversely affects maternal and offspring health. A variety of risk factors, such as BMI and age, have been associated with increased risks of gestational diabetes. However, in many cases gestational diabetes occurs in healthy nulliparous women with no obvious risk factors. Emerging data suggest that the tendency to develop gestational diabetes has genetic and environmental components. Here we develop a polygenic risk score for gestational diabetes. We further investigate relationships between the genetic architecture of GDM and genetically constructed risk factors and biomarkers. Our results show that genetics can be used as an early screening tool that identifies at-risk at higher risk of GDM before its onset to propose comprehensive monitoring and preventative programs to mitigate the risks.

Background: The reliability of a recent review of meningiomas in the archeologic record was difficult to assess, given the inverted sex ratio of the report and other contents apparently at variance with anatomical/medical findings in scientifically-identified cases. It therefore seemed appropriate to reexamine the nature of meningiomas and derive improve criteria for their recognition in the archeologic record and distinguish them from hemangiomas and bone marrow hyperplasia (recognized in the form of porotic hyperostosis). Methods: Medically-documented cases of meningiomas, hemangiomas and cranial bone marrow hyperplasia were examined to establish a macroscopic standard that distinguishing among them. Alleged cases in the archeologic record were examined for conformity with those criteria. Results: An en face pattern of uniform mesh with contained whorls appears pathognomonic for meningiomas. This contrasts with the non-uniform marrow expansion displacement of trabeculae in porotic hyperostosis and non-uniform vascular displacement of trabeculae in hemangiomas. Reassessment of past attributions revealed few cases of meningiomas that could be confidently diagnosed. Those identified has sex ratios parsimonious with medical literature reports. Conclusions: Criteria suggested for identifying meningiomas permits distinguishing from hemangiomas, bone marrow hyperplasia (porotic hyperostosis) and from the macroscopically-observable surface spicules characteristic of osteosarcomas. Examination for fulfillment of criteria for meningiomas and hemangiomas seems to provide a picture (including sex ratios) more parsimonious with the clinical literature, concluding that Cook and Danforth’s disparate ratios were related to less fastidious case selection. Additionally, confidence in recognizing porotic hyperostosis may be compromised because of apparent similar macroscopic alterations to those seen with hemangiomas.

The snap fit is a common mechanical mechanism. We have studied the spherical snap fit carefully for its physical asymmetry which is easy to assemble but difficult to disassemble, and obtained the general law.Because of the complexity of spherical structure, it is difficult to get a theoretical formula to describe its physical asymmetry.In this paper, through the method of combining theory, simulation and experiment, and based on the general rule of cylindrical snap fit obtained in the early stage, pushing assembly and pulling disassembly of spherical snap fit are studied,we not only get the theoretical formula of spherical snap fit, but also further verify the correctness of previous research conclusions on cylindrical snap fit.This research provides strong theoretical support and basis for the optimization design and further research of snap fit.

The article provides an overview of nanocomposites and microelectronic elements used in space electronics and radiation control systems of nuclear reactors. Only those nanocomposites and microelectronic elements are taken into account that improve their characteristics in radiation fields or remain indifferent when exposed to ionizing radiation. Considering the chemical composition of the materials of these nanocomposites and microelectronic elements, it is analyzed from which radioactive materials (RM) obtained by recycling radioactive waste (RW) such composites and microelectronic parts can be made. Thus, an alternative way of radioactive waste disposal is proposed, when these wastes are used in the form of microelectronic elements designed to operate under conditions of cosmic radiation.

“Non-Locality is most naturally incorporated into a theory in which there is a special frame of reference. One possible candidate for this special frame of reference is the one in which the Cosmic Microwave Background (CMB) is isotropic. However, other than the fact that a realistic interpretation of quantum mechanics requires a preferred frame and the CMB provides us with one, there is no readily apparent reason why the two should be linked” (L. Hardy). Starting from this remark we first argue that, given the present view of the vacuum, the basic tenets of Quantum Field Theory cannot guarantee that Einstein Special Relativity, with no preferred frame, is the physically realized version of relativity. Then, to try to understand the nature of the hypothetical preferred Σ−frame, we consider the so called ether-drift experiments, those precise optical measurements that try to detect in laboratory a small angular dependence of the two-way velocity of light and then to correlate this angular dependence with the direct CMB observations with satellites in space. By considering all experiments performed so far, from Michelson-Morley to the present experiments with optical resonators, and analyzing the small observed residuals in a modern theoretical framework, the long sought Σ− frame tight to the CMB naturally emerges. Finally, if quantum non-locality reflects some effect propagating at vastly superluminal speed vQI→∞, its ultimate origin could be hidden somewhere in the infinite speed cs→∞ of vacuum density fluctuations.

Spectrometers have a wide range of applications ranging from optical to non-optical spectroscopy. The need for compact, portable, and user-friendly spectrometers has been the pivot of attention from small laboratories to the industrial scale. Here, the Czerny Turner configuration-based optical spectrometer simulation design is carried out using ZEMAX OpticStudio. A compact and low-cost optical spectrometer in the visible range has been developed by using diffraction grating as a dispersive element and USB-type WebCAM CCD (Charge-coupled device) as a detector instead of an expensive commercial diffraction grating and detector. Using National Instruments LabVIEW, data acquisition, processing, and displaying techniques are made possible. We have employed different virtual images in LabVIEW programs to collect the pixel-to-pixel information and wavelength-intensity information from the image captured using the WebCAM CCD. Finally, we have shown that the OpticStudio-based spectrometer and experimental measurements of the developed spectrometer are in good agreement.

Indoor scene recognition and semantic information can be helpful for social robots. Recently, in the field of indoor scene recognition, researchers have incorporated object-level information and shown improved performances. This paper demonstrates that scene recognition can be performed solely using object-level information in line with these advances. A state-of-the-art object detection model was trained to detect objects typically found in indoor environments and then used to detect objects in scene data. These predicted objects were then used as features to predict room categories. This paper successfully combines approaches conventionally used in computer vision (YOLO) and Term Frequency-Inverse Document Frequency (TF-IDF). These approaches could be further helpful in the field of embodied research and dynamic scene classification, which we elaborate on.

This paper aims to introduce an overview of several aspects of the so-called Artificial Intelligence, their potential impacts on economic and social dimen- sions, and suggestions for possible approaches of investiment based upon effective and mature techniques. In this fashion, it is important to address from educational and academic issues to industrial densities and profiles, rel- atively to a given region, country or continent. Even etymological adequacy and psychological consequences of the denomination ”Artificial Intelligence” need some reflection, and suggestions for a lucid replacement are presented. In addition, suggestions about how can specific firms choose the right type of technique in order to improve profit and organizational efficiency. After all, what are the main transformations needed to amplify gains and structural improvements from the use of higher level technological mecha- nisms? Which connections can be established between the pillars of evolu- tionary economics and this field of knowledge? Which institutional contexts are able to benefit from AI tools, inducing constructive externalities to firms in terms of education, technical and scientific skills upgrading, so as to reach higher levels of employment in the long term and limit unemployment in the short one? Which branches of the so-called Artificial Intelligence are best suited to which types of activities? This work aims to contribute in the search for answers to these questions.

Nowadays molecular and immunological research is essential for the better understanding of tumor cells pathophysiology. The increasing number of neoplasms is taken under ‘the molecular magnifying glass’ therefore it is possible to discover complex relationships between cytophysiology and immune system action. An example could be renal cell carcinoma (RCC) which has deep interactions with immune mediators such as Interleukin 17 (IL-17) - an inflammatory cytokine reacting to tissue damage and external pathogens. RCC is one of the most fatal urological cancer because of its often late diagnosis and poor susceptibility to therapies. IL-17 and its relation with tumors is extremely complex and constitute a recent topic for numerous research. What is worth highlighting is IL-17 dual character in cancer development - it could be pro- as well as antitumorigenic. The aim of this review is to summarize the newest data considering multiple connections between IL-17 and RCC.

The common dandelion uses a bundle of drag-enhancing bristles (the pappus) that enables seed dispersal over formidable distances; however, the scaling laws of aerodynamic drag underpinning pappus-mediated flight remains unresolved. In this paper, we study the aerodynamic shape of dandelion, derive the scaling law of resistance, determine the Vogel exponent. In particular, we find that the total drag coefficient is proportional to the -2/3 power of the dandelion pappus Reynolds number, and obtain the terminal velocity of the dandelion seed under gravitation field.

Fecal microbiota transplantation (FMT) is an emerging therapeutic option for a variety of diseases, which is characterized as transferring fecal microorganisms from a healthy donor into the intestinal tract of a diseased receipt. In human clinics, FMT has been used for treating diseases for decades with promising results. In recent years, veterinary specialists adapted FMT in canine patients, however, compared to humans, canine FMT is more inclined to research purposes than practical applications in most cases due to safety concerns. Therefore, in order to facilitate the application of fecal transplant therapy in dogs, in this paper, we aimed to review recent application of FMT in canine clinical treatments as well as possible mechanisms that are involved in the process of therapeutic effect of FMT.

I want to find an extension of the Hausdorff Measure and Fractal Measure which allows me to compute a unique, satisfying average for functions defined on non-fractal, measurable sets in the sense of Carathedory which has no gauge function.

The soft robot has many degrees of freedom, strong environmental adaptability and good human-computer interaction ability. As the end-effector of the soft robot, the soft gripper can grasp objects of different shapes without destructivity. Based on the theoretical analysis of the soft robot, the kinematics model of the flexible gripper and the theoretical model of the bending deformation of the air cavity were established. Accordingly, the relationship between the bending angle of the soft gripper and the air pressure was determined. Through the application of finite element software, the bending degree of pneumatic network multi-cavity soft gripper was simulated by finite element software, and the influence of structural parameters of soft actuator on bending deformation was determined. In addition, with the 3D technology conducting the printing of soft gripper fixtures and molds, the injection molding the actuator and the human-computer interaction interface controlling the movement of the gripper, the adaptability of the soft gripper in grasping object was verified. The result shows that the software gripper possesses good flexibility and can better grasp objects of different shapes.

Despite several decades’ effort to detect and identify phytoplasmas (Tenericutes: Mollicutes) using PCR and Sanger sequencing focusing on diseased plants, knowledge of phytoplasma biodiversity and vector associations remains highly incomplete. To improve protocols for documenting phyto-plasma diversity and ecology, we used DNA extracted from phloem-feeding insects and com-pared traditional Sanger sequencing with a next-generation sequencing method, Anchored Hy-brid Enrichment (AHE) for detecting and characterizing phytoplasmas. Among 22 of 180 leaf-hopper samples that initially tested positive for phytoplasmas using qPCR, AHE yielded phyto-plasma 16Sr sequences for 20 (19 complete and 1 partial sequence) while Sanger sequencing yield-ed sequences for 16 (11 complete and 5 partial). AHE yielded phytoplasma sequences for an addi-tional 7 samples (3 complete and 4 partial) that did not meet the qPCR threshold for phytoplasma positivity or yielded non-phytoplasma sequences using Sanger sequencing. This suggests that AHE is more efficient for obtaining phytoplasma sequences. Twenty-three samples with sufficient data were classified into eight 16Sr subgroups (16SrI-B, I-F, I-AO, III-U, V-C, IX-J, XI-C, XXXVII-A), three new subgroups (designated as 16SrVI-L, XV-D, XI-G) and three possible new groups. Our results suggest that screening phloem-feeding insects using qPCR and AHE sequencing may be the most efficient method for discovering new phytoplasmas.

We study the deterministic dynamics of N point particles moving at constant speed in a 2D table made of two polygonal urns connected by an active rectangular channel, which applies a feedback-control on the particles, inverting the horizontal component of their velocities, when their number in the channel exceeds a fixed threshold. Such a bounce--back mechanism is non-dissipative: it preserves volumes in phase space. An additional passive channel closes the billiard table forming a circuit in which a stationary current may flow. Under specific constraints on the geometry and on the initial conditions, the large N limit allows nonequilibrium phase transitions between homogeneous and inhomogeneous phases. The role of ergodicity in making a probabilistic theory applicable is discussed both for rational and irrational urns. The theoretical predictions are compared with the numerical simulation results. Connections with the dynamics of feedback-controlled biological systems are highlighted.

Epilepsy is a chronic neuronal disorder characterized by periodic, unpredictable, and recurrent seizures due to either a genetically determined or an acquired brain disorder. Although many anti-epileptics drugs (AEDs) are developed to control epilepsy, 30% of patients still need additional drugs or experience recurrent seizures and psychiatric and behavioral side effects. Thus, the need for medical care for patients with uncontrolled epilepsy remains unmet. The Genus Artemisia L. is one of the largest genera in the Asteraceae family with more than 500 species widely distributed in Europe, Asia, and North America. Many Artemisia species have been used in various treatments since ancient times as folk remedies. They demonstrated strong antioxidant, anti-inflammatory, antimicrobial, antimalarial, and antitumor activity. Recent studies reveal that some species of Artemisia demonstrated a therapeutic benefit for epilepsy by its anti-oxidant, anti-inflammatory, neuroprotective, and anticonvulsant properties. In this review, we investigate the current state of the literature regarding the neuroprotective and antiepileptic potentials of the genus Artemisia and its possible underlying mechanisms.

Molecular motors play a vital role in the transport of material within the cell. A family of motors of growing interest are burnt bridge ratchets (BBRs). BBRs rectify spatial fluctuations into directed motion by creating and destroying motor-substrate bonds. It has been shown that the motility of a BBR can be optimized as a function of the system parameters. However, the amount of energy input required to generate such motion and the resulting efficiency has been less well characterized. Here, using a deterministic model, we calculate the efficiency of a particular type of BBR, namely a polyvalent hub interacting with a surface of substrate. We find that there is an optimal burn rate and substrate concentration that leads to optimal efficiency. Additionally, the substrate turnover rate has important implications on motor efficiency. We also consider the effects of force-dependent unbinding on the efficiency and find that under certain conditions the motor works more efficiently when bond breaking is included. Our results provide guidance for how to optimize the efficiency of BBRs.

When computers start to become a dominant part of technology around the 1950s, fundamental questions about reliable designs and robustness were of great relevance. Their development gave rise to the exploration of new questions such as what made brains reliable (since neurons can die) and how computers could get inspiration from neural systems. In parallel, the first Artificial Neural Networks came to life. Since then, the comparative view between brains and computers has been developed in new, sometimes unsuspected directions. With the rise of deep learning and the development of connectomics, an evolutionary look at how both hardware and neural complexity have evolved or designed is required. In this paper, we argue that important similarities have resulted both from convergent evolution (the inevitable outcome of architectural constraints) and inspiration of hardware and software principles guided by toy pictures of neurobiology. Moreover, dissimilarities and gaps originate from the lack of major innovations that have paved the way to biological computing (including brains) that are completely absent within the artificial domain. As it occurs within synthetic biocomputation, we can also ask whether alternative minds can emerge from A.I.\ designs. Here we take an evolutionary view of the problem and discuss the remarkable convergences between living and artificial designs and what are the pre-conditions to achieve artificial intelligence.

Transposable elements (TEs) ubiquitously exist in the human genome, and some have the ability to copy and paste themselves to other locations, resulting in new insertions. Organisms have evolved with mechanisms and machineries to repress such activity. TEs are also co-opted for beneficial functions by the host and are thus maintained in the genome. During the lifetime of humans, aberrant TE activity might cause or contribute towards diseases including neurological conditions such as Alzheimers Disease (AD) and cancer. While inflammatory pathways linked to TEs may be a part of the disease pathology, on the other hand altered TE activity involving inflammatory pathways could be recognised by disease suppression mechanisms. For this reason, TEs could be targeted for therapeutic applications aiming to prevent TE activity or reduce initial inflammatory pathways as well as to activate disease suppression mechanisms. In this review, we describe the contributory and potential preventative roles of TEs in neurological conditions and cancer from a molecular and evolutionary perspective. Evolutionary paradigms both at the unicellular and organismal level aid understanding the role of TEs in disease. These observations could pave the way for the development of novel therapeutic approaches targeting TEs.

Spatial crowdsourcing emerges as a new computing paradigm that enables mobile users to accomplish spatio- temporal tasks in order to solve human-intrinsic problems. Existing crowdsourcing systems critically use centralized servers for interacting with workers and making task assignment decisions. These systems are hence susceptible to issues such as the single point of failure and the lack of operational transparency. Prior work, therefore, turns to blockchain-based decentralized crowdsourcing systems, yet still suffers from problems of lacking efficient task assignment scheme, requiring a deposit to an untrusted system, low block generation speed, and high transaction fees. To address these issues, we design a blockchain-based decentralized framework for spatial crowdsourcing, which we call SC-EOS. Our system does not rely on any trusted servers, while providing efficient and user-customizable task assignment, low monetary cost, and fast block generation. More importantly, it frees users from making a deposit into an untrusted system. Our framework can also be extended and applied to generic crowdsourcing systems. We implemented the proposed system on the EOS blockchain. Trace-driven evaluations involving real users show that our system attains the comparable task assignment performance against a clairvoyant scheme. It also achieves 10× cost savings than an Ethereum-based implementation.

Marketing is the manner of how to make our sales the best in the market, our prices the most accessible, our clients satisfactory, and thus our brand is the largest distributed. This needs sophisticated and advanced understanding of the total network related. Indeed, marketing data may be seen in different forms such as qualitative and quantitative. However, in the literature, it is easily noticed that large bibliography may be collected about qualitative studies, against few studies on the quantitative point of view. This is a major drawback that makes the marketing science still focusing on the design, although the market is strongly depending on quantities such as money and time. Indeed, marketing data may be a time series such as brand sales per specified periods, brand related-prices over specified periods, market shares, ..., etc. The purpose of the present work is to investigate some marketing models based on time series due to brands. We will precisely study the effect of the time scale on the persistence of brands sales in the market and on the forecasting of such a persistence according to the characteristics of the brand and the related market competition or competitors. Our study is acted on a sample of Saudi brands during the period November 22, 2017 to December 30, 2021.

Habituation is the most ancient and fundamental form of learning. As a firewall that protects our brain from sensory overload, it is indispensable for higher cognitive processes. Studies in humans and animal models provide a growing body of evidence that habituation is affected in autism and related monogenic neurodevelopmental disorders (NDDs). An integrated application of habituation assessment in NDDs and their animal models has currently unexploited potential for fundamental neuroscience and medical care.With the aim to gain mechanistic insights, we systematically retrieved genes that have been demonstrated in the literature to underlie habituation. We identified 258 evolutionarily conserved genes across species, describe the biological processes they converge on, and highlight regulatory pathways and drugs that may alleviate the habituation deficits associated with their dysregulation. We also summarize current habituation paradigms and extract the most decisive arguments from the literature that support the crucial role of habituation for cognition in health and disease. We conclude that habituation is a conserved, quantitative, cognition- and disease-relevant process that can connect preclinical and clinical work, and hence is a powerful tool to advance research, diagnostics,’’ and treatment of NDDs.

Land tenure security is important for achieving a number Sustainable Development Goals (SDGs). The purpose of this paper was to investigate variation in land tenure security across three districts located in different geographical regions of Uganda. Using a quantitative cross-sectional survey data collected in early 2019. The findings show that Kanungu district found in South-Western Uganda had significantly higher levels of land tenure security as compared to Nakasongola (Central) and Nwoya (Northern). Research findings have implications on further study and benchmarking land governance systems in Kanungu. Furthermore, they have implications on implementation of government and donor land titling or registration programs in terms of priority areas. They further sheds light on the importance of accounting for geographical context in land tenure studies.

One of the areas of research on materials for thin-film solar cells focuses on replacing In and Ga with more earth-abundant elements. In that respect, chalcostibite (CuSbS2) is being considered as a promising environmentally friendly and cost-effective photovoltaic absorber material. In the present work, single CuSbS2 phase have been synthesized directly by a short duration (2 h) mechanochemical synthesis step starting from mixtures of elemental powders. X-ray diffraction analysis of the synthesized CuSbS2 powders revealed a good agreement with the orthorhombic chalcostibite phase, space group Pnma, and a crystallite size of 26 nm. Particle size characterization revealed a multimodal distribution with a median diameter ranging from of 2.93 m to 3.10 m. The thermal stability of the synthesized CuSbS2 powders was evaluated by differential thermal analysis. No phase change was observed by heat treating the mechanochemically synthesized powders at 350 C for 24 h. By UV-VIS-NIR spectroscopy the optical bandgap was determined to be 1.41 eV, suggesting that the mechanochemically synthesized CuSbS2 can be considered suitable to be used as absorber materials. Overall, the results show that the mechanochemical process is a viable route for the synthesis of materials for photovoltaic applications.

In 1789, the Annonaceae family was cataloged by de Jussieu. It encompasses tropical and subtropical plants which are widespread in distribution across various continents such as Asia, South and Central America, Australia and Africa. The genus of Annona is one of the 120 genera of the Annonaceae family and contains more than 119 species of trees and shrubs. The majority of these species are found in tropical America with more than 105 species (26 of them are endemic). Due to its edible fruits and medicinal properties, Annona is the most important genus of Annonaceae family. Despite Annona having many species, only limited species of this family are economically important such as A. squamosa L. (sugar apple), A. cherimola Mill. (Cherimoya), A. muricata L. (guanabana or soursop), A. atemoya Mabb. (atemoya), a hybrid between A. cherimola and A. squamosa, A. reticulata L. (custard apple), A. glabra L. (pond-apple) and A. macroprophyllata Donn. Sm. (ilama). Phytochemically, several classes of secondary metabolites such as acetogenins, essential oils, alkaloids, terpenoids and flavonoids have been described in this genus. A variety of pharmacological activities have been reported from various parts of Annona species specially leaves and seeds including applications against antibacterial, anticancer, antidiabetic and anti-inflammatory.

Emission, propagation, and reflection of light as mechanical phenomena in inertial frames are based on the behavior of balls at the limit when their mass is zero. The kinematics of massless balls is like that of balls with mass. Light as a wave or particle is a massless entity. Therefore, it is natural to apply the kinematics of the massless balls to light. Consequently, the kinematics of light depends on its kinetics of electromagnetic nature and its kinematics of mechanical nature in its interactions of emission and reflection with the matter. The study of the physics phenomena in the frame at absolute rest includes those in the inertial frames. Considering this and applying the emission, propagation, and reflection of light as mechanical phenomena in the vacuum of the frame at absolute rest, this study derives formulas for the speed of the wavefront of a ray of light reflected by a fixed and moving mirror when the light comes from a fixed and moving source. The derived formulas apply to the modified Michelson interferometer, employed independently by R. Tomaschek and D. C. Miller in their experiments.

SGLT2 inhibitors act to induce glucosuria and have been shown to be efficacious in the treatment of type II diabetes mellitus but have also been shown to positively affect cardiovascular conditions and some benefitting kidney function. SGLT2i have shown to be effective in more advanced conditions but may eventually be a treatment in more general metabolic dysfunction. Metabolic syndrome is a clinical diagnosis for establishing risk for ischemic heart disease and diabetes. The prevalence of type II diabetes mellitus, heart disease, and severe vascular events steadily increased over recent decades. In addition to the established benefits of diet and exercise, SGLT2 inhibitor therapy may be able to aid in the treatment of metabolic syndrome from its proven cardiovascular and anti-hyperglycemic benefits. Pharmacologic modeling in canines is also considered, as they present with similar diagnoses and offer a model that shares many of the characteristics of humans in metabolic dysfunction.

The personalist ethics of Edith Stein and her feminist thought are intrinsically interrelated. This unique connection constitutes perhaps the main novelty of Stein’s ethical thought that makes her a forerunner of some recent developments in feminist ethics, particularly ethics of care. A few scholars noticed the resemblance between Stein’s feminist personalism and care ethics, yet none of them have properly explored it. This paper offers an in-depth discussion of the overlaps and differences between Stein’s ethical insights and the core ideas of care ethics. It argues that both Stein and care ethicists relocate a certain set of practices, values and attitudes from the periphery to the center of ethical reflection. This includes relationality, emotionality and care. The paper finally argues that it is plausible and fruitful to read Stein’s advocacy of ‘woman’s values and attitudes’ in a critical feminist way, rather than as an instance of essentialist difference feminism.

L-asparaginase (ASNase) is an aminohydrolase currently used in the pharmaceutical and food industries. Enzyme immobilization is an exciting option for both applications, allowing a more straightforward recovery and increased stability. High surface area and customizable porosity make carbon xerogels (CXs) promising materials for ASNase immobilization. This work describes the influence of contact time, pH, and ASNase concentration on the immobilization yield (IY) and relative recovered activity (RRA) using Central Composite Design methodology. The most promising results were obtained using CX with an average pore size of 4 nm (CX-4), reaching IY and RRA of 100%. At the optimal conditions, the ASNase-CXs biocomposite was characterized and evaluated in terms of kinetic properties and operational, thermal and pH stabilities. The immobilized ASNase onto CX-4 retained 71% of its original activity after six continuous reaction cycles, showed a good thermal stability at 37 °C (RRA of 91% after 90 min) and was able to adapt to both acidic and alkaline environments. Finally, the results indicated a 3.9-fold increase in the immobilized ASNase affinity for the substrate, confirming the potential of CXs as a support for ASNase and as a cost-effective tool for subsequent use in the therapeutic and food sectors.

Coronavirus Disease-19 (COVID-19) is presently wreaking havoc on public health and socio-economic development. Besides the upper and lower respiratory tract involvement, gastrointestinal symptoms are also reported in COVID-19 patients through gut-lung axis. Finding its way through the feces of infected individuals and other sources, the genetic material of SARS-CoV-2 (ssRNA) is reported widely in wastewater and is being used as a fingerprint for its detection. With millions of cases arriving every day, there is a need to level up the testing speed efficiency. Due to the restricted sampling potential of testing laboratories, clinical testing is unable to track all the symptomatic and asymptomatic cases. Wastewater-based epidemiology (WBE) bestows an auxiliary monitoring tool that will contribute in community level screening. Sample collection, concentration, RNA extraction, quantification and data analysis are the main steps involved in implementation of WBE that can be relied upon as an alarm call for an upcoming wave, emergence of a new variant or any future pandemic. WBE can be a cheaper and more practical alternative to high end and sophisticated clinical testing for community transmission detection. Worldwide, there are more than 300 reports entailing the occurrence of SARS-CoV-2 in wastewater exhibiting unique temporal trends with five of them in India. This review aims to address the present knowledge on surveillance of SARS-CoV-2 in wastewater and its implications.

Head and neck cancer is the sixth most frequent cancer type. Drug resistance and toxicity are common challenges of the existing therapies, making the development of reliable preclinical models essential for the study of the involved molecular mechanisms as well as for eventual intervention approaches that improve the clinical outcome. Preclinical models of head and neck squamous cell carcinoma have been traditionally based in cell lines and murine models. In this review, we will go over the most frequently used preclinical models, from immortalized-cell and primary tumour cultures in monolayer or 3D, to the currently available animal models. We will scrutinize their efficiency in mimicking the molecular and cellular complexity of head and neck squamous cell carcinoma. Finally, the challenges and opportunities of other envisaged putative approaches, as well as the potential of the preclinical models to further develop customized therapies will be discussed.

A new set of alkoxy alcohols were synthesised by reaction of eugenol oxirane with aliphatic and aromatic alcohols. These eugenol derivatives were evaluated against their effect upon the viability of the insect cell line Sf9 (Spodoptera frugiperda).The most promising compounds, 4-(3-(tert-butoxy)-2-hydroxypropyl)-2-methoxyphenol and 4-(2-((4-fluorobenzyl)oxy)-3-hydroxypropyl)-2-methoxyphenol were submitted to in silico assays to predict possible targets. Thought an Inverted Virtual Screening approach, 23 common pesticide targets were screened and the top 2 targets predicted were further evaluated through molecular dynamics simulations and free energy calculations. In addition, these to eugenol derivatives were subjected to encapsulation and release assays using liposome-based nanosystems of egg phosphatidylcholine/cholesterol (7:3), with encapsulation efficiencies higher than 90% and release profiles well described by both Korsmeyer-Peppas and Weibull models.

In this paper, inspired by quantum field theory, or more specifically QED, we propose a dynamical model for relativity. By adopting the approach provided by this dynamical model, we provide a dynamical explanation for relativistic phenomena such as length contraction, time dilation and clock desynchronization. The result of the dynamical approach for clock desynchronization is especially interesting. Our dynamical approach exhausts the freedom for different clock synchronizations on frames accelerated from an initial reference frame, which is allowed by Einstein’s principle approach. Furthermore, our dynamical approach arrives at the interesting conclusion that Einstein’s equivalence principle and gravitational redshift are necessary to explain special relativistic clock desynchronization. This result shows that special relativity by itself is an incomplete theory. If our dynamical model assumptions are assumed to be valid at a fundamental level, it implies some modifications to quantum field theory and general relativity via the equivalence principle. These modifications have been discussed.

There is increasing interest in automating train operations of mainline services, e.g. to increase network capacity. Automatic train operation (ATO) is already achieved by several pilot projects, but not implemented on a large scale. Before the general introduction of new or adapted technologies can have a transformative effect on the operation of such a complex system as train operation on mainlines, they have to pass functional, interoperability and performance tests. A virtual preliminary analysis is one way to ensure a smooth as well as safe introduction and implementation. This paper aims to present an approach that applies to the performance testing of ATO systems. Therefore, methods and test standards for technologies enabling automatic operation in other transport sectors are reviewed. The main findings have been adapted, transformed and combined to be used as a general strategy for virtual performance testing in the railway sector. Specifically, universal performance indicators, namely punctuality, accuracy, energy consumption, safety and comfort, are presented. A layer model for scenario description is adapted from the automotive sector, as well as the definition of different scenario types. Lastly, factors that can influence the performance of an ATO algorithm are identified. To demonstrate the developed approach, a straightforward investigation of a case study is conducted using a microscopic train simulator in combination with an ATO algorithm.

Natural cycles underpin the very stuff of life. In this commentary we consider unnatural cycles: that is, anthropogenic activities which have a circularity, but whose nature is to have a detrimental effect on human health, exacerbating existing problems. Natural cycles have feedback loops, some of which have recently come to light, with an understanding that everything is connected in some way. In health, feedback loops are imperative in homeostatic mechanisms. However, in the unnatural cycle the feedback loops serve to reinforce (and in some cases amplify) negative problems. We offer a commentary on an unnatural cycle moving from air quality to lung function and back to air quality; we call this the lung disease unnatural cycle. We suggest where links occur, and where wider consideration of interactions between various disciplines can lead to breaking this unnatural (or vicious) cycle, changing it to a healthy cycle where individual health can be improved, along with better global scale outcomes. We suggest that many activities within this unnatural cycle occur within silos. However, the improved cycle incorporates joint activities at geological, health, and financial levels, to the mutual benefit of all, breaking the unnatural cycle, and improving health, life and financial costs.

Abstract: Background: Surgery on varicose veins (crossectomy and stripping) leads to recurrence and has clinical and socio-economic repercussions. Their etiopathogenesis has yet to fully under-stood. Objective: Study the expression of endoglin and other molecules involved in the neovascu-larisation process in patients suffering from this disease. Methods: 43 patients that have undergone surgery for varicose veins (24 primary and 19 recurrent). They were identified on the venous wall (proximal -saphenofemoral junction- and distal), via real-time RT-PCR, and in serum, via ELISA: Endoglin (Eng), Vascular Endothelial Growth Factor (VEGF-A), its receptors 1 and 2 (VEGFR1 or FLT1), (VEGFR2 or FLK), and the Hypoxia-Inducible Factor (HIF-1A). All the patients signed a con-sent form. Results: The recurrent group recorded a higher expression of Eng, VEGF-A, VEGFR1 and VEGFR2 at the level of proximal venous wall compared to the primary group. HIF-1A did not record any differences. As regards the determination of the distal venous wall, no markers recorded differ-ences between the groups. Among the serum determinations, only sFLT1 recorded a significant drop among the patients with recurrent varicose veins. Conclusions: Patients with recurrent vari-cose veins record a higher expression of endoglin and other markers of angiogenesis in proximal veins. Endoglin in the blood (sEng) has not proven to be of any use in recurrent varicose veins.

Abstract: Background: Hemopexin (Hx) is a plasma glycoprotein that scavenges heme (Fe(III) protoporphyrin IX), Hx have important implication in hemolytic disorders and hemorrhagic condition because the release of hemoglobin increase labile heme, which is potentially toxic producing oxidative stress. Hx has been considered for therapeutic use and diagnostics. In this work, we analyzed and mapped interaction sequences of Hx with hemin and hemoglobin (2) Methods: Spot-synthesis technique was used to map human hemopexin (P02790) binding to hemin and human hemoglobin, a library of 15 amino acid peptides with a 10-amino acid overlap was designed to represent the entire coding region (aa 1-462) of hemopexin and synthesized onto cellulose membranes. In silico approach was performed to analyze amino acid frequency in identified interaction regions, and molecular docking was applied for protein-protein interaction (3) Results: Seven linear peptide sequences in Hx were identified to bind hemin (H1-H7), and five were described for Hb (Hb1-Hb5) interaction, with just two sequences shared between hemin and Hb. Amino acid composition of identified sequences demonstrated that Histidine residues are relevant for heme binding, H105, H293, H373, H400, H429, and H462 was distributed in H1-H7 peptide sequences, but other residues may also play an important role. Molecular docking analysis demonstrated Hx association with the β-chain of Hb, with several hot spot amino acids that coordinated interaction. (4) Conclusions: This study highlights new insights on Hx-hemin binding motifs and protein-protein interactions with Hb. Binding sequences and identified specific peptides can be used for therapeutic purposes and diagnostics, as hemopexin is under investigation to treat different diseases, and there is an urgent need for diagnostics of labile heme for monitoring hemolysis.

This paper deals with investigation of changes in geopolymer wettability with increasing mass fraction of high-carbon fly ash and surface treatment by cold atmospheric plasma (CAP). In this study, multiple samples of geopolymers were prepared, including those with 5% and 10% of high-carbon fly ash from coal-fired power station. Wettability of samples was then measured before and after plasma treatment, both on surface and cut surface. While addition of fly ash only had low effect on the wettability, as in most cases, it only lowered the initial contact angle without speeding up the speed of soaking for compact geopolymer and actually slowed the soaking for foamed geopolymer, plasma treatment had significant impact and made the geopolymer hydrophobic.

Mass plays a strange multiple role in classical physics. This results in a difference between gravity and all other forces - a difference that stood at the beginning of Einstein's development of his general theory of relativity. The equivalence principle (EP) deals with homogenious gravitational fields, which, in fact, don‘t exist in nature. There is only an approximation for this field in Einstein-Lift possible for local situations. Nevertheless this EP can be true, because in classical formal binary logic there can be formulated a true conclusion from a wrong premise or assumption.

Background: Immunologic and neuro-inflammatory pathways have been found to play a major role in the pathogenesis of many neurological disorders such as epilepsy, proposing the use of novel therapeutic strategies. In the era of personalized medicine and in the face of the exhaustion of anti-seizure therapeutic resources it is worth looking at the current or future possibilities that neuroimmunomodulator or anti-inflammatory therapy can offer us in the management of patients with epilepsy. Methods: We performed a narrative review on the recent advances on the basic epileptogenic mechanisms related to the activation of immunity or neuroinflammation with special attention to current and future opportunities for novel treatments in epilepsy. Results: Neuroinflammation can be considered a universal phenomenon and occurs in structural, infectious, post-traumatic, autoimmune, or even genetically based epilepsies. The emerging research developed in recent years has allowed us to identify the main molecular pathways in-volved in these processes. These molecular pathways could constitute future therapeutic targets for epilepsy. Conclusions: Different drugs current or in development have demonstrated their capacity to inhibit or modulate molecular pathways involved in the immunologic or neuroinflammatory mechanisms described in epilepsy. Some of them should be tested in the future as possible antiepileptic drugs.

Wheat (Triticum aestivum L.) breeding programs can take over a decade to release a new variety. However, new methods of selection such as genomic selection (GS) must be integrated to decrease the time it takes to release new varieties to meet the demand of a growing population. The implementation of GS into breeding programs is still being explored, with many studies showing its potential to change wheat breeding through achieving higher genetic gain. In this review, we explore the integration of GS for a wheat breeding program by redesigning the traditional breeding pipeline to implement GS. We propose implementing a two-part breeding strategy by differentiating between population improvement and product development. The implementation of GS in the product development pipeline can be integrated into most stages and can predict within and across breeding cycles. Additionally, we explore optimizing the population improvement strategy through GS recurrent selection schemes to reduce crossing cycle time and significantly increase genetic gain. The recurrent selection schemes can be optimized for parental selection, maintenance of genetic variation, and optimal cross-prediction. Overall, we outline the ability to increase the genetic gain of a breeding program by implementing GS and a two-part breeding strategy.

Reducing overall food intake or lowering the proportion of protein relative to other macronutrients, can extend lifespan in diverse organisms. A number of mechanistic theories have been developed to explain this phenomenon, mostly assuming that the molecules connecting diet to lifespan are evolutionarily conserved. A recent study using Drosophila melanogaster females has pinpointed a single essential micronutrient that can explain how lifespan is changed by dietary restriction. Here, we propose a likely mechanism for this observation, which involves a trade-off between lifespan and reproduction, but in a manner that is conditional on the dietary supply of an essential micronutrient – a sterol. Importantly, these observations argue against previous evolutionary theories that rely on constitutive resource reallocation or damage directly inflicted by reproduction. Instead, they are compatible with a model in which the inverse relationship between lifespan and food level is caused by the consumer suffering from varying degrees of malnutrition when maintained on lab food. The data also indicate that animals on different lab foods may suffer from different nutritional imbalances and that the mechanisms by which dietary restriction benefits the lifespan of different species may vary. This means that translating the mechanistic findings from lab animals to humans will not be simple and should be interpreted in light of the range of challenges that have shaped each organism’s lifespan in the wild and the composition of the natural diets they would feed on.

Flaviviruses cause a significant amount of mortality and morbidity, especially in the area where they are endemic. A recent example is the outbreak of Zika virus though out the world. Development of antiviral drugs against different viral targets is as important as development of vaccine. During viral replication, the flavivirus genome is translated as a single polyprotein precursor, which must be cleaved into individual proteins by a complex of the viral protease, NS3, and its cofactor, NS2B. Flavivirus protease is the most attractive target for development of therapeutic antivirals because it is essential for processing of viral polyprotein precursor and generation of functional viral proteins. In this review, we have summarized recent development in drug discovery targeting NS3-NS2B protease of flaviviruses, especially Zika, dengue and West Nile virus.

Bare titania and metal promoted TiO2 catalysts were employed in the treatment of nitrates, which are ubiquitous pollutants of wastewater. The results show that the process can be carried out under visible light (from white light LED lamp) and, in the best case, 23.5% conversion of nitrate was obtained over 4 hours with full selectivity towards N2 by employing 0.1 mol% Ag/TiO2 prepared by flame spray pyrolysis. Moreover, the performance was worse when testing the same catalysts with tap water (11.3% conversion), due to the more complex composition of the matrix. At last, it was found that the photoreduction of nitrate can be effectively performed in combina-tion with the photo-oxidation of ammonium without loss in the activity, opening to the possi-bility to treat highly polluted wastewater with a single process. The latter treatment employs the two contaminants simultaneously as electron and holes scavengers, with very good selectiv-ity, in a completely new process that we may call Photo-Selective Catalytic Reduction (Pho-to-SCR).

Systematics plays the most crucial role in biodiversity conservation which is at stake due to anthropogenic activities and environmental degradations. The ever-increasing decline of classical taxonomic expertise drives the need to develop molecular marker-based tools for quick, efficient, and reliable detection of organisms, to assess their ecological impacts for deepening our understanding of systematic and evolutionary relationships between organisms which is central to biology. The pace of alpha taxonomy has quickened by its integration with an increasingly fashionable and novel concept called DNA barcoding which utilizes a short genetic marker or barcode to categorize species for enhanced biodiversity assessment. As a supplementary but not complete alternative of systematics research, DNA barcoding, however, not error-free, brings precision in identification by solving existing problems of classical taxonomy and phylogenetics, irrespective of the growth stage of organisms, particularly for known taxa rather than unknown ones. Mitochondrial gene Cytochrome C Oxidase 1 (COI) serves as a universal animal barcode but there is no such universal barcode for plants and developing a suitable one is more challenging. With the recent advancement of Next Generation Sequencing (NGS), DNA metabarcoding technology is advancing rapidly. Still, ambiguity and error prevail with the correct identification of species due to some problems. After extensive analysis of the existing DNA barcoding papers, this review discusses commonly used DNA barcodes in plants and animals, their roles, advantages, limitations to solve existing problems of conservation biology and add the author’s views and recommendations.

To substitute of conventional manure and peat with alternatives sourcing from environmental conservation concerns, several promising alternatives has been attracting scientific parties’ interest, recently. However, among them compost perform the best, mostly and support carbon sequestration and mitigation against climate change. The article describes the made locally produced 70% in volume olive pruning branches compost (COMP) performance in two trials as an organic amendment in pepper production and an olive sapling substrate during 2019-2021 organic management in Turkey. The application of COMP to pepper trial conducted using factorial randomised block design with 4 replications and 6 treatments increased total organic matter and soil organic carbon, significantly (p<0.05) as compared to non-used plots in two locations. The olive sapling trial was conducted using a randomised plot design with 4 replications and 4 treatments. After the 12 months of growth, compost had the largest architecture rooted plants significantly different (p<0.05). Fresh volume (cm³) of COMP used saplings were obtained 35% less than 40% peat treatment, significantly (p<0.05) while 6^th month measurement was found as 40%. It is concluded that to enhance circular economy recycling and composting olive pruning branches is lucrative for the country to reduce external input usage in organic horticultural production.

Computational neuroscience combines mathematics, computer science models, and neurosciences for theorizing, investigating, and simulating neural systems involved in the development, structure, physiology, and cognitive abilities of the brain. Computational models constitute a major stake in translational neuroscience: the analytical understanding of these models seems fundamental to consider a translation towards clinical applications. Method: We propose a minimal typology of computational models, which allows distinguishing between more realistic models (e.g., mechanistic models) and pragmatic models (e.g., phenomenological models). Result: Understanding the translational aspects of computational models goes far beyond the intrinsic characteristics of models. First, we assume that a computational model is rarely uniquely mechanistic or phenomenological. Idealization seems necessary because of i) the researcher’s perspectives on the phenomena and the purposes of the study (i.e., by the relativity of the model); ii) The complexity of reality across different levels and therefore the nature and number of dimensions required to consider a phenomenon. Especially, the use of models goes far beyond their function, and requires considering external characteristics rooted in path dependence, interdisciplinarity, and pluralism in neurosciences. Conclusion: The unreasonable use of computational models, which are highly complex and subject to a shift in their initial function, could be limited by bringing to light such factors.

Hantaviruses are enveloped viruses that possess a tri-segmented, negative-sense RNA genome. The viral S-segment encodes the multifunctional nucleocapsid protein (N), which is involved in genome packaging, intracellular protein transport, immunoregulation and several other crucial processes during hantavirus infection. In this study we have generated fluorescently tagged N protein constructs derived from Puumalavirus, the dominant hantavirus species in Central, Northern and Eastern Europe. We have comprehensively characterized this protein in the rodent cell line CHO-K1, monitoring the dynamics of N protein complex formation and investigating co-localization with host proteins as well as the viral glycoproteins Gc and Gn. We found a significant spatial correlation of N with vimentin, actin and P-bodies, but not with microtubules. N constructs also co-localized with Gn and Gc, albeit not as strong as the glycoproteins associated with each other. Moreover, we as-sessed oligomerization of N constructs, observing efficient and concentration-dependent multi-merization, with complexes comprising more than 10 individual proteins.

Snap fit is a common mechanical mechanism. It uses the physical asymmetry that is easy to assemble but difficult to disassemble to provide a simple and fast link between objects. The ingenious combination of geometric shape, bending elasticity and friction of the snap fit is the mechanism behind the easy to assemble but difficult to disassemble disassemble. Yoshida and Wada (2020) has done a groundbreaking work in the analysis of the elastic snap fit. During our study of their paper, while we really enjoyed their research, unfortunately we detected several questioning formulations. After careful checking, we found that those formulations are not typographical, therefore it is necessary to make corrections. This paper reformulates the linear elasticity of a cylindrical snap fit, obtains an exact solution and proposes an accurate relation between the opening angle and bending tangent angle. Under the first order approximation, our formulations can reduced to the results of Yoshida and Wada and hence confirms the scientific correctness of Yoshida and Wada's work. Furthermore, this paper also derives a correct vertical displacement expression, and propose a new way of disassembly by bending for the first time and formulate a scaling law by data fitting. All formulations are validated by finite element simulation and experiment. The research here is helpful to the design of elastic snap fit or adjustable mechanical mechanism and metamaterial cell.

Gestational diabetes (GDM) is considered a significant and increasing problem worldwide. The growing body of evidence points out that a hostile intrauterine environment in mothers with GDM via epigenetic mechanisms induces "diabetogenic" and "obesogenic" changes in an offspring's DNA. This sets in motion a vicious intergenerational cycle of metabolic diseases gradually deteriorating the health of the human population. One of the most important players in this process seems to be altered microbiota/microbiome. There is a chance that the identification of specific epigenetic marks may provide a key for future diagnostic, prognostic and therapeutic solutions/measures in the field of person-alized medicine. Given the reversibility of most epigenetic changes, an opportunity arises to improve the long-term health of the human population/race. In this manuscript, we aim to summarize available data on epigenetic changes among women suffering from GDM and their progeny in association with changes in microbiome.

New setting is introduced to study types of coloring numbers, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges in neutrosophic hypergraphs. Different types of procedures including neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs are proposed in this way, some results are obtained. General classes of neutrosophic hypergraphs are used to obtain chromatic number, the representatives of the colors, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges in neutrosophic hypergraphs. Using colors to assign to the vertices of neutrosophic hypergraphs and characterizing representatives of the colors are applied in neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs. Some questions and problems are posed concerning ways to do further studies on this topic. Using different ways of study on neutrosophic hypergraphs to get new results about number, degree and co-degree in the way that some number, degree and co-degree get understandable perspective. Neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs are studied to investigate about the notions, coloring, the representatives of the colors, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges in neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs. In this way, sets of representatives of colors, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges have key points to get new results but in some cases, there are usages of sets and numbers instead of optimal ones. Simultaneously, notions chromatic number, the representatives of the colors, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges are applied into neutrosophic hypergraphs, especially, neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs to get sensible results about their structures. Basic familiarities with neutrosophic hypergraphs theory and hypergraph theory are proposed for this article.

Published data or available literature on sustainable building plan-design, construction, performance, and renovation criteria have covered some stages or some parts of each stage. These data usually have been published partially in many different papers―there have not been any papers that published these data together. Hence, this paper aims to collectively review these data and publish them together. The collection and review of these data were carried out by our twenty-five team members who specialized in sustainable urban, architectural, and civil engineering and construction management. The gathered and reviewed outputs were combined and validated based on a general group consensus. This consensus decision-making proceeded through two major group meetings with several follow-up meetings. The first major meeting was to combine and improve the gathered reviewed sustainable building criteria for Cambodia. The second major meeting was to validate the improved reviewed sustainable building criteria for Cambodia. The several follow-up meetings were to discuss the relevance and importance of the validated data “criteria and their classifications and descriptions” in all stages and more focused on their importance and applicability to Cambodia. The collective reviewed data in this paper would be useful to researchers in the fields. They could also be useful collective knowledge and information for policymakers from governmental agencies and development partners, particularly for sustainable building and construction companies.

Integer is either a composite number or a prime number. Therefore, detecting composite numbers is important for solving prime numbers. The study of prime numbers, apart from satisfying human curiosity, can be very important. In this article, the order of composite numbers has been detected. And explained with a simple method and a simple function. And, a method has been developed in which all composite numbers and therefore prime numbers can be determined by using the specified methods, functions and formulas.

In view of the problem of cracking easily and partial distortion of images after encryption or decryption, a novel image encryption and decryption algorithm based on Arnod Transform and fractional chaotic is proposed. To begin with, the Arnold transform is used to encrypt. So that the spatial confidence of the original image has been comprehensively disturbed. Secondly, the XOR involving the fractional order chaotic sequence is used to encrypt. The key sequence is dynamically generated to ensure the randomness and difference of key generation. When decryption is required, the first decryption is performed using the key and XOR. Then the second decryption is carried out by using the inverse Arnold transform, and finally the decrypted image is obtained. Experimental results show that the improved algorithm has achieved better performance in encryption and decryption.

The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function computation problem include 1) privacy leakage to an eavesdropper is measured with respect to the remote source rather than the transmitting terminals’ observed sequences; 2) the information leakage to a fusion center with respect to the remote source is considered as a new privacy leakage metric; 3) the function computed is allowed to be a distorted version of the target function, which allows to reduce the storage rate as compared to a reliable function computation scenario in addition to reducing secrecy and privacy leakages; 4) two transmitting node observations are used to compute a function. Inner and outer bounds on the rate regions are derived for lossless and lossy single-function computation with two transmitting nodes, which recover previous results in the literature. For special cases that include invertible and partially-invertible functions, and degraded measurement channels, exact lossless and lossy rate regions are characterized, and one exact region is evaluated for an example scenario.

Positive education is seen as a transformative methodological approach capable of improving the act of teaching and learning and, above all, essential for the development of students' personal skills and competences. However, few studies have been carried out on this subject in the field of lifelong and adult education. This study works with a sample of 399 people over 16 years of age and students of the Universidad Popular de Dos Hermanas in order to show the relationship between the Pygmalion effect and learned helplessness in the process of acquiring knowledge in adulthood. In this way, three tools were used: a questionnaire that showed teachers' perceptions of students' qualities and behaviour and two that provided information on self-concept, self-esteem, personal and social skills and other variables directly related to emotional intelligence and positive education. It shows how exposure to negative operational conditioning factors influences the psychosocial and socio-educational development of students in every possible way, while on the other hand, it indicates the importance of positive education to compensate for this phenomenology by improving the development and growth of those who study and participate in non-formal education. Likewise, the factorial interrelation of both positive and negative conditioning factors and their incidence on learning is shown; the importance of neutralising the negative components and strengthening the positive reinforcement and the role played by the community and education professionals as catalysts and behavioural modulators at any stage of learning and age group for the achievement of the objectives of the student and of education itself in a broad sense

The novel Ionized Gas Thermoelectric Generator (IG-TEG) system that has been studied theoretically showing capabilities to continually extracting energy from the thermal energy of the ambient air, at low temperatures within the standard room temperature and below. This system does not need a temperature gradient in order to work, unlike the other TEGs that use Seebeck effect, and therefore this new system can be utilized for cooling purposes, by extracting energy instead of wasting energy in compressing the gas for cooling. This novel system was designed based on Static Ratchet Potential (SRP), which is known as a spatially asymmetric electric potential produced by an array of positive and negative electrodes. The ratchet potential produces electrical current from random Brownian Motion of charged particles that are driven by thermal energy. Ratchet potential was studied and investigated by several researches in the fields of sensing and energy harvesting. The main ratchet potential system parameter is the particles transportation, this parameter was studied under the condition of flashing ratchet potentials, and was analyzed based on several methods. In this study, a different approach is pursued to estimate particles transportation, by evaluating the charged particles distribution, and applying the other conditions of the SRP.

A convolutional neural network (CNN) is sometimes understood as a black box in the sense that while it can approximate any function, studying its structure will not give us any insights into the nature of the function being approximated. In other terms, the discriminative ability does not reveal much about the latent representation of a network. This research aims to establish a framework for interpreting the CNNs by profiling them in terms of interpretable visual concepts and verifying them by means of Integrated Gradient. We also ask the question, "Do different input classes have a relationship or are they unrelated?" For instance, could there be an overlapping set of highly active neurons to identify different classes? Could there be a set of neurons that are useful for one input class whereas misleading for a different one? Intuition answers these questions positively, implying the existence of a structured set of neurons inclined to a particular class. Knowing this structure has significant values; it provides a principled way for identifying redundancies across the classes. Here the interpretability profiling has been done by evaluating the correspondence between individual hidden neurons and a set of human-understandable visual semantic concepts. We also propose an integrated gradient-based class-specific relevance mapping approach that takes the spatial position of the region of interest in the input image. Our relevance score verifies the interpretability scores in terms of neurons tuned to a particular concept/class. Further, we perform network ablation and measure the performance of the network based on our approach.

By using geodesic equations to obtain a gravitational potential generated from a point-like source, we end up in the concept of a nearly Newtonian gravity to analyse effective potentials of quasi-circular orbits. By means of an approximate solution from an axially static and symmetric Weyl metric, we study an effective gravitational potential to obtain its related rotation curves, orbital planes and orbits. Moreover, using as initial condition a Plummer sphere, some prospects on star cluster disruption are also discussed in this framework.