Platonism and Mathematical Explanations

Ontological parsimony requires that if we can dispense with A when best explaining B, or when deducing a nominalistically statable conclusion B from nominalistically statable premises, we must indeed dispense with A. When A is a mathematical theory and it has been established that its conservativeness undermines the platonistic force of mathematical derivations (Field), or that a non numerical formulation of some explanans may be obtained so that the platonistic force of the best numerical-based account of the explanandum is also undermined (Rizza), the parsimony principle has been respected. Since derivations resorting to conservative mathematics and proofs involved in non numerical best explanations also require abstract objects, concepts, and principles under the usual reading of “abstract,” one might complain that such accounts turn out to be as metaphysically loaded as their platonistic counterparts. One might then urge that ontological parsimony is also required of these nominalistic accounts. It might, however, prove more fruitful to leave this particular worry to the side, to free oneself, as it were, from parsimony thus construed and to look at other important aspects of the defeating or undermining strategies that have been lavished on the disposal of platonism. Two aspects are worthy of our attention: epistemic cost and debunking claims. Our knowledge that applied mathematics is conservative is established at a cost, and so is our knowledge that nominalistic proofs play a genuine theoretical role in best explanations. I will suggest that the knowledge one must acquire to show that nominalistic deductions and explanations do indeed play their respective theoretical role involves some question-begging assumptions regarding the nature and validity of proofs. As for debunking, even if the face value content of either non numerical claims, or conservative mathematical claims, or platonistic mathematical claims didn’t figure in our causal explanation of why we hold the mathematical beliefs that we do, construed or understood as beliefs about such contents, or as beliefs held in either of these three ways, we could still be justified in holding them, so that the distinction between nominalistic deductions or non numerical explanations on the one hand and platonistic ones on the other turns out to be spurious with respect to the relevant propositional attitude, i.e., with respect to belief.

Bayesian Model for Covid-19 to Achieve Immunity by Parsimony of Exponential Functions Minimizing the Inoculum

A ribonucleoside analog MK-4482/EIDD-2801 blocks SARS-CoV-2 transmission in ferrets and might be able to diminish transmission until vaccineinduced or naturally acquired protective herd immunity is reached [1]. As skinner pointed out, behavioral problems have to be solved through behavioral engineering [2]. Cybernetics has full application in the present condition. As in alcohol consumption, smoking, drugs, gun crimes, wars, and sexually acquired diseases, the teleological Aristotelian causes are not tobacco, drugs, and any other issue, but the aberrant behavior. The situation is not trivial and involves non-classic logic and other mathematical logics [3,4]. The neural topography corresponds to the nucleus accumbens. The latter is the battlefield, and the subject’s obsession is the rise of the neurotransmitter dopamine [3,4]. In general, people are very demanding from their governments; nevertheless, at the same time, they are deeply tolerant with their aberrant behavior promoting the dissemination of the SARSCoV-2 [4,5]. This paper examines how to deal with this problem from a scientific perspective, considering probability methods and classical and doxastic logic, using the Parsimony Principle aiming to reach immunity by minimizing the inoculum.

Application of the Parsimony Principle of Exponential Functions to the Production of COVID-19 Immunity, According to Bayesian Theorem and Cybernetics, to Tame Anti-scientific Doxastic Logic and the Pandemic

The purpose of this work is to provide evidence to the scientific community that there is solid scientific knowledge available to tame the pandemic, which is mainly a behavioral problem that requires cybernetics through behavioral engineering. Scientifically it is clear that the problem of the pandemic originates in human behavior and misinformation. Behavioral problems are addressed by cybernetics through behavioral engineering. Aristotelian causes of the pandemic are aberrant behavior. This is the field of battle and the obsession of the subject is the rise of the neurotransmitter dopamine. The question is not what is the probability that a patient with COVID-19 has a certain symptom or sign? Rather it is to calculate the probability that a patient with a certain sign or symptom has COVID-19. Without grasping the differential equations modeled by Kermack and McKendrick, it is impossible to have an idea of what is happening in the pandemic. Our straightforward theoretical approach is to use the wild unmodified SARS-CoV-2 to produce immunity by the simple expedient of diminishing the amount of the inoculum to the minimum minimorum. The problem with allowing people, deliberately attempting herd immunity, is that it has the dire effect that a high percentage will necessarily die. It is a matter of competence between two exponential functions. On one hand the exponential reproduction of the virus, and on the other hand, the exponential production of antibodies and activation of T cells. The aim is to diminish the amount of the inoculum to the minimum minimorum capable of infecting the minimum susceptible cell subpopulation. In this manner, herd immunity could be reached, which would allow a parsimonical response in the viral exponential growth that would not overwhelm the exponential immune response. It is expected that susceptible subjects could be infected in a variolation modality through the universal use of masks, maximizing the distance, rather than in a noregulated exposure of a putative low-risk segment of the population. In the logic of the decision, we must distinguish a desideratum from what is physically, economically, legally, and politically implementable. It is a matter of policy-making supported by science and law instead of doxastic logic based on misinformation and bigotry. It is a matter of policy enforcement by cybernetics, by behavior engineering, not of a recommendation. The guidelines, if they are to be implemented, depend on the application of cybernetics, and behavioral engineering. The apodictic inference from fallacies, in a doxastic and desiderative logic, is the origin of disinformation. Keywords: COVID-19 Inoculum; Bayes Theorem; Cybernetics; Variolation; Herd immunity

Platonism And Mathematical Explanations

Ontological parsimony requires that if we can dispense with A when best explaining B, or when deducing a nominalistically statable conclusion B from nominalistically statable premises, we must indeed dispense with A. When A is a mathematical theory and it has been established that its conservativeness undermines the platonistic force of mathematical derivations (Field), or that a nonnumerical formulation of some explanans may be obtained so that the platonistic force of the best numerical-based account of the explanandum is also undermined (Rizza), the parsimony principle has been respected.Since both derivations resorting to conservative mathematics and nonnumerical best explanations also require abstract objects, concepts and principles, ontological parsimony must also be required of nominalistic accounts. One then might of course complain that such accounts turn out to be as metaphysically loaded as their platonistic counterparts. However, it might prove more fruitful to leave this particular worry to one side, to free oneself, as it were, from parsimony thus construed and to look at other important aspects of the defeating or undermining strategies that have been lavished on the disposal of platonism.Two aspects are worthy of our attention: epistemic cost and debunking arguments. Our knowledge that good mathematics is conservative is established at a cost, and so is our knowledge that nominalistic proofs play a theoretical role in best explanations. I will suggest that the knowledge one must acquire to show that nominalistic deductions and explanations do play their respective theoretical role involves some question-begging assumptions regarding the nature of proofs. As for debunking, even if the face value content of either conservative or platonistic mathematical claims didn’t figure in our explanation of why we hold the mathematical beliefs that we do, we could still be justified in holding them so that the distinction between nominalistic deductions and explanations and platonistic ones turns out to be invidious with respect to the relevant propositional attitude, i.e., with respect to belief.

Chronic Miliarial Gout Associated with Carpal Tunnel Syndrome: A Very Rare Clinical Presentation

This case report describes an unusual form of gout, called miliarial gout, in association with carpal tunnel syndrome in a 54-year-old woman. Miliarial gout was first described in 2007 and is a very rare presentation of chronic tophaceous gout. The latter condition can cause carpal tunnel syndrome, but this association has not previously been described in association with miliarial gout. In addition, the authors discuss the use of the parsimony principle in internal medicine whereby a single cause is first sought for different symptoms presenting at the same time.

O walorach poznawczych negatywnego ujmowania … świadomości (?)

Tak bogata, wielowątkowa i wewnętrznie zróżnicowana tradycja problematyki świadomości, jak i jej wyjątkowa złożoność i trudność, jednoznacznie „podpowiada” oraz uzasadnia nieodrzucanie zaraz na początku, z góry, jakichkolwiek możliwości podejścia do tego szczególnego przedmiotu i jakichkolwiek sposobów jego ujmowania; w tym możliwości podejścia apofatycznego i apofatycznego sposobu ujmowania go. Ich poznawcze walory zdaje się sugerować możliwa, przynajmniej możliwa, interpretacja: zasady ekonomii wyjaśniania (parsimony principle) – podstawowej zasady określającej tryb wyjaśniania realizowany z perspektywy trzecioosobowej – w kategoriach negatywnych i pozytywnych momentów/wątków jej zawartości, Ayera eksplikacji fenomenu prywatności oraz Marcela propozycji ukazania specyfiki (konstruktu) świadomości przy pomocy idiomu over and above, wskazującego nie tylko na nie-zwyczajność świadomości jako konstruktu wyjaśniającego, lecz także odsyłającego do nie-zwyczajności wyjaśnianego przezeń zachowania. Takie apofatyczne podejście – najpierw do zachowania, a potem jego mechanizmu – i takie ich (zachowania i jego mechanizmu) najpierw apofatyczne ujęcie zdaje się naprowadzać tak na samą możliwość, jak i na kierunek oraz sposób pozytywnego do nich podejścia i zawartość pozytywnego ich ujęcia; i taki zdaje się być ich (podejścia i ujęcia) podstawowy poznawczy walor. To, czy ten tryb roboty, zastosowany do pewnej postaci prywatności – wyróżnionej jeszcze na etapie negatywnego do niej podejścia i jej negatywnego jeszcze ujęcia – pozwoli później, na etapie pozytywnego już do niej podejścia i pozytywnego już jej ujęcia, w pewnym momencie na jej identyfikację z najmocniej rozumianą świadomością, to najważniejsza, ale zarazem i najtrudniejsza, z pozostających do rozważenia spraw.

Prediksi Debit Sungai Bedog dan Gajahwong Dengan Model Arima sebagai Dasar Penentuan Pola Tanam (Prediction of Bedog and Gajahwong River Discharges Using Arima Model as A Basis to Determine Planting Pattern)

Planting pattern in an irrigation system is affected by water availability in river which may fluctuate from time to time. The objective of this paper is to assess the discharge fluctuation characteristic of Bedog and Gajahwong Rivers measured respectively in Cokrobedog and Mrican Weirs. The historical discharge data of the two rivers was assessed to predict river discharges of subsequent year as a basis of planting pattern determination. The ARIMA model was employed to predict water avalability. Model test showed that ARIMA (1,1,0) and ARIMA (2,1,0) could accurately predict river discharge of the two rivers. Considering parsimony principle, the ARIMA (1,1,0) model was chosen as the most suitable model. Based on predicted discharge, the previous planting pattern can still be applied in the future.ABSTRAKPola tanam pada sistemirigasi dipengaruhi oleh ketersediaan air di sungai yang bervariasi dari waktu ke waktu. Tujuan penelitian ini adalah untuk menganalisis karakteristik fluktuasi debit Sungai Bedog dan Sungai Gajahwong yang masing-masing diukur di Bendung Cokrobedog dan Bendung Mrican. Data historis debit kedua sungai dianalisis untuk menentukan karakteristik dan memprediksi debit pada tahun berikutnya sebagai dasar penyusunan pola tanam. Model ARIMA dipergunakan untuk memprediksi ketersediaan air. Uji model menunjukkan bahwa ARIMA (1,1,0) and ARIMA (2,1,0) mampu memperkirakan debit kedua sungai. Dengan mempertimbangkan prinsip parsimony, maka model ARIMA (1,1,0) dipilih sebagai model yang paling sesuai. Berdadsarkan prediksi debit, pola tanam sebelumnya yaitu padi-padi-palawija masih dapat diberlakukan di masa yang akan datang.

Foundations of Support Constraint Machines

The mathematical foundations of a new theory for the design of intelligent agents are presented. The proposed learning paradigm is centered around the concept of constraint, representing the interactions with the environment, and the parsimony principle. The classical regularization framework of kernel machines is naturally extended to the case in which the agents interact with a richer environment, where abstract granules of knowledge, compactly described by different linguistic formalisms, can be translated into the unified notion of constraint for defining the hypothesis set. Constrained variational calculus is exploited to derive general representation theorems that provide a description of the optimal body of the agent (i.e., the functional structure of the optimal solution to the learning problem), which is the basis for devising new learning algorithms. We show that regardless of the kind of constraints, the optimal body of the agent is a support constraint machine (SCM) based on representer theorems that extend classical results for kernel machines and provide new representations. In a sense, the expressiveness of constraints yields a semantic-based regularization theory, which strongly restricts the hypothesis set of classical regularization. Some guidelines to unify continuous and discrete computational mechanisms are given so as to accommodate in the same framework various kinds of stimuli, for example, supervised examples and logic predicates. The proposed view of learning from constraints incorporates classical learning from examples and extends naturally to the case in which the examples are subsets of the input space, which is related to learning propositional logic clauses.