Hasil untuk "Property"

Aileen Moreton-Robinson

Xiaoying Chen, J. Zaro, W. Shen

Yongqiang Cheng, E. Ma

Dmitrij Rappoport, F. Furche

Eduardo Sontag, Y. Wang

M. Vallet‐Regí, A. Rámila, A. D. Real et al.

E. Hoffman, K. McCabe, Keith Shachat et al.

J. Weiss, M. Tabor, G. Carnevale

A. Szczesniak

Sheng Wang, Wei Li, Shiwang Liu et al.

RaptorX Property (http://raptorx2.uchicago.edu/StructurePropertyPred/predict/) is a web server predicting structure property of a protein sequence without using any templates. It outperforms other servers, especially for proteins without close homologs in PDB or with very sparse sequence profile (i.e. carries little evolutionary information). This server employs a powerful in-house deep learning model DeepCNF (Deep Convolutional Neural Fields) to predict secondary structure (SS), solvent accessibility (ACC) and disorder regions (DISO). DeepCNF not only models complex sequence–structure relationship by a deep hierarchical architecture, but also interdependency between adjacent property labels. Our experimental results show that, tested on CASP10, CASP11 and the other benchmarks, this server can obtain ∼84% Q3 accuracy for 3-state SS, ∼72% Q8 accuracy for 8-state SS, ∼66% Q3 accuracy for 3-state solvent accessibility, and ∼0.89 area under the ROC curve (AUC) for disorder prediction.

L. Chou, Chung-Yuan Fu

This article using the database of Taiwanese land property lawsuits studies the economic effects of rainfalls on land property lawsuits during the period of Japanese colonial rule (1920–1941). The results obtained from basic ordinary least squares indicate that it shows no significant influences. However, an interesting result is that, when we adopt the approach of two stage least squares and use the variables of temperature and evaporation as the instrument variables of rainfalls, we find that there are highly significant influences on the lawsuits of land property. If 1 year comes with low average rainfalls, it means that the costs of productive inputs increase, because the available natural resource will decrease, and brings the distorted using of land property.

Brenna Bhandar

In Colonial Lives of Property Brenna Bhandar examines how modern property law contributes to the formation of racial subjects in settler colonies and to the development of racial capitalism. Examining both historical cases and ongoing processes of settler colonialism in Canada, Australia, and Israel and Palestine, Bhandar shows how the colonial appropriation of indigenous lands depends upon ideologies of European racial superiority as well as upon legal narratives that equate civilized life with English concepts of property. In this way, property law legitimates and rationalizes settler colonial practices while it racializes those deemed unfit to own property. The solution to these enduring racial and economic inequities, Bhandar demonstrates, requires developing a new political imaginary of property in which freedom is connected to shared practices of use and community rather than individual possession.

Oded Goldreich

Iyko Day

ABSTRACT This essay examines the power of private ownership as a material expression of “property as whiteness.” This reverses Cheryl Harris’s iconic conceptualization of “whiteness as property” in order to capture the racial and colonial dimensions of possessive individualism that anchors the concept of property.

Somporn Sahachaiseree, Takashi Oguchi

ABSTRACT Reinforcement learning (RL) is a promising machine‐learning solution to traffic signal control problems, which have been extensively studied. However, variants of non‐linear, deep artificial neural network (ANN) function approximators (FAs) have been predominantly employed in previous studies proposing RL‐based controllers, leaving a significant interpretability issue due to their black‐box nature. In this work, the use of the linear FA for a value‐based RL agent in traffic signal control problems is investigated along with the least‐squares Q‐learning method, abbreviated as LSTDQ. The interpretable linear FA was found to be adequate for the RL agent to learn an optimal policy. This leads to the proposal to replace a non‐linear ANN FA with the linear FA counterpart, resolving the interpretability issue. Moreover, the LSTDQ learning method shows superior behaviour convergence compared to a gradient descent method. In a low‐intensity arrival pattern scenario, the control by the RL agent cuts about half of the average delay resulting from the pretimed control. Owing to the conciseness of the linear FA, a direct interpretation analysis of the converged linear‐FA parameters is presented. Lastly, two online relearning tests of the agents under non‐stationary arrivals are conducted to demonstrate the online performance of LSTDQ. In conclusion, the linear‐FA specification and the LSTDQ method are together proposed to be used for its control algorithm interpretability property, superior convergence quality, and lack of hyperparameters.

E. J. Kuijer, L. H. Marinelli, S. J. Bailey et al.

ABSTRACT Nalfurafine is the only clinically approved kappa opioid receptor (KOPr) agonist that can cross the blood–brain barrier and exert CNS effects. Because its clinical use is not associated with dysphoria, it is widely believed to have an atypical pharmacological profile. Nalfurafine's atypical properties are proposed to result from its G‐protein‐biased KOPr agonist property, leading to the widespread use of nalfurafine as a nonaversive KOPr agonist in preclinical research. The validity of nonaversive claims for nalfurafine was investigated in mice by comparing its antinociceptive and aversive effects with those of the typical, nonbiased KOPr agonist U50,488 in tail withdrawal and conditioned place aversion (CPA) tests. Dose responses for tail withdrawal with nalfurafine and U50,488 were determined in warm (52°C) water in adult male and female C57BL/6J mice. Doses of U50,488 produced antinociception from 5 mg/kg, and doses of nalfurafine from 0.06 mg/kg. Four‐fold lower doses of either KOPr agonist (U50,488: 1.25 mg/kg; nalfurafine: 0.015 mg/kg) were subthreshold for antinociception. No sex differences were seen. Antinociceptive effects were fully blocked by the KOPr antagonist norBNI (10 mg/kg). Antinociceptive doses of nalfurafine (0.06 mg/kg) and U50,488 (5.0 mg/kg) both induced CPA. Subantinociceptive doses of nalfurafine (0.015 mg/kg) and U50,488 (1.25 mg/kg) were nonaversive in CPA. Thus, in mice, at doses that are antinociceptive, CPA was evident for both KOPr agonists. Neither nalfurafine nor U50,488 showed a separation between their antinociceptive and aversive effects, contradicting the hypothesis that nalfurafine is a nonaversive analgesic in mice. The findings caution against assuming nalfurafine is a nonaversive KOPr agonist for use in preclinical research.

Lingfang Hu, Ian A. Kash

People are commonly interested in predicting a statistical property of a random event such as mean and variance. Proper scoring rules assess the quality of predictions and require that the expected score gets uniquely maximized at the precise prediction, in which case we call the score directly elicits the property. Previous research work has widely studied the existence and the characterization of proper scoring rules for different properties, but little literature discusses the choice of proper scoring rules for applications at hand. In this paper, we explore a novel task, the indirect elicitation of properties with parametric assumptions, where the target property is a function of several directly-elicitable sub-properties and the total score is a weighted sum of proper scoring rules for each sub-property. Because of the restriction to a parametric model class, different settings for the weights lead to different constrained optimal solutions. Our goal is to figure out how the choice of weights affects the estimation of the target property and which choice is the best. We start it with simulation studies and observe an interesting pattern: in most cases, the optimal estimation of the target property changes monotonically with the increase of each weight, and the best configuration of weights is often to set some weights as zero. To understand how it happens, we first establish the elementary theoretical framework and then provide deeper sufficient conditions for the case of two sub-properties and of more sub-properties respectively. The theory on 2-D cases perfectly interprets the experimental results. In higher-dimensional situations, we especially study the linear cases and suggest that more complex settings can be understood with locally mapping into linear situations or using linear approximations when the true values of sub-properties are close enough to the parametric space.

Paul Jolissaint

The aim of the article is to provide characterizations of the Haage-rup property for locally compact, second countable groups in terms of approximations of some non-ergodic invariant states by mixing ones for actions on unital $C^*$-algebras one the one hand, and for pairs of tracial von Neumann algebras by mixing binormal states on the other hand.

Jiashen Meng, Haichang Guo, Chaojiang Niu et al.

Renzo Angles