WGCN: Graph Convolutional Networks with Weighted Structural Features

Graph structural information such as topologies or connectivities provides valuable guidance for graph convolutional networks (GCNs) to learn nodes' representations. Existing GCN models that capture nodes' structural information weight in- and out-neighbors equally or differentiate in- and out-neighbors globally without considering nodes' local topologies. We observe that in- and out-neighbors contribute differently for nodes with different local topologies. To explore the directional structural information for different nodes, we propose a GCN model with weighted structural features, named WGCN. WGCN first captures nodes' structural fingerprints via a direction and degree aware Random Walk with Restart algorithm, where the walk is guided by both edge direction and nodes' in- and out-degrees. Then, the interactions between nodes' structural fingerprints are used as the weighted node structural features. To further capture nodes' high-order dependencies and graph geometry, WGCN embeds graphs into a latent space to obtain nodes' latent neighbors and geometrical relationships. Based on nodes' geometrical relationships in the latent space, WGCN differentiates latent, in-, and out-neighbors with an attention-based geometrical aggregation. Experiments on transductive node classification tasks show that WGCN outperforms the baseline models consistently by up to 17.07% in terms of accuracy on five benchmark datasets

Bank funding constraints and stock liquidity

This paper examines the relationship between bank marginal funding constraints and stock liquidity. Using bank credit default swap (CDS) spreads we show that increased funding constraints weaken bank stock liquidity (as measured by liquidity tightness, depth, and resilience). This effect strengthens during crises periods. Deteriorating bank stock liquidity is in turn priced into excess stock returns. In addition, we find that during liquidity crises, monetary expansion can break the relationship between funding costs and stock liquidity. Heightened monetary policy uncertainty, however, strengthens this relation

Ask Question First for Enhancing Lifelong Language Learning

Lifelong language learning aims to stream learning NLP tasks while retaining knowledge of previous tasks. Previous works based on the language model and following data-free constraint approaches have explored formatting all data as "begin token (\textit{B}) + context (\textit{C}) + question (\textit{Q}) + answer (\textit{A})" for different tasks. However, they still suffer from catastrophic forgetting and are exacerbated when the previous task's pseudo data is insufficient for the following reasons: (1) The model has difficulty generating task-corresponding pseudo data, and (2) \textit{A} is prone to error when \textit{A} and \textit{C} are separated by \textit{Q} because the information of the \textit{C} is diminished before generating \textit{A}. Therefore, we propose the Ask Question First and Replay Question (AQF-RQ), including a novel data format "\textit{BQCA}" and a new training task to train pseudo questions of previous tasks. Experimental results demonstrate that AQF-RQ makes it easier for the model to generate more pseudo data that match corresponding tasks, and is more robust to both sufficient and insufficient pseudo-data when the task boundary is both clear and unclear. AQF-RQ can achieve only 0.36\% lower performance than multi-task learning.Comment: This paper has been accepted for publication at COLING 202

2-(Methoxy­meth­yl)adamantan-2-yl 2-methyl­acrylate

The title compound, C16H24O3, has a cage-type mol­ecular structure and is of inter­est with respect to its photochemical properties. The structure displays non-classical inter­molecular C—H⋯O hydrogen bonding, which links the mol­ecules into a three-dimensional network

Optical limiting using Laguerre-Gaussian beams

We demonstrate optical limiting using the self-lensing effect of a higher-order Laguerre-Gaussian beam in a thin dye-doped polymer sample, which we find is consistent with our model using Gaussian decomposition. The peak phase shift in the sample required for limiting is smaller than for a fundamental Gaussian beam with the added flexibility that the nonlinear medium can be placed either in front of or behind the beam focus.Comment: 3 pages, 4 figure

Comparison of progressive collapse resistance of frame with specially shaped columns and frame with rectangular columns

Konstrukcije okvira od armiranog betona (RC - reinforced concrete) s posebno oblikovanim stupovima i RC konstrukcije okvira s pravokutnim stupovima su različite vrste konstrukcija s različitim poprečnim presjecima stupova. Predlaže se model za analizu progresivnog kolapsa RC okvira primjenom elementa greda-stup i veznog elementa na temelju programa OpenSees. Simulirao se progresivni kolaps eksperimentalnog okvira i rezultati proračuna su se poklapali s rezultatima dobivenim eksperimentom. Karakteristike progresivnog kolapsa okvira s posebno oblikovanim stupovima analizirale su se usporedbom otpora progresivnom kolapsu jednog okvira s posebno oblikovanim stupovima i onog s tri okvira s pravokutnim stupovima koji su konstruirani u skladu s tri različita principa. Vidjelo se iz rezultata da su otpor progresivnom kolapsu okvira s posebno oblikovanim stupovima i okvira s pravokutnim stupovima s istom armaturom pod istim seizmičkim ojačanjem, konstrukcijom i uvjetima primjene bili jednaki. Okvir s posebno oblikovanim stupovima bolje je reagirao u otporu na progresivni kolaps.RC frame structures with specially shaped columns and RC frame structures with rectangular columns are different types of structures with different column sections. A progressive collapse analysis model of RC frames was proposed using the beam-column element and joint element based on the program OpenSees. Progressive collapse performance of the experimental frame was simulated and the calculation results were in good agreement with the experimental results. The characteristics of progressive collapse performance of frames with specially shaped columns were studied by comparing the progressive collapse resistance of one frame with specially shaped columns with that of three frames with rectangular columns which were designed in accordance with three different principles. It was observed from the results that the progressive collapse resistance of frame with specially shaped columns and frames with rectangular columns with the same reinforcement under the same seismic fortification, design and application conditions were equivalent. The frame with specially shaped columns had a superior performance to resist progressive collapse

Enhanced Fairness Testing via Generating Effective Initial Individual Discriminatory Instances

Fairness testing aims at mitigating unintended discrimination in the decision-making process of data-driven AI systems. Individual discrimination may occur when an AI model makes different decisions for two distinct individuals who are distinguishable solely according to protected attributes, such as age and race. Such instances reveal biased AI behaviour, and are called Individual Discriminatory Instances (IDIs). In this paper, we propose an approach for the selection of the initial seeds to generate IDIs for fairness testing. Previous studies mainly used random initial seeds to this end. However this phase is crucial, as these seeds are the basis of the follow-up IDIs generation. We dubbed our proposed seed selection approach I&D. It generates a large number of initial IDIs exhibiting a great diversity, aiming at improving the overall performance of fairness testing. Our empirical study reveal that I&D is able to produce a larger number of IDIs with respect to four state-of-the-art seed generation approaches, generating 1.68X more IDIs on average. Moreover, we compare the use of I&D to train machine learning models and find that using I&D reduces the number of remaining IDIs by 29% when compared to the state-of-the-art, thus indicating that I&D is effective for improving model fairnessComment: 19 pages, 7 figure

Penerapan Pendekatan Pengajaran Terbalik (Reciprocal Teaching) Untuk Meningkatkan Kemandirian Belajar Biologi Siswa Kelas Vii-g SMP N 5 Karanganyar Tahun Pelajaran 2010/ 2011

– The objective of this study is to improve student independence in learning biology by implementing Inverted Teaching Approach (Reciprocal Teaching) on Environmental Management material. This research is a classroom action research. This research was conducted in two cycles. Each cycle consisted of planning, implementation of the action,observation, and reflection. The subjects of the study were VII-G class students of SMP Negeri 5 Karanganyar in the academic year of 2010/2011. The number of the students was 32. The technique and instrumen of collectiing data were questionnaire, observation, and interviews. The technique of analyzing data was descriptive analysis techniques. Triangulation technique was used in data validation. The results proved that by implementing Inverted Teaching Approach (Reciprocal Teaching) students\u27 independence in learning biology enhanced. It is based on the results of questionnaires, observations and interviews. The questionnaire of students\u27 learning independence showed that the mean percentage of students\u27 achievement in each indicator in pre-cycle, cycle I, and cycle II was 67.97%, 72.55%, and 77.58% respectively. The observation of students\u27 learning independence showed that the mean percentage of students\u27 achievement in each indicator in pre-cycle, cycle I, and cycle II was 39.68%, 67.5%, and 80.62% respectively. It can be concluded that the implementation of Inverted Teaching Approach (Reciprocal Teaching) can enhance students learning independence

Dynamic increase factor for RC frame with specially shaped columns against progressive collapse

To investigate the dynamic increase factor (DIF) for nonlinear static (NS) alternate path analysis, the nonlinear dynamic (ND) and static analysis of a 6-storey reinforced concrete (RC) frame with specially shaped columns are carried out by utilizing OpenSees after the corner, side or inner column is removed respectively. Using the vertical displacement of removal column top node and axial force of adjacent column as control, reasonable value of DIF in the NS analysis are estimated according to the analysis results. A DIF about 1.8, 1.2 and 1.4 could capture the dynamic responses in corner, side or inner column removal scenario respectively when a static analysis is performed. The DIF in corner column removal scenario increases with the increasing of the floor on which the failure column locates and reaches the peak value at the top floor, while the DIF in inner or side column removal scenario decrease slightly. The DIF of inner or side column removal scenario increases linearly with the elongation of the beam span. The reinforcement of frame with specially shaped columns has little effect on the DIF