The formation of rock fractures in nature has a certain relationship with water seepage. In order to analyze the shape of rock fracture, we propose a rock deformation theoretical model in three-dimensional space considering with the condition of seepage water pressure, and establish the mass conservation equation, seepage equation, surrounding rock displacement equation, so as to deduce the rock deformation control equation under seepage pressure action. The numerical analysis of the nonlinear quadratic partial differential equation obtains the fracture deformation distribution in the example, and verifies with the calculated fracture morphology. And we further use this principle to analyze the fracture morphology in nature and prove the rationality of the theory.

ATP Synthase is an essential molecule in cell and molecular biology. It is responsible for the production of ATP during cellular respiration, a molecule that provides the energy required to drive a number of cellular processes. In this paper, I explore the rotational physics of ATP Synthase’s rotor, a part of the protein that spins during the production of ATP. Firstly, I discuss some elementary rotational kinematics of the rotor. I then derive two alternate formulations for the total linear acceleration of the rotor. Finally, I derive formulas for the moment of inertia, angular momentum, net torque, and kinetic energy of the rotor. Through this, I hope to provide a theoretical and mathematical insight into the mechanics of ATP Synthase during the production of ATP.

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

Considering the important demand of fresh water and its scarce availability, water desalination is an interesting technology, producing about 44 Mm³/year worldwide, but, in general the most common desalination techniques are highly energy demanding. Freezing-Melting (F/M) desalination uses just up to 70% less thermal energy, but is the least used process mainly, due to the difficulty of the salt separation. This study proposes a model able to analyses the thermodynamic potential that allows the salt diffusion during the F/M process, using an aqueous solution of sodium chloride. This should allow to obtain a sensitive analysis of the process to promote the separation between the high concentration brine and the ice with liquid separation by physical process. The unidimensional model is based on the evolution of both processes: thermal and mass diffusions, depending on temperature and saline gradients, predicting whether the salt will remain inside the ice or not. Thus, the thermal potential is adjusted to frozen only when the salt has been "pushed" towards the brine. Mostly models have base their results on the assumption of a “certain value of saline concentration of the liquid fraction”, value in which there is great disagreement. In this paper the calculations are based on the concentration in the solid-liquid interface, which has been extensively studied and there is a coincidence in those results, being the main advantage of the proposed model.

The energy efficiency of ice hockey arenas is a central concern for the administrations, as these buildings are well known to consume a large amount of energy. Since they are composite, complex systems, solutions to such a problem can be approached from many different areas, from managerial to technological to more strictly physical. In this paper we consider heat transfer processes in an ice hockey hall, during operating conditions, with a bottom-up approach based upon on-site measurements. Detailed heat flux, relative humidity and temperature data for the ice pad and the indoor air are used for a heat balance calculation in the steady-state regime, which quantifies the impact of each single heat source. We then solve the heat conduction equation for the ice pad in transient regime, and obtain a generic analytical formula for the temperature profile that can be used in practical applications. We then apply this formula to the resurfacing process for validation, and find good agreement with an analogous numerical solution. Since it is given with implicit initial condition and boundary conditions, it can be used not only in ice hockey halls, but in a large variety of engineering applications.

In order to meet the military requirements of the fuze, such as precision strike, efficient mutilates ability and low collateral damages, the microminiaturization is an inevitable trend of secure system. Based on the silicon-based MEMS S&A device designed by our term, the design principles of each module and fabrication process are introduced. The average fracture strength and Young's modulus of the silicon are 726 MPa and 175 GPa from the tensile test, respectively. From Hopkinson impact experiment, we can get the threshold-value judging mechanism being safety under the impact overload of 20526 g, and this value is much more than the standard of the drop overload 12000g; the arming value under the centrifugal overload obtained from theory, simulation and experiment is at the range of 28200 g and 32000 g, it shows that the threshold-value judging mechanism can be arming compared with the value 35951g of design principle. Therefore, the threshold-value judging mechanism can meet the design requirements of overload. Furthermore, the relationship of fracture threshold-values obtained by different theories is found out through parametric design method, as shown in Figure 14, it provides the theory evidence to the follow parametric design.

X-ray crystallographic and theoretical charge density data for a series of compounds [(Co(Ts3tren))M(Co(Ts3tren))] (M = Mg, Ca, Sr and Ba) is examined. The crystal structures are isostructural and the alkaline earth metal ions have the same arrangement of donor oxygen atoms despite the large variation in ionic radii. The isomorphism of these molecules is surprising and a theoretical examination of the electronic structures, with the different metal ions along the series, provides detailed insight into their stabilities. The theoretical and experimental data are consistent and agree well. The local properties of the Co(II) ion and its donor atoms are relatively independent of the alkali earth metal.

Counting in terms of cycles allows modeling many processes of Nature. We make use of a slight numerical incongruence within the numbering system to find a translational mechanism which connects sequential ↔ commutative properties of assemblies. The algorithms allow picturing the logical syntax Nature uses when reading the DNA. Ordering a collection on two different properties of its members will impose two differing sequences on the members. The coordinates of a point on a plane of which the axes are the two sorting orders sidestep the logical contradiction arising from the different linear assignments. During a reorder, elements aggregate into cycles. Using an etalon collection of simple logical symbols (which are pairs of natural numbers), which we reorder, we see typical movement patterns along the path of the string of elements that are members of the same cycle. We split the {value, position} descriptions of a natural number and observe the places the unit occupies at specific instances of time among its peers, while being a member of a cycle, under different orders prevailing. Which places elements occupy among their peers, under specific order conditions, is determined by numeric properties of the natural numbers that make up the element. The model presented is therefore tautologic, and can be compared to a hybrid of sudokus with the ultimate form of Rubik‘s cube. It is necessary for the reader to do some self-education on the matter of cycles as a prerequisite to understanding the working principle of the model. The contraption being a new development, it can’t have references in literature.One cannot lose a bet on the idea that sorting and ordering a collection of elementary logical elements will turn up typical patterns and that these archetypes of patterns will be of interest to Theoretical Physics, Chemistry, Biology, Information Theory, and some other fields, too.

We report on the state of the art of research on proteins recognized as potential targets for the development of Leishmania treatments and the search of active chemical species. We have reviewed information from experimental in vitro, in vivo, or in silico sources. We classify the gathered information on: a) vector taxonomy and geographical distribution, b) parasite taxonomy, geographical distribution, c) enzymatic function of proteins related to the parasite/host in any of its development states, id. est., oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases and cytokines, and d) information on standard and non-standard treatments from bioactive chemical species. Our aim is to provide a much needed reference layout for research efforts aimed to understand the interaction mechanisms of ligand-protein activation/inactivation processes, specifically related to Leishmania, thus, we focus on enzymes known to be part of the biochemical molecular pathways initiated following a Leishmania infectious episode.

Featured Application: Bio-electronic devices take advantages of some specific duties of biological matter. The specific ability of some proteins to use sunlight is considered for the realization of photo-electronic devices . Here the focus is on the role of the pH, whose variations seem to affect the protein conductance

In cotton cultivars, an insect that causes irreversible damage is the Spodoptera frugiperda, known as the fall armyworm. Since the visual detection of plants is a burdensome task for human inspection, the spectral information related to plant damage, registered on a spectral scale, can be useful. These measurements, associated with machine learning techniques, produce useful information for a rapid and non-invasive inspection method development. To contribute to this gap fulfillment, this paper proposes a machine learning framework to model the spectral response of cotton plants under the attack of the fall armyworm. Additionally, a theoretical model is presented, built from the results of the machine learning analysis, to infer this damage with up-to-date orbital sensors. The data was composed of the reflectance measurements collected at a cotton field with control plants and plants submitted to Spodoptera frugiperda damage. Their spectral response was recorded with a hand-held spectroradiometer ranging from 350 to 2,500 nm, for eight consecutive days. Different machine learning models were evaluated and the overall best model was defined by accuracies comparisons on a testing-set. A ranking approach was adopted based on the model accuracy, returning the most contributive wavelengths for the classification. Sequentially, an unsupervised neural network (Self-Organizing Map - SOM) was implemented to reduce data-dimensionality and assist in the definition of important spectral regions. The regions were associated with the spectral bands of the two sensors (OLI and MSI) and a theoretical model using a band simulation process with the overall best machine learning model was proposed. The results indicated that the Random Forest (RF) algorithm is the most suitable to predict cotton-plants damaged by insects and that the last day of analysis (8th day) was better to separate it, with F-measure equals 0.912. The ranking approach combined with the SOM method indicated the spectral regions at the red to near-infrared (650 to 1,350 nm) and shortwave infrared (1,570 to 1,640 nm) as the most important regions to the analysis. The proposed theoretical model simulated with the OLI and MSI sensor-bands returned an F-Measure of 0.865 and 0.886, respectively. In conclusion, this framework can be used to map cotton-plants under insect-attack. The theoretical model presents high accuracy to infer the insect-damaged on cotton plants based on multispectral bands from other sensors, being a useful tool for future research that intends to evaluate it in other areas and at different field scales.

In recent years, advances in science, technology, and the way in which we view our world have led to anincreasingly broad use of the term “intelligence”. As we learn more about biological systems, we find more and more examples of complex and precise adaptive behavior in animals and plants. Similarly, as we build more complex computational systems, we recognize the emergence of highly sophisticated structures capable of solving increasingly complex problems. These behaviors show characteristics in common with the sort of complex behaviors and learning capabilities we find in humans, and therefore it is common to see them referred to as “intelligent”. These analogies are problematic as the term "intelligence" is inextricably associated with human-like capabilities. While these issues have been discussed by leading researchers of AI and renowned psychologists and biologists highlighting the commonalities and differences between AI and biological intelligence, there have been few rigorous attempts to create an interdisciplinary approach to the modern problem of intelligence. This article proposes a comparative framework to discuss what we call “purposeful behavior”, a characteristic shared by systems capable of gathering and processing information from their surroundings and modifying their actions in order to fulfill a series of implicit or explicit goals. Our aim is twofold: on the one hand, the term purposeful behavior allows us to describe the behavior of these systems without using the term "intelligence", avoiding the comparison with human capabilities. On the other hand, we hope that our framework encourages interdisciplinary discussion to help advance our understanding of the relationships among different systems and their capabilities.

Chiroptical responses have been an essential tool over the last decades for chemical structural elucidation due to their exceptional sensitivity to geometry and intermolecular interactions. In recent times, there has been an increasing interest for the search of more efficient sensing by the rational design of tailored chiroptical systems. In this Review article, advances on chiroptical systems towards their implementation in sensing applications are summarized. Strategies to generate chiroptical responses are illustrated. Theoretical approaches to assist in the design of these systems are discussed. Development of efficient chiroptical reporters in different states of matter, essential for the implementation in sensing devises, is reviewed. In the last part, remarkable examples of chiroptical sensing applications are highlighted.

The corrosion inhibition performance of pyridine derivatives (4-methylpyridine and its quaternary ammonium salts) and sulfur-containing compounds (thiourea and mercaptoethanol) with different molar ratios on carbon steel in CO2-saturated 3.5 wt.% NaCl solution was investigated by weight loss, potentiodynamic polarization, electrochemical impedance spectroscopy and scanning electron microscopy. The synergistic corrosion inhibition mechanism of mixed inhibitors was elucidated by the theoretical calculation and simulation. The molecule of pyridine derivatives compound with larger volume has the priority to adsorb on the metal surface, while the molecules of sulfur-containing compounds with smaller volume fill in vacancies. A dense adsorption film would be formed when 4-PQ and sulfur-containing compounds are added at a proper mole ratio.

The coal mine underground reservoir is an appropriate solution between coal mining and groundwater resource protection and utilization. By calculating the storage capacity of a groundwater reservoir, the storage coefficient has been proved to be always an empirical value. Based on the mathematical derivation of the vertical fracture area ratio and the horizontal fracture area rate of the collapse zone and the fissure zone in the goaf area of the coal seam, the mathematical models of tem are derived, and the model for calculating the water storage coefficient is derived. The water storage coefficient derived from the theoretical model had more basis and more advanced than the traditional empirical value. By using this method, the practical calculation of No.1 underground reservoir of the DaLliuta Coalmine in Shenhua Shendong, has got a perfect matching with the actual groundwater storage capacity.

The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or combination methods, based on the way they derive the similarity matrix, and investigates whether there a theoretical limit exists for combination methods. We propose and prove necessary and sufficient conditions for the combination method to reach the theoretical limit. The limit theorem reveals the essence of combination method that is to estimate probability density functions of existing links and nonexistent links. Based on limit theorem, a new combination method, theoretical limit fusion (TLF) method, is proposed. Simulations and experiments on real networks demonstrated that TLF method can achieve higher prediction accuracy.

In engineering, connections between components are often weak areas. Unreasonable connection methods can easily reduce the strength of components, resulting in unpredictable failure modes. In nature, numerous connection methods for biological structures with excellent mechanical properties have evolved. Studying the connection methods of organisms in nature can inspire new ideas for bionic connection methods. When the diabolical ironclad beetle is under pressure, the elytra are not easy to separate, which ensures the stability of the beetle's external structure, thus making the beetle extremely resistant to pressure. The reason for this is the interlocking and toughening effect of the unique jigsaw connection between the elytra. Therefore, in this paper a theoretical analysis model is established and used to analyze the mechanical behavior of the diabolical ironclad beetle's jigsaw connection during the drawing process and determine the influence of factors such as quantity, angle, and geometric characteristics on the mechanical properties of the jigsaw connection. The results of the theoretical analysis are then compared with the results of experiments and ABAQUS finite element simulation.

This paper proposes a curved link-slab (CLS) structure, simplified into a hingeless-arch model, to address the current cracking phenomenon of CLS concrete. The stress formula of the hingeless arch under various loads is derived based on the classical mechanic's method. Based on an actual bridge example, the mechanical properties of CLS are analyzed under different loads and load combinations. The results show that: (1) the CLS stress is significantly lower than that of the flat link-slab structure (FLS), (2) its stress values are less than the concrete tensile limit, and (3) the CLS can effectively solve the concrete cracking phenomenon on the link-slab. The rationality of the stress formula derived from the simplified model of the hingeless arch is verified using the finite element method (FEM). The parametric sensitivity analysis shows that variation of the reinforcement ratio of the CLS has a limited impact on it. Considering both the concrete tensile and compressive limit, the thickness of the CLS should be 15 cm to 20 cm, and its design span should be about 5% to7.5% of the main beam length.

Here we use the flat Friedmann-Lemaitre-Robertson-Walker metric describing a spatially homogeneous and isotropic universe to derive the cosmological redshift distance in a way which differs from that which can be found in the astrophysical literature. We use the co-moving coordinate r_e (the subscript e indicates emission) for the place of a galaxy which is emitting photons and r_a (the subscript a indicates absorption) for the place of an observer within a different galaxy on which the photons - which were traveling thru the universe - are absorbed. Therefore the real physical distance - the way of light - is calculated by D = a(t₀) r_a - a(t_e) r_e. Here means a(t₀) the today’s (t₀) scale parameter and a(t_e) the scale parameter at the time of emission (t_e) of the photons. Nobody can doubt this real travel way of light: The photons are emitted on the co-moving coordinate place r_e and are than traveling to the co-moving coordinate place r_a. During this traveling the time is moving from t_e to t₀ (t_e ≤ t₀) and therefore the scale parameter is changing in the meantime from a(t_e) to a(t₀). Using this right way of light we calculate some relevant classical cosmological equations (effects) and compare these theoretical results with some measurements of astrophysics. As one result we get e.g. the today’s Hubble parameter H_0a ≈ 62.34 km/(s Mpc). This value is smaller than the Hubble parameter H_0,Planck ≈ 67.66 km/(s Mpc) resulting from Planck 2018 data [12] which is discussed in the literature.

The theoretical limits of water sorbate based chemical sorption heat storage are investigated in this study. First, a classification of \textit{thermochemical heat storage} is proposed based on bonding typology. Then, thermodynamics of chemical solid/gas sorption is introduced. The analysis of the reaction enthalpy from the literature indicates that this value is only slightly varying for one mole of water. Using this observation, and with the help of thermodynamical considerations, it is possible to derive conclusions on energy efficiency of closed and open heat storage systems. Whatever the salt, the main results are 1) the energy required for evaporation of water is, at least, 65% of the available energy of reaction and 2) the maximum theoretical energy efficiency of the system is about 1.8.

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.

A simple model has been used to investigate the nature of chemical order in Na-Pb and Na-Hg liquid binary alloy at 700K and 673K respectively. The energy parameter obtained from the model was used to calculate the concentration dependent mixing properties such as Gibb’s free energy of mixing, Concentration fluctuations in the long wavelength limit and the Warren-Cowley chemical short range order parameter. Results obtained showed that both alloys are hetero-coordinated throughout the entire concentration and there is tendency for segregation and demixing to take place in the liquid alloys. We observed that Na-Hg liquid alloy is more strongly interacting binary alloy and chemically ordered than Na-Pb liquid alloy.

After UV excitation, gas phase thymine returns to ground state in 5 to 7 ps, showing multiple time constants. There is no consensus on the assignment of these processes, with a dispute between models claiming that thymine is trapped either in the first (S1) or in the second (S2) excited states. In the present study, nonadiabatic dynamics simulation of thymine is performed on the basis of ADC(2) surfaces, to understand the role of dynamic electron correlation on the deactivation pathways. The results show that trapping in S2 is strongly reduced in comparison to previous simulations considering only non-dynamic electron correlation on CASSCF surfaces. The reason for the difference is traced back to the energetic cost for formation of a CO p bond in S2.

To date, no scientific study has found evidence of an afterlife, and the mechanism of consciousness is two of the most challenging questions. Here, I show a hypothesis for consciousness and the probability of an afterlife through three simple thought experiments and theoretical evidence. More studies are needed to understand the mechanism precisely. I found that consciousness can be discussed based on a new theory. Here, I hypothesize that when a person or animal dies, the selection of a new nervous system's characteristic of a new life might depend on the characteristics of the final evolved yet unknown particle. Here, I suggest that the positive or adverse evolution of the said particle depends on the natural evolution of the materialistic brain's cognition, including intelligence. The fittest intellectuals, those who have a higher potential scan mind virus, may survive happier and help more for others to improve psychological well-being. Here, I suggest that when a brain dies, the two microparticles might emit at infinite speed from the dead brain and simultaneously bond with a naturally select suitable zygote or early nervous system somewhere in the universe/s, forming a new life with the impact of new nurture.

Ecologists use the net biotic interactions among plants as a major factor to predict other ecosystem features, such as species diversity, community structure, or plant atmospheric carbon uptake. By adopting this approach, ecologists have built a giant body of theory founded on observational evidence. However, growing evidence points out that this may not be the right approach. The literature addressing the biophysical mechanisms underlying the plant interactions is much scarcer. A rising number of scientists claim the need for a mechanistic understanding of plant interactions due to the limitations that a phenomenological approach raises both in empirical and theoretical studies. Scattered studies have recently taken such a mechanistic approach, but we still lack a general theoretical framework to study mechanistically plant interactions. In this review, we first recapitulate the elementary units of plant interactions, i.e., all the known biophysical processes affected by the presence of an influencing plant and the possible phenotypic responses of plants influenced by those processes. Second, we discuss how a net interaction between two plants emerges from the simultaneous effect of these elementary units. Third, we touch upon the spatial and temporal variability of the net interaction and discuss the links between this variability and the underlying biophysical processes. We conclude by discussing how to integrate these processes into a mechanistic framework for plant interactions that must necessarily focus on the individual scale and explicitly incorporate the spatial structure of the community and environmental factors: the plant interaction models (PIM). A PIM incorporates a pair or few plants interacting with their physical environment so that the biotic interaction is not imposed but emerges from the model. This type of model can provide concise, mechanistic hypotheses to be tested empirically. This review calls for a paradigm shift in the ecology of plant interactions, from the classic species interaction study towards a more mechanistic individual-level approach. It also presents a comprehensive foundation for studying the mechanisms underpinning the net interaction between two plants.

In this part of the two-part series of essays, we first derive some equations for further physical redshift distances. We then analyze a catalog with 132,975 quasars, for which both the apparent magnitude m and the redshift z are given, in order to find the today’s value of the parameter β₀ of the theory presented. We then use this value to determine the today’s value of the radius R_0a of the Friedmann sphere using a magnitude redshift diagram of 19 SNIa. With the help of the known values of R_0a and β₀, statements about astrophysical data from the black hole in the galaxy M87 can be made. In addition, the today’s Hubble parameter H₀ results from both parameters. Furthermore, we calculate the values of the further physical redshift distances for the black hole in M87 and all 19 SNIa. The resulting parameter values are: β₀ ≈ 0.731, R_0a ≈ 2,712.48 Mpc and H₀ ≈ 65.638 km / (s ∙ Mpc). The today’s mass density of the Friedmann sphere is ρ₀ ≈ 4.843 x 10^-27 g / cm 3. For the mass of the Friedmann sphere we find M_FK ≈ 1.206 x 10⁵⁶ g. Annotation: Knowledge of the first part [1] of the series of articles is a prerequisite for understanding this article.

Aero submarines (aerosubs) are vehicles that can both fly both in air and travel under water. The concept of dual aerial and aquatic vehicles emerged in 1939 when Russian engineer Boris Ushakov proposed the “flying submarine”[1], and this was followed by further developments including RFS1 [2], convair project in 1964[3] , etc. however, to date, limited attempt has been diverted towards the advanced development of such aircraft. This is heavily influenced by challenges associated with the design and operation of the same. Based on the review of literature the authors aim to introduce a theoretical design for an aerosub (QFS-20) with a view to address the design and operation issues including power, entry to and exit from water.

Orthogonal operators can successfully be used to calculate eigenvalues and eigenvector compositions in complex spectra. Orthogonality ensures least correlation between the operators and thereby more stability in the fit, even for small interactions. The resulting eigenvectors are used to transform the pure transition matrix into realistic intermediate coupling transition probabilities. Calculated transition probabilities for close lying levels illustrate the power of the complete orthogonal operator approach.

The out-of-time-ordered correlation (OTOC) function is an important new probe in quantum field theory which is treated as a significant measure of random quantum correlations. In this paper, with the slogan "Cosmology meets Condensed Matter Physics" we demonstrate a formalism using which for the first time we compute the Cosmological OTOC during the stochastic particle production during inflation and reheating following canonical quantization technique. In this computation, two dynamical time scales are involved, out of them at one time scale the cosmological perturbation variable and for the other the canonically conjugate momentum is defined, which is the strict requirement to define time scale separated quantum operators for OTOC and perfectly consistent with the general definition of OTOC. Most importantly, using the present formalism not only one can study the quantum correlation during stochastic inflation and reheating, but also study quantum correlation for any random events in Cosmology. Next, using the late time exponential decay of cosmological OTOC with respect to the dynamical time scale of our universe which is associated with the canonically conjugate momentum operator in this formalism we study the phenomena of quantum chaos by computing the expression for {\it Lyapunov spectrum}. Further, using the well known Maldacena Shenker Stanford (MSS) bound, on Lyapunov exponent, λ≤2π/β, we propose a lower bound on the equilibrium temperature, T=1/β, at the very late time scale of the universe. On the other hand, with respect to the other time scale with which the perturbation variable is associated, we find decreasing but not exponentially decaying behaviour, which quantifies the random correlation at out-of-equilibrium. Finally, we have studied the classical limit of the OTOC to check the consistency with the large time limiting behaviour.

Animal-assisted interventions (AAI) are a unique class of complementary medical treatments that can improve a patient’s quality of life, both physically and psychologically. Part I of this two-paper systematic literature review series focused on the study methods and quantitative results of researchers in this field. We continue this in-depth review here in Part II by discussing the common theories associated with AAI in the context of cancer. Of all the factors at work in human-animal interactions, researchers explicitly cite compatible animal personality, physical touch, physical movement, distraction/entertainment, and increased human interaction as the mechanisms responsible for the positive clinical outcomes observed in AAI. In various combinations, these mechanisms group under broader theoretical frameworks that attempt to fully explain the AAI context as it relates to cancer care. The social support hypothesis and the conception of a human-animal bond are the most referenced overarching frameworks. The cognitive activation theory of stress, the science of unitary human beings, and the self-object hypothesis are also referenced. We briefly consider other relevant theories commonly noted in the human-animal interactions literature that have the potential to clarify aspects of cancer-related AAI. We also discuss the neurobiological transduction mechanisms needed to connect theoretical frameworks and their mechanisms directly to the observed clinical outcomes. To advance the field, researchers should consider overarching theories with testable hypotheses when designing studies, and use consistent terminology when reporting results. This review lays a foundation for progress towards a unified theoretical framework and for effective treatment of the whole cancer patient.

Polymer flooding is one of the most successful chemical EOR methods, and is primarily implemented to accelerate oil production by sweep improvement. However, other benefits have extended the utility of polymers. During the last decade, it has been evaluated for an increasing number of fields, both offshore and onshore. This is a consequence of improved polymer properties, which extends the use to HTHS (high temperature high salinity) conditions and of improved understanding of flow mechanisms such as for heavy oil mobilization. A key issue in understanding polymer performance is to control and predict in-situ porous medium rheology. The first part of this paper reviews recent developments in understanding polymer flow in porous medium. Especially, polymer in-situ rheology and injectivity is discussed. The second part of this paper reports polymer flow experiments using the most applied polymer for EOR processes, HPAM (partially hydrolyzed polyacrylamide). The experiments address high rate near-wellbore behavior (radial flow) as well as reservoir rate steady state flow (linear flow) and discuss differences observed in terms of flow conditions. In addition, impact of oil on polymer rheology was investigated, and compared to single-phase polymer flow in Bentheimer sandstone rock material. Presence of oil leads to a reduction in apparent viscosity.