Realistic Explanation Research Articles

Individual Interpretation and Usefulness of Agility in Work and Everyday Life

The global and local changes of the 21st century have brought new types of organisational characteristics to the fore. More and more businesses are looking at how to build more resilient, crisis-resilient organisations and what the real key is. There is a growing consensus that only flexible organisations that are open to change can be truly successful today (and in the future). Flexible organisations, agile companies, promise the greatest growth potential, and there is only one real explanation for this. These companies have the ability to change quickly and flexibly, whereas the vast majority of their competitors have not (or will not) be able to do the same. An organisation that can claim to have the hallmarks of a flexible, business agile organisational culture will have a significant competitive advantage. Agility goes beyond mere flexibility and encompasses a mindset and framework that enables a business to change quickly, make informed decisions and maintain a competitive advantage in a dynamic environment. Agility is also characterised by innovation and the ability to embrace change. We can imagine these at an organisational level, but how well do they translate at an individual level? This research, the results of which this paper seeks to present in more detail, has sought to identify and locate this. In addition to presenting the results, it also takes care to review the literature, which will enable us to draw conclusions about the real meaning and importance of agility, both at the individual and entrepreneurial level.

Neuro-XAI: Explainable deep learning framework based on deeplabV3+ and bayesian optimization for segmentation and classification of brain tumor in MRI scans

The prevalence of brain tumor disorders is currently a global issue. In general, radiography, which includes a large number of images, is an efficient method for diagnosing these life-threatening disorders. The biggest issue in this area is that it takes a radiologist a long time and is physically strenuous to look at all the images. As a result, research into developing systems based on machine learning to assist radiologists in diagnosis continues to rise daily. Convolutional neural networks (CNNs), one type of deep learning approach, have been pivotal in achieving state-of-the-art results in several medical imaging applications, including the identification of brain tumors. CNN hyperparameters are typically set manually for segmentation and classification, which might take a while and increase the chance of using suboptimal hyperparameters for both tasks. Bayesian optimization is a useful method for updating the deep CNN's optimal hyperparameters. The CNN network, however, can be considered a "black box" model because of how difficult it is to comprehend the information it stores because of its complexity. Therefore, this problem can be solved by using Explainable Artificial Intelligence (XAI) tools, which provide doctors with a realistic explanation of CNN's assessments. Implementation of deep learning-based systems in real-time diagnosis is still rare. One of the causes could be that these methods don't quantify the Uncertainty in the predictions, which could undermine trust in the AI-based diagnosis of diseases. To be used in real-time medical diagnosis, CNN-based models must be realistic and appealing, and uncertainty needs to be evaluated. So, a novel three-phase strategy is proposed for segmenting and classifying brain tumors. Segmentation of brain tumors using the DeeplabV3+ model is first performed with tuning of hyperparameters using Bayesian optimization. For classification, features from state-of-the-art deep learning models Darknet53 and mobilenetv2 are extracted and fed to SVM for classification, and hyperparameters of SVM are also optimized using a Bayesian approach. The second step is to understand whatever portion of the images CNN uses for feature extraction using XAI algorithms. Using confusion entropy, the Uncertainty of the Bayesian optimized classifier is finally quantified. Based on a Bayesian-optimized deep learning framework, the experimental findings demonstrate that the proposed method outperforms earlier techniques, achieving a 97 % classification accuracy and a 0.98 global accuracy.

The influence of emotional intelligence and behavioural biases on mutual fund churning frequency: Evidence from India

Behavioural finance invalidates the rationalistic assumptions of the efficient market hypothesis by proposing a realistic explanation for overreaction and underreaction. These phenomena are caused by investors making financial decisions based on their emotions without realizing them. This study attempts to establish the effect of investors' emotional intelligence on behavioural biases, namely, herding, overconfidence bias, and disposition effects, and its consequences for the churning frequency of mutual fund portfolios. This quantitative cross-sectional study was undertaken to collect data from 499 mutual fund investors using a self-administered questionnaire. We found that the disposition effect has a negative impact and that overconfidence bias positively affects the churning frequency of mutual fund portfolios. Furthermore, emotional intelligence, particularly its subconstructs, affects herding bias and overconfidence bias, ultimately impacting the churning frequency of investors. An investor with a higher level of self-motivation is likely to have a disposition effect and herding bias. Investors with disposition impact may be encouraged to reorganize their portfolio if there are any schemes that have been providing negative returns for more than two years or that are not projected to offer significant returns in the future. By understanding how they stack up on each emotional intelligence metric, investors and financial advisors may focus on avoiding the biases that could jeopardize long-term portfolio returns.

Epistolution: a new principle necessary to a learning-first theory of life

ABSTRACT Biological theory assumes the organized appearance of life and the reliable recurrence of traits are due to inheritance. Natural selection acting on blind variations produces phenotypes with heritable traits, one of which may be natural learning. The aim of learning, then, is solving problems related to survival and reproduction. But what if these views confuse cause with effect? Perhaps a learning algorithm is required for any phenotype at all to arise. If so, evolution proceeds learning-first, with individuals pursuing another telos entirely. I argue that this aim may be epistemological, the drive to understand the world through an umwelt. By “understand” I mean neither association nor prediction but Karl Popper’s concept of explanation through conjecture and refutation. I propose that if only genetic materials are truly heritable, not traits, then testing a successful physical theory of life will depend on building abiotic machines which can perform natural learning without the presence of any inherited materials or conditions. I name this process “epistolution,” combining “epistemology” and “evolution,” to distinguish it from other concepts. Epistolution is an integral consequence of any learning-first view of life, such as the Cellular Basis of Consciousness theory. This type of theory suggests that in all cells during the history of life full-blown agency, involving beliefs, intentions, and desires, generated all the phenotypes that have then been winnowed by natural selection. Unlike in other versions, I posit that the aim of agential living systems is the explanation of reality rather than inductive prediction or survival/reproduction.

Einstein–Podolsky–Rosen steering paradox “2=1” for N qubits

Einstein–Podolsky–Rosen (EPR) paradox highlights the absence of a local realistic explanation for quantum mechanics, and shows the incompatibility of the local-hidden-state models with quantum theory. For N-qubit states, or more importantly, the N-qubit mixed states, we present the EPR steering paradox in the form of the contradictory equality “[Formula: see text]”. We show that the contradiction holds for any N-qubit state as long as both “the pure state requirement” and “the measurement requirement” are satisfied. This also indicates that the EPR steering paradox exists in more general cases. Finally, we give specific examples to demonstrate and analyze our arguments.

Statistical Fuzzy Reliability Analysis: An Explanation with Generalized Intuitionistic Fuzzy Lomax Distribution

To illustrate data uncertainty, intuitionistic fuzzy sets simply use membership and non-membership degrees. However, in some cases, a more complex strategy is required to deal with imprecise data. One of these techniques is generalized intuitionistic fuzzy sets (GIFSs), which provide a comprehensive framework by adding extra factors that provide a more realistic explanation for uncertainty. GIFSs contain generalized membership, non-membership, and hesitation degrees for establishing symmetry around a reference point. In this paper, we applied a generalized intuitionistic fuzzy set approach to investigate ambiguity in the parameter of the Lomax life distribution, seeking a more symmetric assessment of the reliability measurements. Several reliability measurements and associated cut sets for a novel L-R type fuzzy sets are derived after establishing the scale parameter as a generalized intuitionistic fuzzy number. Additionally, the study includes a range of reliability measurements, such as odds, hazards, reliability functions, etc., that are designed for the Lomax distribution within the framework of generalized intuitionistic fuzzy sets. These reliability measurements are an essential tool for evaluating the reliability characteristics of various types of complex systems. For the purpose of interpretation and application, the results are visually displayed and compared across different cut set values using a numerical example.

Model of the photon made up of lines of elementary waves. Realistic explanation of obtaining interferences by emitting photons one by one through two Young’s slits

The theory of the dynamic medium of reference (DMR) has already been presented in several articles, in particular, by Olivier Pignard [Phys. Essays 32, 422 (2019)]. The objective of this article is to present a model of the photon within the framework of the DMR theory. A concept of elementary wave on the subatomic level is introduced. An elementary wave is always identical to itself while being constantly renewed by new gravitons (entities that make up the medium of propagation of the wave). This elementary wave propagates in its medium (DMR) at the speed of light whatever its trajectory. A possible model of the elementary wave called light-vortex is presented in Appendix B. Then the concept of line of vortices is introduced. The vortices constituting a line all have their axis parallel to each other and perpendicular to the direction of propagation are separated by half a wavelength and rotate alternately in one direction and the other. The model of the proposed photon is then a set of lines of vortices parallel to each other (the number of lines of vortices as well as the length of the photon are constants whatever the frequency of the photon.) This model makes it possible to attribute to the photon, the speed c, a frequency ν, a period T = 1/ν, a wavelength λ = c/ν, the energy E = hν, the momentum p = E/c =h · ν/c, and even a polarization (rectilinear, circular, or elliptical). It allows above all to explain that the photon has at the same time a wave aspect (because composed only of elementary waves) and a corpuscular aspect (since the elementary waves remain identical to themselves and the photon remains delimited by the same volume). It also explains the phenomenon of diffraction by emitting photons, even one by one, through a slit and that of interferences by emitting photons, even one by one, through two Young’s slits.

The problem with probability

Knightian uncertainty is the circumstance in which there is not enough information available to quantitatively measure in terms of probability the uncertainty that is present. Economic decision makers usually face that kind of uncertainty when attempting to determine their best route forward into the future. But instead of confronting Knightian uncertainty head on, economists generally have assumed it away by opting instead to employ what Knight called risk as measured by probability. But there are serious questions about whether probability has the capacity to coral in a meaningful way the uncertainty many decision makers actually face, and whether its use in models of decision making provides an appropriately relevant and realistic explanation of what is going on. This paper argues that it does not by examining the meaning of the probability concept as it relates to the true uncertain environment the decision maker faces. It also suggests that the alternative measure of surprise introduced by Shackle not only returns such analyses to the more realistic realm of Knightian uncertainty, but is also a workable and suitable replacement for probability in explanations of decision making that need to account for the unpredictability of the future.

Oil Price Uncertainty and M&A Activity

This study examines the impact of oil price uncertainty on mergers and acquisition (M&A) activity in the oil and gas sector. Analyzing this industry enables us to construct a natural forward-looking measure of oil price uncertainty, namely the implied crude oil volatility. Using a sample of U.S. firms in the oil and gas sector from 1994–2018 containing 4,323 announced transactions, we document that oil price uncertainty is negatively related to future M&A activity. Uncertainty is mainly a driver of horizontal and vertical M&A activity, where upstream firms are more affected by this uncertainty than downstream firms. Our results lend support to a real options explanation of investment under uncertainty where firms choose to defer investments as a response to increased uncertainty.

Indigenous mental healthcare and human rights abuses in Nigeria: The role of cultural syntonicity and stigmatization.

Indigenous mental healthcare using traditional non-western methods termed "unorthodox approaches" has been observed in Nigeria historically. This has been largely due to a cultural preference for spiritual or mystical rather than biomedical formulations of mental disorder. Yet, there have been recent concerns about human rights abuses within such treatment settings as well as their tendency to perpetuate stigmatization. The aim of this review was to examine the cultural framework for indigenous mental healthcare in Nigeria, the role of stigmatization in its utilization and interrogate the issues of human rights abuses within a public mental health context. This is a non-systematic narrative review of published literature on mental disorders, mental health service utilization, cultural issues, stigma, and indigenous mental healthcare. Media and advocacy reports related to human rights abuses in indigenous mental health treatment settings were also examined. International conventions on human rights and torture, national criminal legislation, constitutional provisions on fundamental rights and medical ethics guidelines relevant to patient care within the country were examined in order to highlight provisions regarding human rights abuses within the context of care. Indigenous mental healthcare in Nigeria is culturally syntonic, has a complex interaction with stigmatization and is associated with incidents of human rights abuses especially torture of different variants. Three systemic responses to indigenous mental healthcare in Nigeria include: orthodox dichotomization, interactive dimensionalization, and collaborative shared care. Conclusions: Indigenous mental healthcare is endemic in Nigeria. Orthodox dichotomization is unlikely to produce a meaningful care response. Interactive dimensionalization provides a realistic psychosocial explanation for the utilization of indigenous mental healthcare. Collaborative shared care involving measured collaboration between orthodox mental health practitioners and indigenous mental health systems offers an effective as well as cost-effective intervention strategy. It reduces harmful effects of indigenous mental healthcare including human rights abuses and offers patients a culturally appropriate response to their problems.

On the nature of picobirnaviruses.

The picobirnaviruses (Picobirnaviridae, Picobirnavirus, PBVs) are currently thought to be animal viruses, as they are usually found in animal stool samples. However, no animal model or cell culture for their propagation has yet been found. In 2018, a hypothetical assumption about PBVs belonging to prokaryotic viruses was put forward and experimentally substantiated. This hypothesis is based on the presence of Shine-Dalgarno sequences in the genome of all PBVs before three reading frames (ORF) at the ribosomal binding site, with which the prokaryotic genome is saturated, while in the eukaryotic genome such regions occur with low frequency. The genome saturation with the Shine-Dalgarno sequences, as well as the preservation of this saturation in the progeny, according to scientists, allows us to attribute PBVs to prokaryotic viruses. On the other hand, there is a possibility that PBVs belong to viruses of eukaryotic hosts - fungi or invertebrates, since PBV-like sequences similar to the genome of fungal viruses from the families of mitoviruses and partitiviruses have been identified. In this regard, the idea arose that, in terms of reproduction mode, PBVs resemble fungal viruses. The divergence of views on the true PBV host(s) has sparked discussions among scientists and required further research to elucidate their nature. The review highlights the results of the search for a PBV host. The reasons for the occurrence of atypical sequences among the PBV genome sequences that use an alternative mitochondrial code of lower eukaryotes (fungi and invertebrates) for the translation of viral RNA-dependent RNA polymerase (RdRp) instead of the standard genetic code are analyzed. The purpose of the review was to collect arguments in support of the hypothesis about the phage nature of PBVs and to find the most realistic explanation of the reasons for identifying non-standard genomic sequences for PBVs. Based on the hypothesis about the genealogical relationship of PBVs with RNA viruses from other families with similar segmented genomes, such as Reoviridae, Cystoviridae, Totiviridae and Partitiviridae, virologists support the assumption of a decisive role in the origin of atypical PBV-like reassortment strains between PBVs and viruses of the listed families. The collected arguments given in this review indicate a high probability of a phage nature of PBVs. The data presented in the review show that the belonging of PBV-like progeny to prokaryotic or eukaryotic viruses is determined not only by its genome saturation level with a prokaryotic motif, standard or mitochondrial genetic code. The primary structure of the gene encoding the viral capsid protein responsible for the presence or absence of specific proteolytic properties of the virus that determine its ability for independent horizontal transmission into new cells may also be a decisive factor.

Transport mechanisms of hydrothermal convection in faulted tight sandstones

Abstract. Motivated by the unknown reasons for a kilometre-scale high-temperature overprint of 270–300 ∘C in a reservoir outcrop analogue (Piesberg quarry, northwestern Germany), numerical simulations are conducted to identify the transport mechanisms of the fault-related hydrothermal convection system. The system mainly consists of a main fault and a sandstone reservoir in which transfer faults are embedded. The results show that the buoyancy-driven convection in the main fault is the basic requirement for elevated temperatures in the reservoir. We studied the effects of permeability variations and lateral regional flow (LRF) mimicking the topographical conditions on the preferential fluid-flow pathways, dominant heat-transfer types, and mutual interactions among different convective and advective flow modes. The sensitivity analysis of permeability variations indicates that lateral convection in the sandstone and advection in the transfer faults can efficiently transport fluid and heat, thus causing elevated temperatures (≥269 ∘C) in the reservoir at a depth of 4.4 km compared to purely conduction-dominated heat transfer (≤250 ∘C). Higher-level lateral regional flow interacts with convection and advection and changes the dominant heat transfer from conduction to advection in the transfer faults for the low permeability cases of sandstone and main fault. Simulations with anisotropic permeabilities detailed the dependence of the onset of convection and advection in the reservoir on the spatial permeability distribution. The depth-dependent permeabilities of the main fault reduce the amount of energy transferred by buoyancy-driven convection. The increased heat and fluid flows resulting from the anisotropic main fault permeability provide the most realistic explanation for the thermal anomalies in the reservoir. Our numerical models can facilitate exploration and exploitation workflows to develop positive thermal anomaly zones as geothermal reservoirs. These preliminary results will stimulate further petroleum and geothermal studies of fully coupled thermo–hydro–mechanical–chemical processes in faulted tight sandstones.

Potential Users of River Transport Integrated with the South Sumatera Light Rail Transit (LRT) after Improvements to the Facilities in Accordance with Public Perception

The Palembang City, one of the cities in Indonesia with a high population density, is crossed by the Musi River and its networks that flow through 10 sub districts and 30 villages. The shipping lanes of the Musi River within Palembang City and its suburbs can be navigated by huge ships all year round and are means of transportation that is free from congestion, environmentally friendly and energy efficient. Since 2018, river transport in Palembang is connected with the South Sumatra light rail transit (LRT), namely in the Ampera area. The LRT is a convenient and strategic transportation, because it passes through office, business center, entertainment and sports facilities. In addition, this rail-based transportation is connected with Trans Musi and air transportation. Both of these transportations have affordable and competitive fares comparable to other transportation. However, until now these two transportations are still equally struggling to attract customers. Therefore, this study aimed to determine public perception of transportation connected to the LRT and what they want for the integration between these two modes. Then, the public perceptions were visualized into images or computer simulation. The images or simulation was then re-run by the community to see whether it is what they want or whether it still needs revision or addition. The survey also investigated whether there is an increase in users if the perception is realized. It shows that the most desired supporting facility for the integration between the river transport and the LRT is pedestrian lanes or sidewalks. Furthermore, a more realistic explanation tool will help people to imagine the activities that will be carried out in the future; thus, they are more convinced to choose to use it or not.

Insight into the Behavior of Mortars Containing Glass Powder: An Artificial Neural Network Analysis Approach to Classify the Hydration Modes.

In this paper, an artificial neural network (ANN) model is proposed to predict the hydration process of a new alternative binder. This model overcomes the lack of input parameters of physical models, providing a realistic explanation with few inputs and fast calculations. Indeed, four mortars are studied based on ordinary Portland cement (CEM I), cement with limited environmental impact (CEM III), and glass powder (GP) as the cement substitution. These mortars are named CEM I + GP and CEM III + GP. The properties of the mortars are characterized, and their life cycle assessment (LCA) is established. Indeed, a decrease in porosity is observed at 90 days by 4.6%, 2.5%, 12.4%, and 7.9% compared to those of 3 days for CEMI, CEMIII, CEMI + GP, and CEMIII + GP, respectively. In addition, the use of GP allows for reducing the mechanical strength in the short term. At 90 days, CEMI + GP and CEMIII + GP present a decrease of about 28% and 57% in compressive strength compared to CEMI and CEMIII, respectively. Nevertheless, strength does not cease increasing with the curing time, due to the continuous pozzolanic reactions between Ca(OH)2 and silica contained in GP and slag present in CEMIII as demonstrated by the thermo-gravimetrical (TG) analysis. To summarize, CEMIII mortar provides similar performance compared to mortar with CEMI + GP in the long term. This can later be used in the construction sector and particularly in prefabricated structural elements. Moreover, the ANN model used to predict the heat of hydration provides a similar result compared to the experiment, with a resulting R² of 0.997, 0.968, 0.968, and 0.921 for CEMI, CEMIII, CEMI + GP, and CEMIII + GP, respectively, and allows for identifying the different hydration modes of the investigated mortars. The proposed ANN model will allow cement manufacturers to quickly identify the different hydration modes of new binders by using only the heat of hydration test as an input parameter.

The Classical Description of the Meissner Effect: Theory and Applications

When we place a superconductor above a magnet, we observe a levitation of the superconductor above the magnet. But when placing a perfect diamagnetic material above a magnet, no levitation is observed. This difference in behavior between the superconductor and the perfect diamagnetic in the presence of an external magnetic field is explained by the classical description of the Meissner effect implemented in this article. We have shown here that the Meissner effect is nothing more than an electromagnetic interaction between the magnetic field created by the superconductor and the magnetic field of the magnet. This classical description of the Meissner effect also allowed us to give a more realistic explanation of the expansion of the universe. We have shown that this expansion is a phenomenon that simply results from a Meissner effect between superconducting dark matter and the magnetic fields of stars. We also pointed out that this expansion is accelerated because the gravitational force between dark matter and the stars around it decreases as these stars move away from the superconducting dark matter. We also used this classical description of the Meissner effect to propose a new method of remote sensing in space in which the superconducting satellite is in perpetual levitation on the night side of the earth and a new and more efficient way to discover new particles through a superconducting detector levitating in the upper atmosphere.

Degrees of Objectivity? Mathemata and Social Objects

A down-to-earth admission of abstract objects can be based on detailed explanation of where the objectivity of mathematics comes from, and how a ‘thin’ notion of object emerges from objective mathematical discourse or practices. We offer a sketch of arguments concerning both points, as a basis for critical scrutiny of the idea that mathematical and social objects are essentially of the same kind—which is criticized. Some authors have proposed that mathematical entities are indeed institutional objects, a product of our collective imposition of function onto reality (the phrase comes from Searle) and of surrogation or hypostasis. Yet there are significant disanalogies between the typical social objects and mathemata, on which basis I argue that one should make a clear distinction between both. The comparison of mathematical with social objects helps understanding how non-physical objects can figure prominently in our explanations of reality. Yet mathematical objects have a different kind of cognitive grounding, and the more elementary of them emerge under relatively very simple sociocultural conditions. The differences are also reflected in the wide scope of use of mathematical concepts, and the much higher degree of variation found among social objects. On the basis of all of these features, I defend the thesis that one can significantly distinguish degrees of objectivity, and I use the distinction to articulate a graded ontology where one can locate the different kinds of mathematical and social objects.

The Algerian agricultural sector between the question of food security and its implication in economic diversification strategy

AbstractThe agricultural sector in Algeria has always sparked a fascinating and captivating debate for years, in particular in the phase of economic transition started and triggered after the sharp fall in the price of the barrel and the need to adapt to the new, more liberal, and opened economic mechanism. Many scientific writings were devoted to this subject, in particular O. Bessaoud, S. Bedrani, M. Boukella, A. Daoudi, A. Djennane, and others, trying to demonstrate and approve the crucial role played by this sector in the national economy, others to enumerate and identify the hiccups and obstacles to the smooth running of it, but the result remains that agriculture (in all its branches and sub‐activities) does not seem to reach its cruising speed and is content just to meet the expectations and needs of domestic consumers, with particular attention to the prices and quality of products and goods supplied. Of course, we must not deny the efforts made by the State to revive this sector, through the investment programs and the financial envelopes granted, the most resounding consists in the PNDAR (National Agricultural and Rural Development Program) at the beginning 2000, but the result shows a deplorable situation, which does not find a real argument and explanation, despite the innumerable interventions of local administrations (banks, taxes, insurance, justice, customs, and others). So we find ourselves faced with a state of affairs that hardly favors a serious enough reflection on the future deadlines of the sector, in particular in a context where the question of food security arises acutely and the return to the problem of economic diversification (in which a more preponderant and crucial role is reserved for the agricultural sector) is making a strong comeback on the national scene. Our main problem is as follows: “Could the agricultural sector in Algeria succeed to guarantee food security and a contribution in the economic diversification of the State.” For this purpose, some findings can be traced such as the economic perspectives of agriculture, the question of food security, the future of Algerian economy, the policy and strategy of economic diversification, and others. The main results expected turned mainly about the evolution of agricultural products for food consumption, the tools to manage the policy of food security, the means used to realize the economic diversification, and the nature of relation between the agricultural sector and the economic diversification. The scientific methods to be exploited in this paper will be mainly a descriptive analysis based on exploring the agricultural production, the food's consumption evolution, and the evolution of some macroeconomic indicators. Regarding this fact, we will try, in this paper, to seriously and objectively examine what role this sector can play in a double vision: ensuring food security for the population and getting involved in economic diversification initiatives for better economic international competitiveness.

Prediction Accuracy of Production ADMET Models as a Function of Version: Activity Cliffs Rule.

As with many other institutions, our company maintains many quantitative structure-activity relationship (QSAR) models of absorption, distribution, metabolism, excretion, and toxicity (ADMET) end points and updates the models regularly. We recently examined version-to-version predictivity for these models over a period of 10 years. In this approach we monitor the goodness of prediction of new molecules relative to the training set of model version V before they are incorporated in the updated model V+1. Using a cell-based permeability assay (Papp) as an example, we illustrate how the QSAR models made from this data are generally predictive and can be utilized to enrich chemical designs and synthesis. Despite the obvious utility of these models, we turned up unexpected behavior in Papp and other ADMET activities for which the explanation is not obvious. One such behavior is that the apparent predictivity of the models as measured by root-mean-square-error can vary greatly from version to version and is sometimes very poor. One intuitively appealing explanation is that the observed activities of the new molecules fall outside the bulk of activities in the training set. Alternatively, one may think that the new molecules are exploring different regions of chemical space than the training set. However, the real explanation has to do with activity cliffs. If the observed activities of the new molecules are different than expected based on similar molecules in the training set, the predictions will be less accurate. This is true for all our ADMET end points.

Something's Fishy About It: How Opinion Congeniality and Explainability Affect Motivated Attribution to Artificial Intelligence Versus Human Comment Moderators.

An online experiment (N = 384) examined when and how the identity of the comment moderator (artificial intelligence [AI] vs. human) on a news website affects the extent to which individuals (a) suspect political motives for comment removal and (b) believe in the AI heuristic ("AI is objective, neutral, accurate, and fair"). Specifically, we investigated how the provision of an explanation for comment removal (none vs. real vs. placebic), and opinion congeniality between the remaining comments and the user's opinion (uncongenial vs. congenial) qualify social responses to AI. Results showed that news users were more suspicious of political motives for an AI (vs. human) moderator's comment removal (a) when the remaining comments were uncongenial, and (b) when no explanation was offered for deleted comments. Providing a real explanation (vs. none) attenuated participants' suspicion of political motives behind comment removal, but only for the AI moderator. When AI moderated the comments section, the exposure to congenial (vs. uncongenial) comments led participants to endorse the AI heuristic more strongly, but only in the absence of an explanation for comment removal. By contrast, the participants' belief in AI heuristic was stronger when a human moderator preserved uncongenial (vs. congenial) comments. Apparently, they considered AI as a viable alternative to a human moderator whose performance was unsatisfactory.

Electromagnetism's Bridge Across the Explanatory Gap: How a Neuroscience/Physics Collaboration Delivers Explanation Into All Theories of Consciousness.

A productive, informative three decades of correlates of phenomenal consciousness (P-Consciousness) have delivered valuable knowledge while simultaneously locating us in a unique and unprecedented explanatory cul-de-sac. Observational correlates are demonstrated to be intrinsically very unlikely to explain or lead to a fundamental principle underlying the strongly emergent 1st-person-perspective (1PP) invisibly stowed away inside them. That lack is now solidly evidenced in practice. To escape our explanatory impasse, this article focuses on fundamental physics (the standard model of particle physics), which brings to light a foundational argument for how the brain is an essentially electromagnetic (EM) field object from the atomic level up. That is, our multitude of correlates of P-Consciousness are actually descriptions of specific EM field behaviors that are posed (hypothesized) as “the right” correlate by a particular theory of consciousness. Because of this, our 30 years of empirical progress can be reinterpreted as, in effect, the delivery of a large body of evidence that the standard model’s EM quadrant can deliver a 1PP. That is, all theories of consciousness are, in the end, merely recipes that select a particular subset of the totality of EM field expression that is brain tissue. With a universal convergence on EM, the science of P-Consciousness becomes a collaborative effort between neuroscience and physics. The collaboration acts in pursuit of a unified explanation applicable to all theories of consciousness while remaining mindful that the process still contains no real explanation as to why or how EM fields deliver a 1PP. The apparent continued lack of explanation is, however, different: this time, the way forward is opened through its direct connection to fundamental physics. This is the first result (Part I). Part II posits, in general terms, a structural (epistemic) add-on/upgrade to the standard model that has the potential to deliver the missing route to an explanation of how subjectivity is delivered through EM fields. The revised standard model, under the neuroscience/physics collaboration, intimately integrates with the existing “correlates of-” paradigm, which acts as its source of empirical evidence. No existing theory of consciousness is lost or invalidated.