The Singularity of nature

The holism of evolution as consciousness

Quantum Entanglement has been hypothesized to mediate non-local consciousness, underlying which, empirically, is the force of gravity. Upon further reflection, the case can be made for 'the breath' as the physiologic trait that binds all of these properties together, offering further opportunity for hypothesis testing experimentation. Humans have inexplicably made extraordinary intellectual and technical advances within a relatively very short period of time, referred to as the 'great leap forward'. It would be of great value if we could identify how and why we have evolved so rapidly. There is a holotropism that begins with the Big Bang that is centered on the homeostatic control of energy, perpetually referencing the First Principles of Physiology. "The Breath" is how and why our physiology has managed to perpetuate our species, and perhaps why the lung has been 'over-engineered' in order to facilitate the role of breathing in consciousness.

A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset

BACKGROUND

Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable.

RESULTS

Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a "subpopulation aware" 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq).

CONCLUSIONS

This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment.

Ontogeny, phylogeny and cellular energy flows for evolution

The case has previously been made for the 'Singularity of Nature" based on homologies between the inorganic and the organic. But a causal explanation for those homologies was not provided. The following is a hypothetical way to understand how and why physiology emerged from physics, providing a predictive model for cell-molecular evolution.

Systems biology of human aging: A Fibonacci time series model

Fractals are everywhere in nature, particularly at the interfaces where matter or energy must be transferred, since they maximize surface area while minimizing energy losses. Temporal fractals have been well studied at micro scales in human biology, but have received comparatively little attention at broader macro scales. In this paper, we describe a fractal time series model of human aging from a systems biology perspective. This model examines how intrinsic aging rates are shaped by entropy and Fibonacci fractal dynamics, with implications for the emergence of key life cycle traits. This proposition is supported by research findings. The finding of an intrinsic aging rate rooted in Fibonacci fractal dynamics represents a new predictive paradigm in evolutionary biology.

The holism of cosmology and consciousness

The greatest unsolved mystery of all is what consciousness is. Torday and Miller have hypothesized that consciousness is the homologous 'equivalent' of our physiology, behaving as our history, providing an algorithm by which evolution can determine how and why to adapt to ever-changing environmental conditions. Complicated physiology was reduced iteratively to the unicell by tracing the cell-cell signaling mechanisms that dealt with emergent threats based on Bayesian statistics. Unlike Darwinian random mutations, the current approach is predicated on structural and functional changes within the context of pre-existing physiologic traits. The cytoskeleton of the cell is a complete representation for all of the phases of life, past, present and future, controlling the Target of Rapamycin gene, which determines all of the stages of life-homeostasis, meiosis and mitosis. Viewed from this perspective, the cell remains at equipoise relative to the Singularity that existed before the Big Bang. The purpose of life is to collect epigenetic marks by pursuing energy flows, not conventional material change due to random mutations. The cytoskeleton universally controls all of the states of the cell - homeostasis, meiosis and mitosis, rendering the status of the cell relative to the prevailing circumstances. Indeed, the cytoskeleton of the cell is a central player in all of the phases of life, past, present and future. The above-described integration of physiology as the cipher for consciousness is quite ingenious as a 'top-down/bottom-up/middle-out' way of ensuring the holism of life and non-life. Recognition of the centrality of the cell has led to a number of novel insights into biology that have been represented by dogma up until now. Consequently, biology has been simplified by shifting from description to mechanism. Based on Ockam's Razor, the cellular approach to evolution is superior to Darwin.

Consciousness, embodied Quantum Entanglement

We have systematically misconstrued the nature of consciousness by overlooking our own physiology as that awareness. The following is a way to rectify this error through a deep understanding of what life 'means' in order to further advance our knowledge of who and what we are. The evolution of consciousness from the cell membrane to physiology is revealed by the effect of microgravity on phenotypic identity, revealing the two levels of consciousness experimentally. As does the classic Double-Slit experiment, exposing the dual way in which consciousness functions as both the day-to-day of the cell membrane and the transcendent property of our physiology.

The electron as a self-organising entity in physics and biology

A characteristic of living systems is their ability to self-organize. Using appropriate quantum mechanical and mathematical tools, we show that this ability may also be a characteristic of non-living systems, such as the electron, thus establishing an unsuspected relationship between biology and physics, whereby "biology precedes physics". Planck's constant h is not a pure number but an elementary quantum of action, a "real atom" according to Henri Poincaré. Consequently, Louis de Broglie's equation λ = h/p must be rewritten in the form h = λp or lp. This approach gives a new meaning to quantum physics: the precise equivalence lp = h = Ed combined with the conceptual tools of Laurent Nottale's scale relativity allows the reunification of physics and support the development of promising engineering applications, notably in systems biology and medicine.

Evolution, gravity, and the topology of consciousness

It has previously been hypothesized that consciousness is the aggregate of our evolutionary history, forged by ontogeny and phylogeny via cell-cell communications. In an on-going effort to identify the serial pre-adaptations that gave rise to consciousness, certain fundamental properties of the emerging cell are addressed herein. Evolution is topologic because it began as a phase transition caused by gravity attracting lipid molecules, spontaneously forming micelles submersed in the ocean that covered the primordial Earth, forming a surface boundary between the exterior Cosmos and the interior of micelles. Such protocells comply with the First Principles of Physiology-negative entropy, chemiosmosis and homeostasis-the first two principles being deterministic, the last being probabilistic, bestowing them with far more than just random chance. The mechanism of cellular evolution is based on exaptations of sequentially earlier and earlier genetic traits, working in reverse from present-day physiology all the way back to the unicellular state, which is homologous with mathematical 'knots'. Ironically, that relationship is evidence for the ontologic and epistemologic primacy of the cell, which supersedes mathematics and physics as manifestations of the Implicate Order since a conscious cell can conceive of a circle, but an unconscious circle is not able to conceive of a cell.

Cybernetics as a conversation with the Cosmos

Norbert Wiener was the first to functionally define cybernetics as "the study of control and communication in the animal and the machine". Herein, it is shown that as a manifestation of physiology, cybernetics can be further reduced to cell-cell signaling to maintain homeostasis, bridging Newtonian 3rd Order Cybernetics with Quantum Mechanical 4th Order Cybernetics as our 'conversation with the Cosmos' based on Quantum Entanglement, constrained by non-localization. As such, cybernetics can be scientifically tested in toto from the functional to the metaphysical, rendered physical as communication for the first time. If that is correct, then the sooner we begin operating based on Quantum Mechanical principles, the sooner we will function based on predictive algorithms.

Is Consciousness First in Virtual Reality?

The prevailing scientific paradigm is that matter is primary and everything, including consciousness can be derived from the laws governing matter. Although the scientific explanation of consciousness on these lines has not been realized, in this view it is only a matter of time before consciousness will be explained through neurobiological activity in the brain, and nothing else. There is an alternative view that holds that it is fundamentally impossible to explain how subjectivity can arise solely out of material processes-"the hard problem of consciousness"-and instead consciousness should be regarded in itself as a primary force in nature. This view attempts to derive, for example, the laws of physics from models of consciousness, instead of the other way around. While as scientists we can understand and have an intuition for the first paradigm, it is very difficult to understand what "consciousness is primary" might mean since it has no intuitive scientific grounding. Here we show that worlds experienced through virtual reality (VR) are such that consciousness is a first order phenomenon. We discuss the Interface Theory of Perception which claims that in physical reality perceptions are not veridical and that we do not see the "truth" but that perception is based on evolutionary payoffs. We show that this theory may provide an accurate description of perception and consciousness within VR, and we put forward an experimental study that could throw light on this. We conclude that VR does offer an experimental frame that provides intuition with respect to the idea that "consciousness is first" and what this might mean regarding the perceived world. However, we do not draw any conclusions about the veracity of this notion with respect to physical reality or question the emergence of consciousness from brain function.

Approaching biology through the retrocausal apex in physics

Quantum stochasticity carries two incompatible implications. One is for the statistical divergence upon the prior absence of complete controllability over boundary conditions applied to mechanistic causation. One more alternative is for the statistical convergence upon the posterior decidability of measurement despite the absence of the prior decidability. Decidable measurement lacking the prior decidability is retrocausal. The quantum physical likelihood for the life world may derive from the statistical convergence proceeding in a durable manner. This observation suggests that there must have been some type of observers even internal to the lifeless world, otherwise no likelihood of identifying the objects of interest could be available there. Measurement activity intrinsic to the internal observers is indexical, while the similar activity specific to the external observer like us can be symbolic. The difference is in the phenomenological qualification since both are the observers of different types. A most conspicuous case demonstrating the phenomenological difference is revealed in the different nature of time to be employed and experienced there. Time serves as a principal attribute qualifying the phenomenon to be experienced as such. Qualification of time is observer dependent.

Lifting the veil on Bohm's holomovement

In this paper, we argue that Bohm’s unbroken and undivided totality he called the holomovement, the title he gave to the concept of the self-organizing universe, is more coherently understood when viewed as universal consciousness. Bohm’s understanding of consciousness oscillates around being a quality of local minds and the interconnected totality of the holomovement. We suggest such equivocations impose limitations on Bohm’s general holistic framework because they import into his model the limiting restrictions of Cartesian separation and are, therefore, incongruous for use within his holistic model of the holomovement. We also argue that the term ‘meaning’ has a structural and functional agency appropriate to Bohm’s model of the holomovement, while also reflecting the living characteristics of this organic totality that is full of meaning.

Life is a mobius strip

If you cut a mobius strip in half, the edges form a Trefoil Knot, which can be untied to form a circle, proving it's a true mathematical knot. The cell is a homologue of the mathematical knot since it, too, must be able to unknot itself to form the egg and sperm meiotically in order to reproduce. The homology between a knot and a cell is thought-provoking biologically because the Trefoil Knot is a metaphor for the endoderm, ectoderm and mesoderm, the three germ layers of the gastrula that ultimately produce the embryo, beginning with the zygote. Upon further consideration, the cell membrane is like a mobius strip, forming one continuous surface between the inner environment of the cell and the outer environment. However, it is not formed by taking a circular surface, cutting it, twisting it and attaching the two ends as you would conventionally to form a mobius strip. Conversely, David Bohm's Explicate Order forms a boundary with the Implicate Order. That lipid boundary is the prima facie mobius strip that divides the infinite surface of the Implicate Order into inside and outside by 'recalling' its pre-adapted state as lipid molecules before there was an inside or outside.

Cellular evolution as the flow of energy

In contrast to Darwinian evolution, which is founded on the material competition between organisms, cellular epigenetic evolution focuses on cell-cell communication of data from one stage of life to another-developmentally, phylogenetically, as injury-repair - ultimately governed by the First Principles of Physiology. By merging ontogeny and phylogeny, since both are based on cell-cell communication mediated by soluble growth factors and their receptors, evolution complies as one holistic, unified process. As such, the material aspects of the organism can be seen as 'means' instead of 'ends', begging the question as to just what the 'ends' of evolution are ? Once the superficial material aspect of lifeforms is eliminated, only the flow of energy is left, within and between generations. Contemporary biology and physics are at a critical phase, unable to reduce their problems to practice. A paradigm shift to evolution as energy flow is proposed as the solution.

Cellular evolution of language

The evolutionary origin of language remains unknown despite many efforts to determine the origin of this signature human trait. Based on epigenetic inheritance, the current article hypothesizes that language evolved from cell-cell communication as the basis for generating structure and function embryologically and phylogenetically, as did all physiologic traits. Beginning with lipids forming the first micelle, a vertical integration of the evolved properties of the cell, from multicellular organisms to the introduction of cholesterol into the cell membrane, to the evolution of the peroxisome, the water-land transition and duplication of the βAdrenergic Receptor, the evolution of endothermy, leading to bipedalism, freeing the forelimbs for toolmaking and language, selection pressure for myelinization of the central nervous system to facilitate calcium flux, bespeaks human expression, culminating in the evolution of civilization. This process is epitomized by the Area of Broca as the structural-functional site for both motor control and language formation. The mechanistic interrelationship between motor control and language formation is underscored by the role of FoxP2 gene expression in both bipedalism and language. The effect of endothermy on bipedalism, freeing the forelimbs for toolmaking and language as the vertical integration from Cosmology to Physiology as the basis for language bespeaks human expression.

Cellular senomic measurements in Cognition-Based Evolution

All living entities are cognitive and dependent on ambiguous information. Any assessment of that imprecision is necessarily a measuring function. Individual cells measure information to sustain self-referential homeostatic equipoise (self-identity) in juxtaposition to the external environment. The validity of that information is improved by its collective assessment. The reception of cellular information obliges thermodynamic reactions that initiate a self-reinforcing work channel. This expresses as natural cellular engineering and niche constructions which become the complex interrelated tissue ecologies of holobionts. Multicellularity is collaborative cellular information management directed towards the optimization of information quality through its collective measured assessment. Biology and its evolution can now be re-framed as the continuous process of self-referential cellular measurement in the perpetual defense of individual cellular self-identities through the collective form.

Deep learning and regression modelling of cloudless downward longwave radiation

Background

Though downward longwave radiation (DLR) models curb the paucity of data, they are mostly location dependent. Therefore, there is a need to evaluate their relevance given the increasing use of machine learning techniques. In this study, cloudless DLR estimates from regression models and soft computing models of neural networks (NN), support vector regression (SVR) and adaptive neuro-fuzzy inference system (ANFIS) were compared. Clear days from September 1992 to August 1994 and July 1995 to March 1998 in Ilorin (8.50 °N, 4.55 °E), Nigeria were considered, while the predictors for the models were water vapour pressure, e and air temperature, T.

Results

A new regression model in relation to the Boltzmann constant, σ: $$ \left(1.014\left(\frac{1.0\times {10}^{30}\times e}{T^{13}}\right)+0.699\right)\sigma {T}^4 $$1.0141.0×1030×eT13+0.699σT4, was better than other regression models and applicable at another location. Between 1 and 8, the sixth degree was the best polynomial kernel function in SVR models’ estimations of cloudless DLR. Though the new regression model was comparable to expert systems, ANFIS was still the best model due to its consistent high correlations and lowest estimation errors.

Conclusions

Experience-based computational procedures that combine enough logics with neural networks respond effectively to other data. Furthermore, the analytical relationship between water vapour pressure and air temperature in DLR’s mechanism should be redefined accordingly, while the sixth polynomial should be used as the default setting in SVR systems.