The analysis of the impact of panel attrition on estimation of regular-irregular worker wage gap in the KLIPS

The aim of this paper is analyzing the effect of panel attrition on estimation of regular-irregular worker wage gap using KLIPS (Korean Labor and Income Panel Study). Using two wave sub-panels of KLIPS, we first analyze the characteristics of attritions. We find that the nonrandom attrition has occurred and it causes the underestimation of regularirregular worker wage gap. Second, we decompose the attrition bias into ‘ability bias’ and ‘distortion bias’. And third we develop the estimation strategies to reduce the bias. We have found that the bias is not negligible although it has been attenuated by change of job of workers.peer-reviewe

Spatial and Temporal Dynamics of Salt Marsh Vegetation across Scales

Biogeographic patterns across a landscape are developed by the interplay of environmental processes operating at different spatial and temporal scales. This research investigated dynamics of salt marsh vegetation on the Skallingen salt marsh in Denmark responding to environmental variations at large, medium, and fine scales along both spatial and temporal spectrums. At the broad scale, this research addressed the importance of wind-induced rise of the sea surface in such biogeographic changes. A new hypothetical chain was suggested: recent trends in the North Atlantic Oscillation index toward its positive phase have led to increased storminess and wind tides on the ocean surface, resulting in increased frequency, duration, and magnitude of submergence and, hence, waterlogging of marsh soils and plants, which has retarded ecological succession. At the mid-scale, spatial patterns of vegetation and environmental factors were examined across tidal creeks. Sites closer to tidal creeks, compared to marsh interiors, were characterized by the dominance of later-successional species, higher bulk density, and lower nutrient contents and electrical conductivity. This finding implies that locations near creeks have experienced a better drainage condition than the inner marshes, which eventually facilitated the establishment of later-successional plants that are intolerant to physical stress. At the micro-scale, this research examined how the extent and mode of facilitation and competition vary for different combinations of plant species along physical gradients. Both positive and negative relationships were spatially manifested to a greater degree on the low marsh than on the mid marsh. This insight extends our current knowledge of scale-dependent interactions beyond pioneer zones to higher zones. On the low marsh, different types of bivariate point pattern (i.e., clustered, random, and regular) were observed for different combinations of species even at similar spatial scales. This finding implies that it is difficult to generalize at which scales competition and facilitation occur. To conclude, this research stresses the need for a holistic approach in future investigations of salt marsh biogeography. For example, based on results of this current research, it would be meaningful to develop a comprehensive simulation model that incorporates salt marsh ecology, geomorphology, and hydrology observed across scales

Characterizing the Feasible Payoff Set of OLG Repeated Games

We study the set of feasible payoffs of OLG repeated games. We first provide a complete characterization of the feasible payoffs. Second, we provide a novel comparative statics of the feasible payoff set with respect to players' discount factor and the length of interaction. Perhaps surprisingly, the feasible payoff set becomes smaller as the players' discount factor approaches to one

On the Value of Information Structures in Stochastic Games

This paper studies how improved monitoring affects the limit equilibrium payoff set for stochastic games with imperfect public monitoring. We introduce a simple generalization of Blackwell garbling called weighted garbling in order to compare different information structures for this class of games. Our main result is the monotonicity of the limit perfect public equilibrium (PPE) payoff set with respect to this information order: we show that the limit PPE payoff sets with one information structure is larger than the limit PPE payoff sets with another information structure state by state if the latter information structure is a weighted garbling of the former. We show that this monotonicity result also holds for the class of strongly symmetric equilibrium. Finally, we introduce and discuss another weaker sufficient condition for the expansion of limit PPE payoff set. It is more complex and difficult to verify, but useful in some special cases

Tri-Variate Relationships Among Vegetation, Soil, and Topography Along Gradients of Fluvial Biogeomorphic Succession

This research investigated how the strength of vegetation–soil–topography couplings varied along a gradient of biogeomorphic succession in two distinct fluvial systems: a forested river floodplain and a coastal salt marsh creek. The strength of couplings was quantified as tri-variance, which was calculated by correlating three singular axes, one each extracted using three-block partial least squares from vegetation, soil, and topography data blocks. Within each system, tri-variance was examined at low-, mid-, and high-elevation sites, which represented early-, intermediate-, and late-successional phases, respectively, and corresponded to differences in ongoing disturbance frequency and intensity. Both systems exhibited clearly increasing tri-variance from the early- to late-successional stages. The lowest-lying sites underwent frequent and intense hydrogeomorphic forcings that dynamically reworked soil substrates, restructured surface landforms, and controlled the colonization of plant species. Such conditions led vegetation, soil, and topography to show discrete, stochastic, and individualistic behaviors over space and time, resulting in a loose coupling among the three ecosystem components. In the highest-elevation sites, in contrast, disturbances that might disrupt the existing biotic–abiotic relationships were less common. Hence, ecological succession, soil-forming processes, and landform evolution occurred in tight conjunction with one another over a prolonged period, thereby strengthening couplings among them; namely, the three behaved in unity over space and time. We propose that the recurrence interval of physical disturbance is important to—and potentially serves as an indicator of—the intensity and mechanisms of vegetation–soil–topography feedbacks in fluvial biogeomorphic systems

An SRAM Compiler for Monolithic 3D Integrated Circuit

This article presents monolithic-3-D (M3D) SRAM arrays using multiple tiers of carbon nanotube (CNT) transistors. The compiler automatically generates single-tier 2-D SRAM subarrays and multitier 3-D SRAM subarrays with different tiers for cells and peripheral logic. Moreover, the compiler can integrate multiple subarrays of different dimensions to generate larger capacity SRAM arrays. The compiler is demonstrated in a commercial-grade M3D process design kit (PDK) with two tiers of carbon nanotube transistors (CNFETs). Simulations show that the M3D CNT SRAM design can improve the properties of memory compared to the 2-D CNT SRAM design. In a 32-kB memory implementation, the M3D design can reduce footprint, latency, and energy by 33%, 10%, and 19%, respectively. The compiler is used to show the feasibility of fine-grain logic and SRAM stacking in M3D technology.M.S

Object-conditioned Bag of Instances for Few-Shot Personalized Instance Recognition

Nowadays, users demand for increased personalization of vision systems to localize and identify personal instances of objects (e.g., my dog rather than dog) from a few-shot dataset only. Despite outstanding results of deep networks on classical label-abundant benchmarks (e.g., those of the latest YOLOv8 model for standard object detection), they struggle to maintain within-class variability to represent different instances rather than object categories only. We construct an Object-conditioned Bag of Instances (OBoI) based on multi-order statistics of extracted features, where generic object detection models are extended to search and identify personal instances from the OBoI's metric space, without need for backpropagation. By relying on multi-order statistics, OBoI achieves consistent superior accuracy in distinguishing different instances. In the results, we achieve 77.1% personal object recognition accuracy in case of 18 personal instances, showing about 12% relative gain over the state of the art.Comment: ICASSP 2024. Copyright 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in othe