300 research outputs found

    The Form of Practical Knowledge and Implicit Cognition: A Critique of Kantian Constitutivism

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    Moral realism faces two worries: How can we have knowledge of moral norms if they are independent of us, and why should we care about them if they are independent of rational activities they govern? Kantian constitutivism tackles both worries simultaneously by claiming that practical norms are constitutive principles of practical reason. In particular, on Stephen Engstrom’s account, willing involves making a practical judgment. To will well, and thus to have practical knowledge (i.e., knowledge of what is good), the content of one’s will needs to conform to the formal presuppositions of practical knowledge. Practical norms are thus constitutive of practical knowledge. However, I will argue that the universality principles from which Engstrom derives the formal presuppositions of practical knowledge are reflectively and psychologically unavailable. As a result, they cannot help Kantian constitutivism provide an answer to moral realism's worries

    Alachlor and Breast Cancer Risk Bibliography

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    Bibliography on the breast cancer risk of the herbicide alachlorBibliography on the breast cancer risk of the herbicide alachlor. Includes references on history of use and usage, chemical information and trade names, regulatory status, evidence of breast cancer risk in humans and animals, evidence of estrogenicity, effects on reproduction, evidence of mutagenicity and genotoxicity, effects on the immune system, environmental fate and food contamination, occupational exposure, and residues in human and cow's milk.New York State Department of Health, and the United States Department of Agriculture Regional W-45 project, No. NYC 17442

    Vanjski fokus pažnje poboljšava izvedbu bacanja diska

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    A performer’s focus of attention has been shown to influence motor performance and learning in a variety of motor skills. The purpose of the current study was to examine the effects of an external and internal focus of attention on discus throwing. Participants (N=20; mean age: 22 years, SD: 1.58) were recruited from an undergraduate male student population that had limited experience with the task. Using a within-participants design, all participants completed five maximum effort trials under each attentional focus condition (external and internal). The results of a repeated-measures ANCOVA revealed that participants had a significantly more effective performance in external focus of attention condition compared with the internal attentional focus. These findings are in line with the previous studies showing enhanced motor performance as a result of using external versus internal focus of attention. Therefore, it is suggested that coaches and practitioners give instructions that promote an external focus of attention.Dokazano je da usmjerenost pažnje izvođača motoričkog zadatka utječe na motoričku uspješnost i motoričko učenje velikog broja motoričkih vještina. Cilj je ovog istraživanja bio utvrditi učinke vanjskog i unutarnjeg usmjeravanja (fokusa) pažnje na izvedbu bacanja diska. Dvadeset ispitanika, u dobi od 22±1,58 godina, bilo je uzorkovano iz populacije dodiplomskih studenata koji nisu imali velikog iskustva u izvedbi motoričkog zadatka. Svi su ispitanici izveli zadatak po pet puta maksimalnim intenzitetom u svakoj od situacija usmjerenosti pažnje (vanjska i unutarnja usmjerenost pažnje). Rezultati analize ANCOVA pokazali su da je motorička izvedba bila značajno učinkovitija u uvjetima vanjske usmjerenosti pažnje u usporedbi s izvedbom u uvjetima s unutarnjim fokusom pažnje. Rezultati ovog istraživanja u skladu su s rezultatima ranije provedenih istraživanja koji pokazuju poboljšanu motoričku izvedbu u uvjetima vanjskog fokusa pažnje u odnosu na unutarnji fokus pažnje. Preporuča se, stoga, da treneri i stručnjaci daju instrukcije sportašu u vidu promoviranja vanjskog usmjeravanja pažnje

    The Story of the Torah from the Perspective of the Qur'an and History

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    The history of the Bible implies that the Torah has been formed and distorted over time. The Qur'an also confirms this issue. The Holy Qur'an, in addition to introducing the Jews as the People of the Book, uses the word "Torah" eighteen times, "which is a collection of divine teachings bestowed on Prophet Moses." On the one hand, the Holy Qur'an acknowledges and affirms it, and on the other hand, it attributes distortion to this book and introduces the Torah as one of the books that has been distorted throughout history, however, the holy Qur’an considers the part of the Torah that has been preserved to contain the teachings of God and can be acknowledged in general, and considers it a means of guiding the Jewish people and advises them to refer to it. The collection of information in this writing is library-based and their processing is descriptive-analytical. This article seeks to prove the view that the current Torah, with its various versions, has been disappeared in the ups and downs of the times, and that what exists is a very blurred and inconsistent face of the original version, and the Holy Qur'an confirms this

    Feature Unlearning for Generative Models via Implicit Feedback

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    We tackle the problem of feature unlearning from a pretrained image generative model. Unlike a common unlearning task where an unlearning target is a subset of the training set, we aim to unlearn a specific feature, such as hairstyle from facial images, from the pretrained generative models. As the target feature is only presented in a local region of an image, unlearning the entire image from the pretrained model may result in losing other details in the remaining region of the image. To specify which features to unlearn, we develop an implicit feedback mechanism where a user can select images containing the target feature. From the implicit feedback, we identify a latent representation corresponding to the target feature and then use the representation to unlearn the generative model. Our framework is generalizable for the two well-known families of generative models: GANs and VAEs. Through experiments on MNIST and CelebA datasets, we show that target features are successfully removed while keeping the fidelity of the original models

    The Morally Difficult Notion of Heaven

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    Sizing and Modeling of Electric Powertrains for Small Unmanned Aerial Systems

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    The following describes development of performance models for the battery, motor controller (electronic speed controller, or ESC), and brushless DC (BLDC) motor of small unmanned aerial systems (UAS) with a gross takeoff weight less than 20 kg (55 lb). The thesis also develops a sizing algorithm for the brushless DC motor. The performance models for the motor, ESC, and battery use component specifications to enable pre-conceptual design space exploration and mission-based design optimization of small UAS powertrains without a library of test data. The models also enable tradeoffs analysis between existing and conceptual designs without a series of flight tests. To develop, tune, and validate the models, a custom dynamometer test setup was designed and built to measure torque, speed, and electrical power data of brushless DC motor drive systems. The validated models, which could predict the combined motor/ESC efficiency within 5\% points of experimental values, reveal that popular claims of "high efficiency" for electric powertrains are only valid in a narrow band of high speed/low torque operation. Conversely, the sizing algorithm can predict the mass, geometry, and figure of merit (k_m) of a motor rated for a given torque. The algorithm can then predict the optimal torque constant (k_t), speed constant (k_v), and winding resistance (R) given an operating voltage and shaft speed. To develop and validate the algorithm, complementary theoretical and experimental methods were used to overcome two key barriers: (1) motor performance theory was used to generate non-existent performance data, and (2) empirical trends in motor design were leveraged to connect independent theoretical torque, volume, and mass models. The resulting mass and figure of merit predictions are within \pm20\% of actual values for motors ranging in mass from 25--500 g (1--18 oz.) and varying geometries. The validated algorithm also revealed that motor size (and therefore mass) grows with torque, not power

    サンスウ ノ ガクシュウ シドウ ニ オケル ズ ノ ヤクワリ

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