Target Concept Research Articles

Conceptual Engineering, Conceptual Domination, and the Case of Conspiracy Theories

ABSTRACT Using the example of recent attempts to engineer the concept of conspiracy theory, I argue that philosophers should be far more circumspect in their approach to conceptual engineering than we have been – in particular, that we should pay much closer attention to the history behind and context that surrounds our target concept in order to determine whether it is a site of what I have elsewhere called ‘conceptual domination’. If it is, we may well have good reason to avoid engineering. In their recent ‘What is a Conspiracy Theory?’, M. Giulia Napolitano and Kevin Reuter argue that the disagreement between generalists and particularists in the literature on conspiracy theories is best characterized as a set of dueling conceptual engineering projects. While I agree with their turn to this metaphilosophical literature, I give a very different account of its applicability. Particularists, on my account, are better read as aiming to diagnose the ways in which many discussions of the concept of conspiracy theories are a form of conceptual domination, where this broader context should then prompt us to abandon or block any concept of conspiracy theory that treats its referents as inherently defective. Broader metaphilosophical lessons are drawn.

PAC-learning with approximate predictors

Approximate learning machines have become popular in the era of small devices, including quantised, factorised, hashed, or otherwise compressed predictors, and the quest to explain and guarantee good generalisation abilities for such methods has just begun. In this paper, we study the role of approximability in learning, both in the full precision and the approximated settings. We do this through a notion of sensitivity of predictors to the action of the approximation operator at hand. We prove upper bounds on the generalisation of such predictors, yielding the following main findings, for any PAC-learnable class and any given approximation operator: (1) We show that under mild conditions, approximable target concepts are learnable from a smaller labelled sample, provided sufficient unlabelled data; (2) We give algorithms that guarantee a good predictor whose approximation also enjoys the same generalisation guarantees; (3) We highlight natural examples of structure in the class of sensitivities, which reduce, and possibly even eliminate the otherwise abundant requirement of additional unlabelled data, and henceforth shed new light onto what makes one problem instance easier to learn than another. These results embed the scope of modern model-compression approaches into the general goal of statistical learning theory, which in return suggests appropriate algorithms through minimising uniform bounds.

Cognitive model of the ESG transformation of the organization

A universal model of ESG (Environmental, Social, Governance) transformation is proposed as a basis for developing an organization’s ESG strategy. Fuzzy cognitive logic technologies were used as the instrumental base of the study. A fuzzy cognitive map (FCM) of the organization’s ESG transformation has been developed with a substantiation of a set of parameters (concepts) in the environmental, social and managerial spheres. Based on the static analysis of the fuzzy cognitive model (FCM) and the calculation of its system indicators, it was determined that the factors of the level of ESG-corporate culture, ESG-motivation and integration into the practice of corporate management methodology of strategic management have the greatest positive impact on the target concepts and on the process of ESG transformation as a system. The system experiences a significant negative impact from the factor of resistance to changes in the organization. Collectively, these factors are identified as the main control actions for the organization’s ESG transformation.

Discussions on liquid bismuth target use as an alternative for astatine-211 production

Astatine-211 is an alpha emitter that has been identified as a good candidate for targeted alpha therapy. There is an increasing demand on this radionuclide. Very intense beam from linac being put in operation nowadays could be used to meet this demand. This document presents the design exploration of concepts of liquid bismuth targets dedicated to astatine-211 production. Three concepts are presented and analyzed: a capsule, a fluid loop and a windowless fluid loop. Structural and thermal sizing were performed using mechanical Finite Element models (ANSYS Workbench) and Computational Fluid Dynamic models (FLUENT). Production rates were assessed accordingly. Feasibility and expected performances are discussed in conclusion.

INHIBITORS OF BROMODOMAIN-4 AND CYCLOOXYGENASE-2: A REVIEW ON THE ADVANTAGEOUS EFFECT OF DUAL-TARGET APPROACH IN CANCER TREATMENT

The main objective of this review article is to establish a correlation between the roles of BRD-4 and COX-2 inhibitors in anticancer treatment. This article aims to project the synergistic benefits of a dual-target approach. A Literature review was conducted using the keywords such as BRD-4, cyclooxygenase-2, COX-2, Anticancer, anti-proliferative BRD-4 inhibitors, COX-2 inhibitors and dual-target therapy. Searches were made using the mentioned keywords individually as well as in combinations in PubMed, Science Direct and Google Scholar for the past ten years. The correlation between inflammatory mediators, particularly COX-2 and bromodomain in particular BRD-4 in cancers has been studied in a few research articles. These targets have been used for the development of anti-proliferative drugs individually as well as in combination. Combination therapy has been proposed to be better than mono-drug therapy. The need for a dual target concept has arisen to improve the efficacy of chemotherapy. The cancers where BRD-4 is over-expressed and inflammation is observed, it may be very much advantageous to give a combination therapy of BRD-4 and COX-2 inhibitors. Moreover, if the COX-2 inhibitors show anti-proliferative action, then the combination therapy is expected to work better than mono chemotherapy.

The Kazakh Concept of Soul in Abai Kunanbaev’s <i>Book of Words</i>


 
 
 This study explores conceptualisations of ??? ([jan] soul) in the Kazakh language from the perspective of cultural linguistics and its literary representation in the English translation of Book of Words by Abai Kunanbaev, a prominent Kazakh philosopher and writer. The concept of ??? (jan) was analysed from the viewpoint of philosophical and image features and their roles in the formation of the national worldview. A comparative study showed discrepancies in its realisation by Abai Kunanbaev and the English translation even though some variations in the translation cannot be complete equivalents. There is a lack of semantic and cultural identity, and the results indicate that the literal English translation of ??? (jan) does not transmit its whole cultural implications. The article also focuses on determining how different methods of translation reproduce the semantics of the analysed concept. The analysis concludes with the necessity of using structural and semantic shifts to better represent the target concept and culture.
 
 

Practical Applications of Target Costing in a Multidisciplinary R&D Project

R&D requires expertise in the basic sciences, technical and technological knowledge, legal regulations and business, it seems necessary to enhance collaboration between researchers and businesses, especially small and medium-sized enterprises. In this paper, we present a case study of a collaboration between a university and a company in the implementation of R&D projects. The primary research methods used in this study comprised literature analysis, case study analysis, participant observation, direct observation, deductive reasoning, and the authors’ experience with prototype interview design, including telephone interviews (quantitative survey) and interviews with market experts and/or individuals responsible for specific processes in diagnostic and testing laboratories. The calculations presented for studied projects showed a large disproportion between the costs incurred for the production of prototypes and the selling price accepted by the market. However, this does not preclude profitability. Further analysis of the technological processes, materials, components, etc. should be carried out in order to point out the optimization measures and consequently to achieve the target profitability of the product. Conducting R&D works should take into account the task of commercialization. The use of the concept of target costing facilitates the initial assessment of project profitability and should be recommended when conducting R&D, especially at higher stages of technological readiness of the product. Projects involving a higher level of technological readiness should be carried out not only by people representing life sciences, technology, medicine, etc., but also by specialists in social sciences (e.g., accountants and marketing specialists).

The obligation to succeed when it matters the most–The influence of skill and pressure on the success in football penalty kicks

In order to gain a more comprehensive understanding of the influence of skill and pressure on the success in football penalty kicks, we analyzed 1711 penalties taken over a 15-year period in major international tournaments. We conducted a multiple correspondence analysis in order to reduce six variables that are associated with skill and pressure to two dimensions that reflect our target concepts. Then, we used these two factors as independent variables in a logistic regression and fit different models using three binary dependent variables. The results show that high situational pressure significantly increases the probability of missing the goal entirely by about 6%, independent of the player’s skill level. The probability that the goalkeeper saves a penalty significantly decreases by roughly 4% when a highly skilled player takes the shot. In general, high situational pressure decreases the probability of scoring a penalty kick. Furthermore, the probability to score a penalty increases if a highly skilled player takes the kick which indicates that a high skill level can act as a kind of buffer against debilitating effects caused by performance pressure.

Reference the untouchable. On the limits of revising concepts using the method of cases

The paper investigates to what extent the method of cases can be interpreted as either a descriptive or a normative enterprise. I demonstrate that although most instances of the method of cases in most philosophical theories could be interpreted as being intended to either discover or revise the meaning of their target concepts, within a theory of reference this method cannot be used to shift the meaning of the concept of reference. The reason for this is that intuitions of extension in a theory of reference constitute a set of data that needs to be explained, while in most other philosophical theories they could either be abandoned in favor of intuitions of intension or serve as a criterion for the adequacy of the proposed definition of the target concept. This feature of a theory of reference is caused by the fact that an implicit understanding of what reference is in a theory of reference is usually assumed and is out of discussion. In effect, the claim in paradigmatic instances of the method of cases within a theory of reference does not concern whether an expression does or does not refer in particular cases, but rather what the reference of a certain expression is, and therefore it cannot be justified by intuitions of intension.

Cognitive Meaning of Inclusive Education of Students with Disability in Regular Education Teachers

Background: Successful inclusive education strongly represents the development of society, promoting better living conditions for students with disabilities.
 Objective: This study explored the mental representation of knowledge of inclusive education and disability held by regular education teachers with experience in this field.
 Methods: First, participants performed a conceptual definition task through the Natural Semantic Networks technique. Teachers defined ten target concepts related to the cognitive schema of inclusive education. They had 60 seconds to define each target, using verbs, adjectives, nouns, and pronouns, after rating the definers’ quality to conceptualize the target. Subsequently, the authors implemented a constraint satisfaction neural network to simulate the school inclusion schema's behavior and carried out a chronometric cognitive analysis using data from the first study.
 Results: Participants organized the educative inclusion meaning on four dimensions (definition, actors' qualities, stakeholders, and inclusion program effects). However, some concepts about school integration and conventional education appeared in the educative inclusion schema. Further, computer simulations showed that participants seem to have an internal locus of control over inclusive actions. Generally, experience with students with disabilities promotes the formation of a favorable educational inclusion schema. However, even though participants in this study have experience in inclusion programs, they are still constructing the inclusive education schema.
 Conclusion: The cognitive evaluation provides useful information to empower teachers to be aware of their knowledge and biases on inclusive education and the importance of their work in the success of school inclusion programs.

Beyond the classical amyloid hypothesis in Alzheimer's disease: Molecular insights into current concepts of pathogenesis, therapeutic targets, and study models.

Alzheimer's disease (AD) is one of the progressive neurodegenerative disorders and the most common cause of dementia in the elderly worldwide causing difficulties in the daily life of the patient. AD is characterized by the aberrant accumulation of β-amyloid plaques and tau protein-containing neurofibrillary tangles (NFTs) in the brain giving rise to neuroinflammation, oxidative stress, synaptic failure, and eventual neuronal cell death. The total cost of care in AD treatment and related health care activities is enormous and pharmaceutical drugs approved by Food and Drug Administration have not manifested sufficient efficacy in protection and therapy. In recent years, there are growing studies that contribute a fundamental understanding to AD pathogenesis, AD-associated risk factors, and pharmacological intervention. However, greater molecular process-oriented research in company with suitable experimental models is still of the essence to enhance the prospects for AD therapy and cell lines as a disease model are still the major part of this milestone. In this review, we provide an insight into molecular mechanisms, particularly the recent concept in gut-brain axis, vascular dysfunction and autophagy, and current models used in the study of AD. Here, we emphasized the importance of therapeutic strategy targeting multiple mechanisms together with utilizing appropriate models for the discovery of novel effective AD therapy. This article is categorized under: Neurological Diseases > Molecular and Cellular Physiology.

Spontaneous, controlled acts of reference between friends and strangers.

The online version contains supplementary material available at 10.1007/s10579-022-09619-y.

Assessing the effects of data drift on the performance of machine learning models used in clinical sepsis prediction

BackgroundData drift can negatively impact the performance of machine learning algorithms (MLAs) that were trained on historical data. As such, MLAs should be continuously monitored and tuned to overcome the systematic changes that occur in the distribution of data. In this paper, we study the extent of data drift and provide insights about its characteristics for sepsis onset prediction. This study will help elucidate the nature of data drift for prediction of sepsis and similar diseases. This may aid with the development of more effective patient monitoring systems that can stratify risk for dynamic disease states in hospitals. MethodsWe devise a series of simulations that measure the effects of data drift in patients with sepsis, using electronic health records (EHR). We simulate multiple scenarios in which data drift may occur, namely the change in the distribution of the predictor variables (covariate shift), the change in the statistical relationship between the predictors and the target (concept shift), and the occurrence of a major healthcare event (major event) such as the COVID-19 pandemic. We measure the impact of data drift on model performances, identify the circumstances that necessitate model retraining, and compare the effects of different retraining methodologies and model architecture on the outcomes. We present the results for two different MLAs, eXtreme Gradient Boosting (XGB) and Recurrent Neural Network (RNN). ResultsOur results show that the properly retrained XGB models outperform the baseline models in all simulation scenarios, hence signifying the existence of data drift. In the major event scenario, the area under the receiver operating characteristic curve (AUROC) at the end of the simulation period is 0.811 for the baseline XGB model and 0.868 for the retrained XGB model. In the covariate shift scenario, the AUROC at the end of the simulation period for the baseline and retrained XGB models is 0.853 and 0.874 respectively. In the concept shift scenario and under the mixed labeling method, the retrained XGB models perform worse than the baseline model for most simulation steps. However, under the full relabeling method, the AUROC at the end of the simulation period for the baseline and retrained XGB models is 0.852 and 0.877 respectively. The results for the RNN models were mixed, suggesting that retraining based on a fixed network architecture may be inadequate for an RNN. We also present the results in the form of other performance metrics such as the ratio of observed to expected probabilities (calibration) and the normalized rate of positive predictive values (PPV) by prevalence, referred to as lift, at a sensitivity of 0.8. ConclusionOur simulations reveal that retraining periods of a couple of months or using several thousand patients are likely to be adequate to monitor machine learning models that predict sepsis. This indicates that a machine learning system for sepsis prediction will probably need less infrastructure for performance monitoring and retraining compared to other applications in which data drift is more frequent and continuous. Our results also show that in the event of a concept shift, a full overhaul of the sepsis prediction model may be necessary because it indicates a discrete change in the definition of sepsis labels, and mixing the labels for the sake of incremental training may not produce the desired results.

Current concepts of anti-EGFR targeting in metastatic colorectal cancer.

Anti-EGFR targeting is one of the key strategies in the treatment of metastatic colorectal cancer (mCRC). For almost two decades oncologists have struggled to implement EGFR antibodies in the mCRC continuum of care. Both sidedness and RAS mutational status rank high among the predictive factors for the clinical efficacy of EGFR inhibitors. A prospective phase III trial has recently confirmed that anti-EGFR targeting confers an overall survival benefit only in left sided RAS-wildtype tumors when given in first line. It is a matter of discussion if more clinical benefit can be reached by considering putative primary resistance mechanisms (e.g., HER2, BRAF, PIK3CA, etc.) at this early stage of treatment. The value of this procedure in daily routine clinical utility has not yet been clearly delineated. Re-exposure to EGFR antibodies becomes increasingly crucial in the disease journey of mCRC. Yet re- induction or re-challenge strategies have been problematic as they relied on mathematical models that described the timely decay of EGFR antibody resistant clones. The advent of liquid biopsy and the implementation of more accurate next-generation sequencing (NGS) based high throughput methods allows for tracing of EGFR resistant clones in real time. These displays the spatiotemporal heterogeneity of metastatic disease compared to the former standard radiographic assessment and re-biopsy. These techniques may move EGFR inhibition in mCRC into the area of precision medicine in order to apply EGFR antibodies with the increase or decrease of EGFR resistant clones. This review critically discusses established concepts of tackling the EGFR pathway in mCRC and provides insight into the growing field of liquid biopsy guided personalized approaches of EGFR inhibition in mCRC.

Gene targeting as a therapeutic avenue in diseases mediated by the complement alternative pathway.

The complement alternative pathway (AP) is implicated in numerous diseases affecting many organs, ranging from the rare hematological disease paroxysmal nocturnal hemoglobinuria (PNH), to the common blinding disease age-related macular degeneration (AMD). Critically, the AP amplifies any activating trigger driving a downstream inflammatory response; thus, components of the pathway have become targets for drugs of varying modality. Recent validation from clinical trials using drug modalities such as inhibitory antibodies has paved the path for gene targeting of the AP or downstream effectors. Gene targeting in the complement field currently focuses on supplementation or suppression of complement regulators in AMD and PNH, largely because the eye and liver are highly amenable to drug delivery through local (eye) or systemic (liver) routes. Targeting the liver could facilitate treatment of numerous diseases as this organ generates most of the systemic complement pool. This review explains key concepts of RNA and DNA targeting and discusses assets in clinical development for the treatment of diseases driven by the alternative pathway, including the RNA-targeting therapeutics ALN-CC5, ARO-C3, and IONIS-FB-LRX, and the gene therapies GT005 and HMR59. These therapies are but the spearhead of potential drug candidates that might revolutionize the field in coming years.

Death, enemies, and illness: How English and Russian metaphorically conceptualise boredom

AbstractThis study seeks to develop quantified methods for the description of conceptual metaphors. The study examines the target concept ofboredomin contemporary English and Russian. It aims to not only identify which metaphors are used in the two languages, but also how they are used. Using the qualitative-quantitative approach of ‘behavioural profiles’, the study examines comparable informal and personal written language in both cultures, revealing that the most frequent metaphoric conceptualisations ofboredomare asdeath, as anenemyor as anillness. Moreover, the study also shows quantitatively that, despite shared metaphor structures across the languages, there is some difference in how they are used. Through these results, the study highlights that the description of conceptual metaphors needs to pay more attention to their use but also demonstrates the importance of quantitative tools for those usage descriptions.

Mapping musical dynamics in space. A qualitative analysis of conductors' movements in orchestra rehearsals

In this contribution, we examine the way in which orchestra conductors use the space around them to convey aspects of musical dynamics. In music,dynamicsrefers to the intensity of volume of notes and sounds and its interpretation is highly context-bound. We approach dynamics as a phenomenon of emergent and construed meaning in interaction, induced by the music score and the interpretationin situby musicians and the conductor. Conductors' movement-based instructions on dynamics result in highly complex usage events. This study aims at disentangling these instances by asking how conductors move and use the space around them to instruct on (un)desired aspects of musical dynamics, zooming in on movement direction as a central formal feature. We find ourselves at the crossroads of cognitive and interactional linguistics, aligning with existing studies on the interactional and contextually embedded nature of music interaction. From a cognitive linguistic perspective, this endeavor translates as the identification of the construal mechanisms (metaphor, specificity and viewpoint) that underlie and therefore motivate movement directions in the specific instances under examination. The analysis is based on 10h of video data from a corpus recorded during rehearsals of five conductors instructing their respective orchestras in Dutch. Our data reveal that conductors use different movement patterns, some of which appear to involve opposite movement directions for expressing a similar music dynamical aspect, e.g., depending on the usage event, a vertical upward movement can mean both a request for playing louder and softer. By taking into account different construal mechanisms, we are able to provide an encompassing multimodal analysis, in which these allegedly deviating oppositional movements appear as consistently motivated (metaphorical) expressions, which profile a similar target concept involving different viewpoints.

Granularity Selection for Hierarchical Classification Based on Uncertainty Measure

Feature selection is an important preprocessing step for high-dimensional data mining and machine learning; it is viewed as the selection of the optimal granularity to describe the target concept in rough set theory. Currently, research on rough sets mainly focuses on granularity selection in flat classification scenarios, while organizing hundreds of labels for hierarchical classification (HC) can provide additional external information and achieve better performance in terms of both accuracy and efficiency. However, HC also faces the following problems: 1) the current measures’ failure to characterize the uncertainty in HC; 2) the inability to select the optimal granularity of the target concept in HC; and 3) no valid approach to select features in a decision system with hierarchical classification (HieDS). To address these problems, this article introduces HC into rough set theory and proposes an approach to granularity selection for HC. First, we introduce the knowledge distance to reflect the uncertainty of HC and define related important characteristic functions to describe a HieDS. Then, from the perspective of uncertainty, granularity selection for the target concept and feature selection are presented based on these characteristic functions. Finally, we experimentally realize granularity selection and demonstrate excellent performance of feature selection in a HieDS in terms of both feature selection and classification accuracy.

The SuperFGD prototype PID beam tests results

The near detector ND280 of the T2K experiment will be upgraded in 2022 with the aim of measuring precisely CP violation in neutrinos. The ND280 upgrade consists of the installation of 3 new sub-detector types including SuperFGD, a novel neutrino active target concept. SuperFGD (Super-Fine-Grained-Detector) will have 2 million 1 × 1 × 1cm3 plastic scintillator cubes forming a cube array of 184 × 56 × 192 cm3. Each of the cubes will be intersected by 3 orthogonal WLS fibers with an MPPC on one end. Thanks to its super-fine segmentation, high light yield, and excellent time resolution, great particle identification (PID) capabilities are expected. Since 2018, a set of prototypes have been exposed to particle beams (charged tracks and neutrons) to test this concept. Here the results concerning the particle identification (PID) capabilities using the last prototype are presented.

Influence of the magnetic field on properties of hot electron emission from ablative plasma produced at laser irradiation of a disc-coil target

Optical generators of strong magnetic fields based on the laser-driven-coil target concept are considered to be useful tools for studies of magnetized plasmas in particular, for the study of implosion of magnetized fusion targets in inertial fusion research and astrophysical applications. This paper presents the results of the research directed at an investigation of the plasma properties in a laser-induced magnetic field. In the experiment carried out on the kilojoule PALS laser facility, a generator of the magnetic field was a disc-coil (DC) target composed of a Cu disk coupled to a single-turn coil irradiated by a 1ω laser beam with an energy of 500 J. The attention was focused on examining the influence of the magnetic field on properties of the hot electron (HE) flux emitted from the front surface of the irradiated target. The three-frame complex interferometry and four-frame x-ray camera combined with the measurements of the HE population and energy using a multi-channel magnetic electron spectrometer and 2D-resolved imaging of the induced Cu Kα line emission were applied to characterize the ablative plasma and the generated particles. Based on the measured angular distributions of the electron energy spectra, 3D simulations have been performed to visualize the effect of the magnetic field on the HE flux and to provide information on space-time distribution of the electron and current density both without and with the presence of an axial magnetic field. The obtained results confirmed the possibility of generating magnetic fields above 5 T using the proposed DC target design as well as the significant impact of these fields on properties of the ablative plasma and the HE emission.