On 14 March 2020 the state of epidemic threat was introduced in Poland applicable until 20 March 2020 when the state of epidemic was introduced in the territory of the Republic of Poland. The situation associated with the growing number of SARS-CoV-2 infections forced ongoing monitoring of the epidemic situation, which entailed an introduction of a number of restrictions and solutions intended to isolate the infected persons on the one hand, and to minimize the risk of development of an epidemic in Poland on the other. Activity of the Polish legislator is also essential, which tried to introduce solutions that would correspond with current expectations and needs. In this paper, the author points to the issues of communication with a public authority by specific reflections on the principles of serving documents on beneficiaries of EU programs under which they were awarded funding for their implementation. The author points to the dynamics of the legislator’s work in this respect by analyzing the rules for serving documents by a public authority on beneficiaries who are public entities and those who are not.

Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder. One of the important therapeutic approaches of AD is the inhibition of β‐site APP cleaving enzyme‐1 (BACE1). This enzyme plays a central role in the synthesis of the pathogenic β-amyloid peptides (Aβ) in Alzheimer's disease. A group of potent BACE1 inhibitors with known x-ray structures (PDB ID 5i3X, 5i3Y, 5iE1, 5i3V, 5i3W, 4LC7, 3TPP) were studied by molecular dynamics simulation and binding energy calculation employing MM_GB(PB)SA. The calculated binding energies gave Kd values 0.139 µM, 1.39 nM, 4.39 mM, 24.3 nM, 1.39 mM, 29.13 mM and 193.07 nM, respectively. These inhibitors showed potent inhibitory activities in enzymatic and cell assays. The Kd values were compared with experimental values, the structures were discussed in view of the energy contributions to binding. Drug likeness of these inhibitors is also discussed. Accommodation of ligands in the catalytic site of BACE1 is discussed depending on the type of fragment involved in each structure. Molecular dynamics (MD) simulations and energy studies were used to explore the recognition of the selected BACE1 inhibitors by Asp 32, Asp228 and the hydrophobic flap. The results show that selective BACE1 inhibition may be due to the formation of strong electrostatic interactions with Asp32 and Asp228 and a large number of hydrogen bonds, π-π and Van der Waals interactions with the amino acid residues located inside the catalytic cavity. Interactions with the ligands show a similar binding mode with BACE1. These results help to rationalize the design of selective BACE1 inhibitors.

In this report the positive cases of Covid19 in India with effect from 7th September ,2020 to 25th October ,2020 are analysed for statistical relevance . The scattered data are used to find out a model equation correlating two variables number of recovered Covid –patient with an interval of regular seven days . The best fit regression analysis shows a significant correlation of Pearson coefficient (r) with standard error ( s ) with a probable lower mortality rate . Finally the limitations of this analysis is discussed herewith .

Abstract: This article provides a brief review of the ontogeny of chondrocytes and the pathophysiology of osteoarthritis (OA), and details how physical exercise improves the health of osteoarthritic joints and enhances the potential of mesenchymal stem cells for successful transplantation therapy. In response to exercise chondrocytes increase their production of glycosaminoglycans, bone morphogenic proteins and antiinflammatory cytokines and decrease their production of proinflammatory cytokines and matrix degrading metalloproteinases. These changes are associated with improvements in cartilage organization and reductions in cartilage degeneration. Studies in humans indicate that exercise increases peripheral blood recruitment of bone marrow-derived mesenchymal stem cells (BM-MSC) and upregulates BM-MSC expression of osteogenic and chondrogenic genes, osteogenic micro-RNAs, and osteogenic growth factors. Rodent experiments are uniform in demonstrating that exercise enhances the osteogenic potential of BM-MSC while diminishing their adipogenic potential, and that exercise done after stem cell implantation may benefit stem cell transplant viability. Physical exercise also exerts a beneficial effect on the skeletal system by decreasing immune cell production of osteoclastogenic cytokines interleukin (IL)-1β, tumor necrosis factor (TNF)-α, and interferon (INF)-γ while increasing their production anti-osteoclastogenic cytokines IL-10 and transforming growth factor (TGF)-β. In conclusion, physical exercise done both by stem cell donors and recipients may improve the outcome of mesenchymal stem cell transplantation.

C-type lectin CD209/DC-SIGN and CD209L/L-SIGN proteins are distinct cell adhesion and pathogen recognition receptors that mediate cellular interactions and recognize a wide range of pathogens including, viruses such as SARS, SARS-CoV-2, bacteria, fungi and parasites. Pathogens exploit CD209L family proteins to promote infection and evade the immune recognition system. CD209L and CD209 are widely expressed in SARS-CoV-2 target organs and can contribute to infection and pathogenesis. CD209L family receptors are highly susceptible to alternative splicing and genomic polymorphism, which may influence virus tropism and transmission in vivo. The carbohydrate-recognition domain (CRD) and the neck/repeat region represent the key features of CD209L family proteins that are also central to facilitating cellular ligand interactions and pathogen recognition. While, the neck/repeat region is involved in oligomeric dimerization, the CRD recognizes the mannose containing structures present on specific glycoproteins such as those found on the SARS-CoV-2 spike protein. Considering the role of CD209L and related proteins in diverse pathogen recognition, this review article discusses the recent advances in the cellular and biochemical characterization of CD209 and CD209L and their roles in viral uptake, which has important implications in understanding the host-pathogen interaction, the viral pathobiology and driving vaccine development of SARS-CoV-2.

Dyadic data contains co-occurrences of objects, which is often modeled by finite mixture model which in turn is learned by expectation maximization (EM) algorithm. Objects in traditional dyadic data are identified by names, causing the drawback which is that it is impossible to extract implicit valuable knowledge under objects. In this research, I propose the so-called attributed dyadic data (ADD) in which each object has an informative attribute and each co-occurrence of two objects is associated with a value. ADD is flexible and covers most of structures / forms of dyadic data. Conditional mixture model (CMM), which is a variant of finite mixture model, is applied into learning ADD. Moreover, a significant feature of CMM is that any co-occurrence of two objects is based on some conditional variable. As a result, CMM can predict or estimate co-occurrent values based on regression model, which extends applications of ADD and CMM.

This work is a top-level summary of several contributions published in the last three decades. It makes the case that complex dynamics of nonlinear systems lies at the heart of foundational physics.

In this article, author performs computational analysis for the generalized zeta functions by using computational software Mathematica. To achieve the purpose recently obtained difference equations are used. These difference equations have a computational power to compute these functions accurately while they can not be computed by using their known integral represenations. Several authors investigated such functions and their analytic properties, but no work has been reported to study the graphical representations and zeors of these functions. Author performs numerical computations to evaluate these functions for different values of the involved parameters. Taylor series expansions are also presented in this research.

The article contains the results of experimental studies for a multi-opening orifice with substitute constriction factor of β = 0.5 (m = 0.25), mounted in a DN50 hydraulic measuring flume. Flow measurements were taken for a progressing turbulent flow within Reynolds numbers (Re = 4700...19500). Based on experimental data, flow characteristics as well as discharge coefficient C characteristics were determined. Relative expanded uncertainty of determining a discharge coefficient C was estimated within the changes of volume flow qv from 0.35 dm3/s to 0.68 dm3/s. The value does not exceed 1.25% within the changes of Reynolds numbers 9800 ≤ Re ≤ 19500.

By introducing a suitable renormalization process the charge carrier and phonon dynamics of a double-stranded helical DNA molecule is expressed in terms of an effective Hamitonian describing a linear chain, where the renormalized transfer integrals explicitly depend on the relative orientations of the Watson-Crick base pairs, and the renormalized on-site energies are related to the electronic parameters of consecutive base pairs along the helix axis, as well as to the low-frequency phonons dispersion relation. The existence of synchronized collective oscillations enhancing the π-π orbital overlapping among different base pairs is disclosed from the study of the obtained analytical dynamical equations. The role of these phonon-correlated, long-range oscillation effects on the charge transfer properties of double standed DNA homopolymers is discussed in terms of the resulting band structure.

Interactome depicts the arrangement of all atomic communications in cells, particularly with regards to protein-protein collaborations. We look at different strategies for foreseeing protein-protein collaborations utilizing grouping and structure data. A definitive objective of those methodologies is to introduce the total approach for the programmed choice of communication accomplices utilizing their amino corrosive arrangements as well as three dimensional structures, whenever known. The proposed approval of the hypothetical strategies utilizing test information would be a superior appraisal of their exactness.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the Coronavirus Disease 2019 (COVID-19) worldwide pandemic in 2020. In response, most countries in the world implemented lockdowns, restricting their population’s movements, work, education, gatherings, and general activities in attempt to ‘flatten the curve’ of COVID-19 cases. The public health goal of lockdowns was to save the population from COVID-19 cases and deaths, and to prevent overwhelming health care systems with COVID-19 patients. In this narrative review I explain why I changed my mind about supporting lockdowns. First, I explain how the initial modeling predictions induced fear and crowd-effects [i.e., groupthink]. Second, I summarize important information that has emerged relevant to the modeling, including about infection fatality rate, high-risk groups, herd immunity thresholds, and exit strategies. Third, I describe how reality started sinking in, with information on significant collateral damage due to the response to the pandemic, and information placing the number of deaths in context and perspective. Fourth, I present a cost-benefit analysis of the response to COVID-19 that finds lockdowns are far more harmful to public health than COVID-19 can be. Controversies and objections about the main points made are considered and addressed. I close with some suggestions for moving forward.

Arterial wall remodeling underlies increased pulmonary vascular resistance and right heart failure in pulmonary arterial hypertension (PAH). None of the established vasodilator drug therapies for PAH prevents or reverses established arterial wall thickening, stiffening and hypercontractility. Therefore, new approaches are needed to achieve long-acting prevention and reversal of occlusive pulmonary vascular remodeling. Several promising new drug classes are emerging from better understanding of pulmonary vascular gene expression programs. In this review potential epigenetic targets for small molecules and oligonucleotides will be described. Most are in preclinical studies aimed at modifying growth of vascular wall cells in vitro or normalizing vascular remodeling in PAH animal models. Initial success with lung-directed delivery of oligonucleotides targeting microRNAs suggests other epigenetic mechanisms might also be suitable drug targets. Those targets include DNA methylation, proteins of the chromatin remodeling machinery and long noncoding RNAs, all of which act as epigenetic regulators of vascular wall structure and function. Progress in testing small molecules and oligonucleotide-based drugs in PAH models is summarized.

This paper presents Mathematical Formulation for Neutrino-Fission of a heavy nuclei in Neutrino-environments. It has been proposed that neutrino fission is a dynamic two-process reaction, where more than one neutrino can be captured by target nucleus. A quantity named Neutrino-Zeta with units of eV^-1 has been defined to represent Neutrino-environments. Neutrino-zeta with assumed excited energy states for heavy nuclei A∼230-270 is estimated to be 0.0212 MeV^-1, with the probability of fission Barrier energy state P(E_x,f)= 0.169064014 with E_x,f =6MeV. P(E_x,f)=0.222664 is highest at zeta=0.1MeV^-1 . It has been shown that probabilities of certain excitation energy states and their corresponding decay reactions at those excitation energies can be equal for two neutrino-zetas. Neutron induced fission for different neutrinos hypothesize that probability of symmetric fission channels is higher at low neutrino-zetas, which can be tested experimentally.

Objective: To explore the inter-rater reliability of the Measurement Of adherence Via Exercise Demonstration (MOVED) adherence tool. Design: Reliability study of a patient adherence measurement tool.Setting: Simulated physiotherapist-patient consultations. Participants: Sixteen experienced physiotherapists rated patient adherence to exercise. Interventions: N/A Main Outcome Measure: Inter-rater reliability of MOVED.Methods: The MOVED tool consists of two parts. Part one asks patients to self-report their adherence to exercise dose (including number of completed sessions, sets and repetitions in the last seven days). Part two asks patients to demonstrate each exercise. Component scores are totalled to give an overall level of patient adherence to each exercise.Participants were provided with a copy of five physiotherapist-prescribed exercises. Participants were then shown five corresponding video vignettes of simulated physiotherapist-patient consultations where patients were asked to self-report exercise frequency, sets and repetitions and demonstrate each exercise within the context of a consultation. Participants were asked to rate the level of patient adherence to each of the five exercises using the MOVED tool. Inter-rater reliability of MOVED scores was assessed using Intraclass Correlation Coefficient (ICC) and 95% Confidence Intervals. Results: The ICC of part one (self-report) was .90 (95%CI .74-.98), part two (demonstration) was .98 (95%CI .94-.99) and total score was .96 (95%CI .88-.99), demonstrating excellent inter-rater reliability. Conclusion: The MOVED tool, which can highlight whether patients are adhering to exercise technique as well as exercise dose, may provide clinicians and researchers with a more robust measure of exercise adherence when compared with other measures currently available.

The dramatic outbreak of the coronavirus disease 2019 (COVID-19) pandemics and its ongoing progression boosted the scientific community's interest in epidemic modelling and forecasting. The SIR (Susceptible-Infected-Removed) model is a simple mathematical model of epidemic outbreaks, yet for decades it evaded the efforts of the community to derive explicit solution. The present work demonstrates that this is a non-trivial task. Notably, it is proven that the explicit solution of the model requires the introduction of a new transcendental special function, related to the Wright's Omega function. The present manuscript reports new analytical results and numerical routines suitable for parametric estimation of the SIR model. The manuscript introduces iterative algorithms approximating the incidence variable, which allows for estimation of the model parameters from the numbers of observed cases. The numerical approach is exemplified with data from the European Centre for Disease Prevention and Control (ECDC) for several European countries in the period Jan 2020 -- Jun 2020.

In the last decade, unprecedented progress in the development of neural networks influenced dozens of different industries, among which are signal processing for the electroencephalography process (EEG). Electroencephalography, even though it appeared in the first half of the 20th century, to this day didn’t change the physical principles of operation. But the signal processing technique due to the use of neural networks progressed significantly in this area. Evidence for this can serve that for the past 5 years more than 1000 publications on the topic of using machine learning have been published in popular libraries. Many different models of neural networks complicate the process of understanding the real situation in this area. In this manuscript, we provided the most comprehensive overview of research where were used neural networks for EEG signal processing.

Ferric uptake regulation protein is a repressor protein which binds an AT rich region of DNA (the iron box). Fur binds as a dimer in a helix turn helix mode and it is activated by iron(II) and other divalent transition metal ions at elevated concentrations in a process to regulate the ion uptake. Each transition metal ion induces certain conformational changes to aid the Fur binding, both the N-terminal and C-terminal domains take part in binding to DNA in addition to His 88 and His 86 residues. The process is discussed in view of experimental reports. Fe(II), Mn(II) and Co(II) activate Fur to bind DNA experimentally but Zinc plays a structural role and does not activate Fur to bind DNA.

Under the big unified framework of quantum gravitational field and quantum repulsive field, the earlier in this series of work has comprehensively expanded the general relativity and loop quantum ring gravitation theory, set up the quantum repulsive field equation corresponding to the quantum gravitational field equation, and then established the quantum hedge-unified field equation describing the interaction of quantum gravitational field and quantum repulsive field; On this basis, the quantum repulsive universe equation corresponding to the quantum gravitational universe equation has be established, thus a set of new equations describing the expansive universe model under the condition of fully considering the hedge effect of quantum gravitational field and quantum repulsion field, which can be called the expansive universe equation of quantum hedge-unified field theory, has be established. Now, let's go deep into the arche-unified physics behind the creation of the universe. Although all kinds of inflationary universe models can solve cosmological problems to a certain extent, there is no natural and reasonable analysis and explanation for all cosmological and physical consequences. For example, it is impossible to predict a large tensor-scale ratio and a relatively large spectral index run at the same time. At present, string theory, membrane theory, loop quantum gravity theory, super-gravitational holography principle and M theory, which are the theoretical basis of cosmology, are basically established by simplification in the case of breaking away from the extreme background conditions of the universe. While cosmology, which is deficient in nature, cannot provide strong support for particle physics to further advance to a wider field and a deeper level. Due to the lack of new ideas, the construction of existing theoretical models is difficult. Therefore, the existing research can only be further promoted by new astronomical observation. Unlike existing studies, we concentrate on the emergence of the big rip-rebound clusters of quantum chaotic-reticulate distribution between the outwards-push of the universe as a whole (related to pseudo-vacuum energy, Higgs field, dark energy, etc.) and the inwards-pull of the universe in local scale (related to dark matter, quantum gravity and initial gravity separated from high-dimensional supergravity, and the initial strong force separated from the grand unified force subsequently). On the one hand, we find a great impetus to make the inflation of the universe into firstly-imposed suppression, then-imposed acceleration and finally-imposed deceleration, which really explains why the universe expands at a critical rate and has the same temperature in different regions, on the other hand, we find a fundamental unit of matter and its emerging clusters evolving in the big bang, inflation and expansion of the universe accompanied by the great rip-rebound clusters of quantum chaos-reticulate distribution, which can be reduced to an arche-pulsator of neither punctiform particle nor linear string. From these two aspects, it can been seen that the evolution of the early universe is much more complicated than people originally thought. The complexity of the super inflation of the universe is mainly reflected in the big rip-rebound cluster emerging behind the gravitational disturbance (the pressure and tensor disturbance related to dark matter), the repulsive disturbance (the pressure and scalar disturbance related to dark energy), the cosmological disturbance (related to the interaction between high-dimensional supergravity and high-dimensional superrepulsion). This is a system of nonlinear stochastic differential dynamics, or a quantum statistical physical process of nonlinear nonequilibrium state. In the new research paradigms established in this series, the arche-conjugation between the high-dimensional supergravity and the high-dimensional superrepulsion, as well as between the quantum gravity and the quantum repulsion, is higher than the supersymmetry, and then becomes the core concept of the new theory. In this series, cluster-inflating configuration, spin network space and cosmic paradigm vectors are proposed, so the model of the super-inflated universe with quantum chaos-reticulate distribution emerged under the great impetus. The new model reveals that the unified inflation of the universe as a whole and the local inflation of the universe emerge together in the great impetus of the big rip-rebound cluster of quantum chaos-reticulate distribution. As a spin network model variable, the spatiotemporal mode variable is a vector composed of a series of variables, which variables include: dimension, curvature, range, expansion speed, dynamics, quantization, chaotic-reticulate distribution (inhomogeneity, concentration, fluctuation), synergy, and so on. Between particle physics and cosmology, this series of papers proposes the cosmic quantum evolution mode, the physical-sphere distributing configuration and the interaction situation variables, organizes the concepts, variables and models of these three levels, and establishes a systematic super-synergy paradigm. In this paradigm, the general Langevan equation and the general Fokker-Planck equation are established. For the quantum cosmic-sphere, a series of trend parameters are introduced to establish the dynamics of quantum gravitational mode and its master equation, and then to establish the operator distribution function and its motion equation of the action mode. For the Tachyon of upheaval in the rip-rebound-inflating of the universe, the hypothesis on the bifurcate-chaos wave of quantum is given, the quantum theory of the early photons in upheaval is set up, and the analysis on the particles of the ultrahigh energy cosmic ray from the γ ray burst is made. Finally, using Wigner-Ville distribution as a nonlinear time-frequency distribution, we establish the ultra-synergistic field equation of quantum-classic unifying action-sphere.

We report a very frugal microscope building method from easily realizable parts. We show a highly portable field ready compound type microscope with bright field, dark field and projection microscopy capabilities. It has good resolution and magnification for multiple aspects of education and diagnosis. We demonstrate that such a system can be built from simple lenses in laser pointers and camera modules with no specific 3d printed parts or costly lenses. We show all the parts of the system like stage, coarse and fine focussing system, microscope body, even slides can be built from commonly available materials like soda bottle and DVD disks. We list alternate, safer and easily available staining methods and chemicals. The microscope is developed with a target that it can be self-developed even in rural areas of the world with only resources at one’s disposal with very little education. This features a stable focussing and panning system for comfortable viewing through eyes and also easy imaging with a smartphone. We show its utility for microorganism analysis and potential for clinical diagnosis.

We provide a detailed analysis of the electronic properties of graphene-like materials with charge carriers living on a curved substrate, focusing in particular on constant negative-curvature spacetime. An explicit parametrization is also worked out in the remarkable case of Beltrami geometry, with an analytic solution for the pseudoparticles modes living on the curved bidimensional surface. We will then exploit the correspondent massless Dirac description, to determine how it affects the sample local density of states.

Dyadic data which is also called co-occurrence data (COD) contains co-occurrences of objects. Searching for statistical models to represent dyadic data is necessary. Fortunately, finite mixture model is a solid statistical model to learn and make inference on dyadic data because mixture model is built smoothly and reliably by expectation maximization (EM) algorithm which is suitable to inherent spareness of dyadic data. This research summarizes mixture models for dyadic data. When each co-occurrence in dyadic data is associated with a value, there are many unaccomplished values because a lot of co-occurrences are inexistent. In this research, these unaccomplished values are estimated as mean (expectation) of random variable given partial probabilistic distributions inside dyadic mixture model.

Segmentation of Magnetic Resonance Images (MRI) of abdominal organs is useful for analysis prior to surgical procedures and for further processing. Deep Learning (DL) has become the standard, researchers have proposed improvements that include multiple views, ensembles and voting. Loss function alternatives, while being crucial to guide automated learning, have not been compared in detail. In this work we analyze limitations of popular metrics and their use as loss, study alternative loss variations based on those and other modifications and search for the best approach. An experimental setup was necessary to assess the alternatives. Results for the top scoring network and top scoring loss show improvements between 2 and 11 percentage points (pp) in Jaccard Index (JI), depending on organ and patient (sequence), for a total of 22 pp over 4 organs, all this being obtained just by choosing the best performing loss function instead of cross-entropy or dice. Our results apply directly to MRI of abdominal organs, with important practical implications for other architectures, as they can be applied easily to any of them. They also show the worth of variants of loss function and loss tuning, with future work needed to generalize and test in other contexts.

To solve a series of major problems, such as the singularity before the Big Bang, the inflation of the early universe and the accelerating expansion of the present universe, this series of studies start with super gravity, dark energy and dark matter, go beyond the surface of a lot of observation data, and systematically reveal the arche-internal mechanism of all things, to establish the arche-unity of physics, and give a natural and reasonable explanation. At present, there are at least three basic pathways that are leading our research field to repulsion against gravitation, quantum repulsion against quantum gravitation and high-dimensional superrepulsion against high-dimensional supergravity, that is, the research on the accelerating expansion mechanism of the current universe, the research on the dynamic mechanism of the early cosmic inflation, and the research on the rebound mechanism near the singularity before the Big Bang. In this series of studies, the arche problem of everything is always placed under the extreme environmental conditions of the initial universe, the starting point of scientific logic is closely combined with the starting point of the universe history, the pseudo vacuum energy considered by the inflationary universe model, the Higgs field predicted by the standard physical model and the dark energy speculated by the observational cosmology are reduced to the positive energy system with strong negative pressure, and they are reduced to the repulsion (all the resistance to gravity) that forms a conjugate relation with gravity. In our opinion, dark energy and dark matter are essentially at the level of quantum gravity and quantum repulsion. Therefore, we not only consider the conventional quantum effect and non commutative quantum effect, but also further consider the arche-conjugate effect and the cluster resonance-at-cofrenquence effect. For noncommutative space-time, we put forth the ultimate supersymmetry, the arche-conjugation and the cluster resonance-at-cofrenquence. A relatively complete natural mechanism forms such an important inference: the closer they get to Planck scale, the stronger the conventional quantum effect, non commutative quantum effect, arche-conjugate effect and co-frequency resonance effect are. In the high-dimensional space-time (the 11 dimensional hyperspace compactly reduced to M 4 × N r ), corresponding to the introduction of supergravity with the supersymmetry between the graviton and the gravitino, we put forth the superrepulsion with the supersymmetry between the repulsion and the repulsitino, and establish the arche-conjugate relationship between the high-dimensional supergravity and the high-dimensional superrepulsion. Therefrom, we propose a basic inference that can be promoted to the principle of hyperholography of high-dimensional universe (or multiuniverse): in a parallel universe formed by mutual coupling and holographic correspondence between the P universe dominated by negative pressure (high-dimensional superrepulsion and quantum repulsion of accumulating positive energy, mainly composed of dark energy) and the N universe dominated by positive pressure (high-dimensional supergravity and quantum gravity of accumulating negative energy, mainly composed of dark matter), there is a correspondence between the small-scale physics (ultraviolet cutoff) of the P universe and the large-scale physics (infrared cutoff) of the N universe, while there is a correspondence between the large-scale physics (ultraviolet cutoff) of the P universe and the small-scale physics (infrared cutoff) of the N universe. In the new research paradigms set in this series, the arche-conjugation between the high-dimensional supergravity and the high-dimensional super repulsion, as well as between the quantum gravity and the quantum repulsion, is higher than the supersymmetry, so it becomes the core concept of the new theory. The arhce-unity of physics is a super unity that transcends the grand unification of four basic interaction, which is formed between high-dimensional supergravity (related to dark matter) and high-dimensional superrepulsion (related to dark energy), between quantum gravity (related to dark matter) and quantum repulsion (related to dark energy). From the basic component point of view, before or after the big bang, the gravitons and repulsons are coupled together, the negative energy contraction dominated by the positive pressure and the positive energy expansion dominated by the negative pressure work alternately, forming the arche-conjugate pulsaton of neither the point particle nor the linear superstring. Under the big unified framework of quantum gravitational field and quantum repulsive field, this series of work comprehensively expands the general relativity and loop quantum ring gravitation theory, sets up the quantum repulsive field equation corresponding to the quantum gravitational field equation, and then establishes the quantum hedge-unified field equation describing the interaction of quantum gravitational field and quantum repulsive field; On this basis, the quantum repulsive universe equation corresponding to the quantum gravitational universe equation is established, thus a set of new equations describing the expansive universe with quantum hedge-unified field are established. On the one hand, scalar disturbance is considered as the exhibition of repulsive effect, on the other hand, tensor disturbance is considered as the exhibition of gravitational effect. In the initial stage of the big ripping, due to the mutual restraint of quantum repulsion and quantum gravity, the scalar and tensor perturbations are not obvious. However, at the end of the big ripping, the scalar and tensor perturbations are very significant, and there is a large power spectral exponential run. Between particle physics and cosmology, we improve and expand the path integral of quantum gravity, create the path integral of quantum hedge-unified field, and set up the basic equation of quantum cosmic-synergetic dynamics, and then establish the basic equation of quantum-cosmic paradigm dynamics. Thus we put up the operator distribution function and its dynamic equation of the quantum arche- pulsaton, and finally use the Wigner-Ville distribution as a non-linear time-frequency distribution to establish the Wigner joint-distribution of quantum-conjuagted pulsation function, so as to analyze the arche of all things with three evolutionary forms: quantum chaotic-pulsaton, quantum quasi-spherical pulsaton and quantum spherical-pulsaton. In this series of work, the mechanism to avoid the singularity of the universe is put forward fundamentally, and the dark energy and dark matter are explained through new mechanisms and effects at the level of quantum gravity. Between particle physics and cosmology, we improve and expand the path integral of quantum gravity, establish the path integral of quantum hedge-unified field, thus establish the basic equation of quantum cosmic-synergy dynamics, and then establish the basic equation of quantum cosmic-paradigm dynamics. Thus the covariant gravitational mass and the covariant inertial mass formed by the ultra-synergy between particles and the universe are presented, and the equivalence hypothesis on the covariant non-inertial system which can be elevated to the basic principle, is presented. Based on this hypothesis, a systematic calculation and analysis of binary stars composed of neutron stars and black holes are made. The master equation, variance and Fokker-Planck equation for the birth-death and migration of a large number of particles are established between binary stars composed of neutron stars and black holes.

The explosion of data has transformed the world since much more information is available for collection and analysis than ever before. To extract valuable information from the data in different dimensions, various deep learning models have been developed in the past years. Although these models have demonstrated their strong capability on improving products and services in various applications, training them is still a time-consuming and resource-intensive process. Presently, cloud, one of the most powerful computing infrastructures, has been used for the training. However, how to manage cloud computing resources and to perform the training efficiently is still challenging current techniques. For example, general resource scheduling approaches, such as spread priority and balanced resource schedulers, actually do not work well with deep learning workloads. Besides, the resource allocation problem on a cluster can be divide into two subproblems: (1) local resource optimization: improve resource configuration for a single machine; (2) global resource optimization: improve the cluster-wide resource allocation. In this thesis, we propose two novel container schedulers, FlowCon and SpeCon, that are designed to address these two subproblems respectively and specifically to optimize performance of short-lived deep learning applications in the cloud. FlowCon focuses on resource configuration of single-node in a cluster, as show that it efficiently improves deep learning tasks completion time and resource utilization, and reduces the completion time of a specific job by up to 42.06\% without sacrificing the overall system time. SpeCon targets on cluster-wide resource configuration that speculatively migrate slow-growing models to release resources for fast-growing ones. Based on our experiments, SpeCon improves makespan for up to 24.7\%, compared to current approaches.

The advent of deep learning has completely reshaped our world. Now, our daily life is fulfilled with many well-known applications that adopt deep learning techniques, such as self-driving cars and face recognition. Furthermore, robotics developed more forms of technology which share the same principle with face recognition, such as hand pose recognition and fingerprint recognition. Image recognition technology requires a huge database and various learning algorithms, such as convolutional neural network and recurrent neural network, that requires lots of computational power, such as CPUs and GPUs. Thus, clients could not be satisfied with the computational resource of the local machine. The cloud resource platform emerged at a historic moment. Docker containers play a significant role of microservices-based applications in the next generation. However, it could not guarantee the quality of service. From clients’ perspective, they have to balance the budget and quality of experiences (e.g. response time). The budget leans on individual business owners and the required Quality of Experience (QoE) depends on usage scenarios of different applications, for instance, an autonomous vehicle requires real-time response, but, unlocking your smartphone can tolerate delays. Plenty of on-going projects developed user-oriented optimization resource allocation to improve the quality of the service. Considering the users’ specifications, including accelerating the training process and specifying the quality of experience, this thesis proposes two differentiate containers scheduling for deep learning applications: TRADL and DQoES .

Ocean temperatures are increasing. Little work has been done to examine the effects that these changes will have on fishery production. The study at hand seeks to incorporate the influence of climate change into established bioeconomic fishery models. Stock biomass is approximated to be a function of sea surface temperature. Following a feasible generalized least squares regression using data from the Western and Central Pacific, the interaction between fishery effort and temperature is found to be statistically significant. From this model, various functional forms relating effort, catch, and temperature are specified. In particular, a function that returns an effort requirement given a target catch level and temperature forecast is generated.The importance of these tools for fishery management is explored through application to Western and Central Pacific tuna fisheries. Recommendations for extensions into future research are made and the foundation for a model of efficient effort allocation across time and the entirety of a management area, given changing temperatures, is specified.

Upon inbreeding, the architecture of the inbreeding load shifts as selection purges strongly deleterious recessive mutations and drift fixes many milder ones. Most small inbred populations show limited genetic variation while crosses between such populations commonly express pronounced heterosis, confirming fixation. In contrast, purging appears to be limited in that inbred populations often retain substantial inbreeding depression. In addition we have the enigma Darwin noted: purely selfing taxa are unknown. Because both purging and fixation reduce inbreeding depression and load, another mechanism must exist to sustain these. Background selection and the associations that develop among alleles in small inbred populations will shift the architecture of the load potentially creating blocks of recessive mutations linked in repulsion. This would generate pseudo-overdominance that could sustain these “PODs” and inbreeding load. Recombination and crosses between lineages could erode PODs. Crosses between populations fixed for different mutations would generate high pseudo-overdominance, enhancing heterosis and potentially POD formation. New recessive mutations arising within PODs would reinforce overdominance. PODs should generate clear genetic signatures including genomic hotspots of heterozygosity and linkage disequilibrium containing alleles at intermediate frequency generating segregating load. Results from several simulation and empirical studies match these predictions. Further simulations and comparative genomic analyses are needed to rigorously test whether PODs exist in sufficient strength and number to generate persistent inbreeding depression and load in inbred lineages.

Coral reef is an important underwater ecosystem that is rich in biodiversity in it. Coral growth has decreased drastically due to physical and chemical threats, such as the effect of warming seawater, fish bombing activities, and the effects of wastewater. The efficiency level of coral transplantation is determined by many factors, including the stability of the environment's physical condition, the level of coral diversity, and the method of transplantation. The influence of the planting medium can also be a key factor in succeeding the coral transplantation process. The use of stable and natural growing media can be a solution to replace conventional growing media that have been used. Zeolite material is a medium that has many advantages such as amending the trace elemental contents of saltwater such as carbon absorbents, detoxifiers, ammonia remover, catalysts, promoting marine micro-algal growth, become a media for bacterial growth, etc. This review discusses the possibility of zeolites as the candidate media that can be used as a new medium in coral transplantation process to accelerate coral growth and maintain coral health by increasing the adaptation of corals to the effects of global climate change.

Due to the high solar irradiance or energy price, certain regions in the U.S. may reach 100% PV penetration and experience degradation of frequency response greater than the interconnection as a whole. Therefore, in this section, the 100% PV penetration region in each interconnection is simulated to study the local high PV penetration effects. The study was performed by quantifying RoCoF, frequency nadir, and settling frequency at different regional PV penetration levels. The impact of high regional PV penetration on the compliance of grid code on frequency response is also studied.

Three decades have now passed since the first papers linking climate change to issues in human disease and healthcare. One of the most active topics in this area has been the implication of climate change events, particularly temperature and humidity fluctuations, in the northward spread of vector-borne viruses from more tropical regions into Europe and North America. However, some detailed studies of one such emerging disease, tick-borne encephalitis virus (TBEv), have called the connection into question, concentrating the debate on the investigation of precise mechanisms for the spread of viral disease. More recently, firmer statistical correlations have been made between climate variables, the presence of insect vectors and the prevalence of viral disease, particularly for West Nile Virus (WNV). These insights suggest avenues for mechanistic confirmation of the involvement of climate change in other diseases where the connection remains conjectural.

In the present study, the complete mitochondrial genome of the New Zealand parasitic blowfly Lucilia sericata (green bottle blowfly) field strain NZ_LucSer_NP was generated using next-generation sequencing technology. The length of complete the mitochondrial genome is 15,938 bp, with 39.4% A, 13.0% C, 9.3% G, and 38.2% T nucleotide distribution. The complete mitochondrial genome consists of 13 protein-coding genes, two ribosomal RNAs, 22 transfer RNAs, and a and a 1,124 bp non-coding region, similar to most metazoan mitochondrial genomes. Phylogenetic analysis showed that L. sericata NZ_LucSer_NP forms a monophyletic cluster with the remaining six Lucilia species and the Calliphoridae are polyphyletic. This study provides the first complete mitochondrial genome sequence for a L. sericata blowfly species derived from New Zealand to facilitate species identification and phylogenetic analysis.

There are a large number of wildlife and insect species that are in trouble on this planet, and most believe that monarch butterflies in eastern North America are too, because of the well-publicized declines of their winter colonies in central Mexico in the last 25 years. A small number of studies over the last decade have cast doubt on this claim by showing declines are not evident at other stages of the annual cycle. To determine how extensive this pattern is, I conducted an exhaustive review of peer-reviewed and grey literature on (eastern) monarch population censuses and studies, conducted across all seasons, and extracted data from these sources to evaluate how monarch abundance has or has not changed over time. I identified 20 collections of data that included butterfly club reports, compilations of citizen-science observations, migration roost censuses, long-term studies of isotopic signatures, and even museum records. These datasets range in duration from 15 years to over 100 years, and I endeavored to also update each with information from the most current years. I also re-examined the winter colony data after incorporating historical records of colony measurements dating back to 1976. This represents the most complete and up-to-date synthesis of information regarding this population. When I examined the long-term trajectory within each dataset a distinct pattern emerged. Modest declines are evident within the winter colonies (over the full 45 year dataset), and, within three censuses conducted during the spring recolonization. Meanwhile, 16 completely separate monitoring studies conducted during the summer and fall (and from varying locations) revealed either no trend at all or in fact an increase in abundance. While each of these long-term studies has inherent limitations, the fact that all 16 sources of data show the same pattern is undeniable. Moreover, this evidence is consistent with recently-conducted genetic work that shows a lack of decline. Collectively, these results indicate that despite diminishing winter colonies and spring migrations, monarchs in eastern North America are capable of rebounding fully each year, implying that milkweed is not limiting within their collective range. Moreover, there is no indication from these data that the summer population was ever truly diminished by changing agricultural practices in the Midwest that reduced milkweed in crop fields within that region. It is possible that the larger population is not as dependent on Midwestern agricultural milkweed as once thought, and/or that monarchs are adapting to increasingly human-altered landscapes. These results are timely and should bear on the upcoming USFWS decision on whether the monarch requires federal protection in the United States. Importantly, they argue that despite losses of many insects globally, the eastern North American monarch population is not in the same situation.

There is a marked momentum towards the use of clean hydrogen energy as an alternative for fossil fuels. Renewable energies such as solar and wind are being used to generate hydrogen from the water hydrolysis process. Indeed, this approach stores renewable energies in the form of combustible hydrogen for other energy uses. The other alternative that could be economically more cost-effective at the current technology stage is to explore the natural “Hydrogen System” where the natural hydrogen is generated and accumulated within the earth system, the same that stands for a “Petroleum System”. The Discovery of a large accumulation of relatively pure natural hydrogen (H2) in Mali has triggered the opportunity of searching for natural hydrogen accumulations in other countries. The generation of hydrogen from a circular depression in Mali and some other countries is linked to the presence of geologically very old iron-rich basement rocks. Solid-liquid redox reactions between iron-rich minerals and groundwater that split water are a possible source of H2 in deep basement rocks. It is believed that the hydrogen degassing may be detected by surface topographic circular to sub-circular shallow depressions. Chemical processes such as dissolution by hydrogen are considered to play the main role in the formation of the circular depressions through preferential vertical hydrogen migration channel. Archean iron-rich Yilgarn Craton that covers a vast area of Western Australia (WA) contains abundant iron-rich mafic-ultramafic rocks. The craton reveals many surficial circular depressions visible through satellite images. The area has abundant fault systems and is blanketed with Eocene sedimentary rocks containing high-quality reservoir rocks. All these characteristics seem to provide most of the required elements, such as hydrogen source, migration pathway, and reservoir rock for a “Hydrogen System” in this area.

Expectation maximization (EM) algorithm is a powerful mathematical tool for estimating statistical parameter when data sample contains hidden part and observed part. EM is applied to learn finite mixture model in which the whole distribution of observed variable is average sum of partial distributions. Coverage ratio of every partial distribution is specified by the probability of hidden variable. An application of mixture model is soft clustering in which cluster is modeled by hidden variable whereas each data point can be assigned to more than one cluster and degree of such assignment is represented by the probability of hidden variable. However, such probability in traditional mixture model is simplified as a parameter, which can cause loss of valuable information. Therefore, in this research I propose a so-called conditional mixture model (CMM) in which the probability of hidden variable is modeled as a full probabilistic density function (PDF) that owns individual parameter. CMM aims to extend mixture model. I also propose an application of CMM which is called adaptive regressive model (ARM). Traditional regression model is effective when data sample is scattered equally. If data points are grouped into clusters, regression model tries to learn a unified regression function which goes through all data points. Obviously, such unified function is not effective to evaluate response variable based on grouped data points. The concept “adaptive” of ARM means that ARM solves the ineffectiveness problem by selecting the best cluster of data points firstly and then evaluating response variable within such best cluster. In order words, ARM reduces estimation space of regression model so as to gain high accuracy in calculation.

Multi-objective optimization (MOO) is an optimization involving minimization or maximization of several objective functions more than the conventional one objective optimization, which is useful in many fields. Many of the current methodologies addresses challenges and solutions that attempt to solve simultaneously several Objectives with multiple constraints subjoined to each. Often MOO are generally subjected to linear inequality, equality and or bounded constraint that prevent all objectives from being optimized at once. This paper reviews some recent articles in area of MOO and presents deep analysis of Random and Uniform Entry-Exit time of objectives. It further break down process into sub-process and then provide some new concepts for solving problems in MOO, which comes due to periodical objectives that do not stay for the entire duration of process lifetime, unlike permanent objectives which are optimized once for the entire process duration. A methodology based on partial optimization that optimizes each objective iteratively and weight convergence method that optimizes sub-group of objectives are given. Furthermore, another method is introduced which involve objective classification, ranking, estimation and prediction where objectives are classified based on their properties, and ranked using a given criteria and in addition estimated for an optimal weight point (pareto optimal point) if it certifies a coveted optimal weight point. Then finally predicted to find how far it deviates from the estimated optimal weight point. A Sample Mathematical Tri-Objectives and Real world Optimization was analyzed using partial method, ranking and classification method, the result showed that an objective can be added or removed without affecting previous or existing optimal solutions. Therefore suitable for handling time governed MOO. Although this paper presents concepts work only, it’s practical application are beyond the scope of this paper, however base on analysis and examples presented, the concept is worthy of igniting further research and application.

With the prevalence of smartphones, the scope of mobile applications has been significantly broadened in the past few years including almost every aspect of our daily life. Among the applications, message dissemination services play a significant role. Traditionally, users send messages to the servers, which forward them according to friend lists. This client-server architecture is efficient with the support of infrastructures, however, it restricts the application scope and may hinder the wide deployment of location-based mobile applications. This paper proposes a novel communication model called passive broadcast for local message dissemination. In this new model, each node does not maintain a connection state and data delivery is initialized by a receiver via a ’scan’ operation. The representative carriers of passive broadcast include Bluetooth and WiFi-Direct, both of which define a mandatory ‘peer discovery’ function. Passive broadcast features negligible cost for establishing and maintaining direct links and is extremely suitable for short message dissemination in proximity. Furthermore, we study the operation management in the proposed communication model with complete protocols and in-depth analysis for optimization. We prototyped our solution on commercial phones and evaluated it with extensive experiments and simulation.

The current plant two-sex model makes the assumption that there are only two sexual reproductive states: male and female. However, the application of this model to the plant alternation of generations requires the subtle redefinition of several common terms related to sexual reproduction, which also seems to obscure aspects of one or the other plant generation: For instance, the homosporous sporophytic plant is treated as being “asexual,” and the gametophytes of angiosperms treated like mere gametes. In contrast, the proposal is made that the sporophytes of homosporous plants are indeed sexual reproductive organisms, as are the gametophytes of heterosporous plants. This view requires the expansion of the number of sexual reproductive states we accept for plants, therefore a three-sex model for homosporous plants and a four-sex model for heterosporous plants are described and then contrasted with the current two-sex model. These new models allow the use of sexual reproductive terms in a manner largely similar to that seen in animals, and may better accommodate the plant alternation of generations life cycle than does the current plant two-sex model. These new three-sex and four-sex models may also help stimulate new lines of research, and examples of how they might alter our view of the flower, and may lead to new perspectives in terms of sexual determination, are presented. Thus it is suggested that plants have more than merely two sexual reproductive states, and that recognition of this may promote our study and understanding of plants.

This letter introduces a frequency response characteristic (FRC) curve and its application in high renewable power systems. In addition, the letter presents a method for fast frequency response assessment and frequency nadir prediction without performing dynamic simulations using detailed models. The proposed FRC curve and fast frequency response assessment method are useful for operators to understand frequency response performance of high renewable systems in real time.

This paper studied the solar PV frequency control in the U.S. Eastern Interconnection (EI) and Texas Interconnection (ERCOT) systems. The studied frequency control approaches include droop frequency control, inertia control, and droop-inertia-combined frequency control. The control effects of different frequency controls of PV in the EI and ERCOT are studied using actual high PV penetration interconnection grid models to provide suggestions to the future revision of future PV frequency control standards.

C-C Chemokine receptor type 5 (CCR5) is expressed on the CD4 T cell surface where CXCR4 and CCR5 expressions are controlled differently during the activation of T cells and with the binding of interleukin type-2 (IL-2). IL-2 can upregulate CCR1 and CCR2 in CD45R01 T cells and increase the T lymphocyte chemotaxis toward CC-chemokines. CD4+ T cells are either apart of the T helper 1 or Th1 lymphocytes that release interferon gamma (IFNγ) and lymphotoxin that provide cellular immunity to internal pathogens and T helper cells type 2 (Th2), which secrete interleukins 4 and 5 (IL-4 and IL-5). IL-4 and IL-5 cause an allergic and humoral immune response to parasites. Th2 lymphocytes use CCR3 chemokine receptors. CCR5 and CXCR3 chemokine receptors are specific for CD4+ Th1 and Th2 lymphocytes. CCR5Δ32 is a 32-base-pair deletion of the CCR5 gene. CCR5 is a co-receptor for the entrance of the human immunodeficiency virus-1 (HIV-1). CCR5Δ32 creates a malfunction of the CCR5 protein that can prevent HIV-1 infection. However, the CCR5Δ32 32-base-pair deletion is not prevalent and predominant in many populations worldwide and there also exist more genetic variations of CCR5 known as CCR5-SNPs. An alternative polymorphism was identified based on the CCR5 gene that was identified as a A to G (A/G) point mutation. This point mutation is located at the 59029 locus on the promoter that lowers the expression rate of CCR5. Gurdol et al. found activity at the promoter of CCR5/590029G was 45% lesser than the CCR5/59029A. The genetic variations of CCR5 SNPs also include: 2459G>SNP of CCR5, C101X, CCR5 gene position at -2273, and the A to G SNP mutation found in two South African blacks. Therefore, more studies are needed to find more and varied chemokine polymorphisms that are present in many diverse populations in the world. The aim of this literature review is to describe the immense impact of CCR5 SNP mutations on viral infection susceptibility, on the pathogenesis of chronic conditions, to endorse the increased discovery of more novel CCR5 SNPs, and to show the significant potential of anti-CCR5 therapies to treat multiple diseased conditions.

In the last decades, we have witnessed a spectacular information explosion over the Internet. Millions of users are consuming the Internet through various services, such as mobile applications, and online games. The service providers, at the back-end side, are supported by state-of-art infrastructures. Targeting on providing the services at scale, virtualization is one of the emerging technologies used in data centers and cloud environments to improve the quality of services. In this project, we aim to develop a dynamic resource management scheme based on virtual containers. It collects the runtime job progress from the running tasks and allocates the resources dynamically to improve the overall system performance.

Graph entropies have been used to interpret the complexity of the networks. There are various graph entropies in the literature. In this note a new graph entropy is defined which is based on the dominating sets of the graphs. Moreover the entropy of some classes of the graphs is obtained

The article presents the trends in penitentiary work with convicts of different cultures, focuses on their activation, individualisation of work, and organizational difficulties. The purpose of the research has been to discover the ways in which prison staff react to situations requiring flexibility justified by cultural differences of the inmates. The research questions have included: How does prison staff respond to the needs of culturally different inmates? How do the respondents’ reactions correlate with professional experience? Based on the literature, a hypothesis has been established that prison staff avoids individualized treatment of convicted foreigners. Despite the perceived differences in culture, religion, and their different mentality, prison procedures aim at uniformity. Tendencies towards resistance and stiffness to the needs of culturally different people become prevailing. The research method used has included a diagnostic survey (n = 232, F: 40, M: 192) conducted in prison officers in Poland. The written interview technique has been used, where the respondents has reacted to 3 situations of convicts, reflecting their national, religious, and cultural distinctiveness. In their responses, the respondents have decided on the way of action in the situation, as well as their motivation. The operationalization of the source material has been performed in two ways. There has been applied the content analysis method according to the grounded theory (B.G. Glaser, A.L. Strauss), resulting in the creation of categories marking actions and motives. A multiple correspondence analysis (MCA) of the built categories has been carried out using the Statistica program, as well as the correlation analysis of variables with the Cramer's V coefficient. The results of the analysis show statistically created, indicated manners of reacting that have occurred in the studied sample. Additionally, they point out an independent variable - seniority, which has correlated with the quality of the response.

The optimization problem of two or more special-purpose functions of the energy system is subjected to an analysis. Based on experience of our research and general knowledge of partial solutions of energy system optimization at the level of control of production and power energy supply by energy companies in the Czech Republic, a special-purpose (cost) function has been defined. By analysing the special-purpose function, penalty and limitations have been defined. Using the fuzzy logic, a set of suitable solutions for the special-purpose function is accepted. An optimum of the special-purpose function is looked for using the simulated annealing method. The history of electricity consumption is sorted by day and by hour, representing the multidimensional data. When using the cluster analysis, type daytime diagrams of consumption are defined. Type daytime diagrams form prototypes of identified clusters. The so-called self-organizing neural network with Kohonen map attached is used to perform the cluster analysis. The result of our research is presented by an experiment.

Three different approaches show that, contrary to a longstanding conviction older than 160 years, the advance of Mercury perihelion can be achieved in Newtonian gravity with a very high precision by correctly analysing the situation without neglecting Mercury’s mass. General relativity remains more precise than Newtonian physics, but Newtonian framework is more powerful than researchers and astronomers were thinking till now, at least for the case of Mercury. The Newtonian formula of the advance of planets' perihelion breaks down for the other planets. The predicted Newtonian result is indeed too strong for Venus and Earth. Therefore, it is also shown that corrections due to gravitational and rotational time dilation, in an intermediate framework which analyzes gravity between Newton and Einstein, solve the problem. By adding such corrections, a result consistent with the one of general relativity is indeed obtained. Thus, the most important results of this paper are two: i) It is not correct that Newtonian theory cannot predict the anomalous rate of precession of the perihelion of planets' orbit. The real problem is instead that a pure Newtonian prediction is too strong. ii) Perihelion's precession can be achieved with the same precision of general relativity by extending Newtonian gravity through the inclusion of gravitational and rotational time dilation effects. This second result is in agreement with a couple of recent and interesting papers of Hansen, Hartong and Obers. Differently from such papers, in the present work the importance of rotational time dilation is also highlighted.

This paper presents a quantitative approach to poetry, based on the use of several statistical measures (entropy, informational energy, N-gram, etc.) applied to a few characteristic English writings. We found that English language changes its entropy as time passes, and that entropy depends on the language used and on the author. In order to compare two similar texts, we were able to introduce a statistical method to asses the information entropy between two texts. We also introduced a method of computing the average information conveyed by a group of letters about the next letter in the text. We found a formula for computing the Shannon language entropy and we introduced the concept of N-gram informational energy of a poetry. We also constructed a neural network, which is able to generate Byron-type poetry and to analyze the information proximity to the genuine Byron poetry.

Bell's theorem can be refuted by presenting a counterexample which predicts correctly the expectation values of QM. As Bell has only ruled out noncontextual models a contextual model with hidden variables would refute his theorem. Such a model is presented able to explain the spin measurement results with entangled photons or electrons. It is not ruled out by the Kochen-Specker Theorem. Consequences for the feasibility of quantum computers are discussed.

In cricket, particularly the twenty20 format is most watched and loved by the people, where no one can guess who will win the match until the last ball of the last over. In India, The Indian Premier League (IPL) started in 2008 and now it is the most popular T20 league in the world. So we decided to develop a machine learning model for predicting the outcome of its matches. Winning in a Cricket Match depends on many key factors like a home ground advantage, past performances on that ground, records at the same venue, the overall experience of the players, record with a particular opposition, and the overall current form of the team and also the individual player. This paper briefs about the key factors that affect the result of the cricket match and the regression model that best fits this data and gives the best predictions. Cricket, the mainstream and widely played sport across India which has the most noteworthy fan base. Indian Premier League follows 20-20 format which is very unpredictable. IPL match predictor is a ML based prediction approach where the data sets and previous stats are trained in all dimensions covering all important factors such as: Toss, Home Ground, Captains, Favorite Players, Opposition Battle, Previous Stats etc, with each factor having different strength with the help of KNIME Tool and with the added intelligence of Naive Bayes network and Eulers strength calculation formula.

SIGNIFICANCE Putting worth on research and selection of studies by importance are crucial in medical innovation. Practical applications include choosing personal study topics, publication review, study grant selection, and decisions of spending or misspending billions in public health. Multiple studies raised alarm that current methods perform poorly in reproducibility, prediction of best research and objectivity. I propose using the metrics how much disease burden is reduced and calculating objective, numerical research value. The concept is that worth of medical research is not subjective but can be reproducible and numerically quantified. The method increases transparency by giving decision makers an externally accountable proof, and frees peer reviewers to check scientific integrity. Its numerical form can capture small differences important in competition between studies. ABSTRACT Finding value and selecting knowledge by importance are crucial in medical innovation. Applications include individuals designing research, funding organizations selecting grants, journals – publications, institutions – priorities in public health and health policy, and decision makers spending or misspending billions of research funds. Currently finding value of knowledge is done by peer review together with checking scientific integrity. Multiple studies raised alarm that it performs poorly in prediction of highest citations, bias, transparency and quality. The resulting problems include perception of slow medical progress and wasting funds and time. I introduce a standard, objective and numerical method for finding value of medical research. It measures disease burden prevented by new knowledge contained in a study or a publication. In its simple form, it is calculated by multiplying disease prevalence, disease burden, and efficacy of the therapy. It can be modified for risk of failure, multi-disease effect and for ethical considerations. The process is described step-by-step in terms common in medical practice. A quick estimate is often sufficient. The advantage is objectivity, since it is calculated from real world data. This gives transparency and externally accountability of decision making. The second advantage is a numerical form. This can measure small differences in research value which, in sharp competition, determine which studies are selected. A researcher can calculate the value of own future effort. Institutions might ask to provide it at submission. The method is also applicable to broad policy analysis, objective evaluation of scientific achievement and bibliometric studies.

It is shown that the relationship between gravity and quantum physics can be described in terms of the symmetry break of space due to elementary constituents, dubbed as “darks”, which constitute a universal energetic background field that extends from the cosmological level down to the nuclear level. It requires (a) the awareness of the polarisable second elementary dipole moment of a recently discovered third Dirac particle type, next to the electron-type and the Majorana-type, and (b) the awareness that Einstein’s Lambda is not a constant of nature, but, instead, a covariant integration constant with a value that depends on the scope of the cosmological system under consideration, such as solar systems and galaxies, eventually showing up as the Cosmological Constant at the level of the universe. The relationship has been made explicit by relating two major gravitational constants quantaties (the gravitational constant and Milgrom’s acceleration constant) with a single nuclear quantity (the rest mass of the pion derived from the Higgs boson value).

The interaction of ultraviolet radiation with biological matter results in direct damage such as pyrimidine dimers in DNA. It also results in indirect damage provoked by the production of Reactive Oxygen Species (ROS) catalyzed by photo-sensitizers. Photosensitizers can be endogenous (e.g. Tryptophan) or exogenous (e.g. TiO2 and other photo-stable UVA sunscreens). Direct damage triggers an inflammatory response and the oxidative and proteolytic bursts that characterize its onset. The inflammatory reaction multiplies the effects of one single photon. Indirect damage, such as the peroxidative cascade in membrane lipids, can extend to thousands of molecular modifications per absorbed photon. Sunscreens should therefore be formulated in the presence of appropriate anti-oxidants. Superoxide and Singlet Oxygen are the main ROS that need to be tackled: this review describes some of the molecular, biochemical, cellular and clinical consequences of exposure to UV radiation as well as some results associated with scavengers and quenchers of Superoxide and Singlet Oxygen, as well as with inhibitors of singlet Oxygen production.

We consider a multitude of topics in mathematics where unification constructions play an important role: the Yang–Baxter equation and its modified version, Euler’s formula for dual numbers, means and their inequalities, topics in differential geometry, etc. It is interesting to observe that the idea of unification (unity and union) is also present in poetry. Moreover, Euler’s identity is a source of inspiration for the post-modern poets.

In this paper, we consider the problem that the maximal order consider the groups that consisting of transformations we called NG-Transformation on a nonempty set A has no bijection as its element. We find the order of these groups not greater that (n-1)!. In addition, we will prove our result by showing that any kind of NG-group in the theorem be isomorphic to a permutation group on a quotient set of A with respect to an equivalence relation on A.

Background: In 2014 the World Health Organization (WHO) warned of an emerging world-wide crisis of antibiotic resistant microorganisms. In response, government and professional organizations recommended that health care systems adopt antimicrobial stewardship programs (ASPs). In the United States, the Centers for Medicare Services (CMS) mandated antimicrobial stewardship in the hospital inpatient setting. Effective January 1, 2020, the Joint Commission required ambulatory centers that prescribe antibiotics, such as wound centers, to institute an ASP. Chronic wounds often remain open for months, during which time patients may receive multiple courses of antibiotics and numerous antimicrobial topical treatments. The wound clinician plays an integral role in reducing antimicrobial resistance in the outpatient setting: antibiotics prescribed for skin and soft tissue infections are among the most common in an outpatient setting. One of the most challenging aspects of antimicrobial stewardship in treating chronic wounds is the inaccuracy of bacterial and infection diagnosis. Methods: Joint Commission lists five elements of performance (EP): (1) Identifying an antimicrobial stewardship leader, (2) establishing an annual antimicrobial stewardship goal, (3) implementing evidence-based practice guidelines related to the antimicrobial stewardship goal, (4) providing clinical staff with educational resources related to the antimicrobial stewardship goal, and (5) collecting, analyzing, and reporting data related to the antimicrobial stewardship goal. This article focuses on choosing and implementing an evidence-based ASP goal for 2020. Discussion: Clinical trials have demonstrated the ability of fluorescence imaging (MLiX) to detect clinically significant levels of bacteria in chronic wounds. Combined with clinical examination of signs and symptoms of infection, the MLiX procedure improves the clinician’s ability to diagnose infection and can guide antimicrobial use. In order to satisfy the elements of performance, the MLiX procedure was incorporated into the annual ASP goal for several wound care centers. Clinicians were educated on the fluorescence imaging device and guidelines were instituted. Collection of antimicrobial utilization data is underway.

Historical analysis of Australian bushfire data spanning 170 years addresses whether the strength of recent fire events has been exacerbated by human-induced climate change. The question of “cause” looks at the characteristics of a wider range of natural hazards. Fire characteristics are compared with earthquake hazard characteristics: (1) energy – termed “magnitude”; (2) severity – termed “intensity”; and (3) resultant damage to people and structures – termed “impact”.Published global, Northern and Southern hemisphere temperature data are shown to vary consistently in phase over 170 years, but vary in amplitude with statistical significance. CO₂ levels north and south of the Equator have tracked quite consistently. Thus, Southern Hemisphere bushfire magnitude and intensity is compared with the Southern Hemisphere climate record, rather than a global data set.28 major bushfires and associated droughts since 1850 show neither apparent drought extent, nor area burned, nor bushfire intensity, correlates with changes in Southern Hemisphere climate. Average rainfall from 1900 shows a wetter, rather than drier trend. Cyclone energy shows no significant trend with climate. Planet-wide “greening”, through CO₂ fertilisation, is an insignificant contributor to bushfire magnitude. Combustion theory shows recorded “global warming” could have had no significant influence on bushfire magnitude or intensity. Any increase in Australian bushfire impact, as judged by lives lost, similarly, shows no correlation with bushfire magnitude, nor indeed, any observed Southern Hemisphere global warming.Thus, bushfire magnitude seems much more likely driven by fuel load and any anomalous bushfire intensity is likely driven by anomalous ground level fuel load. The evidence suggests that any CO₂ emissions reduction will have no impact on future bushfire “severity.

Under some employment circumstances, individuals in some organizations are willing to engage in unethical behaviors that benefit one’s own supervisors who have a great power to decide the levels of evaluation and compensation for each individual. In this study two hypotheses were examined. First, based on social identification theory, we hypothesized that individuals’ feeling a sense of oneness with one’s own supervisors promote unethical pro-supervisor behaviors (UPSB). Second, based on a person-situation interactionist model, we hypothesized that this positive relationship is strengthen if the individual perceives lower levels of one’s own employability. Data were collected from 185 individuals of various types of organizations in South Korea. A time-lagged field study supported our hypotheses. In particular, supervisor identification was positively related to UPSB. Further, for individuals with a weaker employability perception, supervisor identification was positively related to UPSB.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the disease COVID-19 that has decimated the health and economy of our planet. The virus causes the disease not only in people but also in companion and wild animals. People with diabetes are at risk of the disease. As yet we do not know why the virus is highly successful in causing the pandemic within 3 months of its first report. The structural proteins of SARS include, membrane glycoprotein (M), envelope protein (E), nucleocapsid protein (N) and the spike protein (S). The structure and function of the most abundant structural protein of SARS-CoV-2, the membrane (M) glycoprotein is not fully understood. Using in silico analyses we determined the structure and potential function of the M protein. The M protein of SARS-CoV-2 is 98.6% similar to the M protein of bat SARS-CoV, maintains 98.2% homology with pangolin SARS-CoV, and has 90% homology with M protein of SARS-CoV; whereas, the similarity was only 38% with the M protein of MERS-CoV. In silico analyses showed that the M protein of SARS-CoV-2 has a triple helix bundle, form a single 3-transmembrane domain (TM), and are homologous to the prokaryotic sugar transport protein semiSWEET. SemiSWEETs are related to the PQ-loop family that function as cargo receptors in vesicle transport, mediates movement of basic amino acids across lysosomal membranes, and is also involved in phospholipase flippase function. The advantage and role of the M protein having a sugar transport-like structure is not clearly understood. The M protein of SARS-CoV-2 interacts with S, E and N protein. The S protein of the virus is glycosylated. It could be hypothesized that the sugar transporter-like structure of the M protein influences glycosylation of the S protein. Endocytosis is critical for the internalization and maturation of RNA viruses, including SARS-CoV-2. Sucrose is involved in endosome and lysosome maturation and may also induce autophagy, pathways that help in the entry of the virus. Overall, it could be hypothesized that the semiSWEET sugar transporter-like structure of the M protein may be involved in multiple functions that may aid in the rapid proliferation, replication and immune evasion of the SARS-CoV-2 virus. Biological experiments would validate the presence and function of the semiSWEET sugar transporter.

With the year 2020, the world faced a new threat that affects all areas of life, negatively affects production in all areas, and paralyzes social life. The measures and restrictions taken by the country's governments to prevent the epidemic from spreading rapidly in the society with the effect of the Covid-19 virus, which first appeared in China and spread all over the world, brought a new lifestyle. Covid-19 has been much the impact on electricity use and electricity production in the period in Turkey as in other countries. There was a sharp decline in commercial and industrial electricity use. The coronavirus effect has also been reflected in the electricity demand and the consumption amount has undergone a great negative change. Due to the enactment of measures against the new type of coronavirus (COVID-19) epidemic and the partial or full-time curfews, electricity consumption was moved to homes, supermarkets, and hospitals in April 2020 from places where mass consumption is intense, such as industry, workplaces, and educational institutions. In this study, Covid-19 period, the first cases were examined electricity production and consumption in Turkey as of the date it is seen throughout, in comparison with electricity consumption data in the same month of the previous years corresponding to this period, the effects on electricity generation and consumption habits of this period were examined.

We suggest a deep learning based sensor signal processing method to remove chemical, kinetic and electrical artifacts from ion selective electrodes’ measured values. An ISE is used to investigate the concentration of a specific ion from aqueous solution, by measuring the Nernst potential along the glass membrane. However, application of ISE on a mixture of multiple ion has some problem. First problem is a chemical artifact which is called ion interference effect. Electrically charged particles interact with each other and flows through the glass membrane of different ISEs. Second problem is the kinetic artifact caused by the movement of the liquid. Water molecules collide with the glass membrane causing abnormal peak values of voltage. The last artifact is the interference of ISEs. When multiple ISEs are dipped into same solution, one electrode’s signal emission interference voltage measurement of other electrodes. Therefore, an ISE is recommended to be applied on single-ion solution, without any other sensors applied at the same time. Deep learning approach can remove both 3 artifacts at the same time. The proposed method used 5 layers of artificial neural networks to regress correct signal to remove complex artifacts with one-shot calculation. Its MAPE was less than 1.8% and R² of regression was 0.997. A randomly chosen value of AI-processed data has MAPE less than 5% (p-value 0.016).

Stormwater drainage and urban flooding are the popular issues in policy agendas and academia. Although the research on these title increases steadily an integrated review on stormwater drainage and urban flood with a focus on pluvial flooding has yet to be produced. This paper presents a critical review on stormwater drainage and urban flood based on 78 selected journal papers published over the period of 1990 to 2018. The review focus on pluvial flooding to relate urban stormwater drainage management and urban flood disaster management and to show the links between the two. The methods taken to manage urban stormwater drainage and urban flooding as well as the complexity of achieving a comprehensive urban flood disaster management are evaluated and discussed. To better understand the concepts behind urban flood and improve the urban flood risk management strategies, recommendation of future research directions are also provided.

Background: Overweight and obese adults seek effective exercise interventions to reduce accumulated fat, but the effectiveness of these interventions vary across studies. The purpose of this meta-analysis was to investigate the effectiveness of exercise interventions in overweight and obese adults based on measurement of accumulated fat distributions. (2) Methods: Databases were used to select eligible studies for this meta-analysis. Randomized controlled trials with a control and experimental group were included. Degrees of effectiveness of exercise interventions were computed to assess the benefits on reducing weight and subcutaneous, visceral, and ectopic fat accumulation. (3) Results: A total of twenty-one studies were included in this meta-analysis. Participation in exercise interventions showed beneficial effects in reducing weight and subcutaneous and visceral fat. The effectiveness of exercise interventions on ectopic fat accumulation could not be assessed due to the limited number of studies measuring ectopic fat. Additionally, effectiveness of exercise interventions that depended on measurements of accumulated fat varied. The average exercise intervention for overweight and obese individuals was moderate to vigorous intensity, 4 times per week, 50 minutes per session, and 22 weeks duration. (4) Conclusions: Participating in exercise interventions has favorable effects on reducing weight and accumulation of subcutaneous and visceral fat.

Cheating is a kind of fraud or attempts to get dishonest advantages in an academic institution, it has been increasing dramatically for the last 50 years with the growth of technology. In some countries, this phenomenon has changed to a problematic factor in schools. Plagiarism is also considered as a type of cheating if it occurs intentionally. More efforts are made to mitigate the severity of cheating in an academic institution using technological-based devices. Besides, technology has an effective role in the detection of plagiarism by several detection platforms, however, still, there are some types of plagiarism which cannot be detected by these platforms efficiently, that authors should treat honestly during his/her scientific writing. This work aims to conceptualize and characterize cheating and plagiarism in an academic institution, also it is tried to indicate the relationship of cheating and plagiarism that in which cases, plagiarism becomes cheating. To achieve the purposes, relevant literature including scientific papers, monographs, reports, and authorized website were reviewed, and the literature output are integrated with the observation and experience of author during the teaching and learning in academic institutions.The findings and direct observation from close contact of classrooms show that cheating is felt mostly in classes with large numbers of students, that institution policy, instructor control, and using of technology have the most effect on the controlling cheating. Plagiarism as academic dishonesty is a widespread phenomenon among the students and even the authors. In some cases, the poor understanding of students and authors in scientific writing rules causes plagiarism and is measurable by some available detection platforms.

Teaching is considered a multifarious task. Teachers, in the pursuit of educational success, are burdened with numerous teaching workloads and dilemmas causing them stress. This study endeavored to determine the influence of stress on professional satisfaction of multigrade teachers. It employed correlation research design involving thirty (30) purposively selected multigrade teachers in the Schools Division of General Santos City (GSC), Southern Philippines. Employing the survey method, tailored questionnaires were utilized to gather the needed data. The statistical tools employed in the analysis were weighted mean and Pearson Product Moment Correlation Coefficient. Moderate level of stress and high level of professional satisfaction are gained among the multigrade teachers surveyed. It was further found out that there is no significant relationship between stress and professional satisfaction, providing evidence that stress may not necessarily influence satisfaction. This result offers unique implications in theory, practice, and research which are discussed in the study.

The hydraulic fracturing is studied by using dimensional analysis. A universal scaling law of the hydraulic fracturing is obtained. This simple relation has not been seen in the literature.

Washing hands, social distancing and staying at home are the preventive measures set in place to contain the spread of the COVID-19, a disease caused by SARS-CoV-2. These measures, although straightforward to follow, highlight the tip of an imbalanced socio-economic and socio-technological iceberg. Here, a System Dynamic (SD) model of COVID-19 preventive measures and their correlation with the 17 Sustainable Development Goals (SDGs) is presented. The result demonstrates a better informed view of the COVID-19 vulnerability landscape. This novel qualitative approach refreshes debates on the future of SDGS amid the crisis and provides a powerful mental representation for decision makers to find leverage points that aid in preventing long-term disruptive impacts of this health crisis on people, planet and economy. There is a need for further tailor-made and real-time qualitative and quantitative scientific research to calibrate the criticality of meeting the SDGS targets in different countries according to ongoing lessons learned from this health crisis.

This brief work tenets that inflationary genesis can be obtained within the standard model based on only a few general assumptions. These are that the origin began at a singularity of Planck length and that all quantum transitions take place within Planck time units. From these, the subsequent effects from the Pauli Exclusion Principle (PEP) and the uncertainty principle can then give rise to an inflationary origin.

Since identified as the pathogen responsible for an outbreak of severe respiratory distress in Wuhan, China, the 2019-nCoV coronavirus has caused over 30M cases and 1M deaths globally. Sporadic cases were identified in several states in the US from early January, and large-scale community transmission is believed to have started in late February, leading to a first spike in COVID-19 deaths and overall mortality in late April, and a second spike later in the summer. I show here that the dynamics of the pandemic were different in different regions of the US, showing a north-south pattern, with a first pandemic wave mainly in northern regions, followed by a second wave mainly in southern regions. Analysis of overall mortality data shows that the increase in mortality correlates well with COVID-19 incidence in most regions, and that from April through August COVID-19 deaths accounted for a substantial proportion of all deaths in all parts of the US.

Neonicotinoids, such as dinotefuran (DF), have caused a variety of problems, such as massive loss and winter failure of the bee colony, as a price for the benefit of reducing farm work, because it continues to maintain a high insecticide activity over a long period of time. In this study, a field experiment was conducted for about six months to investigate the effects of DF on bee colonies damaged by Varroa mites. This study examined the long-term changes in such as the size of bee colonies, the intake of sugar syrup (SS), intake of pollen paste (PP), which is a vehicle for administering DF, the intake of DF, the mite-prevalence of bees and the inside and outside temperatures of hive-boxes. The variation width of the inner temperature of the hive-box is less than that of the ambient temperature (Ta). The inner temperature of the hive-box is adjusted with about 30 ℃ of Ta as the boundary. If Ta is lower than 30 ℃, the inner temperature of the box is higher than Ta, and if Ta is higher than 30 ℃, it is lower than Ta. The temperature variation width of the DF-exposed colony is greater than that of the control colony. The average intake of SS per bee per day of the DF-exposed colony is more than that of the control colony. The average intake of PP per bee per day of the DF-exposed colony is almost equal to that of the control colony. These results suggest that bees do not avoid DF, and ingest PP without distinction between toxic and pesticide-free. In the period from the start of DF administration to the colony extinction, the intake of DF per colony is about 865 µg/colony, the intake per bee is 14 ng/bee, and the intake per bee per day is less than 0.1 ng/bee/day in this work. These intakes are much lower than the previous ones (60-65 ng/bee, 0.27-2.32 ng/bee/day). These discrepancies may be because attacks of mites and Japanese giant hornets hastened the colony collapse. Seasonal changes in mite-prevalence of honeybees is approximately the same regardless of the bee colonies. At the end of August (the start of attacks by Japanese giant hornets), the mite-prevalence will increase rapidly. Even if the number of bees damaged by mites turns to decrease, the mite-prevalence will continue to increase, with approaching 100% before bee colonies become extinct. In this study, it was found that the bee colony was collapsed by the intake of a smaller amount of DF due to the synergistic effect of DF and mite-damage. To prevent a bee colony collapse, not only to make an effort to minimalize the adverse effect on the bee colony of neonicotinoids such as DF with long-term residual effect and high insecticide properties, it is necessary to reduce the damage of mites as much as possible, while considering the synergistically adverse effects of neonicotinoids and miticides.

The accurate calculation of real contact area between rough surfaces is a key issue in tribology. In this paper, based on the geometrical information of total contact area and the number of contact spots with respect to surface separation, a new method is proposed to determine the relation between real contact area and normal load. The contact of rough surfaces is treated as an accumulation of incremental multi-plateaus indentations with varying average contact radius. Comparisons with direct finite element calculations and some other theoretical predictions demonstrate the efficiency of this approach.

In this paper we will find that, according to holographic principle {\cite{Holografico}} and thus considering Universe as the ensemble of $\aleph$ information bits or minimum particles of mass $m_{g}$, the contribution to galactic rotation curves can be due the rest of the visible Universe through a non-local collective gravitational interaction of all particles within the Universe's horizon, as a consequence of which all particles are gravitationally entangled and form a unified statistical ensemble. Therefore, we can to describe this global effect in terms of standard local Newtonian gravity within galaxies for the explanation of flatness galactic rotation curves as a possible alternative to the dark matter or MOND hypothesis. We will find a solution for the baryonic Tully-Fischer relation: $M_{b} = A v_{f}^4 \iff A = \left[a_{0}G \right]^{-1}$ with $a_{0} = \frac{cH_{0}}{2\pi}$, where $H_{0}$ is the Hubble constant at present Time $t_{0}$ and $M_{b}$, $G$ and $c$ are the galaxy baryonic mass, gravitational constant and constant speed of light in vacuum respectively. Also we will find the mass discrepancy-acceleration relation, thus obtaining a possible solution for each of the three laws of rotationally supported galaxies proposed in ({\cite{McGaugh}},{\cite{McGaugh1}}).

Background: Forecasting nonlinear stochastic systems most often is quite difficult, without giving in to temptations to simply simplify models for the sake of permitting simple computations. Objective: Here, two basic algorithms, Adaptive Simulated Annealing (ASA) and path-integral codes PATHINT/PATHTREE (and their quantum generalizations qPATHINT/qPATHTREE) are offered to detail such systems. Method: ASA and PATHINT/PATHTREE have been effective to forecast properties in three disparate disciplines in neuroscience, financial markets, and combat analysis. Applications are described for COVID-19. Results: Results of detailed calculations have led to new results and insights not previously obtained. Conclusion: These 3 applications give strong support to a quite generic application of these tools to stochastic nonlinear systems.

This article discusses the implementation of the Water Framework Directive (WFD) in the Netherlands and intends to show how law and politics combine in river basin management. Initially, the implementation of the WFD in the Netherlands was approached as a technical and administrative issue, handled by water quality and ecology experts, but in 2003 this approach was broken open by the agricultural sector, who were worried about stricter regulation. Subsequently, the environmental objectives of the WFD were set as low as possible and they are not used in authorising individual projects. Yet, in 2015 of the European Court of Justice determined that the environmental objectives have binding effect and that Member States have to refuse authorisation for projects that endanger the achievement of these objectives. In the future, the European Court of Justice and national courts may force the Dutch government to change its approach. They may only do so because and as long as they enjoy sufficient social and political support and function relatively independently. The article concludes that, to understand river basin management fully, one has to open up the black box of water law and become a kind of water lawyer.

Ribosomes are macromolecular complexes important to protein translation, and thus, essential to life. Comprising an ensemble of ribosomal proteins and RNA molecules, ribosomes are conserved in structure and function across all domains of life, but recent structural studies have revealed differentiated structures of ribosomes from bacterial, archaea and eukaryotes. Additionally, unique ribosomal protein mass fingerprints have been found for individual species; thereby, indicating that ribosomes are differentiated in structure amongst different species. Given that structure defines function, differentiated function likely exists amongst ribosomes of different species, which could manifest as differences in translation efficiency that could impact on cell growth rate. But ribosomal proteins also hold phylogenetic significance in informing the evolutionary trajectory of each species. Such ribosomal proteins are thus not highly conserved and offers sufficient sequence space for the evolution of differentiated structure and function in different species. Using ribosomal proteins that hold phylogenetic significance as templates, this study sought to understand the mutational and conformational limits that define functional ribosomes. Specifically, ribosomal proteins in Bacillus subtilis that hold phylogenetic cues would be mutated through error-prone polymerase chain reaction to generate variants that are subsequently transformed into Escherichia coli. To help assess the functional properties of the heterologous ribosomal proteins, endogenous ribosomal protein genes would be inactivated by multiplex CRISPR interference. Since variants in ribosomal proteins would likely impact on ribosome function and translation efficiency, live/dead screening on LB agar would be effective as a preliminary screen for functional mutants. These mutants would subsequently be inoculated into liquid LB medium in 96 well plates to quantify relative growth rates between different strains harbouring different heterologous variants of ribosomal proteins. Plasmids containing different ribosomal protein mutants would be extracted from each functional strain and subjected to Sanger sequencing for determining the specific mutations involved. Collection of such mutations would provide a comprehensive mutational map that define the limits of ribosomal protein sequence space important to ribosome function. Furthermore, biochemical isolation of ribosomal proteins and their structural characterization by X-ray crystallography or cryo-electron microscopy would further illuminate the structural significance of each mutation on ribosome structure and function; thereby, elucidating the structural tolerance space for functional ribosomes. Overall, generating a diverse pool of mutant ribosomal proteins in viability assays followed by sequencing and structural characterization would help define the mutational and conformational limits of a functional and efficient ribosome.

The flipped classroom is gaining prominence as an active learning pedagogy to engage a new generation of students. However, all courses do not lend themselves to a fully flipped design and instructors are often reluctant to flip lectures. In this study, I experimented with a “partial” flipped classroom design in a first-year undergraduate economics course. In this partial flipped format, traditional lectures were substituted with micro-lectures and the remaining class time was devoted to activities like quizzes, group work and student presentations. The full lectures were panopto recorded and put up on the e-learning site, Blackboard. This format enabled me to combine the benefits of a traditional lecture with a flipped classroom design. In order to evaluate the effectiveness of the partial flipped classroom format, I compared the final exam scores of students in the partial flipped classroom with those in the control group, which followed a traditional lecture-based approach. The key results from the analysis revealed that students in the partial flipped classroom performed better in the final exams vis-à-vis students in the traditional classroom format. Furthermore, the partial flipped classroom format was associated with lower odds of students failing in the module. This format also resulted in better student engagement, more flexibility and enhanced student-tutor interaction within the classroom.

Biological systems are highly regulated. They are also highly resistant to sudden perturbations enabling them to maintain the dynamic equilibrium essential for sustenance of life. This robustness is conferred by regulatory mechanisms that influence the activity of enzymes/proteins within their cellular context, to adapt to changing environmental conditions. However, the initial rules governing the study of enzyme kinetics were tested and implemented for mostly cytosolic enzyme systems that were easy to isolate and/or recombinantly express. Moreover, these enzymes lacked complex regulatory modalities. Now, with academic labs and pharmaceutical companies turning their attention to more complex systems (for instance, multi-protein complexes, oligomeric assemblies, membrane proteins and post-translationally modified proteins), the initial axioms defined by Michaelis-Menten (MM) kinetics are rendered inadequate and the development of a new kind of kinetic analysis to study these systems is required. The current review strives to present an overview of enzyme kinetic mechanisms that are atypical and, oftentimes, do not conform to the classical MM kinetics. Further, it presents initial ideas on the design and analysis of experiments in early drug-discovery for such systems, to enable effective screening and characterisation of small-molecule inhibitors with desirable physiological outcomes.

In this manuscript a new approach into analyzing the local stability of equilibrium points of non-linear Caputo fractional planar systems is shown. It is shown that the equilibrium points of such systems can be a stable focus or unstable focus. In addition, it is proposed that previous results regarding the stability of equilibrium points have been incorrect, the results here attempt to correct such results. Lastly, it is proposed that a Caputo fractional planar system cannot undergo a Hopf bifurcation, contrary to previous results prior. Though, it is shown that such systems can undergo a Hopf bifurcation (topologically).

This paper is based on a talk given at the 14-th International Workshop on Differential Geometry and Its Applications, hosted by the Petroleum Gas University from Ploiesti, between July 9-th and July 11-th, 2019. After presenting some historical facts, we will consider some geometry problems related to unification approaches. Jordan algebras and Lie algebras are the main non-associative structures. Attempts to unify non-associative algebras and associative algebras led to UJLA structures. Another algebraic structure which unifies non-associative algebras and associative algebras is the Yang-Baxter equation. We will review topics relared to the Yang-Baxter equation and Yang-Baxter systems, with the goal to unify constructions from Differential Geometry.

Daltonisation refers to the recolouring of images such that details normally lost by colour vision deficient observers become visible. This comes at the cost of introducing artificial colours. In a previous work, we presented a gradient-domain colour image daltonisation method that outperformed previously known methods both in behavioural and psychometric experiments. In the present paper, we improve the method by (i) finding a good first estimate of the daltonised image, thus reducing the computational time significantly, and (ii) introducing local linear anisotropic diffusion, thus effectively removing the halo artefacts. The method uses a colour vision deficiency simulation algorithm as an ingredient, and can thus be applied for any colour vision deficiency, and can even be individualised if the exact individual colour vision is known.

Greenhouse have to provide optimal climate conditions for healthy plant growth and high production. Heating of greenhouses is required for an efficient and reliable production specially during winter time in Turkey. However, even in the temperate zones, heating costs has a great portion in the total production costs. Coal is preferred as a fuel in the greenhouse heating in provinces of Turkey where there is no geothermal energy. In this study, the heating requirements and fuel cost (fossil and geothermal energy) for Antalya, Afyon, Kütahya, Denizli, and Aydın provinces in the Aegean and Mediterranean region have been identified based on long term meteorological data. The calculations were made for two model greenhouses located in an area with 1 ha representing modern greenhouses of the regions. The first is a gothic roofed plastic model greenhouse and the second is a gable roofed polycarbonate model greenhouse. According to the results of calculations, total annual heatingrequirement values ranged from 6,096,283 (for Antalya) to 20,359,946 MJ/ha (for Afyon) for the plastic greenhouse wheras these values ranged from 3,187,074 (for Antalya) to 10,643,972 MJ/ha (for Afyon) for the polycarbonate greenhouse.

We present an ontology log-OLOG- representation of the classical Miller-Urey experiment, usually considered as a paradigm for spontaneous generation of biomolecules on the prebiotic Earth and also, as a key in understanding the chemical evolution phenomena linked to the origins of life. Ologging The Miler-Urey experiment enables us, through the categorical notion of fibre product or pullback, to define the concept of Biogenic Space, as a space containing low complexity biogenic units subjected to appropriate physical and chemical conditions, facilitating the synthesis of highly complex organic molecules. Also, we characterize the Biogenic Space as a concrete universal object that could be associated with the preconditions for life inside various structures in the universe such as exoplanets and exomoons located in habitable zones, but also in interstellar and intergalactic organic clouds.

One of factors causing decline of paleo fauna is related to the hunting activities and the use of tools by early hominin. This study aims to observe the relationships of tools and abundances of mammals in early hominin occupancy in Pawon cave for the period of 6000-9000 year ago (ka). The results show low abundances of medium to large mammals. While obsidian tools numbers were observed high. From 8 to 9 ka there were abrupt reductions and followed with the disappearance of medium-large sized mammals included Tragulidae and Bovidae in 6 ka. Simultaneously, uses of obsidian tools in 8-9 ka were common. The reconstructed paleo climate may contribute to the decline of paleo mammal abundances. The temperatures were increasing from 27 0C in 9 ka to 28 0C in 6 ka. Periods of 6-7 ka were indicated by declines of Bovidae and obsidian tools as well. Nonetheless in these periods, there were increase in numbers of pottery and Suidae remains indicated the transition from hunting-gatherer to sedentary prehistoric life

This paper aims to investigate the global asymptotic stability of following system of higher order difference equations with quadratic terms: x_{n+1}=A+B((y_{n})/(y_{n-m}²)),y_{n+1}=A+B((x_{n})/(x_{n-m}²)) where A and B are positive numbers and the initial values are positive numbers. We also study the rate of convergence and oscillation behaviour of the solutions of related system.

As the coproduct of steelmaking, steelmaking slag, volumetrically expansive-prone without treatment, has been satisfactorily used as an aggregate base course material in highway construction. Although numerous technical reports and papers have revealed that steel slag aggreged using in rigid matrixes, the end product, paving block, non-structural concrete, for example, possesses superb strength and durability properties, the application of steel slag aggregate as a concrete aggregate is currently prohibited in highway construction. Naturally, researchers explore the practicality of use of steel slag, how to connect the laboratory experiment results to the end-product behavior, and further convert the research results into real construction? For all nontraditional or secondary materials utilization, the procedure of laboratory material examination, lab and field trial test are critical. To generalize the utilization, usability criteria establishment is necessary. This paper tries to use step-by-step method and plain language to explain how the volumetrically expansion can be simulated in lab testing apparatus, and based on the model, the mathematical deduction can result in a numerical usability criterion for steel slag use as a coarse aggregate in concrete (a rigid material). Therefore the paper is composed four main parts, laboratory test methods to examine the expansion force resulted from steel slag; converting the measured expansion force in a given volume of mass aggregate to the expansion (body) force of a single particle; modeling of slag and end material disruption; and a usability criterion from numerical deduction for the use of expansive-prone coarse slag in concrete or other rigid matrices. The paper provides the solutions to answer the above questions. Through the mathematical and mechanical modeling, provides the potential criteria that could result in specifications and guidance establishment for broad volumetric expansive-prone slags.

The notion that there is a one to one mapping from genotype to phenotype was overturned a long time ago. Along with genotype and environment, ‘non-genetic changes’ orchestrated by altered RNA and protein molecules also guide the development of phenotype. The idea that there is a route through which changes in phenotype can lead to changes in genotype impinges on several phenomena of molecular, developmental, evolutionary and applied interest. Phenotypic changes that do not alter the underlying DNA sequence have been studied across model systems (eg: DNA and histone modifications, RNA editing, prion formation) and are known to play an important role in short term adaptation. However, because of their transient nature and unstable inheritance, the role of such changes in long term evolution has remained controversial. I classify and review three ways in which non-genetic changes can influence genotype and impact cellular fitness across generations, with an emphasis on the enticing idea that they may act as stepping stones for genetic adaptation. I focus on work from microbial systems and attempt to highlight recent experiments and models that bear on this idea. Overall, I review evidence which suggests that non-genetic changes can impact phenotype via their influence on the genotype, and thus play a role in evolutionary change.

GANs are well known for success in the realistic image gen-eration. However, they can be applied in tabular data generation as well.We will review and examine some recent papers about tabular GANs inaction. We will generate data to make train distribution bring closer tothe test. Then compare model performance trained on the initial traindataset, with trained on the train with GAN generated data, also wetrain the model by sampling train by adversarial training. We show thatusing GAN might be an option in case of uneven data distribution be-tween train and test data

In this project, we use a statistical multiple regression to study the impact of eight various predictors (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, glazing area distribution) to estimate the cooling load energy efficiency of residential buildings. We try to analyze and visualize the effect of each predictor with each of the response variable using different classical statistical analysis tools used in describing linear models, in such a way so that we can find out the most strongly related predictor variables. Before starting all of this, we use the idea of model selection by stepwise regression technique and compare the AIC of these models and identified a better model between all of them. Then, we compare a classical linear regression approach by simulations on 768 diverse residential buildings show that we can predict CL with low mean absolute error. By using ANOVA we determine variation in the different residuals. Also, we use non constant variance test to verify it. Furthermore, we check leverage and influence points as well as outliers as well as determined cook distance for influential points. By taking box cox transformation and weights, we also introduce WLS technique to fit the model for better results and did all type of important analysis to understand the energy efficiency. Finally, we show 5-fold cross validation to verify our model.

We present a class of efficient parametric closure models for 1D stochastic Burgers equations. Casting it as statistical learning of the flow map, we derive the parametric form by representing the unresolved high wavenumber Fourier modes as functionals of the resolved variables’ trajectory. The reduced models are nonlinear autoregression (NAR) time series models, with coefficients estimated from data by least squares. The NAR models can accurately reproduce the energy spectrum, the invariant densities, and the autocorrelations. Taking advantage of the simplicity of the NAR models, we investigate maximal and optimal space-time reduction. Reduction in space dimension is unlimited, and NAR models with two Fourier modes can perform well. The NAR model’s stability limits time reduction, with a maximal time step smaller than that of the K-mode Galerkin system. We report a potential criterion for optimal space-time reduction: the NAR models achieve minimal relative error in the energy spectrum at the time step where the K-mode Galerkin system’s mean CFL number agrees with the full model’s.

Recently, there has been, on the one hand, an increase in the complexity of digital device designs and, on the other hand, an increase in the requirements for the development time and the reliability of the designs. One of the directions of solving this problem is developing new techniques for designing digital devices.This paper proposes a new technique for designing digital devices based on finite state machines with datapath (FSMD), when the functioning of the device is described in the form of an algorithm state machine with datapath (ASMD) charts. The new technique is called ASMD-FSMD. Different digital device design techniques are compared to each other using design examples of a synchronous multiplier on field programmable gate array (FPGA). The efficiency of the ASMD-FSMD technique compared to the traditional approach in terms of area and performance was investigated. The ASMD-FSMD technique, compared to the traditional one, reduces the area from 28.6% to 39.7% and increases the speed for some designs to 17.6%. In addition, using the ASMD-FSMD technique significantly reduces design time and increases design reliability. In conclusion, recommendations for using the ASMD-FSMD technique are made.

An equilibrium problem of the Kirchhoff-Love plate containing a nonhomogeneous inclusion is considered. It is assumed that elastic properties of the inclusion depend on a small parameter characterizing width of the inclusion $\varepsilon$ as $\varepsilon^N$ with $N<1$. The passage to the limit as the parameter $\varepsilon$ tends to zero is justified, and an asymptotic model of a plate containing a thin inhomogeneous hard inclusion is constructed. It is shown that there exists two types of thin inclusions: rigid inclusion ($N<-1$) and elastic inclusion ($N=-1$). The inhomogeneity disappears in the case of $N\in (-1,1)$.

The knowledge of human body proportion and segmental properties of limbs, head and trunk are of fundamental importance in biomechanical research. As many methods are employed, it is important to know which they are currently available, which data on human body masses, lengths, center of mass (COM) location, weights and moment of inertia are available and which methods are most suitable for a specific research purposes. The present review examines the literature concerning human body segments properties for biomechanical purposes. It emerges that data obtained in studies on cadaveric specimens are still the most accurate, whilst technological tools currently available are manifolds, each one with proper advantages and disadvantages. Classical studies were focused mainly on white men, while in recent year the available data of body segments has been extended to children, woman, and other races. Also, data on special population (obese, pregnant women) are starting to appear in the scientific literature.

Relationship between caveman prehistoric life in terms of heat induced food processing and its geological ecosystems have received many attentions. Previous studies have investigated the sources of heat included using Fourier transform infrared spectroscopy and biomarker approaches. Here this study proposes the use of remote sensing to identify the relationship of 9500 year old (9.5 ka) prehistoric mongoloid occupancy with hydrothermal manifestations at Pawon cave of West Java. The hydrothermal manifestations around Pawon cave were identified using Landsat 8 band combinations, land surface temperature, and sedimentary lithology. The results showed the hydrothermal manifestations surrounding Pawon cave were within a distance of 0.5-2 km. The results also showed bones representing 12 animal taxon groups with high abundance of rodents. To conclude this study sheds the light of proximity and preferences of mongoloid prehistoric occupancy towards hydrothermal landscape due to its advantage as heat sources for food processing purposes.

The business planning process can be considered as a strategic phase of any business. Given that the business plan is a management accounting tool, there are countless approaches that can be adopted to prepare it since there is no legal requirement, as opposed to obligations relating to financial accounting. However, in general, every business plan consists of a numerical part (budget) and a narrative part. In this research, the author highlights, on the basis of experiences and commonly used theories, a standard process that can be adaptable to the business plan of any type of activity. The use of big data is highlighted as an essential part of feeding the data of almost all the steps of the budget. The author then manages to determine a generally applicable standard process, indicating all the data necessary to prepare an accurate and reliable business plan. A case study will provide adequate support to the demonstration of the immediate applicability of the proposed model.

Together with display and input, storage and processing are requisite to computing. While storage technologies have improved tremendously in capacity and speed over the years, the basic principles enabling information storage into digital 1 and 0 remains the same: induction of phase change in the storage substrate. But recently, there has been much research into structural phase change material (SPCM) and exploration of its possible use in various types of memory storage applications. Despite unconventional use of structural change between amorphous and crystalline state as well as that between crystal structures for encoding information, key barriers for its widespread use remains access speed, capacity to cost ratio, and fidelity of storage. Hence, given the performance requirement of SPCM for memory applications, what are the material and design considerations that feed into translating a promising application into a practical reality? Given the important role of kinetic and thermal energy in structural organization of a phase change material, precise characterization of structural change in the material with external physical factors such as heat, voltage and current, is critical for storage material design. Next comes the precision at which individual memory cells for storing single bits of information could be defined reproducibly and at high fidelity using SPCM. In congruent with memory cell definition lies the equally important aspect of constraining the field characteristics used in modulating the phase state of the memory medium. Specifically, while heat is useful for mediating the “melting” of a crystalline material into its amorphous state, heat conduction is less useful for transferring the “switch command” from the effector to the memory material. More importantly, choice of structural phase change material for memory applications likely revolves around those where individual memory cells could be defined in a cross array format, which is amenable to high density information storage. Durability and fidelity of information storage are additional factors of design that favours selection of SPCM with phase change occurring at narrow operating windows without hysteresis over extended cycling. But, the most important requirement is speed of access. To this end, energetic cost of phase transitions might affect operation of the phase change memory at the system level: for example, usage of large current for high energy transition step may impact on device durability. Ultimately, there is a fundamental limit on the number of reproducible phase transitions in a SPCM before fidelity of information storage is no longer guaranteed. Hence, what are the drivers for uptake of phase change memories in consumer devices? Performance gains must be realized in access speed, storage capacity, form factor, and fidelity of information storage for practical application of structural phase change memories.

The small satellite market continues to grow year after year. A compound annual growth rate of 17% is estimated during the period between 2020 and 2025. Low-cost satellites can send a vast amount of images to be post-processed at the ground to improve the quality and extract detailed information. In this domain lies the resolution enhancement task, where a low-resolution image is converted to a higher resolution automatically. Deep learning approaches to Super-Resolution (SR) reached the state-of-the-art in multiple benchmarks; however, most of them were studied in a single-frame fashion. With satellite imagery, multi-frame images can be obtained at different conditions giving the possibility to add more information per image and improve the final analysis. In this context, we developed and applied to the PROBA-V dataset of multi-frame satellite images a model that recently topped the European Space Agency’s Multi-frame Super Resolution (MFSR) competition. The model is based on proven methods that worked on 2D images tweaked to work on 3D: the Wide Activation Super Resolution (WDSR) family. We show that with a simple 3D CNN residual architecture with WDSR blocks and a frame permutation technique as data augmentation better scores can be achieved than with more complex models. Moreover, the model requires few hardware resources, both for training and evaluation, so it can be applied directly from a personal laptop.

Aim: Despite the endemic nature of contagious ecthyma in Nigeria, there is limited report on the molecular characterization of the isolates responsible for disease outbreaks. The aim of this study was to molecularly characterize ORFV isolated from clinical infections in goats in Sokoto metropolis. Materials and Methods: Seronegative embryonated chicken eggs were used to isolate ORFV via the chorio allantoic membrane (CAM) route according to the established protocol. Viral DNA was extracted from infected CAM and the full coding region of B2L gene was amplified by PCR and subsequently sequenced by Sanger’s method. The nucleotide sequence results were blasted for identification and phylogenetically analyzed using MEGA and Bioedit softwares. Results and Discussion: The results showed that B2L gene sequences of the ORFV UDUS/01/19/More strain showed slight variability (96- 98.7%) with the reference sequences. Our isolate clustered within the same clade with Korean strain signifying a close genetic relationship. Unique amino acid substitutions were noted in our isolate when compared with other references. This is arguably the first genetic characterisation of B2L gene of ORFV circulating in Nigeria. Conclusion: Our study has provided in sight into the genetic diversity of ORFV in the study area. This is crucial for the design of effective vaccines against the disease which are currently lacking in the country.

The concept of sustainability and sustainable development, especially systemic sustainable development, still raises controversy in literature. The article makes an attempt to re-examine these concepts from a systems perspective, seeking foundations and applications in the selected sector. It is becoming increasingly clear that sustainability and sustainable development are aimed at integrated economic, social, cultural, political, and ecological factors [1[,[2] (pp.641-642). This causes that the constructive approach to the issue is required, taking into account all the actors, areas and dimensions involved in the pursuit of systemic sustainable development. As a result, both local and global dimensions and the way they interact must be explored in a multi-faceted manner in order to offer a perspective more useful than other analytical approaches, because the systems view is a way of thinking in terms of connectedness, relationships, and context [3]. The article aims to review selected publications and studies so as to form the general idea of systemic sustainable development and define the systemic development of sustainable transport, including in particular the perspective of the actors of the sector, transport providers (passenger, urban) and transport development program, implemented both by local governments and on the European scale. An attempt was made to identify elements of the systemic sustainable development model, setting it in the reality of the following subcategories: “Society”, “Economy” and “Environment” in sectoral terms. It is supposed that, systemic sustainable development is a conglomerate of public administration entities, companies operating in the sector, individual and corporate customers, acting in certain conditions for economic, social and environmental well-being, and a number of their initiatives of major or minor significance, grouped in six sub-areas, undertaken to achieve systemic value in the examined sector, with a positive or negative business/economic, social and environmental impact.

In the late Pleistocene, a prehistoric hippo species was distributed from Africa to the Asia including Pakistan, India, and Java island. This study aims to model habitat suitability of Asian hippo known as a Hippopotamus sivalensis spp. in east Java. The measured parameters included the fossil locality, vegetation cover, elevation, and distance to the river in a forest river basin sizing 6652 Ha. Those parameters using GIS were weighted, overlaid, and interpolated to determine the most suitable habitats. The model projected that the suitable habitats of H. sivalensis spp. were in the central of the basin near the river. The largest suitable habitats were located in the eastern parts of basin which were dominated by forests

In this paper, we study the global asymptotically stability of following system of difference equations with quadratic terms: x_{n+1}=A+B((y_{n})/(y_{n-1}²)),y_{n+1}=A+B((x_{n})/(x_{n-1}²)) where A and B are positive numbers and the initial values are positive numbers. We also investigate the rate of convergence and oscillation behaviour of the solutions of related system.

In this paper, we introduce a new type of degenerate poly-Fubini polynomials and numbers, are called degenerate poly-Fubini polynomials and numbers, by using the degenerate polylogarithm function and derive several properties on the degenerate poly-Fubini polynomials and numbers. In the last section, we also consider the degenerate unipoly-Fubini polynomials attached to an arithmetic function, by using the degenerate polylogarithm function and investigate some identities of those polynomials. In particular, we give some new explicit expressions and identities of degenerate unipoly polynomials related to special numbers and polynomials.