On the NWT's rendering of Matthew 24:3

New World Translation - Parousia ("Presence") (Mt. 24:3)

Some New Testament Greek words, like modern English words, can have more than one meaning. When translating those words one must carefully determine as best as possible which meaning was intended by studying the context. It may still be impossible, at times, to be absolutely certain which meaning was intended. In cases like this it is to be expected that the translators' own understanding and interpretation will decide which meaning to use.

Many translator's understanding and interpretation of Mt. 24:3 is that when speaking of Christ's parousia, the Bible writers meant his visible, physical coming to earth. Therefore, most "orthodox" members of Christendom, want parousia to mean "coming" in all such instances. This does not make it so!

It is readily admitted by all NT Greek scholars that parousia "lit[erally means] a presence, para, with, and ousia, being" - W. E. Vine, p. 201, An Expository Dictionary of New Testament Words. No one disputes this literal meaning of parousia. Even Young's Analytical Concordance gives this as the literal meaning (" a being alongside, presence" - p. 188.)

As J. B. Rotherham (noted Bible scholar and translator of The Emphasized Bible) wrote in the appendix of his translation:

"in this edition the word parousia is uniformly rendered `presence' (`coming,' as a representative of this word, being set aside). .... The sense of `presence' is so plainly shewn by the contrast with `absence' (implied in 2 Co. x.10, and expressed in Ph. ii. 12) that the question naturally arises, - Why not always so render it? The more so, inasmuch as there is in [2 Peter 1:16] also, a peculiar fitness in our English word `presence.' This passage, it will be remembered, relates to our Lord's transformation upon the Mount. The wonderful manifestation there made was a display and sample of "presence" rather than of "coming." The Lord was already there; and being there he was transformed (cp. Mt. xvii. 2)" - p. 271. [Also cf. 2 Pet. 1:16, Young's Literal Translation; and Lattimore's translation]

In other words, context clearly demands "presence" in some instances. And, although context would allow either "presence" or "coming" in other instances, why should a translator insist on "coming" when the word in question does not even mean that in the first place? Rotherham's answer to this question was to render all uses of parousia into "presence" in his translation.

So it is the meaning "coming" that demands a clear need from context to establish its use instead of the more literal "presence"! If context clearly shows that "presence" cannot be properly used, then, and only then, we may properly consider a different meaning. (For more on this subject see The Watchtower, 15 August 1996, pp. 9-14 and Insight on the Scriptures, Vol. 2, article entitled "Presence" - also compare pp. 201 and 1271, W. E. Vine. Also compare the Ref Bible ('84) Appendix 5B on "parousia".)

Posted by Elijah Daniels 

Darwinism's apologists are yet to get the memo re:free lunches.

Evolutionary Computing: The Invisible Hand of Intelligence

Evolution News & Views 

Darwinian evolution is characterized by an utter lack of guidance; it is the "blind watchmaker" of Dawkins. It doesn't know where it's going. It doesn't know it is building a watch. It doesn't know what a watch is. There is no goal, no plan, and no target in "natural evolution." Mutations bounce around against environmental constraints, and whatever happens, happens.

William Dembski and Robert Marks have shown that no evolutionary algorithm is superior to blind search -- unless information is added from an intelligent cause, which means it is not, in the Darwinian sense, an evolutionary algorithm after all. This mathematically proven law, based on the accepted No Free Lunch Theorems, seems to be lost on the champions of evolutionary computing. Researchers keep confusing an evolutionary algorithm (a form of artificial selection) with "natural evolution."

A recent example is seen in a Review paper in Nature by Agoston Eiben and Jim Smith, "From evolutionary computation to the evolution of things," where they claim:

Analogous to natural evolution, an evolutionary algorithm can be thought of as working on two levels. At the higher level (the original problem context), phenotypes (candidate solutions) have their fitness measured. Selection mechanisms then use this measure to choose a pool of parents for each generation, anddecide which parents and offspring go forward to the next generation. At the lower level, genotypes are objects that represent phenotypes in a form that can be manipulated to produce variations (Box 1). Genotype-phenotype mapping bridges the two levels. At the genotypic level, variation operators generate new individuals (offspring) from selected parents. Mutationoperators are based on one parent (asexual reproduction) and randomly change some values. Recombination operators create offspring by combining values from the genotypes of two (or more) parents. Finally, an execution manager controls the overall functioning of the algorithm. It regulates the initialization of the first population, the execution of the selection-variation cycles, and the termination of the algorithm. It also manages the population size (typically kept constant) and other parameters affecting selection and variation. For instance, it determines the number of parents per generation, and whether mutation, recombination or both produce the offspring for a given set of parents. [Emphasis added.]

This is no analogue to natural evolution. Indicators of intelligently guided information saturate this paragraph. We see decisions, operations, choices, management, and regulation. Don't the authors recognize their error?

They know that the two processes (evolutionary computing and natural evolution) are only analogous. They produced a table that compares and contrasts the two (see Table 1, "Main differences between natural evolution and evolutionary algorithms").

It's apparent that they recognize some serious differences between computer evolution and natural evolution. For one thing, evolutionary computation is vastly simpler than the "highly complex biochemical and developmental process" that they know characterizes life. For another, the definitions of fitness, selection, mapping, and other key words in evolutionary computing are so different from those in Darwinian theory that you wonder how the comparisons convey any meaning at all.

What is entirely lost on Eiben and Smith is the most important distinction: intelligent intervention. Everything from hardware to software has been intelligently designed -- including the definition of a problem, the choice of processes and their parameters, and their recognition of what constitutes a solution. To really compare what they do with natural evolution, they would have to stand by a sterile volcano or hot spring with their hands over their eyes, ears, and mouth, and just let things happen. Then, when something happens, say, "Who cares?" That would be Darwinian evolution.

There's no question that intelligently guided "evolutionary computing" has been very successful at solving problems. Marks and Dembski can testify to that from work in their own Evolutionary Informatics Lab. It can be as successful as artificial selection in breeding. Even when random variation is involved, a little intelligent guidance can go a long way. The authors' blindness to this is evident:

Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronomical. Today, the field is entering a new phase as evolutionary algorithms that take place in hardware aredeveloped, opening up new avenues towards autonomousmachines that can adapt to their environment. We discuss how evolutionary computation compares with natural evolution and what its benefits are relative to other computing approaches, and we introduce the emerging area of artificial evolution in physical systems.

By contrast, Marks and Dembski account for the invisible hand required in evolutionary computing. The Lab's website states, "The principal theme of the lab's research is teasing apart the respective roles of internally generated and externally applied information in the performance of evolutionary systems." So yes, systems can evolve, but when they appear to solve a problem (such as generating complex specified information or reaching a sufficiently narrow predefined target), intelligence can be shown to be active. Any internally generated information is conserved or degraded by the law of Conservation of Information.

But is such an idea too "spooky" and thus outside the bounds of science? The website answers that objection:

Simply put, intelligent design, when applied to biology, seems to invoke 'spooky' forms of causation that have no place in science. Evolutionary informatics eliminates this difficulty associated with intelligent design. By looking to information theory, a well-established branch of the engineering and mathematical sciences, evolutionary informatics shows that patterns we ordinarily ascribe to intelligence, when arising from anevolutionary process, must be referred to sources of information external to that process.

What is spooky is failing to see the obvious, believing that information-rich patterns can emerge without intelligence. What is unscientific is explaining an effect without a necessary and sufficient cause, thinking you can get something from nothing.

What Marks and Dembski prove is as scientifically valid and relevant as Gödel's Incompleteness Theorem in mathematics. You can't prove a system of mathematics from within the system, and you can't derive an information-rich pattern from within the pattern. The information in a book, for instance, cannot be derived from the paper and ink used to print it. It's impossible to bootstrap a book from the bare ingredients.

Eiben and Smith, in contrast, see humans as pulling themselves up out of their own evolutionary bootstraps and taking control of evolution:

From a historical perspective, humans have had two roles in evolution. Just like any other species, humans are the product of, and are subject to, evolution. But for millennia (in fact, for about twice as long as we have used wheels) people have also actively influenced the course of evolution in other species -- by choosingwhich plants or animals should survive or mate. Thus humans have successfully exploited evolution to create improved food sources or more useful animals, even though the mechanisms involved in the transmission of traits from one generation to the next were not understood.

Question: Did humans influence, choose, exploit, create, and improve things by intelligent design? Think about that as they continue:

Historically, the scope of human influence in evolution was very limited, being restricted to interfering with selection for survival and reproduction. Influencing other components, such as thedesign of genotypes, or mutation and recombination mechanisms, was far beyond our reach. This changed with theinvention of the computer, which provided the possibility ofcreating digital worlds that are very flexible and much morecontrollable than the physical reality we live in. Together with the increased understanding of the genetic mechanisms behind evolution, this brought about the opportunity to become active masters of evolutionary processes that are fully designed and executed by human experimenters 'from above'.

So ask: Did humans interfere, influence, design, influence, create, control, understand, and take mastery of these things as an intelligent cause?

It could be argued that evolutionary algorithms are not faithful models of natural evolution (Table 1). However, they certainly are a form of evolution. As Dennett said "If you have variation, heredity, and selection, then you must get evolution".

There you go -- a proof by assertion and argument from authority. But can they really dismiss critics so easily? Artificial selection is "a form of evolution," too. What's the difference between that and natural evolution? Intelligence. The breeder makes use of natural processes to obtain the outcome that his designing mind sought. Without intelligent interference, no evolutionary algorithm would be superior to blind search.

In the early days of intelligent design, Thaxton, Bradley, and Olsen recognized the fallacy at work here: the problem of "investigator interference." In their milestone book The Mystery of Life's Origin (1984), they showed the many ways that investigators in the origin-of-life field "played a highly significant but illegitimate role in experimental success." At the end of Chapter 6, they concluded with a quote by Brooks and Shaw:

These experiments... claim abiotic synthesis for what has in fact been produced and designed by highly intelligent and very much biotic man. (p. 110)

The results would never have occurred without the investigators' help. Like puppet masters, they guide outcomes even if some randomness is thrown in. The same applies to evolutionary computing. Eiben and Smith fail to see that the "invisible hands" running the show are their own. And unless they are willing to claim their hands are unguided by any intelligence, they don't establish Darwinian evolution; they confirm intelligent design.

The best explanation for sophisticated engineering remains a skilled engineer II

Cell Vesicles Wear Sophisticated Coats
Evolution News & Views 

Envision a day when self-driving cars make driving obsolete. Now, imagine a far-future day when you don't even have to get in the car. Instead, as you walk out the front door, a car assembles around you, lifts off the ground, floats you to your destination, then disassembles in anticipation of picking up the next passenger. Something like this actually happens in living cells. According to news from the European Molecular Biology Laboratory (EMBL):

Researchers at EMBL Heidelberg have produced detailed images of the intricate protein-coats that surround trafficking vesicles -- the "transport pods" that move material around within biological cells. The study, published today in Science, provides a new understanding of the complex machines that make up the cells' logistics network.

Vesicles are responsible for transporting molecules between the different compartments within a cell and also for bringing material into cells from outside. There are several types of vesicle: each has a specific type of coat which is made up of different proteins and assembles onto a membrane surrounding the vesicle. [Emphasis added.]

There are three models of "transport pods" that molecular biologists know about, each with its own specific coat proteins: Coat Protein 1 (COPI), Coat Protein 2 (COPII), and clathrin-coated vesicle (CCV). Each coat has its own proteins, adaptors, and functions. The first paper in Science looks in detail at COPI; but first, let's mention COPII. This type of vesicle takes proteins from the endoplasmic reticulum (ER), where they were assembled, to the Golgi apparatus where they will be packaged for delivery. This is called anterograde (forward) transport.

COPI is the reverse; it takes proteins from the Golgi back to the ER, or to different compartments of the Golgi. This is called retrograde (backward) transport. Surprisingly, the coat proteins on these vesicles are very different. COPII coats are made of four proteins that assemble with four-fold symmetry in a sequential manner, using separate adaptor proteins. COPI is more complicated. It has seven discrete proteins that come together simultaneously, forming complexes with triangular symmetry that include the adaptor function (i.e., allowing the complex to attach to the vesicle membrane).

The EMBL researchers pushed the envelope of cryoelectron microscopy to determine the nature of the "triads" called coatomers that make up the coat. They found that the seven proteins form two complexes that overlap into a layer 14 nanometers (nm) thick -- a substantial fraction of the typical 100-nm-diameter vesicle. A Perspective article in the same issue of Science says there's still a lot to learn about these coats: "it remains to be determined what specific roles these conformations play in the respective coat functions," Noble and Stagg write. What is known is that the coatomer triads make contact with up to four neighboring triads. This gives them structural flexibility that is distinct from the other coated vesicle types. The authors of the paper speculate about the reasons for this:

In existing models for clathrin and COPII vesicle coats, multiple identical subunits each make the same set of interactions with the same number of neighbors. Structural flexibility allows formation of vesicles from different total numbers of subunits. Based on these principles, both clathrin-like and COPII-like models have been proposed for the assembled COPI coat. We found instead that assembled coatomer can adopt different conformations to interact with different numbers of neighbors. By regulating the relative frequencies of different triad patterns in the COPI coat during assembly -- for example, by stabilizing particular coatomer conformations -- the cell would have a mechanism to adapt vesicle size and shape to cargoes of different sizes.

The paper includes color models and two motion animations of how the proteins fit together, protecting the cargo as it rides to its destination from organelle to organelle.

Clathrin Coats

A better-understood protein coat is made of clathrin. The name comes from a Latin word for lattice. Individual clathrin molecules, made of 3 heavy chains and 3 light chains, look like a three-spoked pinwheel called a triskelion. They fit together beautifully around the vesicle into a cage-like structure that resembles a geodesic dome. A beautiful animation from Harvard Medical School shows how numerous other proteins work with clathrin to form the vesicle coat and disassemble it after use, so the triskelia can be recycled. The vesicles can import and export molecules to the exterior of the cell or transport them within the cytoplasm. Clathrin proteins are also implicated in cell division, where they assist in arranging chromosomes on the spindle.

The animation will need an update, because something new was reported about clathrin-coated vesicles (CCV) and the pits (CCP) that form when the membrane invaginates to bring cargo in from outside. Another EMBL team, also reporting in Science, found that clathrin is more gymnastic than previously recognized.

Unlike as shown in the animation, the clathrin lattice forms flat on the inner membrane surface before invagination begins. Then, as the membrane folds inward, the lattice stretches and reconfigures itself, maintaining the same surface area but following the shape of the vesicle as it elongates. With its cargo safely inside, the vesicle pinches off and forms a sphere. The press release from EMBL expresses the surprise at the shape changes:

John Briggs, senior scientist at EMBL Heidelberg, said: "Our results were surprising, because the proteins have to undergo some complicated geometric transformations to go from a flat to a curved shape, which is why the second model was favoured by scientists for such a long time."

(The "second model", now falsified, refers to the idea that "clathrin assembles directly, assuming the shape of the membrane as it is drawn inwards.") The paper describes how the growing cage must change its geodesic structure as the vesicle forms:

In order to bend, flat lattices composed primarily of hexagons must acquire pentagons requiring extensive molecular rearrangements and removal of triskelia.

Why would the cell perform this more difficult gymnastic routine? The final paragraph offers some possible reasons:

Recruitment of clathrin before membrane bending provides a flat, dynamic array as a platform for cargo recruitment. This implies that the membrane to be internalized and the size of the future vesicle are not determined by clathrin geometry during assembly into a curved cage but rather are selected before invagination during cargo recruitment. Rapid clathrin exchange is consistent with a dynamically unstable lattice -- dynamic instability is a common property within networks of low-affinity protein interactions. It would allow for stochastic abortion of sites that initiate but fail to cross a growth- or cargo-mediated checkpoint before investing energy in membrane bending. During invagination, further exchange would allow clathrin reorganization and bending of the lattice into a defined cage that requires active disassembly.

One thing not mentioned in the articles is the rapidity of vesicle formation and disassembly. Suffice it to say that clathrin-coated endocytosis and exocytosis occur at the tips of nerve cells, where electrical signals must cross synapses. The vesicles form at one nerve, cross the synapse carrying the cargo, and are taken in by the next nerve cell in line. How long does it take your brain to feel pain from a stubbed toe? A lot of CCVs formed, crossed synapses, and disassembled in that very quick response!

Evolution or Design?

As usual, the articles and papers say very little about evolution. If mentioned at all, it was about the lack of evolution: e.g., "The archetypal protein coats COPI, COPII, and clathrin are conserved from yeast to human." Only the Perspective piece by Noble and Stagg ventures further:

Individual proteins in the three different coat protein complexes share similar folds and are proposed to be distant evolutionary relatives. Despite these similarities, the coats have evolved different functional mechanisms....

One possibility is that the proto-COPI coat evolved the four different linkages to expand the repertoire of geometries that the coat can accommodate and thus adapt to the secretory needs of the cell.

These suggestions amount to little more than after-the-fact assertions of evolutionary belief. One cannot invoke a blind, unguided process to say that it "evolved to" meet the needs of the cell. Darwinian natural selection has no foresight.

The complexity of these coats, and the accessory proteins that build them, attach them to vesicles and disassemble them, defy unguided evolutionary explanations. They exhibit irreducible complexity; they don't work unless all the protein parts are present simultaneously. They exhibit beauty in the way they organize into geometric shapes. The shapes, in turn, are dictated by digital codes in the genome that produce sequences that fold into building blocks. These building blocks, like the triskelion of clathrin, have no knowledge of the elegant geodesic domes that they will be fitted into. The triskelia are also blind to their attachment points that will be used by two other proteins that will disassemble the vesicle.

We see only glimpses of structures we don't yet fully understand. Why are separate coats needed for the three types of transport? What types of vesicles need the different coats? What specific advantages do the different coats provide for transport in one direction and not the other? What molecules need coated vesicles opposed to uncoated vesicles? What function does each protein in the coat provide?

Further research at higher resolution will undoubtedly yield more knowledge about vesicular transport. One thing is clear so far; the elegance of these systems, their ability to reshape their geometry as they grow, their adaptability to cargoes of many sizes, the rapidity of their action, and their conservation from yeast to humans all proclaim, "design!"