358 research outputs found
Implementing Default and Autoepistemic Logics via the Logic of GK
The logic of knowledge and justified assumptions, also known as logic of
grounded knowledge (GK), was proposed by Lin and Shoham as a general logic for
nonmonotonic reasoning. To date, it has been used to embed in it default logic
(propositional case), autoepistemic logic, Turner's logic of universal
causation, and general logic programming under stable model semantics. Besides
showing the generality of GK as a logic for nonmonotonic reasoning, these
embeddings shed light on the relationships among these other logics. In this
paper, for the first time, we show how the logic of GK can be embedded into
disjunctive logic programming in a polynomial but non-modular translation with
new variables. The result can then be used to compute the extension/expansion
semantics of default logic, autoepistemic logic and Turner's logic of universal
causation by disjunctive ASP solvers such as claspD(-2), DLV, GNT and cmodels.Comment: Proceedings of the 15th International Workshop on Non-Monotonic
Reasoning (NMR 2014
Differential metabolic responses of clam Ruditapes philippinarum to Vibrio anguillarum and Vibrio splendidus challenges
Clam Ruditapes philippinarum is one of the important marine aquaculture species in North China. However, pathogens can often cause diseases and lead to massive mortalities and economic losses of clam. In this work, we compared the metabolic responses induced by Vibrio anguillarum and Vibrio splendidus challenges towards hepatopancreas of clam using NMR-based metabolomics. Metabolic responses suggested that both V anguillarum and V splendidus induced disturbances in energy metabolism and osmotic regulation, oxidative and immune stresses with different mechanisms, as indicated by correspondingly differential metabolic biomarkers (e.g., amino acids, ATP, glucose, glycogen, taurine, betaine, choline and hypotaurine) and altered mRNA expression levels of related genes including ATP synthase, ATPase, glutathione peroxidase, heat shock protein 90, defensin and lysozyme. However, V. anguillarum caused more severe oxidative and immune stresses in clam hepatopancreas than V splendidus. Our results indicated that metabolomics could be used to elucidate the biological effects of pathogens to the marine clam R. philippinarum. (C) 2013 Elsevier Ltd. All rights reserved.Clam Ruditapes philippinarum is one of the important marine aquaculture species in North China. However, pathogens can often cause diseases and lead to massive mortalities and economic losses of clam. In this work, we compared the metabolic responses induced by Vibrio anguillarum and Vibrio splendidus challenges towards hepatopancreas of clam using NMR-based metabolomics. Metabolic responses suggested that both V anguillarum and V splendidus induced disturbances in energy metabolism and osmotic regulation, oxidative and immune stresses with different mechanisms, as indicated by correspondingly differential metabolic biomarkers (e.g., amino acids, ATP, glucose, glycogen, taurine, betaine, choline and hypotaurine) and altered mRNA expression levels of related genes including ATP synthase, ATPase, glutathione peroxidase, heat shock protein 90, defensin and lysozyme. However, V. anguillarum caused more severe oxidative and immune stresses in clam hepatopancreas than V splendidus. Our results indicated that metabolomics could be used to elucidate the biological effects of pathogens to the marine clam R. philippinarum. (C) 2013 Elsevier Ltd. All rights reserved
Computing Loops With at Most One External Support Rule
If a loop has no external support rules, then its loop formula is equivalent to a set of unit clauses; and if it has exactly one external support rule, then its loop formula is equivalent to a set of binary clauses. In this paper, we consider how to compute these loops and their loop formulas in a normal logic program, and use them to derive consequences of a logic program. We show that an iterative procedure based on unit propagation, the program completion and the loop formulas of loops with no external support rules can compute the same consequences as the “Expand ” operator in smodels, which is known to compute the well-founded model when the given normal logic program has no constraints. We also show that using the loop formulas of loops with at most one external support rule, the same procedure can compute more consequences, and these extra consequences can help ASP solvers such as cmodels to find answer sets of certain logic programs
PSAT1 prompted cell proliferation and inhibited cell apoptosis in multiple myeloma through regulating PI3K/AKT pathway
Purpose: To identify the biological function of phosphoserine aminotransferase 1 (PSAT1) in regulating cell proliferation and apoptosis in multiple myeloma (MM).Methods: The mRNA and protein levels of PSAT1 were determined using quantitative real-time polymerase chain reaction (PCR) and western blotting, respectively. Cell proliferation was measured using CCK-8 assay.Results: PSAT1 mRNA and protein expression levels were significantly increased in MM cell lines when compared to control cells. Moreover, downregulation of PSAT1 inhibited MM cell proliferation and induced cell apoptosis, whereas overexpression of PSAT1 promoted MM cell proliferation and suppressed cell apoptosis. Further analysis demonstrated that the underlying mechanism was via regulation of PI3K/AKT pathway.Conclusion: The results identified a novel role for PSAT1 in the progression of MM, which may provide a therapeutic and a new anticancer target for the therapy of MM.
Keywords: Multiple myeloma, PSAT1, Cell proliferation, PI3K/AKT pathwa
OCC-VO: Dense Mapping via 3D Occupancy-Based Visual Odometry for Autonomous Driving
Visual Odometry (VO) plays a pivotal role in autonomous systems, with a
principal challenge being the lack of depth information in camera images. This
paper introduces OCC-VO, a novel framework that capitalizes on recent advances
in deep learning to transform 2D camera images into 3D semantic occupancy,
thereby circumventing the traditional need for concurrent estimation of ego
poses and landmark locations. Within this framework, we utilize the TPV-Former
to convert surround view cameras' images into 3D semantic occupancy. Addressing
the challenges presented by this transformation, we have specifically tailored
a pose estimation and mapping algorithm that incorporates Semantic Label
Filter, Dynamic Object Filter, and finally, utilizes Voxel PFilter for
maintaining a consistent global semantic map. Evaluations on the Occ3D-nuScenes
not only showcase a 20.6% improvement in Success Ratio and a 29.6% enhancement
in trajectory accuracy against ORB-SLAM3, but also emphasize our ability to
construct a comprehensive map. Our implementation is open-sourced and available
at: https://github.com/USTCLH/OCC-VO.Comment: 7pages, 3 figure
Multi-Modal 3D Object Detection in Autonomous Driving: a Survey
In the past few years, we have witnessed rapid development of autonomous
driving. However, achieving full autonomy remains a daunting task due to the
complex and dynamic driving environment. As a result, self-driving cars are
equipped with a suite of sensors to conduct robust and accurate environment
perception. As the number and type of sensors keep increasing, combining them
for better perception is becoming a natural trend. So far, there has been no
indepth review that focuses on multi-sensor fusion based perception. To bridge
this gap and motivate future research, this survey devotes to review recent
fusion-based 3D detection deep learning models that leverage multiple sensor
data sources, especially cameras and LiDARs. In this survey, we first introduce
the background of popular sensors for autonomous cars, including their common
data representations as well as object detection networks developed for each
type of sensor data. Next, we discuss some popular datasets for multi-modal 3D
object detection, with a special focus on the sensor data included in each
dataset. Then we present in-depth reviews of recent multi-modal 3D detection
networks by considering the following three aspects of the fusion: fusion
location, fusion data representation, and fusion granularity. After a detailed
review, we discuss open challenges and point out possible solutions. We hope
that our detailed review can help researchers to embark investigations in the
area of multi-modal 3D object detection
Radiative absorption enhancement of dust mixed with anthropogenic pollution over East Asia
The particle mixing state plays a significant yet poorly quantified role in aerosol radiative forcing, especially for the mixing of dust (mineral absorbing) and anthropogenic pollution (black carbon absorbing) over East Asia. We have investigated the absorption enhancement of mixed-type aerosols over East Asia by using the Aerosol Robotic Network observations and radiative transfer model calculations. The mixed-type aerosols exhibit significantly enhanced absorbing ability than the corresponding unmixed dust and anthropogenic aerosols, as revealed in the spectral behavior of absorbing aerosol optical depth, single scattering albedo, and imaginary refractive index. The aerosol radiative efficiencies for the dust, mixed-type, and anthropogenic aerosols are −101.0, −112.9, and −98.3 Wm⁻²τ⁻¹ at the bottom of the atmosphere (BOA); −42.3, −22.5, and −39.8 Wm⁻²τ⁻¹ at the top of the atmosphere (TOA); and 58.7, 90.3, and 58.5 Wm⁻²τ⁻¹ in the atmosphere (ATM), respectively. The BOA cooling and ATM heating efficiencies of the mixed-type aerosols are significantly higher than those of the unmixed aerosol types over the East Asia region, resulting in atmospheric stabilization. In addition, the mixed-type aerosols correspond to a lower TOA cooling efficiency, indicating that the cooling effect by the corresponding individual aerosol components is partially counteracted. We conclude that the interaction between dust and anthropogenic pollution not only represents a viable aerosol formation pathway but also results in unfavorable dispersion conditions, both exacerbating the regional air pollution in East Asia. Our results highlight the necessity to accurately account for the mixing state of aerosols in atmospheric models over East Asia in order to better understand the formation mechanism for regional air pollution and to assess its impacts on human health, weather, and climate
- …